DOT/FAA/AM-02/9

Dana M. Broach

Carolyn S. Dollar

Civil Aerospace Medical Institute

Federal Aviation Administration

Oklahoma City, OK 73125

May 2002

Final Report

This document is available to the public

through the National Technical Information

Service, Springfield, VA 22161.

Relationship of Employee

Attitudes and SupervisorController Ratio to En Route

Operational Error Rates Office of Aerospace Medicine

Washington, DC 20591
NOTICE

This document is disseminated under the sponsorship of

the U.S. Department of Transportation in the interest of

information exchange. The United States Government

assumes no liability for the contents thereof.
i

Technical Report Documentation Page

1. Report No. 2. Government Accession No. 3. Recipient's Catalog No.

DOT/FAA/AM-02/9

4. Title and Subtitle 5. Report Date

Relationship of Employee Attitudes and Supervisor–Controller Ratio May 2002

to En Route Operational Error Rates 6. Performing Organization Code

7. Author(s) 8. Performing Organization Report No.

Broach, D., & Dollar, C.S.

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

Training & Organizational Research Laboratory

FAA Civil Aerospace Medical Institute

P.O. Box 25082 11. Contract or Grant No.

Oklahoma City, OK 73125

12. Sponsoring Agency name and Address 13. Type of Report and Period Covered

Office of Aerospace Medicine

Federal Aviation Administration

800 Independence Ave., S.W.

Washington, DC 20591 14. Sponsoring Agency Code

15. Supplemental Notes

Work was accomplished under approved subtask AM-B-01-HRR516.

16. Abstract

An operational error (OE) results when an air traffic control specialist (ATCS) fails to maintain appropriate

separation between aircraft, obstacles, etc. Recent research on OEs has focused on situational and individual

characteristics (Center for Naval Analyses Corporation, 1995; Della Rocco, 1999; Rodgers, Mogford, Mogford,

1998). In this study, the relationship of organizational factors to en route OE rates was investigated, based on

an adaptation of the Human Factors Analysis and Classification System (HFACS; Shappell & Wiegmann,

2000) to air traffic control as HFACS-ATC (Scarborough & Pounds, 2001). OE rates (errors per 100,000

operations) for 1997 and 2000 were obtained from the National Airspace Incident Monitoring System

(NAIMS) for 21 air route traffic control centers (ARTCC). Organizational factors were represented by facility

mean scores on scales constructed from 1997 and 2000 FAA Employee Attitude Survey (EAS) data. Factors

included employee perceptions of equipment/facilities, performance management, overall job satisfaction, and

perceptions of other human resources management practices. The supervisor-controller ratio (SCR) was

calculated for each ARTCC by year from agency personnel data. SCR and organizational factors facility mean

scores were regressed on OE rate (N=42). Two organizational factors and SCR accounted for 50% (adjusted R2

= .505, p < .001) of the variance in OE rates across ARTCCs for the two years. The standardized regression

coefficients were -.290 for perceptions of equipment/facilities (t=-2.07, p < .05), -.302 for perceptions of

performance management (t=-2.28, p < .05), and -.395 for SCR (t=-3.360, p < .01). As expected from prior

research, SCR was a significant predictor of en route OE rates. In addition, the results indicated that

perceptions of how performance was managed and of facilities and equipment were also predictors of OE rates.

Overall, the results support the inclusion of organizational factors as well as individual and situational

characteristics in the investigation of ATCS operational errors.

17. Key Words 18. Distribution Statement

Air Traffic Controllers, Job Attitudes, Operational Errors,

Human Factors, Performance, Psychology, Organizational

Characteristics

Document is available to the public through the

National Technical Information Service,

Springfield, VA 22161.

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price

Unclassified Unclassified 13

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
1

RELATIONSHIP OF EMPLOYEE ATTITUDES AND SUPERVISOR-CONTROLLER

RATIO TO EN ROUTE OPERATIONAL ERROR RATES

Air traffic controllers ensure the safe, orderly, and

expeditious flow of air traffic through the National

Airspace System (NAS). To ensure the safety of flight,

controllers maintain adequate separation between aircraft and obstacles to flight. They issue speed, altitude, and heading commands to pilots to provide and

maintain required separation. An operational error

(OE) results when an Air Traffic Control Specialist

(ATCS, “air traffic controller,” or “controller”) fails

to maintain appropriate separation between aircraft,

terrain, and other obstacles to safe flight. The number

of OEs per 100,000 facility activities (“OE rate”) has

long been an index of NAS safety. Reduction in the

OE rate is a safety goal for the FAA “line-of-business”

responsible for the delivery and management of air

traffic services. For example, the Air Traffic Services

Performance Plan FY2001-2003 (Air Traffic Services,

2000) calls for the reduction of OEs by 2.5% per year

in FY2002 and FY2003.

