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Prioritisation of performance indicators in air cargo demand management: an insight from industry

Alexander May (School of Management, University of Southampton, Southampton, UK)
Adrian Anslow (Cargo Systems Development, Virgin Atlantic Airways Ltd, Crawley, UK)
Yue Wu (University of Southampton, Southampton, UK)
Udechukwu Ojiako (Faculty of Management, University of Johannesburg, Johannesburg, South Africa)
Max Chipulu (School of Management, University of Southampton, Southampton, UK)
Alasdair Marshall (Southampton Management School, University of Southampton, Southampton, UK)

Supply Chain Management

ISSN: 1359-8546

Article publication date: 7 January 2014

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Abstract

Purpose

Real operational data are used to optimise the performance measurement of air cargo capacity demand management at Virgin Atlantic Cargo by identifying the best KPIs from the range of outcome-based KPIs in current use.

Design/methodology/approach

Intelligent fuzzy multi-criteria methods are used to generate a ranking order of key outcome-based performance indicators. More specifically, KPIs used by Virgin Atlantic Cargo are evaluated by experts against various output criteria. Intelligent fuzzy multi-criteria group making decision-making methodology is then applied to produce rankings.

Findings

A useful ranking order emerges from the study albeit with the important limitation that the paper looked solely at indices focussing exclusively on outcomes while ignoring behavioural complexity in the production of outcomes.

Originality/value

This paper offers a practical overview of the development of performance measures useful for air cargo capacity demand management.

Keywords

Acknowledgements

Received 9 May 2012 Revised 21 September 2012 27 May 2013 18 June 2013 26 June 2013 10 July 2013 2 October 2013 Accepted 9 October 2013

Citation

May, A., Anslow, A., Wu, Y., Ojiako, U., Chipulu, M. and Marshall, A. (2014), "Prioritisation of performance indicators in air cargo demand management: an insight from industry", Supply Chain Management, Vol. 19 No. 1, pp. 108-113. https://doi.org/10.1108/SCM-07-2013-0230

Publisher

:

Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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