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International Journal of Environment Science and Technology
Center for Environment and Energy Research and Studies (CEERS)
ISSN: 1735-1472
EISSN: 1735-2630
Vol. 12, No. 1, 2015, pp. 15-34
Bioline Code: st15002
Full paper language: English
Document type: Research Article
Document available free of charge

International Journal of Environment Science and Technology, Vol. 12, No. 1, 2015, pp. 15-34

 en Lean, green and resilient practices influence on supply chain performance: interpretive structural modeling approach
Govindan, K.; Azevedo, S.G.; Carvalho, H. & Cruz-Machado, V.

Abstract

Nowadays, companies are struggling to find an appropriate supply chain strategy to achieve competitiveness. Among the available strategies lean, green and resilient are considered as a new management strategies for the supply chain management to achieve competitiveness. The major issues with theses strategies are the integration and identification of critical issues related to the strategies. This paper aims to identify the critical lean, green and resilient practices on which top management should focus in order to improve the performance of automotive supply chains. The systematic analysis of the lean, green and resilient practices is expected to be of great value for their effective implementation by the automotive companies. The interpretive structural modeling approach is used as a useful methodology to identify inter-relationships among lean, green and resilient practices and supply chain performance and to classify them according to their driving or dependence power. According to this research, the practices with the main driving power are just-in-time (lean practice), flexible transportation (resilient practice) and environmentally friendly packaging (green practice). Customer satisfaction is the performance measure with strong dependence and weak driving power; that is, it is strongly influenced by the other researched variables but does not affect them.

Keywords
Lean; Green; Resilient; Supply chain performance; Interpretive structural modeling; Automotive supply chain

 
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