Driver Issues: 

Commercial Motor Vehicle Safety 

Literature Review 

June 2007

PREFACE 

The objective of this project was to provide the Federal Motor Carrier Safety Administration 

(FMCSA) with a more complete understanding of the non-regulatory factors which make for 

safer commercial motor vehicle (CMV) drivers. Through the review of available literature, the 

relationship between the CMV driver and the motor carrier was explored with respect to safety 

outcomes. A tailored Haddon Matrix was used as a means to structure the literature and provide 

clear direction for the development of future intervention strategies. Haddon’s Matrix provides a 

framework for identifying factors that influence an event by dividing the event in terms of 

timeframe (i.e., pre-event, event, and post-event) and the actors and/or environments involved in 

the event. The Haddon Matrix was adapted for the current project by considering the driver and 

the motor carrier as the major actors/environments, and identifying events in the driver-motor 

carrier relationship that are important for improving driver safety. Two separate reviews were 

conducted. Review #1 examined literature relating to the selection of safe drivers; its outcomes 

pointed to employee turnover as a primary focus of the data-driven research conducted over the 

past decade, as well as a primary concern highlighted in trade and industry sources. Review #2 

investigated research and trade publications as related to improving driver safety; its outcomes 

demonstrated that recent literature has largely concentrated on the identification and 

comprehension of driver characteristics and motor carrier practices as they relate to safety 

outcomes (e.g., age and CMV driving history). General conclusions derived from the literature 

and future research needs are also discussed.

NOTICE 

This document is disseminated under the sponsorship of the U.S. Department of Transportation 

in the interest of information exchange. The U.S. Government assumes no liability for its 

contents or use thereof. 

The contents of this report reflect the views of the contractor who is responsible for the accuracy 

of the data presented herein. The contents do not necessarily reflect the official policy of the U.S. 

Department of Transportation. 

This report does not constitute a standard, specification, or regulation. 

The U.S. Government does not endorse products or manufacturers named herein. Trade or 

manufacturers’ names appear herein only because they are considered essential to the objective 

of this document. 

Technical Report Documentation Page (Form 1700.7) 

1. Report No. 

FMCSA-PSV-07-006 

2. Government Accession No. 3. Recipient’s Catalog No. 

4. Title and Subtitle: 5. Report Date: 

June 2007 

Driver Issues: Commercial Motor Vehicle Safety Literature Review 6. Performing Organization Code 

7. Author(s): 

Heidi Howarth, Stephanie Alton, Natasha Arnopolskaya, Larry 

Barr, Tara Di Domenico 

8. Performing Organization Report No. 

DOT-VNTSC-FMCSA-0701 

9. Performing Organization Name and Address: 10. Work Unit No. (TRAIS) 

U.S. Department of Transportation 

Research and Innovative Technology Administration 

Volpe National Transportation Systems Center 

Human Factors Division, RTV-4G 

55 Broadway, Kendall Square 

Cambridge, MA 02142 

11. Contract or Grant No. 

13. Type of Report and Period Covered 

Final Project Report 

12. Sponsoring Agency Name and Address: 

U.S. Department of Transportation 

Federal Motor Carrier Safety Administration 

Bus & Truck Standards and Operations 

1200 Seventh St., S.W. 

Washington, D.C. 20590 

14. Sponsoring Agency Code 

FMCSA 

15. Supplementary Notes: 

Contracting Officer’s Technical Representative: Deborah M. Freund 

16. Abstract: 

The objective of this project was to provide the Federal Motor Carrier Safety Administration (FMCSA) with 

a more complete understanding of the non-regulatory factors which make for safer commercial motor 

vehicle (CMV) drivers. Through the review of available literature, the relationship between the CMV driver 

and the motor carrier was explored with respect to safety outcomes. A tailored Haddon Matrix was used as a 

means to structure the literature and provide clear direction for the development of future intervention 

strategies. Haddon’s Matrix provides a framework for identifying factors that influence an event by dividing 

the event in terms of timeframe (i.e., pre-event, event, and post-event) and the actors and/or environments 

involved in the event. The Haddon Matrix was adapted for the current project by considering the driver and 

the motor carrier as the major actors/environments, and identifying events in the driver-motor carrier 

relationship that are important for improving driver safety. Two separate reviews were conducted. Review 

#1 examined literature relating to the selection of safe drivers; its outcomes pointed to employee turnover as 

a primary focus of the data-driven research conducted over the past decade, as well as a primary concern 

highlighted in trade and industry sources. Review #2 investigated research and trade publications as related 

to improving driver safety; its outcomes demonstrated that recent literature has largely concentrated on the 

identification and comprehension of driver characteristics and motor carrier practices as they relate to 

safety outcomes (e.g., age and CMV driving history). General conclusions derived from the literature and 

future research needs are also discussed. 

17. Key Words: 

Commercial Motor Vehicle, Safety, Driver Characteristics, 

Selection, Retention, Turnover, Motor Carrier, Trucking, Haddon 

Matrix 

18. Distribution Statement 

No restrictions 

19. Security Classif. (of this report) 

Unclassified 

20. Security Classif. (of this page) 

Unclassified 

21. No. of Pages 

219 

22. Price 

N/A 
SI* (MODERN METRIC) CONVERSION FACTORS 

APPROXIMATE CONVERSIONS TO SI UNITS APPROXIMATE CONVERSIONS FRO

Symbol When You Know Multiply By To Find Symbol Symbol When You Know Multiply By 

LENGTH LENGTH 

in Inches 25.4 millimeters mm mm millimeters 0.039 inft Feet 0.305 meters m m meters 3.28 feyd Yards 0.914 meters m m meters 1.09 Yami Miles 1.61 kilometers km km kilometers 0.621 m

AREA AREA 

in2 square inches 645.2 square millimeters mm2 mm2 square millimeters 0.0016 sqft2 square feet 0.093 square meters m2 m2 square meters 10.764 sqyd2 square yards 0.836 square meters m2 m2 square meters 1.195 sqac Acres 0.405 hectares ha ha hectares 2.47 acmi2 square miles 2.59 square kilometers km2 km2 square kilometers 0.386 sq

VOLUME VOLUME 

fl oz fluid ounces 29.57 milliliters ml ml milliliters 0.034 flugal Gallons 3.785 liters l l liters 0.264 gaft3 cubic feet 0.028 cubic meters m3 m3 cubic meters 35.71 cuyd3 cubic yards 0.765 cubic meters m3 m3 cubic meters 1.307 cu

MASS MASS 

oz Ounces 28.35 grams g g grams 0.035 oulb Pounds 0.454 kilograms kg kg kilograms 2.202 poT short tons (2000 lbs) 0.907 megagrams Mg Mg megagrams 1.103 sh

TEMPERATURE (exact) TEMPERATURE (exac

°F Fahrenheit 5(F-32)/9 Celsius °C °C Celsius 1.8 C + 32 

Temperature or (F-32)/1.8 temperature temperature 

ILLUMINATION ILLUMINATION 

fc foot-candles 10.76 lux lx lx Lux 0.0929 fl foot-Lamberts 3.426 candela/m2 cd/m2 cd/m2 candela/m2 0.2919 

FORCE and PRESSURE or STRESS FORCE and PRESSURE or S

lbf pound-force 4.45 newtons N N newtons 0.225 psi pound-force per square inch 6.89 kilopascals kPa kPa kilopascals 0.145 

* SI is the symbol for the International System of Units. Appropriate rounding should be made to comply with Section 4 of ASTM E380.
TABLE OF CONTENTS 

LIST OF ABBREVIATIONS AND ACRONYMS ..................................................................III

EXECUTIVE SUMMARY ..........................................................................................................V

INTRODUCTION..........................................................................................................................1

PROJECT GOAL AND APPROACH ...................................................................................1 

PROCESS AND METHODOLOGY .....................................................................................2 

Search Strategy ............................................................................................................. 2 

Selection Criteria .......................................................................................................... 4 

Review Strategy............................................................................................................ 6 

Organization and Presentation of Results..................................................................... 7 

LITERATURE REVIEWS ...........................................................................................................8

REVIEW #1: SELECTING SAFE DRIVERS .......................................................................8 

Literature Search Results.............................................................................................. 8 

Selecting Safe Drivers Outcomes ................................................................................. 9 

Findings from Trade and Industry Sources................................................................. 12 

Review #1 Annotations............................................................................................... 16 

Pre-event................................................................................................................16

Event ......................................................................................................................23

Post-event...............................................................................................................26

Secondary Sources...................................................................................................... 62 

REVIEW #2: IMPROVING DRIVER SAFETY.................................................................66 

Literature Search Results............................................................................................ 66 

Improving Driver Safety Outcomes............................................................................ 67 

Findings from Trade and Industry Sources................................................................. 73 

Review #2 Annotations............................................................................................... 75 

Pre-event................................................................................................................75

Event ....................................................................................................................144

Post-event.............................................................................................................161

Secondary Sources.................................................................................................... 180 

CONCLUSIONS ........................................................................................................................192

REFERENCES...........................................................................................................................195

i 
LIST OF TABLES 

Table 1. Haddon Matrix for Review #1: Selecting Safe Drivers.................................................... 8 

Table 2. Haddon Matrix for Review #2: Improving Driver Safety. ............................................. 66 

LIST OF FIGURES 

Figure 1. A sample Haddon Matrix with Blank Cells .................................................................... 6 

ii 
LIST OF ABBREVIATIONS AND ACRONYMS 

AAMVA American Association of Motor Vehicle Administrators

ANOVA Analysis of Variance

ANPRM Advance notice of proposed rulemaking

ATA American Trucking Association

ATAF American Trucking Association Foundation

ATRI American Transportation Research Institute 

BBS Behavior-Based Safety

BLS Bureau of Labor Statistics

CDL Commercial Drivers License 

CDLIS Commercial Drivers License Information System 

CMV Commercial motor vehicle 

CPS Current Population Survey

CR Compliance review 

CTBSSP Commercial Truck and Bus Safety Synthesis Program

CVSA Commercial Vehicle Safety Alliance 

CWS Collision warning system 

DBQ Driver Behavior Questionnaire

DEA Data envelopment analysis 

DMV Department of Motor Vehicles 

DVI Driver-vehicle interface 

DVN Driver violation notification 

ECM Engine control module 

EPN Employee/Employer Pull Notice 

EU European Union 

FARS Fatality Analysis Reporting System 

FMCSA Federal Motor Carrier Safety Administration 

FMCSR Federal Motor Carrier Safety Regulations

FOT Field operational test

FTA Federal Transit Administration

GES General Estimates System 

HOS Hours of service

HR Human resources 

HRM Human resource management 

ICC Interstate Commerce Commission

ITS Interpersonal Trust Scale 

LMX Leader-member exchange

LTCCS Large Truck Crash Causation Study 

LTL Less-than-truckload 

LTSA Land Transport Safety Authority

MCMIS Motor Carrier Management Information System 

MCSOTS Motor Carrier Safety, Operations and Technology

MPS Motivating potential score

NDSU/UGPTI North Dakota State University Upper Great Plains Transportation Institute 

iii
NHTSA National Highway Traffic Safety Administration 

NPRM Notice of proposed rulemaking

NPTC National Private Truck Council 

NTIS National Technical Information Service

NYCT New York City Transit

OSH Occupational safety and health

OSHA Occupational Safety and Health Association

OOS Out-of-service 

P-J Person-job 

P-O Person-organization 

PUMS Public Use Microdata Sample 

RJP Realistic job preview

ROA Return on assets

ROI Return on investment

SafeStat Motor Carrier Safety Status Measurement System 

SEA Safety Evaluation Area 

SME Subject matter expert 

SMS Self-management for safety 

SVA Single vehicle accident 

TL Truckload 

TRIS Transportation Research Information Services 

UMTIP University of Michigan Trucking Industry Program 

iv
EXECUTIVE SUMMARY

The primary mission of the Federal Motor Carrier Safety Administration (FMCSA) is to improve 

safety by reducing crashes, injuries, and fatalities involving commercial motor vehicles (CMVs). 

The goal of the current project is to provide FMCSA with a more complete understanding of the 

non-regulatory factors which make for safer CMV drivers. Through the review of available 

literature, our primary focus is to explore the relationship between the CMV driver and the motor 

carrier with respect to safety outcomes. 

A tailored Haddon Matrix was used as a means to structure the literature and provide clear 

direction for the development of future intervention strategies. Haddon’s Matrix provides a 

structure for identifying factors that influence an event by dividing the event in terms of 

timeframe (i.e., pre-event, event, and post-event) and the actors and/or environments involved in 

the event. The Haddon Matrix was adapted for the current project by considering the driver and 

the motor carrier as the major actors/environments, and identifying events in the driver-motor 

carrier relationship that are important for improving driver safety. 

This project considers two non-regulatory approaches to support FMCSA’s mission of 

improving safety on the roadways. Review #1: Selecting Safe Drivers addresses the workforce 

“pipeline” issue—who is applying to and being recruited for CMV driver positions—extending 

to the hiring process, and further, considering retention and turnover. Review #2: Improving 

Driver Safety focuses on improving the safety of those drivers already “on the road” by 

considering the various driver and motor carrier practices that affect safety outcomes, prior to, 

during, and after safety incidents. 

In order to focus on only the most current findings concerning safety in the trucking industry, 

selection of literature was limited to references published in 1995 or later. Only works published 

in English and studies conducted in the US, Canada, Australia, or the European Union (EU) were 

considered. All sources address truck, bus, or van drivers who operate CMVs, or motor carriers 

that employ such drivers. Relevant reference works were divided into primary and secondary 

sources based on a review of abstract and/or executive summary information, where available, or 

the full text, if necessary. The primary sources consist mainly of peer-reviewed literature and 

conference proceedings that are based on first-hand empirical data, and were annotated by one or 

more reviewers. References identified as secondary sources consist largely of high-level reviews 

and synthesis reports that contain relevant information, but do not utilize first-hand data (e.g., 

meta-analyses). Applicable references from trade publications were also included to fill gaps in 

search results as necessary. The final database included 65 primary sources (20 annotated for 

Review #1 and 45 annotated for Review #2), 30 secondary sources, and 36 trade sources. 

The outcomes of Review #1 point to employee turnover as a primary focus of the data-driven 

research conducted over the past decade. Negative impacts associated with turnover and 

subsequent hiring needs include substantial organizational costs to hire a full complement of 

drivers each year, estimated as a $7,000 expense per lost employee (Griffin et al., 2000). This 

number increases further when related human-resource costs, such as recruiting, training, and 

insurance, are factored in. Furthermore, safety performance decrements associated with 

inexperienced drivers and operational inefficiencies resulting from new drivers who are not 

familiar with the service requirements necessary to maintain good customer service are 

v 
problematic (Griffin et al., 2000). Additionally, the research points to a number of factors that 

may impact a driver’s decision to leave or stay with an organization. In particular, compensation 

was indicated by drivers as a reason of primary importance in a study by Stephenson and Fox 

(1996), and in surveys of motor carriers conducted by Dobie, Rakowski, and Southern (1998), 

and Min and Lambert (2002), suggesting that carriers that pay better wages are more likely to 

retain drivers. As a final consideration, an obvious shortcoming to the majority of the academic 

literature that resulted for this first review is that existing research findings do not provide a link 

to outcomes beyond implications for turnover, or turnover rates themselves. Safety is a major 

focus of the trucking industry; yet, in the literature, this outcome was more likely to be 

referenced for its indirect over its direct relationships with study variables. 

In contrast to the first review, the annotated literature for Review #2 is concentrated in the 

identification and comprehension of driver characteristics and motor carrier practices as they 

relate to safety outcomes. For instance, age and CMV driving history, including experience and 

past history of crash involvement and safety violations, are two pertinent areas to this review that 

are frequently addressed in the literature (Knipling, Hickman, & Bergoffen, 2003). Driving 

history is another factor the literature supports as impacting safety. In a study by Murray, Lantz, 

and Keppler (2006), future truck crash involvement was predicted based on past driver 

behaviors. Using Motor Carrier Management Information System (MCMIS) and Commercial 

Drivers License Information System (CDLIS) data, they determined that drivers with prior crash 

involvement were 87% more likely to be involved in a future crash. Results also showed that 

drivers who had been cited for reckless driving violations and improper turn violations were, 

respectively, 325% and 105% more likely to be involved in future crashes. 

Additionally, a number of studies purport to draw a relationship between driver compensation 

and safety outcomes, for example, that increased pay is associated with a reduction in crashes. 

The reviewers offer a cautionary note to these assertions: generally, it is not possible to 

understand the true nature of the relationship between these two factors. Specifically, it may be 

unclear whether cash bonuses for safe driving are responsible for higher pay, or that offering 

better pay at a company improves its ability to recruit and hire greater numbers of quality 

drivers. Taking an organizational focus, there are also practices of the motor carrier that have 

been found to influence safety and promote safety culture. Deserving of mention are reports of 

safety management best practices (e.g., American Trucking Association [ATA] Safe Returns, 

1999; Mejza, Barnard, Corsi, & Keane, 2003; Corsi & Barnard, 2003), listing factors including 

commitment to safety by top management, employee involvement, prioritizing safety in all 

aspects of an operation, and making safety management a continuous process. 

Research gaps within the Haddon matrix for the second review are not as marked as those in 

Review #1. Nevertheless, literature relevant to the event and post-event stages is lacking in 

comparison to that for the pre-event stage. This may, as noted previously, simply reflect a desire 

by researchers to preemptively understand and address safety issues. Moreover, articles found in 

the pre-event stage often discuss safety-management issues and practices that can also be 

conceptualized to pertain to the event, or even post-event stages. 

This review demonstrates the utility of using tailored versions of Haddon’s matrix as a 

framework for addressing some of the prime safety concerns in the trucking industry and 

FMCSA alike. These include the recruitment, selection and retention of a safe workforce, and the 

vi
vii

factors related to improving safety as associated with existing drivers and motor carrier 

operations. Although it was not possible to annotate the hundreds of trade sources that were 

obtained in the same way as the resultant scientific literature, exploring both the academic and 

industry viewpoints was beneficial and allowed for a more complete understanding of the 

complex nature of the trucking industry. Precisely because new and updated industry information 

is constantly being generated, in particular online, only the most recent published trade material 

was relied upon as cited sources. Lastly, as a caveat regarding the current effort that should be 

restated here, this document is not intended as a comprehensive review of the many antecedents 

of safety outcomes, and it intentionally did not duplicate the focus or content of any recent 

FMCSA-sponsored work. 

INTRODUCTION 

The primary mission of the Federal Motor Carrier Safety Administration (FMCSA) is to improve 

safety by reducing crashes, injuries, and fatalities involving commercial motor vehicles (CMVs). 

As particularly important, FMCSA has identified a need for improving the safety practices of 

drivers and motor carriers; however, this goal must be balanced by the need for industry 

productivity and efficiency in an era of goods transport that increasingly focuses on just-in-time 

delivery. Ultimately, the challenge is to produce safer drivers through encouraging motor carriers 

to use industry best practices, including the use of data-driven feedback, without concomitantly 

sacrificing system efficiency. Although positive reinforcement and supportive (non-regulatory) 

outreach are generally preferred as initial steps in this process, the agency also takes appropriate 

measures to ensure regulatory compliance and to remediate non-compliance. 

FMCSA and its predecessor agencies have historically responded to specific and targeted driver 

safety issues, rather than viewing the recruitment, pre-employment assessment, entry, training, 

and operational and regulatory oversight of drivers in a holistic fashion. Examples of specific 

safety issues addressed in the past have been the development of a Commercial Drivers License 

(CDL) program in the late 1980s, the development of regulations in the early 1990s to prevent 

and detect transportation workers’ use of controlled substances and abuse of alcohol, and 

development and publishing in 2003 and 2005 of revisions to the nearly-60-year-old hours of 

service (HOS) regulations. However, the organization of the highway transportation industry has 

undergone significant changes since 1980, when the first layers of economic regulation were 

removed by the Interstate Commerce Commission (ICC). The accelerating pace of changes in the 

makeup of the industry (firms and people), the increasing demands for efficiency in operation to 

support the needs of shippers and to conserve fuel, and the decreasing number and availability of 

potential CMV drivers, demand that FMCSA take steps to better understand the roles, needs, and 

responsibilities of CMV drivers and the entities with whom they interact. 

PROJECT GOAL AND APPROACH 

The goal of the current project is to provide FMCSA with a more complete understanding of the 

non-regulatory factors which make for safer CMV drivers. Through the review of available 

literature, our primary focus is to explore the relationship between the CMV driver and the motor 

carrier with respect to safety outcomes. Ensuring safe driving practices is vital from the moment 

a prospective CMV driver begins training for a license to drive a CMV, as well as throughout the 

driver’s working relationship with a motor carrier, especially in the event of an adverse safety 

incident (e.g., crashes, injuries, traffic citations). The motor carrier may address the need for 

safety oversight in a number of ways, including thorough background checks before hire, inservice training, reward programs and promotion strategies for positive safety behaviors, and 

stringent policies for enforcing governmental and company-specific regulations in the event of a 

safety violation. At the same time, characteristics of the driver, such as age, experience, attitudes 

about safety, and behavioral norms (e.g., speeding) strongly influence whether, and to what 

extent, drivers adhere to motor carrier rules and regulations. 

A tailored Haddon Matrix was used as a means to structure the literature and provide clear 

direction for the development of future intervention strategies. This model was developed by Dr. 

1 
William Haddon and is commonly used in highway safety research as a framework for 

identifying intervention strategies that may aid in preventing or reducing the severity of adverse 

events, such as injuries or accidents (Teret, 1997). Haddon’s Matrix provides a structure for 

identifying factors that influence an event by dividing the event in terms of timeframe (i.e., preevent, event, and post-event) and the actors and/or environments involved in the event. The 

Haddon Matrix was adapted for the current project by considering the driver and the motor 

carrier as the major actors/environments, and identifying events in the driver-motor carrier 

relationship that are important for improving driver safety. To this end, targeting the selection of 

CMV drivers by recruiting, screening, hiring, and retaining the safest drivers is one avenue for 

improving CMV safety and preventing accidents long before they occur. Additionally, 

identifying the causes and consequences of adverse safety events may aid in a better 

understanding of the necessary and desirable driver characteristics and motor carrier practices 

that may mitigate the occurrence of future incidents, reduce the number of repeat occurrences, 

and prevent lapses and minor operational errors from progressing to crashes and other adverse 

safety events. 

PROCESS AND METHODOLOGY 

With respect to the purpose of this project, a search for relevant published literature regarding 

CMV drivers was conducted using multiple internet sites and searchable literature databases 

containing peer-reviewed and trade publications, government reports, and conference 

proceedings. 

Search Strategy 

The following databases were used to conduct the literature search: 

ABI/INFORM Global: contains 1800 worldwide business periodicals with coverage of business 

and economic conditions, management techniques, theory, and practice of business, advertising, 

marketing, economics, human resources (HR), finance, taxation, computers, and more. 

ABI/INFORM Trade & Industry: covers more than 750 business periodicals and newsletters 

with a trade or industry focus. Contains publications on every major industry, including finance, 

insurance, transportation, construction, and many more. 

EconLit: from the American Economic Association’s electronic database, covers economic 

literature, with more than 735,000 records. 

The National Technical Information Service (NTIS): from the U.S. Department of 

Commerce’s Technology Administration. NTIS annually receives tens of thousands of new 

publications, technical reports, and other products from hundreds of government agencies and 

other organizations. 

PsycARTICLES: from the American Psychological Association (APA), contains more than 

45,000 articles from 57 journals - 46 published by the APA and 11 from allied organizations. It 

includes all journal articles, letters to the editor and errata from each journal. 

2 
3 

PsycINFO: from the American Psychological Association (APA), contains nearly 2.3 million 

citations and summaries of scholarly journal articles, book chapters, books, and dissertations, all 

in psychology and related disciplines. 

Transportation Research Information Services (TRIS) Online: a public-domain, web-based 

version of the TRIS bibliographic database, contains over half a million records of published 

transportation research including technical reports, books, conference proceedings and journal 

articles. 

The aforementioned databases were searched using a combination of subject and topic terms that 

were identified as appropriate for the current review. The search criteria identified all 

publications that had at least one subject term and one topic term in the abstract and/or title. 

Subject terms

• Bus 

• Bus Driver 

• Bus Operator 

• Commercial Vehicle 

• Commercial Vehicle Driver 

• Commercial Vehicle Operator 

• Motor Carrier 

• Motor Coach 

• Motor Coach Driver 

• Motor Coach Operator 

• Truck* 

• Truck Driver 

• Truck Operator 

• Van 

• Van Driver 

• Van Operator 

Topic terms

• Accident* 

• Attitude* 

• Behavior* 

• Compensat* 

• Crash* 

• Death* 

• Demand* 

• Employ* 

• Fatal* 

• Hir* 

• Incentive* 

• Insurance 

• Performance 

• Personality 

• Recruit* 

• Regulat* 

• Retain 

• Retention 

• Safe* 

• Satisfaction 

• Select* 

• Speed* 

• Train* 

• Turnover 

• Violat* 

Note that the asterisk is used as a Boolean operator denoting a root word search. For example, a 

search using select* encompasses all words that begin with select, including select-s, select-ing, 

select-ion, and select-ed. 
Citations matching the search criteria were captured and compiled into a single database using 

ProCite bibliographic database management software. First article titles, and when necessary, 

abstracts were reviewed by the contractor’s project staff to determine relevance to the focus of 

the current effort. The articles marked as relevant were then distributed to project team members 

for review, with an emphasis on matching article topics to the expertise of the reviewer. 

Selection Criteria 

In order to focus on only the most current findings concerning safety in the trucking industry, 

selection of literature was limited to references published in 1995 or later. Only works published 

in English and studies conducted in the US, Canada, Australia, or the EU were considered. All 

sources address truck, bus, or van drivers who operate CMVs, or motor carriers that employ such 

drivers. As defined in 49 Code of Federal Regulations (CFR; part 390), a CMV consists of any 

self-propelled or towed motor vehicle used on a highway in interstate commerce to transport 

passengers or property when the vehicle: 

1. Has a gross vehicle weight rating or gross combination weight rating, or gross vehicle 

weight or gross combination weight, of 4,536 kg (10,001 pounds) or more, whichever is 

greater; 

2. Is designed or used to transport more than 8 passengers (including the driver) for 

compensation; 

3. Is designed or used to transport more than 15 passengers, including the driver, and is not 

used to transport passengers for compensation; 

4. Is used in transporting material found by the Secretary of Transportation to be hazardous 

under 49 U.S.C. 5103 and transported in a quantity requiring placarding under 

regulations prescribed by the Secretary under 49 CFR, subtitle B, chapter I, subchapter C. 

In accordance with the scope of the project, an effort was made to identify literature that 

addressed one or more of the following topic areas: 

• Driver recruitment, selection, hiring 

• Driver turnover and/or retention practices 

• Driver safety training 

• Driver compensation and incentives to drive safely 

• Driver-related predictors of accidents 

• Characteristics of safe drivers (e.g., behaviors, abilities, demographics) 

• Relationships between motor carriers and drivers (e.g., organizational culture, driver 

commitment, job satisfaction) 

• Driver-focused safety practices of motor carriers 

4 
In addition, the following topic areas were identified as out of scope for the current project, per 

discussions with the FMCSA sponsor: 

• Aviation 

• Rail 

• Maritime 

• School buses 

• Driver fatigue and sleep disorders 

• HOS regulations 

• Driver physical qualifications; medical conditions 

• Crash causation mechanisms 

• Environmental and mechanical factors related to accidents 

Transportation research outside of CMV operations was excluded due to marked differences 

between operations in the trucking and motor coach industries and other forms of transportation. 

Topic areas such as fatigue and HOS regulations were also excluded in a desire to reduce overlap 

with other on-going research efforts. 

The initial stage of the literature search returned over 2,000 total potential citations. Reduction of 

the ProCite database began by viewing records as grouped by keywords, imported from the 

specified data sources. It was determined that using a liberal search strategy and subsequently 

eliminating obviously unrelated sources by keyword was more efficient than attempting to add 

articles on an individual basis. Articles with unrelated keywords and/or keywords related to 

excluded topic areas, as specified above, were marked so the articles could be removed at a 

future point. A second reviewer confirmed that each article marked for deletion was not 

applicable to the scope of the current project, at which point the article was removed from the 

database. After this initial pass, reviewers more closely scrutinized the content of the remaining 

articles through title and abstract reviews. Additional deletions were made throughout the course 

of the project as full-text was reviewed and articles that were not relevant to the project scope 

were eliminated, leaving a total of 131 sources. 

Relevant reference works were divided into primary and secondary sources based on a review of 

abstract and/or executive summary information, where available, or the full text, if necessary. 

The primary sources consist mainly of peer-reviewed literature and conference proceedings that 

are based on first-hand empirical data. References identified as secondary sources consist largely 

of high-level reviews and synthesis reports that contain relevant information, but do not utilize 

first-hand data (e.g., meta-analyses). Applicable references from trade publications were also 

retained in the database to fill gaps in search results as necessary. The final database included 65 

primary sources (20 annotated for Review #1 and 45 annotated for Review #2), 30 secondary 

sources, and 36 trade sources. 

5 
Review Strategy 

All articles deemed appropriate for inclusion as primary sources were annotated by one or more 

reviewers using the format outlined below. References that were published as a series or utilized 

the same data set are included as a single annotation. The following format was used when 

annotating primary sources: 

Complete Citation (APA Format): Author(s). (Year). Title. Journal, Volume, Page numbers. 

Immediately below the source citation, a Haddon matrix is used to show the context of the 

source in relationship to all areas being reviewed. A blank matrix is shown in Figure 1 below. 

For further explanation of the Haddon matrix content cells, see Table 1 on page 8. 

Haddon Matrix #

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix #

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Figure 1. A sample Haddon Matrix with Blank Cells 

Author Abstract: If available, this section includes the abstract taken directly from the 

source article. 

Industry Sector: Describes the subject matter of the source (e.g., trucking, bus industry). 

Purpose: Briefly summarizes the purpose of the article. 

Sample: Provides number of participants and criteria for selection. Also includes 

relevant sample demographic information. 

Methodology: Describes the methods and procedures used to collect the data (e.g., 

survey, field study, lab experiment, focus group). 

Relevant Findings: Identifies specific study findings and general study conclusions that relate 

to the purpose of the literature review. 

Limitations: Describes limitations of the study from the perspective of both the 

author(s) and the reviewer (e.g., methodology used, inconsistent findings, 

no causality). 

Categorization: Explains where, how, and why the article fits within the framework of the 

Haddon Matrix as identified in the small matrix presented prior to each 

annotation (see matrix above).

6 
Secondary sources are provided as a separate reference list at the end of the annotations for each 

review. Author abstracts are included when available. If no author abstract existed, an abstract 

was acquired from one of the databases used in the literature search or composed by a member of 

the project team. 

Given the varied content of trade publication sources located in the search, and their nearly 

universal lack of data-based results, it was not possible to annotate them in the same manner as 

was done for primary sources. Nevertheless, trade sources were reviewed by members of the 

project team and have been incorporated into the synthesis, where appropriate, to supplement 

gaps identified in the literature and better characterize the state of affairs in the industry. 

Organization and Presentation of Results 

This project effort is presented as a series of two annotated literature reviews. An adapted 

Haddon Matrix is employed as the framework for describing the intent and focus of each review. 

The first literature review concerns the selection of safe CMV drivers; the second literature 

review relates to improving CMV driver safety through the prevention of adverse safety events. 

Primary source annotations and secondary source abstracts are presented separately for each 

review. 

The content of annotated reviews and any additional commentary are presented as an objective 

summary/synthesis of the literature, in language understandable to a non-subject matter expert, 

defined as a person familiar with the motor carrier industry, but who does not necessarily have 

advanced training or experience in psychology, business, or HR. Each annotation necessarily 

reflects the level of detail in the corresponding study and primarily concentrates on findings 

relevant to the scope of the review. In cases where works are clearly related (e.g., identical data 

sets; pilot and follow-on studies), superscripts separate multiple references contained within a 

single annotation. 

7 
LITERATURE REVIEWS 

This project considers two non-regulatory approaches to support FMCSA’s mission of 

improving safety on the roadways. The first approach addresses the workforce “pipeline” issue—

who is applying to and being recruited for CMV driver positions—extending to the hiring 

process, and further, considering retention and turnover. Review #1: Selecting Safe Drivers 

provides a synthesis and discussion of the available and applicable literature in this area. The 

second approach is to focus on improving the safety of those drivers already “on the road” by 

considering the various driver and motor carrier practices that affect safety outcomes, prior to, 

during, and after safety incidents. In the same manner as for the first review, Review #2: 

Improving Driver Safety addresses this area. 

REVIEW #1: SELECTING SAFE DRIVERS 

For this review, Haddon’s matrix was adapted such that CMV drivers and motor carriers are the 

two environments, and the events in the driver-motor carrier relationship are those important for 

ensuring that the CMV workforce is comprised of safe drivers. To this end, Review #1 

encompasses literature addressing the selection of an ideal crop of CMV drivers by recruiting, 

screening, hiring, and ultimately, retaining the safest employees. Each primary source for 

Review #1 was annotated and then categorized within one of the six Haddon matrix cells below, 

as determined by its main focus with regard to environment and event timeframe. 

Table 1. Haddon Matrix for Review #1: Selecting Safe Drivers 

Pre-Event Event 

(Hiring of CMV Drivers) 

Post-Event 

Driver 

Environment 

Who is applying for 

CMV driver positions 

(and why)? 

What factors are part of the 

decision a person makes to 

accept or reject a job offer? 

What driver-related factors 

influence whether or not 

CMV drivers remain at a 

particular job and/or in the 

workforce? 

Motor Carrier 

Environment 

Who is being recruited 

for CMV driver positions 

(and how)?

What criteria/applicant 

selection strategies are 

used as part of the hiring 

process?

What organizational factors 

influence whether or not 

CMV drivers remain at a 

particular job and/or in the 

workforce?

Literature Search Results 

The literature search for this project generated a total of 20 articles, referencing 16 unique study 

efforts for Review #1. The material that was annotated covered topics addressing each stage of 

the event cycle; however, comparable numbers of documents did not result for all six cells of the 

matrix. Rather, the bulk of the applicable sources for Review #1 pertained to the post-event 

stage. 

8 
As a general overview, referencing Table 1, studies categorized into the pre-event stage, driver 

environment answered the focus question, “Who is applying for CMV driver positions (and 

why)?” and covered the topics of driver recruitment and driver demographics. Also within the 

pre-event stage, the available literature addressing the motor carrier environment answered the 

question, “Who is being recruited for CMV driver positions (and how)?” and focused solely on 

recruitment. The event stage of the matrix for the driver environment was conceptualized to 

address the question, “What factors are part of the decision a person makes to accept or reject a 

job offer?”; however, the research team located no published literature to address this area. In 

the motor carrier environment, the event stage was formulated to encompass the question, “What 

criteria/applicant selection strategies are used as part of the hiring process?” and resulted in a 

single study that investigated criteria for selecting safer drivers. The post-event stage of the 

matrix and accompanying question, “What driver-related factors influence whether or not CMV 

drivers remain at a particular job and/or in the workforce?” pertained to the driver environment 

and resulted in a group of studies covering driver turnover and retention. Finally, the post-event, 

motor carrier environment, and question “What organizational factors influence whether or not 

CMV drivers remain at a particular job and/or in the workforce?” mapped to a variety of 

applicable studies on driver turnover, retention strategies, management relations, and employee 

fit. 

Selecting Safe Drivers Outcomes 

The outcomes of Review #1 point to employee turnover as a primary focus of the data-driven 

research conducted over the past decade. Driver turnover—in particular, voluntary turnover—has 

been considered a substantial problem in the trucking industry since deregulation took place in 

1980. Deregulation, which allowed new firms to enter the industry, led to an increase in 

competition among carriers, lower wages, and a more demanding work environment for drivers, 

thus indirectly increasing turnover (Min & Emam, 2003; Min & Lambert, 2002). Currently, 

reports of annual turnover rates in excess of 150% are not uncommon within the truckload (TL) 

segment of the motor carrier industry (Griffin, Kalnbach, Lantz, & Rodriguez, 2000), and 

therefore, concerning for both motor carriers and safety regulating agencies alike. Whether these 

employees are leaving the profession entirely or simply “churning” (moving from one company 

to another; Gallup Organization, 1997), both voluntary and involuntary turnover necessitate 

additional hiring. This is increasingly true in light of overall growth in the trucking industry 

paired with an ongoing economic recovery from the recession of 2000 (Global Insight, 2005). In 

fact, over a 10 year span through 2005, the Gallup Organization (1997) projected an increased 

need for truck drivers at 12-13%. Paired with a shrinking pool of young, white males—a 

traditional recruitment source—they suggest a need to explore beyond this group, and possibly 

look to women and minorities. 

Negative impacts associated with turnover and subsequent hiring needs include substantial 

organizational costs to hire a full complement of drivers each year, estimated as a $7,000 

expense per lost employee (Griffin et al., 2000). This number increases further when related 

human-resource costs, such as recruiting, training, and insurance, are factored in. Furthermore, 

safety performance decrements associated with inexperienced drivers and operational 

inefficiencies resulting from new drivers who are not familiar with the service requirements 

necessary to maintain good customer service are problematic (Griffin et al., 2000). Alternately, if 

hiring demands are not successfully met by organizations, the outcome is an inadequate staff, 

9 
where drivers potentially work beyond their personal limits (and in some cases, legal limits) to 

accomplish their work—or underqualified and/or undesirable drivers have been hired to fill gaps 

(Gallup Organization, 1997; Min & Emam, 2003; Min & Lambert, 2002). 

Research points to a number of factors that may impact a driver’s decision to leave or stay with 

an organization. In particular, compensation was indicated by drivers as a reason of primary 

importance in a study by Stephenson and Fox (1996), and in surveys of motor carriers conducted 

by Dobie, Rakowski, and Southern (1998), and Min and Lambert (2002), suggesting that carriers 

that pay better wages are more likely to retain drivers. Other factors cited by drivers in the 

Stephenson and Fox (1996) study pertained to corporate culture. For example, they noted pride 

in one’s company, an organization’s fair treatment and appreciation of workers, followed by 

safety, security, equipment, and working conditions. Motor carrier managers, when surveyed, 

reported similar factors as impacts to turnover (Dobie et al., 1998; Min & Lambert, 2002). In 

addition to the above, managers cited reasons of carrier reputation and available benefits (e.g., 

health benefits). 

On a more general level, job satisfaction was linked to turnover in a study by Kalnbach and 

Lantz (1997), such that new truck drivers who had remained with the company for four months 

and reported greater job satisfaction were also more committed to the organization and less likely 

to have contemplated quitting. For most occupations, four months’ tenure may be considered a 

premature point at which to assess job satisfaction; however, in an industry that suffers from 

annual turnover at the rate that trucking does, this was probably not an unreasonable timeline. In 

a complimentary research effort, the Gallup Organization (1997) surveyed long-tenured truck 

drivers who had been with their company for five or more years, and were therefore presumed to 

be satisfied with their jobs. Results of a regression analysis of 21 job attributes associated with 

trucking indicated “steadiness of the work,” “genuine care of managers,” “pay,” “support from 

company while on the road,” and “hours of work,” respectively, as the top five predictors of 

overall job satisfaction. 

A pair of studies by Gupta, Jenkins, and Delery (1996), and Shaw, Delery, Jenkins, and Gupta 

(1998) investigated organizational-level turnover in terms of both voluntary and involuntary 

turnover from the perspective of HR managers in the trucking industry. As driver quit rates were 

reported at four times higher than discharge rates, this distinction is an important consideration. 

Generally, they noted a similar set of factors leading to turnover as those previously cited; 

further, they found that lower quit rates were associated with being home more times per month 

and less on-board technology. The lowest discharge rates were established for companies using a 

low selection ratio (few drivers hired out of many applicants), as well as those that employed 

performance and/or technical knowledge tests instead of unstructured interviews as part of the 

hiring process. Pertaining to human resource management (HRM) strategies, voluntary turnover 

was predicted by investment-focused practices. Specifically, they found a negative relationship 

between voluntary turnover and pay and benefits (higher pay and benefits associated with lower 

quit rates); a positive relationship with voluntary turnover was determined for companies 

reporting more time spent on the road and more frequent use of electronic monitoring. 

Additionally, involuntary turnover was predicted by staffing practices (a low selection ratio), as 

discussed above. 

10
Although minimizing voluntary and involuntary driver turnover is indeed a means of stabilizing 

the size of a company’s workforce, retaining employees who engage in unsafe driving practices, 

or are otherwise unsuited for the job, highlights a problem with the prevalent focus of recent 

academic research efforts. At the post-event stage of the Haddon matrix, an organization has 

already invested substantial time, money, and HR for the purposes of driver recruitment, 

selection, and training. Yet there is no guarantee that maximizing only retention will improve the 

quality of a company’s drivers, particularly if recruitment and selection strategies are not 

concomitantly bolstered. 

To this end, a small number of studies in the first review addressed recruitment and selection. 

Research gaps in these areas may be a function of what researchers perhaps believe is 

unavoidable industry churn, if, as Richard, LeMay, and Taylor (1995) pointed out, drivers have 

little loyalty to a company when they perceive that drivers working elsewhere are treated at least 

as well as they are. Min and Emam (2003) nevertheless posited that it may benefit organizations 

to tailor policies to recruit drivers with a history of changing jobs less frequently , in addition to 

older, experienced (>5 years CMV driving experience) drivers, especially as younger, 

inexperienced drivers were perceived by managers as “obstacles” to successful recruitment and 

retention (Min & Lambert, 2002). As touched upon briefly above, it again bears mention that the 

results of Gupta et al. (1996) and Shaw et al. (1998) illustrate the utility of using performancebased and knowledge hiring tests instead of unstructured interview formats, in conjunction with 

conservative selection techniques, to select only the most qualified drivers. 

Although this approach appears logical, it may not be practical or possible for motor carriers to 

implement at a time when there are already driver shortages, as industry need continues to rise 

by 1-2% per year (Gallup Organization, 1997), and a mere 18% of students at two and four year 

colleges indicated that they would even consider a career in transportation (Philbrick & Sherry, 

2004). Alternately, in cases where selection procedures are necessarily less rigorous, a composite 

developed by Jacobs, Conte, Day, and Silva (1996) for transit bus operators may be beneficial. 

Their model combined six predictor components into a composite measure: biographical 

information related to temperament and sense of timeliness; personality measures of 

conscientiousness and openness; and attitudes regarding safety and authority. Resulting 

composite scores were related to both objective performance criteria (e.g., attendance, accidents) 

and subjective performance ratings by supervisors. Use of the composite was therefore shown to 

provide enhanced ability to select bus operators who will drive more safely, miss fewer 

workdays, and be viewed by supervisors as strong performers. Moreover, a utility analysis 

suggested that composite use could reduce operating expenses related to accidents/absences by 

over $550,000 per year, using cost estimates derived from discussions with managers at six 

transit properties. Although these results appear encouraging, it is important to note that for such 

a process to work optimally for selecting the safest and most qualified drivers, applicants must 

buy into it and accurately provide the requested sensitive, personal data. Also, once hired, intraorganizational factors, such as culture and climate, have the rapid potential to influence safety 

and other behaviors. If these influences are negative, they could easily negate such a system’s 

benefits. 

As a final consideration, an obvious shortcoming to the majority of the academic literature that 

resulted for this first review is that existing research findings do not provide a link to outcomes 

beyond implications for turnover, or turnover rates themselves. Safety is a major focus of the 

11
trucking industry; yet, in the literature, this outcome was more likely to be referenced for its 

indirect over its direct relationships with study variables. Despite that turnover is a problem for 

trucking organizations even more than for the typical employer in the United States, when unsafe 

drivers remove themselves from the workforce or are discharged, it is then, in fact, appropriate 

and desirable. It is proposed that further, systematic investigation into the voluntary and 

involuntary turnover of unsafe or otherwise objectionable drivers is warranted for its potential to 

help carriers avoid their recruitment, selection, and hiring. 

Findings from Trade and Industry Sources 

Forums conducted by the Department of Labor in 2005 suggested that the major issues facing the 

trucking industry at the time included the following: low wages and undesirable benefits relative 

to other jobs; a lack of career advancement opportunities for drivers; relatively untapped labor 

markets of recent immigrants with limited English-speaking ability, military veterans, and older 

workers; a minimum entry age of 21 that makes it more difficult to recruit young people into the 

industry; and that not enough new workers are in the pipeline to meet labor market demand, in 

addition to accounting for attrition and turnover (Bearth, 2005). 

In comparison with the academic literature, trade-publication sources provide an even more 

varied explanation of the turnover problem. Statistics from 2006 identify the turnover rate for 

large TL firms—those with at least $30 million in revenue—at around 116%, a slight decrease 

from previous years, and 111% for small TL firms, a 9% increase from the previous year 

(Reddy, 2006c). Less-than-truckload (LTL) firms have an average turnover rate of between 13-

15%. Private fleets, like LTL carriers, enjoy a relatively low turnover rate of 16% (Leavitt, 

2006). Significant differences in how the various sectors of the trucking industry operate, as well 

as the activities required of their drivers, may also be driving these exceptional differences in 

turnover rates. In terms of the differences between private and for-hire carriers, Gary Petty, 

president of the National Private Truck Council (NPTC) concludes that “driving for a private 

fleet and driving for a long-haul, for-hire carrier are really two different jobs” (as cited in Leavitt, 

2006, p. 18). For one, drivers who work for private and LTL firms are typically home more 

often, if not every night of the week. Drivers in private fleets often run regular routes and meet 

with the same customers, providing structure and predictability to their job. 

Although the jobs can be vastly different, TL carriers may be able to learn from private and LTL 

carriers, and it may involve a global change in how drivers are both perceived and treated. Petty 

notes that “private fleets tend to have a culture of longevity ... fifteen to twenty years [tenure] is 

not uncommon at all” (as cited in Leavitt, 2006, p.18). This long-term mentality is, in theory, 

within the reach of any trucking company, regardless of long- or short- haul, private or for-hire. 

Susan Rhodes, a driver recruiter for a small family-owned trucking company, emphasizes that 

her firm treats drivers “better than family” because drivers are “the connection between the 

corporate office, the shippers, the customers, and the consumers who eventually use the products 

we haul” (Rhodes, 2006). Smaller TL firms have fewer drivers than their larger counterparts, 

often putting them in a better position to maintain one-on-one contact with their drivers. 

Contrastingly, for larger TL carriers, the dispatcher becomes the sole “face” of the company. An 

examination of printed and online industry publications in fact revealed that the majority of 

factors identified as primary contributors to driver retention were attributable to interactions 

between drivers and field management (i.e., dispatchers). These included communication, 

12
problem resolution, respect and honesty, equipment maintenance, home time, adequate driver 

training, and clear and fair working rules (White, 2005). Mercer, a TL firm that leases owneroperators, attributes their low turnover rate, at 32%, to a commitment to fostering positive 

relationships, where drivers are encouraged to speak frankly and discuss any issues they have 

with their dispatcher. Mercer also makes an effort to pair drivers and dispatchers with similar 

interests in order to encourage a personal connection (Kilcarr, 2007). 

As recommended based on the annotations for this review, it was encouraging to note in the 

associated trade and industry sources, that there are efforts to shift the focus of motor carriers to 

the recruitment process as a means of bolstering driver retention. This is related to cost savings, 

as well as a potential safety benefit, since a well-trained and well-informed recruiter should 

theoretically be able to identify applicants who will be steady, longer-term employees, while 

avoiding those who will not (Galligan, 2003). Furthermore, it is suggested that recruiters be upfront with applicants and provide realistic information about the challenges of being a driver, as 

many times those who quit do so because they were not well informed about the requirements of 

the job (Kilcarr, 2004; Reddy, 2006b). For those motor carriers that expend time and effort to 

hire quality drivers up-front, more time can and should be spent on retaining these workers. 

Experts also stress that a recruiter’s job should not end at the point of hire. In fact, for drivers 

who fail to meet carrier expectations, it is recommended that recruiters go back and review notes 

from the interview, application, and reference checks to determine what was missed and what 

lessons learned may reduce excessive turnover in the future (Bookbinder, 2003). 

In addition to turnover, the perceived lack of qualified applicants for truck driving positions has 

also made the process of recruiting drivers more time consuming than in the past. One carrier 

reported that it took eight months to find drivers for only two positions (Fischer, 2005). 

However, fortunately, new computer software and the internet are helping to streamline hiring 

and speed up the process of getting drivers out on the road by improving the efficiency and 

effectiveness of receiving and reviewing applications. Additionally, many carriers are 

automating hiring by using online applications and software that allows for tracking candidates 

through the company from the time they submit their application to the point of hire. When 

quality drivers are such a valuable commodity, it becomes even more important to keep track of, 

and follow up with, every applicant (Smith, 2006). 

To the same degree that the trade literature over the past five to ten years has targeted driver 

shortage as the biggest issue faced by the trucking industry, the most commonly proposed 

solution to this problem has been to increase driver pay. Indeed, average per mile pay rates have 

been on the rise to better compete with other industries that often recruit from the same pool of 

applicants, such as construction. However, the wage hikes have not produced the desired result, 

as driver shortages continue to plague the industry. Instead, wage increases may have had the 

unintended effect of promoting what the industry terms “job churn” (Reddy, 2006c), as drivers 

frequently hop, and are sometimes poached, from one carrier to another in order to earn the 

highest pay possible (Guerrero, 2005). 

