Lean, green and resilient practices influence on supply chain performance: interpretive structural modeling approach

被引:196
|
作者
Govindan, K. [1 ]
Azevedo, S. G. [2 ]
Carvalho, H. [3 ]
Cruz-Machado, V. [3 ]
机构
[1] Univ Southern Denmark, Dept Econ & Business, Odense, Denmark
[2] Univ Beira Interior, Dept Econ & Business, P-6200209 Covilha, Portugal
[3] Univ Nova Lisboa, Fac Ciencias & Tecnol, Dept Engn Mecan & Ind, UNIDEMI, P-2829516 Caparica, Portugal
关键词
Lean; Green; Resilient; Supply chain performance; Interpretive structural modeling; Automotive supply chain; TOTAL QUALITY MANAGEMENT; JUST-IN-TIME; AUTOMOTIVE INDUSTRY; IMPLEMENTATION; EDUCATION; SYSTEM; IMPACT; INDEX; AGILE; ISM;
D O I
10.1007/s13762-013-0409-7
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:15 / 34
页数:20
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