Tseng, M.-L., Tan, K.-H., Lim, M. K. , Lin, R.-J. and Geng, Y. (2014) Benchmarking eco-efficiency in green supply chain practices in uncertainty. Production Planning and Control, 25(13-14), pp. 1079-1090. (doi: 10.1080/09537287.2013.808837)
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Abstract
Benchmarking has not received much attention in the eco-efficiency literature because of the lack of an appropriate methodology to aid the electronic production process in green supply chain (GSC) practices. This study fills this analytical gap and suggests a rigorous quantitative approach for benchmarking eco-efficiency. However, there are qualitative and quantitative approaches to the eco-efficient criteria. Hence, this study undertakes fuzzy set theory within reference model (known as TODIM), a method that allows users to assess both qualitative and quantitative data together. This study is to aid traditional benchmarking activities and to provide guidance to practitioners and an example of a largest smart phone manufacturer across the globe to demonstrate the proposed technique with appropriate result to benchmark the eco-efficiency in GSC under uncertainty. TODIM is useful for identifying the best performing units against which to be benchmarked as well as for providing actionable measures for improvement of a firm’s performance. This study compares gain and loss functions as benchmarking tools in GSC practices. Implications for managers and directions for future research are discussed.
| Item Type: | Articles |
|---|---|
| Additional Information: | This study is supported by National Science Council, Taiwan (NSC 101-2410-H-262 -004 -). In addition, this study was partially supported by the Natural Science Foundation of China (71033004), the Chinese Academy of Sciences (2008–318), and the Ministry of Science and Technology (2011BAJ06B01). |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Lim, Professor Ming |
| Authors: | Tseng, M.-L., Tan, K.-H., Lim, M. K., Lin, R.-J., and Geng, Y. |
| College/School: | College of Social Sciences > Adam Smith Business School > Management |
| Journal Name: | Production Planning and Control |
| Publisher: | Taylor & Francis |
| ISSN: | 0953-7287 |
| ISSN (Online): | 1366-5871 |
| Published Online: | 21 June 2013 |
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