ENRI International Workshop on ATM/CNS (EIWAC2009)

Applying Cognitive Work Analysis to Study Airport
Collaborative Decision Making Design
Matthias Groppe

Romano Pagliari

Donald Harris

School of Engineering
Cranfield University
Cranfield, Bedfordshire, UK
m.groppe@cranfield.ac.uk

Air Transport Department
Cranfield University
Cranfield, Bedfordshire, UK
r.pagliari@cranfield.ac.uk

Human Factors Group
Cranfield University
Cranfield, Bedfordshire, UK
d.harris@cranfield.ac.uk

Abstract— This paper outlines the usage of a Work Domain
Analysis (WDA) for the assessment of operational information
requirements for pilots during Airport Collaborative Decision
Making (A-CDM). A-CDM presents unique challenges for
decision support during dispatch of aircraft and passengers.
Decisions by participating airport partners require anunderstanding of own capabilities as well as the capabilities ofparticipating actors like pilots, air traffic controllers, or otheractors involved. While some situations can be pre-planned,
decision makers during turn-round operation will always be
faced with unanticipated situations resulting from unknown
variables in the environment or technological capabilities.

I.

Airport Collaborative Decision Making (A-CDM) has been
introduced in Europe during field trials at selected airports as aconcept which aims at improving air traffic flow and capacity
management at airports by improving the communication andinformation sharing between the various actors at an airport.
An airport is considered as CDM airport when A-CDM
Information Sharing (ACIS), Turn-Round Process (CTRP), andVariable Taxi Time Calculation (VTTC) concept elements areapplied at the airport [1].
CTRP describes the flight progress from initial planning
until take-off by defined ‘milestones’ to allow close monitoringof significant events. Flight Update Messages (FUMs) and
Departure Planning Information (DPI) are in place to inform allparticipating CDM partners about the flight progress.
Monitoring the flight between the period of milestone 6(aircraft landed) and milestone 15 (aircraft off-blocks) is acomplex task, because situational awareness has to beestablished across various subsystems of different
organizational and operational structures having their own
causal and intentional domain constraints. ‘Subsystems’ here
refer to actors who include airport operator, airline company,
air traffic control, ground handler, and Central Flow
Management Unit (CFMU). Additionally, all terminal andramp processes have operational interdependencies, e.g.
processes can normally not be parallelized, as well as legal
requirements, e.g. one side of the aircraft has to be clear of
obstructions to ensure that fire fighting access is always
possible [2]. In order to increase situational awareness, anumber of agreed and trigger events are defined by the A-CDM
concept to inform about updates to estimates and/or aircraft
turn-round status. A CDM compliance alert will emerge within
the Airport CDM Information Sharing Platform (ACISP) incase of disruptions. Any internal or external disruption at thesemilestones generates an alarm and has to be communicated to
all partners in order to maintain situational awareness.

Work Domain Analysis (WDA) is a technique which allows tomodel systems by using event-independent representations thatcan be used to cope with such unanticipated situations. However,to confirm that this technique can be applied usefully, an earlyvalidation is required to ascertain that the WDA is relevant to the
problem context. This paper presents an approach for confirminga WDA by using pilots as subject matter experts (SMEs) during
aircraft turn-round. Firstly, pilots’ operational information
requirements were identified via an Abstraction-Decomposition
Space (ADS) of the A-CDM system developed by the analysis.
Then, pilots were asked via a survey to report about events whereproblems with operational information sharing were encounteredduring turn-round. Finally, these events experienced by thepilots were mapped through the pilots’ information requirements
derived from the ADS. The results reveal that pilots’ information
requirements are not entirely satisfied by current approach to ACDM and provide confirmation for the usefulness of the WDA tothe proposed application as a technique for an A-CDM interface
design cycle.

Key words –abstraction-decomposition space, aircraft turnround, collaborative decision making, cognitive work analysis, work
domain analysis



INTRODUCTION

However, while situational awareness can be createdthrough defined A-CDM rules (milestones) and information
sharing between subsystems, decision makers are often facedwith unanticipated situations where ad hoc decisions arenecessary, e.g. missing passenger or incorrect catering. These

This study is conducted with the financial support from EUROCONTROL
Experimental Centre and FRAPORT Foundation ‚Erich Becker’77situations require decision support to all airport partners andactors involved in operational decision making, since the detailof operational information which is required for decision
making can only be found at action level, however operational
decisions are usually made at tactical level. Action levelreferrs to the level where flight operation takes place, e.g.
airplane, ramp, or airport building; humans executing tasks at
this level are referred to as actors, e.g. pilots, ramp agents, or
air traffic controllers. But these actors are at various distributed
locations and have no access to the ACISP. Therefore
communication channels have to be established from actionlevel to tactical level and vice versa to ensure that a distributed
situational awareness and information sharing can be achievedat all levels.

TOBT is the time that an aircraft operator estimates that anaircraft will be ready to start up immediately upon reception ofclearance from tower. TOBT predictability is a pre-requisite for
ATC to establish a push back/ pre-departure sequence and it isrecognized that the main benefits of sharing TOBT are
expected in case of disruptions.
Within such environment, the task of a theoreticalframework being used must be able to provide a method foranalysis, evaluation, and design of a decision support system toaid decision makers during such turn-round operation. E.g. how
can required information be determined to display, which
format should be used to display information in order tofacilitate cooperative working behavior and effective decision
making? How should the task be effectively distributed acrossthe humans or automated systems? And at a later stage itshould be evaluated how usable and effective the system iswhich has been developed and whether it leads to enhanced
performance.

Another reason for the decision making complexity is the
responsibility of the flight crews for the safety of the flight.
Maintaining safety of the flight can require decision making
already during turn-round, e.g. necessary tire/ equipmentchanges, deloading of unruly passengers or leaving hazardous
cargo behind. Such decisions made by flight crews caninterfere with the pre-planned work procedures of an aircraft
turn-round. Flexible behaviour and problem-solving skills arenecessary in order to manage such situations with minimal timeeffort. Decision support also for such unanticipated situations
demands that all affected participants or actors are provided
with as complete and flexible decision support models of thesituation as possible.

Cognitive Engineering is an interdisciplinary approach todesigning computerized systems intended to support humanperformance [8]. It is concerned with the analysis, design, andevaluation of complex sociotechnical systems (Andriole &Adelman [9], Rasmussen et al. [10], Woods & Roth [11], andVicente [12]). The methods of Cognitive Engineering consider
workers and the tasks they perform as the central drivers for
system design and provide a framework about how people
perform cognitive work. Therefore an approach to cognitiveengineering is chosen as the concept method for the analysis.

