An environmental uncertainty-based diagnostic reference tool for evaluating the performance of supply chain value streams

Abstract

This research has responded to the need for diagnostic reference tools explicitly linking the influence of environmental uncertainty and performance within the supply chain. Uncertainty is a key factor influencing performance and an important measure of the operating environment. We develop and demonstrate a novel reference methodology based on data envelopment analysis (DEA) for examining the performance of value streams within the supply chain with specific reference to the level of environmental uncertainty they face. In this paper, using real industrial data, 20 product supply value streams within the European automotive industry sector are evaluated. Two are found to be efficient. The peer reference groups for the underperforming value streams are identified and numerical improvement targets are derived. The paper demonstrates how DEA can be used to guide supply chain improvement efforts through role-model identification and target setting, in a way that recognises the multiple dimensions/outcomes of the supply chain process and the influence of its environmental conditions. We have facilitated the contextualisation of environmental uncertainty and its incorporation into a specific diagnostic reference tool.

Publication DOI: https://doi.org/10.1080/09537287.2013.808838
Divisions: Aston Business School > Marketing & Strategy
Aston Business School
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis Group in Production Planning & Control on 25 June 2013, available online at: http://www.tandfonline.com/10.1080/09537287.2013.808838
Uncontrolled Keywords: data envelopment analysis,Diagnostic reference tool,environmental uncertainty,performance measurement,supply chain,Computer Science Applications,Strategy and Management,Management Science and Operations Research,Industrial and Manufacturing Engineering
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.tan ... 287.2013.808838 (Publisher URL)
PURE Output Type: Article
Published Date: 2013-06-25
Published Online Date: 2013-06-25
Authors: Gallear, David
Ghobadian, Abby
Li, Yanhong
Oregan, Nicholas
Childerhouse, Paul
Naim, Mohamed
O'Regan, Nicholas ( 0000-0003-3014-0373)

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