A recent article in Transport Topics argues that wage increases are not effectively attracting new 

drivers to the industry (Anonymous, 2005a), and anecdotal evidence from motor carriers echoes 

findings from the academic literature. Quite simply, pay raises are not sufficient to attract and 

hold good drivers. Rather, improving driver quality of life may be just as, if not more, important 

13
(Reddy, 2006a). Carriers that have seen reductions in their turnover rates often attribute their 

success to a focus on improving the quality of drivers’ working lives by providing more 

predictable work schedules, more time at home, and better benefits. In addition, fostering driver 

commitment and loyalty to the company goes a long way toward retention. Motor carriers can 

increase driver investment by getting them involved and making them feel like a member of the 

team, as opposed to merely a number. Brad Penneau, a former driver and recruiter with over 18 

years experience in the industry, notes that “Pay may attract a driver to a company, but pay will 

not keep a driver. Pay alone is not an investment, but if a driver has an investment in the carrier, 

that’s harder to walk away from” (as cited in Galligan, 2003, p. 15). 

As a means of combating turnover, recommendations from academic sources include a careful 

and systematic selection of applicants for hire. Not surprisingly, many carriers are concerned 

that, paired with a perceived labor shortage or, at minimum, a dearth of qualified applicants, 

maintaining stringent hiring qualifications will put them at a competitive disadvantage and 

render them unable to keep up with the demands of the industry (Fischer, 2005). Improvements 

in obtaining accurate background checks and accident history reports have allowed safetyconscious carriers to make more informed hiring decisions. However, some argue that being 

more thorough also shrinks the pool of available applicants (Bearth, 2006). This may not be an 

entirely negative outcome; however, as research clearly suggests that past performance predicts 

future performance. Compromising selection criteria is done at a carrier’s own risk, and hiring 

unsafe or undesirable drivers is bound to affect a company’s bottom line. It may even result in 

legal action if the driver is involved in a crash. 

In fact, Paul Berne, an attorney and member of the Trucking Industry Defense Association, notes 

that claims for negligent hiring—the failure to use reasonable care in the employment selection 

process—have increased exponentially over the past five years (Bearth, 2006). Even so, as 

stringent selection procedures targeting only highly qualified drivers may not be an option for 

many carriers, they have taken to training their own potential driver-applicants as an alternative 

solution. For example, New England Motor Freight invested about a half-million dollars to start 

up their own training school. Thomas Hartley, director of safety for the firm, came up with the 

idea for the school as a way to “produce safe driving” (as cited in Gower, 2005). Motor carriers 

are also teaming with local community colleges to recruit and train new drivers (Waters, 2006). 

Many of the new workers in these programs are middle-aged and looking to driving as a second 

career; in fact, the average age of students enrolled in a commercial driver training program at 

Hagerstown Community College, in Maryland, is 39 (Heerwagen, 2004). It appears, though, that 

despite their concerted efforts, motor carriers will continue to face great difficulty recruiting 

younger workers to the industry. 

Jim York, manager of Zurich Service Corp.’s Risk Engineering Transportation Team, proposed 

that “Perhaps drivers are leaving because they feel that we are not investing in their future 

success through effective training and support” (York, 2004, p. 53). Citing research suggesting 

that younger drivers experience more crashes than older drivers, he acknowledged the need for 

better training for younger drivers in hopes of addressing this safety problem. Related to this 

need, a UK motor carrier recently won an award for excellence for its development of an 

apprenticeship program designed to introduce younger workers to driving from as early as age 

17. Trainees begin by driving local delivery trucks, and can then move on to an advanced 

apprenticeship where they are taught to drive larger commercial vehicles (Jack, 2006). 

14
Additionally, the government in Ontario, Canada is teaming with industry groups to create a 

voluntary apprenticeship program where drivers will learn such things as trip planning, 

equipment inspection procedures, and how to safely handle cargo (Anonymous, 2005b). 

Similarly, Pitt-Ohio, a LTL fleet based in Pennsylvania, developed a pilot, in-house “stepping 

stone” training/apprenticeship program, allowing dock workers a clear path to becoming a truck 

driver. In this program, dock workers, who have an advantage of already being familiar with how 

the company handles freight, gain initial driving experience with 14 ft. straight trucks. Successful 

workers can then move up to a tractor-trailer after 2 years experience. In turn, Pitt-Ohio reports 

that the drivers trained in-house have been involved in fewer accidents (Cullen, 1998). 

As suggested in a report by the Gallup Organization (1997), there is evidence that motor carriers 

are also making a concerted effort to reach out to populations of workers, beyond young, white 

males, that have not been actively recruited as truck drivers in the past. Currently, many older 

workers reaching retirement age are looking towards truck driving as a post-retirement career. 

Indeed, Schneider National is actively pursuing older workers to join their workforce, and 

reports that 15% of the professional truck drivers they hired in 2005 were at least 50 years old 

(Jadin, 2006). Military veterans represent another underutilized labor market for the trucking 

industry. Many veterans who leave the military have experience operating heavy-duty vehicles, a 

strong work ethic, and are capable of working independently (Reddy, 2006b), suggesting that 

they might be a naturally good fit for a career in truck driving. Companies are also attempting to 

attract Hispanics to the industry by recruiting in traditionally Hispanic communities, advertising 

in Spanish, participating in job fairs and stay-in-school programs, and hiring bilingual 

dispatchers and recruiters to bridge the language barrier (Levy, 2005; Schulz, 2001). 

A final issue raised by experts and investigated in Griffin et al. (2000) is that it may be difficult 

to attract and retain workers because of the lack of a well-defined career path for a driver. For 

example, an accountant’s career path may start in from billing, and move on to receivables, to 

asset management, and ultimately to a position of controller in a trucking firm. A driver will 

almost always stay a driver, with little to show for it besides seniority (Labbe, 2006). The lack of 

a career path may also be driving the problem of job churn within the industry. Duff Swain, 

president of Trincon Group, a consulting firm specializing in long-haul trucking, points out that 

“As a result of industry deregulation in 1980, driver pay rates have been set by the market rather 

than based on experience and competence and drivers have little loyalty to a particular employer, 

since they can obtain comparable pay and benefits with any number of fleets” (as cited in Cullen, 

July 2004, p. 20). Swain’s consulting firm suggests a complete overhaul of the profile of a 

typical truck driver: “The industry must recruit or create a driver who is security- and careerconscious, and self-motivated to increase their wage or standing in a company” (as cited in 

Cullen, 2004, p. 20). In the past, motor carriers have attempted to attract workers to driving 

positions because of the independent lifestyle it affords. While independence is indeed attractive, 

it is not enough to keep drivers for the long term. Without a clear path for career advancement, 

drivers are unable to make goals for the future and have little reason to stay loyal to a single 

company (Swain, 2000; Nguyen, 2007). Interestingly, rather than the existing focus on turnover 

in much of the literature, a more innovative solution may be required—one that is long term and 

involves changing the image of trucking to better equip the industry, while also meeting the 

needs of today’s workforce. 

15
Review #1 Annotations 

Pre-event 

Driver Environment: Who is applying for CMV driver positions (and why)? 

Global Insight, Inc. (2005). The U.S. truck driver shortage: Analysis and forecasts. American 

Trucking Association. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Demographics Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Demographics Driver

Environment

Pre-Event Event Post-Event

Author Abstract: No author abstract 

Industry Sector: Long-haul, heavy duty trucking 

Purpose: The purpose of this study was to assess the long-term needs for truck 

drivers in the trucking industry. The study sought to quantify growth in the 

demand and supply of truck drivers over the next decade, and also to 

identify the demographic and regulatory factors that affect the supply of 

truck drivers. It also explained how the industry can adjust to the 

imbalances between supply and demand. 

Sample: Census data includes over 62,653 responses from the year 2000 where the 

responders identified themselves as truck drivers. 

Global Insight estimated a population of 780,000 long-haul truck drivers, 

including owner-operators, based on Bureau of Labor Statistics (BLS) 

data. 

Methodology: The study first used Census Bureau statistics, BLS, and industry statistics 

to quantify the size of long-haul trucking. Global Insight attempted to 

reconcile the Census and the BLS data, which differ in their definitions of 

the truck driver occupation and the truck transport industry. The BLS 

estimate was used for the total population of long-haul heavy duty truck 

drivers in the Truck Transportation industry, whereas Census supplied 

demographic data. 

The Office of Occupational Statistics and Employment Projection of the 

BLS used data from the year 2000 to identify job types in all industries. 

Global Insight extracted only heavy-duty and tractor trailer drivers 

employed in the “truck transportation” industry and owner-operators from 

16
the BLS data, thus excluding drivers from non-trucking industries. The 

owner-operator population estimate was comparable to the Census 

Bureau’s 2002 Vehicle Inventory and Use Survey and the 2002 Current 

Population Survey (CPS) estimates. Global Insight further narrowed the 

population to include only long-haul, heavy-duty truck drivers, arriving at 

the final estimate of 780,000 drivers based on the BLS data. 

The authors also used 2000 Census of Population and Housing data, CPS 

data, and the Public Use Microdata Sample (PUMS) to analyze truck 

driver demographics. (The PUMS contains responses from 5% of the 

households that received the long form of the census, 62,653 of whom 

were truck drivers.) The total CPS estimate in 2000 was 1.5 million 

drivers. 

The CPS industry classification is broader than the population of longhaul, heavy duty truck drivers in the truck transportation industry of 

interest to the authors; however, it was the only source of demographic 

data available. 

Secondly, the authors used proprietary forecasting models to project job 

growth in the long-haul trucking industry. Third, the authors looked at 

changing demographics of the general population to develop various 

scenarios of change in the supply of long-haul truck drivers. Census and 

CPS data from 2000 were used to analyze the labor force participation rate 

in heavy-duty driving by age, sex, and race/ethnicity. Lastly, the study 

analyzed how wages must adjust in order to close the gap between supply 

and demand. This was done by comparing wages in trucking to wages in 

industries often seen as alternative occupations for drivers, such as 

construction. 

Relevant Findings: Based on demographic trends and growth rates in labor force participation, 

Global Insight predicted that the supply of long-haul truck drivers will 

grow at an average annual rate of 1.6% over the next 10 years. This 

growth rate will not be adequate compared to the estimated average annual 

growth rate in demand (2.2%, or 320,000 jobs over the next 10 years.) It 

was found that one in six drivers was 55 or older in 2000, making the 

average age of truck drivers higher than that of the overall labor force. An 

additional 219,000 drivers will be needed to replace these drivers when 

they retire or leave the industry. Taking both growth and demographic 

change into account, a net of 54,000 drivers per year will be needed over 

the next 10 years. The dearth of drivers will widen from a current 20,000 

to 111,000 by 2014. Further, individual truck firms will need to hire at a 

greater rate because of frequent inter-firm turnover, or churn, and 

ultimately the shortage of qualified, safe drivers will be even greater. 

Demographic factors were found to account for some of this predicted 

17
shortage. The entire labor force is projected to grow by only 0.5% by 

2014. In addition, the largest demographic group of truck drivers—white 

males aged 35–54—will make up an increasingly smaller percentage of 

the population. Some of this decline will be offset by workers who are 

currently in the 35–54 year old age group continuing to work into their 

sixties and by an increase in Hispanic male drivers, who already represent 

an increasing share of truck drivers. 

In order to close this gap, firms will need to offer higher wages to attract 

workers from other industries. The competitiveness of wages in the 

trucking industry fell during the 2000 recession and has not yet recovered. 

Whereas average weekly earnings in the long-haul trucking sector were 6-

7% above earnings in construction throughout the 1990s, they fell to 

below 9% in 2001 and remain at below 1%. The authors expect to see 

wage gains of 6-7% per year over the next three years in long-haul 

trucking. However, wages will need to grow at an even faster rate (more 

than 8%) once demographic trends worsen in the second half of the 

decade. Firms will also need to address non-monetary aspects of the job, 

such as time away from home. Closing the gap in the supply of truck 

drivers is achievable by attracting workers from other industries because 

the shortage in the total number of truck drivers needed by the industry 

will account for less than 0.1% of the total labor force in 2014. 

In summary, the supply of truck drivers is projected to grow, but not 

enough to meet the growth in demand. Wages and non-monetary benefits 

will have to increase in order to fill the labor market gap. 

Limitations: The study does not directly address safety. However, the shortage in all 

drivers, especially qualified ones, may put pressure on the industry to hire 

under-qualified and potentially unsafe drivers. 

The CPS, used to analyze demographics, aggregates occupational data, 

making it impossible to separate non-long-haul drivers from total truck 

driver data. However, the authors exclude local haul drivers from the total 

population estimates. Thus, the authors estimate the size of the trucking 

industry using only heavy-duty long-haul drivers, but analyze 

demographics using data on both long-haul and short-haul heavy-duty 

truck drivers. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #1: Driver Demographics, because the paper describes 

the current and future supply and needs in the driver labor market, 

including driver demographic factors as explanations for some of the 

projected shortages. 

18
Philbrick, K.E., & Sherry, P. (2004). Perceptions of the intermodal transportation industry 

related to recruitment and retention of human resources (Publication No. DTRS98-G-0017). 

National Center for Intermodal Transportation: Research and Special Programs 

Administration. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Recruitment Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Recruitment Driver

Environment

Pre-Event Event Post-Event

Author Abstract: No author abstract 

Industry Sector: Intermodal transportation and the transportation industry in general 

Purpose: The purpose of the study was to assess college students’ perceptions of the 

transportation industry and make recommendations regarding future 

recruiting efforts. The authors highlight the importance of attracting young 

people to the transportation industry as a way to potentially begin to 

remediate the shortage of skilled workers in transportation. 

Sample: 447 college students. 

Methodology: Researchers surveyed students from community colleges and four-year 

universities using a questionnaire developed specifically for this study. 

They approached students in public areas on campus to solicit 

participation. The questionnaire included items intended to measure 

influencing factors for career choice, occupational values, preference for a 

career in transportation, job preference (measured using the RIASEC 

vocational interest typology), knowledge of various career types, 

perceived desirability of various career types, and demographic 

information. 

Relevant Findings: Individuals considering a career in transportation were found to be more 

likely to value employee assistance, wellness and fitness programs, 

labor/management relations, travel opportunities, and opportunities for 

career advancement and leadership. Not surprisingly, a vast majority of 

the participants, regardless of career preference, reported that financial 

gain and competitive fringe benefits were important to them in making a 

career decision. The transportation industry ranked the third lowest, out of 

14 career fields, in terms of desirability. Also, only 18% of participants 

indicated that they would consider a career in transportation. Participants 

also indicated only limited knowledge of the different types of careers 

available in transportation, suggesting that a lack of knowledge about the 

19
opportunities that exist in the transportation industry may be a serious 

barrier to recruitment. In terms of vocational interest, the results of the 

study also suggest that people with an interest in conventional jobs, and 

that prefer highly ordered activities with little artistic or physical skill are 

most likely to choose a career in transportation. People who highly value 

career stability, but do not have strong preferences for geographic 

location, are also prime targets for recruitment into the transportation field. 

Colleges and universities should clearly be a target for recruiting people to 

the transportation field. However, more focused recruitment efforts, as 

well as increased advertising about transportation opportunities, is 

necessary in order to utilize this recruiting population to its fullest 

potential. 

Limitations: One limitation of the current study is that there is no indication of whether 

the participants included in the study have declared a major. The 18% of 

students who would consider a career in transportation may already be 

enrolled in a traditional transportation-related major. Thus, the necessity 

of introducing transportation to a more diverse range of students becomes 

even more important. There are also some limitations to the applicability 

of this study to the truck driving occupation in particular. Although 

recruiting directed at community colleges or trade schools may be 

successful, students at 4-year universities may be less likely to desire a 

career as a driver, opting instead to attain a position requiring a bachelor’s 

degree (e.g., in management or engineering). Nevertheless, it is clear that 

recruiting younger populations necessitates an increased effort to educate 

students about the breadth of opportunities available in the transportation 

industry and focused efforts to recruit students based on their career values 

and vocational interests. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #1: Driver Recruitment, as the researchers sought to 

assess perceptions of the transportation industry in an effort to refine 

existing recruiting strategies.

20
Motor Carrier Environment: Who is being recruited for CMV driver positions (and how)? 

Dobie, K., Rakowski, J.P., & Southern, R.N. (1998). Motor carrier road driver recruitment in a 

time of shortages: What are we doing now? Transportation Journal, 37, 5–12. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Driver Recruitment Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Driver Recruitment Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: No author abstract 

Industry Sector: TL and LTL trucking 

Purpose: The study is a follow up on a prior study of recruitment strategies 

conducted in 1989. This paper identifies changes in managerial 

perceptions of recruitment and recruitment strategies. The authors felt that 

a reassessment was necessary given the rapidly changing demographics, 

new regulations, and an increased emphasis on driver retention. 

Sample: 62 motor carriers responded to a survey mailed to 517 firms. 

Methodology: The study surveyed recruiters listed in the Traffic Management Directory 

of “Motor Carrier Services,” excluding local cartage companies. Motor 

carrier managers were asked to respond to demographic questions, current 

and past turnover rates, and the following four major questions from the 

original 1989 survey: 1) What did managers feel was most important to 

drivers when they selected a company for employment? 2) What forms of 

communication were used to reach potential drivers? 3) What incentives 

did managers stress when recruiting drivers? and 4) What were the preand post-employment training requirements for their firms? 

Relevant Findings: The top five incentives managers identified as being most important to 

drivers remained the same from 1989, and included pay, condition of 

equipment, time at home, carrier reputation, and health benefits. 

Equipment type, access to management, and pension were not included in 

the 1989 survey, but ranked sixth, seventh, and eighth, respectively, in the 

1996 survey. Firms are also diversifying their recruitment communication 

sources, using a mix of newspapers, magazines, word of mouth, 

advertising on company trailers, and driver training schools. The most 

frequently used source was word of mouth, with over 75% of the motor 

carriers sampled indicating that they used current employees as an avenue 

to recruit new employees. The use of newspapers declined from 1989 

21
levels, but magazine use dramatically increased from 10% to 45%, 

suggesting a trend toward the use of professional association publications 

as a beneficial recruiting source. Common incentives like pay and health 

benefits continue to be stressed by motor carriers during recruitment. Time 

at home made a dramatic jump in 1996 as a recruitment incentive, with 

over 80% of managers indicating that they stress time at home during the 

recruitment process (from 40% in 1989). Factors that may be of interest to 

drivers seeking long-term employment, such as training and advancement 

opportunities, were ranked last by managers. The majority of firms 

surveyed had minimum age requirements of 23 years and experience 

requirements of 2 years, but a small trend of declining age and experience 

requirements can be detected. 

Overall, there seems to be an increased emphasis on using current drivers 

and trade publications to attract new drivers. Incentives related to quality 

of life, such as health care and time at home, are also being more heavily 

marketed, in addition to pay, during the recruiting process. 

Limitations: The study cited in this article is now about ten years old. Given the 

changes that occurred over a seven year time period, it would be 

advantageous to re-administer the survey and document motor carrier 

recruiting practices of today. Changes in the motor carrier industry over 

the past ten years may have also triggered additional changes in recruiting 

practices. For example, the FMCSA has been established, driver training 

schools have grown dramatically, and the accessibility of the internet has 

provided an additional avenue for advertising. 

In addition, this study concentrates on management perceptions of factors 

deemed important to drivers. A more effective study might also directly 

survey the drivers. 

Categorization: This study fits within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #1: Driver Recruitment, because it 

summarizes the recruitment practices of 1996 for a sample of motor 

carriers and compares the results to those documented in 1989. 

22
Event 

Motor Carrier Environment: What criteria/applicant selection strategies are used as part of the 

hiring process? 

Jacobs, R.R., Conte, J.M., Day, D.V., & Silva, J.M. (1996). Selecting bus drivers: Multiple 

predictors, multiple perspectives on validity, and multiple estimates of utility. Human 

Performance, 9, 199-217. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Criteria for Selecting 

Drivers

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Criteria for Selecting 

Drivers

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: No author abstract 

Industry Sector: Transit bus industry in the U.S. and Canada 

Purpose: The purpose of this study was to develop and validate a reliable model for 

optimally selecting bus drivers for employment, and to show the utility of 

such a model in reducing transit property operating expenses. 

Sample: Job analysis survey: 309 bus operators; 62 supervisors in 9 transit 

properties across the U.S. (8 cities) and Canada (1 city). 

Predictor battery: 864 bus operators in 9 bus properties across the U.S. 

and Canada (8 of these properties also participated in the job analysis 

survey). 

Methodology: First, researchers performed a job analysis, using results of this activity to 

form a theory describing the job of a bus operator and operator 

performance. 

Subsequently, criterion measures were developed that corresponded to the 

theorized performance dimensions. Data collected to address these criteria 

consisted of property archival data regarding objective measures of driver 

performance (number of days of worker’s compensation and days absent; 

total number of accidents). Additionally, supervisors provided subjective 

driver performance ratings in areas of attendance, safety, and customer 

courtesy. 

A battery of questions reflecting job content was assembled based on 

results of the job analysis and academic literature review. Consultation 

23
with SMEs from an advisory panel representing the transit industry 

established the content validity of this predictor set. 

Predictor battery data collected from bus operators and a concurrent, 

criterion-related validity study allowed for an analysis of the relationship 

between the predictor data and objective and subjective measures of job 

performance. Based on these results, a predictor composite was formed. 

Finally, a utility analysis was conducted to estimate a cost savings to 

transit agencies using this composite for bus operator selection purposes. 

Relevant Findings: Based on the job analysis, researchers concluded that the job of a bus 

operator encompassed three performance dimensions: timeliness, safety, 

and courtesy to riders. The resulting selection model was derived from an 

inter-correlation matrix of all variables. This model was used in 

conjunction with a conceptual view of the predictor set of variables that 

encompass the job of a bus operator. It combined six predictor 

components containing biographical information relating to temperament 

and sense of timeliness, personality measures of conscientiousness and 

openness, and attitudes regarding safety and authority, into a predictor 

composite. The six predictor components were weighted equally and 

summed to calculate a composite score that reliably differentiated 

candidates and may be used for the purpose of selection. In addition, the 

composite score was significantly related to existing measures of objective 

performance criteria and subjective performance ratings. 

Content validity, established by SMEs, was bolstered by evidence of 

criterion-related validity. Significant correlations were obtained among 

supervisor performance ratings and scores on the composite for safety, 

courtesy, attendance, and overall performance criteria. The ability of the 

composite to accurately forecast objective job performance in terms of 

attendance and accident measures was also supported. Results indicated 

that use of the predictor composite provided an enhanced ability to select 

bus operators who will drive more safely, miss fewer workdays, and be 

viewed by supervisors as strong performers. 

Finally, a utility analysis was based on cost estimates for absences and 

accidents derived from discussions with managers at six different transit 

properties. Results suggest that use of the composite has the potential to 

reduce operating expenses related to accidents and absences by over 

$550,000 per year. 

Limitations: Selection of the most qualified and safety-conscious operators is only 

possible using this system if applicants buy into the process and are 

willing to provide the potentially sensitive personal data that is requested. 

Moreover, although this system may select the most desirable workers, 

once hired, intra-organizational factors such as culture and climate, have 

24
the rapid potential to influence safety and other behaviors. If these 

influences are negative, they could easily negate the system’s benefits. 

Categorization: This study fits within the event timeframe of the motor carrier 

environment for Haddon Matrix #1: Criteria for Selecting Drivers, because 

it proposes a selection strategy for hiring bus operators who are likely to 

display good job performance and be safety-sensitive. 

25
Post-event 

Driver Environment: What driver-related factors influence whether or not CMV drivers remain 

at a particular job and/or in the workforce? 

Gallup Organization. (1997). Empty seats and musical chairs: Critical success factors in truck 

driver retention. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Driver Turnover 

and Retention

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Driver Turnover 

and Retention

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: This study set out to do three things: (1) update the trucking industry and 

labor force demographic analysis from the 1988 Hudson Institute study; 

(2) provide a better understanding of the unique attitudes about trucking 

held by people both inside and outside the industry and the effect of these 

attitudes on personnel management; and (3) develop a retention model 

based on the factors that are most significant in promoting job satisfaction 

of long-tenured truck drivers—drivers who have been with their current 

company for five years or more. Principal findings are: (1) driver turnover 

continues to represent 80 percent of the trucking industry’s need for new 

drivers; (2) the workforce segment—males 20–24—that has been the main 

source for the trucking industry, will grow by an average of only 0.7 

percent per year between 1994 and 2005; (3) the population groups that 

show the greatest labor force growth are those that have not traditionally 

been drawn to trucking—women and minorities. [Reviewer note: this is 

the TRIS abstract; the author abstract is multiple pages.] 

Industry Sector: Trucking 

Purpose: An initial purpose of this study was to update demographic information 

previously obtained by the 1988 Hudson study in order to estimate labor 

pool size, and compare trucking industry growth with that of construction, 

an industry with which trucking competes. Additionally, researchers 

sought to gain a better understanding of public and industry perceptions of 

trucking, and how these attitudes affect turnover and retention. Data 

gathered from interviews with long-tenured truck drivers was used to 

create a model of job retention based on the job attributes that most 

significantly impact job satisfaction. 

26
Sample: 15 trucking company executives from different firms. 

1,000 adults in the continental United States. 

801 drivers who had been with their current company for 5 years or more. 

Methodology: For the first part of the study, researchers reviewed existing demographic 

and economic data from DRI/McGraw-Hill and Martin Labbe Associates, 

the US BLS, and the ATA from the time period of 1994 to 2005. 

Researchers conducted in-depth interviews with 15 executives from 

different trucking firms to extract information regarding how fleet 

company executives view driver shortage, turnover, and retention issues. 

Additionally, a random sample of adults in the US was polled to gain an 

understanding of public perceptions of truck drivers, and the industry as a 

whole. They were asked questions regarding whether their view of truck 

drivers was mostly positive, or mostly negative, as well as to rate different 

characteristics of truck drivers such as friendliness and independence. 

Researchers also interviewed long-tenured truck drivers (employed with 

the same company for five or more years) by phone to understand what 

aspects of their job led to increased satisfaction and commitment to their 

company. These drivers were selected based on the assumption that 

remaining at an organization for that long equates to relative satisfaction 

with the job. They were asked to rate their level of satisfaction on 21 job 

attributes. A subsequent data reduction analysis of these job attributes 

revealed 4 factors, conceptualized as: company support, non-driving 

activities and customer friendliness, hours of work and time with family, 

and work rewards. Factor groups, as well as the individual job attributes 

were then used in multiple regression analyses to determine which most 

reliably predicted driver satisfaction. 

Relevant Findings: Results of the initial review of available data from the US BLS and 

DRI/McGraw-Hill and Martin Labbe Associates confirmed the increasing 

need for qualified drivers through 2005. Based on freight volumes across 

numerous industry sectors and delivery modes, DRI, for example, 

estimated the truck population to grow by 13.4% (1.26% annually). 

Having combined the effects of industry growth and driver turnover, and 

assuming that these would remain stable, a need to hire 894,000 new 

drivers was estimated between 1995 and 2005. Given such projections, the 

authors sought to understand what specific factors lead to greater driver 

satisfaction and commitment so that trucking firms could potentially be 

better equipped to retain drivers. 

Most of the 15 trucking company executives who were interviewed stated 

that the current driver shortage was moderate to severe, and not as much a 

shortage of available candidates, as a dearth of qualified candidates. 

Additionally, 11 of the 15 believed that this problem was more severe than 

27
compared with 5 years prior to the study, in 1991. All agreed that the longhaul, full TL segment suffered most from the shortage of qualified drivers, 

likely as a result of the quality of life on the road and long periods of time 

away from home. 

Also noted was the shrinking demographic group (young, white males) 

from which drivers were typically recruited. Executives reported 

additional frustration regarding minimum-age requirements for their role 

in preventing companies from hiring directly out of school, so as to mold 

career drivers. Interestingly, here responses were evenly split when 

executives were asked about driver quality: half indicated that quality had 

improved over the past five years, half indicated that it had worsened, and 

one respondent reported no change. Responses paralleled those regarding 

the overall driver population when queried regarding their own drivers. 

Though executives reported believing that the public has an overall 

negative perception of truck drivers, instead, 80% of a random sample of 

US adults purported a positive view. Of characteristics rated for how well 

they described professional truck drivers, independence was rated the 

highest, with 93% of the sample reporting that this trait “definitely” or 

“probably” describes them. As independence is highly valued in American 

culture, such a public perception of truck driving should be capitalized 

upon when trying to recruit new drivers into the industry. Interestingly, 

although almost two-thirds (65%) of the sample agreed that “the industry 

needs to recruit more women drivers,” the two groups who least agreed 

with this statement were persons 55 and older, and women themselves. 

The authors suggest that this may equate to substantial resistance from 

women when attempting to recruit them into the trucking industry. 

With regard to the satisfaction and commitment of long-tenured drivers, as 

expected, researchers found that 86% of their sample were either “very 

satisfied” or “somewhat satisfied” with trucking as an occupation, and the 

longer the tenure, the more satisfied drivers tended to be. Of interest, 

though in the public sample, women appeared to resist the idea of a career 

in the trucking industry, long-tenured female drivers reported greater job 

satisfaction than their male counterparts (59% of the women drivers 

reported being “very satisfied” compared to 42% of the male drivers). 

An additional aspect of surveying the long-tenured drivers was to obtain 

information regarding their level of job commitment, as this strongly 

relates to retention. Though satisfaction was found to be very high, 

commitment to the job was not as strong. Compared to the 86% who 

reported being “very” or “somewhat satisfied” with truck driving, only 

63% said they would “definitely” or “probably” choose it as an occupation 

again. Additionally, only 44% responded that they would “definitely” or 

“probably” recommend trucking to their family and friends. Similar to the 

28
higher ratings for satisfaction, women were also significantly more likely 

to say they would choose trucking as an occupation again. This finding, in 

conjunction with the increased satisfaction reported by female drivers, 

suggests that recruitment of females could be vital to the trucking industry. 

Finally, the 21 job attributes, as subsequently collapsed into 4 categories, 

were rated by the long-tenured drivers using a 5-point scale ranging from 

“very dissatisfied” to “very satisfied.” Multiple regression analyses using 

the four factors evidenced the largest increases in overall job satisfaction 

as a result of improving in the areas of company support (39%; e.g., 

“friendliness of managers”) and work rewards (32%; e.g., “steadiness of 

the work”). Of lesser importance were the hours of work and time with 

family factor (20%; e.g., “time spent on the road”) and the non-driving 

activities and customer friendliness factor (9%; e.g., “amount of physical 

loading and unloading have to do”). The job attributes were also each 

separately analyzed to determine the most important specific predictors of 

overall job satisfaction. This analysis revealed “steadiness of the work,” 

“genuine care of managers,” “pay,” “support from company while on the 

road,” and “hours of work,” respectively, as the top five predictors of 

overall satisfaction. 

Limitations: The results from the survey on long-tenured drivers evidenced a high level 

of satisfaction with trucking, paired with a lesser level of reported 

commitment to the job; however, the study did not seek parallel 

information from drivers with shorter tenure at organizations. As driver 

turnover is extremely common in trucking, resulting often in short 

successions of brief organizational tenure, research in this area should be 

considered in conjunction with the current findings. Additionally, the 

findings of this study are now 10 years old, and are, thus, likely in need of 

updating. 

Categorization: This paper fits within the post-event timeframe of the driver environment 

for Haddon Matrix #1: Turnover and Retention, as the researchers 

investigated aspects of truck driving that lead to increased job satisfaction 

in an effort to increase driver retention. 

29
Kalnbach, L., & Griffin, G. (2002). Predicting and classifying voluntary turnover decisions for 

truckload drivers. National Transportation Library (U.S. Department of Transportation). 

(NTIS No. PB2003-102189) 

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Turnover 

and Retention

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Turnover 

and Retention

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: Voluntary turnover rates among truckload carriers are extremely high, 

ranging from 50% to more than 100% annually. These high turnover rates 

result in elevated costs for carriers in terms of recruitment and training as 

well as costs associated with reduced productivity and decreased customer 

satisfaction resulting from inexperienced drivers. Although much research 

has been conducted to determine the relationship between job satisfaction 

of drivers and the likelihood of them leaving or intending to leave an 

organization, research addressing other reasons why drivers leave their 

organizations has been lacking. As a result, this project was designed to 

increase understanding of voluntary turnover of drivers. 

To accomplish this objective, written surveys were used to gather data 

from drivers. Surveys were completed by drivers at two different times 

during the study. The first survey, assessing personal and situational 

characteristics, was completed by applicants for the job of driver during 

the hiring process. The second survey was distributed only to those drivers 

who quit their jobs during the study in order to ascertain how they made 

their decisions to leave their organizations. Although the actual number of 

drivers that completed both surveys was very small, analyses were 

conducted to determine how those that left the organization compared to 

those who stayed with the organization. Results and recommendations are 

provided in subsequent sections of this report. 

Industry Sector: Trucking 

Purpose: The authors used the unfolding model of turnover, developed by Lee and 

Mitchell (1994), to classify and characterize reasons why truck drivers 

voluntarily choose to leave their jobs. The unfolding model of turnover is 

characterized by four decision paths that may explain why people choose 

to quit their jobs. The first three paths involve a shock component, defined 

as a “jarring event that initiates the psychological analyses involved in 

quitting” (p. 4). 

30
Path 1 involves a shock followed by the enactment of a pre-existing script 

(i.e., planned or automatic behaviors based on past experience in similar 

situations) without consideration for alternatives. 

Path 2 involves a shock that prompts feelings of image violation, where 

the person reconsiders his/her attachment to the organization, and 

alternative job options are not considered before the decision to quit is 

made. 

Path 3 again involves a shock and image violation; however, the person 

chooses to search for alternatives prior to leaving the organization. 

Paths 4a and 4b involve the decision to turnover due to a gradual feeling 

of dissatisfaction, without the existence of a specific “shock” event. Path 

4a is dissatisfaction without consideration for alternatives, whereas path 

4b is defined as dissatisfaction leading to a search for alternative 

opportunities before deciding to leave the organization. 

It was hypothesized that: 1) people receive scores on psychological 

measures indicating a low level of conscientiousness, a high level of risk 

taking, and high level of openness to experiences will be more likely to 

leave an organization without considering alternatives, thus taking paths 1, 

2, or 4a; 2) people who report more responsible behavior in the past (e.g., 

longer tenure, more work experience) will be more likely to seek 

alternatives before quitting, thus following paths 3 or 4b; 3) people who 

have voluntarily left jobs in the past are more likely to follow path 1 and 

use a script for leaving the organization; 4) people who perceive there to 

be many alternatives to their jobs in general will be less likely to search 

for alternatives before quitting (paths 3 or 4b) than their counterparts who 

perceive there to be fewer alternatives; 5) low perceptions of fit will lead 

to more quit decisions due to general dissatisfaction (paths 4a or 4b) than 

due to a specific shock event (paths 1, 2, or 3). 

Sample: The first survey collection included 804 new-hire truck drivers at U.S. 

motor carriers (i.e., Schneider National, Barr Nunn, C.R. England, M.S. 

Carriers). Only 37 out of the 247 drivers who left the organization in their 

first six months of employment completed the second survey. 

Methodology: Newly hired drivers were asked to complete a survey as part of their initial 

paperwork. Turnover data were gathered from organizational records for 

six months after the initial survey distribution. Truck drivers who chose 

the leave the organization in that time period were given a second survey 

assessing their reasons for quitting. The second survey was mailed to their 

homes to ensure confidentiality. Turnover decisions described in the 

second survey were classified into one of the five decision paths (where 

possible) using the methodology developed by Lee et al. (1999). 

31
Relevant Findings: Researchers were unable to classify 7 of the 37 turnover decisions 

described in the second survey. Out of the 30 classifiable decisions, 13 

followed path 3, which is a shock prompting feelings of image violation, 

followed by the consideration of possible job alternatives before leaving 

the organization. Also, drivers who left the organization reported lower 

levels of conscientiousness and more work-related skills than those who 

chose to stay with the organization. 

The small sample size obtained in the second survey precluded the use of 

statistical analyses to test the proposed hypotheses. Percentage 

comparisons did indicate marginal support for hypotheses 1, 2, and 4. 

Qualitative analyses from the second survey also indicate that many of the 

drivers who chose to quit felt that they had been misled about various 

aspects of the job (e.g., amount of pay, time at home, and driving routes) 

and that the organization failed to keep promises made when the drivers 

were hired. Four drivers also indicated concern about the quality of 

training they received. Better communication during the hiring process 

and improved training may go a long way to improve driver retention. 

Limitations: Due to the small sample size obtained in the second survey and the 

inability to classify the turnover decisions of 18% of the truck drivers who 

did respond, the results should be interpreted with caution. Furthermore, 

this study only sampled truck drivers who quit within the first six months 

of hire, making it difficult to generalize to the much larger population of 

drivers who quit after that period. However, there is still a strong 

indication that drivers who decide to quit due to a shock and image 

violation often explore alternative opportunities before quitting, 

suggesting that there is a window of time when the organization may be 

able to intervene and attempt to remediate the image violation, reducing 

the likelihood that the driver will decide to quit. Future research is 

necessary. 

Categorization: This paper fits within the post-event timeframe of the driver environment 

for Haddon Matrix #1: Driver Turnover, as the focus of the article was the 

five potential paths that lead drivers to voluntarily quit a company. 

32
Kalnbach, L.R., & Lantz, B.M. (1997). The effects of optimism and willingness to trust on workrelated attitudes and behaviors: An application to the commercial vehicle industry (MPC 

Publication No. 97-75). Mountain-Plains Consortium. (NTIS No. PB97-190748) 

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Turnover 

and Retention

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Turnover 

and Retention

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: The main objective of this study was to explore the determination of 

commercial vehicle driver attitudes and the effect of these attitudes on 

driving performance, job satisfaction, and turnover. It was hypothesized 

that if a relationship is found, it may then be worthwhile to select 

applicants with the highest potential for good work habits and company 

loyalty. 

Previous research was reviewed to help define measures of trust, 

optimism, organizational commitment, job satisfaction, intent to turnover, 

and commitment to work. Productivity measures included miles driven, 

out-of-route percentage, late deliveries, and accidents. 

Optimism and trust measures were obtained over a two month time period 

from 584 new drivers from a national trucking company. Turnover of 

these drivers was measured four months later. The drivers still with the 

company were sent a second survey to obtain the additional job-related 

measures. At the same time, productivity measures for these drivers were 

obtained from the company. 

Results showed moderate support for the stated hypotheses. There is some 

credibility to using measures of trust and optimism in the selection 

process. Other measures in the study also could help to predict intent to 

turnover. A discussion and explanation of the results is given. 

Industry Sector: Trucking 

Purpose: The purpose of the study was to examine trust and optimism as global 

personality characteristics that may relate to positive work attitudes and 

work behaviors. 

Sample: Initial sample—584 newly-hired truck drivers working for a national 

motor carrier in the initial sample. 

After four months, 103 of the remaining 326 drivers completed the second 

survey (31.6% response rate). 

Methodology: The researchers surveyed new drivers from a national trucking company 

during their initial training period. The survey included measures of 

33
willingness to trust, optimism, and demographic characteristics. 

Willingness to trust was measured using 25 items from the Interpersonal 

Trust Scale (ITS; Rotter, 1967). Respondents were asked to rate the extent 

to which they agreed or disagreed with statements such as, “Most people 

can be counted on to do what they say they will do,” using a 1–5 point 

scale where 1 equaled “strongly agree” and 5 equaled “strongly disagree.” 

Optimism was measured using the eight-item Life Orientation Test 

(Scheier & Carver, 1985). Statements such as, “I am always optimistic 

about my future” were rated on the same 1–5 scale. 

Four months later, a second survey was distributed to those truck drivers 

who remained with the company. The second survey asked about drivers’ 

organizational commitment (e.g., “I really care about the fate of this 

organization”), intent to turnover (e.g., “I will probably look for a new job 

in the near future”), job satisfaction (e.g., “I am satisfied with my current 

job in this company”), and commitment to work (e.g., “What I do at work 

is more important to me than the money I earn”). Driver productivity and 

accident rates were recorded from company data gathered for drivers who 

stayed with the company. Actual turnover was recorded for drivers who 

participated in the first survey, but quit in the four months before the 

second survey. 

Relevant Findings: Willingness to trust and optimism were not significantly correlated with 

job satisfaction or other job-related attitudes. However, job satisfaction 

was correlated with organizational commitment and intentions to leave the 

company. Drivers reporting greater job satisfaction also reported being 

more committed to the company and were less likely to have considered 

quitting. Furthermore, trust significantly predicted actual turnover such 

that drivers who reported a greater willingness to trust were more likely to 

have stayed with the company after four months. There were no 

significant relationships between driver characteristics and accident rates. 

Limitations: Although this study utilized self-report data measured at different time 

points, there is some question about the reliability of the measures used. 

The measures of optimism and commitment to work demonstrated internal 

consistencies below 0.70, the typical cut-off score used to establish 

reliability. Furthermore, job satisfaction was measured using a single item 

indicator. The sample used in the current study consisted entirely of entrylevel truck drivers. It is unclear whether the results obtained would 

generalize to more tenured truck drivers, or whether the results would 

remain consistent if the period between the initial and follow-up survey 

was longer than four months. Willingness to trust may contribute to 

explaining why newly hired truck drivers’ turnover within the first four 

months of working for a company, but may not be a contributing factor 

when more tenured employees choose to leave their company. 

34
Categorization: This paper fits within the post-event timeframe of the driver environment 

for Haddon Matrix #1: Driver Turnover, as the authors identified trait 

characteristics they felt would have an impact on driver turnover rates.

35
Lauver, K.J., & Kristof-Brown, A. (2001). Distinguishing between employees’ perceptions of 

person-job and person-organization fit. Journal of Vocational Behavior, 59, 454–470. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Employee Fit Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Employee Fit Driver

Environment

Pre-Event Event Post-Event

Author Abstract: This study examines the relationship between employees’ perceptions of 

person-job (P-J) and person-organization (P-O) fit. Survey data was 

collected from 231 employees (104 office personnel and 127 drivers) of a 

national trucking company show a low correlation (r = .18) between the 

two types of self-reported fit. Both P-J and P-O fit had a unique impact on 

job satisfaction and intent to quit. P-O fit was a better predictor of 

intentions to quit than was P-J fit, but there was little difference in their 

relative influence on job satisfaction. The predicted positive relationship 

between perceived P-O fit and contextual performance (extra-role 

behaviors an employee performs beyond those prescribed in their job 

description) was also supported. No relationship was found between 

perceived P-J fit and task performance. Taken as a whole, these results 

provide further evidence that employees’ perceptions of P-J and P-O fit 

should be treated as distinct constructs. 

Industry Sector: Trucking 

Purpose: The purpose of the current study was to examine the differential 

contributions of perceived P-J and P-O fit as predictors of job satisfaction 

and performance. The authors defined P-J fit as “the match between the 

abilities of a person and the demands of a job” (p. 455). Whereas P-O fit 

was defined as “the compatibility between people and organizations that 

occurs when at least one entity provides what the other needs, they share 

similar fundamental characteristics, or both” (as cited in Kristof, 1996, pp. 

4–5). In summary, P-J fit refers to a person’s compatibility with a job, and 

P-O fit concerns the match between a person and the organization’s 

values, goals, and mission. 

Sample: 231 employees of a large national trucking company (15% of the total 

number of employees in the trucking company): 104 office personnel and 

127 truck drivers. 

Methodology: The researchers conducted a survey with office workers and truck drivers 

of a national trucking company. Perceived P-J fit was measured by asking 

participants to respond to five statements concerning their fit with the job 

36
in terms of skill and personality/temperament (e.g., “There is a good 

match between the requirements of this job and my skills”). Perceived P-O 

fit was measured using three items asking participants about the fit 

between their personal values and the values of the organization (e.g., “My 

values match or fit the values of this organization”). Employees also 

responded to statements measuring job satisfaction and intent to quit. 

Contextual performance data was gathered using peer ratings of perceived 

performance and task performance data was obtained from performance 

appraisal records for office workers, and company records on average 

miles traveled per month and number of accidents per 10,000 miles 

traveled for truck drivers. 

Relevant Findings: Findings suggest that perceived P-O and P-J fit are both positively related 

to job satisfaction and negatively related to intent to quit. Additionally, PO fit had a significantly greater impact on intentions to quit than did P-J 

fit. P-O fit was also significantly related to contextual performance (i.e., 

peer ratings of performance), suggesting that greater perceptions of 

organizational fit are related to peer ratings of engagement in extra-role 

behaviors (e.g., volunteering to carry out extra activities and 

helping/cooperating with others). Disappointingly, the hypothesized 

relationship between perceived P-J fit and task performance was not 

supported. 

Limitations: One major limitation of the current study is the low response rate (15%) 

obtained from the trucking company. Although there were no significant 

demographic differences between respondents and the profile of the 

average worker employed within the company, there could still be 

potential for self-selection bias such that only employees with extreme 

positive or negative attitudes chose to participate. In addition to the low 

response rate, there was an extremely low sample size obtained for the 

peer-rated contextual performance data (n=47). The small sample size 

calls into question the generalizability of these results. Thus, the 

relationship between P-O fit and contextual performance should be 

reviewed as preliminary and in need of replication before solid 

conclusions may be drawn. 

In light of the focus of the current literature review, the lack of a 

significant relationship between job fit and task performance was 

disappointing, as the measure of truck driver task performance included 

accident rates. However, there is some concern that range restriction for 

the measure of job fit may have contributed to the lack of a significant 

finding. The average level of perceived job fit was extremely high, with a 

mean of 6.22 on a seven point scale and a low standard deviation of 0.86, 

suggesting that most drivers reported their skills and temperament as an 

extremely good match to the job of a truck driver. Future research should 

include testing and validation of the measures of perceived P-O and P-J fit 

37
before reexamining the relationship between perceived fit and 

performance. 

Categorization: This paper fits within the post-event timeframe of the driver environment 

for Haddon Matrix #1: Employee Fit, as the focus of the article was on P-J 

and P-O fit, and how they relate to job satisfaction and performance.

38
Richard, M.D., LeMay, S.A., & Taylor, G.S. (1995). A factor-analytic logit approach to truck 

driver turnover. Journal of Business Logistics, 16, 281. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Turnover 

and Retention

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Turnover 

and Retention

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: No author abstract 

Industry Sector: TL trucking 

Purpose: The purpose of this study was to find a practical solution to give motor 

carrier management a better understanding of driver turnover. 

Sample: 402 out of 1,500 irregular route truck drivers employed by a U.S. motor 

carrier (26.8% response rate). 

Methodology: Researchers conducted a survey of TL drivers within a single motor 

carrier. Using a scale from 1 to 5, drivers were asked to rate their job 

satisfaction as well as firm characteristics such as pay, managers, 

dispatchers, other drivers, and time at home. These responses were used as 

independent variables. Drivers were also asked to rate their likelihood of 

leaving the company in the near future. The answer was used as the 

dependent variable. Respondents were thus classified into two groups: 

those likely to leave the company, and those likely to remain. Survey 

results were analyzed using a combination of logit and factor analysis. 

Relevant Findings: The authors found that a driver’s attitudes towards management, 

dispatchers, and other companies are significant factors in determining 

intentions to leave their current employer. Drivers who evaluated 

dispatchers and management in a positive way were more likely to remain 

with their company. Conversely, drivers who did not perceive any major 

differences between the policies and managerial attitudes at their own or 

other trucking companies were more likely to leave their current 

employer, even as a result of minor irritants. Drivers who perceived all 

trucking companies as treating drivers the same, good or bad, had little 

motivation to remain loyal to their current employer. The authors 

recommend realistic job previews (RJPs) that set reasonable expectations 

about managers and dispatchers, and, in doing so, distinguish the company 

as honest and fair. Recruiter and dispatcher training are recommended to 

teach supervisory and human relation skills. To retain drivers, motor 

39
carriers need to maintain open communication with drivers about their 

perceptions of the effectiveness of management policies and activities. 

Limitations: The survey was only distributed to drivers from one large TL carrier. 

Thus, the data may not be generalizeable to other, smaller companies. 

Categorization: This paper fits within the post-event timeframe of the driver environment 

for Haddon Matrix #1: Driver Turnover, because it models drivers’ choice 

to leave or stay with a motor carrier. 

40
Stephenson, F.J., & Fox, R.J. (1996). Driver retention solutions: Strategies for for-hire truckload 

(TL) employee drivers. Transportation Journal, 35, 12-25. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Turnover 

and Retention

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Motor Carrier 

Environment

Driver Turnover 

and Retention

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: No author abstract 

Industry Sector: For-hire TL trucking 

Purpose: Voluntary driver turnover is a major problem for trucking companies since 

the economic deregulation of the industry in 1980. The purpose of this 

study was to provide retention strategies for employee drivers (as opposed 

to contract drivers) to firms in the TL for-hire trucking sector, as this 

sector suffers from the highest driver turnover rate. 

Sample: 1,464 employee drivers from 57 for-hire TL firms. 

Methodology: A four-page survey was mailed to carriers for distribution to a portion of 

drivers in each organization. Drivers were asked why they chose driving 

as a profession, about job and demographic information, and regarding 

factors important to them in their decisions to leave or stay with an 

employer. Importance-ratings for 37 items were made using seven-point 

scales. These data were then analyzed using a statistical technique to 

establish which groups of survey items were most closely related and in 

order to form groups for the purposes of comparing ratings. 

Relevant Findings: Overall, drivers identified compensation as the most important reason for 

deciding to remain with their current employer, although drivers reporting 

a higher annual income were more likely to report working a greater mean 

number of hours per week. This was followed by pride in one’s company 

and the profession, and factors regarding fair job treatment and worker 

appreciation. Aspects related to safety/security and equipment, and finally 

working conditions, were of lesser importance. 

Based on these results, the authors advocate an increase in annual gross 

pay levels, or a reduction in hours (to increase pay per hour), and the 

creation of a corporate culture built around employee appreciation and 

communication. 

41
Limitations: Although 79% of questionnaires were returned and usable, the sampling 

strategy chosen by the authors attempted to survey only approximately 9% 

of each company’s employees. The authors acknowledge that their sample 

is not random, but do not specify even whether there was a prescribed 

methodology for use by each carrier to distribute questionnaires. 