The following chapter will outline the motivation which has
led to the development of the research methodology for ananalysis of such a problem. Also the research approach will be
described and how these initial results are useful to support theoverall concept of a Cognitive Work Analysis (CWA) of thisongoing research project with an outlook of the next steps to be
done. The research proposal is in accordance with the SESAR
IP R&D need of developing, testing, and validating the
supporting CDM processes for increased process efficiency andbenefits for the ATM network as a whole [7]. Within the
SESAR proposed operating principles, A-CDM, System Wide
Information Management (SWIM), Network management
function in support of User Driven Priorisation (UDPP), andthe Total Airport Management (TAM) have been realized as
the main enablers to support such airspace/ airport users’
requirements [3].
II.

Activity Theory and Distributed Cognition are the foremost
theories about cognition. They both show descriptive,
rhetorical, inferential power as well as fitness for application
and are both predestinate to be applied to the proposed problem
context. However, activity theory has the human activity as afundamental unit of analysis where Distributed Cognition uses
an ecological perspective as a central element.
The Distributed Cognition theory seems to be the mostpromising approach for the analysis of the A-CDM work
system, because it can be used to analyze how coordination andcooperation of the various subsystems during interdependent
work practices are disrupted due to current information
representation. While mapping out data/ information/knowledge and the means of how it is represented,
communicated, and adapted during A-CDM, implications canbe drawn for the design of information provision in order tosupport human-human and human-machine interactions. Thisapproach has the potential to identify problems within existing
work practices of A-CDM, and has ability to highlight whatneeds to be attained in a future system design. Most of theother approaches used for human-computer interaction analysis
only describe settings and systems; Distributed Cognition
however approaches the design of a system (formative
approach).

MOTIVATIONThe A-CDM system has characteristics of decision making
in a complex and dynamic environment where decisions often
have to be made during unanticipated situations. A single
decision can have dramatic effects that propagate rapidly andwidely through the air transport system.
During present approach to execution of turn-roundprocesses, time constraints are prevailing and the turn-roundprocess is accomplished aiming at a completion in a MinimumTurn-Round Time (MTTT); However, events which can not be
anticipated as mentioned in chapter I, even further increasetime constraints on the Target Off Block Time (TOBT);
especially if only MTTT is scheduled for the turn-round,boundaries of established turn-round practices are explored.

Another prevailing advantage of Distributed Cognition isthat the theory can accommodate the rich variety of systems
and media inherent in organizations’ or groups’ cognitive
processes like within A-CDM. Since the unit of analysis is notcommitted to a fixed value, the entire system can be
decomposed into the smaller, functional groups. However,78

Nardi [13] and Rogers [14] argue that analysis towards
distributed cognition approach cannot generally be used: a lowlevel distributed cognition analysis will not enhanceengineering practices for building design applications. Also thetheoretical perspective is committed to ethnographical datacollection: a substantial investment is required to actually apply
the theory to any specific issue [15, 16].

information actors need in order to deal with unanticipated
events.
Problem solving using the ADS can be carried out via
identification of constraints by starting at high level ofabstraction and then deciding which lower level function isrelevant to the current situation. This iterative “zoom-in”
supports goal-directed problem solving via a “why, what, orhow” questioning. E.g. the present level of observation defines
the what level, while the level above specifies why or the level
below the how.

A framework for using Distributed Cognition theory which
has recently grown in popularity is the Cognitive Work
Analysis. Originated from the problems faced in nuclear power
plant control, Rasmussen [17] has developed the analyticalframework of a Cognitive Work Analysis (CWA) as a basis forthe design of decision support systems in complex
environments. CWA is a conceptual framework that allows
analysis of the forces which shape human-informationinteractions via application of conceptual constructs rather thantesting and verification of models and theories [18]. It is work
centered rather than user centered and considers people whointeract with information as actors involved in their workrelated actions, rather than as users of the system. CWA isusing a range of methods to analyze the various constraints thatare imposed on the activities of a particular system. For the
analysis of a system design, it is necessary to understand not
only the work actors do, but also their information behavior incontext of their work and the reason for their actions. This
allows an application to specific situations.

However, the greatest value of this framework can bederived from its ability to identify information needs which is
required to cope with unanticipated events. Although someresearchers argue that it is not possible to identify suchinformation (Mitchell, 1996 [22]; Shepherd, 1993 [23]),
Rasmussen [24] disagrees by laying out the rationale ofcomplex systems control requirements imposed byunanticipated events: This leads to the design requirements of
information representation for actors’ needs during such events.
III.

METHOD

A methodological approach is used for the analysis of the
CDM turn-round. Firstly, an ADS is developed by using thestep-by-step WDA methodology described by Naikar et al [25].
The ADS is then used to make implications for information
requirements of pilots during A-CDM by representing thedifferent categories of required information, based on the ADS
summary table (figure 1). However, it has to be confirmed that
this technique can be applied usefully and the analysis isrelevant: Work domain model based interfaces can also lead tofalse diagnosis because its validity is initially not based on
experimental results (Burns et al [26]; Vicente, Christoffersen& Pereklita [27]; Christoffersen, Hunter & Vicente [28]). To
confirm the A-CDM system constraints, the work domain
model is compared with the results from a pilot questionnaire
on unanticipated events during turn-round which wasdeveloped independent from the ADS. Pilots were asked toforward information requirements and current interface design
constraints during turn-round situations which were seen as
critical for situational awareness in the existing turn-roundprocesses. According to Naikar [25], validation of the ADS
should be based on other information than that was used tocreate the ADS.

For this reason, CWA was already successfully applied tomany other complex domains. The majority of studies on CWA
have focused on its application to interface design (e.g. Burns,
2000 [19]; Burns, Bryant & Chalmers, 2000 [20]; Dinadis &Vicente, 1999; Gualtieri, Elm, Potter & Roth, 2001, Naikar,
Hopcroft & Moylan, 2005). CWA was also applied to existing
systems, e.g. for process control (Vicente 1996; Jamieson &Vicente, 1998), to design interfaces designing teams (e.g.
Gualtierir, Roth & Eggleston, 2000; Naikar, Pearce, Drumm &Sanderson, 2003), evaluating design proposals (Naikar &Sanderson, 2001); analyzing training needs (Naikar &Sanderson, 1999; Naikar & Saunders, 2003); and developing
specifications (Leveson, 2000).
CWA consists of five stages: Work Domain Analysis WDA(1), Control Task Analysis (2), Strategies Analysis (3), Social
Organization and Cooperation Analysis (4), and Worker
Competencies Analysis (5). Primary focus of the analysis isoriginally on the work domain. This first phase of analysis, the
WDA, identifies a fundamental set of constraints imposed on
the actions of any actor, and develops an event-independent
representation that can be used to cope with novel situations.
However, a clear distinction between the different types ofhierarchical relations within the work system is necessary for aproper WDA [21]. The decomposition (part-whole) hierarchy
and an abstraction (means-end) hierarchy together form a twodimensional Abstraction-Decomposition Space (ADS) which isable to show the generic properties of a complex system. This
adds unique value for understanding the system, and the ADS
modeling tool is used here to develop a schematic
representation of the A-CDM domain. The important feature ofan ADS is the way it provides a representation of the complex
system and also how it provides a basis for identification of the

