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Developing green supply chain management taxonomy-based decision support system

Kumar, V.; Holt, D.; Ghobadian, A.; Garza-Reyes, J. A.

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Authors

D. Holt

A. Ghobadian

J. A. Garza-Reyes



Abstract

© 2014 Taylor & Francis. The aim of this paper is to develop a comprehensive taxonomy of green supply chain management (GSCM) practices and develop a structural equation modelling-driven decision support system following GSCM taxonomy for managers to provide better understanding of the complex relationship between the external and internal factors and GSCM operational practices. Typology and/or taxonomy play a key role in the development of social science theories. The current taxonomies focus on a single or limited component of the supply chain. Furthermore, they have not been tested using different sample compositions and contexts, yet replication is a prerequisite for developing robust concepts and theories. In this paper, we empirically replicate one such taxonomy extending the original study by (a) developing broad (containing the key components of supply chain) taxonomy; (b) broadening the sample by including a wider range of sectors and organisational size; and (c) broadening the geographic scope of the previous studies. Moreover, we include both objective measures and subjective attitudinal measurements. We use a robust two-stage cluster analysis to develop our GSCM taxonomy. The main finding validates the taxonomy previously proposed and identifies size, attitude and level of environmental risk and impact as key mediators between internal drivers, external drivers and GSCM operational practices.

Citation

Kumar, V., Holt, D., Ghobadian, A., & Garza-Reyes, J. A. (2015). Developing green supply chain management taxonomy-based decision support system. International Journal of Production Research, 53(21), 6372-6389. https://doi.org/10.1080/00207543.2014.917215

Journal Article Type Article
Publication Date Nov 2, 2015
Deposit Date Apr 9, 2015
Publicly Available Date Feb 10, 2016
Journal International Journal of Production Research
Print ISSN 0020-7543
Electronic ISSN 1366-588X
Publisher Taylor & Francis
Peer Reviewed Peer Reviewed
Volume 53
Issue 21
Pages 6372-6389
DOI https://doi.org/10.1080/00207543.2014.917215
Keywords green supply chain management, taxonomy, decision support, environmental attitude, structural equation modelling
Public URL https://uwe-repository.worktribe.com/output/842845
Publisher URL http://dx.doi.org/10.1080/00207543.2014.917215
Additional Information Additional Information : This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 21 May 2014, available online: http://wwww.tandfonline.com/10.1080/00207543.2014.917215

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