Additionally, data were collected in 1995, which potentially dates this 

study’s findings. 

Categorization: This paper fits within the post-event timeframe of the driver environment 

for Haddon Matrix #1: Driver Turnover, as the focus is on driver attitudes 

regarding their job and the decision to stay or leave their current employer. 

42
Motor Carrier Environment: What organizational factors influence whether or not CMV drivers 

remain at a particular job and/or in the workforce? 

Griffin, G., Kalnbach, L., Lantz, B., & Rodriguez, J. (2000). Driver retention strategy: The role 

of a career path (UGPTI Publication No. DP-135). North Dakota State University. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Retention Strategies Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Retention Strategies Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: The voluntary turnover rate among truckload carriers, at 50-100%, is 

excessive when compared to other industries. The turnover rate has been 

known to exceed 150%. It is believed that several factors are involved in 

this retention problem suggested by anecdotal evidence coupled with 

human resource management theory. One factor that contributes to such a 

high turnover rate is the lack of a meaningful career path for drivers. This 

has been identified in several studies of job satisfaction conducted at the 

Upper Great Plains Transportation Institute, North Dakota State 

University, and elsewhere. 

The purpose of this study was to evaluate (1) how the motivating potential 

for this job compares with other industries, (2) how much drivers agree 

with the components of the hypothetical career path, (3) how likely a 

career path or developmental opportunities is to improve 

retention/commitment, and (4) how drivers and managers differ in terms 

of their perceptions of realistic career paths. From this information and 

analysis, truckload firms can determine what drivers’ career path needs are 

and identify potential strategies that they can implement to meet those 

needs. 

The initial part of the study identifies a hypothetical career path based on 

theories of industrial psychology. This is followed with an in-depth 

analysis of what drivers’ perceptions are of a career path that would 

improve job satisfaction. A final component of the study will identify 

management’s perceptions of what a career path should consist of. This 

information is evaluated and synthesized into this report with conclusions 

and recommendations. 

Industry Sector: TL trucking 

Purpose: The primary goal of the current study was to determine whether the job of 

a TL driver would be enriched by the implementation of a career path. The 

43
authors used the Hackman and Oldham (1980) Job Characteristics Model 

to assess whether a career path would be of value to truck drivers by 

encouraging job enrichment, or making the job more personally rewarding 

and satisfying. The underlying assumption of the Job Characteristics 

Model is that employees who find their work rewarding and satisfying will 

tend to stay with their organization longer, thus improving retention. In 

addition, the Job Characteristics Model suggests a cause and effect chain 

reaction, whereby the way the work is designed triggers the driver’s 

psychological experience, which produces positive personal outcomes, 

and thereby results in improved employee effectiveness. 

Sample: First survey: 3,811 drivers from 11 different trucking companies were 

mailed questionnaires—736 drivers responded (response rate of 19.3%). 

Second survey: managers and decision makers from 191 trucking 

companies who were members of the Truckload Carrier Association—113 

managers responded (59% response rate). 

Methodology: Measures from the Job Diagnostic Survey (Hackman & Oldham, 1980) 

were included in the first questionnaire to assess driver perceptions of 5 

core job characteristics (skill variety, task significance, task identity, 

autonomy, and feedback), 3 critical psychological states (meaningfulness, 

responsibility for outcomes, and knowledge of the results), and 4 work 

outcomes (internal work motivation, growth satisfaction, general job 

satisfaction, and work effectiveness). In addition, questions asking about 

drivers’ perceived knowledge and skills, need for personal growth, and 

satisfaction with specific aspects of their job were included to assess 

whether drivers would be receptive to job enrichment. 

In order to trigger the positive chain reaction described in the Job 

Characteristics Model, the way the work of a driver is designed must have 

the motivating potential to benefit from the addition of a career path. The 

five core job characteristics mentioned above are all factors necessary for 

job enrichment, as determined by calculating a motivating potential score 

(MPS). The MPS for truck drivers was calculated by taking their average 

value for skill variety, task significance, and task identity, and then 

multiplying that by the value for autonomy and the value for feedback. A 

high MPS would indicate that truck drivers may be receptive to the 

introduction of a career path that would promote job enrichment. 

The authors also developed a hypothetical career path for truck drivers in 

order to ascertain how drivers would actually react to the proposed career 

path. The hypothetical career path includes two major stages. The first 

stage focuses on the development of core driving skills and knowledge 

through driving experience. Stage one incorporates four levels of 

promotion on the career ladder, from an “undergraduate driver” at hire to 

44
an “advanced driver” after a minimum of three years of experience. Stage 

two involves taking on greater responsibility and more involvement with 

the company by encouraging truck drivers to increase their business 

knowledge and take on additional job responsibilities such as training, 

safety management, customer service, or equipment maintenance. Stage 

two allows for advancement to the title of “senior driver” and later, 

“master driver.” Additional questions asking specifically about drivers’ 

opinions of the hypothetical career path were also included in the first 

survey. 

Finally, a second survey was administered to a sample of managers and 

decision makers in the trucking industry in order to compare truck driver 

perceptions of their job to the perceptions of management. Many of the 

same questions used in the first survey were included in the second 

survey; however, the wording was modified to reflect managers’ 

perceptions of drivers’ attitudes. 

Relevant Findings: Results suggest that a majority of truck drivers describe the core job 

characteristics of their job in positive terms. When compared with 

normative data from other job families, the MPS score for truck drivers 

was equal to that of management, and exceeded scores in other job 

families such as clerical, processing, and bench work. This suggests that 

the job of truck driving has high motivating potential and may benefit 

from the implementation of a career path. 

However, there were mixed results when drivers were asked about 

feedback they receive from their supervisors. Over 40% of drivers 

reported that they never get feedback from their supervisors and that 

supervisors do not let them know how they are performing, with most, if 

any, feedback received being negative. When asked about personal 

feelings regarding their job (psychological states), drivers also responded 

positively. On the other hand, almost 30% of drivers sampled also 

indicated that they think about quitting their job, with the majority of those 

30% being more experienced, tenured drivers. Thus, the problem of 

retention may not be limited to only younger drivers with less experience 

and less tenure in a trucking company. It is somewhat troubling that nearly 

a third of the sample indicated that they think about quitting their current 

job, even though they feel positively about other aspects of their job. This 

result, however, is not surprising given the high turnover percentages 

among trucking companies. 

A vast majority of drivers, ranging from 80 to 90%, also reported a strong 

desire for a sense of worthwhile accomplishment in their work, 

opportunities to learn new things, stimulating and challenging work, and 

opportunities for personal growth and development. The positive results 

45
indicate that drivers would be receptive to additional opportunities for 

enrichment in their job. 

When asked specifically about the hypothetical career path outlined by the 

authors, 70% of the drivers indicated that implementing such a career path 

would make them feel better about their job. Eighty-seven percent of 

drivers also agreed that the career path should be performance-based, 

rather than based on time with the company. 

Manager perceptions of the characteristics of the job of a truck driver were 

very similar to driver perceptions, indicating a good understanding 

between drivers and managers of what the job entails. However, managers 

underestimated the motivating potential of the job, suggesting that they are 

not entirely aware of truck drivers’ reported desire and need for personal 

growth in the job. Although the results indicate that the implementation of 

a career path would be beneficial to truck drivers, the career path may not 

be successful in promoting job enrichment without buy-in and backing 

from management. 

Overall, truck drivers reported feeling positively about their jobs, but may 

lack a desired level of feedback from supervisors and opportunities for 

personal growth. Implementing a career path for truck drivers may be a 

way to make the work of a driver more personally rewarding and 

satisfying. Tying the career path to performance may also increase 

effectiveness and allow more recognition for drivers that perform their job 

effectively and safely. Part of the retention problem in the industry may 

stem from a lack of opportunities for job growth combined with a lack of 

recognition from management concerning the need for job enrichment in 

truck driving. 

Limitations: This study is only a first attempt to assess whether there is a need and a 

desire for the implementation of a career path for truck drivers. Although 

the potential does appear to exist, the actual career path has yet to be 

implemented and studied. Likewise, it is still unclear whether such a 

system would pay for itself. Thus, the organizational costs and benefits 

need to be examined further. 

Categorization: This paper fits within the post-event timeframe of the motor carrier 

environment for Haddon Matrix #1: Retention Strategies. The purpose of 

the article was to test whether having a defined career path would lead to 

greater driver retention. 

46
a

Gupta, N., Jenkins, G.D., & Delery, J.E. (1996). Motor carrier effectiveness: A study

personnel practices, driver turnover, and company effectiveness in the trucking industry. 

University of Arkansas, Fayetteville. 

 of 

b

Shaw, J.D., Delery, J.E., Jenkins, G.D. Jr., & Gupta, N. (1998). An organization-level analysis 

of voluntary and involuntary turnover. Academy of Management Journal, 41, 511–525. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Driver Turnover 

and Retention

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Driver Turnover 

and Retention

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: aNo author abstract 

 bAlthough there are many individual-level models of turnover, little 

research has examined the effects of human resource management 

practices on quit rates and discharge rates at the organizational level. This 

study used organization-level data from 227 organizations in the trucking 

industry to explore this issue. Results show that human resource 

management practices predict quit rates and discharge rates but that the 

determinants of each are quite different. Implications are derived and 

directions for future research suggested. 

Industry Sector: TL and LTL trucking 

Purpose: aDriver turnover (in particular, voluntary turnover) has been a substantial 

problem in the trucking industry since deregulation took place in 1980. As 

a means of helping to guide HR decisions, this report provided a 

comprehensive, largely descriptive, assessment of the practices used by 

motor carriers to recruit, hire, and motivate their drivers. Researchers 

focused on the effects of HR practices on turnover rates, and also 

considered the additional outcomes of performance and safety. 

 bThis study used a subset of respondents from the Gupta, et al. sample to 

investigate, in greater detail, the relationship of HRM practices in trucking 

organizations to voluntary and involuntary turnover. Distinction was 

sought between these two types of turnover, the HRM practices that 

predict each, and the interaction of selection procedures and selection ratio 

as a predictor of discharge. The study was also conducted to address a 

perceived gap in the organizational sciences literature, as most studies 

focus on individual- as opposed to organizational-level predictors of 

turnover. 

47
Sample: a379 HR managers at trucking companies. 

 b227 HR managers at trucking companies who also provided turnover rate 

data. 

Methodology: a

HR managers from trucking organizations with a minimum of 30 

company drivers, as listed in the 1993–94 TTS Blue Book of Trucking 

Companies, completed a survey requesting information regarding the 

nature of their HRM systems as pertaining to their driver workforce. The 

survey was sent to an initial sample of 1,072 qualifying companies. The 

resulting sample contained a subset of companies whose managers 

returned completed surveys. 

 bShaw et al. further narrowed the Gupta, et al. sample to include only 

those companies that also provided turnover rate data. As Shaw et al. 

expanded on the findings of Gupta et al., they reported additional 

statistical detail: analyses were performed to ensure that groups of survey 

scale items each explained a sufficient percentage of unique variance and 

were adequate in terms of their reliability. The authors used HRM 

variables selected based on previous literature in analyses to predict both 

voluntary and involuntary turnover, expecting that those practices related 

to one type of turnover would not be related to the other (i.e., that their 

theoretical framework discriminated between the two). 

Relevant Findings: a

After statistically controlling for carrier type, lower quit rates were 

associated with being home more times per month (as is the case for LTL 

drivers), higher pay, more attractive benefits, job security, less on-board 

technology, and smaller and older companies. Smaller and older 

companies (those that have been in operation longer) were also associated 

with lower discharge rates. The greatest determinant of discharge rates, 

however, was selection ratio. Motor carriers using a low selection ratio 

(i.e., hiring few drivers based on many applicants), as well as employing 

selection techniques that included performance tests and/or technical 

knowledge tests (as opposed to unstructured interviews) were found to 

have the lowest discharge rates. Driver turnover was reported by HR 

managers to “hurt” driver accident rates (30.1%) and profits (39.5%), 

among other checklist factors. 

Safety factors were broadly reported as “potentially affected by driver 

behaviors.” Reported driver behaviors included accident frequency ratio, 

traffic violations per driver, equipment violations per truck, and driver 

absenteeism rate. 

Reported driver compensation and benefit policies established that TL 

firms offer lower pay rates than LTL firms, giving potential insight into 

the higher quit rates for TL drivers. Additionally, longer tenure at a 

48
company garners higher pay; however, incentive systems and 

compensation innovations to bolster wages were not often reported. The 

authors suggest that motor carriers link financial incentives to desirable 

driver behaviors, such as safe driving records. Although it costs companies 

financially to do so, these costs must be weighed against the costs of high 

turnover, including necessitating the hire of inexperienced drivers, who 

may be a greater safety risk. 

Finally, other HRM practices, such as staffing and training were 

discussed. Recruitment did not appear to be of primary concern to 

respondents, despite a perceived shortage of applicants. Newspaper 

advertisements and walk-ins were cited as the primary sources for new 

drivers. The authors indicate that alternatives, such as radio and television, 

should be given greater consideration. No systematic relationship was 

evidenced between the amount of training respondents reported and 

financial performance outcomes, quit, or discharge rates. In addition, the 

type of training (e.g., safety, on-the-job, simulator) was not a factor. 

 bThis research focused specifically on the turnover data from the Gupta, et 

al. report and carried out further statistical analyses. Results of this study 

confirmed that it is important to distinguish between involuntary and 

voluntary turnover. Reported driver quit rates were over four times greater 

than reported discharge rates, indicating that voluntary turnover is a much 

bigger problem in the industry than involuntary turnover. 

Additionally, different HRM practices predicted the two different turnover 

types. Investment-focused HRM strategies (e.g., pay, benefits) and 

employer expectations (e.g., time on the road, use of electronic 

monitoring) predicted voluntary, but not involuntary turnover. Staffing 

practices (e.g., selection ratio) predicted involuntary, but not voluntary 

turnover. 

Examining individual variables, HRM-investments in pay and benefits 

were negatively related to quit rates, while employer expectations (time on 

the road, electronic monitoring) were positively related to quitting. Also, 

involuntary turnover was positively related to selection ratio, indicating 

that a more conservative approach to hiring is associated with lower 

discharge rates. Despite predicting that electronic monitoring would also 

be related to involuntary turnover, since this technology may give 

employers better information on which to base discharges, no relationship 

was found. 

An interaction resulted between selection procedures and selection ratio 

for discharge rates. This relationship suggested, as one would expect, that 

discharge rates are low when there is high use of valid selection 

procedures combined with a favorable (low) selection ratio. Selection 

49
procedure validity was established by the authors based on a review of 

meta-analytic or validity generalization studies, if a validity coefficient of 

at least 0.25 was reported for a measure. Interestingly, the highest 

discharge rates existed with high use of valid selection procedures in 

conjunction with a high selection ratio. Perhaps an explanation of this 

finding exists for companies with high discharge rates, who must hire 

many drivers to meet needs, yet are able to identify and discharge those 

who are poor performers. Low use of valid selection procedures produced 

a relationship whereby selection ratio was irrelevant to discharge rates. 

Overall, the study suggests that in order to reduce quit rates, trucking 

organizations should strive to pay well and provide good benefits, use 

electronic monitoring sparingly, and provide for low duration of time on 

the road. Further, as a means of minimizing involuntary turnover, use of 

valid selection techniques and a conservative selection ratio is 

recommended. 

Limitations: a

The report is informative, but entirely descriptive. Analysis outcomes, 

reported in this review where available, were summarized and did not 

include statistical values to allow for first-hand interpretation. This report 

provides the basis for much additional data mining (i.e., Shaw et al.), but 

does not include any hypothesis testing or theoretically-driven analysis. At 

present, some of the information it provides is dated; for instance, 

suggesting recruitment using radio and television, given the current 

popularity of the internet. 

 bDriver turnover is not linked with safety outcomes or cost, both of which 

are industry concerns. In fact, lower turnover in an organization may 

actually be related to reductions in financial performance, if unsafe or 

otherwise poor drivers are retained when they should be discharged. 

Categorization: Both studies fit within the post-event timeframe of the motor carrier 

environment for Haddon Matrix #1: Turnover and Retention, as their 

primary focus is on the explanation and impact of HRM practices 

regarding these outcomes. 

50
Holmes, S.M., Power, M.L., & Walter, C.K. (1996). A motor carrier wellness program: 

Development and testing. Transportation Journal, 35, 33-48. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Retention Strategies Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Retention Strategies Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: Motor carriers have experienced a shortage of drivers, leading to high 

turnover rates and the attendant costs of hiring and training new drivers. 

Drivers cited compensation, loneliness, unpredictable work schedules, 

poor working conditions and lack of advancement opportunities as reasons 

for leaving. Two approaches to the driver shortage problem are recruiting 

and retention. While pay issues may dominate recruiting efforts, retention 

may depend on other issues such as how drivers are treated by their 

employers. Some employers have reported favorable results with 

programs designed to aid employees in achieving and maintaining better 

health. The development of such a wellness program by a motor carrier is 

described. 

Industry Sector: Over-the-road and short-haul trucking 

Purpose: The purpose of the study was to develop and implement a driver nutrition 

program and test whether this program reduced driver health risk by 

decreasing weight, body fat, blood pressure, and other problem areas of 

driver health. It is expected that implementing a motor carrier wellness 

program will increase driver satisfaction and provide an added benefit to 

drivers that may increase their desire to stay with the organization. 

Sample: 300 truck driver completed nutrition survey—15 drivers were identified 

for the nutrition program; 15 drivers were identified for the control group. 

Methodology: Researchers developed a survey to determine drivers’ current health and 

nutrition habits. Using the results from the survey, a nutrition program was 

developed and implemented using a small sample of over-the-road truck 

drivers within the TL company. A matched sample of short haul truck 

drivers was selected as a control group. The short haul truck drivers were 

selected based on similar weight characteristics to the test group 

participants. The short haul truck drivers also had the advantage of being 

home every evening, as opposed to being on the road. Both groups 

received an initial health screening. In addition, participants in the test 

group received an in-depth examination of their test results, nutrition 

information pamphlets, and were provided with daily “healthy snack” bags 

51
to encourage better snacking habits. At the end of six months, both teams 

completed a second round of health screenings. The pre- and postscreenings were then analyzed and compared for the test and control 

groups. 

Relevant Findings: The test group reported improvements in weight, body fat, cholesterol, and 

smoking habits. The test group also reported high levels of satisfaction 

when evaluating the program and anecdotal evidence suggested improved 

mood. 

Limitations: Although the authors make a strong argument for improving retention 

through the implementation of wellness programs and back the argument 

with previous research, there is little evidence that the wellness program 

described in the study improved driver retention. In fact, driver attitudes 

about the company were not directly assessed. Instead, drivers reported 

being satisfied with the wellness program itself. Although a wellness 

program may improve driver retention by reducing driver stress and 

increasing job satisfaction, the current study provides little evidence to 

support that assertion. Future research specifically tying wellness program 

implementation to subsequent rates of driver turnover would be necessary 

to draw a clear link to driver retention. 

Categorization: This paper fits within the post-event timeframe of the motor carrier 

environment for Haddon Matrix #1: Driver Retention, as the researchers in 

this study created a wellness program for drivers and attempted to tie its 

benefits to greater job satisfaction and incentive to stay with the company.

52
a

Min, H., & Lambert, T. (2002). Truck driver shortage revisited. Transportation Journal, 42, 

5–16. 

b

Min, H., & Emam, A. (2003). Developing the profiles for truck drivers for their successful 

recruitment and retention: A data mining approach. International Journal of Physical 

Distribution & Logistics Management, 33, 149. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Retention Strategies Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Retention Strategies Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: a

Despite the recent economic downturn and the subsequent increase in 

unemployment rates, driver turnover remains a serious problem in the 

trucking industry. Since driver turnover contributes to cost inflation and 

service disruptions, it has a far-reaching effect on the trucking firm’s 

competitiveness. To control high driver turnover, trucking firms have 

attempted to implement various driver recruitment and retention strategies, 

including pay raises, bonuses, equipment upgrades, and flexible schedules, 

Based on exploratory findings of selected U.S. firms, this article has 

studied the impact of these strategies on turnover. This article also 

assesses the extent of driver shortage and its impact on competitiveness, 

while developing a profile of drivers who are likely to cause turnover. 

 bChronic driver turnover can adversely influence a trucking firm’s 

competitiveness through disrupted delivery services, equipment down time 

and excessive recruiting expenses. Thus, a key to the survival of the 

trucking firm rests with its ability to recruit and retain qualified drivers 

who are less likely to cause turnover. In an effort to develop the ways to 

recruit and retain those drivers, data mining techniques are proposed. 

Based on an empirical study of trucking firms in the US, this paper not 

only develops a viable driver recruitment and retention strategy, but it also 

demonstrates the usefulness of the proposed data mining techniques. 

Industry Sector: For-hire trucking 

Purpose: These articles aimed to identify the important causes of driver shortages, 

assess the degree to which various motor carrier policies are effective at 

reducing turnover, and recommend the most viable driver recruitment and 

retention strategies based on driver profiling. 

53
 In addition, the b

2003 article identified data mining techniques that have 

the potential to help motor carriers identify drivers who fit the profile for 

optimal retention. 

Sample: ab422 motor carriers from 3,000 Midwestern and Southern national and 

regional carriers (14% response rate). 

Methodology: Researchers surveyed a stratified sample of motor carriers, including 

various national and regional sectors of the trucking industry, to determine 

potential causes of high turnover. The survey was tested for response bias, 

and analyzed using both hypothesis testing for pre-conceived theories, 

and, in the later bpaper, data mining techniques (based on decision trees) to 

find new patterns. 

 

Based on survey outcomes, the authors developed “If-Then” rules that 

were expected to explain the impact of organizational characteristics on 

driver turnover. These rules combined both motor carrier and driver 

characteristics to form profiles intended to predict high and low turnover 

rates. Combinations of the following characteristics were used to develop 

decision trees and to build the profiles: firm size, operating area (national, 

regional, local), carrier type (TL, LTL), carrier location, percent part-time 

drivers, unionization, tenure, age, experience, and annual starting salary. 

Relevant Findings: aConsistent with other studies, pay was identified as the most important 

factor influencing turnover; however, condition of equipment and 

company reputation were also cited as important. This study found that, 

according to motor carrier managers, the three most important obstacles to 

driver recruitment and retention are a lack of qualified drivers in terms of 

age, experience, dependability, and safety, a tight labor market that 

reduces the size of recruiting pools, and fierce competition between motor 

carriers forcing a rise in driver pay rates. Mandatory drug testing, lack of 

driving schools, lumper costs, and labor union demands were not found to 

be of great significance to drivers. 

 bThe 2003 article suggests that motor carrier incentives and recruitment 

policies should be tailored for different driver and firm profiles. Motor 

carriers should focus retention efforts on drivers who fit profiles with 

higher turnover rates, and recruitment efforts should be focused on drivers 

fitting profiles with lower turnover rates. In general, retention incentives 

should be targeted at non-unionized, part-time drivers with shorter tenure, 

while targeting recruitment efforts at older drivers who have more than 

five years of CMV driving experience. 

Limitations: These papers do not directly address safety as an important consideration 

in recruitment and retention strategies. Although the authors’ main 

concerns were with reducing the costs that result from high rates of 

54
turnover, this research may also be used in conjunction with studies that 

link a lower turnover rate to better safety outcomes. The development of 

profiles as a means to target retention efforts should also include a careful 

examination of driver safety. Retention efforts should primarily focus on 

keeping the safest drivers, not just those drivers most likely to quit. 

In addition, the response rate is relatively low and the sample is 

geographically restricted to Southern and Midwestern carriers. Because of 

this, many of the decision tree rules and subsequent driver profiles are 

narrowly focused and may not generalize to the larger, national population 

of motor carriers and drivers. 

Categorization: This paper fits within the post-event timeframe of the motor carrier 

environment for Haddon Matrix #1: Retention Strategies. Although this 

paper also discussed recruitment, its purpose was to suggest recruitment 

strategies that maximize retention and reduce turnover. 

55
Morrow, P.C., Suzuki, Y., Crum, M.R., Ruben, R., & Pautsch, G. (2005). The role of leadermember exchange in high turnover work environments. Journal of Managerial Psychology, 

20, 681–694. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Management Relations 

and Turnover

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Management Relations 

and Turnover

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: Purpose—To assess the role of leader-member exchange (LMX) in 

affecting voluntary turnover in a high turnover work context. 

Design/methodology/approach—Following consideration of traditional 

predictors of employee turnover, how LMX is related to voluntary 

turnover is examined among 207 over-the-road truck drivers using a 

telephone survey. 

Findings—Leader member exchange is found to be nonlinearly related to 

turnover such that turnover is lowest when LMX is moderate (i.e., both 

“bad” and “good” LMX are associated with higher levels of turnover). 

Research limitations/implications—Findings indicate that LMX and 

other antecedents should be examined for nonlinear relationships to 

turnover. This research may help to bridge the gap between turnover 

research and that associated with supervision and leadership. 

Practical implications—These study results suggest that unrealistic 

expectations should not be formed regarding the power of any single 

factor (e.g., LMX) to reduce turnover. 

Originality/value—This paper suggests that nonlinear relationships 

between antecedents of turnover and turnover receive fuller consideration. 

Industry Sector: Over-the-road trucking 

Purpose: LMX concerns the quality of a driver’s work-related and social 

relationships with his/her supervisors. Past research has suggested that the 

relationship between LMX and turnover is relatively weak. This study 

sought to examine the potential for a curvilinear relationship between 

LMX and turnover in a high turnover work environment (i.e., the trucking 

industry). It is hypothesized that turnover is lowest when LMX is 

moderate. Thus, having too much, or too little LMX is related to higher 

levels of turnover. 

Sample: 294 of 724 truck drivers employed with a mid-sized motor carrier in the 

Midwest—207 of the respondents provided usable data, after surveys with 

missing or incomplete data were removed. 

56
Methodology: A telephone survey was initiated in a medium sized trucking firm that 

employed approximately 724 drivers. Drivers were given information 

about the survey with their payroll statements and asked to call al toll-free 

number to participate in the survey. 

LMX was assessed using 12 statements intended to measure 4 major 

components: affect (friendship and liking), loyalty (feeling of mutual 

support and obligation), contribution (performing at a level beyond 

minimal standards), and professional respect (appreciation of job 

knowledge and competence). Drivers were asked to indicate their 

agreement with statements such as “I like my team leader very much as a 

person,” and “I am impressed with my team leader’s job knowledge” on a 

1 (strongly disagree) to 5 (strongly agree) scale. Drivers were also asked 

to respond to statements concerning organizational commitment (e.g., “I 

feel a strong sense of belonging to this organization”) using the same 1–5 

scale, and to report their average amount of time spent at home per week. 

Demographic and organizational information such as company tenure, 

number of dependents, driver pay, and average loading/unloading wait 

time was gathered from company records. Voluntary turnover was also 

recorded by tracking resignations for approximately one year after data 

collection. Seventy five of the 207 drivers that participated in the study 

quit during the 1 year period. 

Relevant Findings: The authors used logistic regression with actual turnover as the dependent 

variable. The LMX variable was calculated by taking an average score out 

of 5 on the statements assessing LMX. The possibility of a curvilinear 

relationship was assessed by testing the significance of the squared LMX 

variable (suggesting a “U” shaped relationship) and the cubed LMX 

variable (suggesting an “S” shaped relationship). 

After controlling for demographic characteristics commonly associated 

with turnover (i.e., tenure, number of dependents, organizational 

commitment, pay, time at home, and consignment wait time) there was a 

significant “U” shaped curvilinear relationship between LMX and 

turnover. Both low and high LMX were associated with higher turnover 

rates. Turnover probability was highest when drivers indicated that their 

LMX relationship was extremely negative (1–1.5 on a 1–5 scale) or 

extremely positive (4.5–5 on a 1–5 scale). On the other hand, average 

levels of LMX (2.5–3.5 on a 1– 5 scale) were related to the lowest 

probabilities of turnover. This suggests that simply improving the quality 

of the relationship between supervisors and subordinates will not reduce 

turnover rates. Instead, it appears that there is a threshold for “good” 

LMX, such that turnover probability decreases until the threshold is 

reached and at that point begins to increase again. The authors theorize 

that turnover may be more likely at high levels of LMX because 

57
employees who have strong relationships with their supervisors are often 

afforded special attention (e.g., better training, more performance 

feedback, additional opportunities for advancement) making them more 

marketable. Thus, they are more likely to leave voluntarily to pursue better 

job opportunities. 

Interestingly, organizational commitment, a person’s sense of loyalty or 

belonging to their organization was not related to turnover intentions in 

this study. This is contrary to past research exploring the relationship 

between commitment and turnover, where organizational commitment is 

typically negatively related to turnover intentions, such that people who 

are more committed to their organization are less likely to want to quit. 

The authors theorize that the lack of a relationship between commitment 

and turnover may be due to the nature of this particular work environment. 

Jobs are readily available in the trucking industry, potentially making level 

of organizational commitment less relevant when it comes to turnover 

decisions. 

Limitations: Subjective data from supervisors concerning perceptions of LMX were not 

utilized in the current study. Thus, LMX was only assessed from the 

perspective of the subordinate. It is also unclear what type of 

recommendations for practice can be drawn from the results of this study. 

Clearly, promoting interactions between supervisors and subordinates is 

important. In spite of this, interactions of superior quality appear to 

increase the likelihood of turnover. More research is necessary to 

determine how much LMX is too much, or if there are other factors yet to 

be explored that contribute to, or better explain, the curvilinear 

relationship demonstrated in this study. 

Categorization: This paper fits within the post-event timeframe of the driver environment 

for Haddon Matrix #1: Management Relations and Turnover, as it 

examines the relationship between LMX and turnover rates.

58
a

Ozment, J. & Keller, S. (1999). Exploring dispatcher communication effectiveness: 

Implications for retaining drivers in the trucking industry. Journal of Managerial Issues, 11, 

94–109. 

b

Keller, S.B. & Ozment, J. (1999a). Managing driver retention: Effects of the dispatcher. Journal 

of Business Logistics, 20, 97. 

c

Keller, S.B. & Ozment, J. (1999b). Exploring dispatcher characteristics and their effect on 

driver retention. Transportation Journal, 39, 20–33. 

Haddon Matrix for Review #1: Selecting Safe Drivers

Management Relations

and Turnover

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #1: Selecting Safe Drivers

Management Relations

and Turnover

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: aNo author abstract 

 bNo author abstract 

 cNo author abstract 

Industry Sector: abcTL trucking 

Purpose: abcThe following articles explore the relationship between dispatcher 

characteristics and driver turnover. The primary goal of this research was 

to examine potential interventions that may be instituted by motor carriers 

at the level of the dispatcher to reduce truck driver turnover. The first a

article examined the relationship between dispatcher sensitivity and 

dispatcher responsiveness. The second b article re-tested the 

aforementioned relationships with a larger, more diverse sample, and in 

addition, proposed a theoretical model incorporating relationships between 

sensitivity, responsiveness, and driver turnover. The third carticle 

expanded upon the first and second by examining dispatcher demographic 

characteristics (e.g., age, tenure, past experience as a driver) as 

antecedents of dispatcher responsiveness and driver turnover. 

Sample: abcInitial sample: 132 dispatchers from a single TL carrier—73 usable 

responses were obtained and analyzed. 

 bcSecond sample: 222 dispatchers from 5 leading TL motor carrier firms 

ranked in a listing of the 100 largest motor carriers in the US (Transport 

Topics, August 11, 1997). Researchers received 164 questionnaires—149 

were identified as usable. 

59
Methodology: abcAll data collection efforts involved surveying dispatchers from national 

TL carriers using a mailed questionnaire. Dispatchers were asked to 

respond to statements assessing their sensitivity to voice (e.g., “I always 

encourage drivers to let me know when something goes wrong on the 

job”), sensitivity to reasons for driver turnover (exiting behavior; e.g., 

“When drivers quit, it is most important to understand their reasons for 

quitting”), and responsiveness to receiving complaints or becoming aware 

of driver resignations (e.g., “It is very important to respond to all driver 

complaints”). Responses were rated using a 5-point Likert scale from 

strongly agree to strongly disagree. Data cited in articles two and three 

also asked dispatchers to report their monthly truck driver turnover 

percentages, how much their drivers are paid relative to other drivers, and 

how much time their drivers are regularly routed home relative to other 

drivers. Additional dispatcher characteristics such as age, tenure, 

education, and job satisfaction were also included in the data collection. 

Relevant Findings: 

and 

mple did suggest a strong relationship (r = 0.60) 

between those factors. 

y 

authors give no 

explanation for this seemingly contradictory result. 

 a driver gets to be 

home, the less likely they are to leave a trucking firm. 

Limitations:

abcAlthough the initial analysis, using a sample of 73 dispatchers, did not 

yield a significant relationship between dispatcher sensitivity to voice 

dispatcher sensitivity to exit, subsequent analyses using more refined 

measures and a larger sa

Additional testing of the model suggested a positive relationship between

sensitivity and dispatcher responsiveness, such that the more sensitive a 

dispatcher is to driver concerns and reasons for quitting, the more likel

they are to act upon those concerns. Furthermore, responsiveness was 

related to driver turnover, such that more responsive dispatchers also

indicated lower levels of turnover. Interestingly, dispatcher age was 

positively associated with driver turnover, whereas dispatcher experience

was negatively associated with driver turnover, indicating that older 

dispatchers have higher rates of driver turnover but more experienced

dispatchers have lower rates of driver turnover. The 

c

In addition, the third study in this series replicated past findings that 

driver pay and time at home are negatively associated with turnover. As 

expected, the more pay a driver gets and the more time

d 

lly 

abcAll three studies used self-report methodologies to examine only 

dispatcher sensitivity and responsiveness. Although the use of turnover 

rates may provide some insight into driver behaviors, future studies shoul

collect information from both the driver and the dispatcher to more fu

understand the dynamic relationships between dispatchers and their 

drivers. This is especially important when soliciting information about 

60
dispatcher behaviors, as driver perceptions of dispatcher sensitivity and 

responsiveness may vary greatly from a dispatcher’s self-perception of 

their own attitudes and behaviors. 

Categorization: These papers fit within the post-event timeframe of the motor carrier 

environment for Haddon Matrix #1: Management Relations and Turnover, 

as they focus on how the relationships between drivers and dispatchers 

affect turnover rates. 

61
Secondary Sources 

Federal Motor Carrier Safety Administration. (2003). Results from the 2003 R&T stakeholder 

forums (TRIS No. 00989307). 

Executive Summary: FMCSA’s Office of Research and Technology held a series of five 

stakeholder forums throughout February and March 2003. These forums were structured to 

gather stakeholder input regarding the agency’s research agenda, and educate stakeholders 

about the FMCSA Research and Technology program and key ongoing projects. The forums 

were attended by a wide range of stakeholders, including representatives from: motor 

carriers; motor coach companies; industry associations; safety advocacy groups; state 

enforcement agencies; commercial vehicle manufacturers; academia; and vendors of systems 

and services focused on improving commercial vehicle safety. The forums generated over 

150 recommendations regarding FMCSA’s research program. Recommendations ranged 

from the need for better data sources to specific research questions that need to be 

investigated to improve commercial motor vehicle safety. The majority of recommendations 

focused on driver-related factors. Recommendations also were made regarding vehicle, 

carrier/shipper, and roadside/environmental issues. This document summarizes the forum’s 

recommendations. 

Federal Motor Carrier Safety Administration. (2005). 2005 model commercial driver’s license 

manual (FMCSA Publication No. DTFH61-97-X- 00017). 

No summary information available 

Grenzeback, L.R., Lin, S., & Meunier, J. (2005). Operational differences and similarities among 

the motorcoach, school bus, and trucking industries (TRIS No. 00987800). Transportation 

Research Board. 

Foreword: This synthesis will be useful to commercial truck and bus carriers, state agencies, 

and others interested in improving commercial vehicle safety. This synthesis discusses the 

operational differences and similarities among the motorcoach, school bus, and trucking 

industries. It provides a single resource for information on industry profiles, safety statistics, 

and general business operations. Information for this synthesis was obtained through a 

literature review that included Federal Motor Carrier Safety Administration (FMCSA) 

databases, industry association publications, industry trade magazines, internet searches, and 

documents from the Bureau of Labor Statistics and the U.S. Census Bureau. This information 

was supplemented by interviews with staff of various relevant government and industry 

organizations. 

Moffat, G.K., Ashton, A.H., & Blackburn, D.R. (2001). A challenged employment system: 

Hiring, training, performance evaluation, and retention of bus operators. Transportation 

Research Board. (NTIS No. PB 2002-107846) 

Foreword: This synthesis will be of interest to transit agency professionals and the 

consultants who work with them in dealing with bus operator employment processes. It 

offers a snapshot of public agencies’ practices in bus operator hiring, training, performance 

evaluation, and retention. Each of these areas is uniquely different, but also highly 

interrelated; therefore, it is necessary to consider all areas for a complete understanding of 

the subject. The transit industry is experiencing the same stresses on its employment 

62
processes as are affecting employers across the country. This tight labor market, combined 

with changing work-force demographics and difficult transit working conditions, creates a 

definite staffing challenge. Survey information provided might suggest that transit has not yet 

adopted an across-the-board, systematic approach to employment systems, where the 

elements of hiring, training, performance evaluation, and retention are handled in an 

integrated fashion. The focus in this document is on presenting information reported simply 

and in such a way as to reinforce the interrelated nature of employment processes and 

opportunities for transit agencies to realign efforts so that they might work in an integrated 

fashion. This document integrates information from a literature review of transit and related 

periodicals and websites, from survey responses from 29 transit agencies, and from contacts 

with agencies reporting new and innovative practices. 

National Private Truck Council. (2006, June). Standards of fleet excellence (Version 1.0). 

NPTC Summary: NPTC’s Standards of Fleet Excellence is a copyrighted 158-page 

document designed to help qualify and quantify the value of a company’s private fleet using 

criteria—including best practices, benchmarks, protocols and metrics—commonly found in 

many of America’s leading private fleets. 

National Transportation Safety Board highway special investigation report: Transit bus safety 

oversight. (1998). Washington, DC: National Transportation Safety Board. (NTIS No. PB 

98-917006) 

Author Abstract: After the National Transportation Safety Board (NTSB) conducted several 

accident investigations involving transit buses (Normandy, Missouri; Cosmopolis, 

Washington; New York, New York; and Nashville, Tennessee) and held a public hearing on 

transit bus safety in March 1998, it found that substantial safety deficiencies and little 

Federal or State government safety oversight existed within the transit bus industry. During 

the public hearing, participants discussed transit agency self-regulation, the extent of Federal 

and State safety oversight, accident data, pupil transportation, and driver selection and 

qualification. 

Occupational Safety and Health Association, National Highway and Transportation Safety 

Administration, & Network for Employers for Traffic Safety. (2006). Guidelines for 

employers to reduce motor vehicle crashes (OSHA Purchase Order No. B-9-4-2-3576). 

Washington, DC: U.S. Department of Labor. 

Booklet Introduction: This booklet outlines ten steps for building a driver safety program in 

your workplace. These steps will be useful to any organization regardless of size of the 

organization, type of traffic encountered, number of vehicles involved, or whether employees 

drive company or personal vehicles for work purposes. Also included are real-life examples 

of successful safety programs, key traffic safety issues to address in the workplace, 

instructions for calculating your organization’s loss from motor vehicle crashes, and a list of 

resources to help you fine-tune your program. 

Pratt, S.G. (2003). Work-related roadway crashes: Challenges and opportunities for prevention. 

Department of Health and Human Services: National Institute for Occupational Safety and 

Health. (NTIS No. PB 2004-101216) 

TRIS Abstract: The purpose of this document is to provide an overview of current issues 

63
affecting work-related roadway crashes with a focus on preventing injuries and fatalities to 

vehicle drivers and passengers. Fatalities and injuries to pedestrian workers are not within the 

scope of this document, nor are events occurring at locations such as parking lots and 

industrial sites away from public roadways. The document begins by illustrating the scope 

and nature of the problem and presenting data on both fatal and nonfatal injuries. The next 

section summarizes the large body of regulations that apply to the operation of motor 

vehicles. Some are specific to work-related driving, and others apply to all drivers or all 

vehicles. The sections that follow address special topics critical to the formulation of 

strategies to prevent work-related roadway fatalities and injuries. These topics include driver 

fatigue, special issues regarding the motor carrier industry, driver distraction and cell phone 

use, age-related factors, and general fleet safety issues. Following the discussions of special 

topics are detailed strategies for preventing work-related roadway crashes. The document 

concludes with lists of additional readings and vehicle-related Internet resources from 

government agencies, research organizations, industry, and citizen groups. 

Smadi, A. (1998). Educational and technical assistance to CMV drivers and motor carriers. 

Washington, DC: Federal Highway Administration, Office of Motor Carriers. (NTIS No. PB 

99-149759) 

TRIS Abstract: The Peer Exchange is a process adopted by the Office of Motor Carrier and 

Highway Safety in which teams of professionals, representing state and federal government 

and private industry, identify effective commercial motor vehicle safety findings for 

implementation by other jurisdictions throughout North America. The peer exchange process 

has proven to be an effective technique by which to share and develop ideas among States to 

address important safety issues. The educational and technical assistance peer exchange had 

two main objectives: to identify best practices for providing effective educational and 

technical assistance to commercial drivers and motor carriers, and to disseminate information 

on the best practices to States and private industry. 

Staplin, L., Lococo, K.H., Decina, L.E., & Bergoffen, G. (2004). Training of commercial motor 

vehicle drivers. CTBSSP Synthesis of Safety Practice, 5. 

Foreword: This synthesis will be useful to commercial truck and bus carriers, state agencies, 

and others interested in improving commercial vehicle safety. The synthesis identifies and 

documents training strategies and curricula from existing commercial driver training 

programs, with the goal of identifying those commercial motor vehicle driver training tools 

and techniques that hold the greatest potential to improve commercial motor vehicle safety. 

Information for this synthesis was obtained through surveys of commercial motor vehicle 

training schools and carriers; a review of relevant literature; and a review of comments 

received on the U.S. DOT Federal Motor Carrier Safety Administration (FMCSA)-issued 

advance notice of proposed rulemaking (ANPRM) and notice of proposed rulemaking 

(NPRM) 

Stumpo, D.M. (2001). Performance beyond words: Are employees most important? Bus & 

Paratransit Conference (pp. 1-8). Washington, DC: American Public Transportation 

Association. 

Author Abstract: Leaders within our transportation industry have consistently stated that 

employees are very important. The American Public Transportation Association has defined 

64
two main strategic goals on the development of our industry’s workforce. Our managers and 

supervisors have stated that training and development is the core requirement to long range 

success. Ask yourself, “Why is training and development, attracting and retaining transit 

workers such a problem? Why doesn’t the transit industry create a market of certified transit 

professionals? Why aren’t we teaching our employees how vision, mission and values link to 

our every day business?” 

Organizations still ponder with the need to invest current dollars in training and certification 

processes, in place of short-term fixes that tend to add only little value to our industry’s 

success. Anyone managing a multi-million dollar public transit operation today realizes that 

this industry employs over 450,000 people in North America and moves over four billion 

people annually. Ensuring our employees have the tools needed to be successful, improving 

their skills through training and managerial dedication that will pay dividends. 

Many leaders underestimate the importance of designing an organization’s future with this in 

mind. However, I challenge our leaders to take the steps to have the goals of training, 

development, and recognition as part of our industry’s way of operating. Having these goals 

that invests in our employees, will sustain long needed success for our customers and the 

growth of our industry into the 21st Century. 

65
REVIEW #2: IMPROVING DRIVER SAFETY 

For the second review, Haddon’s matrix was adapted in a similar manner to that used in the first. 

The two environments again consisted of the driver and the motor carrier; however, for this 

review, the events in the driver-motor carrier relationship are those important for improving 

driver safety. Thus, the Haddon Matrix for Review #2 outlines driver- and motor carrier-related 

factors that impact safety, such as driver characteristics, as well as those that play a role in 

maintaining safe operations and enhancing the safety performance of CMV drivers. The 

available, published literature on these topics was annotated and subsequently characterized 

within one of the six Haddon matrix cells below, as determined by its primary focus with regard 

to environment and event stage: 

Table 2. Haddon Matrix for Review #2: Improving Driver Safety 

Pre-Event Event 

(Adverse Safety Incident) 

Post-Event 

Driver 

Environment 

What driver-related 

factors affect safety? 

How are driver behaviors 

related to event occurrence? 

How can feedback provided 

to the driver benefit safety? 

Motor Carrier 

Environment 

What motor carrier 

practices affect safety?

How are motor carrier 

operations related to event 

occurrence?

How can feedback provided 

to the motor carrier benefit 

safety?

Literature Search Results 

The references obtained for Review #2 resulted in annotations of 45 sources, referencing 36 

unique study efforts. These covered topics addressing each stage of the event cycle in the 

Haddon matrix; however, in contrast to the distribution of references for Review #1, the bulk of 

the annotations for Review #2 fit within the pre-event stage. 

As shown in Table 2, studies for the driver environment of the pre-event stage of the matrix 

addressed the question, “What driver-related factors affect safety?” and encompassed the topics 

of driver compensation and driver characteristics (e.g., age, abilities, perceptions). In the motor 

carrier environment, the literature that resulted for the pre-event stage and accompanying 

question, “What motor carrier practices affect safety?” consisted of themes such as safety 

management and incentive programs. The event stage of the matrix for the driver environment 

addressed the question, “How are driver behaviors related to event occurrence?” and 

encompassed literature relating to unsafe driving behaviors. Also within the event stage, the 

available literature pertaining to the question, “How are motor carrier operations related to 

event occurrence?” focused on the area of motor carrier operations, particularly the association 

between commodity segments and safety performance measures. For the post-event stage of the 

matrix and the driver environment, a number of studies in the areas of driver self-management 

and attitudes toward technology addressed the question, “How can feedback provided to the 

driver benefit safety?” Finally, with regard to the post-event stage of the matrix and motorcarrier environment, the question, “How can feedback provided to the motor carrier benefit 

safety?” resulted in literature in the area of safety oversight. 

66
Improving Driver Safety Outcomes 

In contrast to the first review, the annotated literature for Review #2 is concentrated in the preevent stage of the matrix. This suggests a perceived priority regarding the identification and 

comprehension of driver characteristics and motor carrier practices as they are related to safety 

outcomes. Studies pertaining to the relationship of driver behaviors and motor carrier operations 

to safety event occurrence, or the impact of feedback provided to drivers and motor carriers on 

safety outcomes, were considerably less prevalent. This may reflect an academic, if not industry, 

desire to understand and address safety issues preemptively; that is, at the pre-event stage of the 

Haddon matrix. With more than 5,000 deaths each year in the U.S. as a result of accidents 

involving large trucks (NHTSA Traffic Safety Facts, 2005), and annual industry direct costs for 

safety expenditures, such as training and incentives, in the billions of dollars (ATA, 1999), 

making a case for improving driver safety is not difficult. 

Indeed, establishing which driver-related factors impact safety has implications for improving 

recruitment and selection techniques; as such factors may serve as “markers” for targeting 

desirable drivers in the future. For instance, age and CMV driving history, including experience 

and past history of accident involvement and safety violations, are two pertinent areas to this 

review that are frequently addressed in the literature (Knipling, Hickman, & Bergoffen, 2003). 

These characteristics of drivers, as related to safety, lend insight into statistics reported in the 

Large Truck Crash Causation study (LTCCS; 2006). The authors of that study determined that 

when a large truck was responsible for a crash, 87% of the time this was due to an error on the 

part of the truck driver, such as a poor driving decision or a failure to correctly recognize the 

situation. 

The effect of age as a driver factor impacting safe operations is often confounded in studies that 

do not investigate or control for related variables of driving experience, or tenure, because older 

drivers are also frequently more experienced drivers. Nevertheless, research suggests that the 

relationship between driver age and safety outcomes is often a “U” shaped function, such that 

both younger and older drivers are less safe on the road than those in the middle age range. For 

example, Blower (1996) assessed differences between younger (18-21) and older (30-49) truck 

drivers and found that the younger drivers were more likely to have experienced a moving 

violation in the previous three years, and when involved in a traffic accident, were more likely to 

have been cited by police as responsible for the accident (70% versus 55% of older drivers). 

Regarding crash severity outcomes, a study of single vehicle accidents (SVAs) within a 

Canadian for-hire carrier determined that drivers under the age of 24 were more likely to be 

involved in severe crashes; however, because SVAs account for only a small percentage of all 

trucking accidents, this finding must be interpreted with caution. It does, nevertheless, raise the 

possibility that physical driving skill (e.g., quick reaction time) may have played a role in 

allowing younger drivers to avoid less severe crashes in some cases (Goodwin, 1996). In a 

related finding, a laboratory study by Llaneras, Swezey, Brock, Rogers, & van Cott (1998) 

reported that driving-related abilities in older, commercially-licensed drivers (> 65 years), such 

as accurately and quickly positioning controls and object tracking, were significantly impaired 

when compared with those under 50. Of note regarding the applicability of these results is that, 

while the average age of the U.S. workforce is indeed increasing, the proportion of CMV drivers 

who are employed over the age of 65 continues to be small in comparison with younger and 

middle-aged workers. This, in part, may be a function of the taxing nature of truck driving as a 

67
profession (Mayhew & Quinlan, 2006), as an examination of worker’s compensation claims in 

Oregon over seven years determined that the average number of workdays lost to injury 

increased from 41.9 days for drivers under 25 to 87.0 days for drivers over 65 (McCall & 

Horwitz, 2005). 

Driving history is another factor the literature supports as impacting safety. In a study by 

Murray, Lantz, and Keppler (2006), future truck crash involvement was predicted based on past 

driver behaviors. Using Motor Carrier Management Information System (MCMIS) and 

Commercial Drivers License Information System (CDLIS) data, they determined that drivers 

with prior crash involvement were 87% more likely to be involved in a future crash. 

