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.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- Environmental Science(all)
- Strategy and Management
- Industrial and Manufacturing Engineering