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Collaborative Measures: Challenges in Airport Operations
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.), Industrial Management.
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Over the last 20 years, internal use of Performance Management(PM) within organizations has become much more complex in terms measurement techniques and approaches as well as their deployment within different organizational structures. In contrast to the traditional use of PM as an intra-organizational system, the emergence of networked operations, has extended organizational boundaries of Performance Management System (PMS) to new operational settings where actors often deal with a challenge of Collaborative Measures. Consequently, there is a significant lack of feedback and feedforward reporting mechanisms. This raises an important question for Performance Measurement & Management (PMM) literature. How do actors manage operations through inter- organizational performance measures? Hence, the purpose of this thesis is to investigate the management of collaborative measures in a quest to attain better operational performance for inter- organizational PM.

The thesis builds on four studies investigating a collaborative PMS for capacity enhancements in airport operations. Due to their operational complexity and highly networked subsystems, airport operations provided a fitting empirical scene for studying PM that transcends organizational boundaries. Within the context of this thesis, airports are viewed as a System of System (SoS), and inter- organizational PM is investigated with the dimensions Organizational Complexity, Continuous Improvement and Social system. The studies use a multimethod approach, including longitudinal action research, multiple-case study, Systematic Literature Review (SLR), Classification and Regression Tree method (CART) and Artificial Neural Network (ANN) Method.

The findings show that that (1) inter- organizational performance is affected by intrinsic Performance Measurement Complexity (PMC) which aggregates as interactive complexity with many actors. (2) The challenge of feedback and feedforward mechanisms as a dual control for collaborative performance is analysed with four cybernetic functions: sensor, commander, actuator and process. (3) The concept of Reflective Performance Measurement System (RPMS) is introduced with general conditions to facilitate collaborative decision-making within such platforms.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2017. , 76 p.
Series
TRITA-IEO, ISSN 1100-7982 ; 7
Keyword [en]
Performance Measurement, Airport Operations, Collaboration Decision Making
National Category
Business Administration
Research subject
Industrial Economics and Management; Planning and Decision Analysis; Transport Science; Industrial Information and Control Systems
Identifiers
URN: urn:nbn:se:kth:diva-207780ISBN: 978-91-7729-331-6 (print)OAI: oai:DiVA.org:kth-207780DiVA: diva2:1098284
Public defence
2017-06-14, F3, Lindstedtsvägen 26, Stockholm, 09:00 (English)
Opponent
Supervisors
Projects
MASCA- Managing System Change in Aviation
Note

This research was conducted within the framework of the European Doctorate in Industrial Management—EDIM, which is funded by the Education, Audiovisual and Culture Executive Agency (EACEA) of the European Commission. QC 20170524

Available from: 2017-05-24 Created: 2017-05-23 Last updated: 2017-06-07Bibliographically approved
List of papers
1. Preparing for Airport Collaborative Decision Making (A-CDM) implementation: an evaluation and recommendations
Open this publication in new window or tab >>Preparing for Airport Collaborative Decision Making (A-CDM) implementation: an evaluation and recommendations
Show others...
2015 (English)In: Cognition, Technology & Work, ISSN 1435-5558, E-ISSN 1435-5566, Vol. 17, no 2, 207-218 p.Article in journal (Refereed) Published
Abstract [en]

The key objective of this paper was to report on one of the industrial-based change case studies of the MASCA project (MAnaging System Change in Aviation-EU FP7, 2010-2013 ). This case study provides a systematic insight into one airport's approach to their preparation for full implementation of Airport Collaborative Decision Making (A-CDM). An action-based methodological approach was applied over a 3-year period, and a particular focus of this paper is on the application of the MASCA system change and operational evaluation tool (SCOPE/Structured Enquiry). Key recommendations resulted in research-led interventions, such as the development of a Serious Game to facilitate co-ordination and communications. The paper also reports on future recommendations for the implementation of A-CDM, such as prioritising social relations and trust building amongst airport stakeholders as opposed to viewing A-CDM solely as an IT-led project. Recommendations and learning from this case study can also be disseminated to other airports who are about to embark on the preparation for full A-CDM implementation and compliance.

