Interpretive structural modelling approach to evaluate knowledge sharing enablers in circular supply chain: A study of the Indian manufacturing sector

Ganguly, Anirban and Farr, John V. (2024) Interpretive structural modelling approach to evaluate knowledge sharing enablers in circular supply chain: A study of the Indian manufacturing sector. Journal of Information & Knowledge Management. ISSN 0219-6492 (In Press)

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Abstract

Knowledge sharing can be considered an important activity to improve the performance among various entities of a supply chain. The purpose of this study is to identify and evaluate a set of critical knowledge-sharing enablers that might aid in successfully managing a circular supply chain (CSC) in the context of the Indian manufacturing sector. The knowledge-sharing enablers were determined through a review of the extant literature, coupled with discussion with subject matter experts (SMEs). The quantitative technique of interpretive structural modelling (ISM) was used to analyse the identified knowledge-sharing enablers. The findings of this study revealed that the knowledge-sharing capabilities of an organisation, organisation structure and support from the top management formed the most significant enablers for Indian manufacturing organisations. This study has significant managerial and academic contributions. While supply chain managers can use the findings of this study to gain a better understanding of the role of knowledge sharing in managing CSC in the Indian manufacturing context, policymakers can use these findings to formulate strategies for effectively managing the CSC, as well as improving its operational effectiveness. The findings can also aid academic researchers to further analyse the role that knowledge sharing might play in successfully managing CSC, including other industries (for example, service industries), as well as other geographical regions.

Item Type: Article
Keywords: Circular supply chain | Circular supply chain management | Knowledge sharing | Interpretive structural modelling | Knowledge sharing enablers | Manufacturing sector | India
Subjects: Social Sciences and humanities > Business, Management and Accounting > Management of Technology and Innovation
Physical, Life and Health Sciences > Computer Science
JGU School/Centre: Jindal Global Business School
Depositing User: Subhajit Bhattacharjee
Date Deposited: 01 Jul 2024 06:28
Last Modified: 01 Jul 2024 06:28
Official URL: https://doi.org/10.1142/S021964922450076X
URI: https://pure.jgu.edu.in/id/eprint/8020

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