The overall objective of the study was to confirm that the
ADS model captures the domain constraints during A-CDM
seen from pilots’ perspective that were used in the turn-round
scenarios. If any constraints were missing, the ADS can be
improved by adding those constraints. At a later stage of theresearch, also the constraints identified by all otherparticipating airport partners and actors will be identified via
brainstorming sessions and unstructured interviews with SMEs.
Constraints other than from work domain itself will beanalyzed in the next phases of the CWA.
A. Work Domain Analysis of the A-CDM System
A WDA is required to develop an event-independent
representation of the work system. Naikar [25] describes a stepby-step methodology for a WDA which is now outlined as79

applied for the A-CDM system. The following steps were
executed in order to develop the ADS.

For construction of an ADS, the potential sources of
information have to be identified [25]. A large number of data/
information sources were found that could inform the A-CDM
system domain. This is due to the large number of different
participating operators in this system including the airport
representatives, airline companies, flight crews, air traffic
control, technicians, ramp agents, loaders, airport & ramp
personnel, Central Flow Management Unit and passengers.
One major information source are documents relating tolegislation and company policies, training manuals, airport
infrastructure, company reports, and the A-CDM genericprocedures.

Step 1: Establish the purpose of the WDAThis step involves defining the purpose of the analysis. It
includes two parts which are defining the problem and defining
how WDA will be used to address the problem [25]. For the
analysis, two main purposes were identified which are theidentification of the information requirements of all operators
during turn-round in order to maintain turn-round process
predictability, and identification of the underlying airport
infrastructure necessary to support these requirements. The
WDA is used for developing a functional model of A-CDM
system from the viewpoint of an actor: it should be able toidentify the different categories of information which decision
makers require, and the airport infrastructure that might berequired to support decision making during A-CDM. In thenext steps of the research project, also other actors’ and airport
partners’ viewpoints will be captured.

The work setting itself was used as the second source of
information gathering, where observations of work settings
were made with minimal interruptions of the observed
activities. Observed items include tools and interactions thatworkers use. Hajdukiewicz [30] recommends distinguishing
between exploratory observations for understanding the work
environment, and focused observations concentrated onparticular aspects of a chosen system that should be made.
Initially only exploratory observations were made for this firststage of analysis.

Step2: Identify Project Constraints
Not only the purpose, but also the constraints that may
affect how the WDA is conducted have to be identified in orderto maintain the pursued scope and focus of the analysis. For
this research on A-CDM, the main constraints emerged fromcomplexity of the problem environment, time & expertise
related constraints. The scope of the analysis depended heavily
on the information made available by participating stakeholders.

Additionally, also focus group meetings, observation,
brainstorming, and interviews with pilots as SMEs contributed
to information gathering. Additional data was also gathered via
talkthroughs, and tabletop analyses. For this phase of research,
Rasmussen [17] points out that the analyzer should keep inmind the danger that real constraints and actual reasons of
behavior are often hidden behind routines and rationalizations,and regardless of the source of information the analyzer shouldbear in mind the constraints that shape the behavior.

Step 3: Determine the Boundaries of the WDA
The analyzed work system can be defined as the processes
necessary to maintain situational awareness during turn-roundin order to achieve a reliable TOBT. During this step, humanhuman or human-computer interactions related to operational
information sharing processes are reviewed in regard of the aim
to make the TOBT as predictable as possible between
milestones 6 and 15. This artificial boundary was chosen inorder to keep the WDA in a useful and obtainable scope.
Nevertheless there are numerous elements outside the focus
system which influence elements within the focus of theanalysis, e.g. weather, legal requirements, but for practicalconsiderations they will be left outside of the analysis.

Step 6: Construct ADS- First Iteration
For a first iteration of an ADS, Naikar [25] outlines five phasesof developing the ADS which are:

Step 4: Identify the Nature of Constraints
According to Naikar [25], it is necessary to identify thelocation of the focus system on the causal-intentional
continuum, because the nature of the constraints that should bemodeled in the ADS has to be found (Hajdukiewicz [29]). The
categories defined by Rasmussen [17] are used as a basis todetermine the nature of the constraints of the proposed problem
space. It was concluded that A-CDM has major attributes to asystem governed by actors’ intentions and the nature ofconstraints modeled by the WDA are intentional constraints
based on organizational policies, legislation, and other forms ofregulation, social laws and conventions, and actors’ intentions
or motives. This goes along with the identified purpose of the
WDA.

x

Identification of Work-Domain Propertiesx

Defining theDecompositionx

Developing a Sketch of the ADS

xEvaluating which Cells of the ADS to Populate, andx

Population of Selected Cells of the ADS.

IV.

Levelsof

Abstraction

andRESULTSAs a first result of following Naikar’s step-by-stepmethodology, a matrix was developed which populates all cells
based on the identified work-domain properties, levels of
abstraction, and levels of decomposition (table 1). This matrix
describes a conceptual view of the A-CDM system and offers a

Step 5: Identify Potential Source of Information80

Total System

conceptual level of resolution for viewing the A-CDM work
domain. The conceptual view of the A-CDM proposed here
offered by the three cells at the purpose-related functions levelof abstraction is that of the possible functions of the A-CDM
system. The three cells offer different resolutions for viewing
the functions of the A-CDM which are the functions of thewhole A-CDM Decision Making system, the functions of the
CDM Turn-Round Element, and the functions of the different
components of A-CDM like the milestones, ACISP, and ACDM Partners (Fig 1).
Total System
Functional
Purpose

Abstract
Function

Generalised
Function

Physical
Function

Physical
Form

Sub-System

Functional
Purpose
Abstract
Function
Generalised
Function

CDM Turn-round Process
Element

Milestones, ACISP, A-CDM
Partners

Purposes
 Improve work together at an
operational level
 Efficient and safe daily flight
operation with reliable information
provision & Common Situational
Awareness
External Constraints
 Laws & Regulations by airport,
national government, Europe, IATA,EUROCONTROL, ICAO Local Standard Operationg
Procedures
Criteria
 ATTT Turn-round compliance (STTT vsATTT) TOBT/TSAT Predictability
 EIBT Predictability: EIBT vs time Ready Reaction Time: AOBT ARDT