Place, publisher, year, edition, pages
Springer, 2015
Keyword
MASCA, Implementing change, Airport Collaborative Decision Making, Multi-stakeholder collaborations
National Category
Other Engineering and Technologies
Identifiers
urn:nbn:se:kth:diva-171671 (URN)10.1007/s10111-014-0295-x (DOI)000353465700009 ()2-s2.0-84939957242 (Scopus ID)
Note

QC 20150812

Available from: 2015-08-12 Created: 2015-08-05 Last updated: 2017-05-29Bibliographically approved
2. Sources of Complexity within a System of System: Implications for Performance Management
Open this publication in new window or tab >>Sources of Complexity within a System of System: Implications for Performance Management
2014 (English)In: EurOMA Conference, Palermo, Italy, 20- 25 June 2014, 2014Conference paper, Abstract (Refereed)
Abstract [en]

The purpose of this paper is to identify factors that induce complexity in the airport Turn-Around Process (TAP) so as to understand implications for Perfromance Measurement and Management (PMM). The study is addressed as an inductive/exploratory case study. The unit of analysis is the Turn-Around Process at a major Swedish airport. Data is obtained from conducting twenty-three semi-structured interviews. In addition, participant observations during eight months were conducted. As a result, three implications for PMM are identified as (i) organizational complexity, (ii) Continious improvement, (iii) social system. The findings support the challenge of managing interoperability within complex multi-stakeholder settings. The value of this study is that it enhances our understanding on how inter- organizational performance can be examined and hence managed

Keyword
Airport services, Turnaround Process, Perfromance Measurement.
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:kth:diva-206834 (URN)
Conference
EurOMA Conference, Palermo, Italy, 20- 25 June 2014
Note

An earlier version of this paper was presented at EurOMA Conference, Palermo, Italy, 20- 25 June 2014

QC 20170519

Available from: 2017-05-08 Created: 2017-05-08 Last updated: 2017-06-13Bibliographically approved
3. Performance Measurement Systems: Art and Science: A Perspective from Complexity Theory
Open this publication in new window or tab >>Performance Measurement Systems: Art and Science: A Perspective from Complexity Theory
2016 (English)In: Performance Management Association (PMA) conference, Edinburgh, Scotland 26- 29 June 2016 / [ed] Umit S Bititci , Herriot - Watt University: Professor of Business Performance, 2016Conference paper, Abstract (Refereed)
Abstract [en]

Complexity negatively impacts the process of continually improving Performance Management Systems (PMS). Extant literature in PMS considers complexity to be a result of complex external environments rather than user’s response to it. However, this paper argues that organisations face internal complexity while adopting a PMS. Miscalculations of this complexity increases uncountable costs to organisations. Henceforth, this study adopts a complexity-theory perspective, and explores how organisational controls amplify complexity at the three core process stages of a PMS i.e., design, implementation and use. The paper builds on a Systematic Literature Review, comprising 58 papers, which are analysed in depth using a framework typifying technical and social controls as suggested by Smith and Bititci (2017). Results demonstrate that social and technical controls impact PMS process stages and contribute to complexity of PMS in two ways: First, a lack of clear and concise administration between the balance of objectivity and subjectivity in PMS at each process stage results in social complexity. Second, a range of interacting elements make it difficult to manage PMS and their inter- relationships across the three process stages resulting in technical complexity. The findings reinforce that the interaction of organisational controls in the system is emergent, unintended, unpredictable, and ambiguous in what to measure and how to manage it. In conclusion, this study posits that users’ response to the external environment causes internal Performance Measurement Complexity (PMC). In doing so, this paper highlights the propagation of complexity in six forms i.e. Analytical, Methodological, Technological, Role, Procedural and Task Complexity.