Additionally, results showed that drivers who had been cited for reckless driving violations and 

improper turn violations were, respectively, 325% and 105% more likely to be involved in future 

crashes. A pair of studies by Nafukho and Hinton (2004), and Nafukho, Hinton, and Graham 

(2007) also utilized accident data. Results indicated that drivers who were involved with three 

crashes also had the highest mean monthly mileage driven, while those with one crash drove the 

least. The authors suggested that because high-mileage drivers were associated with greater crash 

involvement, carriers should consider compensation based on the value of goods transported 

instead of miles driven. One obvious difficulty with this suggestion would appear to be that 

drivers may only then be motivated to haul loads of higher value. Additionally, these results 

were reported in such a manner that did not preclude exposure as a simple explanation for their 

findings. In other words, drivers with higher monthly mileage rates may have also been involved 

in more accidents simply because they were on the road more. 

A number of studies purport to draw relationship between driver compensation and safety 

outcomes, for example, that increased pay is associated with a reduction in crashes. The 

reviewers offer a cautionary note to these assertions: generally, it is not possible to understand 

the true nature of the relationship between these two factors. Specifically, it may be unclear 

whether cash bonuses for safe driving are responsible for higher pay, or that offering better pay 

at a company improves its ability to recruit and hire greater numbers of quality drivers. Data 

reported by Belzer, Rodriguez, and Sedo (2002) indicated that truck drivers receiving a higher 

pay rate, or who received a raise during the study’s data collection period were less likely to be 

involved in a crash. A pair of studies by Monaco and Williams (2000), and Williams and 

Monaco (2001), also investigated crash probability and determined that a $0.10 increase in pay 

rate per mile would reduce the probability of crash involvement by 1.76%. In a study on 

implementing safety incentive programs, a pilot investigation of a long-haul trucking firm in 

Canada demonstrated a decrease in driver turnover from 98% to 20% after offering safety 

bonuses to drivers who had not been involved in an adverse incident after six months (chosen 

because most of the company’s turnover occurred after this duration of time; Barton, Tardif, 

Wilde, & Bergeron, 1998; Barton & Tardif, 2002). Indeed, to the extent that driver pay and 

incentives are higher due to the payment of safety bonuses, an associated reduction in turnover 

(as noted by Barton et al.,1998) is further linked to accident rate in a pair of studies by Staplin 

and Gish (2005), and Staplin, Gish, Decina, and Brewster (2003). These authors reported that 

drivers who changed jobs less frequently were less than half as likely to be involved in multiple 

crashes, as drivers who had changed jobs more than three times per year. However, the causal 

direction of this relationship remains unclear. Is accident involvement more common in drivers 

who frequently change jobs, or do drivers change jobs because they were involved in accidents? 

68
Taking an organizational focus, there are also practices of the motor carrier that have been found 

to influence safety and promote safety culture. Deserving of mention are reports of safety 

management best practices (e.g., American Trucking Association [ATA] Safe Returns, 1999; 

Mejza, Barnard, Corsi, & Keane, 2003; Corsi & Barnard, 2003), listing factors including 

commitment to safety by top management, employee involvement, prioritizing safety in all 

aspects of an operation, and making safety management a continuous process. Driver opportunity 

for safety input and top management commitment to safety were also among antecedents in a 

model of safety culture that was based on driver perceptions of their respective corporate safety 

cultures (Arboleda, Morrow, Crum, & Shelley, 2003). The use of incentive or recognition 

rewards for safe performance, holding regular safety meetings, and consistently tracking all 

driver-related accidents and incidents for the purpose of taking disciplinary action, such as 

termination or suspension, in response to safety violations were also noted. 

Furthermore, experts responding to a survey regarding management practices recommended 

training, such as apprenticeship programs, standardized training for new hires, refresher training, 

and remedial training (Knipling, Hickman, & Bergoffen, 2003). In fact, companies identified in 

the ATA Safe Returns report (1999) as having superior safety records reported spending at least 

$2,500 per power unit per year on direct safety costs (incentives, meetings, training), an amount 

that is nearly $1,500 more than the average firm spends. As a counter point to the above training 

recommendation, however, it should be mentioned that in a study by Dobie and Glisson (2005), 

although motor carrier managers and drivers agreed regarding components of safety training 

programs that they found beneficial (e.g., personal safety training), drivers, in turn, did not 

indicate that training availability would affect their decision to stay at a company. In fact, 50% 

stated that it did not matter whether or not the company they worked for offered such training. 

This may be due, at least in part, to the fact that 61.7% of drivers surveyed indicated that they 

were not compensated for time spent in training, nor did they receive other benefits in the form 

of promotions or route assignments. The benefits to training with regard to the potential for 

improved safety are not tangible, and therefore not enough to keep drivers at companies without 

a strong, homogeneous safety culture. 

There is a small body of literature cited in this review linking differences in motor carrier 

operations to safety performance. Findings for motor carriers were not conclusive due to the 

limited number of studies, and because each study analyzed different segments of the trucking 

industry and different safety areas. Nevertheless, there is reason to believe that passenger 

carriers, on measures including compliance reviews (CRs), roadside inspections, and fatal 

crashes, are among the best performing motor carriers when compared with carriers of particular 

commodities (Corsi, Newhouse, Shukla, & Chandler, 2002). Furthermore, in a comparison of 

for-hire and private commodity segments, Keane, Corsi, and Braaten (2002) determined that 

private carriers were statistically safer than for-hire carriers on seven of nine safety measures. 

Also, results across the four Safety Evaluation Areas (SEAs) of the Motor Carrier Safety Status 

Measurement System (SafeStat) indicated that passenger carriers and the LTL freight segment 

were the safest for-hire performers. The tank and household goods segments were the safest 

private carriers. 

A more micro-level approach to investigating how driver actions are related to event occurrence 

documents deleterious impacts on safety pertaining to aspects of individual driving behavior. For 

example, Sullman, Meadows, & Pajo (2002) surveyed truck drivers in New Zealand to assess the 

69
relationship of aberrant driving behaviors to previous crash involvement. Data analysis yielded 

four distinct groups of behaviors. The first group, labeled “errors”, consisted of mistakes 

involving failures of observation and misjudgment. The second group, labeled “lapses”, 

encompassed problems with attention or memory. The third group, labeled “violations”, was 

made up of deliberate deviations from practices believed to be necessary to safely operate a 

vehicle. Finally, the fourth group, labeled “aggressive violations”, consisted of violations that 

specifically involved expressing hostility toward another road user, or driving in an aggressive 

manner. Only the group of behaviors labeled “violations” significantly predicted crash 

involvement; however, to the extent that social desirability may have affected responses for 

drivers who did not feel comfortable negatively portraying themselves in a survey, this 

relationship may actually be stronger than documented. 

Similarly, quantitative data were collected in two studies investigating unsafe driving behaviors. 

The first, a naturalistic study of driving in long-haul truck drivers, used instrumented trucks and 

video to track driver actions surrounding critical incidents (Hanowski, Perez, & Dingus, 2005). 

Critical incidents were recorded based on triggers that were likely to produce video of drivers 

engaged in activities that were not related to primary driving duties (i.e., “distraction events”). A 

total of 34 distraction types, and 7 clusters that tended to statistically separate based on event 

duration and frequency of occurrence were identified. The majority of all incidents grouped into 

a single cluster, representing “average frequency” and “average event duration.” Considered a 

greater safety risk, high frequency events are dangerous because the driver is repeatedly being 

inattentive to the driving task (e.g., looking around or outside of the cab to the left and right). 

Also, visually demanding tasks are dangerous because they take drivers’ eyes off of the road 

(e.g., reaching to the floor). Especially concerning are tasks combining moderate levels of 

duration, visual demand, and frequency (e.g., talking on/adjusting CB or talking on a cellular 

phone). Although no crashes were recorded during the course of this study, results suggest an 

opportunity to use these objective data as an educational tool, especially because professional 

drivers may be inclined to overestimate their skills or safety. The second set of qualitative data 

regarding unsafe driving behaviors investigated speed-related variability during driving, or 

celeration, for its ability to predict accident rate. This was done through a series of studies 

conducted by af Wahlberg (2000; 2004; 2006). Indeed, support for using this measure as a 

slightly superior predictor of accidents over individual speed variables of mean and maximum 

speed was generated in the final study. However, even as each effort sought to address 

weaknesses from the previous, a new shortcoming to the existing data and/or results seemed to 

appear as an explanation for an overall lack of significant findings (e.g., low power; restriction of 

range; small sample size). 

A final set of studies relevant to this review address the means by which drivers and motor 

carriers can receive feedback to improve safety performance and outcomes. Feedback may be 

provided by technology or from people, but in every case it is important that it be accurate, 

appropriate to the situation, and where possible, that those who are receiving the feedback have 

been given a role in developing the related safety program or technology. This should help build 

a strong safety climate and ensure that users will buy into how, when, and at what intervals they 

will receive feedback and/or interact with the technology. As reported in a pair of studies by 

Roetting, Huang, McDevitt, & Melton (2003), and Huang, Roetting, McDevitt, and Melton 

(2005), truck drivers were quite receptive to receiving feedback concerning their safe driving 

behaviors, especially if the feedback was positive. If coming from a person, the greatest 

70
preference was for feedback from a safety director or supervisor, as opposed to peers, 

dispatchers, or motorists. Feedback from in-vehicle technology was viewed as objective and 

valuable for its potential to aid drivers in case of a crash or incident. 

In independent jobs where people typically work alone, such as CMV driving, the only logical 

behavior-based safety (BBS) management programs are those that employ self-monitoring, as 

opposed to techniques where peer-to-peer feedback is provided. To this end, Olson, & Austin 

(2001) performed an intervention on bus operators who monitored and reported their own safetycritical behaviors, in addition to being observed by experimenters posing as passengers. 

Behaviors included coming to complete stops, remaining stopped during passenger 

loading/unloading, mirror checking, and proper selection of stopping position. A 13-day 

baseline, compared with observations over the subsequent 18 days, indicated an average of 

12.3% improvement across drivers and conditions. Despite a small sample size that cautions 

against generalization, extrapolating to the entire transit system in the study (68 drivers) 

translated into the possibility of 31,200 fewer at-risk behaviors per month. In another selfmanagement for safety (SMS) study, Hickman and Geller (2003) investigated differences in 

short-haul truck drivers who either recorded their intentions to engage in specific safe versus atrisk driving behaviors prior to leaving the terminal, or recorded actual behaviors after returning 

to the terminal. An on-board monitoring device tracked instances of overspeeding (>63 mph) and 

hard stopping/braking (>0.319 g). Both groups decreased their risky safety behaviors during the 

four week intervention, but then returned to near baseline levels of performance over the four 

weeks after the intervention was discontinued. This suggests that behavioral change in this study 

was related specifically to SMS techniques, and was not an artifact of training or increased safety 

awareness. In order to retain SMS benefits, then, it may be necessary for organizations to 

maintain ongoing monitoring and oversight programs. 

Feedback from on-board vehicle and driving monitoring technologies is another avenue for 

improving driver safety, albeit an oftentimes controversial approach because of its potential for 

misuse. As a natural response, drivers may be wary of having their actions monitored and 

recorded, especially if they do not have a full understanding of the purpose of the technologies, 

how they work, and what information they provide. As these devices and monitoring systems 

have matured, false-alarm rates have dropped, and costs for the devices and their operation have 

decreased. Increasingly, more motor carriers are using the technologies, or considering doing so. 

The use of technology to help counteract deficiencies in driving-related abilities that decline with 

age, as well as errors related to lack of job experience, may prove invaluable, especially in light 

of the current driver shortage and resultant need for motor carriers to explore recruiting 

inexperienced, older workers pursuing second careers (Llaneras et al., 1998). Testing of one such 

collision warning system (CWS) with visual and auditory warning components was performed in 

a simulator study of transit bus operators (Reinach & Everson, 2005). No statistical differences 

among conditions (no system; visual warning only; visual plus auditory warnings) were found 

for stopping distance to a lead-braking vehicle during critical events. Additionally, time-tocollision differences were not demonstrated. However, initial brake application response to the 

critical event was slightly faster for the visual plus auditory warning condition. Low power was 

cited as an explanation of the lack of obvious performance benefits to the system; however, there 

is also the possibility that the task itself was to blame, or that the visual and/or auditory interface 

simply was not optimized for use in a low-speed, high-obstacle-laden urban driving environment. 

Nevertheless, drivers generally found the CWS useful and overall not annoying or distracting, 

71
but noted that the visual and auditory warnings were slightly more annoying and distracting than 

the visual-only warnings. Clearly, as is the case with many of these evolving technologies, there 

is a fine line between effective and annoying warnings. In all instances, investigating driver 

acceptance is recommended during later stages of product development, as well as in the field, to 

help ensure worker buy-in and support for the technology. 

Finally, a small number of applicable studies reported on the usefulness of information regarding 

CMV driver safety as contained within various databases maintained by outside agencies, for the 

purpose of providing subsequent feedback to motor carriers. Research by Lantz and Blevins 

(2002) linked individual driver conviction data from the CDLIS to employers, such that those 

motor carriers with higher (worse) “history measures” were associated with more safety 

problems, including higher out-of-service (OOS) rates, accident rates, and SAE scores. Using 

this methodology, it appears that high-risk motor carriers can be systematically identified based 

on the drivers they employ. As a practical use of such data in the field, this motor carrier history 

measure was incorporated into the Inspection Selection System (ISS) utilized by roadside 

inspectors beginning in March 2007. A second study assessed the utility of driver violation 

notification (DVN) programs, whereby states automatically inform motor carriers of changes in 

employee CDL records based on recorded violations and convictions (Smith, Owens, Stock, 

Lantz, & Murray, 2005). Support was established for an estimated economic benefit to instating 

DVN programs using cost data from three states with existing DVN-type programs. The authors 

calculated a benefit/cost ratio of $121million/$7.8 million per year (~ 16:1). Focus groups, 

interviews, and surveys provided to DVN users indicated a benefit to safety as related to the 

timeliness of reports generated by existing DVN programs. Additionally, non-users were 

enthusiastic regarding the potential for a DVN program to decrease carrier liability while 

increasing safety. These studies offer more in the way of suggestions than hard data regarding 

the safety impact of providing feedback at the motor carrier level. Nevertheless, they are a 

helpful starting point in the development of reliable, comprehensive, real-time (or at least very 

current) information dissemination systems for carriers who may use such data to improve the 

safety of their firm and employees in particular. 

Research gaps within the Haddon matrix for the second review are not as marked as those in 

Review #1. Nevertheless, literature relevant to the event and post-event stages is lacking in 

comparison to that for the pre-event stage. This may, as noted previously, simply reflect a desire 

by researchers to preemptively understand and address safety issues. Moreover, articles found in 

the pre-event stage often discuss safety-management issues and practices that can also be 

conceptualized to pertain to the event, or even post-event stages. For instance, research on 

incentive programs recommends the use of bonuses and rewards as a means of improving safe 

driving behaviors (event), yet may also be framed in terms of feedback (i.e., rewards for good 

behavior; post-event). Although crafting study placement within the matrix based on “need” 

would have resulted in a more balanced distribution of the literature, it would not have changed 

the respective findings. For this reason, where a particular study fit within the matrix was 

entirely determined based on the perceived intent of the author(s) regarding “who” results were 

geared towards (driver or motor carrier) and which focus question and stage of the event cycle 

was best addressed. 

Limitations to the Review #2 literature suggest two general caveats. The first is related to using 

crash data, especially as the sole safety outcome for a study. Although beyond the scope of this 

72
review, it is well-established that crashes are associated with a multitude of factors in addition to 

those covered in this document, including fatigue, stress, workload, time of day, medical 

conditions and health, alcohol and drug abuse, and even personality. It is, of course, impossible 

to control for all of these in any given research effort. Perhaps then, in contrast to the first 

review, it should be positively noted that a more direct link to safety outcomes was at least 

feasible for studies in Review #2. Second, with regard to reports of best practices: indeed it is 

valuable to understand what industry top performers are doing that makes them superior to other 

firms. However, this leaves much to speculation regarding what safety missteps lesser 

performing companies make, so that these pitfalls may be circumvented by others. It seems 

perhaps odd to recommend research to identify industry “worst practices;” yet for the singular 

purpose of avoiding the possibility of history repeating itself, it may be a worthwhile endeavor. 

Furthermore, information on best practices is also typically provided as groups of practices in 

which top performing companies are engaged. Not only does this make it impossible to isolate 

and evaluate the potential impact of any individual practice, but rarely are poor performing 

organizations in a position (financial or otherwise) to implement a full complement of drastic, 

costly changes. 

Findings from Trade and Industry Sources 

Safety is also reported as a prevalent concern of trade sources; however much of the information 

regarding safe driving that is published stems directly from the scientific literature and is not 

novel. The sheer volume of articles referencing the same studies annotated in this review 

suggests that, at the very least, the trucking industry is taking notice of academic safety research. 

Results from the LTCCS are noted at every turn, with emphasis on the finding that “driver 

factors were up to 10 times more prevalent than vehicle or environmental factors in events that 

led up to crashes” (as cited in McNally, 2006). A study sponsored by the American 

Transportation Research Institute (ATRI) and annotated in this document (see Murray, Dick, et 

al., 2006) was labeled a “landmark report” by Jim York, a frequent contributor to the trade 

publication Fleet Owner, due to its development of a model using past performance data to 

predict risk of future crash involvement (York, 2005). In fact, consulting firms are using the 

ideas behind the ATRI report and applying them to the driver turnover problem. FleetRisk 

Advisors is using two years worth of data on driver demographics, driver performance, company 

logistics, and financial performance to develop models to predict and rank drivers with the 

highest risk of turnover (Kilcarr, 2006). 

Despite some redundancy, it is more the case that the trade literature complements the academic 

press than detracts from it. For instance, trade publications are able to quickly disseminate 

information, such as in a recent article in Transport Topics cautioning against using cash awards 

when implementing safety incentive programs (Abt, 2006). As the author noted, cash does not 

provide long-lasting recognition to drivers, especially in comparison to material awards such as 

rings, belts, or jackets. Also, cash rewards are taxable, thus a $100 award does not translate into a 

full $100 for the driver. Because long-term motivation is important when building an incentive 

program, cash awards may not always be as good an idea as they are made to sound in the 

scientific literature. Correspondingly, this type of award quickly disappears, because it is more 

likely to be perceived as part of one’s income, rather than something extra. 

73
Additionally, experiences from the insurance industry as reported in trade sources supplement 

the literature on driver behaviors, suggesting that risky drivers are more than simply those with a 

lack of skill or inadequate training. In an interview with Peter Van Dyne, technical director for 

Liberty Mutual, he explains that “many crashes are caused by drivers’ habits and practice, not by 

their lack of technical knowledge. For example, a driver may be careless about making lane 

changes, or the use of cruise control, even though he or she knows the proper procedures” (as 

cited in Leavitt, 2005). This reinforces the notion that safety cannot simply be improved with 

more training. Often drivers possess the skill and knowledge needed to drive safely, but a bad 

habit or outside factors, such as a weak safety climate or lack of communication within an 

organization, will intervene and result in unsafe driving behaviors. 

Insurance providers also offer additional information in trade sources that would generally not be 

part of a scientific publication (as insurers are generally less involved with this literature than 

academics). An example of this type of information is an explanation for why private carriers 

benefit from lower insurance rates than for-hire fleets. Just as they typically have lower turnover 

rates than for-hire carriers, insurance providers report that private fleets are perceived as a “better 

risk” than their for-hire counterparts. The reasoning behind this risk differential reflects the 

inherent differences in how each sector operates. Greg Golden, COO for the Aon Truck Group (a 

company that provides brokerage services to the trucking industry), explains that private fleets 

“tend to exclusively carry their own goods, have more regular routes, and far fewer long, overthe-road trips, which means they are also apt to have a more stable driver work force” (as cited in 

Leavitt, 2005, p.16). Indeed, research comparing private and for-hire carriers parallels the 

assessment of insurance companies—private fleets are generally safer than their for-hire 

counterparts (Keane, Corsi, & Braaten, 2002). However, Golden also notes that “when for-hire 

carriers move toward this private carrier operating model, we [insurance companies] typically 

see their risk levels drop and their profitability improve” (as cited in Leavitt, 2005, p. 16). Again 

emphasizing a need to move toward the operating model typical of private fleets, Liberty Mutual 

reports that companies that use scheduled departure times and planned routes have fewer crashes 

and crash costs than those that do not. In addition, companies may be unintentionally 

encouraging bad and/or unsafe driving habits, such as speeding, due to poor routing, or late 

departures coupled with expectations of on-time delivery (Leavitt, 2005). 

Finally, the trade literature is useful for the anecdotal evidence it provides from various motor 

carriers and industry experts; for example, ways to effectively increase oversight while drivers 

are on-the-road. Companies that download engine control module (ECM) data at every vehicle 

service evidence 34% lower crash rates and 50% lower costs than those that do not regularly do 

so, reports Peter Van Dyne of Liberty Mutual. Because ECM data have the potential to help 

identify risky behaviors, such as extreme braking resulting from following too closely, 

companies that download these data regularly are better equipped to intervene and correct bad 

habits before they result in a crash (Leavitt, 2005). Setting up an essentially real-time scenario 

for receiving safety information in order to assist with carrier oversight, New England Motor 

Freight instated a policy requiring drivers to report crashes at the scene or from the nearest 

phone. They are also provided with disposable cameras and encouraged to take pictures at the 

scene of an accident for use in court (Atkinson, 2002). Generally, communication between 

drivers and motor carriers is viewed as key to successful oversight, particularly with respect to 

preventing incidents before they occur and handling them effectively when they do take place. 

74
Review #2 Annotations 

Pre-event 

Driver Environment: What driver-related factors affect safety? 

Belzer, M.H., Rodriguez, D., & Sedo, S.A. (2002). Paying for safety: An economic analysis of 

the effect of compensation on truck driver safety (Contract number: DTFH 61-98-C-0061). 

FMCSA.

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Compensation Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Compensation Driver

Environment

Pre-Event Event Post-Event

Author Abstract: No author abstract 

Industry Sector: Trucking 

Purpose: The purpose of this study was to thoroughly test the theory that driver 

compensation is linked to safety by using multiple datasets. The authors 

expected that compensation would be linked to safety, as quality drivers 

are attracted to jobs with higher current and expected future pay, and 

because turnover rates have been linked to both compensation and safety. 

Sample: Three separate samples were used in this study: 198 truck-load firms were 

taken from The National Survey of Driver Wages and the University of 

Michigan Trucking Industry Program (UMTIP) supplement; 11,540 

individual J.B. Hunt drivers were examined for 1 - 26 months, for a total 

observation count of 92,528 person-months; and data on 1,000 drivers, 

employed by various firms, were taken from the UMTIP survey of drivers. 

Methodology: The three data sets were analyzed separately. The first data set, which was 

used for cross-sectional analysis, gathered information regarding pay, 

benefits, and hours from the National Survey of Driver Wages and a 

supplemental UMTIP survey. The National Motor Carrier Directory and 

MCMIS provided data on the number and type of vehicles and crashes, 

respectively. This data was used to run a negative binomial regression to 

predict the number of crashes in each firm as a function of various pay 

variables and other carrier characteristics. The predictions were converted 

to elasticities, indicators of sensitivity to a change of 1% in the 

independent variables, for all significant variables. 

75
The second set of data, which came from J.B. Hunt drivers, was used for 

an individual firm, driver-level study. Data were analyzed using standard 

multivariate regression from two time periods, one before a pay increase 

and one after. 

The third set of data, which included individual drivers from a sample of 

firms, came from an UMTIP survey and was collected in two periods from 

truck stops in the Mid-West. The first period covered the Summer of 1997 

and the second period lasted from the Spring of 1998 through the Winter 

1998/99. This data was used to develop a driver supply curve. The supply 

curve indicates how many hours drivers work for a given pay rate. The 

same data was also used in a probit regression to predict the likelihood 

that a driver reported having a crash during the past year. This type of 

regression uses a dependent variable with two possible categories. In this 

example, the categories were “crash occurs” or “crash does not occur.” 

The model shows the probability that a driver will experience, or not 

experience, a crash based on the independent compensation, demographic, 

and operating variables. 

Relevant Findings: The cross-sectional analysis showed a nearly one to one relationship 

between the compensation variables and crash probability. For every 10% 

increase in average driver compensation (including benefits and 

anticipated raise), the carrier experienced 9.2% less crashes. The presence 

of a safety bonus was also a significant variable. 

Analyses of the J.B. Hunt data corroborated findings from the crosssectional data. Drivers who experienced a pay raise, or were paid a higher 

base rate, evidenced a reduction in their crash probability. Findings also 

showed that driver crash risk decreases until the age of 41, and again 

increases thereafter. Safer drivers were also shown to have driven more 

miles and to have longer tenure at the firm than less safe drivers. 

Additionally, safe drivers were identified, generally, as non-married. The 

data showed a decrease in crash risk for all drivers over time when all 

compensation and demographic variables were held constant. 

The supply curve derived from analysis of the multi-firm, driver-level data 

showed that the leisure and income preferences of drivers were consistent 

with the prevailing economic theory, which postulates that workers, at 

first, respond to a higher wage rate by working longer hours in order to 

achieve a higher income. However, at higher levels of pay, the income 

becomes sufficient enough that workers feel comfortable seeking more 

leisure time. The shape of the supply curve showed that, at pay rates 

below 31.4 cents per mile, drivers worked longer hours. For rates above 

31.4 cents per mile, drivers worked fewer hours, choosing leisure time 

over the extra income. 

76
Probit regression results evidenced pay rate and paid time off as the only 

two significant variables to reliably predict a decrease in crash probability. 

Taken together, the three analyses and data sets show that current 

compensation and increases in compensation both have a negative 

relationship with crash rates. Crash rates decrease when compensation 

increases, although demographic variables also account for some of the 

differences in crash rates among drivers. 

Limitations: The series of studies described in this report suggest strong support for the 

existence of a relationship between compensation and safety. However, 

the underpinnings behind such a relationship remain unclear. Future 

research should continue to examine the mechanisms that explain why 

compensation and safety are related. What is clear is that targeting driver 

compensation may be an effective way to improve driver safety in the 

trucking industry. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for the Haddon Matrix #2: Compensation. Although compensation 

policies are set by motor carriers, this study evaluates how drivers behave 

and respond to different pay rates and raises. 

77
Blower, D.F. (1996). The accident experience of younger truck drivers (GLCTTR Publication 

No. 81-96/1). Michigan University, Transportation Research Institute; Trucking Research 

Institute 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

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Driver Age Driver

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Driver Age Driver

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Author Abstract: The purpose of this project is to identify the special problems related to 

the high accident involvement of younger truck drivers and to suggest 

possible countermeasures. In this project, younger drivers are those in the 

18-21 age group and the older drivers selected for comparison are ages 30-

49. The project consisted of a driver survey, analysis of traffic violations, 

analysis of the accident record, and examination of police reports covering 

selected accident types. 

Driver records and accident data from Michigan were used primarily. The 

survey was done on Michigan CDL holders. Accident data from North 

Carolina supplemented the Michigan data, and police reports from both 

Michigan and North Carolina were reviewed. 

Young drivers had significantly more traffic violations than older drivers, 

with higher proportions of unsafe speed, reckless/careless, and failure to 

yield violations. Accident types with significant younger driver 

overinvolvement included single vehicle loss of control, rear end truck 

striking, and truck backed into other. Case review of accident reports 

showed problems with following too closely; failure to anticipate the 

actions of other road users; problems with vehicle control, as in low speed 

offtracking accidents; and possible attentional overload, as in some loss of 

control accidents. 

Industry Sector: Trucking 

Purpose: The purpose of this study was to assess differences between younger and 

older truck drivers in an attempt to explain why younger truck drivers are 

more likely to be involved in accidents. 

Sample: Male holders of Class A or B CDLs in Michigan between the ages 18–24 

or 30–49; 4,689 drivers were mailed surveys and over 2,000 responded. 

78
Methodology: This project involved a number of related research efforts, including a 

driver survey, analysis of driver history files, analysis of accident records, 

and a detailed examination of individual police-reported traffic accidents. 

The driver survey was designed to obtain basic information about CDLholders. Participants were asked if they actively use their CDL, what types 

of training they have received, the type of truck they drive, and the type of 

firm for which they drive. Driver history files were used to provide 

detailed information about accident and violation records. Accident files 

provided more information about trends in types of accidents, while the 

individual police reports allowed the researchers access to specific details 

about the circumstances surrounding accident occurrence. 

Drivers were divided into three age groups for analysis purposes. The 

group of “younger drivers” consisted of drivers between the ages of 18 

and 21. A second group of younger drivers, aged 22 to 24, was included 

because drivers aged 22 to 24 were expected to share similar 

characteristics with the youngest group of drivers. Finally, the comparison 

group of “older drivers” included drivers between the ages of 30 to 49. 

Relevant Findings: In comparison to older drivers, younger drivers typically drove 30% fewer 

miles, drove less at night, and were more likely to work for intrastate firms 

and firms operating fewer trucks. Younger truck drivers were more likely 

to have experienced a moving violation in the past three years (56% 

compared with 29% for older drivers), were twice as likely to be cited for 

unsafe speed (8.2% compared with 4.8% for older drivers), and were more 

likely to be cited by the police when involved in a traffic accident (70% 

compared with 55% for older drivers). 

Analysis of driver accident records and case studies revealed a number of 

common themes in accidents involving younger truck drivers. Younger 

drivers most often exhibited: excessive and unsafe speed; overly 

aggressive driving, as in following other vehicles too closely; failure to 

anticipate and provide for the unexpected actions of other road users, as in 

both rear-end and backing accidents; failure to maintain proper vehicle 

control, as in low-speed turning and backing accidents; and possible 

attention overload, as in loss of control accidents. 

Although evaluating the means to effectively address the problems of 

younger truck drivers is outside the scope of this study, the authors 

suggest increasing practical, real-world training for younger drivers, with 

special attention given to aggressive driving, accounting for the actions of 

other road users, and basic vehicle control. 

Limitations: This study only examined male truck drivers, more research is necessary 

to examine differences between male and female truck drivers, especially 

in the younger age group. 

79
Although particular interest is often devoted to truck drivers under the age 

of 21, the relatively small population of younger truck drivers made it 

necessary to expand the sample of younger drivers to those aged 18 to 21 

and, in some cases, aged 18 to 24. 

Finally, more research is necessary to determine if and what types of 

training can effectively reduce accident involvement for younger truck 

drivers. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Age, as it focused on factors related 

specifically to younger drivers who had been involved in accidents. 

80
Goodwin, D. (1996) Single vehicle accidents: A fleet insurer’s perspective. F. Saccomanno & J. 

Shortreed (Eds.), Truck safety: Perceptions and reality (pp. 59–72). University of Waterloo: 

Institute for Risk Research. 

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Author Abstract: Single vehicle accidents (SVAs) involving tractor-trailers pose significant 

risks to all users of the highway, result in financial losses and may receive 

hysterical media coverage to the detriment of the trucking industry. 

This study considers fleet operating and driver characteristics as well as 

environmental and road conditions for 40 SVAs reported by 27 Canadian 

trucking firms April 1989 to April 1990. It identifies the major factors that 

contribute to the SVAs and provides recommendations for future 

improvements in trucking safety. Inadequate driver selection, indifferent 

supervision, and poor driver training appear to be reliable predictors for 

SVA involvement. 

Industry Sector: For-hire trucking in Canada 

Purpose: The purpose of the study was to inform motor carriers and insurers of 

factors that can lead to higher rates of SVA involvement. 

Sample: Truck drivers employed by 27 firms and involved in 40 SVAs where the 

trailer was either severely damaged or demolished beyond repair, as 

reported by a large Canadian fleet insurer. 

Methodology: This study considered fleet operating and driver characteristics as well as 

environmental and road conditions for 40 SVAs reported by 27 Canadian 

trucking firms between April 1989 and April 1990. Factors of interest 

contributing to the SVAs were classified into three categories: operating 

characteristics, environmental and road conditions, and driver 

characteristics. The categories were analyzed for frequency of occurrence 

and compared to the distribution of the characteristics of the entire 

available driver force and motor carrier population. 

Relevant Findings: Driver age was not found to be a significant factor in explaining the 

frequency of SVAs. However, drivers under the age of 24 tended to be 

involved in more severe crashes. Drivers with less than seven years of 

commercial driving experience were responsible for more than half of the 

81
SVAs in the sample. On average, new employees had experienced an SVA 

within the first five months of driving for a company. Many of the new 

hires had multiple recorded accidents or violations with previous 

employers, or were not investigated by employers prior to hire. 

The authors recommend that a standard be developed for classifying 

accident circumstances, using on-board monitoring devices for data 

collection. They also recommend that motor carriers employ driver 

trainers to evaluate drivers pre-employment and perform training after 

hire. Driver performance evaluations should be on-going. 

Limitations: The sample size of 27 firms is small and the time period of analysis from 

April 1989 to April 1990 may be outdated. Furthermore, SVAs accounted 

for only 2.2% of all trucking accidents in 1990. Thus, the findings of this 

study may not be applicable to the entire trucking industry. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for the Haddon Matrix #2: Driver Characteristics, because the authors 

sought to extract specific driver characteristics that were linked to higher 

rates of involvement in SVAs. 

82
Llaneras, R.E., Swezey, R.W., Brock, J.F., Rogers, W.C., & Van Cott, H.P. (1998). Enhancing 

the safe driving performance of older commercial vehicle drivers. International Journal of 

Industrial Ergonomics, 22, 217–245. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Age 

and Abilities

Driver

Environment

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Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

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Driver Age 

and Abilities

Driver

Environment

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Author Abstract: This research effort involved investigations of fifteen human abilities, 

their changes which occur with aging, and their effects upon commercial 

truck driving performance. One-hundred and seven commercially licensed 

truck drivers, divided into five age cohort groups, participated in the 

research study. An ability testbed, consisting of laboratory-based 

assessment devices, was used to measure 15 driving related perceptual, 

cognitive, and psychomotor abilities. The influence of these functional 

abilities on driving performance was assessed using an interactive 

commercial truck driving simulator. Relationships between perceptual, 

cognitive, and psychomotor abilities and measures of driving performance 

indicated that functional levels on these tasks and driving performance are 

significantly related. How well drivers performed on a number of ability 

tests was predictive of driving performance. However, age, in and of itself, 

was not predictive of driving performance. Interventions designed to target 

ability deficiencies were also developed and evaluated during the course 

of this effort. Four interventions, consisting of three in-vehicle 

compensatory aids and a single driver training program, were used in the 

study. The degree to which the interventions enhanced, or otherwise 

influenced driving performance was examined by contrasting performance 

with versus without the interventions. Results indicated that all four 

interventions led to enhanced performance. 

Industry Sector: Trucking 

Purpose: The primary objective of this research was to identify and reduce risks 

associated with older commercial drivers, thereby enabling this growing 

segment of the population to continue to effectively contribute to the 

workforce, while ensuring safe and productive driving. To meet this 

objective, a series of empirical research analyses was conducted. These 

were designed to: (1) examine the effects of increasing age on perceptual, 

cognitive, and motor abilities by collecting data on ability measures that 

have been shown to be related to driving; (2) investigate the effects of 

diminished abilities on direct measures of driving performance in order to 

determine how age-related ability deterioration affects performance in 

83
commercial vehicle driving; and (3) evaluate methods of compensating for 

age-related ability changes through vehicle design changes, and/or 

training-related interventions. 

Sample: 107 commercially licensed truck drivers. 

Methodology: This study examined important driving-related perceptual, psychomotor, 

and cognitive abilities associated with commercial vehicle driving. Ability 

scores were derived from context-free (i.e., non-driving) tests 

representative of the driving task and were related to age and to driving 

performance. This approach enabled the researchers to determine the 

independent effects of each ability on driving performance, as well as 

provide a way to compare the relative importance and contributions of 

each ability to overall driving performance and to particular driving 

maneuvers and tasks. Interventions designed to target ability deficiencies 

common among older commercial vehicle drivers were also developed 

and evaluated. Four interventions designed to mitigate age-related 

problems were evaluated by measuring driver performance, under 

controlled conditions, with and without the presence of these 

interventions. A between-subjects design was used to assess the effects of 

these interventions; subjects assigned to an experimental group received 

all four interventions, while those in the control group were not exposed to 

any countermeasures. Thus, two grouping factors were incorporated into 

the design: Age, expressed across five age groups (under 50, 50–54, 55–

59, 60–64, and 65 and older), and interventions, captured by the 

experimental vs. control group distinction. 

Investigations among 15 human abilities, their changes that occur with 

aging, and their effects on commercial truck driving performance were 

conducted during this study. Perceptual ability measures included static 

visual acuity, dynamic visual acuity, contrast sensitivity, useful field of 

view, field dependence, and depth perception. Cognitive ability measures 

consisted of decision-making, selective attention, information processing, 

and attention sharing. Psychomotor ability measures included reaction 

time, multi-limb coordination, control precision, tracking, and range of 

motion. The influence of these perceptual, cognitive, and psychomotor 

abilities on driving performance was assessed using the TT150 

Professional Truck Driving Simulator. Simulator-based driving 

performance variables collected automatically included lane position, gear 

shifting performance, speed maintenance, and time to complete course. 

Two trained observers documented driving-related behaviors (e.g., mirror 

checks, search, speed control, lane position, etc.) at different junctions and 

various sections of the simulated driving course. In addition, the observers 

also rated each driver’s performance across seven distinct categories, 

including an overall index of driving performance, using a five-point 

rating scale ranging from poor to excellent. All participants drove a 

84
standardized 10-mile course that included a variety of road conditions and 

driving tasks. 

Data analyses were structured to address three basic issues: (1) 

relationships among the various ability measures and age; (2) relationships 

among the various perceptual, cognitive, and psychomotor abilities and 

driving performance; and (3) the effectiveness of specific interventions. 

Analytical techniques included independent Analysis of Variance 

(ANOVA), bivariate Pearson correlations, and stepwise linear regression. 

Relevant Findings: Results relating perceptual abilities to age showed that each of the six 

measured abilities tended to deteriorate with advancing age. Drivers in the 

65 and older age category had significantly poorer static visual acuity, 

dynamic acuity, contrast sensitivity, useful field of view, field 

dependence, and depth perception compared to drivers below age 50. With 

regard to cognitive abilities, the results indicated that drivers 65 and older 

showed significant deterioration in decision-making, selective attention, 

information processing, and attention sharing abilities compared to drivers 

in all other age groups, particularly the below age 50 group. Results of the 

relationship between psychomotor abilities and age showed drivers under 

age 50 outperformed drivers age 65 and older in tasks requiring control 

precision, tracking, and range of motion. Drivers 65 and older also showed 

significant impairment in the ability to accurately position controls quickly 

and the ability to track objects. No significant differences were found 

among the age groups in terms of simple reaction time. In summary, 13 of 

the 15 abilities tested were found to degrade with age on the basis of one 

or more of the analyses. It was noted, however, that although an 

overwhelming number of perceptual, cognitive, and psychomotor abilities 

were found to exhibit age differences, the degree of deterioration was not 

the same for all measured abilities. 

Correlations between age and driving performance revealed that 10 of the 

24 driving performance aspects measured showed significant age 

relationships; two correlations indicated that driving performance actually 

improved with increasing age. Specifically, older drivers tended to have 

better lane position and fuel mileage than younger drivers. The remaining 

significant relationships were in the expected direction, suggesting that 

advancing age is associated with poorer driving performance. As indicated 

by these results, age appears to be associated with some aspects of driving 

performance. However, given that chronological age is also strongly 

related to perceptual, cognitive, and psychomotor abilities, it would be 

misleading to suggest that age, in and of itself, is directly contributing to 

poor driving performance. This issue was addressed by regressing age and 

ability scores on driving performance. Results of this analysis provided 

strong support indicating that driving-related abilities, not chronological 

age, were critical determinants of driving performance. Age appeared to 

85
indirectly influence driving by affecting basic functional abilities that are 

related to driving. Consequently, age alone has not been found to be a 

reliable indicator of driving performance; it appears to function as a 

moderator variable. 

The degree to which the interventions used in this study enhanced, or 

otherwise influenced, driving performance was also examined. Data 

generated from this study indicated that interventions might prove to be 

effective strategies for dealing with declines in driving-related abilities. 

For example, deteriorating range of motion, control precision, and tracking 

ability suggested that older commercial vehicle drivers might benefit from 

automatic transmissions (though the benefits associated with automatic 

transmission are not limited to older drivers). Also, auditory warning 

systems offer the capability to further reduce visual demands associated 

with driving. Although the majority of past studies have emphasized 

vehicle and roadway accident countermeasures, this research indicated 

that countermeasures designed to influence the driver directly via trainingoriented interventions (e.g., driver education, physical therapy, etc.) might 

also be an effective strategy for combating age-related ability deficiencies. 

Limitations: Given the nature of the study and the requirement for strict environmental 

controls, driving performance was assessed in a commercial vehicle 

driving simulator. While this approach maximized the study’s internal 

validity, it also limited its external validity, making it difficult to 

generalize the findings to actual on-road vehicle driving environments. 

Time and resource constraints also led the researchers to expose each 

driver in the experimental group to all four driving countermeasures. 

Therefore, interventions were not manipulated independently, making it 

difficult to determine the specific effects associated with a given 

intervention. Despite these concerns, the researchers pointed out that the 

results obtained in this study were consistent with many earlier on-theroad studies of older automobile drivers’ performance. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Age and Abilities, because the researchers 

were concerned about how perceptual, cognitive, and psychomotor 

abilities change with advancing age, what abilities are important to 

driving, and how results generalize to the commercial driving domain. 

86
Mayhew, C. & Quinlan, M. (2006). Economic pressure, multi-tiered subcontracting and 

occupational health and safety in Australian long-haul trucking. Employee Relations, 28, 

212-229. 

Haddon Matrix for Review #2: Improving Driver Safety

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Driver

Environment Driver Characteristics

Motor Carrier 

Environment

Author Abstract: Purpose—The purpose of this research is to analyze the relationship 

between economic pressure, multi-tiered subcontracting and occupational 

safety and health (OSH) outcomes for employee and owner/drivers in 

long-haul trucking, using Australian evidence. 

Design/methodology/approach—The analysis is based on direct 

interviews with 300 long-haul drivers, using a structured questionnaire 

along with an examination of documentary records, statistics and 

government reports. Qualitative and quantitative data were gathered on 

self-reported acute and chronic injuries, the incidence of occupational 

violence, truck crashes, indicators of illicit drug use, hours of work/fatigue 

and psychological distress. 

Findings—Variations between owner/drivers and employees working for 

small and large firms were investigated. Overall, owner/drivers reported 

worse OSH than small fleet and, more especially, large fleet drivers. 

Evidence also indicated a connection between economic pressure, the 

expansion of contingent work [the use of self-employed subcontractors or 

owner-operators] and negative OSH outcomes. 

Research Limitations/implications—Further longitudinal and 

comparative research is needed to test the hypothesized link between 

competitive pressures, supply chain rationalization and OSH outcomes. 

Research to investigate these issues in other countries is required in order 

to compare findings with those for Australia and to assess the 

effectiveness of new enforcement initiatives. 

Practical implications—Findings suggest the need for policy 

interventions aimed at improving OSH to address commercial practices, 

including elaborate subcontracting chains, more explicitly than is currently 

the case with road transport regulation. Recent moves in this direction are 

identified. 

Originality/value—Unlike manufacturing, healthcare and the public 

sector, there have been few studies of the OSH effects associated with 

contingent work arrangements in transport. In addition to helping to gill 

this gap the paper provides evidence on the effects of competitive pressure 

and supply chains on work practices and OSH. 

87
Industry Sector: Long-haul trucking in Australia 

Purpose: The purpose of this study was to demonstrate the effect of increasing 

competition and supply chain dependencies on the OSH of truck drivers. 

The authors emphasize the OSH research approach and concern with 

overall driver well-being, as opposed to the more commonly used roadsafety approach, which focuses on truck related accidents. 

Sample: 300 long-haul drivers. 

Methodology: The authors interviewed 300 long-haul drivers over the course of 2 months 

in 2000. The sample contained owner-operators, small carriers with less 

than 20 vehicles, and large carriers with more than 20 vehicles. The three 

types of carriers are represented in almost equal numbers. The survey 

included closed and open ended questions on acute and chronic injuries, 

occupational violence, truck crashes, illicit substance abuse, hours of 

work, fatigue, and levels of stress as measured by the General Health 

Questionnaire. The survey yielded both quantitative and qualitative data. 

Relevant Findings: One in four drivers reported suffering from acute or chronic injuries, a 

number much higher than the percentage of drivers filing worker 

compensation claims. Owner-operators were less likely to treat or take 

time off for their injuries, the majority citing financial pressures as the 

reason. Drivers working for large firms felt more secure about reporting 

injuries and being able to take time off for them. 

About half the drivers experienced verbal abuse or threats on the job, the 

majority from other motorists, but some from customers or loading dock 

employees. A total of 12.5% of the owner-operators, 10.1% of small 

company drivers, and 5.9% of large company drivers reported having been 

involved in an accident over the past 12 months. Large company drivers, 

however, reported a higher occurrence of minor crashes that did not 

necessitate taking time off from driving. Large company drivers reported 

being fatigued less frequently than small company drivers or owner 

operators. They also reported greater compliance with log-book 

requirements. 

Twenty-three percent of drivers reported either using or having observed 

others use illicit substances, especially amphetamines. Forty percent 

reported working longer than the legal limit of 72 hours per week. Owner 

operators were more likely to ignore HOS regulations. Drivers 

consistently scored above the normal baseline on the health questionnaire, 

and owner-operator scores were twice as high as that of employee drivers. 

High scores on the health questionnaire indicate that driver physical and 

mental well-being is significantly worse than that of the general 

88
population. The drivers with the highest level of stress overwhelmingly 

indicated financial pressures as the leading cause. 

Limitations: The findings of this paper may only be applicable to Australian motor 

carriers. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Characteristics because it reports 

differences in driver well-being and accident rates for different types of 

truck drivers. 

89
McCall, B.P. & Horwitz, I.B. (2005). Occupational vehicular accident claims: A workers’ 

compensation analysis of Oregon truck drivers 1990–1997. Accident Analysis & Prevention, 

37, 767-774. 

Haddon Matrix for Review #2: Improving Driver Safety

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Author Abstract: This study used workers’ compensation data from Oregon from 1990 to 

1997 to examine workers’ compensation claims from vehicular accidents 

by truck drivers, and to calculate claim rate estimates using baseline data 

derived from the US Bureau of Census’ Current Population Surveys. 

During this period, 1168 valid injury claims due to vehicular accidents 

were filed representing an accident claim rate of 50.3 (95% CI: 45.1-55.5) 

per 10,000 truck drivers annually. There were 19 work-related vehicular 

accident fatalities recorded in the data over the 8-year period. Of all 

claimants, males constituted the majority (80.7%), most were 35 years of 

age or younger (51.4%) and had less than 1 year of job tenure (51.0%). 

Truck driver claim rates due to vehicular accidents were lowest during the 

6 a.m. to 12 p.m. period. The average amount of compensable lost work 

days per injury claim was 57.8 days (SD = 124.7) and the median claim 

time was 16.0 days with the inter-quartile range being 53.5 days. The 

amount of lost work reported increased with the claimant’s age. A total of 

US$ 11,642,635 was paid in claims for vehicular accidents of truck drivers 

in Oregon over the time examined, which averaged US$ 9966 per claim, 

with a median claim amount of US$ 2590 and inter-quartile range of US$ 

7670. Claims citing sprains were the most frequently recorded injury 

experienced from vehicular accidents. 

Industry Sector: Trucking 

Purpose: The purpose of the study was to analyze the characteristics of risky drivers 

and the causes of truck accidents using a large population of drivers. 

Sample: 1,168 accepted injury claims. 

Methodology: The study analyzes all injury claims due to vehicular accidents filed by 

truck drivers in Oregon for the years 1990-1997. Claims data included the 

age and gender of drivers, time of day and day of the week of the accident, 

precipitating events, and injuries and compensated days of lost work. 

Census’s CPS was used to establish a baseline of the number of people 

employed as truck drivers in Oregon. In addition, the CPS Work Schedule 

90
Supplement Survey provided data on the time of day and day of the week 

worked by a sample of all U.S. truck drivers. The schedule data was used 

to establish a baseline for Oregon drivers, as they were not found to be 

statistically different from the general population of U.S. drivers. 

Although the data was adjusted for the number of truck drivers working 

during each time of the day and each day of the week, the data was not 

adjusted for overall traffic volumes. 

Relevant Findings: The majority of the claims were filed by drivers under 35 years of age, 

with drivers under 25 filing 19.5% of the claims, although they constituted 

only 8.5% of all Oregon truck drivers during that time period. Although 

women constitute just over 5% of the truck driver population in Oregon, 

19.3% of claims were filed by women. Women, however, had shorter time 

away from work and less expensive claims because on average the female 

drivers in this sample experienced less severe accidents than the male 

drivers. The difference in severity may be explained by possible 

differences in truck types driven by men and women, though no specifics 

on vehicle types were provided. Fifty-one percent of drivers who filed 

claims had tenure of less than one year. Only 9% of the accidents occurred 

at night, with another 9% in the evening. The highest number of accidents 

occurred during the third hour of work, and the fewest number of injuries 

occurred on the weekends. The number of lost days of work increased 

with age, such that those under the age of 25 lost an average of 41.9 days, 

while individuals over 65 lost an average of 87.0 days. 

Limitations: The number of worker compensation claims likely underestimates the total 

number of truck accidents, particularly less serious accidents. 