Purposes Provide the A-CDM partners
with a common situationalawareness
 Anticipation of disruptions &expeditious recovery throughinformation sharing among all
partners including passengers
External constraints
 Distributed location between
CDM partners and actors
 Laws & Regulations

Purposes Milestones: To provide decision
makers with information aboutflight progress and trigger
decision making
 ACISP: To provide
information sharing between the
Airport CDM Partners
 A-CDM Partner Goals

 Safe & efficient usage of available
resources Effective law, regualation,
procedure, and policy enforcement
 Redesign of airport operational
procedures
 Implementation of CDM functions

 Safe & efficient turn-round &flight Adherence to CDM procedures
 Efficient implementation ofcollaborative decisions at actionlevel Enforcement of laws,
regulations, procedures Provision of reliable information for
all CDM partners
 Collaborative operational decision
making Increasing Situational Awareness A-CDM Information Sharing
Platform (ACISP) Efficient information provision& cooperation between operators& actors
 Distributed Situational
Awareness at action level
 Efficient command & control
structure between pretactical &action level of operation

MilestonesFunctionalability/capability/limit
ations & status Inform all partners
ACISP & A-CDM Partners
Functionalability/capability/limi
tation Establish Situational
Awareness IT platforms with operational
information sources, e.g. TOBT/ TSAT AMAN/DMAN
 Airport Operation Centre (APOC) Representative Decision Makers of
all partners
 Meteorlogical features, e.g. adverse
weather condition

 Printed Information/ Data
about TOBT/TSAT Information Screens forpassengers
 Airport Infrastructure &Airspace Structure Alert Messages to all CDM
partners via the ACISP Flight Update Messages(FUMs)

 Electronic Data/ Information
 Software Applications
 HMIs, e.g. ACARS, Telefon,
computer Computer Network Operation Room Passengers
 Actors

Walkthroughs and TalkthroughsxInterviewsx

Table-Top Analysis

ShorterTravelTime

WHY

Increased
Passenger
Satisfaction

Safe & Efficient Usage of
Ressources/ Information

WHAT

CompliantOperator
Behavior

Effective
Turn-Round
Procedures

HOW

Operators’
Capabilities &Limitations

Milestones’
Functionability& Limitations

ACISP &
Infrastructure

A. Pilots’ Decision Support
The next step was to draw implications from the ADS for
possible information provision to pilots and pilots´ support for
decision making during turn-round. These identified
information requirements will later be mapped against theresults from the cockpit survey in order to confirm that the
WDA is on the right track and the ADS is valid.

Milestones
 Data/ Information availability& Practicability of Information
ACISP & A-CDM Partners
 Physical dynamics of user
behaviour

Implications are divided in two main areas which are:1.

Pilots’ Information Requirements

Information requirements identified by the ADS include data
which should be provided to pilots to increase situationalawareness at the distributed location of the cockpit. Failing topresent required data, presenting data in an inappropriatemanner or presenting too much data can potentially havedetrimental effect upon task performance (Salmon et al [31]).
These information requirements can then be used to inform the
A-CDM design by specifying what data should be presented tothe cockpit via available communication devices like ACARS,
phone, or two-way radio. E.g. Salmon et al [32] has used the
ADS to specify information requirements for a command andcontrol knowledge wall display, or Ahlstrom [33] used the
ADS for determining the types of information that air traffic
controllers require for effective performance during adverse
weather conditions. Therefore it is argued that the ADS of the
A-CDM system can be used to identify different categories of
information that pilots require to support effective decision
making during turn-round.

For the second iteration of the ADS, additional information
sources were used to further develop the ADS. Therefore, thefollowing phases were again carried out:x

Increased
Punctuality(Reliability)

Component
Milestones, ACISP, A-CDM
Partners

Figure 2. A-CDM Abstraction-Decomposition Space

External Constraints
 No & design of Milestones,
Alert
Milestones
 CDM Procedure Group
Meetings
 Performance Assessments
ACISP & A-CDM Partners
 User feedback & Performance
Assessment

Step 7: Construct ADS- Second Iteration

Focused Field Observations

Safe & Efficient
Flight Operation

Physical
Form

Figure 1. A-CDM Conceptual Matrixx

Sub-System
CDM Turn-round Process
Element

Physical
Function

Component

Airport Collaborative Decision

Criteria
 ATTT Turn-round compliance (STTTvs ATTT) TOBT/TSAT Predictability
 EIBT Predictability: EIBTvs time Ready Reaction Time: AOBT –ARDTAirport Collaborative Decision

Information requirements are extracted from the ADS of ACDM as they relate to purpose related functions of cockpit
information requirements. (Figure 3)

The resulting ADS (Figure 2) involved reviewing the ADS
with domain experts who agreed on the variouselements of the
ADS model including the levels of abstraction and means-ends
relations in the ADS, the level of decomposition and partwhole relations in the ADS, and the categories of constraints ineach cell of the ADS.

81

Total System
Airport Collaborative Decision

Functional
Purpose A-CDM Information Sharing, e.g.
TOBT, TSAT Common Situational Awareness

Abstract
Function ETTT Turn-round compliance of Actors
involved
 TOBT/TSAT/TTOT/CTOT
Creation EIBT Predictability: EIBT vsproposed waiting time

Generalised
Function

Physical
Function

PhysicalForm Airport Apron Rules & Regulations
 Warnings, e.g. airport policies &
local restrictions
 Behavioral recommendations, e.g.
taxi time required,

Sub-System
CDM Turn-round Process
Element

procedures as identified by the ADS. This table compares theinformation which is already given to pilots and theinformation which is required by them according the ADS. It isalso taken into account, if the information given complies withall information requirements or only partially.

