Performance Management of Supply Chain Sustainability in Small and Medium-sized Enterprises Using a Combined Structural Equation Modelling and Data Envelopment Analysis


Although the contribution of small and medium-sized enterprises (SMEs) to economic growth is beyond doubt, they collectively affect the environment and society negatively. As SMEs have to perform in a very competitive environment, they often find it difficult to achieve their environmental and social targets. Therefore, making SMEs sustainable is one of the most daunting tasks for both policy makers and SME owners/managers alike. Prior research argues that through measuring SMEs’ supply chain sustainability performance and deriving means of improvement one can make SMEs’ business more viable, not only from an economic perspective, but also from the environmental and social point of view. Prior studies apply data envelopment analysis (DEA) for measuring the performance of groups of SMEs using multiple criteria (inputs and outputs) by segregating efficient and inefficient SMEs and suggesting improvement measures for each inefficient SME through benchmarking it against the most successful one. However, DEA is limited to recommending means of improvement solely for inefficient SMEs. To bridge this gap, the use of structural equation modelling (SEM) enables developing relationships between the criteria and sub-criteria for sustainability performance measurement that facilitates to identify improvement measures for every SME within a region through a statistical modelling approach. As SEM suggests improvements not from the perspective of individual SMEs but for the totality of SMEs involved, this tool is more suitable for policy makers than for individual company owners/managers. However, a performance measurement heuristic that combines DEA and SEM could make use of the best of each technique, and thereby could be the most appropriate tool for both policy makers and individual SME owners/managers. Additionally, SEM results can be utilized by DEA as inputs and outputs for more effective and robust results since the latter are based on more objective measurements. Although DEA and SEM have been applied separately to study the sustainability of organisations, according to the authors’ knowledge, there is no published research that has combined both the methods for sustainable supply chain performance measurement. The framework proposed in the present study has been applied in two different geographical locations—Normandy in France and Midlands in the UK—to demonstrate the effectiveness of sustainable supply chain performance measurement using the combined DEA and SEM approach. Additionally, the state of the companies’ sustainability in both regions is revealed with a number of comparative analyses.

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Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School > Aston India Foundation for Applied Research
College of Business and Social Sciences > Aston Business School
Additional Information: © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Funding: H2020 Marie Skłodowska-Curie Actions
Uncontrolled Keywords: Benchmarking,DEA,Performance measurement,SEM,SMEs,Supply chain,Sustainability,Economics, Econometrics and Finance (miscellaneous),Computer Science Applications
Publication ISSN: 1572-9974
Last Modified: 09 Jul 2024 07:06
Date Deposited: 19 Nov 2019 15:24
Full Text Link:
Related URLs: https://link.sp ... 614-019-09948-1 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2021-10
Published Online Date: 2019-11-18
Accepted Date: 2019-11-06
Authors: Dey, Prasanta (ORCID Profile 0000-0002-9984-5374)
Yang, Guo-Liang
Malesios, Chrysovalantis (ORCID Profile 0000-0003-0378-3939)
De, Debashree
Evangelinos, K. I.



Version: Published Version

License: Creative Commons Attribution

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