The data excluded owner-operators. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Characteristics. The study used workers’ 

compensation claims to analyze the characteristics of risky drivers. 

91
a

Monaco, K. & Williams, E. (2000). Assessing the determinants of safety in the trucking 

industry. Journal of Transportation and Statistics, 3, 69–79. 

b

Williams, E., & Monaco, K. (2001). Accidents and hours-of-service violations among over-theroad drivers. Journal of the Transportation Research Forum, 40, 105–115. 

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Driver Characteristics Driver

Environment

Pre-Event Event Post-Event

Author Abstract: a

Using data from the 1997 Survey of Drivers conducted by the University 

of Michigan Trucking Industry Program, we identify the factors which 

substantially affect three safety measures: accidents, moving violations, 

and hours of service violations. The variables used include both 

operational characteristics (firm size, trailer type) and personal 

characteristics (age, race, union status). Using both basic descriptive 

statistics and probit estimation, we find that the variables that have the 

most impact on the three safety measures are operational in nature, not 

individual characteristics. 

 bUsing data from the 1997 UMTIP’s Survey of Drivers, we estimate 

models of driver accidents and compliance with hours-of-service 

regulations. We find links between these safety measures and the 

economic conditions of truck drivers. Drivers who drive more miles have 

a greater likelihood to be involved in accidents and to violate the federal 

Hours of Service (HOS) regulations. Rate and method of pay are also 

significant across the models estimated, suggesting that drivers who are 

under more economic pressure are more likely to violate regulations and 

to be involved in accidents. 

Industry Sector: Trucking 

Purpose: a

The purpose of the Monaco and Williams (2000) paper was to examine 

how various individual and work-related driver characteristics influence 

driver safety. In addition, statistical estimation techniques were used to 

assess the relative impact of each of these characteristics. 

 bThe Williams and Monaco (2001) paper primarily focused on the 

development of models of driver accidents and compliance with HOS 

regulations using an updated database and similar estimation techniques as 

described in the 2000 article. The authors sought to examine the extent to 

92
which demographic and occupational characteristics predict the 

occurrence of accidents and HOS violations. 

Sample: abMore than 900 truck drivers were surveyed as part of the UMTIP Survey 

of Drivers. 

Methodology: abData were collected from truck stops in the Upper Midwest (Ohio, 

Indiana, Illinois, Michigan, and Wisconsin) throughout 1997 and 1998. 

The Monaco and Williams (2000) paper used data collected in 1997, and 

the Williams and Monaco (2001) paper used data from an updated UMTIP 

database which included information from 1997 and 1998. 

 aFor this study, probit regression models were used to estimate the 

probability of accidents, moving violations, and logbook violations given 

various driver and operational characteristics. A probit modeling 

technique is used in cases where the dependent variable is dichotomous. In 

the current study, all three dependent variables were recorded as a yes or 

no response. Each driver reported whether he/she had: 1) been involved in 

an accident reported to the police while on duty in the last 12 months (i.e., 

accident involvement), 2) been cited for a moving violation while on duty 

in the last 12 months (i.e., moving violations), and 3) worked more than 

he/she had logged in the last 30 days (i.e., logbook violations). For each of 

the three questions, an affirmative response was recorded as a value of one 

in the model estimation, and a value of zero was recorded otherwise. The 

driver characteristic variables included in the models were gender, 

education level, race, ethnicity, veteran status, union status, marital status, 

job tenure, occupational experience, driver training, trailer configuration, 

mileage in the last 24 hours, sleep in the last 24 hours, and a calculated 

mileage pay rate. 

 bIn the later study, probit regression models were again tested to determine 

whether driver and/or firm characteristics explain the probability of 

accident involvement (as defined in the 2000 study) and HOS violations 

[Reviewer note: same as the definition for “logbook violations” in the 

2000 study]. 

Relevant Findings: a

Descriptive analyses revealed that 15% of the sample reported having 

been involved in an accident, 30% reported having received a moving 

violation, and 58% reported having worked more than they logged in the 

last 30 days. Descriptive analyses of driver characteristics showed that 

white drivers and drivers with less than one year experience reported the 

highest percentage of accidents (16% and 28%, respectively, versus 15% 

for the rest of the sample). Drivers paid by percentage of revenue, 

primarily owner-operators, reported a higher than average percentage of 

accidents, moving violations, and logbook violations (18%, 38%, and 

63%, respectively) than those paid by the mile. Drivers who reported zero 

93
hours of sleep in the last 24 hours were also more likely to have been 

involved in an accident in the past year (28% versus 15% for the rest of 

the sample). 

Accident Involvement: aThe probit estimation model of accidents revealed that work-related 

driver characteristics were more likely to be related to accident 

involvement than demographic characteristics. Pay rate, method of 

payment, firm size, region, and source of training were all significant 

work-related predictors of accidents. Marital status was the only individual 

characteristic significantly related to accident rate. For pay rate, results 

suggested that a $0.10 increase in the rate paid per mile would decrease 

the probability of being involved in an accident by 1.76%. In addition, 

drivers paid by the hour were 10.2% less likely to have been involved in 

an accident than those paid by the mile or percentage of revenue. Drivers 

at firms with 1,000 to 4,999 employees were 11% less likely to be 

involved in an accident than drivers at firms with less than 25 employees. 

The authors suggest that this result may indicate that large trucking firms 

are succeeding in their long-asserted commitment to safety. Northeast and 

Mid-Atlantic drivers were significantly more likely to have been involved 

in an accident (56% and 21%, respectively) than those working in the 

Upper Midwest. This regional finding is consistent with driver reports that 

driving on the East coast can be more hazardous than other areas, probably 

due to population density and greater road congestion. Drivers who 

received training through a trucking company program were 14% more 

likely to have been involved in an accident than those who learned on-thejob. Unfortunately, it is unknown what type of training (e.g., novice, 

advanced skills, classroom, etc.) drivers received through their company 

versus the training drivers received on the job, and whether or not they 

remained at the company that trained them. Finally, drivers categorized as 

separated, divorced, or widowed were 8.9% less likely to have been 

involved in an accident than drivers categorized as single.

 bRate and method of pay were again found to be significant predictors of 

accident involvement in the follow-up study. Drivers who are paid more 

per mile and those who are paid by the hour, rather than by the mile, are 

less likely to be involved in an accident. In fact, for every additional 100 

miles driven per day, the likelihood of being involved in an accident 

increased by 1.6%. 

94
Moving Violations:

 aUnion members, drivers at larger firms, and drivers who learned to drive 

a truck at a private trucking school were significantly less likely to have 

received a moving violation in the last 12 months. Drivers at smaller 

firms, owner-operators, drivers who drove more miles in the last 24 hours, 

and drivers who learned to drive at a public or technical school were all 

more likely to have received a moving violation. Although it is an 

important distinction, the authors did not define the differences between 

public and private trucking schools. Those who responded to the survey 

were simply asked to check off where they received training on a list of 

possible places. 

Logbook Violations:

 aDrivers who reported getting greater amounts of sleep in the last 24 

hours, hauling a dry van trailer, driving more miles per year, being paid by 

the hour, and being black or female were less likely to report logbook 

violations. Drivers who graduated college or had some college experience 

were more likely to report that they drove more than reported in their 

logbooks than high school graduates. In addition, married drivers were 

more likely to report logbook violations than single drivers. 

 bThe Williams and Monaco (2001) study found similar results for logbook 

violations in their model of HOS violations. White drivers and owneroperators were more likely to report logbook violations. In addition, 

results suggested that driving 100 more miles in a day may increase the 

probability of logbook violations by 2.6% and sleeping one additional 

hour may decrease the probability of logbook violations by 3.6%. 

Limitations: The authors used an archival dataset, so there is very little information in 

either article concerning how the data was collected. It is clear that all data 

were self-report. Thus, there is some concern that drivers may not have 

accurately reported their involvement in accidents, moving violations, 

and/or logbook violations due to a social desirability bias (e.g., “They will 

think I am a bad driver if I tell the truth”) or fear of repercussions for rule 

violations. It is also important to note that most of the results were 

reported in a descriptive nature, thus more explanation is needed to 

identify why some of the occupational characteristics identified predict 

accident, moving violation, and/or logbook violation occurrence. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Characteristics, as it evaluated how various 

individual and work-related characteristics influence driver safety and, 

specifically, accident rates. 

95
Murray, D.C., Lantz, B., & Keppler, S. (2006) Predicting truck crash involvement: Developing a 

commercial driver behavior model and requisite enforcement countermeasures. 

Transportation Research Board 85th Annual Meeting Washington, D.C.: Transportation 

Research Board. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Characteristics Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Characteristics Driver

Environment

Pre-Event Event Post-Event

Author Abstract: The majority of prior research and analysis, including the Federal Motor 

Carrier Safety Administration Large Truck Crash Causation Study 

(LTCCS) points toward driver-related factors as the main cause of most 

commercial vehicle-related crashes. Therefore, in order to have the most 

profound impact on the number of crashes, more must be done to 

understand and mitigate the driver behaviors which lead to crashes. 

To do so, the American Transportation Research Institute (ATRI) 

conducted this research to identify a driver performance-based model for 

predicting future crash involvement based on prior driver history. ATRI’s 

research team included North Dakota State University Upper Great Plains 

Transportation Institute (NDSU/UGPTI) and the Commercial Vehicle 

Safety Alliance (CVSA). 

The analysis identifies eight moving violations as significant with an 

associated crash likelihood increase between 21 and 325 percent. Four 

driver violations were identified as having a significant associated crash 

likelihood increase between 18 and 56 percent. Twelve convictions were 

significant with an associated crash likelihood increase between 24 and 

100 percent. Drivers with a past crash were found to have an increased 

likelihood of a future crash of 87 percent. 

In order to address the driver behaviors identified, successful enforcement 

strategies were identified through interviews and surveys with CVSA 

members. The CVSA work identified “top-tier” states as those having 

more traffic enforcement and lower crashes, and from those states, 

recommended practices have emerged including: focusing on both truck 

and car driver behavior patterns; conducting highly visible enforcement 

activities; using a performance-based approach to identify specific crash 

types, driver behaviors and locations; and, conducting covert enforcement 

activities. 

Industry Sector: Trucking 

96
Purpose: The purpose of this research was to determine whether an overall driver 

performance-based indicator can be developed that will have the ability to 

predict accident likelihood. In addition, the research identified the types of 

driver violations or convictions that are more highly correlated with future 

crash involvement. The two major goals were to: design and test a model 

for predicting future crash involvement based on prior driver history 

information; and, in conjunction with the CVSA, identify effective 

enforcement countermeasures to address and alleviate the driving 

behaviors and events that were shown to be predictive of future crash 

involvement. 

Sample: 586,894 CMV drivers for the initial statistical analysis, of which traffic 

conviction data were available for 540,750. 

245,467 CMV drivers for the predictive regression analysis. 

Methodology: Data sources for the analysis included the MCMIS and the CDLIS. The 

main dependent variable in the model was crash involvement, which was 

also considered the objective measure of driver safety. The independent 

variables were driver-specific performance indicators mined from 

available data, including specific violations discovered during roadside 

inspections, driver traffic conviction information, and past crash 

involvement information. Driver data were gathered across a several-year 

time frame, and analyzed across years to determine future crash 

predictability. Appropriate statistical tests, including chi-square analyses, 

were used to assess whether a significant difference existed in future crash 

rates for drivers based on past inspection, conviction, and/or crash 

information. In addition, logistical regression was used to develop a 

predictive model with the prior crash status of each driver as the nominal 

(non-continuous) dependent variable. 

In order to identify effective enforcement countermeasures, a survey was 

distributed to 51 enforcement jurisdictions to identify how enforcement 

agencies address overall CMV driver behavior and performance issues. A 

targeted survey was later distributed to those states that had been 

identified as having a higher level of CMV traffic enforcement and a 

lower level of crashes. The primary purpose of this targeted survey was to 

identify preliminary enforcement strategies and best practices among 

states that appear to be proactive in conducting traffic enforcement and 

achieving positive results. 

Relevant Findings: Statistical analysis of the data showed that the two violations associated 

with the highest increase in likelihood of a future crash were reckless 

driving and improper turn violations. When a driver was cited for one of 

these violations, their likelihood of having a future crash increased 325% 

97
and 105%, respectively. Both log book (i.e., false or no log book entry) 

and disqualified driver violations were associated with more than a 50% 

increase in the likelihood of a future crash. An HOS violation and a 

medical certificate violation were found to increase crash likelihood 41% 

and 18%, respectively. 

The four convictions associated with the highest likelihood of a future 

crash were improper or erratic lane changes; failure to yield right of way; 

improper turn; and failure to keep in proper lane. Drivers convicted of one 

of these types of convictions increased their likelihood of a future crash 

91% to 100%. Finally, the results of the crash data analysis indicated that 

drivers who had prior crash involvement increased their likelihood of 

having a future crash by 87%. 

The targeted survey indicated that successful enforcement strategies for 

addressing problem driver behaviors are those that exhibit one or more of 

the following components: creation of aggressive driving apprehension 

programs/initiatives, a focus on both CMV and non-CMV behavior 

patterns, highly visible enforcement activities, use of a performance-based 

approach to identify specific crash types, driver behaviors, and locations, 

and covert enforcement activities. The states identified as having a higher 

level of traffic enforcement and a lower level of crashes were found to be 

significantly more likely to compare traffic enforcement programs with 

crash data and other information in order to monitor the program’s 

effectiveness. 

Limitations: No goodness-of-fit statistics were provided for the predictive regression 

model. Thus, it was difficult to judge the robustness of the model for 

predicting the likelihood of future crash involvement based on the 

explanatory variables. 

Categorization: This study fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Characteristics, as the research focused on 

driver-specific behaviors and events and their relationship to future crash 

involvement. 

98
a

Nafukho, F.M. & Hinton, B.E. (2004). A model for predicting tractor-trailer truck drivers’ 

job performance related to highway safety (Publication No. MBTC2043). University

Arkansas, Fayetteville, Research and Special Programs Administration. 

 of 

b

Nafukho, F.M., Hinton, B.E., & Graham, C.M. (2007). A study of truck drivers and their job 

performance regarding highway safety. Performance Improvement Quarterly, 20, 61–74. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Characteristics Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Characteristics Driver

Environment

Pre-Event Event Post-Event

Author Abstract: aA number of factors may contribute to road traffic accidents, namely: 

reckless driving, having un-road worthy vehicles on the road, and poor 

conditions of the roads. However, this study examined the performance of 

tractor-trailer truck drivers in a leading transportation company in the 

United States of America. Limited research has addressed the issue of 

working conditions of the drivers, especially incentive, compensation, and 

workplace variables and how these variables affect job performance in 

terms of reduced accidents. Therefore, the primary purpose of this study 

was to determine how tractor-trailer truck drivers’ job performance could 

be improved while at the same time ensuring increased revenue for the 

transportation companies employing them. The target population for the 

study comprised of tractor-trailer truck drivers employed by a major 

transportation company in the U.S. The researchers obtained data on the 

drivers from the database maintained by the company. Data were obtained 

for 14,340 drivers. The data used in the study included demographic, 

incentive, compensation and workplace variables. The results of the study 

showed that a statistically significant model did exist that explained the 

variance in the dependent variable, the number of accidents, which was 

used as a measure of driver performance. The variables cost of accidents, 

miles driven per month, safety bonus, pay time off, drivers’ age and salary 

earned combined explained 3.2% of the changes in the dependent variable 

(number of accidents) in the study. The demographic variables miles 

driven and age of the driver had linear and positive relationship with the 

dependent variable, number of accidents. Based on the results of the study, 

several policy implications and recommendations for further studies are 

made. 

 bLimited research has addressed the issue of truck drivers and their 

performance regarding highway safety in terms of reduced number of 

crashes per driver. The primary purpose of this study was to determine 

how tractor trailer truck drivers’ job performance could be improved while 

99
at the same time ensuring increased revenue for transportation companies 

employing them. The target population for this study comprised of tractortrailer truck drivers employed by a leading transportation company in the 

United States. The data used in the study included demographic, human 

capital, compensation and workplace variables. The results of this study 

should be useful to several individuals, organizations and the entire U.S. 

economy. The transportation companies should benefit by knowing the 

factors that predict good job performance for the drivers. This should 

assist management in designing work conditions or other activities that 

promote good performance in terms of reduced crashes and improved 

productivity of drivers. 

Industry Sector: abTrucking 

Purpose: aThe purpose of this study was to evaluate the effect of driver 

characteristics, driver compensation, and workplace variables on safety 

outcomes as measured by accident rate per driver. 

b

The later paper reports on the same study and explains the link between 

workplace variables and the crash rate per driver. This paper also makes 

recommendations for further study. 

Sample: ab14,340 tractor-trailer drivers. 

Methodology: abThe authors obtained data for 14,340 drivers from a major motor carrier 

for the year 2002. Standard regression analysis was used to determine the 

relationship between driver characteristics and the dependent variable 

(number of accidents per driver). The independent variables included were 

cost of accident, salary, gender, marital status, age, race, miles driven per 

month, times of dispatching, miles, paid time-off, and safety bonus 

provided by employer. All drivers in the company had received an equal 

amount of training, and 19.2% or 2,754 of the drivers in the sample had 

been involved in at least one accident. 

Relevant Findings: abThe drivers who had been involved in at least one accident were, on 

average, one year older, earned about $20 less paid time off during 2002, 

and drove, on average, 630 miles more in 2002 than the drivers with no 

accidents. In 2002, this group of drivers also earned a smaller average 

safety bonus, but only by approximately $10. 

Six variables were found to be significant in the regression model and 

together explained 3.2% of the variance in driver accident rates. The 

variables included cost of accident, miles driven per month, safety bonus 

amount, paid time off, age, and salary. Incentives thus have a positive 

effect on driver safety. b. While the model explains only 3.2% of the 

100
variation in crashes, a 3.2% reduction in total crashes could have a 

significant effect on a company’s bottom line. 

 bThe authors performed further analysis of the miles driven per month and 

age variables. Within the sample of drivers with crashes, drivers with three 

crashes had the highest mean of miles driven and drivers with one crash 

had the lowest mean of miles driven. Older drivers experienced more 

crashes than younger drivers. 

Since the average miles driven per month correlated highly with the crash 

rate, the authors recommend that companies revisit their compensation 

schemes, perhaps compensating drivers based on the value of the goods 

transported instead of the miles driven. They also recommend further 

qualitative study focusing on the factors that drivers think can make them 

more efficient and effective at work. Lastly, the authors recommend a 

study focusing on drivers above 50 years of age. 

Limitations: abThe authors acknowledge that other variables shown to affect driver 

safety such as experience, and use of alcohol, are not included in this 

study. 

Categorization: These papers fit within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Characteristics, as they examine the 

characteristics of both risky and safe drivers. 

101
Report to congress on the large truck crash causation study. (2006). (TRIS No. 01023450). 

Federal Motor Carrier Safety Administration. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

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Driver Characteristics Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

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Driver Characteristics Driver

Environment

Pre-Event Event Post-Event

Author Abstract: No author abstract 

Industry Sector: Trucking 

Purpose: The purpose of the LTCCS was to conduct a comprehensive examination 

into the causes of, and contributing factors to, crashes involving CMVs. 

This study was designed to permit consideration of a broad range of 

factors that could be used to guide development of crash countermeasures. 

The LTCCS collected the same type of descriptive data as other national 

traffic safety databases such as the Fatality Analysis Reporting System 

(FARS), the General Estimates System (GES), and the MCMIS, but it also 

focused on pre-crash factors such as driver distraction and fatigue, vehicle 

condition, weather, and roadway problems. This makes the LTCCS the 

only national examination of all factors related to causation in large truck 

crashes. 

Sample: 967 crashes involving large trucks. 

Methodology: The LTCCS collected data on crashes at 24 sites in 17 states during the 

period 2001 through 2003. An attempt was made to ensure that each crash 

involved at least one truck with a gross vehicle weight rating of more than 

10,000 pounds and also resulted in at least one fatality, incapacitating, or 

non-incapacitating but evident injury. Data were collected on up to 1,000 

elements in each crash. The factors coded were selected from a broad 

range of factors thought to contribute to crash risk. These include, for 

example, vehicle factors such as brake failure, environmental factors such 

as roadway and weather conditions, and driver factors such as fatigue, 

distraction, speeding, and making an illegal maneuver. To ensure high 

data quality, onsite investigations began as soon as possible after a crash 

occurred. 

The coding of the events surrounding the crash began with the “critical 

event” (the event that immediately led to the crash), the “critical reason” 

(the immediate reason for the critical event or failure leading to the critical 

event; the critical reason describes why the critical event occurred), and 

102
the “associated factors” (any of approximately 1,000 conditions or 

circumstances present at the time of the crash that could possibly 

contribute to the crash). 

Relevant Findings: In the 967 crashes that comprise the LTCCS database, there were 1,127 

large trucks, 959 non-truck motor vehicles, 223 fatal crashes resulting in 

251 fatalities, and 744 injury crashes resulting in 1,408 injuries. Thus, 

23% of the LTCCS cases resulted in at least one fatality. One-fourth of the 

cases involved only one vehicle, including a truck that rolled over, struck 

an object, hit a pedestrian, or collided with a non-motorized vehicle such 

as a bicycle. Over 60% of the 1,127 trucks involved in the crashes were 

tractors pulling a single semi-trailer. 

The remaining results discussed in this section are national estimates 

based on weighted data. During the 33-month study period of the project, 

FMCSA estimated that there were approximately 141,000 large trucks 

involved in fatal, incapacitating, and non-incapacitating injury crashes. 

Almost one-fourth of the crash involvements consisted of rear end 

collisions, about 18% represented a truck either running off the road or out 

of its lane, and almost 27% of all large trucks were involved in crashes 

where they were the sole motor vehicle. 

Trucks were assigned the critical reason for the crash in 77,000 (55%) of 

the estimated 141,000 cases of large trucks involved in fatal, 

incapacitating, and non- incapacitating injury crashes. For those 77,000 

cases, the driver accounted for 87% of the critical reasons, and most 

involved failure to correctly recognize the situation or poor driving 

decisions. The critical reason was assigned to environmental conditions 

(roadway or weather) in only 2% of the cases. In addition, the most 

common associated factors recorded were driver factors, such as legal 

drug use, traveling too fast for conditions, unfamiliarity with the roadway, 

inadequate surveillance, fatigue, and feeling under pressure from motor 

carriers. For two-vehicle crashes involving a truck and a passenger 

vehicle, trucks were assigned the critical reason in 44% of the crashes and 

passenger vehicles in 56%. Driver recognition and driver decision errors 

were the most frequently cited critical reasons for both types of vehicles. 

Limitations: The LTCCS contains a large amount of descriptive data. It was never the 

intent of the study to perform crash causation analyses. Thus, additional 

analyses must be conducted in order to identify specific risk factors for 

large truck crashes. Another limitation is the results of the weighted 

estimates may differ from true values, as they are based on a probability 

sample of crashes and not a census of all crashes. 

Categorization: This study fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Characteristics, as the study focused on 

determining the causes of, and contributing factors to, crashes of CMVs. 

103
Rodriguez, D.A., Rocha, M., Khattak, A.J., & Belzer, M.H. (2003). Effects of truck driver wages 

and working conditions on highway safety: Case study (TRIS No. 00965381). Transportation 

Research Board. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

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Driver Compensation Driver

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Haddon Matrix for Review #2: Improving Driver Safety

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Driver Compensation Driver

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Author Abstract: The role that driver compensation and work conditions play in influencing 

driver safety outcomes has gained increased attention from trucking firms 

and policy-makers. This paper examines the role of these factors, in 

addition to driver behavioral and demographic factors in influencing crash 

frequency at the driver level. A unique driver-level dataset from a large 

truckload firm collected over a period of 26 months is used for estimating 

regression models of crash counts. Based on estimates from a zero inflated 

Poisson regression model, results suggest that occupational and labor 

market factors, such as pay, tenure at the job, and percent of miles driven 

during winter months, have a significantly better explanatory power of 

crash frequency than demographic factors. Taking into account both the 

inflation and the count model, results suggest that higher pay rates and 

getting a pay raise are related to lower expected crash counts and to a 

higher probability of zero crash counts, ceteris paribus. Although a partial 

equilibrium approach is followed, the evidence provided is a first step in 

examining the structural causes of unsafe driving behavior, such as driver 

economic rewards, and crash outcomes. These results can motivate firms 

in modifying operations and driver hiring practices. They also support the 

need for a general equilibrium examination of the relationship between 

driver compensation and driver safety. 

Industry Sector: Trucking 

Purpose: The purpose of this paper was to add to the literature examining the effect 

of behavior on safety outcomes by examining some of the factors that 

motivate driver behavior, particularly compensation and occupational 

factors. 

Sample: 11,540 unscheduled over-the-road, dry-van, tractor-trailer drivers from JB 

Hunt. 

Methodology: This paper used regression models to estimate driver level truck crash 

counts. The data used in this analysis were driver-level HR, operations, 

and safety records from JB Hunt, whose drivers were shown to be 

104
comparable to industry-wide drivers in terms of demographic and 

occupational characteristics. Accident data were collected over a 26 month 

period, with each driver being observed on average for 9.2 months. The 

regression model included driver socio-demographic characteristics, 

occupational factors, and individual exposure as explanatory variables. For 

example, driver compensation per mile, tenure in years, total number of 

miles driven during period observed, percentage of miles driven during 

winter, age, gender, race, and marital status. The dependent variable was 

total number of crashes costing the firm $500 or more during the period of 

observation. The data included drivers who received a pay raise, and 

drivers who did not receive one, either because they left the firm prior to 

the raise or were hired at a higher pay rate. 

Relevant Findings: Higher pay rates, as well as pay raises, were shown to lower expected 

crash frequency. The model estimated that, on average, a one cent per mile 

raise in pay resulted in a 2.27% reduction in crash frequency, which is 

known as the elasticity of the crash rate with respect to the pay raise. This 

result translates into a less than 50% probability of having no crashes at a 

pay rate of 16 cents per mile and a more than 95% probability of having 

no crashes at a pay rate of 49 cents per mile. A higher pay rate lowered 

crash frequency even for drivers with many years of experience. Crash 

probability, at first, declines with tenure, and then begins to increase after 

about six years. While crash frequency decreases with driver age, it is at a 

decreasing rate. Policies that allow drivers opportunities for pay raises or 

higher rates of pay when hired may contribute to better safety outcomes. 

Limitations: This study uses a firm-specific data set from a very large firm that 

implemented significant pay raises. The same results may not hold for 

smaller firms or firms implementing smaller pay raises. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Compensation. The study primarily looked 

at the effect of compensation on safety outcomes, but also looked at driver 

demographic and occupational characteristics. 

105
a

Staplin, L. & Gish, K.W. (2005). Job change rate as a crash predictor for interstate truck 

drivers. Accident Analysis & Prevention, 37, 1035–1039. 

b

Staplin, L., Gish, K.W., Decina, L.E., & Brewster, R.M. (2003). Commercial motor vehicle 

driver retention and safety (FMCSA-RT-03-004). ATA Foundation, Alexandria, VA.; 

Federal Motor Carrier Safety Administration, Washington, DC. Office of Research and 

Technology. 

Haddon Matrix for Review #2: Improving Driver Safety

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Driver Characteristics Driver

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Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

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Driver Characteristics Driver

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Pre-Event Event Post-Event

Author Abstract: a

This research analyzed the Motor Carrier Management Information 

System (MCMIS) database to develop estimates of the increased risk of 

crash involvement experienced by commercial drivers who change jobs 

frequently. These analyses quantified the risk of single- and multiple-crash 

involvement as a function of annual job change rate, and expressed the 

relative risk for drivers with more versus fewer job changes through 

calculation of the odds ratio statistic. Significant odds ratio values were 

found, indicating that crash risk begins to rise when a driver has averaged 

more than two jobs with different employers each year for 2 years or 

longer, and that the odds of being involved in multiple crashes more than 

doubles for drivers with three or more jobs per year during this same 

interval. Opportunities for further research, focusing on variables that 

could be extracted from existing data sources to further enhance the 

validity and predictive value of the relationships found in this study, were 

also identified. 

 bWithin this research, the study team analyzed the MCMIS database to 

develop estimates of the increased risk of crash involvement experienced 

by commercial drivers who change jobs frequently, conducted a literature 

review, and contacted industry experts to identify strategies with the best 

potential to improve trucking companies’ retention of safe drivers. 

The database analyses quantified the risk of single- and multiple-crash 

involvement as a function of annual job change rate, and expressed the 

relative risk for drivers with more versus fewer job changes through 

calculation of the “odds ratio” statistic. Significant odds ratio values were 

found, indicating that crash risk begins to rise when a driver has averaged 

more than two jobs with different employers each year for two years or 

longer, and that the odds of being involved in multiple crashes more than 

106
doubles for drivers with three or more jobs per year during this same 

interval. 

The literature review coupled with contacts with drivers, motor carrier 

management, motor carrier insurers, and other groups and associations 

supported recommendations in the areas of selection and hiring of new 

driver applicants; new driver orientation; driver training, including 

refresher training; driver-dispatcher operations; the measurement and 

recognition of safe driving performance by trucking companies; 

scheduling and hours-of-service compliance; and the needs of industry to 

improve perceptions of the profession and to convey respect for and a 

commitment to its drivers. 

Industry Sector: abTrucking 

Purpose: abPrevious research suggests that motor carriers with higher driver 

turnover rates have higher crash rates than their counterparts with lower 

turnover rates. This study sought to expand upon previous findings by 

determining if drivers with higher rates of job change were also involved 

in more crashes than drivers with lower job change rates. The 2003 

FMCSA report and 2005 journal article both outline the same study. 

Sample: ab25,609 truck drivers. 

Methodology: abJob change and crash rate data were obtained from the MCMIS, operated 

and maintained by the FMCSA. Data were gathered specifically from the 

Crash File, Census File, and the Inspection File, with all driver 

information being recorded during roadside inspections. Drivers were 

included in the sample if they were involved in at least two inspections 

during a two year period. Relative crash risk was then identified using the 

calculation of an odds ratio. 

Relevant Findings: abOf the 25,609 drivers included in the sample, 16,249 had no crashes, 

8,797 had one crash, and 563 had two or more crashes. Drivers who had 

more than six jobs in the given sampling period of 2 or more years, 

depending on the data available, were 1.6 times more likely to have been 

involved in at least one crash, and 2.2 times more likely to have been 

involved in multiple crashes. 

Additional analyses examining rates of job change, or number of jobs per 

year, revealed similar results. The odds of being involved in at least one 

crash significantly increased for drivers who had changed jobs more than 

two times per year. An examination of drivers involved in multiple (two or 

more) accidents revealed that drivers who had changed jobs three or more 

times per year were over twice as likely to be involved in multiple crashes 

than drivers who changed jobs less frequently. The relationship between 

107
turnover and crash risk suggests that frequent turnover may serve as a 

potential indicator of risky drivers. In other words, those who job-hop 

between motor carriers more often may also be the more risky drivers. 

Limitations: abThe inspection sampling period for drivers included in the study varied 

markedly, although all drivers had a sampling period of at least 24 months, 

many drivers had a much longer sampling period. Thus, the results 

examining job change rate are more stable because they standardize the 

count of the total number of unique jobs held in the total sampling period 

to a measure of unique jobs held per year. Restricting the dataset to 

include only a common sampling period would have dramatically 

decreased the number of data points available. Causal inferences cannot be 

made about the identified relationships because of the cross-sectional 

nature of the dataset and the retrospective analyses. Other variables, such 

as age, education, and personality factors may also be involved and 

warrant further research. Unfortunately, raw numbers were not available 

in the article, and actual percentages were not reported. It would be 

necessary to contact the authors in order to further investigate these other 

variables. 

Categorization: These papers fit within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Characteristics, because they identify 

characteristics of drivers that may indicate more frequent accident 

involvement. This could aid motor carriers in identifying risky drivers 

within their organization. 

108
Sumer, N., Ayvasik, H.B., & Er, N. (2005). Cognitive and psychomotor correlates of selfreported driving skills and behavior. Third International Driving Symposium on Human 

Factors in Driver Assessment, Training, and Vehicle Design (pp. 96-103).University of Iowa, 

Iowa City. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Abilities Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Abilities Driver

Environment

Pre-Event Event Post-Event

Author Abstract: No author abstract 

Industry Sector: Trucking and motor vehicles in Turkey 

Purpose: The researchers developed a computerized psycho-technical assessment 

system that included a number of tests to measure cognitive and 

psychomotor performance (e.g., driver attention and reaction time). The 

purpose of this study was to examine cognitive and psychomotor 

correlates of self-reported driving skills and behaviors. 

Sample: 716 non-professional passenger car and professional drivers. 

Methodology: Participants were administered computer-based cognitive and 

psychomotor tests in a research center established to investigate the 

validity of a psycho-technical driver assessment system. The computerized 

test battery consisted of the following: Traffic Monotonous Attention Test; 

Selective Attention Test; Visual Pursuit Test to assess drivers’ visual 

plasticity and tracking ability; Eye-Hand Coordination Test; Reaction 

Time Test; and Peripheral Perception Test to measure drivers’ ability to 

pay attention and detect stimuli coming from peripheral panels of the 

monitor while simultaneously attending to a demanding task on the screen. 

After completing these computerized tests, participants completed a 

Driver Behavior Questionnaire (DBQ) that assessed driver behaviors, 

specifically driving violations and inattention errors. They also completed 

a Driver Skill Inventory that provided a self-reported measure of driving 

(perceptual-motor) and safety skills. 

Relevant Findings: This study revealed that self-reported driving skills, as well as driving 

behaviors, could be systematically predicted by the computerized 

measures of cognitive and psychomotor performance. Correlations 

between driving skills and behaviors and both peripheral perception and 

reaction time were moderately strong. Drivers with higher levels of 

peripheral perception ability and quicker reaction time tended to report 

109
that they had a higher level of perceptual-motor performance, better safety 

skills, fewer driving violations, and made fewer inattention errors. It was 

also found that, as expected, both cognitive and psychomotor performance 

deteriorated as age increased. 

Regression analysis showed that the drivers’ level of education was a 

significant predictor of all driving skill and behavior variables. Driving 

exposure was also significantly related to driving perceptual-motor skills, 

but was not associated with safety skills or driving behaviors. The study 

revealed that higher levels of selective attention were associated with 

diminished skills and increased violations and errors. This suggested that 

high levels of selective attention, in fact, create a proclivity for unsafe 

driving and aberrant behaviors. Peripheral perception, on the other hand, 

was found to be a critical element of safe driving, as evidenced by a 

positive correlation with safety skills and a negative correlation with 

violations and errors. Finally, a decline in both reaction time and visual 

pursuit seemed to be linked with unsafe driving. 

Limitations: Very high correlations were observed between the driving skills and safety 

skills measured with the Driver Skill Inventory and between the driving 

violations and attention errors assessed using the DBQ. As a result, the 

researchers’ expectation that computerized measures of cognitive and 

psychomotor abilities would be mainly linked with driving skills and 

attention errors, but not with safety skills and driving violations, was not 

supported. 

Another limitation concerns the nature of self-reported survey instruments; 

past studies have demonstrated that both young and old drivers tend to 

overestimate their driving skills and underestimate their limitations and 

may, therefore, bias the results. The majority of the 716 study participants 

in this study were young and middle-aged, with older drivers not well 

represented (mean age was 36.59 and the oldest driver was 61; however, 

this is nevertheless a representative sample of the CMV operator 

population, at least within the United States). 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Abilities, because the researchers focused 

on predicting driving skills and behaviors that affect safety on the basis of 

the driver’s cognitive and psychomotor abilities and characteristics. 

110
Walton, D. (1999). Examining the self-enhancement bias: Professional truck drivers’ perceptions 

of speed, safety, skill and consideration. Transportation Research Part F: Traffic Psychology 

and Behaviour, 2, 91–113. 

Haddon Matrix for Review #2: Improving Driver Safety

Pre-EventPre-Event Event Post-Event

Driver Driver Perceptions of Driver Perceptions of 

Environment Self and Other

Motor Carrier 

Environment

Author Abstract: A sample of 1,006 professional truck drivers were surveyed on their 

perceptions of self and average other speeds, consideration, relative safety, 

and relative skill. A disproportionate frequency of responses is found in 

the measures of speed, safety, and consideration, but not skill. In the 

measures of speed and consideration this bias is found to operate in a 

negative direction. Truck drivers are found to evaluate other road users 

negatively, they do not demonstrate ‘self-enhancement’ indicative of 

driver overconfidence. Drivers responsible for the biases are isolated from 

the sample using a method of triangulation. Background factors relating to 

driver characteristics and employment conditions are examined. 

Characteristics of the drivers’ employment indicate the perceptions are 

related to factors external to the drivers’ self-conceptions. These contrasts 

provide further support for the contention that the ‘self-enhancement bias’, 

as it appears in this sample, operates as a negative-other rationalization. 

Industry Sector: Trucking in New Zealand 

Purpose: The purpose of this study was to examine whether or not ‘selfenhancement bias’ was present in a sample of truck drivers. This bias 

posits that drivers overestimate their own skill and safety, as compared 

with others, and regard the average driver as more likely to be involved in 

an accident than they are. Further, the authors sought to determine whether 

the bias was related to an inflation in perception of one’s own ability 

(‘positive-self’) or a negative evaluation of others’ abilities (‘negativeother’). 

Sample: 1,006 professional truck drivers in New Zealand. 

Methodology: Researchers contacted 680 transport firms located on one island of New 

Zealand. They distributed 1,995 surveys to drivers who worked for, or 

through, these companies. At total of 1,013 surveys were returned by the 

due date, and 1,006 were deemed usable. Respondents were nearly all 

111
male, 25.5% were owner-operators, and the mean, median, and mode of 

the age distribution all fell within the category 41–48 years. 

The survey consisted of 25 items, including measures from previous 

studies on self-enhancement bias. The pre-existing scales for selfenhancement bias measured speed (Walton & Bathurst, 1998), 

consideration (McCormick, Walkey, & Green, 1986), and safety and skill 

(Svenson, 1981). Additionally, there were questions regarding typical type 

of truck driven, type of load hauled, driver-firm relations, pay, and safety 

equipment. In New Zealand speed limit varies by trailer type, so, drivers 

were also asked to provide the speed limit of the vehicle they reported 

operating on a regular basis. While the author did not provide explicit 

examples of survey item wordings, it was explained that speed was 

measured using continuous scales with a range from 70–130 km/h; 

consideration was measured using scales that each ranged from 0–6; and 

safety and skill were assessed using ‘forced-choice’ items that asked, for 

each dimension, whether drivers considered themselves better than the 

average truck driver. 

Relevant Findings: The professional truck drivers in the current sample exhibited a selfenhancement bias on measures of speed, safety, and consideration. 

Largely independent of the type of truck driven and whether or not drivers 

considered themselves to be safer or more skilled than the average truck 

driver, they believed that other drivers traveled at speeds that were higher 

than they actually traveled. This indicates a negative-other bias, where the 

thinking is that ‘others drive faster than me’ rather than ‘I drive slower 

than others.’ Despite being experienced drivers, logging approximately 

100,000 km per year, this sample reported inflated speeds for others on the 

road. At the same time, they were very accurate when self-assessing their 

own speed, as compared with data records collected by Land Transport 

Safety Authority (LTSA) regarding the actual average speeds of different 

vehicle classifications. 

Results also indicated a negative bias for the measure of consideration, 

where survey respondents reported other truck drivers to be less 

considerate than themselves, and car drivers as far less considerate than 

other truck drivers. 

Findings for the measure of skill did not reflect a self-enhancement bias, 

as younger drivers (< 28 yr) accurately deferred to more experienced 

drivers when rating their assessments of skill; indeed younger drivers are 

generally not as skilled as older drivers. Additional support for lack of bias 

on this measure was found in that older drivers (> 55 yr) more frequently 

claimed to be less skilled than the average truck driver, recognizing that 

age can have a deleterious impact on skill. 

112
Background variables external to driver characteristics especially 

impacted reports on the safety measure. In particular, drivers who claimed 

they were less safe than the average driver reported more frequently that 

their employer had less regard for their safety as an employee. 

Additionally, these drivers also claimed more frequently that their 

employer had no concern for their work hours. They were more likely to 

be employed at a large company, and less likely to indicate that they 

would be trained to drive a new type of vehicle. These findings suggest the 

importance of large companies emphasizing and attending to safety, 

training employees, and adhering to HOS limits. The sample subset of 

owner-operators also more frequently reported driving less safely than the 

average truck driver. The authors indicated that this may be related to the 

fact that the owner-operator is solely responsible for his/her truck, 

including all maintenance (or lack thereof), and thereby possesses detailed 

knowledge regarding its mechanical condition. For some drivers, then, 

factors external to their control were influential, which is not consistent 

with an overly positive self-conception of their driving. 

An explanation of the negative-other rationalization may be found in 

Wills’ (1986) downward comparison theory, which suggests that drivers 

may justify their own non-compliant behavior by “reporting as ‘average’ 

those who are more extreme than themselves” (p.111). A negative regard 

for average allows for the driver to consequently perceive his or her own 

speed as slower, and levels of consideration as higher, in comparison. 

Regarding skill level, where no measure of bias was found, the authors 

purported that justification was not necessary because skill level does not 

have implications for external standards of conduct. Rather, it is the acting 

out of that skill on various measures (e.g., speed and consideration) that is 

negatively evaluated. 

Limitations: There are certain operational variations in truck driving in New Zealand 

compared with the United States that likely differentially impact safety 

outcomes. For example, in New Zealand, seat belt use is not required by 

law, speed limits differ depending on the type of trailer being hauled, and 

HOS regulations are not in parallel with the United States. Caution should 

therefore be exercised regarding the generalizability of the findings in this 

study. 

Categorization: This paper fits within the pre-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Perceptions of Self and Other, in that it 

evaluates perceptions of ‘self’ and ‘other’ on various measures and in light 

of background factors relating to driver characteristics. 

113
Motor Carrier Environment: What motor carrier practices affect safety? 

American Trucking Associations. (1999). Safe returns: A compendium of injury reduction and 

safety management practices of award winning carriers. 

Haddon Matrix for Review #2: Improving Driver Safety

Safety Management 

Practices

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Safety Management 

Practices

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: No author abstract 

Industry Sector: LTL, TL, and private trucking 

Purpose: The purpose of this project was to: identify and document highly effective 

motor carrier safety management practices; identify and document 

successful approaches to reducing the risk and cost of workplace injuries; 

and share this information with industry and the general public. 

Sample: Phase I interview: 48 award winning motor carriers; Phase II interview: 1 

carrier from the Phase I, and 10 additional carriers. 

Questionnaire: 200 motor carriers in California, Washington, and Oregon. 

Methodology: The American Trucking Association Foundation (ATAF) identified a 

stratified sample of award winning carriers based on carrier type, 

operation type, and size. Carriers were selected based on having 

exemplary safety performance records and/or injury rates that were 

significantly lower than the industry average. Interviews were then 

conducted with safety management directors, personnel directors, owners, 

and/or other staff responsible for safety. The interviews included questions 

about the integration of the safety function within the organization, 

employee hiring, employee training, employee award and incentive 

programs, equipment specifications and maintenance, safety policies and 

meetings, injury prevention, accident and injury investigation, claims 

management, monetary investment in safety, and other factors critical to 

safety success as identified by interviewed carriers. 

In addition, a survey was administered to 200 motor carriers in order to 

determine benchmarks for typical practices in the trucking industry. 

Survey questions requested information regarding safety-related hiring 

criteria, driver training, award and incentive programs, safety meetings, 

114
accident review, key factors in effective safety management program 

implementation, and general information about the respondent carrier. 

Finally, an additional sample of motor carriers was selected based on 

recommendations from insurance providers. Carriers participating in the 

Phase II interviews were asked more detailed information concerning their 

injury prevention practices. 

Relevant Findings: Four factors were highlighted as critical to successful safety management: 

1) Top management must support and be committed to safety; 2) 

Employees must be included in safety management by keeping lines of 

communication open, encouraging employee feedback, and rewarding 

employees with bonus, incentive, and recognition programs; 3) Safety 

must be a focus in all aspects of operations and at all levels of the 

organization, including hiring, compensation and benefits, and day-to-day 

protocols; and 4) Safety management should be on-going and 

comprehensive to identify and address problems before an event occurs. 

While employee retention is a serious problem in the trucking industry, 

most of the award winning carriers interviewed had lower than industryaverage annual turnover rates. Participants stressed treating their 

employees with respect as critical to successful retention. In addition, 

some firms had developed programs designed to increase retention of new 

hires during the first four months of employment by pairing new hires 

with more senior employees using a “buddy” support system. 

All of the participating companies used merchandise incentive or 

recognition programs where employees could earn points toward rings, 

belts, jackets, or vacations for safety-related performance. Over two-thirds 

of the companies also provided cash incentive programs, with safe 

performance awards ranging in value from several hundred to several 

thousand dollars. 

All of the participating firms reported holding regular safety meetings. 

Attendance was typically mandatory and employees were paid for 

attendance. In addition, the use of employee-staffed safety subcommittees, 

responsible for accident investigations, work environment safety, and 

training needs assessment, was reported to help make employees feel more 

involved in safety management. 

Most of the training and safety programs identified consistently tracked 

and analyzed all accidents and incidents, regardless of severity. 

Monitoring even the most minor of events allowed the companies to 

develop more effective tools for accident and injury prevention to prevent 

minor events from becoming major events in the future. 

115
Finally, participating companies reported spending an average of $2,500 

per power unit per year on direct safety expenditures, such as safety 

administration, awards and bonuses, safety meetings, and training 

expenses. This figure is almost $1,500 higher than what is spent by the 

average motor carrier and demonstrates a clear investment in safety 

through out-of-pocket costs. Safety is viewed as an investment that more 

than pays for itself through reductions in insurance premiums and accident 

costs, and increases in productivity and employee retention. 

 

Limitations: This report provides a general overview of the best practices employed by 

award winning motor carriers. A more detailed analysis, broken down by 

carrier type, operation type, and/or size may be helpful in assessing best 

practices and developing training programs for different types of motor 

carriers. In addition, the researchers primarily focused on interviewing 

management to determine best safety practices. It may also be informative 

to interview drivers working for award winning motor carriers to 

determine what policies and practices they believe assist them in being 

safer drivers and if there are any differences between drivers at award 

winning motor carriers and drivers employed by carriers with poor safety 

performance records. 

Categorization: This paper fits within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Safety Management Practices, 

because the purpose of the study was to gain a better understanding of the 

management practices that can lead to safer fleet performance. 

116
Arboleda, A., Morrow, P.C., Crum, M.R., & Shelley, M.C.I. (2003). Management practices as 

antecedents of safety culture within the trucking industry: Similarities and differences by 

hierarchical level. Journal of Safety Research, 34, 189–197. 

Haddon Matrix for Review #2: Improving Driver Safety

Safety Management 

Practices

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Safety Management 

Practices

Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: Problem: A homogeneous perception of safety is important for the 

achievement of a strong safety culture; however, employees may differ in 

their safety perceptions, depending on their position and/or hierarchical 

level within the organization. Moreover, there is limited information on 

the antecedents of safety culture. This study examines how safety training, 

driver scheduling autonomy, opportunity for safety input, and 

management commitment to safety influence individuals’ perceptions of 

safety culture. Method: Data for this study were drawn from 116 trucking 

firms, stratified by three safety performance levels. The data were 

collected from drivers (lowest hierarchical level), dispatchers (medium 

hierarchical level), and safety directors (highest hierarchical level), 

regarding their perceptions of their respective corporate safety cultures. 

Perceptions of safety culture were analyzed through a linear regression 

using dummy variables to differentiate among the three hierarchical 

groups. The resulting model allowed for examination of the specific 

antecedents of safety culture for the three employee groups and the extent 

to which the hierarchical groups were in agreement with each other. 

Results: Driver fatigue training, driver opportunity for safety input, and 

top management commitment to safety were perceived to be integral 

determinants of safety culture in all three groups. Impact on industry: 

Trucking firms seeking to strengthen employees’ perceptions of safety 

culture might begin by improving these safety management practices 

while appreciating that they may have a different impact depending on the 

employee’s hierarchical position (e.g., drivers’ perceptions of safety 

culture are more influenced by top management commitment and driver 

fatigue training). A fourth safety practice examined, driver scheduling 

autonomy, was not found to be instrumental in shaping safety culture for 

any of the three hierarchical levels. Consistent with previous research, 

implementation of stronger safety cultures should result in fewer 

accidents. 

117
Industry Sector: Trucking 

Purpose: The purpose of the current study was to examine management practices as 

predictors of safety culture in the trucking industry. In addition, the 

perceptions of drivers, dispatchers, and safety directors were explored to 

determine if management practices could predict safety culture at different 

levels of the trucking industry’s hierarchy. 

Sample: 116 firms (32 top safety-performing firms, 53 average firms, and 31 poor 

performing firms), yielding individual responses from 113 drivers, 98 

dispatchers, and 109 safety directors. 

Methodology: The authors sampled from trucking firms listed in the federal 

government’s Motor Carrier Census file that had also been rated for safety 

in the SafeStat. A total of 77,216 motor carrier firms exclusively engaged 

in trucking (i.e., no passengers) were eligible for selection in the study, 

based on their inclusion in the aforementioned databases. The population 

of firms was then divided by quartiles into three safety performance 

categories based on SafeStat ratings (numerical thresholds not provided): 

top safety-performing firms, average firms, and poor performing firms. 

Motor carriers were randomly selected from within each category and 

contacted to participate. Of the 566 firms contacted, 374 agreed to 

participate and 116 returned usable surveys. 