Component
Milestones, ACISP, A-CDM
Partners
 Pilots`Goals
 Safety Level
 Airport Performance Aircraft Technical Status
 A-CDM Partner Goals

 Milestones 6 until milestone 15
 Not time & time related data Aircraft operational statu
 Variable Taxi Time
Calculation
 CDM Complicance Alarms

 Economic Cost of Planned/
Alternative Turn-Round Safety Level
 Performance and Status of All
Participating Aircraft Requirements & Status TIBT & Stand Information
 Ground Handling Start Delay Runway in use
 EOBT/TOBT/CTOT
Complicance alarms
 EXOT Physical turn-round control task
support Cognitive turn-round control task
support Turn-Round Complicance control

Table 1 Information for Pilots’ Decision Support
Information Requirement

Information Provided to Pilots
YES

Information from ACISP Operational Information Sharing
with Cockpit
 CDM operating procedures Information Sharing among
particpating actors
 A-CDM Information Sharing
Platform (ACISP) Information about Changes of
TIBT & Stand Information about Ground
Handling Start Problems
 Information about Runwaychanges Information about
EOBT/TOBT/CTOT changes
 Information about scheduled
EXOT, if relevant Access to ACISP from cockpit
 Provision of TOBT/TSAT/TTOT to
cockpit Information about Passenger
Boarding Time Environmental Condition
Information
 Turn-Round disruptions

TOBT/ TSAT Capability/ Knowledge Level of
All Participating Availability of Resources Current task status in relation to
goals

x
x

Turn-Round Compliance of other actors

x
x

TTOT
Apron Rules & Regulations

 Current Component Performance& Status Current Airport & Aircraft
Condition
 Other A-CDM users location &future movementsxxInfrastructure related warningsx

Behavioral Recommendations

x

Operational Information
CDM Operating Proceduresxx

Information Sharing among participating actors

xPassenger Boarding Time

Figure 3. Pilots Information Requirements during Turn-RoundEnvironmental Condition Informationxx

Turn-Round Disruptionsx

Time related Data

The information requirements can be grouped in categories
which are not available to pilots in current A-CDM
approach:xx

Aircraft Operational Statusx

Variable Taxi Time Calculationx

CDM Compliance AlertsxStand Information

Runway in Use

A-CDM compliance alarmsx

Airport warnings & recommendations

EXOT

x

Operational status information
disruptions and other actors’ goals

Safety Level

xx
x

EOBT/TOBT/CTOT Compliance alarms

Pilots`Goals

includingAircraft Technical Status

Participating actors’ performance, status, andknowledge level

A-CDM Partner Goals

Availability of resources

Aircraft Requirements & Statusx

Understanding of the integration within trafficof other aircraft (e.g. pre-departure sequence)x

Physical turn-round compliance control task
supportx

Ensuring of awareness & knowledge level ofother participating actors

x
x
x
x
x

Performance & Status of all participating actorsxx

Physical turn-round control task support

The ADS reveals also information which could support
pilots in decision making during turn-round, if it would bemade available to cockpits. This includes:
Understanding of A-CDM generic procedures(e.g. DPI or FUMs)xx

Economic Cost of planned/ alternative Turn-RoundPossible Support for Pilotsxx

Airport Performance

Cognitive turn-round control task support

2.

x
x

Ground Handling Start Delay

x

x

x

Not time related Data

Target In Block Time

A-CDM Information Sharing elements, e.g.
TTOT, EXOTxx

Turn-Round Compliance control task supportx

Capability/ Knowledge Level of all participating actorsx

Available Resourcesx

Current task status in relation to goalsxCurrent component performance & statusx

Current airport & aircraft condition
Other A-CDM users location & future movements

PARTIALLY

x

ETTT

CTOT

NO

x
x

Focus has not yet applied on provision of such information to
the cockpit or how it should be provided. It is argued howeverthat availability of this information could contribute to a
distributed situational awareness while improving turn-roundefficiency.
B. Validation of the ADS
This step aims to determine whether the ADS is as accurate
and complete as possible. Naikar [25] proposes a number ofpossibilities for the validation of ADS. One possibility is to use

Table 1 shows the information that should be provided tosupport pilots for safe, efficient, and reliable turn-round82the material already studied for the construction of the ADS,
however it is not necessarily useful to use the same sources of
information for validating the ADS.

The turn-round situations were grouped into three categories:
x Information provision from other actors to cockpit
during flight
x Information provision from other actors to cockpit
during turn-roundx Information provision from cockpit to otherparticipating actors
The survey was conducted on-line for a period of two months
with invitations to pilots from many European airlines.

A better option is to use reasoning patterns of actors invarious situations, e.g. incident reports with necessary decision
making (Naikar, 2005). For this reason, the pilot survey wasdeveloped aiming at reconstructing such situations which pilots
encountered during turn-round. The situations proposed in thesurvey were all concerning turn-round process reliability andrequired cooperation and awareness of various actors or airport
partners similar to the A-CDM Turn-Round concept element,
however seen only from pilots’ perspective. A large number ofsituations critical for TOBT adherence were proposed to thepilots; nevertheless pilots were allowed to add also otherroutine or novel events which they encountered.

Table 2 provides an overview of the different turn-round
operation situations and the categories of questions whichwere asked together with each of these situations:
Table 2: Turn-Round Situations

Thereafter, the collected data was analyzed and examined
for work-domain properties that characterized actors’ reasoning
patterns during these turn-round situations. The work-domain
property data were then mapped in form of examples onto the
ADS and examined as to whether the situations are captured by
the different categories of constraints, and analyzed which partsof the decomposition space that are represented in the ADS,
were involved.

TURNROUND
Gate
Assignment
GroundHandling/
Ramp
Delay
ATC
RelatedDelay
Operational
Info OUT
RelatedDelay
Operational
Info IN
RelatedDelay

C. The Design of the Cockpit Survey
The cockpit survey examined five different turn-round
operation situations which entail the risk to jeopardize flightpunctuality by delayed turn-round processes due to problems
with information-interactions between aircraft cockpit anddecision makers like airport partners at operation center or
actors at the ramp. The ADS developed by the WDA provided
some insights for understanding the cockpit’s information
requirements during turn-round. However, the analysis is not
validated through experimental results.
The aim of the questionnaire was therefore to capture pilots’view on non-cooperative information-interaction behavior
between pilots and other airport partners or actors, and thepossible reasons and consequences of such behavior.
Cooperative behavior is seen as a synchronous andhomogeneous sharing of required information for operational
decision making or situational awareness among participating
actors. This should enable the pilots and all airport partners or
actors involved to respond to the local context in real time.
Hence, the survey addressed how the airport information
sharing process was influenced by the following variables:
x Interaction Mode (synchronous versus
asynchronous)
x Information Distribution (homogenous versus
heterogenous)(NON-)
COOPERATION/

