An ISM approach for the barrier analysis in implementing green supply chain management

K. Mathiyazhagan, Kannan Govindan, A. NoorulHaq, Y. Geng

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

As customers are becoming more environmental conscious and governments are making stricter environmental regulations, the industries need to reduce the environmental impact of their supply chain. Indian auto component manufacturing industries especially SMEs (Small and Medium Enterprises) are focused to cleaner production by implementing Green Supply Chain Management (GSCM) in their industries. But they are struggling to implement GSCM concept. The present research analyzes the barriers for the implementation of GSCM concept which has been divided into two phases such as identification of barriers and qualitative analysis. The study has used three different research phases: identification of barriers from the literature, interviews with various department managers and a survey of auto component manufacturing industries. The identification phase led to the selection of twenty-six barriers based on literature and in consultation with industrial experts and academicians. The Interpretive Structural Modeling (ISM) qualitative analysis was used to understand the mutual influences amongst the twenty-six barriers by survey. This study seeks to identify which barrier is acting as the most dominant one for the adoption of green supply chain management and this result is helpful for industries to make easier the adoption of green concept in their supply chain by removing the dominant barrier. It indicates that different Indian auto component manufacturing industries have differing barriers for the implementation of green supply chain management. However, in their GSCM implementation, especially for maintaining the environmental awareness, the supplier barrier is the dominant one. Finally the approach has been applied to ten auto components manufacturing industries in Tamilnadu, South India.
Original languageEnglish
JournalJournal of Cleaner Production
Volume47
Pages (from-to)283-297
ISSN0959-6526
DOIs
Publication statusPublished - 2013

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