However, the OE rate has increased in recent years.

For example, the number of OEs increased from 754

in fiscal year (FY) 1997 to 1,194 in FY2001.The goal

for FY2001 was 812 errors (Figure 1). The rate also

increased, from .51 to .68 per 100,000 facility operations (Department of Transportation Office of the

Inspector General, 2000, 2002). Explanations for the

increase include better reporting and increased traffic.

Possible situational and individual causal factors have

been investigated in several studies (see, for examples,

Broach, 1999; Della Rocco, Cruz, & Clemens, 1999;

Endlsey & Rodgers, 1997; Rodgers & Nye, 1993;

Rodgers, Mogford, & Mogford, 1998; Schroeder &

Nye, 1993). The Center for Naval Analyses Corporation (CNAC, 1995) examined the relationship of

individual characteristics, staffing ratios, and facility

characteristics to en route OEs for the period 1990

through 1995. There appeared to be little correlation

between the supervisor-controller staffing ratio and

0

250

500

750

1000

1250

OE 754 885 941 1145 1194

Goal 816 829 812

1997 1998 1999 2000 2001

Figure 1: Actual operational errors (OE) and goal by fiscal year (Adapted

From Department of Transportation Office of the Inspector General, 2002)
2

the OE rate (p. 94). CNAC concluded that the number of OEs were primarily a function of the complexity of the sectors being supervised rather than individual

characteristics of the supervisor (p. 97).

This study replicated and extended the CNAC

study by focusing on the influence of organizational

characteristics on OE rate at the 21 continental air

route traffic control centers (ARTCCs, or centers).

Organizational characteristics have been hypothesized

to influence the occurrence of human errors (Reason,

1990; Shappell & Wiegmann, 2000). Organizational

characteristics in the Human Factors Classification

and Analysis System–Air Traffic Control (HFACSATC; Scarborough & Pounds, 2001) include (a)

organizational climate, (b) organizational structure, (c)

policies and procedures, and (c) resource management.

Organizational climate in HFACS-ATC refers to

the working atmosphere within the organization. An

organizational climate characterized by confusion and

conflict may have a detrimental effect on safety

(Shappell & Wiegmann, p. 13). Job satisfaction, for

example, might serve as an overall indicator of the

organizational climate. Schneider (2001) investigated

the relationship of job satisfaction to operational

errors in the en route environment. Facility mean

scores were computed for selected items from the

FAA’s 1997 Employee Attitude Survey (EAS).

Schneider then correlated those scores with the number of OEs for each en route facility (N = 21). No

significant correlations between operational errors

and various measures of job satisfaction were found.

Organizational structure refers to attributes such as the

ratio of supervisors to controllers and the hierarchical

organization of the facility. The 1995 CNAC study

reported no significant correlation between OE rates

and the ratio of supervisors to controllers. However,

Fisher (2001) qualitatively linked reductions in the

number of operational supervisors, an organizational

structure characteristic, to increases in operational

errors. Other facets of organizational structure might

include the degree of oversight exercised over employees, and the accountability of management employees

for performance. Policies and procedures in the HFACSATC refer to the broad class of corporate decisions

and rules that structure everyday working life. Kinney

(1977) qualitatively described how organizational

policies influenced the occurrence of operational errors. However, no recent research has investigated the

influence of organizational policies and procedures.

Finally, resource management in HFACS-ATC encompasses the allocation of organizational assets such

as personnel, money, and facilities or equipment. One

aspect of resource management might be employee

perceptions of the quality of equipment, the facility

overall, and maintenance services. The purpose of the

present study was to explore possible relationships

between several of the organizational facets proposed

by HFACS-ATC to OE rates in today’s air traffic

control system.