The authors then administered a survey to drivers, dispatchers, and safety 

directors at the participating firms concerning management practices at 

their organization and perceived safety culture. Management practices 

were measured by asking participants to report the extent to which they 

thought: 1) drivers in their firm were trained about driver fatigue issues 

(driver safety training); 2) drivers in their firm were the best judges of 

whether they were too tired to driver (driver autonomy); 3) drivers in their 

firm had opportunities to make suggestions and voice complaints 

regarding safety and fatigue (driver safety input); and 4) top management 

in their firm was committed to driving safety (top management 

commitment). 

Safety culture was measured by asking respondents to indicate their level 

of agreement (strongly agree to strongly disagree) with four statements: 1) 

our company makes driving safety a top priority; 2) driving safety is an 

important concern at this company; 3) I am satisfied with the amount of 

emphasis this company places on driving safety; and 4) drivers and 

management openly discuss issues related to driver fatigue. A multiple 

linear regression model was then used to estimate the effect that 

management safety practices had on individuals’ perception of safety 

culture. 

118
Relevant Findings: Driver safety training was a significant predictor of safety culture for 

drivers, dispatchers, and safety directors. In addition, drivers’ opinions 

regarding their own training were the most influential predictors of safety 

culture. Thus, when drivers receive safety-related training, all employees 

(and particularly drivers) may be more likely to perceive a strong, positive 

safety culture in the organization. 

Driver autonomy was not a significant predictor of safety culture for any 

of the three groups of employees. Drivers, dispatchers, and safety directors 

did not view driver scheduling autonomy as an important contributor to 

safety culture in their organizations. 

Driver safety input was a significant predictor of safety culture for 

dispatchers and safety directors, but was not a significant predictor of 

safety culture for drivers. However, a comparison between drivers, 

dispatchers, and safety directors revealed no statistical differences in effect 

sizes, suggesting that all employees agreed about the extent to which 

driver input is important in regards to safety culture. In effect, driver input 

may be a predictor of safety culture, but it is not as strong a predictor of 

safety culture as driver training. 

Top management commitment to safety was a significant predictor of 

safety culture for all three groups of employees. When employees believe 

that top management values safety, they are more likely to perceive a 

strong safety culture in the organization. Results also indicated that 

drivers’ perceptions of top management were significantly more important 

in predicting safety culture than were dispatchers’ or safety directors’ 

perceptions. Therefore, it is most important that drivers perceive top 

management as safety-conscious when fostering a strong safety culture. 

Limitations: This research is limited by its reliance on self-report data, potentially 

resulting in artificially inflated relationships between variables. However, 

self-report methodologies are often the only practical means of gathering 

information on employee perception, and recent research suggests that the 

problem of inflation in self-report data is often over-emphasized. 

Categorization: This paper fits within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Safety Management Practices, as it 

examined driver, dispatcher, and safety director perceptions of safety 

culture as a function of management practices. 

119
a

Barton, R., Tardif, L.P., Wilde, G., & Bergeron, J. (1998). Incentive programs for enhanci

truck safety and productivity: A Canadian perspective (Publication No. TP 13256E). 

Transport Canada; Canada Safety Council. 

ng 

b

Barton, R. & Tardif, L.P. (2002). Implementing successful incentive programs within transport 

fleets. In Z.G. Zacharia (Ed.), International Truck and Bus Safety Research and Policy 

Symposium (pp. 45–55). University of Tennessee, Knoxville: National Safety Council. 

Haddon Matrix for Review #2: Improving Driver Safety

Incentive Programs Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Incentive Programs Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: a

No author abstract 

 bIncentive programs strengthen the motivation to be safe and, combined 

with proper tools and knowledge, will result in improved safety. An 

estimated $30 to $50 million is spent annually by Canada’s trucking 

industry on this type of program. 

A review of theoretical considerations respecting safety incentive 

programs is provided. Forty trucking companies across Canada are 

interviewed regarding their use of incentive programs, and findings of the 

interviews summarized. Guidelines for developing and evaluating safety 

incentive programs are provided along with a series of factors for 

enhancing the effectiveness of these programs. 

A two-year pilot program is recommended to develop and validate a 

procedures manual for companies to follow when designing, 

implementing and administering a safety incentive program. This would 

include detailed benefit-cost analyses of these programs within a 

minimum of four trucking companies. A nationwide recognition-based 

incentive program is recommended. The framework and organizational 

structure for this program would be developed as part of the pilot program. 

Industry Sector: Long-haul trucking in Canada 

Purpose: The purpose of both articles was to identify what programs are currently in 

place in the industry, their strengths and weaknesses, and make 

recommendations for adopting industry best-practices. 

120
 bThis article also documents the results of three pilot tests of a manual 

developed to help motor carriers design and implement incentive 

programs. 

Sample: 40 Canadian-based firms, including companies of various sizes and types 

(private for-hire, LTL, and bulk). 

Methodology: aThe authors initially conducted on-site personal interviews at 40 carriers. 

Managers were interviewed at all 40 firms, while drivers were interviewed 

at 2 of the firms and at 1 truck stop. 

 bThe results were later compiled into a manual describing the 

implementation of successful incentive programs. The manual was 

evaluated in a pilot study of three different carriers that implemented 

safety, driver retention, performance and fuel economy programs. The 

pilot studies documented the implementation steps taken by each company 

and assessed their success. Results were used to further develop the 

incentive program implementation manual. 

Relevant Findings: Safety technologies and vehicle engineering provide the tools needed to 

drive safely. Safety training provides the knowledge to drive safely. 

Incentive programs then provide the motivation to use safety technologies, 

tools, and knowledge. It is necessary to use incentives, education, and 

safety engineering in conjunction with each other in order to produce 

positive safety outcomes. Incentive programs can be effective at 

improving safety, with some motor carriers achieving reductions in 

negative safety events of up to 80% when combined with safety 

engineering and training. Motor carriers recoup the costs of incentive 

programs through reduced crash rates and rebates on reduced insurance 

claims. In the literature reviewed by the authors of both studies, the 

majority of motor carriers that have evaluated their incentive programs 

report benefit-cost ratios exceeding two to one. 

However, motor carriers lack a reference point for developing incentive 

programs. Thus, many are unable to implement successful programs. 

Existing programs vary widely in the type of reward given, the timing of 

the reward and reward eligibility. The authors list a number of criteria that 

must be met in order for an incentive program to be effective: 

• Management must be committed to the program. A budget should be 

set aside and a coordinator and incentive planning team named. The 

firm should promote a strong safety culture among all employees. 

• Incentives should be attainable and awarded fairly, of high perceived 

value, and increase with long-term performance. Recognition 

programs, such as driver of the year, are highly effective as an addition 

to a cash bonus. 

121
• Graduated rewards tend to be more successful than all-or-nothing 

rewards. 

• Management should evaluate the plan regularly for costs, benefits, and 

effectiveness. A successful incentive program changes over time and 

incorporates employee feedback. A time lag of about one year from 

the time a program is introduced or substantially modified should be 

expected for results to appear. 

• The program must be clearly communicated to employees through an 

initial manual and regular follow-up communications. 

• New drivers must be trained for safety habits. 

The pilot study findings of one LTL carrier showed successful 

implementation of safety and driver retention programs. First, the 

company appointed a safety director who met with each employee. The 

company then implemented a bonus which all drivers received after six 

months, provided they had not been involved in an adverse safety event. 

This six month period was chosen because the majority of company 

turnover happens during the first six months of employment. After 

implementation, driver turnover for new employees fell from 98% to 20%. 

A recognition incentive, which was not specified, decreased adverse 

events by 35% per vehicle and per million vehicle mile. Other pilot studies 

have shown that incentive programs targeted at fuel economy, safety, or 

performance indirectly reduce turnover by increasing job satisfaction. 

The authors also recommend an industry-wide, recognition-based safety 

program for both companies and drivers. 

Limitations: Small sample size. 

Categorization: These papers fit within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Incentive Programs, as these articles 

discuss the development and implementation of safety incentive guides 

and programs. 

122
Dammen, S.J. (2005). The effects of safety practices, technology adoption, and firm 

characteristics on motor carrier safety. Journal of the Transportation Research Forum, 44, 

103–20. 

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Author Abstract: The theory of the firm suggests that firms should maximize profit by 

investing in safety until marginal cost is equal to the marginal benefit. 

This paper addresses motor carrier safety from the perspective of the firm, 

developing the theoretical framework for firm safety decisions. 

Additionally, this paper tests the relationship between firm safety 

performance and safety practices, new safety technologies, and firm 

marketing strategies. By testing the impact of the safety performance 

marketing strategy on carrier accident rates, it can be shown that firm 

managers have control over the safety performance of their firms through 

management decisions. 

Industry Sector: Trucking 

Purpose: The purpose of this paper was to empirically evaluate the effect of firm 

safety practices, characteristics, and technology use on accident rates and 

to demonstrate that a motor carrier’s management can impact the fleet’s 

safety performance. 

Sample: 516 Class I and Class II motor carriers. 

Methodology: This study tested the effect of safety practices, technologies, and firm 

characteristics on carrier injury and fatality rates. Safety practices 

measured included safety meetings, firm speed limit, motorist “call-in” 

numbers, and apprenticeship training programs. The firm characteristics 

included size, LTL or TL industry sector, use of owner-operators, 

unionization, and marketing strategies that emphasize either on-time 

performance or safety performance. These practices and characteristics 

were analyzed in the context of the theory of the firm. 

The theory of the firm broadly stipulates that firms are profit maximizers 

and make all decisions, including safety decisions, in order to maximize 

profit. Firms thus make investments in both safety and non-safety inputs to 

maximize the profit of their output. When making these decisions, they 

also face uncertainty, which in this model is the probability of having an 

123
accident. The firms final profit is thus its revenue, less the cost of safety 

and non-safety inputs (such as wages), and less the cost of accidents. 

The study uses firm-level data from the 1996 Motor Carrier Safety, 

Operations and Technology (MCSOTS) survey, and also from annual 

financial and operating statistics. Only Class I and Class II for-hire motor 

carriers were included in the study sample. [Reviewer note: As of January 

1, 1994, the ICC defined Class I carriers as those establishments with 

annual revenues greater than $10 million, Class II carriers with annual 

revenues between $3 and $10 million, and Class III carriers with annual 

revenues of less than $3 million.] Data from the MCSOTS survey 

contained information regarding firm operating characteristics, safety 

practices, use of technology, and carrier safety performance. The 

technologies included for analysis were collision avoidance systems, 

automated vehicle diagnostics, and on-board computer monitors. Fatality 

and injury accident rates were taken from the SAFER system 1996 

database. The SAFER system provided profiles of carriers’ safety, and 

captured information regarding inspections, OOS rates, accidents, and 

their FMCSA safety rating. It was the precursor system to SafeStat. 

Relevant Findings: As hypothesized, firms that utilized technology and safety practices had 

lower accident rates with fatalities and injuries, showing that managers 

can control the safety outcomes at their firms. The one unexpected result 

was that safety meetings were one type of safety practice that actually 

correlated with higher accident rates. One possible explanation for this 

result may be that firm safety meetings are an Occupational Safety and 

Health Administration (OSHA) work rule. Firms may implement the 

meetings to satisfy these regulations, even if they do not decrease the firm 

accident rate. 

The most significant factors shown to affect a firm’s accident rate were the 

firm’s characteristics, particularly safety performance marketing 

strategies, use of owner-operators, and unionization. Unionized firms and 

firms that used owner-operators had significantly lower accident rates. 

Firm size was also shown to be inversely related to accident rate. LTL 

firms did not have an accident rate that differed statistically from that of 

TL firms. Unionized firms and firms with speed limit policies reduced 

their accident rate by roughly 30% relative to their peers. Collision 

avoidance systems were also shown to significantly reduce accident rates. 

Limitations: Additional firm characteristics and safety practices, such as training and 

recruiting, should be added to the analysis, since their omission may bias 

the included variables. The firm characteristics and technology variables 

are all dichotomous variables; they indicate whether or not a firm uses a 

certain practice or technology, but not its use intensity or quality. 

124
The author also acknowledges that the paper does not test for causality, 

and it is possible that firms with high accident rates adopt safety practices 

retroactively in order to decrease the future accident rate. 

The study uses data from 1996. Since then, the role of LTL carriers and 

their share of the motor carrier industry have changed considerably. 

Categorization: This paper fits within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Safety Management Practices. The 

premise of the paper is the assumption that firms impact their accident rate 

through safety management practices and safety technology adoption. 

125
Dobie, K. & Glisson, L.M. (2005). Investigation of the safety training of motor carrier drivers. 

Greensboro, NC: Southeastern Transportation Center. 

Haddon Matrix for Review #2: Improving Driver Safety

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Author Abstract: No author abstract 

Industry Sector: Trucking 

Purpose: Researchers surveyed motor carrier managers and operators to examine 

the state of the relationship between on-going motor carrier safety training 

and reports from their respective drivers. The survey also assessed the 

benefits of training, with a goal of improving training programs, carrier 

safety and driver retention. 

Sample: 60 motor carrier operators. 

47 motor carrier managers. 

Methodology: Researchers distributed tailored surveys each to motor carrier managers 

and drivers. The surveys solicited information regarding the current state 

of training within the motor carrier industry. Specifically, managers were 

asked about available training opportunities for their drivers, and operators 

were asked to provide information regarding the value they place on the 

different types of training available to them. 

Relevant Findings: The types of training which drivers reported as being most useful and 

beneficial largely mapped to the training that motor carriers indicated 

would most benefit their organizations in terms of profits and competitive 

position. For instance, a vast majority of drivers and managers (86.7% and 

93.6%, respectively) responded that training to keep drivers “up-to-date 

regarding laws and company rules” is important. Additionally, both agreed 

that training with respect to personal safety was important and desirable. 

In general, although management and operators tended to agree regarding 

the information and skills training should provide, drivers did not 

uniformly indicate that availability of this training would persuade them to 

stay at a company. When asked, 50% of drivers reported that it did not 

matter whether or not the company they worked for offered training. 

Additionally, 73.3% of the drivers indicated that availability of training 

126
would not affect their decision to stay at a company. This may be due to 

an apparent lack of tangible benefits for drivers as a result of training. 

With regard to financial compensation, 61.7% of drivers reported 

receiving no compensation for time spent in training, nor benefits with 

regard to pay, job assignments, route assignments, or promotions. 

Management responses corroborated driver perceptions. The authors 

concluded that without such incentives, it is clear as to why training 

opportunities alone are not enough to keep drivers at a company. Rather, 

participation in training must also benefit drivers in tangible ways, such as 

increased level of responsibility and pay. 

Despite that motor carriers reported having instituted various programs to 

help improve their drivers’ safety performance, the incidence of crashes 

involving large trucks increased between 2002 and 2003 according to the 

FMCSA. As a partial explanation, the authors suggested that driver 

turnover may be a confounding factor, in that potential benefits from 

targeted safety programs, as individually developed by carriers, are lost on 

drivers who leave their company before completing such programs. 

Limitations: The suggested link among safety training, driver turnover, and FMCSA 

accident rates involving large trucks is speculative and was not 

systematically evaluated; as such, it must be interpreted with caution. 

Additionally, a small sample of convenience was used for this research 

and procedural details regarding methodology were not provided. As 

reported by the authors, the majority of drivers they received data from 

were owner/operators. 

Categorization: This paper fits within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Safety Management Practices, as this 

study assessed the state of safety training programs in the trucking 

industry.

127
LaMere, J.M., Dickinson, A.M., Henry, M., & Henry, G. (1996). Effects of a multicomponent 

monetary incentive program on the performance of truck drivers: A longitudinal study. 

Behavior Modification, 20, 385–405. 

Haddon Matrix for Review #2: Improving Driver Safety

Incentive Programs Motor Carrier 

Environment

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Author Abstract: A multiple-baseline experimental design across two groups was used to 

examine the effects of a multi-component individual system on the 

performance, safety, and satisfaction of 22 truck drivers. The intervention 

included incentive pay, which was increased twice; individual and group 

feedback; and loss of incentive pay for accidents. Drivers earned points for 

completing various types of jobs. The primary measure was the percentage 

of job points earned in less time than the baseline average, which 

controlled for number of hours worked and miles driven. After 

intervention, performance increased and remained high for nearly 4 years. 

Accidents did not increase when the intervention occurred, and 

satisfaction with pay and work were not affected by it. Labor cost savings 

averaged more than $5,000 a month while the incentive program was in 

effect, and drivers’ pay increased. These results add to the substantial 

literature on individual incentives by documenting increased productivity 

sustained over a long period without accompanying increases in accidents 

or decreases in workers’ satisfaction. 

Industry Sector: Waste disposal trucking 

Purpose: Researchers were asked by a waste management company to develop an 

incentive system that would increase driver productivity without 

increasing accidents or producing driver dissatisfaction. The study also 

sought to examine the long-term effects of performance incentives. 

Sample: 22 drivers at a single waste management company. 

Methodology: The incentive program was implemented over the course of 78 weeks with 

follow-up data collected during an additional 116-week period. Drivers 

were divided into two groups, with baseline data collected for both groups. 

The baseline period began on October 29, 1989 for both groups of drivers, 

and lasted 20 weeks for Group 1 and 34 weeks for Group 2. Thus, 

incentives for Group 1 began 14 weeks prior to the incentives for Group 2. 

Both groups were first observed for 20 weeks in order to obtain baseline 

128
data. This data provided information across time and between the two 

groups. 

Incentive-based pay was increased during two phases, first by 92% and 

then by 57%. The incentive program did not change the drivers’ base pay, 

which was equal among all drivers at the beginning of the study. Drivers 

received awards when their weekly performance exceeded the baseline 

average. Performance was measured as a ratio of “job points” (the number 

of jobs weighed by job type) to the number of hours worked, given the 

number of miles driven. However, drivers lost their week’s award if they 

had a chargeable accident, defined as accidents in which the driver was 

found at fault by either police or management. This was done to 

discourage improving productivity at the expense of safety. Drivers were 

taught to record and calculate their own performance, which supervisors 

later verified. 

Researchers then compared the number of chargeable accidents for the 

same time period of October 8 through March 17 during the baseline and 

one year later during the first incentive increase phase. Only changes in 

productivity, measured as the number of “job points” completed per day 

given miles driven, were closely compared to the baseline in the second 

phase. Changes in chargeable accidents were not analyzed. Net labor cost 

savings were calculated on a weekly basis during the incentive phases. 

Labor cost savings resulted from more work being done in the same 

amount of time. The data was analyzed using an ANOVA. 

Relevant Findings: The percentage of jobs completed, given number of miles driven, 

increased with the introduction of incentives relative to the baseline. Thus, 

drivers were completing more jobs given the number of miles driven in the 

same amount of time as before the incentives were implemented. The 

increase was substantial during the initial introduction of incentives, 

though subsequent raises in the reward rate did not produce a statistically 

significant effect on productivity. Nevertheless, the increase in 

productivity resulting from the first introduction of incentives was 

sustained over a period of four years. 

Since drivers were paid per hour, the company also saw labor cost savings, 

which were larger than the cost of the incentive program. The company 

had a return on investment (ROI) ratio of 2.8 during the first incentive 

phase, meaning that for every dollar invested in the incentive program, the 

company saved $2.80 in labor costs and increased business. 

Three fewer accidents were reported during the incentive phase than 

during the baseline period, but the authors did not calculate the change in 

accident rates. There were no statistically significant changes in the level 

of job satisfaction. 

129
Carefully designed incentive programs have the ability to increase 

productivity without diminishing safety performance. In this study, a 

safety incentive was built into the productivity incentive. Drivers were 

active participants in program design, implementation, and operation. 

Limitations: This paper documents the implementation of one successful incentive 

program. Although many of the features of this specific program may be 

transferable to other trucking companies, in all likelihood, incentive 

programs need to be tailored to fit the unique characteristics of each 

organization. 

Categorization: This paper fits within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Incentive Programs, because the study 

evaluates changes to accident rate and job productivity after the 

introduction of incentives. 

130
a

Mejza, M.C., Barnard, R.E., Corsi, T.M., & Keane, T. (2003). Driver management practices

of motor carriers with high compliance and safety performance. Transportation Journal, 42

16–29. 

, 

b

Corsi, T.M., & Barnard, R.E. (2003). Best highway safety practices: A survey about safety 

management practices among the safest motor carriers. Washington, D.C.: Federal Motor 

Carrier Safety Administration: Data Analysis Division. 

Haddon Matrix for Review #2: Improving Driver Safety

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Author Abstract: aThis article reports findings from a survey conducted in order to 

characterize the driver management practices of trucking companies that 

are recognized as being among the safest companies in the motor carrier 

industry. Using primary data collected from a geographically stratified 

judgment sample of the safest U.S. motor carriers, we present observations 

and analysis of aspects of the driver hiring, driver training, and driver 

reinforcement activities of the “best safety performers” in the trucking 

industry. The findings imply that the safest trucking firms apply screening 

criteria consistently in all driver-hiring situations; emphasize pre-service 

and in-service training for company drivers and owner-operators alike; 

cover a broad scope of topics in several venues during their training 

programs and use several methods to evaluate drivers in those programs; 

and use an array of different types of rewards to support drivers who 

demonstrate safe driving performance. The information developed in this 

study could be useful to managers of new entrant carriers who are still 

developing their safety management programs, to managers of established 

carriers who might wish to compare or benchmark their existing driver 

hiring, training, and reinforcement practices to those of the safest trucking 

companies, and finally, to public safety agencies that might use the results 

as input to the development of educational components of their motor 

carrier safety programs. 

 bNo author abstract 

Industry Sector: Freight trucking 

Purpose: abThese studies sought to address the lack of data regarding carrier 

management practices, as this has hampered past studies of carrier safety. 

Unlike data on carrier safety performance or compliance, data on 

management practices is more limited. The authors thus sought to 

131
systematically characterize the safety management programs and policies 

of the best performing carriers so that other carriers and regulators will 

have a point of reference when designing their own programs and policies. 

Sample: ab148 freight carriers from the 48 continental states. The sampled group 

was heterogeneous in size and commodity carried. 

Methodology: The papers in this annotation report on the same study. The Mejza et al. 

(2003) paper is a shortened version that covers only driver-related 

management policies. The Corsi and Barnard (2003) report includes 

survey results on vehicle-related management policies as well as a detailed 

appendix on the questionnaire and survey results. 

 abThe authors used a three-stage process to select the “best performing” 

motor carriers in each continental state. First, the authors used FMCSA’s 

September 2000 SafeStat compilation to divide carriers into 12 

commodity categories, with 3 equal-sized groups within each commodity 

category. The carriers in each commodity and size group were rank 

ordered from best to worst, based on the sum of their scores for the 

following SafeStat performance indicators: temporary accident 

involvement indicator, temporary vehicle inspection indicator, and 

temporary driver inspection indicator. The 20 safest large, and the 20 

safest medium-sized carriers in each commodity group were then selected 

for a total of 440 freight and 40 passenger carriers. Second, these selected 

carriers were grouped by state, and lists consisting of 10 firms each were 

sent to their respective state safety directors, who then selected four freight 

and one passenger carrier for administration of the questionnaire. Safety 

directors were also given the choice to select carriers not on the original 

list of 10 firms. The authors then surveyed those motor carriers, receiving 

usable responses from 148 freight carriers. 

The survey assessed three driver-related activities that managers perform, 

to varying degrees, in an attempt to improve their firm’s safety outcomes. 

The three areas were selection, training, and reinforcement. 

 bThe survey also asked managers about their general attitudes towards 

safety and the safety culture at each firm, but the results of these questions 

was reported only in the second study. In addition, the practices of the 

responding carriers were examined based on size to determine if 

management practices differed for large, medium, and small firms. 

Researchers segmented, by size, the responding 148 firms into three 

groups, with the smallest group comprised of firms with less than 25 

power units, the medium group having between 25 and 94 power units, 

and the largest group having 95 or more power units. Each size group 

contained 33% of the responding firms. Results in the second study are 

reported based on these size delineations. 

132
Relevant Findings: abThe safest firms, as identified by these studies, strongly and widely 

exhibited three main driver-related management practices. The first was 

driver selection. These firms chose drivers without prior alcohol or drugrelated violations, without chargeable crashes, without speeding tickets 

and traffic violations and with driving experience. Over 90% of the firms 

used drug testing, past traffic records, on-road tests, and license 

qualification checks to assess potential hires. The same criteria were 

applied to owner-operators, although only one third of surveyed firms 

actually considered owner-operators for employment. Age was a 

significant consideration only when contracting with owner-operators. So, 

motor carriers were more willing to hire employees than owner-operators 

between the ages of 21 and 25, as long as they had a good driving record, 

recommendations, and adequate driving experience. 

 The second driver-related management practice was driver training. Most 

firms required both pre-service and in-service training. The five most 

popular training topics were reported as HOS regulations, pre-trip 

inspection, accident notification, federal safety regulations, and post-trip 

inspections. The carriers reported using a combination of classroom, onroad vehicle, and off-road vehicle training. Most carriers reported utilizing 

both written or oral examinations and in-vehicle tests. Computer 

evaluations were reported to be used less frequently. 

The third driver-related management practice most commonly utilized by 

the firms in this study was reinforcement. The most commonly reported 

safety incentives were recognition rewards, such as letters or plaques. Two 

thirds of the companies reported giving cash rewards, and the majority 

utilized a combination of both recognition and compensation rewards. 

Most rewards were given after a driver was accident-free for a specified 

time period. It is evident that safe motor carriers have strict selection 

criteria, multi-faceted training, and broad safety incentive programs. 

The surveyed firms also indicated a dedication to deploying a defect-free 

fleet, with over 80% reporting that they rarely need to conduct 

unscheduled maintenance as a direct result of their strict preventive 

maintenance policies. A majority of the firms used computerized 

equipment maintenance, although less than one fourth of the smaller firms 

reported investing in such systems. Maintenance schedules were typically 

time-based and frequent, depending on the part of the truck being 

maintained. For example, brakes are maintained on average every 10,000 

miles by the majority of the carriers. 

 bThe respondents to this survey also reported using disciplinary actions as 

repercussions for safety violations, with larger carriers being more likely 

to terminate or suspend than smaller carriers. Researchers also found that, 

133
regardless of firm size, many of the surveyed firms monitored their drivers 

using various technologies. The most common were speed regulators and 

engine diagnostics. 

Larger carriers were more likely to utilize strict selection criteria, conduct 

thorough training, and offer incentives to drivers than were smaller firms. 

For example, a higher percentage of large carriers reported hiring drivers 

only over the age of 25, requiring driving experience with other carriers 

and a lack of prior speeding tickets. A higher percentage of large firms 

also performed license qualification checks, required both pre-service and 

in-service training, and provided individual driver safety incentives. 

Although the percentages were higher for large firms, over 50% of best 

performing carriers in all size categories demonstrated strict selection 

criteria, thorough training, and the use of incentives. 

Limitations: abThese papers did not test for causation or significance. It is unclear 

whether the practices identified in this study lead to safer motor carriers, 

or if other, unidentified, factors contribute to the safety rankings of these 

firms. As these papers report only on a characterization study, the authors 

recommend that similar data be collected, compared, and tested for 

statistically significant differences between the practices of the safest 

motor carriers to the practices of less-safe carriers. 

Categorization: These papers fit within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Safety Management Practices, taking 

a holistic approach in considering a broad range of factors that motor 

carriers employ to improve safety. This includes driver selection, 

retention, and reinforcement practices. 

134
Mejza, M.M., & Corsi, T.M. (1999). Assessing motor carrier potential for improving safety 

processes. Transportation Journal, 38, 36–50. 

Haddon Matrix for Review #2: Improving Driver Safety

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Motor Carrier 

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Haddon Matrix for Review #2: Improving Driver Safety

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Author Abstract: No author abstract 

Industry Sector: Trucking 

Purpose: The majority of federal programs seek to identify the riskiest motor 

carriers by evaluating negative safety outcomes. The purpose of this study 

was to develop a technique for identifying positive safety outcomes as 

well as the management practices that led to them. These identified 

practices can then be used to improve safety at problem carriers. 

Sample: 52 Class I carriers and 41 Class II carriers. 

Methodology: Motor carrier safety was modeled as a process with a set of safety inputs 

that are used to generate safety-related outcomes. Inputs were vehicle and 

driver safety management activities and outputs were defined as driver and 

vehicle compliance with Federal Motor Carrier Safety Regulations 

(FMCSR). Management inputs were categorized into planning, 

implementation, and control, taken from the ATA’s 1995 Motor Carrier 

Annual Report for Class I and Class II freight carriers. Inputs included 

driver compensation, driver exposure, vehicle exposure, and vehicle 

servicing. Safety-outputs were taken from SafeStat. 

These inputs and outputs were then used in a linear programming 

technique called data envelopment analysis (DEA). The model in this 

paper measured compliance efficiency relative to the performance of other 

motor carriers in the sample by determining the maximum levels of output 

(compliance) that motor carriers could have achieved from the 

management inputs that were utilized. Motor carriers in the sample were 

ranked according to their efficiency scores, slack (the difference between 

potential and observed output given a set of inputs), and excess values (the 

amount of inputs used in excess of the amount necessary to achieve a 

given level of output). 

Relevant Findings: The study does not identify specific management practices that lead to 

either good or poor performance. Instead, the authors demonstrate a model 

135
that can provide a basis for regulators to identify the best and worst 

performing carriers, for carriers to develop carrier-specific safety 

improvement objectives, and for carriers and shippers to facilitate the 

carrier selection decision. 

Rankings resulting from a DEA model can be used by regulators to 

identify best and worst performing motor carriers and to develop 

benchmarks. The DEA model in this paper identified 27 carriers as having 

achieved maximal compliance with both vehicle and driver regulations in 

an efficient manner relative to their combination of safety inputs. The 

paper also demonstrated how to measure the degree of underperformance 

for inefficient carriers relative to their efficient peers. 

Limitations: Data were not available for the authors to include driver training, driver 

reinforcement, and vehicle evaluations performed by motor carriers as 

variables in the DEA model. Other variables used in the model were proxy 

variables. For example, driver compensation was used as a proxy for 

driver skill under the assumption that drivers with more skill receive 

higher pay. 

Categorization: This paper fits within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Safety Management Practices. The 

study takes a holistic approach in considering a broad range of factors that 

motor carriers employ to improve safety, including driver selection, 

retention, and reinforcement practices. 

136
Naveh, E., Marcus, A., & Allen, G. (2003). ISO 9000’s effects on accident reduction in the U.S. 

motor carrier industry (Publication No. MN/RC 2003-29). University of Minnesota, 

Minneapolis; Minnesota Department of Transportation. 

Haddon Matrix for Review #2: Improving Driver Safety

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Motor Carrier 

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Author Abstract: This report aims at establishing a correlation between the voluntary ISO 

9000 certification by motor carriers and traffic safety. The report shows 

that improvement of operating and quality performance improved safety 

performance. As part of the analysis, several ISO 9000 certified and noncertified motor carrier companies were compared based on their social and 

financial performance prior to, during and after the certification process. 

The authors have shown that there is a positive increase in performance 

during and after the certification process. The number of motor carrier 

companies certified by ISO 9000 is limited and unique. The uniqueness 

arises from the fact that the certified organizations haul specialized 

products such as automobiles and hazardous materials. That shows that 

most organizations are certified due to mandatory reasons. 

In conclusion, the observations and results have thrown light in a new 

direction that indicates that there exists a significant relationship between 

the quality assurance and safety performance of a motor carrier 

organization. The authors feel that further research is necessary to 

investigate the circumstances under which ISO 9000 and other programs 

for upgrading motor carrier performance help lead to an increase in safety. 

Industry Sector: Specialized trucking (trucks over 10,000 pounds in gross vehicle weight 

rating) 

Purpose: The purpose of this study was to see if a voluntary ISO-9000 certification 

program, or a similar program, can complement safety regulation and 

contribute to an improvement in motor carrier safety. 

Sample: 40 ISO-9000 certified U.S. motor carriers and 20 similar, non-certified 

U.S. motor carriers. 

Methodology: ISO-9000 certification is a set of audited quality assurance standards 

covering service, processes, and delivery that allow customers to choose 

certified suppliers. For the motor carrier industry, the practices include 

driver hiring, licensing procedures, work hours, training, safety programs, 

and driver and vehicle monitoring. 

137
The study compared certified and uncertified motor carriers. McGraw-Hill 

provided the list of ISO-9000 certified carriers, from which 40 were 

selected. Twenty uncertified carriers were chosen that were similar to the 

certified carriers with respect to miles driven and goods hauled. The return 

on assets (ROA) ratio was chosen as the independent variable. The ratio 

was taken from the ATA data set, which includes financial data on all U.S. 

motor carriers. The US-DOT SAFER data set provided the dependent 

variables which included safety performance data, the number of injuries, 

fatalities and tow accidents. Driver, vehicle, and management SafeStat 

scores were also used as control variables. Data was taken from a five year 

period, with two years prior to ISO registration, one year during ISO 

registration and two years after ISO registration. The authors also 

performed a more in-depth case study of a single hazmat carrier. 

Relevant Findings: The results show that ISO 9000-certified carriers had significantly better 

safety performance, as measured by number of accidents, than similar 

carriers without this certification. The study also found that a carrier’s 

profitability, as measured by its ROA ratio, is highly correlated with a 

good safety record. Firms that became ISO 9000-certified improved both 

their safety and financial performance. 

As a component of this research, the in-depth case study of a hazmat 

hauler revealed that the company was under pressure from its insurer to 

reduce accident rates or face higher fees. It was already implementing 

safety changes prior to beginning the certification process including driver 

background checks, additional training, performance monitoring and the 

establishment of safety goals and a safety committee. To become certified, 

the company involved employees in the production of a safety and 

operations manual. The company thus used ISO-9000 certification as part 

of a broader commitment to a safety culture. 

Limitations: The performance of the certified firms may, however, differ from their 

peers for other reasons. These firms tended to be automobile or hazardous 

materials haulers, and early adopters of the certification. In addition, the 

reason that firms seek certification is important, since voluntary 

certification indicates a desire to improve performance in a verifiable 

manner. Mandatory certification may not produce the same positive results 

on safety and performance. The conditions under which certification has 

the ability to enhance safety need to be further investigated. 

Categorization: This paper fits within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Safety Management Practices. The 

study examined the effect of voluntary quality certification on safety and 

performance. 

138
Shaw, J.D., Gupta, N., & Delery, J.E. (2002). Pay dispersion and workforce performance: 

Moderating effects of incentives and interdependence. Strategic Management Journal, 23, 

491–512. 

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Incentive Programs Motor Carrier 

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Author Abstract: The compensation literature is replete with arguments, but lacking in 

empirical tests, regarding the effects of pay dispersion on organizational 

outcomes. Pay dispersion may increase effort and provide incentives for 

high workforce performance levels, but may also inhibit cooperation and 

goal orientation among employees. Drawing on several theoretical 

perspectives (individual motivation, institutional theory, organizational 

justice, and neoclassical economics), this study predicts that pay 

dispersion will be associated with higher levels of workforce performance 

when accompanied by formal individual incentive systems and 

independent work, while pay compression is desirable in the absence of 

individual incentive systems and when work is interdependent. Survey 

research studies in two industrial sectors (the motor carrier and concrete 

pipe industries) were conducted to address these issues. Interactive 

regression results were generally supportive of the predictions across 

several measures of workforce performance (accident rates, safety 

violations, and productivity). Implications of these studies for strategy 

implementation in terms of compensation theory and practice are 

addressed. 

Industry Sector: Trucking 

Purpose: The purpose of this study was to explore the fit between an organization’s 

compensation structure and its business strategy and performance. In 

particular, the authors tested the effects of compressed and dispersed 

compensation structures on organizations. In a compressed structure, 

salaries do not vary greatly among employees across positions, as opposed 

to a dispersed structure where compensation can vary widely. Previous 

studies have found conflicting results, showing that pay dispersion can 

both benefit and hurt worker performance. The authors performed this 

study to show that the effect that dispersion has on productivity depends 

on whether incentives are targeted at individuals or teams, and on whether 

the nature of the work performed by employees is independent or 

interdependent. 

139
Sample: 379 trucking firms with more than 30 employee drivers per company. 

Methodology: This study focused on the effect of horizontal pay dispersion (the degree 

of difference in pay within a group of employees at the same level) on 

workforce performance, as opposed to vertical pay dispersion (the degree 

of difference in pay among employees at different levels of an 

organization). To measure the effect the authors use two empirical case 

studies. 

The study used the TTS Blue Book of Trucking Companies data gathered 

between the years 1994 and 1995 to select motor carriers with more than 

30 company drivers. The heads of HR at the chosen firms were surveyed 

about driver compensation practices, and 379 replied. Organization and 

financial data were taken from the Blue Book and safety data were taken 

from SAFER (the precursor to SafeStat). Independent variables resulting 

from this data include pay dispersion (difference between the annual pay 

of new hires and the annual pay of senior drivers) and four types of 

individual incentives such as on-the-spot bonuses for exceptional 

performance, and the use of a merit pay system. The dependent variables 

were the accident frequency ratio, driver-related OOS percentage, and a 

company’s relative performance as measured by on-time deliveries, ontime pick-ups, and other measures over which the driver has at least partial 

control. Control variables included company size, company age as 

determined by year founded, percent of drivers unionized, carrier type 

(i.e., TL or LTL), driver tenure (i.e., percentage of drivers employed at the 

company for more than 24 months), the extent to which pay is based on 

seniority, average annual pay level, level of communication about pay at 

the company, and the average value of benefits paid by the company. 

The second study performed similar regression analysis on the concrete 

pipe production workers; however, as its sample falls outside the scope of 

this review, results will not focus on this study. 

Relevant Findings: The use of individual incentives and dispersed wages was associated with 

better performance in an organization environment where work was 

independent (i.e., the trucking industry). Workers can perceive the 

existence of wide differences in pay as a motivating factor, as long as the 

differences result from fair and consistent management policies. 

This study of the motor carrier industry revealed that accident rates can be 

explained by the interaction between individual incentives and pay 

dispersion. The accident frequency ratio was lowest when individual 

incentives were high, but especially with high pay dispersion. The highest 

accident rates were seen when pay was dispersed, but individual 

incentives were low. Thus, dispersed pay was not a motivating factor for 

drivers because it did not result from the presence of individual incentives. 

140
The same pattern was seen with the percentage of driver-related OOS 

occurrences. Driver-related OOS rates were lowest in the presence of 

wage differences together with the use of individual incentives. However, 

company performance variables had a negative relationship with pay 

dispersion. Performance was always better with compressed wages than 

with dispersed wages. However, company performance was better if 

dispersed wages were used with individual incentives than when dispersed 

wages were not accompanied by individual incentives. 

Limitations: The authors do not explore the effect of pay progression over time on 

motivation and workforce performance. Studies have shown that workers 

compare their income to that of their colleagues and to their past income. 

Some of the negative effects of pay dispersion can be offset for an 

individual worker by growth in his/her compensation over time. In 

addition, it is unclear whether drivers at each of the carriers sampled were 

paid by the mile or by the hour, as pay dispersion was calculated using 

average annual earnings for entry-level and senior drivers. It would be 

interesting to examine whether the effects of pay dispersion differ based 

on method of payment (i.e., by mile, hour, or another method, such as 

revenue-based pay). 

Categorization: This paper fits within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Incentive Programs. The study 

primarily looked at the effect of incentives on organizational performance 

and used the motor carrier industry as one case study, where safety is a 

performance measure. 

141
Wright, I.D., Veith, G., & Tsolakis, D. (2005). Productivity implications of heavy vehicle safety 

programs (Austroads Publication No. Ap-R263/05). Austroads. 

Haddon Matrix for Review #2: Improving Driver Safety

Safety Management 

Practices

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Haddon Matrix for Review #2: Improving Driver Safety

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Author Abstract: No author abstract 

Industry Sector: Trucking in Australia 

Purpose: This study evaluated the information available through previous literature 

and company evaluations regarding the link between safety programs and 

productivity. The purpose is both to report available information and to 

identify data gaps. 

Sample: 12 Australian companies provided information on their safety programs 

for a total of 20 different firm safety programs. 

Methodology: The authors first performed a literature review to identify studies that link 

motor carrier productivity and safety programs. The authors then 

contacted companies to identify those with safety programs. Managers at 

twelve companies were interviewed in person with the aid of a 

questionnaire. All companies provided a qualitative assessment of their 

safety programs and associated costs and benefits. Only a few companies 

were able to provide a limited amount of quantitative data, showing that 

rigorous safety program evaluation is lacking among Australian motor 

carriers. 

 

Relevant Findings: The literature review showed that the incentive programs developed by the 

Canadian Safety Council were the only programs where the relationship 

between productivity and safety had been comprehensively evaluated.

Australian firms and state road transport agencies have implemented the 

Trucksafe and National Heavy Vehicle Accreditation Schemes, 

respectively. Both of these recent programs are truck driver accreditation 

schemes, and neither program had been systematically evaluated at the 

time of this study. 

Three of the 12 companies examined in this study had a fatigue 

management program, half focus on driver training, drug testing, and 

medical examinations, and three companies had systematic driver 

selection procedures. Half of the 12 companies conducted drug tests and 

142
medical examination on current drivers and provided driver training. 

Companies also reported encouraging driver involvement in vehicle 

selection, vehicle management, and maintenance. 

Interviews and surveys revealed significant gaps in data on the costs, 

benefits, and effectiveness of safety programs. Trucking firms in Australia 

are not collecting extensive quantitative data on their programs. It is 

therefore not possible to draw authoritative conclusions from the data 

collected. However, the authors report all qualitative information gathered 

during the interviews as a case study of each of the 12 firms. 

Of the qualitative benefits reported, nine companies claimed overall 

improved safety. All of these companies had a considerable degree of 

similarity across some of their programs, particularly in relation to the 

benefits of employee selection, induction, and training. There were also 

similarities with regard to utilizing employee knowledge and input to 

improve vehicle selection and maintenance. Firms that encouraged 

involvement of their workers in vehicle management, including selection 

and maintenance, reported lower maintenance costs, less accidents, and 

less time spent by drivers away from work due to injuries. Four companies 

experienced reduced insurance costs and improved vehicle utilization 

through less OOS time. 

Limitations: The small sample size and lack of quantitative data prevented the authors 

from making firm conclusions. The purpose of this study, however, was to 

demonstrate the lack of data on the effect of safety programs on firm 

productivity. 

In addition, the study only examined safety programs in Australia, thus 

any conclusions may only be generalizable to Australian carriers. 

Categorization: This paper fits within the pre-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Safety Management Practices. The 

paper analyzed the existence and benefits of safety programs used by 

Australian motor carriers. 

143
Event 

Driver Environment: How are driver behaviors related to event occurrence? 

a

af Wahlberg, A.E. (2000). The relation of acceleration force to traffic accident frequency: A 

pilot study. Transportation Research Part F: Traffic Psychology and Behaviour, 3, 29–38. 

b

af Wahlberg, A.E. (2004). The stability of driver acceleration behavior, and a replication of its 

relation to bus accidents. Accident Analysis & Prevention, 36, 83–92. 

c

af Wahlberg, A.E. (2006). Speed choice versus celeration behavior as traffic accident predictor. 

Journal of Safety Research, 37, 43–51. 

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Unsafe Driving Behaviors Driver

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Author Abstract: a

Acceleration- (g-) force and mean speed are measured onboard city buses 

in regular traffic. The means of Right/Left, Gas/Brake, the composite gforce and speed are correlated with drivers’ frequency of (bus) accidents 

for different time periods. No stable relationship is found, only a weak 

tendency for the dimensions of mean speed and Right/Left to predict bus 

accidents when time periods of one to five years are used. The many 

problems inherent in this kind of field research are discussed and some 

remedies proposed. 

 bThe reliability over time of a method for measuring driver acceleration 

behavior was tested on bus drivers in regular traffic. Also, a replication of 

an earlier finding of a correlation between driver acceleration behavior and 

accident frequency for the individual drivers was made. It was found that 

the split-half correlation is probably around 0.50 for the mean (of 

accelerations) of a 30-min drive, and similar for the test-retest of 2.5 h 

measured about a month apart. With such reliability, the sample was 

probably too small to reliably determine any association with accidents, 

but some significant correlations were found. Some ways of holding 

constant the differences in exposure and driving environment were tried 

with mixed success. Alternate ways of analyzing the data and several 

methodological problems were briefly discussed. It was concluded that the 

measurements of acceleration behavior, for bus drivers, are fairly reliable 

over at least a few months. However, some strange discrepancies between 

samples make all interpretations concerning the link to accidents tentative. 

144
 cIntroduction: The driver celeration behavior theory predicts that this 

variable is superior to all other variables as a predictor of individual traffic 

accident involvement, including the ever-important speed parameter. 

[Reviewer note: celeration refers to speed variability during driving (i.e., 

speeding up and slowing down).] The study was undertaken to test this 

prediction. Also, it was expected that most variables would associate fairly 

strongly. 

 Method: The use of speed choice as a predictor of individual traffic 

accident record was discussed, and four different variants of this variable 

(maximum, net mean, gross mean, and standard deviation of speed) 

identified. These variables were then compared to celeration behavior as 

predictors of accident record of bus drivers in the same set of data. 

 Results: Celeration behavior was found to be slightly superior, in 

accordance with the prediction made from the driver celeration behavior 

theory, although the differences were not significant. Furthermore, the 

predictor variables were found to associate fairly strongly between 

themselves, with the exception of gross mean speed, and to have fair 

stability over time, especially when aggregated. 

 Conclusions: These results tentatively confirm some of the predictions 

made from the driver celeration behavior theory. As the results for 

accidents were in the expected direction, but not significant, and the 

maximum speed variable may have suffered from a ceiling effect, the 

conclusion is provisional. 

Impact on industry: The correlations found were strong enough to warrant 

the use of celeration behavior as a predictive variable for transportation 

companies in their safety work. 

Industry Sector: abcTransit bus industry in Sweden 

Purpose: The purpose of this series of research studies was to determine if driver 

celeration behavior is related to, and can predict, accident frequency. The 

author stated that g-force is a measure of the force of acceleration, and that 

variability of driving, or celeration behavior, could be measured as the gforces in a vehicle during a specified time. If greater variation in driving 

behavior results in more accidents, then celeration behavior, measured as 

g-force, should predict accident frequency. Thus, the primary hypothesis 

tested by these studies was that drivers with a higher past frequency of 

accidents will tend to have higher values of g-force. Each study expanded 

upon the previous to develop and test this theory of celeration behavior. 

Sample: a

47 bus drivers with at least 2 years of service. 

 b125 bus drivers. 

 c203 bus drivers. 

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Methodology: a

For the first study, vehicle g-force was measured using a g-analyst that 

measures acceleration forces in two dimensions: longitudinal (Gas/Brake) 

and lateral (Right/Left). These two variables were used to calculate the 

Resultant g-force variable, which was used as the indicator of celeration 

behavior. The g-analyst consisted of a transducer and control unit 

contained in a case. A researcher, whose identity was unknown to the 

driver, entered the bus and placed the case on the floor at the rear of the 

bus, unpacking the control unit. Measurements were made unobtrusively 

as the drivers worked their normal routes. 

Accident data for the participants were collected from accident reports 

filed during the years 1994–1998 at Gamla Uppsalabuss, the drivers’ 

employer. The accidents for each driver were converted to a frequency by 

dividing them by the number of years the driver had been in service during 

this period. Thus, there was one frequency for each of the resulting four 

time periods (1994-1998, 1995-1998, 1996-1998, and 1997-1998) for each 

driver. 

 bThis study used a larger sample of bus drivers and the same methods for 

collecting celeration behavior as the 2000 study. Accident data were 

obtained from accident reports during 1998 through 2001, and an accident 

rate, or frequency, for each driver was again calculated. 

 cThis study measured driver behavior continuously and repeatedly from 

August 2001 through March 2004, with the exception of the summer of 

2003, for technical reasons. In addition, four other variants of speed choice 

(net mean, gross mean, maximum, and standard deviation) were measured 

to determine which variable was a superior predictor of accidents. Only 

incidents where the driver was deemed to be at least partly at fault were 

included in the dependent variable. Statistical relationships between 

accidents and speed behavior were determined by Pearson correlations. 

Relevant Findings: a

No consistent relationships were found between the three acceleration 

force variables and accidents. The main conclusion that was drawn from 

this pilot study was that such a small sample of drivers is too unstable for 

the use of acceleration force and speed variables. 

 bFor the drivers who worked the entire period from 1997 to 2001, it was 

found that, among driver demographic variables, only hours worked had a 

significant association with crashes. Contrary to previous studies, mean 

speed had no significant correlation with accidents, when adjusted for 

hours worked. Two possible explanations for this result were suggested: 

either the sample was too small to detect this effect, or the urban driving 

environment did not allow for large enough mean speed differences 

between drivers for a significant association. 

 

146
 cThe results revealed that, as predicted, celeration behavior yielded a 

higher mean correlation with accident frequency than the other speed 

variables. However, these differences were very small and not statistically 

significant. The author asserts, however, that doubling the sample size 

would have yielded significant results at p < 0.05. Additionally, findings 

remain inconclusive regarding the main predictions since the celeration 

variable was not optimally measured due to equipment malfunctions (i.e., 

only longitudinal acceleration was used as an approximation of the 

theoretical parameter). 

Although all the speed variables analyzed in this study were very similar 

as predictors of accidents, celeration behavior was found to be slightly 

superior. The author was careful to point out that these results do not 

suggest that speed is not a major cause of accidents; instead, he concludes 

that the normally used speed variables, such as mean and maximum speed, 

are not better predictors of accidents on the individual level as compared 

to celeration behavior. 

Limitations: abcAlthough the celeration behavior theory predicts the type of relationship 

observed in this study for all types of drivers and vehicles, the data used 

here may only be valid for the population from which the subjects came, 

namely city bus drivers. Mean speed is low and maximum speed is limited 

in urban transit operations, as buses run on city streets and must stop 

regularly for passengers. 