COOPERATIVECOMPONENTAIRPORT

FREQUENCY

RELEVANCE

Y/N

Aims/Resources/
Abilities

Hub/ Non
Hub

Daily/Weekly/Monthly/
Irregularly

Avoidable Delay
Likelihood

Y/N

Aims/Resources/
Abilities

Hub/ Non
Hub

Daily/Weekly/Monthly

Avoidable Delay
Likelihood

Y/N

Aims/Resources/
Abilities

Hub/ Non
Hub

Daily/Weekly/Monthly

Avoidable Delay
Likelihood

Y/N

Aims/Resources/
Abilities

Hub/ Non
Hub

Daily/Weekly/Monthly

Avoidable Delay
Likelihood

Y/N

Aims/Resources/
Abilities

Hub/ Non
Hub

Daily/Weekly/Monthly

Avoidable Delay
Likelihood

Approach of the Survey
The pursued approach had the aim to lay out the broadest
range of possible turn-round situations in order to cover as
many situations as possible. Accomplished brainstorming
sessions with pilots revealed that information sharing
problems during turn-round can be manifold and that each
event can potentially be unique in its specific situation.
However, a number of problems occur regularly and canpotentially be attributed to a specific category of problem.
Therefore, the questionnaire proposed to the pilots included
various situations with all CDM partners and actors involvedin operational information sharing. These are the airport
operator, air traffic control, CFMU, airline company, groundhandler, ramp agent, flight manager, check-in and boarding
personnel, loaders for cargo, mail and baggage, and service
providers like fueling, catering, cleaning.

The result should then allow deducting information
requirements for achieving distributed situational awareness ofthe pilots during these situations. Pilots were asked to report
recent experiences on failed sharing of operational informationand the consequences on the process delay. They were also
asked whether a departure delay was encountered after thedelayed turn-round process.

83causes analogous a cooperation model of Ferber [34]. The
reasons are divided into three categories which are theTable 3 Possible Information-Interactions during Turn-Round
Turn-Round Problem

Information Required

Availibility of Parking Stand

Expected Delay /Reason of Delay for Parking
Delay: Expected duration, reason, No ofbaggage

Baggage Loading/ Unloading
Ramp Transfer Bus (Passenger or Crew)

Delay: Expected duration, reason

Catering

Delay: Expected duration, reason

Cleaning

Delay: Expected duration, reason

Fueling

Delay: Expected duration, reason

Check-In

Delay: Expected duration, reason

Security

Delay: Expected duration, reason

Boarding

Delay: Expected duration, reason

Airport Facilities

Delay: Expected duration, reason

Wheelchair-boarding

Delay: Expected duration, reason

UM Boarding

Delay: Expected duration, reason

Special Loading (e.g. musical instrument)

Delay: Expected duration, reason

VIP Boarding

Delay: Expected duration, reason

ATC Request

Delay: Expected duration, reason

CFMU Regulation

Delay: Expected duration, reason

Aircraft Change

Reason and status of new aircraft

Technical Repair

Reason and expected l duration of repair

Crew Duty Change (new duty roster)

Timely Provision

Crew Change (new crew member)Timely Provision

Crew Proposal: Connecting Passenger

Response and expected action

Crew Proposal: Necessary A/C repair
Crew Proposal: Avoidance of A/C
ChangeResponse and expected action
Response and expected action

Other: No Flight documents delivered

Response and expected delivery

Other: No Ramp Agent available
Crew Proposal: Avoidance of A/C
ChangeStatus of Service Delivery

 Aims Resources, and Abilities
The level of agreement to each of the three categories wasmeasured with 1 = very unlikely to 4 = very likely. This data
will at later stage also be used to identify non-cooperative
situations according to Ferbers’ Cooperation Model.
In all questions, multiple and equivalent choices were allowed,that means the pilots could assign multiple causes of failures
to each specific event.
Survey Data Analysis
For the data analysis, only situations were chosen where pilots
reported an information-interaction problem has taken place
which has an impact on ground handling or on other service
delivery during turn-round. They were organized as follows: The situations reported by pilots are summarized in atable, displaying the number of occurrences.
 Descriptive data analysis was used to obtainmeasures of central tendency or dispersion about the
avoidability of delay via Likert scale. It was
discovered that some situations were more avoidable
than others.
 Delay of the service delivery was reported to bedifferent for different situations.
 Correlation analysis was carried out between turnround process delay and departure delay.
Statistical Analysis was performed with SPSS 17.0 and Excel.
An  level of 0.5 was chosen as decision criterion. Spearman’s
rho was used as a measure of correlation.

Response and expected action

Pilots were asked to choose their agreement between two
statements entailing information provision for each of theinformation problems from table 3:
 I was informed about the problem in time (includes
possibility to take appropriate action)
 I learned about the problem having observed that theprocess was not executed or I received information
too late.
For each turn-round situation of the survey, the pilots wereasked to rate on a scale from 1 = very unlikely to 4 = very
likely, whether the delay of the turn-round process was
avoidable or not.
Additionally, the pilots were asked to assess how many
minutes of delay resulted from the turn-round process which
was deviating from established turn-round schedule, and how
many minutes departure delay were encountered after thatturn-round with this service failure. Only events were taken
into account which were reported to occur at least on amonthly basis.
The ADS reveals also a pilots’ information need about ‘task
status in relation to goals’ derived from the physical functionof the A-CDM Partners component. Therefore, the pilots werealso asked to attribute the possible reason for the problem

Survey Results
1. Pilots’ General Information
The 196 pilots participated in the survey with useful results(n=106) from for airlines like Austrian (n=2), Air Berlin(n=16), Air France (n=9), Easy Jet (n=1), Lufthansa (n=77),
and Transavia (n=1). 44.6% of the pilots were captains, 55.4%
first officers. Average experience was reported by 6.58 years
as First Officer and 7.37 years as Captain.

2. Pilots’ Information Requirements from Survey
In this section, the results concerning information
requirements will be shown as a function of avoidability ofdelay like reported by pilots. Figure 4 shows the mean values
that received high ratings of the five proposed turn-roundsituations:84

Mean Rating Avoidability
Operational Information
From Cockpit

3. Effect of Process Delay on Departure Punctuality
A statistically significant correlation could be identified for theturn-round processes which produced a delay (independent
variable) in relation to the departure delay after turn-round as
shown in percent of of all reported information sharing
failures (dependent variable). Following figures show the
proposed situations like late parking stand assignments (figure6), ramp & terminal service delivery (figure 7), operational
information sharing to cockpit (figure 8), and operational
information sharing from cockpit (figure 9):3,2Operational Information
To Cockpit