METHOD

Data sources

OE rates (errors per 100,000 operations) were

obtained from the National Airspace Incident Monitoring System (NAIMS) for calendar years 1997 and

2000 for 21 U.S. ARTCCs. The combined en route/

approach control facilities in Guam, Hawaii, and

Puerto Rico were excluded from the analysis as they

are operationally different from the 21 continental air

route traffic control centers. Response data for selected items from the EAS for the years 1997 and 2000

were used to construct the organizational factors used

in this study. Staffing data for 1997 and 2000 were

extracted from the FAA’s Consolidated Personnel

Management Information System (CPMIS), the

agency’s official system of personnel records.

Organizational factors

Items from the EAS for 1997 and 2000 were

selected to represent the organizational factors hypothesized to influence operational errors in the

HFACS-ATC model. The EAS is a broad instrument

used to assess FAA employee perceptions of the workplace (Thompson, et al., 2000). Sufficient organizational demographic data were collected from each

respondent to allow segmentation of the data by

workforce and facility. The overall response rate from

the 21 centers were 41% in 1997 and 33% in 2000.

Centers have, on average, about 300 controllers, with

the exception of Anchorage which has just over 200

controllers.

The mapping of 1997 and 2000 EAS items and

scales to the HFACS-ATC organizational factors is

shown in Table 1. Only items that had remained

unchanged between the two EAS administrations

were considered to ensure comparability across years.

A measure of the internal consistency, known generally as Cronbach’s alpha (α; Cronbach, 1951), or the

degree to which the items were related to one another,

was calculated for each set of items selected to represent a HFACS-ATC factor. Cronbach’s α can be

computed if there are at least two items in the scale.

Higher values for Cronbach’s α for a HFACS-ATC

factor indicated greater consistency in responses to

the items, while lower values indicated less consistency.
3

Table 1:Mapping of EAS items to HFACS-ATC organizational factors

HFACS-ATC DOMAIN NAME

Definition

HFACS-ATC FactorDefinition

EAS (Year)

1997 Items 2000 Items

ORGANIZATIONAL CLIMATE

Prevailing atmosphere within the organization. Morale/job satisfaction

Workforce Attitudes (HFACSAT1)Prevailing attitudes of the workforce, e.g., Job satisfaction, trust, contextual performance.Q5 Q5 Overall, how satisfied are you with: your job – the kind of work you do?Q9 Q8 Overall, how satisfied are you with: your job overall?Q97 Q23 (R) Some employees may be hesitant to speak up for fear of retaliation.Q98 Q24 (R) It is generally safer to say that you agree with management even when you don’t really agree.Q99 Q25 We are encouraged to express our concerns openly.Workforce Behavioral Factors (HFACSAT2): Prevailing behavioral sets of the workforce, e.g., following the rules.Q75 Q96 To what extent are there things about working in the organization (such as policies, practices, or conditions) that

encourage you to work hard?

Q78 Q107 To what extent does the FAA inspire the very best in you?Informal Socialization Processes (HFACSAT3): The process used to teach new members of the organization the Attitudinal and BehavioralWorkforce Factors, e.g., Communicating the rules of the organization. Includes such things as describing how to interact with managers and

supervisors, the organization’s “real” values and priorities.Q29 Q34 To what extent has the FAA done a good job creating an environment where all employees have the opportunity

to broaden their knowledge of the FAA (e.g., town hall meetings, attending briefings)?

Q47 Q57 My immediate supervisor is fair with subordinates.Q48 Q58 My immediate supervisor keeps informed about the way subordinates think and feel about things.

(Table 1 continues)
4

(Table 1 continued)Q51 Q61 (R) My immediate supervisor tends to play favorites.Q96 Q84 I feel free to discuss with my immediate supervisor the problems and difficulties I have in my job without

jeopardizing my position or having it “held against” me later.

Q69 Q100 To what extent do you receive sufficient information from the FAA to understand how major innovations and

changes might affect you?

ORGANIZATIONAL STRUCTURE

e.g., Chain-of-command, delegation of authority and responsibility, communication channels, and

accountability for actions. Organizations with maladaptive structures will be more prone to accidents and

incidents.

Structural Oversight (HFACSAT4): Control vs. commitment, number of levels from top to bottom; span of control, e.g., number of peoplesupervised, availability of communication channels, support for programs which are initiated.Q25 Q22 In my organization, managers show commitment to customer support through their actions.Q87 Q85 Managers and supervisors in my organization are held accountable for achieving important agency goals.Q88 Q86 Nonsupervisory employees in my organization are held accountable for achieving important agency goals.Decision Making Structure (HFACSAT5): The hierarchical and decision flow process of information during a decision making episode. Levelof accountability; Level of responsibility; Level of empowerment, e.g., level of ATC responsibility for incidents.Q17 (R) Q17 (R) I am required to get approval for decisions that I think I should be able to make myself.Q18 Q18 Decisions in my organization are made at those levels where the most adequate and accurate information is

available.

