Adaptations in SCOR based performance metrics of airline catering supply chain during COVID-19 pandemic

Dhaarsan Rajaratnam, Funlade Sunmola

Abstract


Purpose: There is the propensity of the Airline catering supply chain to adapt their performance measures in order to meet desired service level due to the challenges of the Covid-19 pandemic. The aim of this paper is to develop a set of metrics for airline catering organization and explore the choices of SCOR based performance metrics during the Covid-19 pandemic.

Design/methodology/approach: The SCOR framework is applied in the context of the airline catering supply chain to develop performance metrics. In this case study, the performance metrics model is analysed and validated by experts. Then, metrics are prioritised using MoSCoW method based on the experience of the Covid-19 challenges.

Findings: A hierarchical performance measure framework is proposed, and a set of 55 metrics is identified. The validation of these metrics recognises the initial work. With the prioritisation, 13 level-2 & level-3 metrics are considered necessary in addition to 7 level-1 metrics to mitigate Covid-19 pandemic challenges better.    

Research limitations/implications: This research is based on a single case study. The validation is restricted to a small sample size.

Practical implications: With the development of performance metrics and prioritization, airline catering organisation able to monitor their catering logistics performance.

Originality/value: The work contributes to the measurement of performance in airline catering logistics, and adapted metrics would help business to be more responsive and flexible as per the market changes to alleviate Covid-19 challenges.

 

Keywords


Airline Catering Supply Chian, SCOR, Performance Metrics, MoSCoW

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DOI: https://doi.org/10.3926/jiem.3592


Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Journal of Industrial Engineering and Management, 2008-2024

Online ISSN: 2013-0953; Print ISSN: 2013-8423; Online DL: B-28744-2008

Publisher: OmniaScience