Two additional limitations concern the use of accidents as a dependent 

variable for predictions from behavior variables. First, accidents are rare 

events; furthermore, they are often underreported. These features of 

accidents may result in large error variances and thus low statistical power 

in the analysis. Secondly, no optimal time period has been identified to use 

in the calculation of accident frequencies, although reliability tends to 

increase over longer time periods. Although the use of a longer time 

period for calculating accident frequency provides a more reliable 

measure, it also results in a shrinking sample, since, as the author notes, 

few bus drivers remain at one company for long periods of time (say, more 

than five years). The statistical power gained by the longer time periods is 

therefore offset by a smaller sample. 

Categorization: These studies fit within the event timeframe of the driver environment for 

Haddon Matrix #2: Unsafe Driving Behaviors, as the research focused on 

establishing a positive relationship between driver acceleration behavior 

and traffic accident frequency. 

147
Hanowski, R.J., Perez, M.A., & Dingus, T.A. (2005). Driver distraction in long-haul truck 

drivers. Transportation Research: Part F Traffic Psychology and Behaviour, 8, 441–458. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Unsafe Driving Behaviors Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Unsafe Driving Behaviors Driver

Environment

Pre-Event Event Post-Event

Author Abstract: Research on driver distraction has typically been conducted by means of 

epidemiology or experimental testing. The study presented here uses a 

naturalistic approach, where real-world driving data were collected from 

truck drivers as they worked their normal delivery runs. Crash, near-crash, 

and crash-relevant conflict data from 41 long-haul truck drivers, driving 

approximately 140,000 miles, were examined. Of the 2,737 crashes, nearcrashes, and crash-relevant conflicts (collectively termed “critical 

incidents”) that were recorded, 178 were attributed to “driver distraction.” 

The 178 distraction-related critical incidents were analyzed and 34 unique 

distraction types were identified. Results showed that a small number of 

long-haul drivers were involved in a disproportionate number of 

distraction-related critical incidents. For example, two of the drivers 

accounted for 43 of the 178 distraction incidents. Important insight was 

also gained into the relative safety impacts of different distracting agents 

and behaviors. The frequency and duration of a task, along with the visual 

demand associated with performing the task, were found to contribute in 

combination to the prevalence of critical incidents. Finally, it was found 

that simply because a task does not necessarily require visual attention 

does not mean that long-haul drivers will not look (sometimes often) away 

from the roadway. However, it is also clear that visually demanding tasks 

carry the highest degree of risk, relative to other categories of tasks. 

Industry Sector: Long-haul trucking 

Purpose: The purpose of this study was to examine the driving of long-haul truckers 

using a naturalistic approach, with the goal of identifying critical incidents 

(crashes, near-crashes, and crash-relevant conflicts) related to distraction. 

These distraction-related incidents were described in terms of the way that 

they clustered into groups based on frequency and duration (i.e., event 

duration and eyes-off-road time). Additionally, various tasks were 

examined for associated risk depending on their time demand, visual 

demand, and frequency of occurrence. 

Sample: 33 long-haul truck drivers who were involved in distraction-related critical 

incidents. 

148
Methodology: The sample consisted of data from a subset of long-haul truck drivers used 

in previous research conducted by Dingus, et al. (Sleeper Berth study, 

2002). The original sample contained 41 drivers. 

Data were gathered naturalistically during driving using two tractors 

instrumented for data-collection purposes. Due to the length of driver runs 

(6-10 days in duration), continuous data recording was not possible. 

Rather, data were selected for retention and analysis based on a high 

probability of surrounding a critical incident (e.g., pre-determined 

thresholds for unusually high lateral and longitudinal acceleration, short 

time-to-collision, and incomplete lane changes). 

The flagged video and electronic data were subsequently reviewed by a 

trained data analyst to determine whether they did, in fact, surround a 

valid critical incident. Researchers defined three types of incidents as valid 

for this study: crash, defined as any incident where the truck came in 

contact with another vehicle, fixed object, pedestrian, or animal; nearcrash, defined as any conflict with another vehicle, fixed object, 

pedestrian, or animal that required a rapid maneuver to avoid it; and crashrelevant conflict, defined as a conflict or driver error that resulted in an 

unsafe scenario but did not require an evasive maneuver to avoid it. 

Incident types were assigned to each clip surrounding an incident, as were 

primary causes of the incident. Data analysts assigned one of three main 

cause categories to each. “Judgment error” was defined as any error made 

by the driver, such as following too closely. “Other vehicle” causes were 

assigned when the driver of another vehicle was deemed to have initiated 

the accident. Lastly, “driver distraction” was cited as the cause when the 

driver had been engaged in an activity not related to his or her primary 

driving duties, such as talking on a cell phone. This process identified 178 

distraction events; subsequently, the cause of the distraction was 

determined. Additionally, events were classified based on driver 

demographics and other between-driver factors (e.g., single vs. team 

driving). 

As a second step, researchers analyzed the data to determine exposure 

criteria for assessing relative risk among the various distraction clips. 

However, because the events recorded were triggered, traditional exposure 

estimates were not possible. Without the ability to generate accurate base 

rates, it was necessary to consider data on the time exposure required by a 

task instead. Time exposure was estimated using the mean amount of time 

it took to finish the distraction task (estimate of overall exposure) and the 

mean amount of time a driver’s eyes were off the forward roadway while 

performing the task (estimate of exposure relative to the risk the task 

presented). 

149
Finally, eye-glance analyses were conducted using 20-second epochs 

surrounding the event trigger (10 seconds prior and 10 seconds after an 

event). Analysts recorded driver glance locations and lengths, which were 

used to determine mean and maximum glance durations, as well as the 

proportion of time the driver spent with his or her eyes off the road. 

Relevant Findings: The distribution of the types of 178 critical incidents attributed to the 

driver was highly non-normal: no crashes were recorded; six distraction 

events did not contain a kinematics trigger because they were part of timetriggered baseline data collection; one event was considered a near crash; 

and the remaining events were determined to be crash-relevant conflicts. 

For this reason, no further distinction was made regarding event severity 

and incidents were considered collectively. 

Further investigation of the data determined that two drivers alone 

accounted for approximately 24% of the recorded distraction incidents. 

This is consistent with previous findings of a small number of drivers 

contributing to a large number of incidents (Hanowski, Wierwille, 

Garness, & Dingus, 2000). While this degree of over-representation is 

astonishing, the authors did not provide any further analyses pertaining to 

these two drivers specifically. Further, the distribution of incidents among 

distraction types for these two drivers appeared similar to the overall 

distribution of incidents for the rest of the sample. [Reviewer note: 

findings showing a small number of people as accounting for a large 

proportion of safety incidents suggests that it may be worthwhile to focus 

on those who are most responsible (i.e., Pareto’s Principle, also known as 

the 80/20 Rule)]. Similarly, although there was a nearly even split of team 

and single drivers, single drivers accounted for almost 65% of all 

incidents. As a possible explanation of this result, it was suggested that 

having a second person present in the truck cab may help avoid unsafe 

situations, rather than contribute to distraction. Age and gender differences 

were not considered, however. 

Analysis of the incidents themselves established 34 unique distraction 

types contained within 7 distinct clusters; these tended to statistically 

separate based on duration and frequency. Additional analysis of the 20-

second epochs surrounding events resulted in significant differences 

across clusters for the mean duration of a distracter and the proportion of 

eyes-off-road time. Generally, there was a large degree of variation in 

distracter duration, and this did not correspond with the relative frequency 

of events. Overall, Cluster 1 encompassed the majority of all events. The 

authors described these 121 incidents as those of “average frequency” and 

“average event duration,” such as looking at the CB and lighting a 

cigarette. The remaining clusters contained incidents of varying degrees of 

frequency and duration, both event and eyes-off-road duration. High 

150
frequency events, such as looking around or outside the cab to the left or 

right, were considered a safety risk independent of their duration and 

visual demand because the driver was frequently being inattentive to the 

driving task. Visually demanding tasks of short duration and lower 

frequency were considered a risk because they very much take the driver’s 

eyes off the road, such as when reaching to the floor to pick up an object. 

Finally, some tasks were moderately high in terms of their duration, visual 

demands (eyes-off-road), and frequency. These are particularly concerning 

from a safety perspective and include activities such as talking 

on/adjusting the CB or talking on a cell phone. 

Limitations: As acknowledged by the authors, a lack of continuously collected data 

meant that determining accurate levels of exposure was not possible. 

Further, it was not possible to establish the proportion of time where a 

particular task was performed and did not result in a critical incident. 

Additionally, the data set appeared to be limited by two drivers accounting 

for nearly one quarter of all incidents. Given Pareto’s Principle, the data 

provided by this small number of drivers contributing disproportionately 

to a safety risk is important to recognize; however, a larger sample would 

probably be helpful in establishing a less skewed distribution of incidents. 

Categorization: This paper fits within the event timeframe of the driver environment for 

Haddon Matrix #2: Unsafe Driving Behaviors, as it investigates the 

manner in which performing tertiary tasks during driving is associated 

with a risk of being involved in a critical incident. 

151
Sullman, M.J.M., Meadows, M.L., & Pajo, K.B. (2002). Aberrant driving behaviours amongst 

New Zealand truck drivers. Transportation Research Part F: Traffic Psychology and 

Behaviour, 5, 217–232. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Unsafe Driving Behaviors Driver

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Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

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Unsafe Driving Behaviors Driver

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Author Abstract: Research using the driver behavior questionnaire (DBQ) has found that 

aberrant driving behaviors can be categorized into: errors, lapses and 

violations. There is also extensive evidence that it is only the “violations” 

score which is significantly correlated with, and predictive of, crash 

involvement. This consistency has been found both across different 

samples and different countries. However, recent research conducted on 

those driving cars in a work-related context has found a different factor 

structure and a different pattern of correlations with crash involvement. 

The present study extends this research by investigating the factor 

structure of the DBQ and the relationship between aberrant driving 

behavior and crash involvement for a sample of truck drivers. Factor 

analysis yielded a four factor solution, that broadly replicated the four 

hypothetical factors (errors, lapses, violations and aggressive violations) 

found in the general driving population. Only the violations factor was 

found to be significantly predictive of crash involvement. This research 

provides evidence of the robust nature of the DBQ findings in populations 

other than the drivers of private motor vehicles. 

Industry Sector: Trucking in New Zealand 

Purpose: The DBQ (Reason, Manstead, Stradling, Baxter, & Campbell, 1990) is a 

measure of aberrant driving behaviors typically used with motor vehicle 

drivers to assess driving behavior. The purpose of the current study was to 

administer the DBQ to a sample of truck drivers and investigate the 

pattern of responses for truck drivers as compared to previous research on 

motor vehicle drivers. In particular, the authors sought to establish a 

relationship between reported truck driver behaviors and previous crash 

involvement. 

Sample: 378 truck drivers working for companies transporting logs, milk, and 

petrol in New Zealand. 

Methodology: Fifty five transport companies were contacted to participate in the study. 

The transport companies were asked to distribute copies of the 

152
questionnaire and a cover letter explaining the project to their drivers. 

Drivers were then asked to complete the questionnaire and return it to the 

researchers through the mail. As an incentive to participate, each driver 

that returned a survey was entered into a drawing to win one of three 

prizes, valued at $120, $50, or $30. 

The questionnaire included demographic information (e.g., age, 

experience, and crash involvement in the past 3 years) and the 28-item 

version of the DBQ, asking drivers to indicate, on a 6-point scale from 

“never” to “all the time,” how often they engage in each aberrant behavior. 

Example behaviors from the DBQ included: speed in a residential area; 

race away from traffic lights to beat another driver; hit someone when 

reversing that you had not seen; and brake too quickly on a slippery road 

or steer the wrong way into a skid. 

Relevant Findings: The three most common aberrant driving behaviors reported by truck 

drivers were: Disregard the speed limit of the open road (mean = 1.45, SD 

= 1.26); sound your horn to indicate your annoyance with another road 

user (mean = 1.29, SD = 1.02); and become angered by a particular type of 

driver and indicate your hostility by whatever means you can (mean = 

1.07, SD = 1.00). 

The pattern of responses to the DBQ for truck drivers was similar to that 

of motor vehicle drivers. Analyses revealed four distinct groups of 

behaviors, similar to those found in previous research. The first group of 

behaviors was “errors,” defined as driving mistakes involving failures of 

observation and misjudgment. The second group was labeled “lapses,” and 

defined as problems with attention or memory. The third group was 

“violations,” or deliberate deviations from practices believed to be 

necessary to safely operate a vehicle. The last group was labeled 

“aggressive violations,” and defined as violations that also involved 

expressing hostility toward another road user or driving in an aggressive 

manner. 

An examination of the correlations between driving behaviors and crash 

involvement over the previous three years revealed that those who 

reported being involved in a crash tended to have higher scores on 

violation behaviors. In addition, they were more likely to be young and 

have less experience driving trucks. Additional regression analyses 

suggested that drivers who reported higher levels of violations were 50% 

more likely to have been involved in a crash over the previous three years. 

Limitations: There is some concern about social desirability affecting the responses to 

the self-report behaviors recorded in this study. Truck drivers may have 

underestimated their aberrant driving behaviors. However, the 

underestimation of behaviors would only result in under-estimates of real 

153
associations, rather than over-estimates. Therefore, the relationship 

between driver violations and accident involvement may be stronger than 

documented in this study. 

Categorization: This study fits within the event timeframe of the driver environment for 

Haddon Matrix #2: Unsafe Driving Behaviors, as it sought to establish a 

relationship between self-reported aberrant driving behaviors and crash 

history. 

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Motor Carrier Environment: How are motor carrier operations related to event occurrence? 

Corsi, T.M., Newhouse, M.L., Shukla, A., & Chandler, P. (2002). Passenger motor carriers: A 

safety performance profile. In Z.G. Zacharia (Ed.), International Truck and Bus Safety 

Research and Policy Symposium (pp. 523). University of Tennessee, Knoxville: National 

Safety Council. 

Haddon Matrix for Review #2: Improving Driver Safety

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Author Abstract: No author abstract 

Industry Sector: Private and for-hire trucking 

Purpose: The purpose of this study was to compare the safety performance of 

passenger carriers to the safety performance of commodity motor carriers. 

A stand-alone, more in-depth analysis of passenger carrier safety 

performance was also conducted in order to evaluate the effect of firm size 

on performance. 

Sample: 2,826 for-hire and 114 private passenger motor-carriers were included in 

the broad comparison between passenger carriers and other carriers; 444 

for-hire passenger carriers were included in a detailed comparative 

analysis of SafeStat component safety measures; 2,403 for-hire passenger 

carriers were analyzed for size effects on safety performance. 

Methodology: The study used data beginning January 1999 through July 2000 from the 

SafeStat. SafeStat provides performance indicators based on the results of 

a carrier’s roadside inspections, CRs, enforcement actions taken against 

the firm, and crashes. SafeStat evaluates performance in four SEAs. 

SafeStat assigns a score to each firm for each SEA based on underlying 

safety measures. The scores are used to compare motor carriers to their 

peers. The four SEAs are the driver SEA, vehicle SEA, accident SEA, and 

safety management SEA. The study used data from each SEA and its 

underlying components or safety measures. 

The study first compared all passenger carriers in the database to all 

carriers in other major industry segments, such as building materials, 

household goods and general freight. All industry segments were broken 

down into for-hire and private groups. The segments were then compared 

using the results of the most recent available CR, regardless of when it 

155
occurred. In addition, only 444 for-hire passenger carriers were analyzed 

using the detailed component measures that are used to calculate the SEA 

scores. In particular, the recordable crash rate (number of crashes per 

million vehicle miles), driver safety review measure (driver-related acute 

and critical violations weighted for severity), safety management review 

measure (safety management-related acute or critical violations weighted 

for severity), and enforcement severity measure (number of closed 

enforcement cases) were compared. These 444 carriers had been given a 

CR within the 18 months prior to the development of the database. These 

recent CRs reflect a concerted effort to target at-risk carriers in the CR 

process. 

Second, additional comparisons between passenger and all other industry 

segments were made based on driver and vehicle safety inspections. 

Safety measures evaluated include driver and vehicle OOS violation rates, 

fatal crash rates per vehicle, and total crash rates per vehicle. 

Lastly, the passenger carrier group alone was analyzed. It was broken into 

five sub-groups based on the number of power units owned by each firm 

to evaluate the relationship between the effect of firm size and a firm’s 

SafeStat safety scores. Carriers were separated into the five groups based 

on the following categorizations based on number of power units: 1 unit, 

2-3 units, 4-8 units, 9-25 units, and 26 or more units. 

Relevant Findings: Comparison between passenger carriers and various commodity segments 

revealed that passenger carriers are among the best performing motor 

carriers, as measured by results from both CRs and roadside inspections. 

For example, only 5% of private passenger carriers had overall 

unsatisfactory reviews. Additionally, 100% of for-hire passenger carriers 

had satisfactory reviews. Passenger carriers also had some of the lowest 

numbers of driver OOS violations, fatal crashes, and enforcement cases. 

The comparison also revealed a disparity in safety performance between 

for-hire and private carriers; with more for-hire carriers receiving overall 

satisfactory CR reviews. Private commodity carriers had recordable crash 

rates higher than for-hire commodity carriers, private passenger carriers 

and for-hire passenger carriers. On average, private carriers were more 

likely to have a severe safety management violation than a for-hire carrier. 

However, private carriers are less likely, on average, to have a driver 

safety violation. Also, with the exception of passenger carriers, a higher 

percentage of for-hire firms than passenger firms had an enforcement case 

that was initiated and closed within the 30 month period prior to the period 

of analysis. 

Evaluation of roadside inspections produced similar results as the CRs. 

For example, for-hire carriers had lower driver OOS rates than did private 

156
carriers, although their vehicle OOS rates were comparable. The authors 

suggest that a greater degree of familiarity with FMCSA regulations 

among for-hire carriers may explain these differences. 

The in-depth analysis of passenger carrier size groups revealed that there 

were more large carriers receiving overall satisfactory CRs than small 

carriers. However, results vary with firm size once individual CR 

components are analyzed. The recordable crash rate first increases with 

firm size and then decreases with firm size; thus, the largest firms 

demonstrate the lowest overall recordable crash rate and medium firms 

exhibit the highest overall recordable crash rate. Larger firms have a 

higher frequency of involvement in driver violations than smaller firms, 

but a lower frequency of involvement in safety management violations. 

The smallest firms also had less enforcement cases than their larger 

counterparts. 

Evaluation of roadside inspections revealed significant differences 

between for-hire passenger carriers of various sizes. The largest carriers, 

with more than 26 power units, had lower driver-related and vehiclerelated OOS rates. HOS violations were also significantly higher for small 

passenger carriers; 20.21% inspections of smallest firms found HOS 

violations in contrast to 2.11% for the largest firms. There was also a 

significant decline in both the fatal and total crash rate, per power unit, as 

firm size increased. 

Limitations: The sample size of private carriers was small in comparison to the sample 

size of for-hire carriers. However, the authors were careful not to draw 

firm conclusions from the firm-size analysis that divided passenger 

carriers into five subgroups and alert the reader to the small sample size. 

In addition, during the period of analysis, only passenger and hazardous 

materials motor carriers with unsatisfactory safety ratings were prohibited 

from operating vehicles in interstate commerce. On November 20, 2000, 

several months past the end of the study period, the FMCSR was changed 

to prohibit all motor carriers with unsatisfactory safety ratings from 

operating vehicles in interstate commerce. 

Categorization: This paper fits within the event timeframe of the motor carrier 

environment for Haddon Matrix #2: Motor Carrier Operations. The article 

analyzed the adherence to safety rules by passenger motor carriers in 

comparison to motor carriers other industry segments. 

157
a

Keane, T., Corsi, T., & Braaten, K. (2002). Motor industry profile study: Evaluating safe

performance by motor carrier industry segment. In Z.G. Zacharia (Ed.), International Truck 

and Bus Safety Research and Policy Symposium University of Tennessee, Knoxville: 

National Safety Council. 

ty 

b

Horrace, W.C., & Keane, T.P. (2004). Ranking and selection of motor carrier safety 

performance by commodity. Accident Analysis & Prevention, 36, 953–960. 

Haddon Matrix for Review #2: Improving Driver Safety

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Haddon Matrix for Review #2: Improving Driver Safety

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Author Abstract: aNo author abstract

 bWe use recent safety performance data to rank US motor carrier 

commodity segments (e.g., Tank segment or Produce segment) in terms of 

several driver-related, vehicle-related, and crash-related safety measures. 

Ranking and selection inference techniques are used to determine the best 

and worst performing commodity segments at the 95% confidence level. 

The results are mixed, however the Passenger segment is generally best, 

while the Produce, Intermodal, and Refrigerated segments tend to be 

worst. 

Industry Sector: abFor-hire and private trucking 

Purpose: abThe purpose of this study was to explore potential differences in safety 

performance across industry segments. The 2002 conference proceedings 

and 2004 journal article both outline the same study. 

Sample: abApproximately 94,000 for-hire carriers in 11 commodity segments, and 

55,000 private carriers in 10 commodity segments. 

Methodology: abResearchers used the MCMIS and the SafeStat to rank commodity 

segments by safety through the evaluation of various safety performance 

measures. Only carriers having an inspection within the past 30 months 

were included. Eleven for-hire carrier commodity segments and ten 

private carrier commodity segments were identified in the MCMIS 

system. The 10 private segments examined were: Building Materials, Bulk 

Freight, Refrigerated (non-produce), General Freight Truckload, 

Household Goods, Intermodal, Large Machinery, Passenger, Produce and 

Tank. The 11 for-hire segments examined included the same 10 

commodity segments, plus the General Freight, LTL segment. 

158
The SafeStat data provided nine safety performance measures for ranking 

the commodity segments. These included two driver-related measures, two 

vehicle-related measures, three crash-related measures and two safety 

management performance measures. Examples of the measures are the 

total crash rate and the driver OOS rate. An average safety performance 

measure was developed for each segment from carrier level data. Ranking 

and Selection Theory was then used to identify and rank the best, and 

worst, performing commodity segments. This theory is a probabilistic 

technique that divides observations into three groups: a best group, a worst 

group, and a group containing all other observations that can not be 

classified at a statistically significant level. In this study, the individual 

commodity segments were divided into these three groups. 

Relevant Findings: abOverall, the Passenger and General Freight LTL segments performed the 

best, being in the best subset for six measures. The Intermodal and 

Produce segments performed the worst among the for-hire segments, 

being in the worst subset for four measures. However, many segments, 

especially private-carrier segments, received both best and worst rankings, 

depending on the safety measure being used or were not able to be 

classified at all. The authors attributed this lack of clarity in ranking for 

private-carrier segments to the small sample size for some of the privatecarrier segments. For example, the Passenger, Intermodal, and Household 

private segments had only 7, 12, and 29 observations in one of the safety 

management performance measures. 

The authors recommend that different safety measures be applied to 

evaluate the performance of different segments. The research shows that if 

identifying the best and worst performing segments is important, then it is 

even more important to recognize that there may be more than one best or 

worst segment along any safety metric. In addition, a segment may be best 

according to one measure and worst according to another. Since SafeStat 

contains data on crashes, and crashes are clearly important safety 

measures, the authors recommend that the database be expanded to 

include commodity segment as a variable. 

Limitations: abThe nine safety performance measures used in this study were selected 

from a larger list of 23 measures for which data were collected. Many of 

the 23 measures are closely correlated, and several serve as direct inputs to 

others. Consequently, there was some concern that relatively poor 

performance on one measure would automatically result in poor 

performance on another related one. The researchers addressed this 

limitation by balancing the types of measures used in the analysis, 

including two driver-related measures, three crash-related measures, two 

vehicle-related measures, and two safety management-related measures. 

159
Thus, there was a fairly even representation among the types of measures 

examined. 

A second limitation of the data involved the inability of the researchers to 

assign motor carriers to a single segment if they had indicated that they 

carried two or more commodities. The potential difficulty is that the mean 

scores for some of the more common, generalized segments (e.g., General 

Freight) will presumably track close to the industry means since many 

carriers assigned to different segments will also be assigned to General 

Freight. This also led to small sample sizes for many private-carrier 

segments. 

Additionally, results of the study are valid only for motor carriers that 

have had an inspection within the past 30 months (the criteria used for 

inclusion of MCMIS data in SafeStat). 

Categorization: These papers fit within the event timeframe of the motor carrier 

environment for Haddon Matrix #2: Motor Carrier Operations, because 

they provided overall safety ratings for firms by industry segment. 

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Post-event 

Driver Environment: How can feedback provided to the driver benefit safety? 

Hickman, J.S., & Geller, E.S. (2003). Self-management to increase safe driving among shorthaul truck drivers. Journal of Organizational Behavior Management, 23, 1. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

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Driver Selfmanagement

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Haddon Matrix for Review #2: Improving Driver Safety

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Author Abstract: The relative impact of a self-management for safety (SMS) process was 

evaluated at two short-haul trucking terminals. Participation in the PreBehavior group (n = 21) recorded their intentions to engage in specific 

safe versus at-risk driving behaviors before leaving the terminal (i.e., 

before making any of their deliveries for the day), whereas participants in 

the Post-Behavior group (n = 12) recorded their actual safe versus at-risk 

driving behaviors after returning to the terminal (i.e., after making all their 

deliveries for the day). Each participant drove a truck equipped with an 

on-board computer-monitoring device that recorded two driving 

behaviors, traveling > 63 mph (overspeed) and stopping or braking > 7 

mph/sec (extreme braking) [Reviewer note: 7mph/sec equals 0.319 g]. 

During the SMS intervention, participants in the Pre-Behavior group 

reduced their mean percentage of time overspeeding by 30.4%, and their 

mean frequency of extreme braking incidents by 63.9%. Similarly, during 

the SMS intervention, the Post-Behavior group reduced their mean 

percentage of overspeed and their mean frequency of extreme braking 

incidents by 19.3% and 49.4%, respectively. 

Industry Sector: Short-haul trucking 

Purpose: The purpose of the current study was to examine the potential benefits of 

using SMS techniques in combination with on-board monitoring devices 

to improve safety in the trucking industry. SMS is a behavior-focused 

improvement process whereby individuals change their own behavior in a 

goal-directed fashion, thereby precluding the need for interpersonal 

observation and feedback. 

Sample: 33 short-haul truck drivers from 2 trucking terminals in the northeastern 

U.S.: 21 in the Pre-Behavior experimental condition and 12 in the PostBehavior experimental condition. 

161
Methodology: The two short-haul trucking terminals were randomly assigned to a PreBehavior or Post-Behavior experimental condition. Drivers in the PreBehavior condition were asked to record their intentions to engage in 

specific safe versus at-risk driving behaviors before leaving the terminal at 

the beginning of their shift. The drivers who participated in the PostBehavior condition were asked to record their actual safe versus at-risk 

driving behaviors after returning to the terminal at the end of their shift. 

All participants had trucks equipped with on-board monitoring devices 

that recorded overspeeding (defined as traveling greater than 63 mph) and 

extreme braking (defined as braking the vehicle at a decrease in speed 

greater than 7mph/second). Drivers were aware that the monitoring 

devices were installed on their trucks. Each driver entered an individual ID 

number into the on-board computer before the start of each trip, linking 

their ID to the data obtained from the trip. 

Both experimental groups were given a two-hour training session 

explaining the rationale and importance of SMS techniques, as well as 

how to identify the antecedents and consequences of safe and at-risk 

behaviors, how to record behavioral self-intentions (Pre-Behavior group) 

or self-observations (Post-Behavior group), and how to set goals and 

administer self-rewards. All participants were then asked to complete the 

self-monitoring forms on a daily basis for four consecutive weeks. The 

Pre-Behavior group was asked to estimate the percentage of time they 

would drive without overspeeding and the number of times they would 

have an extreme braking incident while driving on a particular day. The 

Post-Behavior group was asked to estimate the actual percentage of time 

they drove without overspeeding and the number of times they had an 

extreme braking incident on each day. 

Baseline data were recorded by the in-vehicle technology for 11 weeks 

preceding the 4-week intervention period. In addition, information was 

collected during a four week withdrawal phase, following the completion 

of the intervention phase, where the in-vehicle monitoring equipment 

continued to record data on overspeeding and extreme braking. 

Relevant Findings: Results for the Pre-Behavior group demonstrate that the mean percentage 

of time overspeeding (2.3% during baseline) and the mean frequency of 

extreme braking incidents (1.22 during baseline) was reduced by 30.4% 

and 63.9%, respectively, during the intervention period. Drivers in the 

Post-Behavior group decreased their mean percentage of time 

overspeeding (5.7% during baseline) and mean frequency of extreme 

braking incidents (7.3 during baseline) by 19.3% and 49.4%, respectively. 

Over the four-week intervention period, the Pre-Behavior group had 16 

fewer extreme braking incidents and 9.7 fewer hours overspeeding than 

during the baseline period. Taken cumulatively, these results suggest that, 

if SMS monitoring were to continue for an entire year, a total of 192 fewer 

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extreme braking incidents and 116.4 fewer hours overspeeding would 

occur for the Pre-Behavior group. In addition, the Post-Behavior group 

could expect 516 fewer extreme braking incidents and 352.8 fewer hours 

overspeeding over the course of a year. 

Both the Pre- and Post-Behavior groups returned to near baseline levels of 

performance after the intervention was discontinued, suggesting that the 

behavioral change that occurred during the intervention was due to the 

actual SMS techniques, and not an artifact of training or simply an 

increased awareness of safety conscious behaviors. Overall, the SMS 

techniques significantly reduced the occurrence of at-risk behaviors for 

both Pre- and Post-Behaviors groups. However, these techniques must be 

used continuously to maintain their effectiveness, suggesting the need for 

an ongoing SMS program. 

Limitations: Although one of the original goals of this study may have been to compare 

the results of the Pre- and Post-Behavior groups to determine whether 

SMS was more effective when self-monitoring intentions or actual 

behaviors, systematic differences in the Pre- and Post-Behavior groups 

preclude the authors from drawing conclusions about the observed 

differences in results. For example, the results suggested that the PostBehavior group had superior decreases in the targeted at-risk behaviors. 

However, the Pre-Behavior group drove more safely during the baseline 

than did the Post-Behavior group, and thus did not have the potential to 

improve behaviors at the same rate as the Post-Behavior group. In 

addition, the Post-Behavior group had fewer drivers, but each driver drove 

significantly more minutes during the study than the drivers in the PreBehavior group. This may be because the Pre-Behavior trucking terminal 

lost a major business account prior to the study, resulting in a significant 

decline in business. Additional data analysis would be necessary, 

examining rate-based assessments and outcomes, before valid 

comparisons could be made between the two groups. Nevertheless, the 

small sample sizes of the Pre- and Post-Behavior groups suggest a need 

for replication of the aforementioned findings with more participants and 

randomization of experimental groups. 

Categorization: This paper fits within the post-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Self-management, as it discusses the 

potential benefits of implementing SMS programs in the trucking industry. 

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Olson, R., & Austin, J. (2001). Behavior-based safety and working alone: The effects of a selfmonitoring package on the safe performance of bus operators. Journal of Organizational 

Behavior Management, 21, 5–43. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

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Haddon Matrix for Review #2: Improving Driver Safety

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Author Abstract: Experimental evaluations of Behavior-Based Safety (BBS) processes 

applied with lone workers are scarce. Clinical and organizational 

researchers alike have studied the effectiveness of self-monitoring as a 

performance improvement strategy, but further work is needed to 

determine the power of such interventions for improving safe behavior and 

to explore the best practices for using such processes with lone workers. In 

this study, 4 male bus operators (20.5 yrs average experience) selfmonitored their safe performance and received feedback based on selfmonitoring data. Dispatch supervisors used radio communication to 

prompt Ss [subjects] to complete self-monitoring forms and also 

conducted special observations of Ss to measure target performances. Both 

operators and supervisors were unaware of experimental Os [observers] 

who measured the performance of each S by riding on busses as 

passengers. A multiple baseline design across performances was used to 

assess the effects of the intervention on 4 performance targets. The 

intervention resulted in a 12.3% increase in safe performance for the 

group, with individual increases in performance ranging from 2 to 41% for 

specific target performances. The results are discussed in terms of the 

value of BBS processes for employees who work alone and the research 

needed to determine the components of self-monitoring processes that are 

most critical for generating improvements in safe performance. 

Industry Sector: Transit bus industry 

Purpose: The goal of the current study was to evaluate the effectiveness of selfmonitoring procedures for improving the safe performance of bus 

operators. 

Sample: 4 male bus drivers employed by a Midwestern public transportation 

system with 19–23 years of experience who worked a regular 10-hour 

shift (6:30am–4:30pm) driving a route on a university campus. 

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Methodology: Bus drivers were observed at least once a day for approximately 30 days. 

The experimenters rode a complete one-way cycle of the bus route (lasting 

30 minutes) for each session and monitored safety-critical behaviors. 

Experimenters recorded performance for (1) complete stopping, defined as 

the complete termination of forward movement at stop signals; (2) 

remaining stopped during passenger loading and unloading, defined as 

remaining motionless for at least two seconds after the last 

loading/unloading passenger either steps behind the yellow line on the 

bus, steps off the bus to the right, or clears the front left corner of the bus; 

(3) mirror checking, defined as visually checking both side mirrors after 

loading/unloading passengers as the bus pulls out of a loading zone; and 

(4) stopping position, defined as keeping bus doors shut until the bus is 

completely stopped and positioning the bus so that no cars can pass on the 

right. 

After an initial baseline observation period of 13 days, the participating 

bus drivers attended an informational meeting where they were introduced 

to the behavior-based self-monitoring program. Drivers were given 

information on the purpose and rationale behind the use of BBS 

techniques, and instructions for completing self-monitoring forms. The 

first stage of the intervention lasted 8 days and asked drivers to complete 

self-monitoring on stopping performance forms twice per day. Phase two 

added self-monitoring of remaining motionless after loading/unloading 

and continued for five days. Phase three added self-monitoring of bus 

stopping position and checking mirrors and was also five days in duration. 

Bus drivers received regular feedback on their self-monitoring data from 

the previous day in the form of individual and group graphs posted in the 

drivers’ lounge. As a validity check, drivers were asked to initial the 

feedback graphs each day to indicate that the feedback had been viewed. 

In addition, supervisors were asked to prompt drivers via radio twice each 

day to complete their self-monitoring forms. 

Supervisors also conducted special ride-along sessions with drivers to 

observe the behaviors being self-monitored by the drivers. On such 

occasions, experimental observers were also present on the bus during the 

duration of the supervisor assessment to record driver performance. The 

drivers were not informed of the presence of the experimental observers 

until the debriefing following conclusion of the study. 

Relevant Findings: Overall, the drivers improved their safe driving by an average of 12.3% 

over baseline conditions. Complete stopping improved by an average of 

21.2% (range: 14%–41%), motionless after loading/unloading improved 

by an average of 11.8% (range: 3%–19%), mirror checking improved by 

an average of 10% (range: 3%–15%), and bus stopping position improved 

by an average of 6.2% (range: 2%–12%). Individual levels of 

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improvement varied greatly across different behaviors, suggesting 

individual differences in the effectiveness of the self-monitoring 

procedures. Interestingly, participant 1 demonstrated the greatest average 

improvement (14%), the most consistent improvements across phases, and 

also provided the most accurate estimations of his own safe performance 

levels. An in-depth examination of participant 4 demonstrated the smallest 

average improvement over baseline (10%), and the least accurate selfratings. This may suggest that the greatest improvements in performance 

occur when participants are most accurate in their self-estimations of 

performance. However, accuracy levels were not directly related to 

performance levels at all points in the study for all participants. The 

accuracy of self-observations appears to be related to performance, but a 

clear pattern is not apparent given the current data. 

Although only small improvements in behavior were observed in this 

study, the cumulative benefits of small effects should not be ignored. A 

12.3% improvement in overall performance of safety-critical behaviors 

may have a large impact on an organization if those effects are observed 

across all employees. Given similar levels of improvement as observed 

from the four drivers that participated in the study, the transit system could 

experience 31,200 fewer at-risk behaviors across all (68) employed drivers 

each month, and 374,400 fewer at-risk behaviors each year. 

Limitations: The sample used in the current study was extremely small, thus making it 

difficult to draw conclusions about observed trends in the data. In 

addition, a longer time period of observation would be beneficial to assess 

whether performance improvements remain stable after the completion of 

the intervention. 

In addition, the study may not have succeeded in adequately motivating 

employees to participate in the self-monitoring process because employees 

were not involved in the design of the BBS procedures. Past research on 

BBS suggests that employee participation is key to the success of the 

process because it encourages employee buy-in. 

Categorization: This paper fits within the post-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Self-management, as it evaluates the 

effectiveness of driver self-monitoring in the busing industry. 

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Reinach, S.J., & Everson, J.H. (2005). Transit bus operator performance and attitudes toward a 

collision warning system: Results of a simulator experiment. Traffic Injury Prevention, 6, 

248–57. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

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Driver Attitudes 

Towards Technology

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Haddon Matrix for Review #2: Improving Driver Safety

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Author Abstract: Objective: This article discusses the results of a simulator experiment to 

examine the efficacy of a collision warning system for transit bus 

operators. 

Methods: Bus operators from a major metropolitan transit agency were 

assigned to one of three conditions: a collision warning system with a 

visual-only driver-vehicle interface, a collision warning system with a 

visual and auditory driver-vehicle interface, or no collision warning 

system (baseline). Operators were exposed to a critical event at the end of 

the simulation, in which a vehicle suddenly stopped in front of the bus 

while the operator was distracted by an in-vehicle task. Upon completing 

the experiment, operators who used the collision warning system were 

asked about their experience using the system, as well as whether or not 

they would like such a system in real life. 

Results: Experimental results revealed new information about transit bus 

operator performance, but indicated no statistically significant differences 

among the three conditions. Subjective data indicated that operators had a 

positive attitude toward collision warning system usage. Operators 

generally liked the collision warning system and felt that a system such as 

the one used in the experiment would help them in avoiding crashes in the 

real world. 

Conclusions: These findings suggest that a collision warning system for 

transit bus operators is feasible from the perspective of user acceptance. 

However, several technical areas still need to be resolved. 

Industry Sector: Transit bus industry 

Purpose: The purpose of this research was to further the Federal Transit 

Administration’s (FTA) understanding of the potential efficacy of a transit 

bus CWS and how such a system may be designed to be most effective 

and accepted by transit bus operators. 

Sample: 24 bus operators from New York City Transit (NYCT). 

167
Methodology: The simulator used in the experiment consisted of a mock bus driver’s 

workstation, similar to that used by many NYCT operators. The CWS 

driver-vehicle interface (DVI) consisted of two columns of seven 

vertically-stacked light segments mounted in the simulator cab, as well as 

an auditory warning alert. It was designed to present the operator with 

information regarding the imminence of the collision as well as the 

location of the threat. As a hazardous situation became more imminent, 

progressively more light segments illuminated; in addition, the visual 

display illuminated amber to indicate the presence of a less severe threat 

and changed to red to indicate a more imminent hazard. At the seventh, 

and most imminent, level, the audible warning alert also sounded. 

Participants received an incentive for on-time performance and successful 

responses to master alarms. The drivers encountered two very minor 

hazardous situations involving a threat vehicle during a practice route, and 

encountered one additional minor hazard part-way through the 

experimental route. The critical event at the end of the experimental route 

consisted of a lead vehicle braking to a stop in front of the bus, just as 

operators were distracted by the need to respond to the master alarm. The 

goal was to create a simulated distraction that required the operator to look 

away from the forward roadway just as the scenario became hazardous. 

The 24 participants were equally divided into one of three conditions: A 

visual-only DVI, visual and auditory DVI, or baseline (no DVI and, 

consequently, no CWS). The dependent variables included whether or not 

drivers crashed, operator response time to the lead vehicle braking, and 

various vehicle velocity, response time, and time-to-collision values at 

various points in the critical event sequence. The operators who were 

exposed to the CWS were asked to complete a brief survey regarding 

subjective workload and preference ratings with respect to the CWS and 

DVI. It was expected that operators with the visual and auditory DVI 

would perform better than those with the visual-only DVI, and both sets of 

operators exposed to the DVI would outperform those with no CWS. 

Relevant Findings: Five of the 24 bus operators crashed in response to the experimental 

critical event (two in the baseline condition, two in the visual-only DVI 

condition, and one in the visual and auditory DVI condition). In addition 

to crash outcome, a number of other safety measures were examined for 

the 17 participants who did not crash and who braked as their primary 

evasive maneuver. Operators in all three conditions averaged the same 

maximum deceleration of −0.433 g in response to the critical event. 

Although not statistically significant, those in the baseline group stopped 

closer to the lead vehicle than those in the two DVI conditions. Operators 

in the visual and auditory DVI condition were also slightly faster to brake 

in response to the critical event compared to operators in the visual-only 

DVI and baseline groups. 

168
Responses to the survey questions, completed by the 16 operators exposed 

to the CWS, revealed that the visual and auditory DVI was rated as 

slightly more useful than the visual-only DVI. However, operators also 

found the visual and auditory DVI slightly more annoying and distracting 

than the visual-only DVI. Overall, operators gave a positive assessment of 

CWS usefulness, and did not find the CWS to be overly annoying or 

distracting. Seven operators reported that the CWS improved their 

workload, while another seven reported no difference. One operator felt 

that the CWS negatively affected his or her workload. In general, 

operators felt that a CWS like the one they experienced in the simulator 

would be useful to them in the real world. 

Overall, experimental results indicated that the CWS appeared to neither 

improve nor worsen operator performance during the critical lead vehicle 

event. As a possible explanation for these inconclusive findings, the 

authors posited that a CWS may not improve operator performance, given 

that operators are already highly trained, defensive drivers. It is also 

possible that the design of the critical event did not allow for differences 

in operator performance to be exhibited; in other words, the critical event 

may have been too easy to avoid. Another possibility is that the CWS was 

not optimized for use in the low-speed, high-obstacle-laden urban transit 

bus driving environment. 

Limitations: The authors suggested that the sample used in this experiment may have 

been too small to allow a difference between CWS usage and no CWS to 

be detected. A post-hoc power analysis indicated that adding a few more 

participants in each condition (from about 6 to 8) would increase the 

power to detect a difference from 67% in the current study to 85%. 

Another shortcoming of the study was that false alarms (providing a 

warning when no hazard exists) and nuisance alarms (providing a warning 

to the operator when the operator is already aware of the hazard) were not 

evaluated as a measure of effectiveness of the CWS performance. The 

researchers stated that the impact of false and nuisance alarms on operator 

performance, acceptance, and trust of the CWS is a major issue that must 

be studied further and resolved prior to CWS deployment. 

Categorization: This paper fits within the post-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Attitudes Toward Technology, as the 

project assessed the usefulness of a vehicle-based CWS and DVI in terms 

of driver performance and operator acceptance. 

169
a

Roetting, M., Huang, Y.-H., McDevitt, J.R., & Melton, D. (2003). When technology tells 

you how you drive—truck drivers’ attitudes towards feedback by technology. Transportat

Research Part F: Traffic Psychology and Behaviour, 6, 275–287. 

ion 

b

Huang, Y.-H. , Roetting, M., McDevitt, J.R., Melton, D., & Smith, G.S. (2005). Feedback by 

technology: Attitudes and opinions of truck drivers. Transportation Research: Part F Traffic 

Psychology and Behaviour, 8, 277–297. 

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Attitudes 

Towards Technology

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Motor Carrier 

Environment

Driver Attitudes 

Towards Technology

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: aBehavior based safety approaches have proven effective in reducing 

accidents in industrial settings, but cannot easily be extended to 

commercial driving. For considerable periods of working time, truck 

drivers are alone, and do not interact with peers. It might be possible to 

use data gathered by new in-vehicle technology to provide real-time and 

post-shift feedback to drivers about their driving behavior. This paper 

reports the results of focus group interviews conducted with SMEs from 

the trucking industry (truck drivers, supervisors, managers, and other 

involved persons, such as insurance industry safety professionals). The 

focus groups discussed safety critical behaviors in commercial driving, the 

best way to provide feedback to truck drivers, and benefits of feedback by 

technology as well as concerns drivers and operators may have regarding 

monitoring and feedback systems. The focus group discussions showed 

that, in general, drivers would like to receive more feedback and that 

feedback by technology is acceptable, if designed and implemented 

properly. In addition, the participants had many suggestions on how to 

properly design and implement such systems. 

 bThis study explored the potential uses of feedback systems in the trucking 

industry as a means of improving safety. Since truck drivers spend a 

majority of their working time alone and do not interact with peers, it may 

be possible to use data gathered by in-vehicle technology to provide 

feedback to drivers about their driving behavior. The purpose of this study 

was to examine truck drivers’ attitudes toward using in-vehicle technology 

to provide feedback for enhancing driving safety and to understand the 

best ways of providing feedback to truck drivers. Nine focus groups were 

conducted, with a total of 66 participants, to collect qualitative data on 

attitudes toward technology and feedback. The focus group results were 

used to develop a questionnaire. Survey data were then collected from 198 

long-haul truck drivers to provide quantitative information. Truck drivers 

170
reported that they would like to receive more feedback and that positive 

feedback was preferred over negative feedback. Feedback from truck 

drivers’ supervisors or managers was more desired than feedback from 

technology. However, most drivers were willing to accept feedback by 

technology if the program was designed properly. The truck drivers 

expressed no strong preference regarding the best form of feedback by 

technology on driving performance (i.e., modality, frequency and timing). 

Therefore it is important for a program which uses technology for 

providing feedback to be adaptable to different drivers’ preferences. 

Industry Sector: abTrucking 

Purpose: abThe purpose of the Roetting (2003) and Huang (2005) studies were to 

explore truck driver opinions of the use of technology as a means of 

providing feedback to drivers concerning safety-related behaviors. BBS 

methods focus on using feedback as a teaching mechanism to encourage 

improvements in safety. However, most commercial drivers work alone in 

the truck, leaving little opportunity for immediate driving feedback. Invehicle technology may function as a feedback tool that drivers can use to 

improve their safe driving behaviors. 

Sample: abThe initial focus group sample included a total of 66 participants: 35 

long-haul drivers, 5 short-haul drivers, 12 managers, and 6 insurance 

professionals, all recruited from the northeast. 

 bThe follow-up survey sample included 198 North American, long-haul 

truck drivers. 

Methodology: abNine focus groups were conducted with truck drivers, managers, and 

insurance professionals. Each of the focus groups incorporated openended questions concerning characteristics that make a safe driver, past 

experiences receiving feedback, awareness of in-cab technology, benefits 

and drawbacks of receiving feedback from in-cab technology, and how 

one would prefer to receive safety feedback. All focus groups used a 

discussion format to obtain the answers to these questions. Data from 

audio recordings, detailed notes taken by a member of the research team, 

and flip charts created in each session were consolidated into a single 

transcript. The written information was then coded and sorted to identify 

major themes from the focus group discussions. 

 bUsing the results from the focus groups, a survey was developed to 

collect additional data from long-haul truck drivers concerning the use of 

in-vehicle technology for safety feedback. Truck drivers were recruited 

from a truck stop in New England to participate in the survey. Participants 

were asked to provide demographic information, rank the most important 

critical safety behaviors of truck drivers, and respond to a number of 

171
questions concerning in-vehicle technology using a 1 to 5 response scale 

where 1 equaled “strongly disagree” and 5 equaled “strongly agree.” The 

major topic areas of the survey questions paralleled those covered in the 

focus groups. 

Relevant Findings: abDrivers in both studies reported that using mirrors and turn signals, 

looking well ahead of the vehicle to adjust to what is happening, having 

patience, and being ready to expect the unexpected from other drivers on 

the road are all characteristics that make for a good, safe truck driver. 

Drivers in the focus groups also reported that they believe other truck and 

automobile drivers were often equally, or more, responsible for the unsafe 

behaviors of truck drivers. In addition, there was concern that safety can 

be negatively affected by demanding dispatchers who are unaware of the 

challenges of driving, inconsistent application and enforcement of federal 

regulations, and a lack of secure rest areas to stop at when fatigued. 

The group discussions also suggest that drivers want feedback that is 

specific, constructive, respectful, and individualized. However, responses 

varied when participants were asked about the feedback given and 

received at their particular company. Feedback appears to be dependent 

upon the safety climate of the company. Some drivers reported receiving 

very little feedback and having very little interaction with their company’s 

management, whereas others reported more positive and frequent 

interactions, including regular feedback from supervisors. 

The focus group participants indicated that they expected in-cab 

technology to be beneficial for driving performance and efficiency. It was 

also perceived as having the potential to reduce driver stress. Feedback 

from technology was viewed positively because it is objective, and 

therefore may aid in vindicating drivers in the event of an incident or 

crash. However, participants reported some concern about privacy issues 

when using in-cab technology. Many reported that they would not be 

comfortable being “watched” by technology. Other concerns included the 

initial costs and reliability of the technology, and the potential to rely too 

heavily on technology and less on routine safe driving habits. 

Participants agreed that even when feedback is given by a machine, 

additional human feedback is still wanted. There was less agreement 

concerning the form and timing of the feedback received from the in-cab 

technology. Some drivers preferred an audible or visual alarm 

immediately, whereas others suggested composing an electronic report or 

printout that would be available on a daily, weekly, or monthly basis. Still, 

others wanted to be able to access feedback information using multiple 

formats at driver-specified times. 

172
 bResults from the truck driver survey support the findings of the focus 

groups. In general, truck drivers expressed a desire to receive more 

feedback, and preferred feedback that was positive in nature. When asked 

about the perceived benefits of receiving feedback by technology, 56% of 

drivers believed that the data from the technology may aid in defending a 

driver if involved in an accident, 46% of the drivers agreed that in-vehicle 

technology would make them a safer driver, and 31% thought that the 

technology might reduce their stress levels. Privacy issues were again 

cited as a drawback to in-vehicle technology in the survey sample, with 

65% of drivers reporting concern about the data from in-vehicle 

technology getting into the wrong hands. The majority of drivers were not 

concerned about the complexity of the technology. However, 52% of the 

drivers agreed that relying too heavily on in-cab technology may lead to a 

loss in safe driving skills. Additionally, 49% of the drivers thought that 

receiving feedback from technology could be a distraction for drivers. 

