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

Alexander May, Adrian Anslow, Yue Wu, Udechukwu Ojiako*, Max Chipulu, Alasdair Marshall

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)108-113
Number of pages6
JournalSupply Chain Management
Volume19
Issue number1
DOIs
Publication statusPublished - 7 Feb 2014

Keywords

  • air cargo
  • fuzzy multi-criteria decision
  • KPIs
  • logistics
  • modelling
  • revenue management
  • operational data
  • performance measures

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