Q19 Q19 I am able to contribute to decision-making that affects my job.Q20 Q20 I have the authority to make decisions required by my day-to-day work problems.

(Table 1 continues)
5

(Table 1 continued)

RESOURCE MANAGEMENT

Management, allocation, and maintenance of organizational resources.

Equipment & Facilities (HFACSAT8): Refers to issues related to facility and equipment design, including the inadequate design of equipmentand work spaces, and failures to correct known design flaws. Also failures to correct known facility shortcomings.Q4 Q4 Overall, how satisfied are you with your physical working conditions?Notes: (R) indicates item that is reversed for scoring purposes.

Table 2Descriptive statistics and correlation matrix for operational error rate, supervisor-controller ratio, and HFACS-ATC organizationalfactors (N=42)a

Descriptive Statistics Correlations

Mean SD Min Max OE_RATE SCR HFACSAT 1 HFACSAT 2 HFACSAT 3 HFACSAT 4 HFACSAT 6 HFACSAT 7

OE_RATE OEs per 100,000 Ops 1.21 0.65 0.07 3.46SCR Supervisor-Controller Ratio 0.14 0.02 0.11 0.22 -0.54**HFACSAT1 Attitudinal Factors 3.15 0.12 2.89 3.41 -0.22 0.01HFACSAT2 Behavioral Factors 2.04 0.19 1.64 2.42 -0.43** 0.04 0.60**HFACSAT3 Informal Socialization 2.95 0.14 2.56 3.22 -0.48** 0.17 0.68** 0.70**HFACSAT4 Structural Oversight 2.56 0.17 2.23 2.95 -0.40** 0.15 0.45** 0.71** 0.72**HFACSAT6 Human Resources 2.64 0.14 2.32 2.94 -0.45** 0.23 0.62** 0.50** 0.79** 0.59**HFACSAT7 PerformanceManagement

2.35 0.16 1.94 2.66 -0.52** 0.14 0.70** 0.74** 0.85** 0.81** 0.75*

HFACSAT8 Equipment & Facilities 2.70 0.55 1.28 3.78 -0.59** 0.35* 0.34* 0.68** 0.53** 0.57** 0.33* 0.56*Notes: aDescriptive statistics are aggregated facility mean scores * p < .05, **p < .01
6

Although there is no absolute cut-off, scales with

alphas of less than about .5 to .6 are not commonly

used in research, as the scores on such scales are viewed

as unreliable.

There were multiple items from both iterations of

the EAS related to the HFACS-ATC organizational

climate factor. Two EAS items specifically assessed

job satisfaction, and three directly assessed employee

trust. A scale to represent the workforce attitudes

(HFACSAT1; Cronbach’s α = .73) was constructed

from these five items. The underlying hypothesis was

that facilities with higher satisfaction and trust were

more likely to have lower error rates. Another aspect

of organizational climate is the extent to which employees were willing to work hard. Two items from

the EAS addressed this facet of the facility organizational climate (HFACSAT2; Cronbach’s α = .67),

with the underlying hypothesis that facilities with

higher levels of willingness to work hard would have

lower OE rates. How employees are socialized into the

organization plays a role in determining the organizational climate. Six items were identified from the EAS

related to the informal socialization process

(HFACSAT3; Cronbach’s α = .81). The underlying

hypothesis for these items was that facilities with more

positive perceptions of informal socialization processes would have lower error rates.

The organizational structure factor of the HFACSATC model was represented by two scales derived by

combining EAS items. First, three EAS items referring to managerial accountability and commitment to

customer support were combined to represent general

supervision (HFACSAT4; Cronbach’s α = .58). We

expected that facilities with more positive perceptions

of general supervision would have lower OE rates.

Second, four EAS items specifically focused on empowerment were used to represent decision-making

structure (HFACSAT5), with the expectation that

facilities with higher levels of perceived empowerment would have lower error rates. However, this

“decision-making structure” scale was dropped from the

analysis due to poor reliability (Cronbach’s α = .25).

The policies and procedures facet of the organization

was reflected in two scales constructed from the EAS.