2,8

ATC Information
Provision

3

Ramp & Terminal Service
Problems

2,7

Availibility of Parking
Stand

2,3
1

1,5

2

2,5

3

3,5

4

Process Delay

Figure 4 Mean Rating Avoidability of Delay
60
50
40
30
20
10
0

The highest rating received by the pilots was the need to take
into account operational information given by pilots, where
the pilots see fewer options to avoid delays through timely
notification of parking stand availability.
Pilots were asked to report events they experienced, however,most of the pilots used the proposed situations which wereverified as critical turn-round events during focus groupmeetings. Figure 5 shows reported frequency of the fiveproposed turn-round situations of all participating pilots andreported turn-round events as frequency in percent in the orderof the survey.
Turn-Round Problem
Availability of Parking Stand
Baggage Loading/ Unloading

Reported
Situation
Frequency
in %
95,1
100

41,8

6,1
1-5 Minutes

Catering

100

1Cleaning

100

2,9

Fueling

100

4,9Check-In100

1Security100

2

Boarding

100

13,7

Airport Facilities

100

4,9

Wheelcharboarding

100

3,3

UM Boarding

100

0Special Loading (e.g. musical instrument)

100

1

VIP Boarding

100

5,9

Missing Flight Documents

100

2

ATC Request

95,1

99

Aircraft Change
Crew Duty Change (new duty roster)

95,1

63,1

95,1

18,4

95,1

1,9

Technical Repair

95,1

7,8

Other

95,1

3,9

Crew Proposal: Connecting Passenger

93,2

5,8

Crew Proposal: Necessary A/C repair

93,2

33

Crew Proposal: Avoidance of A/C Change

93,2

47,5

Crew Other Proposal

93,2

5,8

2

6

11-15 Minutes 16-20 Minutes

1,2More than 20
Minutes(Spearman’s rho = 0.363, p=0.001, two tailed test, N=84)
Process Delay
40

32,4

20

15,7

Departure Delay

36,3
27,5

30

47,1
11,8

6-10 Minutes

11,9

Figure 6 Process & Departure Delay for Parking Stand Assignment

95,1

100

46,4

23,8

Reported
Event
Frequencyin %Ramp Transfer Bus (Passenger or Crew)

Crew Change (new crew member)

50

Departure Delay

24,5

10,8

8,8

10

14,7

10,8
3,9

0
1-5 Minutes

6-10 Minutes

11-15 Minutes 16-20 Minutes

More than 20
MinutesFigure 7 Ramp & Terminal Service Delivery(Spearman’s rho = 0.424, p=0.000, two tailed test, N=102)

Process Delay
50
40
30
20
10
0

Departure Delay

45,4

1

7,2

1-5 Minutes

13,4

17,5

6-10 Minutes

22,7

20,6

13,4 16,5

11-15 Minutes 16-20 Minutes

27,8More than 20
MinutesFigure 8 Operational Information to Cockpit(Spearman’s rho = 0.760, p=0.000, two tailed test, N=97)

Figure 5 Turn-Round Events reported by pilots

85

Process Delay
25
20
15
10
5
0

functional relations as the ADS identified by the analysis.
Figure 11 shows the specific information requirements during
turn-round service processes as reported by the pilots:

Departure Delay
21,5

17,1

15,7 16,5

15,7

11,4 10,1

10,1
4,3 3,8

Total System
Airport Collaborative Decision

1-5 Minutes

6-10 Minutes

11-15 Minutes 16-20 Minutes

More than 20
Minutes

Functional
Purpose
Abstract
Function

Figure 9 Operational Information From Cockpit(Spearman’s rho = 0.854, p=0.000, two tailed test, N=79)
Generalised
Function

Even though it is not possible to infer that the turn-roundprocess delay can be merely contributed to the overall
departure delay, it entails a high risk of being responsible forthe delay since also the amount of delay correlates
significantly between process delay and departure delay. It canbe argued that this result is only pilots’ assessments and notreal data during turn-round. However, in all situations pilots
are always directly affected by the delay and physicallypresent where the turn-round takes place.

Physical
Function

Physical
Form

Sub-System
CDM Turn-round Process
Element

 Pilots`Goals
 Safety Level
 Airport Performance Aircraft Technical Status
 A-CDM Partner Goals

 A-CDM Information Sharing Common Situational Awareness ETTT Turn-round compliance of Actors
involved

 Airport Apron Rules & Regulations
 Warnings, e.g. airport policies &
local restrictions
 Behavioral recommendations, e.g.
taxi time required Operational Information Sharing
with Cockpit
 CDM operating procedures Information Sharing among
particpating actors
 A-CDM Information Sharing
Platform (ACISP)

 Access to ACISP from cockpit
 Provision of TOBT/TSAT/TTOT to
cockpit Information about Passenger
Boarding Time Environmental Condition
Information
 Turn-Round disruptions

Component
Milestones, ACISP, A-CDM
Partners

 Milestones 6 until milestone 15
 Not time & time related data Aircraft operational statu
 Variable Taxi Time
Calculation
 CDM Complicance Alarms

 Economic Cost of Planned/
Alternative Turn-Round Safety Level
 Performance and Status of All
Participating Aircraft Requirements & Status TIBT & Stand Information
 Ground Handling Start Delay Capability/ Knowledge Level of
All Participating Availibility of Ressources Information about Changes of
TIBT & Stand Information about Ground
Handling Start Problems
 Information about Runwaychanges Information about
EOBT/TOBT/CTOT changes
 Information about scheduled
EXOT, if relevant Current Component Performance& Status Current Aircraft & Airport
Condition
 Other A-CDM users’ location &future movements

 Current Component Performance& Status Current Airport & Aircraft
Condition
 Other A-CDM users location &future movements

4. Current Task Status in Relation to Actors’ Goals
Following table provides the pilots’ assessment of possible
failure causes expressed in three components like aims,
resources, and abilities. Even though it can be questioned that it
is possible for pilots to identify failure causes objectively, it isargued that pilots have operational experience from a homebase airport which they are familiar with. Since all participating
pilots fly for airlines having a large network, pilots can easycompare turn-round services from other airports with theirhome base. This allows a unique way to compare service
provision of various airports. Figure 10 compares the different
assigned ratings of the three components aims, resources, andabilities:
Operational Information From Cockpit

3,06
3,12

1,77

ATC Information

1,82

2,26

3,59

2,41
2,76
2,84

Parking Stand

2,59

1
Competing Aims

Other problems were reported as caused by noninformation sharing of ATC: Because information about arunway change is not communicated to the pilots, cockpit
needs extra time for changing take-off performance
calculations after clearance request and this entails the risk ofjeopardizing TOBT and TTOT adherence. Short notices of
runway changes can also significantly change taxi times withadditional risk of missing CTOT. Figure 12 shows the specificinformation requirements for such situations as identified from
ADS.