When asked about the preferred mode of feedback, results were mixed. 

Forty seven percent reported that they would like to receive feedback from 

a display on the dashboard, 37% responded favorably to receiving a 

computer printout at the end of their shift, and 20% indicated that they 

would like a computerized voice. Results were also split regarding the 

timing of feedback, 51% of respondents preferred having feedback 

delivered when they requested it, whereas 43% agreed that they would like 

to receive feedback at regularly scheduled intervals. Fifty six percent of 

drivers reported that they would like to receive feedback immediately after 

driving. However, there was no clear preference for how frequently 

feedback should be received. It ranged from once a day to once a year. 

Results were split when asked about feedback from technology in 

comparison to feedback from a real person. Equal numbers of truck 

drivers (37%) agreed and disagreed with the statement, “Receiving 

feedback about how I drive from technology is as helpful as feedback 

from a real person,” with the rest indicating that they were neutral. As in 

the focus groups, the survey results suggested that, even though drivers 

may find feedback from technology helpful, they would still like feedback 

from a real person in addition to the technology. The majority of drivers 

reported that when it comes to receiving feedback from a person, they 

would most like feedback from a safety director or their direct supervisor, 

followed by a dispatcher, driving partner, or another truck driver. Drivers 

most often disagreed with wanting to receive feedback from a “1-800 

how’s my driving” service or “4-wheelers” (truck driver slang for 

automobile drivers). 

 abOverall, participants from both studies seemed to be receptive to 

additional feedback concerning their safe driving behaviors, especially 

positive feedback. Participants were receptive to feedback from in-vehicle 

173
technology, yet there were lingering concerns about how data from 

monitoring systems might be used. Using feedback from technology may 

only be beneficial when there exists a strong climate for safety within the 

company and buy-in at all levels. Drivers should also be included in the 

development and implementation of the technology and given some 

choice about how, when, and how frequently they will receive feedback 

from the technology. 

Limitations: abThese studies are preliminary in nature as they are part of an initial needs 

assessment examining feedback by technology as a viable tool to assist in 

implementing BBS initiatives in the trucking industry. All data were selfreport in nature, and participants may not have responded with complete 

candor. In addition, responses from various participants may heavily 

depend on their knowledge and past experience with in-vehicle technology 

and how such a hypothetical system might work. Participants in the focus 

groups and the survey were all recruited from the New England region of 

the United States. In addition, drivers that participated in the survey were 

recruited from a single truck stop. Although participants resided in 40 

different states, caution should be used when generalizing to the entire 

U.S. trucking industry. 

Categorization: These papers fit within the post-event timeframe of the driver environment 

for Haddon Matrix #2: Driver Attitudes Towards Technology, because 

they explored driver opinions about receiving feedback from in-cab 

technologies regarding their safety-related behaviors. 

174
Motor Carrier Environment: How can feedback provided to the motor carrier benefit safety? 

Lantz, B.M. & Blevins, M.W. (2002). An analysis of commercial vehicle driver traffic 

conviction data to identify high safety risk motor carriers. In Z.G. Zacharia (Ed.), 

International Truck and Bus Safety Research and Policy Symposium (pp. 549–556). 

University of Tennessee, Knoxville: National Safety Council. 

Haddon Matrix for Review #2: Improving Driver Safety

Safety Oversight Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Safety Oversight Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: This project explores the idea of using commercial motor vehicle driver 

traffic conviction data from the Commercial Drivers License Information 

System (CDLIS) to help identify high safety risk motor carriers. Prior 

research and intuitive knowledge suggest that certain types of motor 

carriers may employ drivers with higher than average traffic conviction 

rates. This study should help to provide new knowledge of high-risk 

carriers, and allow better focusing of enforcement efforts to reduce crashes 

and fatalities on the highways. 

Because there is not a national traffic citation database, and there are 

substantial problems with state or local police officers accurately 

identifying the employing motor carrier when issuing a traffic citation, a 

direct approach of using citation data for analysis is not feasible 

nationwide. Therefore, the present project studies whether a correlation 

exists between traffic conviction data (a subset of citations), accessible 

through CDLIS, and high risk motor carriers linked to drivers through 

inspection and crash reports contained in the Motor Carrier Management 

Information System. 

This study concludes that linking driver conviction data to the employing 

motor carrier provides a method to identify those motor carrier companies 

with safety problems. A carrier driver history measure created based on 

the average number of convictions of drivers associated with the carriers is 

significantly correlated with carriers’ out-of-service (OOS) rates, accident 

rates, and SafeStat Safety Evaluation Area (SEA) scores. Carriers with 

higher (worse) driver history measures are also more likely to have higher 

OOS rates, accident rates, and SEA scores. 

Industry Sector: Trucking 

Purpose: The purpose of this study was to explore the idea of using CMV driver 

traffic conviction data from the CDLIS to help identify high safety risk 

175
motor carriers. The intended goal of the project was to provide new 

knowledge of high-risk carriers and to allow better focusing of 

enforcement efforts to reduce highway crashes and fatalities. 

Sample: 64,711 truck drivers representing 13,829 carriers. 

Methodology: Carriers were selected using census data from the MCMIS. A stratified 

random sampling scheme was used to include carriers across various size 

categories and geographic regions, with a maximum of 50 drivers per 

carrier being sampled. Drivers were matched to CDLIS driving history 

records for the time period of 1997–2000. Individual driver history 

measures were subsequently created as a weighted sum of each driver’s 

convictions/offenses, where higher scores indicated more and/or more 

serious offenses. Carrier driver history measures were then created by 

calculating the mean value of all individual driver history measures 

associated with that carrier. For each carrier, critical safety data were also 

obtained. This included the number and type of crashes, number and type 

of OOS roadside inspections and violations, and scores in each of the four 

SEAs (Accident, Driver, Vehicle, and Safety Management) of the 

SafeStat. 

Relevant Findings: Results of correlation analyses indicated significant positive linear 

relationships, where, generally, higher carrier driver history scores were 

associated with higher OOS rates, crash rates, and SEA scores. A detailed 

examination of carriers by size group also revealed significant positive 

correlations between the carrier driver history measure and carrier safety 

data. In addition, significant positive correlations were found between the 

carrier driver history measure and driver OOS rates and driver SEA scores 

for carriers in each region of the country; and the carrier driver history 

measure was significantly correlated with crash rates per power unit in 

every region except the Deep South and Great Lakes regions. Thus, 

carriers employing drivers with more severe driving history records were 

also more likely to have greater numbers of recorded crashes, OOS 

violations, and poorer performance on the SafeStat SEAs. Based on these 

results, the authors reached the overall conclusion that linking driver 

conviction data to the employing motor carrier appeared to serve as an 

indicator of those motor carrier companies that have safety problems. 

Limitations: This study is very exploratory in nature as only correlational analyses 

were performed to test for a relationship between driver history and carrier 

safety status. The authors also point out the need for further research to 

determine exactly how this information can be used. 

Categorization: This study fits within the post-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Safety Oversight, as driver conviction 

data was used to link drivers with their carriers as a means to identify high 

safety risk motor carriers. 

176
Smith, M., Owens, N., Stock, D., Lantz, B., & Murray, D.S.G. (2005). Driver violation 

notification service feasibility study. Washington, D.C.: Federal Motor Carrier Safety 

Administration. (NTIS No. PB2005-110645) 

Haddon Matrix for Review #2: Improving Driver Safety

Safety Oversight Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Haddon Matrix for Review #2: Improving Driver Safety

Safety Oversight Motor Carrier 

Environment

Driver

Environment

Pre-Event Event Post-Event

Author Abstract: The Driver Violation Notification Service Feasibility Study assessed the 

safety benefits of driver violation notification programs (also known as 

Employee Pull Notice or Driver Pull Notice programs). In these programs, 

states automatically notify motor carriers of changes in their drivers’ CDL 

records due to violations and convictions. The project team analyzed 

programs in ten States, and surveyed several motor carriers, in order to 

both determine how well these programs work and establish requirements 

for an expanded nationwide program. 

Industry Sector: Trucking 

Purpose: This study evaluated the design of commercial DVN systems, also known 

as an Employee/Employer Pull Notice (EPN), and their relationship to 

highway safety. One of the major goals was to shorten the time between a 

driver receiving a conviction for a driving violation and the employer 

being notified. It was surmised that more prompt notification of 

convictions will allow more carriers to take immediate and appropriate 

corrective action to mitigate the potential negative consequences of highrisk driving behaviors. 

Sample: 10 states already using a DVN-type program and 4 states that did not have 

DVN programs in place. 

Methodology: The DVN Study Team conducted a five-stage research program. The 

approach used for each stage or study task is described below. 

Task 1: State Visits to Government Agencies—Interviews were conducted 

with representatives responsible for implementing each state’s DVN 

program, as well as representatives from FMCSA, in order to understand 

existing DVN-type programs and obtain information on costs and 

effectiveness. For states without an existing DVN program, potential 

implementation issues were identified that, if not addressed, would impact 

the success of a national program. 

177
Task 2: Document User Requirements for DVN Programs—The Study 

Team conducted focus groups, interviews, and a motor carrier survey to 

obtain information on the effectiveness and user requirements of existing 

DVN-type programs, as well as to identify lessons learned and best 

practices. 

Task 3: Cost/Benefit Analysis—Two analyses were conducted to 

determine the economic feasibility of expanding DVN programs on a 

nationwide basis. The first analysis used data from national commercial 

vehicle and CDL databases to assess the relationship between previous 

serious convictions or crash involvement for drivers who were involved in 

fatal crashes. The second analysis focused on identifying the difference in 

crash risk between drivers with no convictions in the prior 12 months and 

those having had a crash within 12 months of the most recent conviction. 

Task 4: Develop Alternate Approaches for the Deployment of DVN 

Programs—The functional requirements of an Employer Notification 

Service (ENS) were defined. In DVN states, state DMVs and law 

enforcement agencies offered suggestions based on their own state’s 

experience with a DVN program. In non-DVN states, suggestions were 

based on what they believed would be needed for an effective ENS. 

Task 5: Recommend Deployment Approach and Work Plan for the 

Development of DVN Programs—The recommended deployment 

approach was developed using findings from the preceding four tasks, in 

particular, the preferences stated by government and industry stakeholders 

identified in Tasks 1 and 2. 

Relevant Findings: Results of the focus groups, interviews, and surveys indicated support 

from both DVN and non-DVN participants for a national DVN program. 

Motor carriers expressed a preference for an internet-based, national 

program with a centralized registration and notification system. 

Additionally, a considerable number of participants indicated that the 

national program should be mandatory in order to create a level playing 

field for all carriers, and should provide some type of incentive for 

enrollment. 

Results of the cost/benefit and crash risk analyses confirmed the 

hypothesis that poor driving behavior, as demonstrated by prior 

convictions and involvement in crashes, increases the risk of involvement 

in future crashes. A greater percentage of drivers had one or more crashes 

within the 12-month period following a conviction than those with no 

convictions in the previous 12 months (2.98% as compared to 2.17%) This 

difference, multiplied by the number of convictions nationally, represents 

the maximum potential DVN benefits, in terms of reducing the number of 

drivers involved in crashes. Costs of a DVN program were estimated 

178
based on information obtained from three states with existing DVN-type 

programs. Thus, the overall outcome from this analysis was a Benefit/Cost 

Ratio of $121 million/$7.8 million per year. In other words, the benefits of 

a DVN program are estimated to outweigh the costs by a magnitude of 

15.6. 

Several alternative approaches to the design and operation of an ENS were 

evaluated. Currently, a jurisdiction-based approach is used, in which each 

jurisdiction determines whether or not to offer an ENS, which employers 

to include, and how best to provide it. After considering many alternatives, 

the DVN Study Team recommended a decentralized nationwide system 

that would include: the ability to post a notice of change in a driver’s 

history record, which would in turn direct the notice to the driver’s 

employer; the capability for motor carriers to receive DVNs from all 

states; web-based processing to enable all motor carriers to access 

program services, irrespective of size or technical capability; and public 

domain ownership of the system, with system operation done through 

either the Federal government (e.g., FMCSA) or through an association 

representing public agencies involved in motor carrier regulation and 

credentialing (e.g., American Association of Motor Vehicle 

Administrators [AAMVA]). 

Limitations: The DVN Study Team identified several issues that will need to be 

addressed prior to implementation of the national system; these issues will 

be evaluated in an upcoming national pilot program. 

Categorization: This study fits within the post-event timeframe of the motor carrier 

environment for Haddon Matrix #2: Safety Oversight, because the 

program is aimed at providing CDL driver conviction information to 

motor carriers in a timely manner to enable the carriers to take quick 

corrective action to potentially reduce crash risks caused by at-risk drivers. 

179
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bus safety: Guidelines for acquiring and using transit bus operator driving simulators

(TCRP Publication No. 72). Transportation Research Board; Milestone Group, L.L.C. (NTIS 

No. PB2002-102252) 

Foreword: TCRP REPORT 72, “Simulators and Bus Safety: Guidelines for Acquiring and 

Using Transit Bus Operator Simulators,” provides guidance to transit agency managers on 

whether to purchase a driving simulator and, if so, what kind. Also, this document provides 

guidance on how to use simulation effectively to improve bus operator training and safety. 

Information was obtained from a literature search, surveys, and site visits. The guidelines are 

designed to be used by transit-operations management, human resource management, 

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prevention may seem fundamental, but it is absolutely essential that we be able to identify the 

right issues and quantify those issues before developing, negotiating and implementing any 

strategy that requires changes to the existing programs and/or union contracts. Listed below 

are the four (4) steps to accident reduction identified by the Denver RTD: (1) Identify and 

quantify the right issues; (2) Negotiate any necessary changes in union contracts; (3) 

Implement strategy or changes needed to reduce accidents; and (4) Measure effectiveness. 

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Symposium (pp. 371-385). University of Tennessee, Knoxville: National Safety Council. 

Abstract: Roadway fatalities represent the single greatest cause of death for young adults in 

North America, ages 15 to 29. The societal cost of roadway fatalities and injuries in the 

United States alone exceeds Canada’s national revenue budget. Between the United States 

and Canada, the cost of roadway fatalities and injuries is in the order of $160 billion 

annually. Although motor vehicle injuries and fatalities can be attributed to a wide variety of 

drivers and vehicles, the carrier industry including regulators and legislators, public safety 

advocates, shippers, and insurers are facing significant pressure to improve on-road safety in 

both the trucking and busing sectors. Historically, these pressures have been satisfied through 

the creation of more legislation and regulations, followed by enhanced enforcement and 

increased punitive action. The purpose of this paper is to highlight, for the benefit of 

transportation safety stakeholders, the value and contribution consensus based, national or 

international standards can bring to achieving these initiatives and road safety goals, and the 

support than can be derived through third party certification/qualification programs. This 

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180
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TRIS Abstract: This report presents a directory of effective practices used to prevent bus 

accidents at small, medium, and large transit systems. Most of the information was obtained 

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insurance pools in six states. The directory is designed to be used by transit management, 

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Farber, F.S. & Miskulin, J.C. (2004). Performance management - Is it time? Bus and Paratransit 

& Bus Rapid Transit Conference. Washington, D.C.: American Public Transportation 

Association. 

 Author Abstract: How do transit agencies know when they are meeting strategic objectives? 

Are they driving the right behaviors in their organizations? Do they identify the warning 

factors of negative change? 

Those familiar with performance management design, implementation, and analysis 

understand the challenges of establishing a system of effective performance measures. 

However difficult it may be, successful organizations attest to the rewards. Measuring results 

allow a transit agency to determine what is successful and what is not. 

Establishing a successful performance management program requires a focus in several key 

areas. The first requires the creation of a framework that links organizational objectives to 

the business unit (departments) and individual levels by ensuring that everyone understands 

not only how roles align with organizational objectives, but also how each unit and 

individual contributes to the outcome. 

The next area is the design of measures. Transit agencies need to produce measures that align 

with strategic objectives, demonstrate results, and focus on the results, while avoiding 

potential challenges (and/or pitfalls) during the development process. 

The third topic area centers on the determination of how to use measures and get more 

leverage; and finally, converting theory into practice. This is often regarded as the most 

difficult aspect of successfully implementing a performance management system. For any 

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increasing data integrity, building communications and ensuring a firm commitment to the 

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350).University of Iowa Public Policy Center. 

Author Summary: A two-day conference that addressed “improving safety for drivers and 

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truck alliance and the Federal Motor Carrier Safety Administration (FMCSA). The 

conference brought together stakeholders within the trucking industry and safety experts 

181
from other industries to explore approaches to improve driver and fleet safety. The goal of 

the conference was to facilitate discussions among industry stakeholders as a first step in 

identifying and implementing effective safety processes that may advance the FMCSA’s 

ambitious goal of 50% reduction in truck-related fatalities by 2010. On day one there were 

three sessions related to trucking and industrial safety. The first session offered two views of 

historical safety initiatives as a foundation for understanding current industry safety 

practices. The second session focused on current efforts by government, fleets and truck 

manufacturers. The third session provided an opportunity for presenters to describe 

successful safety programs not currently being widely applied to the trucking industry. 

 On day two a morning-long panel discussion considered the approaches presented the 

previous day. A subsequent brainstorming session involving all attendees generated other 

independent or related approaches. The goals of the discussions on day two were 1) to 

identify practical safety steps that can be applied by fleets and drivers now and in the near 

future and 2) to identify potential partnerships for implementing and testing new safety 

initiatives. Ultimately, the panelists and participants developed 26 action items that will be 

ranked and used as a springboard for future truck safety efforts. 

Hartman, K., Jennings, K., Johnsom, J., Knipling, R., Macgowan, J., Oliphant, L., Onder, M., 

Pritchard, B., & Sanft, C. (2000). Commercial vehicle safety: Technology and practice in 

Europe (FHWA Publication No. PL-00-010). Federal Highway Administration (U.S. 

Department of Transportation). (NTIS No. PB2001-101244) 

Author Abstract: The United States and countries of the European Union share many of the 

same concerns and face similar challenges about commercial vehicle safety issues. This 

summary report describes the September 1998 technology transfer scan tour to four European 

countries to learn how these countries are addressing their own safety issues, even as they 

comply with the increasing centralization of rules and regulations enacted by the European 

Commission. The nine-member scan tour team that visited France, Germany, Sweden, and 

the Netherlands represented the Federal Highway Administration, the Virginia and 

Minnesota State Departments of Transportation, the Owner/Operators and Independent 

Drivers Association, and independent transportation consultants. The key areas examined by 

the team were human resources, vehicle safety systems, and regulations. The report also 

includes recommendations and implementation strategies. 

 As this report demonstrates, team members were particularly interested in the European’s 

integrated approach to driver training and preparation, the role of truck manufacturers in 

assessing crash causes and statistics to improve safety design, and the public/private 

partnerships that enhance training and safety, and augment regulatory policies and practices. 

The team believes that these practices provide valuable models for fresh opportunities for 

public/private cooperation in the areas of safety enhancement, regulatory policies, and 

standards enforcement for the U.S. motor carrier industry. 

Hickman, J.S. (2006). High-risk commercial motor vehicle drivers and differential crash risk: 

Future directions. In N. Kassabian (Ed.), Future Truck and Bus Safety Research 

Opportunities (pp. 16-23). Washington, D.C.: Transportation Research Board. 

TRIS Abstract: A variety of factors influence commercial motor vehicle (CMV) driver risk. 

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Few studies have attempted to integrate all the interacting factors that may contribute to an 

increased risk of a crash and most studies fail to account for exposure. Most studies use selfreports of prior crashes or retrospective Department of Motor Vehicle records. These 

approaches have limited utility because they are likely to be inaccurate, crashes are not 

always reported, and near crashes are not considered. Current knowledge suggests there are 

certain factors associated with high-risk driving, but a comprehensive model on how these 

factors interact with each other does not exist. Further, all of these factors have not been 

included in one study, nor have they been studied under naturalistic driving conditions. The 

finding of differential crash risk among CMV drivers along many safety-related personal 

dimensions presents an opportunity for the trucking industry and government safety officials. 

Suggested research and development opportunities for addressing the problem of high-risk 

drivers include the following: validating prior research findings indicating differential driver 

risk; determining how enduring these differences are across time; profiling individual 

differences within a group of drivers and relating these differences to safety outcomes; 

assessing the efficacy of various driver selection instruments; verifying that differences in 

fatigue susceptibility are long-term personal traits, identifying ways to assess the level of 

fatigue susceptibility, and determining the physiological basis of differential fatigue 

susceptibility; documenting and disseminating the best driver management practices for use 

by carrier safety managers; developing onboard safety monitoring (OBSM) devices that can 

record a variety of safety-related driving behaviors and management protocols for the 

successful use of OBSM data for reducing at-risk driving behaviors and crash rates; 

improving driver training programs; and industry pilot testing of behavioral safety 

management techniques to reduce the risky driving behaviors of high-risk drivers. 

Iavicoli, S., Rondinone, B., Marinaccio, A., & Fingerhut, M. (2006). Research priorities in 

occupational safety and health: A review. Industrial Health, 44, 169-178. 

Author Abstract: Changes in the world of work in the last few decades have markedly 

affected questions regarding OSH. Jobs in our economy continue to shift from manufacturing 

to services. Longer hours, shift work, reduced job security, temporary work are realities in 

the modern workplace, new chemicals, materials, processes are developed at an ever 

accelerating pace. The workforce is also changing. It will become older and more racially 

diverse and women are increasing. These changes present new challenges to protect worker 

safety and health and it was been indispensable to redefine priorities, by consulting all those 

involved in OSH. The present study therefore made a critical comparative analysis of the 

main published projects to identify research priorities in the OSH field, comparing methods, 

approaches and results. Comparison of the priority areas established in each of these studies 

is inherently difficult due to differences in socio-cultural backgrounds, in the methods 

employed to identify priority topics, and the many factors involved. However, it is clear that 

the Delphi technique is widely used as a reliable method, in that it covers a broad range of 

qualified witnesses, from a variety of backgrounds-such as trade union representatives and 

researchers-providing different viewpoints. It also takes account of the intrinsic features of 

OSH which-compared to other disciplines-involves multidisciplinary factors calling into play 

a range of scientific settings, such as toxicologists, molecular biologists, epidemiologists, 

occupational hygienists and occupational physicians. This analysis showed how important it 

is to reach consensus among all those operating in the OSH sector, in order to establish 

standard methods that can be applied in different contexts, and give results that can be validly 

183
compared. 

King, R. D. (1996). Bus occupant safety. TCRP Synthesis of Transit Practice, 18.

Author Abstract: This synthesis will be of interest to transit agency general managers, bus 

operations, safety, and risk management staffs, as well as agency human resources, 

personnel, and training staffs. It offers information on the current practices of transit agencies 

to reduce injuries to bus occupants during collisions and injuries to passengers while 

boarding, riding, and leaving the bus. This synthesis covers characteristics of bus occupant 

safety and transit agency programs for reductions of accidents/incidents such as those 

addressing driver and customer safety, vehicle improvement needs and safety inspections, 

bus stops and stations, safety management, and state transit agencies and transit operating 

companies. 

Knipling, R.R. (2005). Evidence and dimensions of commercial driver differential crash risk. 

Driving Assessment 2005: 3rd International Driving Symposium on Human Factors in Driver 

Assessment, Training, and Vehicle Design (pp. 2-8). Iowa City: University of Iowa. 

Summary: This paper highlights evidence from several instrumented vehicle studies that 

crash risk varies significantly among commercial truck drivers, and also cites findings from 

surveys of fleet safety managers and other experts on the topic of individual differences in 

commercial driver crash risk. Within various subject groups, 10-15% of the drivers typically 

account for 30-50% of the crash risk. This pattern is seen in measures of driver errors 

associated with crashes and also in measures of driver drowsiness. The evidence also 

suggests, but does not yet prove, that these individual differences are long-term. To the 

extent that these individual differences are long-term, they may be considered personal traits. 

This paper conceptualizes driver risk factors, provides illustrative examples of differential 

individual risk within groups of drivers, identifies driver factors thought to be most 

associated with crash risk, and considers the opportunities for improved commercial driving 

safety presented by differential crash risk. 

Knipling, R.R., Alvarez, A., Carroll, R.J., Robin, J.L., & Roke, P.J. (2002). Commercial driver 

human factors R&T. In Z.G. Zacharia (Ed.), International Truck and Bus Safety Research 

and Policy Symposium (pp. 3-14). University of Tennessee, Knoxville: National Safety 

Council. 

Author Abstract: The human element is dominant in commercial motor vehicle (CMV) 

crashes, as in all types of traffic crashes. Driver human factors research and technology 

(R&T) at the Federal Motor Carrier Safety Administration (FMCSA) is directed toward 

improving CMV driver safety performance as a means of CMV crash reduction. This 

includes R&T to better assess the problem; improvement of driver physical qualifications and 

health; R&T on CMV driver training, licensing, and safety performance; and R&T on CMV 

driver alertness and fatigue. In addition, studies of carrier safety management include human 

factors-related approaches to increasing the safety knowledge and motivation of drivers and 

other carrier personnel. This paper reviews the principal safety issues and agency activities 

associated with these human factors R&T areas, which are coordinated and managed 

primarily by the Research Division of the FMCSA Office of Research and Technology. It 

highlights recent findings, current activities, and future plans relating to these human factors 

issues. 

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Knipling, R.R., Boyle, L.N., Hickman, J.S., York, J.S., Daecher, C., Olsen, E.C.B., & Prailey, 

T.D. (2004). Individual differences and the high-risk commercial driver. Transportation 

Research Board Commercial Truck and Bus Safety Synthesis Program (CTBSSP) Synthesis 

4. (NTIS No. PB2005-100981). http://www.trb.org/news/blurb_detail.asp?id=4295

Foreword: This synthesis will be of use to state agencies, commercial truck and bus carriers, 

and others interested in improving commercial vehicle safety. It explores individual 

differences among commercial drivers, particularly as these differences relate to the “highrisk” commercial driver. The synthesis identifies factors relating to commercial vehicle crash 

risk and assesses ways that the high-risk driver can be targeted by various safety programs 

and practices, at both fleet- and industry-wide levels. It summarizes available information on 

individual differences in commercial driver safety performance and alertness, examines 

various metrics and tests that might be used to hire safer drivers and avoid hiring high-risk 

drivers, and identifies safety management techniques that are currently used by commercial 

vehicle carriers to target problem drivers and their specific risky behaviors. Information for 

this synthesis was obtained through surveys of current commercial motor vehicle safety 

managers and other experts in commercial motor vehicle safety; a focus group conducted 

with staff members of the U.S. Department of Transportation Federal Motor Carrier Safety 

Administration; and a review of relevant literature. 

Knipling, R.R., Hickman, J.S., & Bergoffen, G. (2003). Effective commercial truck and bus 

safety management techniques. Transportation Research Board Commercial Truck and Bus 

Safety Synthesis Program (CTBSSP) Synthesis 1. (NTIS No. PB2003-107644) 

http://www.trb.org/news/blurb_detail.asp?id=1619

Foreword: This synthesis, the first in the CTBSSP series, will be of use to commercial truck 

and bus carriers and others interested in improving commercial vehicle safety. It provides a 

useful summary of practice in the area of commercial truck and bus safety management 

techniques. The synthesis focuses on the problems fleet managers confront and the methods 

that are available to address these problems. Twenty discrete safety problems and 28 safety 

management methods are identified. Problems addressed encompass driver-safety 

knowledge, skills, alertness, physical/medical condition, attitudes, and driving behaviors. In 

addition, several vehicle-related problem areas, including vehicle maintenance and 

inspection, are discussed. Major safety management approaches addressed include driver 

recruiting and selection, carrier-based training, management-driver communications, driver 

safety-performance evaluation, safety incentives, behavior-based safety, on-board safety 

monitoring, event-data recorders, accident investigation, improved driver scheduling and 

dispatching, fatigue management, carrier-based medical programs, preventive maintenance 

and vehicle inspection, advanced safety technologies, and industry-based safety standards 

and certification. The synthesis is based on a review of relevant literature, as well as a survey 

of commercial motor vehicle safety managers (139 respondents) and other experts in motor 

carrier safety (57 respondents). 

Kompier, M. A. J., Aust, B., van den Berg, A.-M., & Siegrist, J. (2000). Stress prevention in bus 

drivers: Evaluation of 13 natural experiments. Journal of Occupational Health Psychology, 

5, 11–31. 

Author Abstract: The research aim was to select, compare, and analyze interventions and 

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preventive actions from international bus companies to decrease bus drivers’ occupational 

stress and sickness absenteeism. Through networking, international surveys, and literature 

study, 13 “natural experiments” were identified with an acceptable research design rating. 

Interventions were both work and person directed. Principles of worker participation were 

often followed. The variety in intervention programs, outcome measures, case evaluations, 

and methodological flaws makes it difficult to present a general picture of program 

effectiveness. However, analyses on more objective and more subjective outcomes do point 

at positive effects. This study suggests that stress prevention that combines adequate 

interventions and proper implementation may be beneficial to both the employee and the 

company. 

Krause, T.R., Robin, J.L., & Knipling, R.R. (1999). Potential application of behavior-based 

safety in the trucking industry - Final rept. Aug 98-May 99 (FHWA Publication No. MC99/071). Federal Motor Carrier Safety Administration. 

TRIS Abstract: Behavior-based safety (BBS) is a set of methods to improve safety 

performance in the workplace by engaging workers in the improvement process, identifying 

critical safety behaviors, performing observations to gather data, providing feedback to 

encourage improvement, and using gathered data to target system factors for positive change. 

In August, the Federal Motor Carrier Safety Administration (FMCSA) sponsored a group of 

seminars on BBS as part of its human factors research program on driver performance 

enhancement. In particular, FMCSA is interested in ensuring the safe, effective use of current 

and advanced in-vehicle driver performance monitoring devices (e.g., speed monitoring, 

headway monitoring, alertness monitoring). Performance monitoring offers an opportunity to 

improve driver safety and productivity by measuring and providing feedback to drivers on 

critical performance variables. 

Mullen, M. (1996). Truck safety: The search for excellence. F. Saccomanno & J. Shortreed 

(Eds.), Truck safety: Perceptions and reality (pp. 23-28). University of Waterloo: Institute for 

Risk Research. 

TRIS Abstract: The author of this paper acknowledges problems with public perceptions of 

truckers and the trucking industry. He offers ways in which the trucking industry can 

improve its image and its performance. Some of these are: management commitment and 

leadership; setting performance standards; safety accountability; recruitment standards; 

training and skills upgrading; performance measurement; excellence rewards; and correction 

of non-conformance. 

Murray, D.C., Dick, V.R., & Houser, A. (2006). Synthesis of commercial motor vehicle safety 

technology surveys: What have we learned? Transportation Research Board 85th Annual 

Meeting. 

TRIS Abstract: This paper documents and synthesizes the major qualitative survey efforts 

within the U.S. relating to stakeholder design, use and perspectives of onboard truck safety 

technologies. The Federal Motor Carrier Safety Administration (FMCSA) and the American 

Transportation Research Institute (ATRI) have conducted a survey synthesis and metaanalysis to consolidate, analyze, and identify gaps in the existing survey research on safety 

technologies. Over the last several years, there has been an increasing interest in onboard 

truck safety technologies. At different times, entities such as the FMCSA, Federal Highway 

186
Administration (FHWA), ATA and ATRI have undertaken different survey projects to 

document and understand onboard safety technology applications. While a wide variety of 

data has been collected by these projects, there has been little effort to aggregate data across 

projects. The current synthesis includes the analysis of over 11 survey, interview and focus 

group instruments; representing 558 respondents and 56 unique questions. Preliminary 

results indicate that while the existing research addresses many issues related to carrier 

purchase and use of technologies, there is a considerable gap in research addressing driver 

attitudes, experiences, and preferences. At the technology level, satellite or cellular 

communication between terminal and vehicle and GPS are the technologies most commonly 

used by carriers. Most carriers who have a safety technology installed on their fleet have 

already realized the desired safety benefits, often an intangible one from a quantitative 

perspective. Cost and lack of clear data about benefits are the two biggest factors preventing 

wider installation of safety technologies.

Murray, W., & Whiteing, T. (1995). Reducing commercial vehicle accidents through accident 

databases. Logistics Information Management, 8, 22. 

Author Abstract: Commercial vehicle accidents impose very significant costs on industry 

and society but for a variety of reasons the full costs are often poorly understood. It is 

advocated that vehicle operators should undertake a full and systematic analysis of accident 

levels, causes and costs. The CCSM model of vehicle accident reduction is introduced. By 

undertaking analysis based on this approach, most vehicle operators should be able to 

identify measures to reduce accidents substantially. Typical measures include the 

implementation of vehicle accident monitoring systems, driver age and experience policies, 

reviews of vehicle speed policy, driver training schemes, more systematic driver recruitment 

and better vehicle specification. 

National Private Truck Council (2006). National Safety Conference: Solving the Safety Puzzle. 

Program Agenda, Retrieved from https://www.nptc.org/pdf/nscwebprog06.pdf on February 

15, 2007. 

Porter, R.C. (2002). Training and supervision safety regulations used to support company 

negligence claims. In Z.G. Zacharia (Ed.), International Truck and Bus Safety Research and 

Policy Symposium (pp. 323-325). University of Tennessee, Knoxville: National Safety 

Council. 

TRIS Abstract: Is it proper to hire or retain a driver who received two speeding tickets 

within the past year? What about a driver who was convicted of check fraud? Can you hire or 

retain a driver who takes Prozac by prescription? Suppose the driver has been involved in a 

previous major accident? What about four minor accidents, three of which were preventable? 

What if the driver has driven only a box van and you want him to pull a flat bed? If the driver 

has worked as a truck driver for less than a year can you put him to work without any 

training? Should you accept a driver whose eye tests are right at the outer limit of 20/40? The 

answer is “yes,” you can hire these drivers in full compliance with the regulations. Of course, 

if the question is being asked in the aftermath of a serious accident involving that driver, the 

company will be portrayed as acting in reckless disregard of its safety obligations. In any 

driver work force there are many drivers with blemishes such as these which may make them 

less than perfect, but not necessarily ineligible for hiring. How can it be that these drivers 

187
may appear entirely proper in any sort of Department of Transportation audit or safety review 

and yet become an abomination merely because they had the misfortune of being involved in 

a serious accident? The problem lies in the subjective nature of certain regulations. 

Proceedings of the first international driving symposium on human factors in driver assessment, 

training and vehicle design. (2001). In D.V. Mcgehee, J.D. Lee, M. Rizzo, K. Holeton, and T. 

Lopes (Eds.), International Driving Symposium on Human Factors in Driver Assessment, 

Training and Vehicle Design. University of Iowa, Iowa City. 

TRIS Abstract: Driving Assessment 2001 was originally conceived to fill a 

multidisciplinary gap in driver safety research. The symposium brought together experts in 

human factors, medicine, engineering design, operations and policy from all over the world. 

Participants from 16 countries contributed to the scientific program. The friendships and 

partnerships forged at this meeting have created new opportunities for collaboration. The 

papers contained in these proceedings represent a significant contribution to the human 

factors and driver safety research literature. The proceedings include 81 papers, a panel 

discussion, and an author index. The papers are organized into the following technical 

sessions: Attention and Distraction; Driver Training and Licensing Issues; Fatigue and 

Impairment; Driver Performance Assessment; Information Display Issues in Driver-Vehicle 

Interface Design; Medical Factors; Commercial Vehicle Operations; Infrastructure and inVehicle Systems. 

Roberts, S. & York, J. (2000). Design, Development, and Evaluation of Driver Wellness 

Programs, Final Report, FMCSA Report No. MC-00-193.

Introduction: The initial step in designing a successful wellness program for commercial 

vehicle drivers is to review the current literature and practice with regards to the health status 

of the population and wellness programs in operation.

As the literature and practice review are presented it must be noted, that even though there 

are almost three million commercial motor vehicle drivers in the United States, little research 

has been done specifically to examine the health status of these workers. Likewise they are 

not a population that has had frequent opportunity to participate in company sponsored 

wellness programs. This is quite ironic and of significant importance considering the results 

of this review. 

The following sections provide an overview of the driver health literature and a review of 

existing wellness programs and practices—both within and outside of the trucking industry. 

The results of the first two driver focus groups are also included in this document to provide 

a summary of research progress to date. A summary of this effort’s research implications and 

next steps are also provided. 

Schneider, N.R. & Cottrell, D.P. (2002). Using performance measures to effect safety 

improvements: A case study from the New York State comprehensive bus safety inspection 

program. In Z.G. Zacharia (Ed.), International Truck and Bus Safety Research and Policy 

Symposium. University of Tennessee Knoxville: National Safety Council. 

Author Abstract: This paper describes how the New York State Department of 

Transportation, through a cooperative relationship with the bus industry, undertook an action 

188
plan to clarify and strengthen its Bus and Passenger Vehicle Safety Regulations and to 

establish industry performance goals to reduce Bus Safety Out-of-Service (OOS) rates 

statewide. Over the course of 5 years, the State’s regulations were updated with extensive 

industry input and the average OOS rate for key operators has been reduced from 24.5% in 

1995 to 9.6% in 2002—a 60% reduction in vehicles being placed Out-of-Service and 

requiring a safety re-inspection before being operated on a public highway in the State. The 

paper is intended to assist others involved in performance based safety programs better 

understand how to build outcome driven performance programs that can achieve significant 

results. 

Stock, D. (2001). I-95 Corridor Coalition Field Operational Test 10: Coordinated Safety 

Management. Volume I: Best Practices in Motor Carrier Safety Management, Final Report. 

NTIS Abstract: Coordinated Safety Management is an I-95 Corridor Coalition-sponsored 

project which was designed to identify the factors that contribute to exemplary motor carrier 

safety performance and develop outreach materials and tools to help carriers operate more 

safely. One of the goals of the I-95 Corridor Coalition Field Operational Test No. 10 (FOT 

10)-Coordinated Safety Management-is to develop recommendations for educational and 

outreach programs and materials to improve motor carrier safety and compliance with 

regulations. Maximizing the value of these efforts requires an understanding of what the 

common safety deficiencies are and what safe carriers do to avoid these deficiencies. To this 

end, the study team analyzed the results of roadside safety inspections for motor carriers 

based in the I-95 Corridor Coalition states; performed an extensive review of motor carrier 

safety educational materials and programs; and, conducted a survey of nearly 600 

commercial motor carriers who are, arguably, among the safest operators. This report 

provides an overview of: Motor carrier safety/compliance deficiencies; The safety 

management practices of safer fleets; The topic and delivery media the safer carriers feel 

would be of most value to their safety programs; and, Motor carrier views on enforcement 

and regulations. 

Truck safety: Perceptions and reality. (1996). F. Saccomanno & J. Shortreed (Eds.) University of 

Waterloo: Institute for Risk Research. 

TRIS Abstract: This book is the result of a North American conference of industry 

stakeholders, government regulators, and highway safety researchers held to review factors 

affecting safety in the trucking industry and to develop a collective view of critical truck 

safety issues. Published with support from Transportation Development Centre and Ontario 

Ministry of Transportation, the book features current issues, trends, and future directions on 

the following topics: 

• Carrier management practices to improve safety and profitability 

• Driver fatigue and accident risk 

• Causes and consequences of truck accidents 

• New technologies in vehicle and roadway design 

• Regulation and policy in Canada, U.S. and Mexico 

• Load security issues 

• Industry stakeholder consensus on critical truck safety issues and proposed initiatives 

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Tse, J.L.M., Flin, R., & Mearns, K. (2006). Bus driver well-being review: 50 years of research. 

Transportation Research Part F: Traffic Psychology and Behaviour, 9, 89-114. 

Author Abstract: This review paper consolidates the key research on the occupational 

health of urban bus drivers since the 1950s. Several electronic databases were searched and 

27 key studies were identified, which form the basis of this paper. Early findings that bus 

drivers are liable to suffer ill health as a result of the job remain true today. The research has, 

however, demonstrated a greater understanding that specific stressors result in certain 

physical (cardiovascular disease, gastrointestinal disorders, musculoskeletal problems, 

fatigue), psychological (depression, anxiety, post-traumatic stress disorder) and behavioural 

outcomes (substance abuse). Bus driver ill health will have consequences for organisational 

performance in terms of employee absence, labour turnover and accidents. Stressors for bus 

drivers include poor cabin ergonomics, rotating shift patterns and inflexible running times. 

Over the last few decades, the heightening of other work stressors such as traffic, and 

violence from passengers have compounded the situation for bus drivers. Greater attention to 

salient moderating and mediating variables in the stressor-strain relationship is featuring in 

more recent research. Despite such theoretical advances, the research needs to also 

concentrate on practical interventions that are systematically implemented and evaluated, to 

improve the well-being of bus drivers. By improving this ‘human side’ of the role, it is 

expected that the efficiency of this transport will be enhanced for bus drivers, operators and 

passengers alike. 

Wachtel, J., Sizov, K., Fisher, D.L., Mourant, R., & Crean, C.M. (2006). Safety challenges 

facing tomorrow’s commercial drivers and the role of new simulation technology to meet 

them. In N. Kassabian (Ed.), Future Truck and Bus Safety Research Opportunities 

Washington, D.C.: Transportation Research Board. 

Preface: On March 23 and 24, 2005, a group of industry, government, university, and 

consultant experts gathered in Arlington, Virginia, to participate in a conference on future 

truck and bus research opportunities. The purpose was to ponder the future of the commercial 

vehicle industry and to identify research requirements in preparation for the proposed future. 

The conference was jointly sponsored by the Transportation Research Board and the Federal 

Motor Carrier Safety Administration. 

The conference was planned and conducted under the auspices of a specially appointed 

committee convened by the National Research Council. The purpose of the project was to 

examine future scenarios and consider the following questions: What will the future be like 

in terms of truck and bus travel? What will be the impact of the anticipated conditions on 

safety? What research should be accomplished to prepare for the future? Some related issues, 

such as potential barriers to implementation of research findings, were briefly raised during 

the conference and their importance noted. Because such issues go beyond the scope of this 

project, however, they were not a focus of conference or committee discussions, and they are 

not addressed in this report. 

Wilde, G. (1996). Improving trucking safety and profitability through safety incentive schemes.

F. Saccomano & J. Shortreed (Eds.), Truck safety: Perceptions and reality (pp. 21-252). 

University of Waterloo: Institute for Risk Research. 

Author Abstract: The current state of knowledge concerning the effects of incentives for 

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safety in industrial settings and in road traffic is applied to the specific purpose of enhancing 

the safety of long-haul trucking in Canada. Mobility and accident statistics pertaining to 

recent years in the U.S. and Canada are reviewed. Attention is drawn to the important 

distinction between incentives for specific behaviors (such as using safety equipment, 

sobriety, or obeying the speed limit) and incentives for successful avoidance of accidents of 

their own fault. The disadvantages of the use of disincentives (punishments) as compared to 

positive incentives (rewards) are also pointed out. The report includes a checklist of the 

requirements for maximally effective incentive programs for accident-free operation 

according to the present state-of-the-art. The issues of benefit-cost ratios of incentive 

programs and of the possible desirable and undesirable side-effects of their implementation 

are also discussed. 

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CONCLUSIONS 

This review demonstrates the utility of using tailored versions of Haddon’s matrix as a 

framework for addressing some of the prime safety concerns in the trucking industry and 

FMCSA alike. These include the recruitment, selection and retention of a safe workforce in 

Review #1, and the factors related to improving safety as associated with existing drivers and 

motor carrier operations in Review #2. As a caveat that should be noted regarding the current 

effort, this document is not intended as a comprehensive review of the many antecedents of 

safety outcomes, and it intentionally did not duplicate the focus or content of any recent 

FMCSA-sponsored work. 

With regard to the findings presented in this document, although it was not possible to annotate 

the hundreds of trade sources that were amassed in the same way as was done for the resultant 

scientific literature, exploring both academic and industry viewpoints was beneficial and allowed 

for a more complete understanding of the complex nature of the trucking industry. Precisely 

because new and updated industry information is constantly being generated, in particular online, 

only the most recent published trade material was relied upon when citing sources. 

Also, as previously mentioned, the scientific literature pertaining to the two Haddon matrices 

used to structure the reviews did not produce a uniform distribution of studies across pre-event, 

event, and post-event stages. There are a number of plausible explanations for this outcome. For 

example, it may be the case that trends in research areas (i.e., current, popular topics) drive 

individual academic pursuits more so than do industry needs; or alternately, that studies indeed 

exist, but have not been published in the open literature for reasons of perceived competitive 

advantage or even potential liability. Further, although research often could have been framed by 

reviewers to fit within more than one area of the matrix, the literature was categorized with the 

perceived purpose of the author(s) in mind regarding whether results were geared towards the 

individual (driver) or organizational (motor carrier) level, and additionally by which focus 

question and stage of the event cycle was best addressed. 

This process resulted in 80% of studies falling within the post-event stage for Review #1, where 

the bulk of the research concentrated on issues related to voluntary and involuntary driver 

turnover. It bears restating here that a company’s singular focus on minimizing turnover, while 

indeed a means of stabilizing workforce size, may have the unintended consequence of retaining 

unsuited or undesirable drivers. If not carefully considered and implemented, such practices have 

the potential to negatively impact both safety and motor carrier performance. For this reason, a 

more complete consideration of the pre-event and event stages as pertaining to selecting safe 

drivers is recommended. This implies the need for additional, systematic investigation of 

methods for improving motor carrier strategies and procedures for recruitment and selection, so 

that larger pools of qualified applicants may be hired, and ultimately retained as CMV drivers. In 

contrast to Review #1, the second review of literature, which explored improving driver safety, 

resulted in over twice as many annotations, with 50% of the studies falling within the pre-event 

stage of the Haddon matrix. This focus on the driver factors and existing motor carrier practices 

that impact various safety outcomes is logical in the sense that it concentrates on issues that may 

be preemptively used to help ensure safe driving, including attending to individual driver 

differences pertaining to age and abilities, considering past behavior as a predictor of future 

behavior, and organizational factors, such as safety climate and incentives. However, in an effort 

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to more fully consider the entire event-stage continuum, additional research in the areas of 

improving safety outcomes through real-time monitoring of driver-generated data and including 

successful strategies for providing feedback to drivers and motor carriers is recommended. 

Research gaps in the annotated literature aside, certain related themes span the two reviews or 

are common across the scientific and trade publications. As stated within the goal of this effort, 

study outcomes that focused on safety were of primary importance to the project. Objective 

measures of safety, including crash rates, driving performance, and motor carrier safety records, 

were directly assessed within the second review; whereas indirect impacts to safety, such as the 

organizational effects of and individual reasons for driver turnover, as well as costs associated 

with company efforts to recruit, select, train, and retain the best/safest drivers, were more 

common within the first review. As an example, findings in Review #2 referenced a favorable 

performance record for passenger over commodities carriers, and that private carriers tended to 

be statistically safer than for-hire carriers. This is noteworthy in conjunction with results from 

the first review indicating that quit rates are lower for drivers who are home more times per 

month, as is the case with passenger over commodities carriers and is also true for smaller, 

private firms. Additionally, information provided in trade publications suggests that insurance 

policies are less expensive for private carriers due to generally superior safety records and a 

more stable workforce than their for-hire counterparts. Indeed, drivers with longer job tenure, as 

often found in private fleets, are likely to be a reflection of a successful organizational model that 

serves to promote a culture of longevity and should be considered across trucking sectors. This 

model encompasses direct communication with drivers and maintaining one-on-one contact to 

the extent possible, so that dispatchers are not perceived as the sole “face” of the company. 

Moreover, offering competitive wages, fair treatment of employees, appreciation of effort, and 

favorable and safe working conditions is prescribed in the first review as a means of bolstering 

job satisfaction. The organizational benefit to satisfied drivers is a workforce that is less likely to 

turnover, or “churn,” thus reducing the need for and cost of additional recruitment, selection, 

hiring, and training. 

Overall, outcomes from the two reviews suggest that the safety of CMV drivers may be 

improved through a multifaceted approach that strives to consider all stages of the Haddon 

matrix event-cycle as tailored for this project. To start, the systematic and selective use of 

inexpensive technology (e.g., the internet and available methods for obtaining current driver 

history data) in the applicant recruitment and selection process will both reach the greatest 

number of potential employees and most effectively eliminate those who are not well-suited for 

the job. Given the projected, continued growth of the trucking industry, this demand for drivers 

will remain unmet to the extent that non-traditional applicant source pools are left untapped. 

These include younger people, who may not have otherwise considered truck driving as a job 

and can be initially trained in apprentice programs; the older generation now looking for a career 

change; women, who have not, historically, been a focus of recruiting; and minorities, who may 

require additional training to help develop necessary English-language skills, but are otherwise 

well-equipped for such a career. 

Once a company has successfully hired the most qualified and motivated workers, it is 

imperative that compensation is adequate, and also essential that employees are satisfied with 

their jobs and quality of life outside of work. This is especially important for truck driving, as it 

does not typically provide the same type of career path as other occupations (beyond the benefits 

193
associated with seniority). In this manner, over time and in conjunction with continued 

organizational investment, it should be possible to build a workforce that is stable and welltrained. Ultimately, these conditions are optimal for engendering employee trust, commitment, 

and buy-in. With employee trust, effective communication, and a positive safety climate, 

promising technologies such as on-board monitoring and programs utilizing behavior-based 

safety are likely to be more favorably received and more effective due to a universal 

understanding of organizational goals pertaining to safety. All things considered, the outcome for 

trucking organizations that commit more time and additional resources up-front should include a 

larger, more qualified workforce, improved job satisfaction, increased safety performance, and 

ultimately, a significant cost savings. 

194
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