Comparisons of sustainable supply chain management practices in the automotive sector

Deepak Mathivathanan and A. Noorul Haq

International Journal of Business Performance and Supply Chain Modelling, 2017, vol. 9, issue 1, 18-27

Abstract: Sustainable supply chain management (SSCM) has gained huge attractions in the past decade in both academia and industries. Many developing countries have difficulty in adapting to emerging market trends and realise the need to shift towards sustainable supply chains. Yet SSCM related issues have not been investigated enough regarding different geographical areas. This paper compares SSCM practices focusing on differences in their adoption in differently developed environments. This study attempts to find where differences occur and why they prevail using statistical tools with input from industrial experts in relevant fields. The statistical analysis proved that the geographies are a main reason behind the pattern of adoption of practices due to differences in the scale of industrial development between the compared landscapes. It is found that industries in developed geographical locations find it easier to adopt SSCM practices than those in the developing and under developed geographies.

Keywords: sustainable supply chain management; SSCM; SSCM practices; empirical analysis; comparison. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.inderscience.com/link.php?id=83884 (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:9:y:2017:i:1:p:18-27

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 ().