2,48

2,89

Ramp & Terminal Services

It can be seen from figure 11 that although actors like pilots
are not inherent A-CDM Partners, the low level details of
information about the capability/ knowledge level of allparticipating at physical function level can be traced back to theoverall purpose of A-CDM Information Sharing. Also thephysical form of the identified components which reveals aneed for the current component performance and status, canaffect other CDM related processes in a dynamic way as shownby the other active highlighted areas of the ADS. Therefore it isargued that sufficient situational awareness should be
distributed among airport partners and actors involved and notsolely established among airport partners only.

2,96
2,9

1,81

Operational Information To Cockpit

Figure 11 Mapping of Service Information Requirements on ADS

1,5

Insufficient Resources

2

2,5

3

3,5

4

Insufficient Abilities

Figure 10 Possible Information Sharing Failure Causes

V.

MAPPING SURVEY RESULTS ON THE ADS

The events experienced by the pilots were mapped through thepilots’ information requirements derived from the ADS, andthe relevant areas identified and highlighted. The particular
information gained from the pilots’ survey followed the same86Total System
Airport Collaborative Decision

Functional
Purpose
Abstract
Function

Generalised
Function

Physical
Function

Physical
Form

Sub-System
CDM Turn-round Process
Element

 Pilots`Goals
 Safety Level
 Airport Performance Aircraft Technical Status
 A-CDM Partner Goals

 A-CDM Information Sharing Common Situational Awareness ETTT TTOT Creation

 Airport Apron Rules & Regulations
 Warnings, e.g. airport policies &
local restrictions
 Behavioral recommendations, e.g.
taxi time required Operational Information Sharing
with Cockpit
 CDM operating procedures Information Sharing among
particpating actors
 A-CDM Information Sharing
Platform (ACISP)

Component
Milestones, ACISP, A-CDM
Partners

 Milestones 6 until milestone 15
 Not time & time related data Aircraft operational statu
 Variable Taxi Time
Calculation
 CDM Complicance Alarms

 Economic Cost of Planned/
Alternative Turn-Round Safety Level
 Performance and Status of All
Participating Aircraft Requirements & Status

 Runway in Use
 EXOT Capability/ Knowledge Level of
All Participating Availibility of Ressources Information about Changes of
TIBT & Stand Information about Ground
Handling Start Problems
 Information about Runwaychanges Information about
EOBT/TOBT/CTOT changes
 Information about scheduled
EXOT, if relevant Access to ACISP from cockpit
 Provision of TOBT/TSAT/TTOT to
cockpit Information about Passenger
Boarding Time Environmental Condition
Information
 Turn-Round disruptions

 Capability/ Knowledge Level of
All Participating Availability of Ressources Current Task Status in Relation
to Goal Current Airport & Aircraft
Condition
 Other A-CDM users location &future movements

Figure 12 Mapping of ATC Information Requirements on the ADS

This change in use of runway at physical level depends on
knowledge level of all participating and in case of a CTOT
regulated flight also estimated taxi out time. Changing the
runway without prior notice affects pre-plannned ATTT,
however adherence to it is necessary for a reliable sequenceplanning at the airport. Even figure 7 shows only pilots’
information requirements, a not communicated runway change
will also affect other A-CDM partners and the environment as
well.
These two examples give only a snapshot of the overall
information requirements from pilots during A-CDM. The
other proposed situations follow a similar pattern through the
ADS. However it could be confirmed that all information
requirements reported via the survey could be identified byusing the ADS.

VI.

A. Abbreviations and Acronyms
ADS
Abstraction-Decomposition Space
A-CDM

Airport Collaborative Decision Making

ACIS

Airport CDM Information Sharing

ACISP

Airport CDM Information Sharing Platform

AOP

Airport Operation PlanATCAir Traffic Control

ATTT

Actual Take of TimeCTOT

Calculated Take Off TimeCTRP

CDM Turn Round Process

CWA

Cognitive Work Analysis

DPI

Departure Planning Information

ETTT

Estimated Turn Round Time

EXOT

Estimated Taxi Out Time

FUM

Flight Update Messages

MTTT

Minimum Turn-Round Time

TAM

Total Airport Management

TOBT

Target Off Block TimeTSAT

Target Start-Up Approval Time

TTOT

Target Take Off Time

VTTC

Variable Taxi Time Calculation

WDA

Work Domain Analysis

ACKNOWLEDGMENT
I would like to thank all pilots from Air Berlin, Air France,
Austrian, Easy Jet, Lufthansa, Lufthansa CityLine, andTransavia who participated in this study, also for the countlessinterviews and discussions.
I would also like to thank EUROCONTROL Experimental
Centre and FRAPORT Foundation ‘Erich Becker’ for theirfinancial support.

CONCLUSIONThe CWA has confirmed its usefullness for application to
the A-CDM work system for several reasons: via an ADS it
allows to derive domain constraints and operational
information requirements of pilots which could be verified by
the results of a cockpit survey. This encourages its further
application to identify also information requirements of otherparticipating actors. It cannot be claimed that the ADS is able
to cover all sytem constraints, however evidence could begiven that a numerous operational information which arerequired by pilot are not yet accessible to them.

87

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Matthias Groppe is a doctoral researcher at EUROCONTROL Experimental
Center in Brétigny sur Orge. He earned his master’s degree in Business
Administration at the CityUniversity of London in 2006. In his diploma
project he set out a consulting project for the ground handling company
GlobeGround to improve operational procedures at Berlin Tegel airport. The
PhD research project is supported by FRAPORT foundation ‘Erich Becker’
and EUROCONTROL Experimental Centre. Matthias Groppe is employed at
Lufthansa CityLine as a pilot on regional operation, CST Simulator Centre
Berlin as training consultant and works as examiner for the German Aviation
Authority LBA in Braunschweig.
Romano Pagliari obtained a master’s degree in transport and a PhD in airport
slot allocation from the Cranfield University School of Management. He
presently lectures on airport economics and business issues in addition toorganising various airport management short course / CPD programmes. His
research interests include airport economics and business development and airtransport issues that affect remoter regions. Dr Pagliari is currently Director of
the MSc in Airport Planning and Management, a member of the ScientificCommittee of the International Center for Competitiveness Studies in
Aviation and a member of the editiorial board of the Journal of Airport
Management.
Don Harris is Course Director for the MSc in Ergonomics and Safety at
Work and is the Director of both the Flight Deck Design and Aviation Safety
Group and of the Defence Human Factors Group. Dr Harris is currently
investigating the design requirements for a single crew operated commercial
aircraft and is involved in research addressing several aspects of Defence
Human Factors, but in particular the use of Serious Games to improve
decision making.

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