EconPapers    
Economics at your fingertips  
 

Analysis of sustainable supply chain management enablers and their benefits realised to business organisations

Pankaj C. Shete, Zulfiquar N. Ansari and Ravi Kant

International Journal of Business Performance and Supply Chain Modelling, 2021, vol. 12, issue 2, 85-115

Abstract: The objective of this study is to identify and analyse the sustainable supply chain management (SSCM) benefits realised due to adoption of SSCM enablers. A hybrid modified step-wise weight assessment ratio analysis (SWARA) - weighted aggregated sum product assessment (WASPAS) approach has been adopted in this research work for the analysis. Modified SWARA is used to determine the relative importance of SSCM enablers while WASPAS method is used to prioritise the benefits. The findings of the study reveal that more attention should be on the adoption of environmental and regulatory enablers for effectiveness in SSCM implementation. It is also found that improved ability of 6R practices is a highly realised benefit due to the adoption of SSCM enablers. This research will help decision makers to effectively implement sustainability in their business organisation by developing a strategic action plan at the initial stage of SSCM implementation.

Keywords: sustainable supply chain management; SSCM; enabler; benefits; step-wise assessment ratio analysis; SWARA; weighted aggregated sum product assessment; WASPAS. (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=116206 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbpsc:v:12:y:2021:i:2:p:85-115

Access Statistics for this article

More articles in International Journal of Business Performance and Supply Chain Modelling from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijbpsc:v:12:y:2021:i:2:p:85-115