Six EAS items addressed human resources management policies such as training and promotion opportunity (HFACSAT6; Cronbach’s α = .68). As with the

other HFACS-ATC scales, we hypothesized that facilities with more positive perceptions of human resources management policies would have lower error

rates. Five EAS items focused on performance management (HFACSAT7; Cronbach’s α = .67). We hypothesized that facilities with more positive perceptions of

performance management would also likely experience lower error rates. Finally, resource management

was reflected by a single scale addressing the quality of

equipment and facilities. A single EAS item was used

to represent employee perceptions of the quality of

equipment and facilities (HFACSAT8), with the expectation that more positive perceptions would be

reflected in lower facility error rates. Scale scores were

calculated for each respondent. The six reliable, multiitem scales and HFACSAT7 (a single item scale) were

then aggregated by year and facility. The resulting

data file included facility identifier, number of respondents, and the facility mean scores on the seven

HFACS-ATC scales (HFACSAT1 to HFACSAT4,

HFACSAT6 to HFACSAT8) by year and facility.

Employment data extracted from the FAA’s CPMIS

were used to estimate the supervisor-to-controller

ratio (SCR) in 1997 and 2000 for each center. The

SCR was computed as the ratio of the number of

Operations Supervisors to the total number of Certified Professional Controllers and controllers in training at each center at the end of calendar years 1997

and 2000. The SCR represented an objective measure

of an aspect of the organizational structure.

Error data and analyses

Operational error data were extracted from the

National Airspace Incident Monitoring System

(NAIMS). SCR and OE (errors per 100,000 operations) were matched by year and center with the

aggregated HFACS-ATC scale data file created for

this analysis. The OE rate was regressed on the seven

mean HFACS-ATC scale scores and the SCR. SPSS®

for Windows (Version 10.0.7; SPSS, Inc., 1999) was

used for all file manipulations and statistical analyses.

RESULTS

Descriptive statistics across centers and the correlation matrix are displayed in Table 2. The correlations

between operational error rate (OE_RATE) and the

hypothesized predictors were all negative and significant. The correlation between SCR and OE_RATE

was -.54 (p < .001; Figure 2). In other words, facilities

with about 1 supervisor for every 6-7 controllers (SCR

= .14 to .17) had lower error rates than facilities with

1 supervisor for every 8-10 controllers (SCR = .10 to

.12).The moderate to moderately large correlations

between the HFACS-ATC factors suggested that collinearity might be problem for the analysis. Collinearity refers to the degree to which the predictors are

related to one another. When the predictors are highly

related to one another, the information each provides
7

Supervisor-Controller Ratio (SCR)

OE Rate (OE_RATE: Errors per 100,000 Activities)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0.08 0.10 0.12 0.14 0.16 0.18 0.20 0.22 0.24

Figure 2: Correlation (r = -.54, p < .001) between Supervisor-Controller Ration (SCR) &

Operational Error Rate (OE_RATE)

may be duplicated by the other predictors. As a result,

a regression analysis based on highly correlated predictors will be unstable, as one predictor could easily

be substituted for another. Therefore, in view of the

apparent collinearity among the predictors, regression

diagnostics were examined during the course of the

analysis.

The results of the stepwise regression of the seven

HFACS-ATC scale scores and SCR on the operational error rate are shown in Table 3. Stepwise

regression is a technique for identifying the optimally

weighted variables from a given set that best predict

the criterion (OE_RATE in this instance). Regression

diagnostics provided little evidence of problematic

collinearity. Variance inflation factor (VIF) scores, a

commonly used regression diagnostic, ranged from

1.143 to 1.622 for the three predictor scales that

comprised the final model. VIF is equal to 1.0 when

the predictors are independent and have no correlation with one another; a value of 10 or greater is often

used as a benchmark indicating problematic collinearity among the predictors. VIF scores near 1 indicated

that the optimally weighted set of variables that best

predicted OE_RATE was stable and interpretable.

Overall, the supervisor-controller ratio (SCR),

employee perceptions of how performance was managed in the facility (HFACSAT7), and employee

perceptions of the quality of equipment and facilities

(HFACSAT8) accounted for 51% (Adjusted R2

 =

.505, F(3,38) = 14.925, p < .001) of the variance in

1997 and 2000 operational error rates across the 21

centers. The other factors did not meet the statistical

criteria for inclusion in the final model.

