Optimisation of key performance measures in air cargo demand management

This article sought to facilitate the optimisation of key performance measures utilised for demand management in air cargo operations. The focus was on the Revenue Management team at Virgin Atlantic Cargo and a fuzzy group decision-making method was used. Utilising intelligent fuzzy multi-criteria m...

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Main Authors: Alexander May, Adrian Anslow, Udechukwu Ojiako, Yue Wu, Alasdair Marshall, Maxwell Chipulu
Format: Article
Language:English
Published: AOSIS 2014-04-01
Series:Journal of Transport and Supply Chain Management
Subjects:
Online Access:https://jtscm.co.za/index.php/jtscm/article/view/125
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spelling doaj-a8f86d4225384ebdbe403f91f22e63292020-11-24T22:55:24ZengAOSISJournal of Transport and Supply Chain Management2310-87891995-52352014-04-0181e1e910.4102/jtscm.v8i1.125107Optimisation of key performance measures in air cargo demand managementAlexander May0Adrian Anslow1Udechukwu Ojiako2Yue Wu3Alasdair Marshall4Maxwell Chipulu5School of Management, University of SouthamptonRevenue Management and Pricing Analytics, Virgin Atlantic CargoFaculty of Management, University of JohannesburgSchool of Management, University of SouthamptonSchool of Management, University of SouthamptonSchool of Management, University of Southampton, United Kingdom and Faculty of Management, University of Johannesburg, South AfricaThis article sought to facilitate the optimisation of key performance measures utilised for demand management in air cargo operations. The focus was on the Revenue Management team at Virgin Atlantic Cargo and a fuzzy group decision-making method was used. Utilising intelligent fuzzy multi-criteria methods, the authors generated a ranking order of ten key outcome-based performance indicators for Virgin Atlantic air cargo Revenue Management. The result of this industry-driven study showed that for Air Cargo Revenue Management, ‘Network Optimisation’ represents a critical outcome-based performance indicator. This collaborative study contributes to existing logistics management literature, especially in the area of Revenue Management, and it seeks to enhance Revenue Management practice. It also provides a platform for Air Cargo operators seeking to improve reliability values for their key performance indicators as a means of enhancing operational monitoring power.https://jtscm.co.za/index.php/jtscm/article/view/125OptimisationKey Performance MeasuresDemand ManagementAir Cargo
collection DOAJ
language English
format Article
sources DOAJ
author Alexander May
Adrian Anslow
Udechukwu Ojiako
Yue Wu
Alasdair Marshall
Maxwell Chipulu
spellingShingle Alexander May
Adrian Anslow
Udechukwu Ojiako
Yue Wu
Alasdair Marshall
Maxwell Chipulu
Optimisation of key performance measures in air cargo demand management
Journal of Transport and Supply Chain Management
Optimisation
Key Performance Measures
Demand Management
Air Cargo
author_facet Alexander May
Adrian Anslow
Udechukwu Ojiako
Yue Wu
Alasdair Marshall
Maxwell Chipulu
author_sort Alexander May
title Optimisation of key performance measures in air cargo demand management
title_short Optimisation of key performance measures in air cargo demand management
title_full Optimisation of key performance measures in air cargo demand management
title_fullStr Optimisation of key performance measures in air cargo demand management
title_full_unstemmed Optimisation of key performance measures in air cargo demand management
title_sort optimisation of key performance measures in air cargo demand management
publisher AOSIS
series Journal of Transport and Supply Chain Management
issn 2310-8789
1995-5235
publishDate 2014-04-01
description This article sought to facilitate the optimisation of key performance measures utilised for demand management in air cargo operations. The focus was on the Revenue Management team at Virgin Atlantic Cargo and a fuzzy group decision-making method was used. Utilising intelligent fuzzy multi-criteria methods, the authors generated a ranking order of ten key outcome-based performance indicators for Virgin Atlantic air cargo Revenue Management. The result of this industry-driven study showed that for Air Cargo Revenue Management, ‘Network Optimisation’ represents a critical outcome-based performance indicator. This collaborative study contributes to existing logistics management literature, especially in the area of Revenue Management, and it seeks to enhance Revenue Management practice. It also provides a platform for Air Cargo operators seeking to improve reliability values for their key performance indicators as a means of enhancing operational monitoring power.
topic Optimisation
Key Performance Measures
Demand Management
Air Cargo
url https://jtscm.co.za/index.php/jtscm/article/view/125
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