Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Prediction of Airport Infrastructures performance with Collaborative Decision Making: Studies from Barajas Airport
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.), Industrial Management.
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.

Place, publisher, year, edition, pages
2017.
Keyword [en]
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: urn:nbn:se:kth:diva-206832OAI: oai:DiVA.org:kth-206832DiVA: diva2:1094011
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
In thesis
1. Collaborative Measures: Challenges in Airport Operations
Open this publication in new window or tab >>Collaborative Measures: Challenges in Airport Operations
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
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:nbn:se:kth:diva-207780 (URN)978-91-7729-331-6 (ISBN)
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

Open Access in DiVA

No full text

Search in DiVA

By author/editor
Okwir, Simon
By organisation
Industrial Management
Production Engineering, Human Work Science and Ergonomics

Search outside of DiVA

GoogleGoogle Scholar

Total: 27 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf