Abstract
This paper argues for the use of Total Interpretive Structural Modeling (TISM) in sustainable supply chain management (SSCM). The literature has identified antecedents and drivers for the adoption of SSCM. However, there is relatively little research on methodological approaches and techniques that take into account the dynamic nature of SSCM and bridge the existing quantitative/qualitative divide. To address this gap, this paper firstly systematically reviews the literature on SSCM drivers; secondly, it argues for the use of alternative methods research to address questions related to SSCM drivers; and thirdly, it proposes and illustrates the use of TISM and Cross Impact Matrix-multiplication applied to classification (MICMAC) analysis to test a framework that extrapolates SSCM drivers and their relationships. The framework depicts how drivers are distributed in various levels and how a particular driver influences the other through transitive links. The paper concludes with limitations and further research directions.
DOI
10.1016/j.jclepro.2016.03.117
Publication Date
2017-01-20
Publication Title
Journal of Cleaner Production
Volume
142
Issue
2
First Page
1119
Last Page
1130
ISSN
0959-6526
Embargo Period
2017-04-12
Organisational Unit
Plymouth Business School
Recommended Citation
Dubey, R., Gunasekaran, A., Papadopoulos, T., Childe, S., Shibin, K., & Fosso, W. (2017) 'Sustainable supply chain management: framework and further research directions', Journal of Cleaner Production, 142(2), pp. 1119-1130. Available at: https://doi.org/10.1016/j.jclepro.2016.03.117