Keyword
Social controls, Technical control, Performance Measurement Complexity
National Category
Business Administration
Research subject
Industrial Economics and Management; Production Engineering; Industrial Information and Control Systems; Planning and Decision Analysis
Identifiers
urn:nbn:se:kth:diva-206831 (URN)
Conference
Performance Management Association (PMA) conference, Edinburgh, Scotland 26- 29 June 2016
Funder
Knut and Alice Wallenberg FoundationEU, European Research Council
Note

This paper was invited for a special issue on PMM- Towards a Theoretical Foundation for Performance Measurement and Management.

QC 20170519

Available from: 2017-05-08 Created: 2017-05-08 Last updated: 2017-05-29Bibliographically approved
4. Managing turnaround performance through Collaborative Decision Making
Open this publication in new window or tab >>Managing turnaround performance through Collaborative Decision Making
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2017 (English)In: Journal of Air Transport Management, ISSN 0969-6997, E-ISSN 1873-2089, Vol. 58, 183-196 p.Article in journal (Refereed) Published
Abstract [en]

The purpose of this paper is to explore turnaround performance as a resultant from both Collaborative Decision Making (CDM) processes and collaborative measures. This paper presents how CDM operates in the Turnaround Process (TAP) to propose a new method for managing the collaborative turnaround performance of all actors by predicting the most critical indicators. To achieve this, data from a CDM airport is used. Sample data of 6500 observations, taken from turnaround movements handled in 2014 at Madrid-Barajas Airport, were obtained from three separate databases and analyzed separately (in three databases). To predict turnaround performance, this paper also introduces a predictor dependent variable called "star values" as a measure of minimal delay conditions in order to predict time performance. The analysis shows that the proposed method unveils a new approach in determining how collaborative performance can be measured in the TAP and the predicted key performance indicators, which shows variations in the predicted CDM indicators. Results challenge managers and policymakers to find which improvements can be enacted for better usage of airport infrastructures and resources for optimum use as well as enhanced TAP. In terms of theory use and extension, the study reveals how CDM is an essential element in the literature on air traffic management.

Place, publisher, year, edition, pages
Elsevier, 2017
Keyword
Collaborative Decision Making, Collaborative measures, Turnaround process, Performance measurement
National Category
Transport Systems and Logistics
Identifiers
urn:nbn:se:kth:diva-199470 (URN)10.1016/j.jairtraman.2016.10.008 (DOI)000389294200019 ()2-s2.0-84995906521 (Scopus ID)
Note

QC 20170123

Available from: 2017-01-23 Created: 2017-01-09 Last updated: 2017-05-29Bibliographically approved
5. Prediction of Airport Infrastructures performance with Collaborative Decision Making: Studies from Barajas Airport
Open this publication in new window or tab >>Prediction of Airport Infrastructures performance with Collaborative Decision Making: Studies from Barajas Airport
2017 (English)Report (Other academic)
Abstract [en]

The purpose of this paper is to explore among many airport infrastructures and resources, what is critical to collaborative Performance Management System (PMS) to cause delays. To achieve this, operational data from Madrid Barajas airport was used. A sample data consisting of 2100 movements recorded in airport turnaround operations was analyzed using a neural network predictive model.  Results show that, aside from Key Performance Indicators (KPIs), airport infrastructures as exogenous factors have an effect on- time performance in turnaround operations with a high degree of relevance. The identified airport infrastructures are stand/gate, size of aircraft, company (Type of airline) and runaway selection.

Keyword
Prediction, airport infrastructures, Multi-actor collaboration, neural network
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Industrial Economics and Management; Planning and Decision Analysis; Transport Science
Identifiers
urn:nbn:se:kth:diva-206832 (URN)
Projects
CDM implementation at Barajas Airport and Benefit study
Funder
EU, European Research Council
Note

QC 20170509

Available from: 2017-05-08 Created: 2017-05-08 Last updated: 2017-05-29Bibliographically approved

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