The adjusted R2

 is a conservative estimate of the

relationship between the predictors (SCR,

HFACSAT7, HFACSAT8) and OE_RATE. The adjusted R2

 indicates how well OE_RATE can be predicted from the combination of weighted variables.

An R2

 of 1.00 indicates that the criterion (OE_RATE)

is perfectly predicted from SCR, HFACSAT7, and

HFACSAT8. Conversely, an R2

 = 0 indicates that

OE_RATE could not be predicted at all from SCR,

HFACSAT7, and HFACSAT8. An R2

 of about .3 is

very common in the social sciences, particularly in

attitude-related research. An R2

 of .5 is much less

common, and indicates that supervisor-controller ratio, employee perceptions of how performance is
8

Table 3Results of stepwise regression of ARTCC operational error rate on supervisor-controller ratio and HFACS-ATC organizational factors

Regression

Coefficients

B SEB β t R ∆R2 R2 Adj-R2 F

Model 1

Intercept 3.129 .417 7.495***HFACSAT8 -.709 .151 -.595 -4.681*** .595 .354 .354 .338 21.912***

Model 2

Intercept 4.479 .584 7.674***HFACSAT8 -.553 .147 -.464 -3.765**SCR -12.782 4.190 -.376 -3.048** .692 .124** .478 .451 17.870***

Model 3

Intercept 6.880 1.191 5.780***HFACSAT8 -.345 .167 -.290 -2.071*SCR -13.425 3.995 -.395 -3.360**HFACSAT7 -1.225 .538 -.302 -2.279* .735 .063* .541 .505 14.925***

*p < .05, **p < .001, ***p < .001
9

managed and the facilities and equipment have some

relationship to the operational error rate at each en

route center.

DISCUSSION

The results of this descriptive study suggest that

organizational factors might influence the operational

error rate in en route air traffic control at the facility

level. This conclusion provides support for including

organizational factors in the analysis of operational

errors as suggested by HFACS-ATC. The regression

analysis also suggests that span-of-control, as represented by the supervisor-to-controller ratio, may be

related to en route facility operational error rates.

On the one hand, the analysis indicated that both

subjective and objective measures might be useful in

explaining differences in error rates between centers.

Similar results have been found in examining organizational and work unit attitudes towards safety and

accidents in other settings. For example, Zohar (2000)

demonstrated an empirical link between perceptions

of organizational safety climate and objective injury

data. Similarly, Thompson, Hilton, and Witt (1997)

demonstrated how perceptions of organizational climate and management roles might affect safety-related outcomes. The measures drawn from the EAS

reflect subjective perceptions of equipment and performance management. In contrast, the SCR represents an objective, structural characteristic of each

center. Overall, the present analysis suggests that it would

be fruitful for human factors investigations of operational errors in air traffic control to take into account

subjective perceptions of the organizational climate,

including perceptions of safety, as well as objective

characteristics of the organizational structure.

On the other hand, the study is descriptive, and it

is unlikely that future operational error rates at a

particular facility can be predicted from past measures

of employee attitudes or supervisor-controller ratios.

Moreover, the results of this analysis are not consistent with those reported by CNAC (1995) with respect to supervisor-controller ratio. In that study,

staffing ratio, based on mid-year figures, was regressed

on the yearly average error rate (CNAC, 1995, p. 94).

It is not clear from the description whether the averages were computed across facilities, across years, or

both. Consequently, it is unclear as to how to interpret the results of the present study with respect to the

CNAC study. Further research is clearly needed to

explore and explain any differences as well as to

replicate the findings of the present study.

Finally, it must be noted that this study did not

examine relationships between attitudes and errors at

the level of the individual controller. The unit of

analysis for this study was the facility. The attitudinal

predictors were composite, aggregated average scores

at the facility level created from anonymous survey

data. EAS data cannot be matched with OE data, as

the EAS is anonymous, and the final OE reports do

not identify the involved controller(s). The results of

this study cannot be used in any way to predict the

likelihood of an individual controller being involved

in an operational error. However, they do underscore

the need to collect data at multiple levels of analysis,

including organizational characteristics as well as information on the individual controllers involved in

errors. While the organizational data might or might

not be relevant to any single OE, patterns across errors

and over time might be found. Identification of such

patterns, in turn, might guide interventions and risk

mitigation strategies as the FAA actively seeks to

reduce the incidence of en route operational errors.

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