| Title | Partner selection in sustainable supply chains: A fuzzy ensemble learning model |
|---|---|
| ID_Doc | 74336 |
| Authors | Wu, C; Lin, CL; Barnes, D; Zhang, Y |
| Title | Partner selection in sustainable supply chains: A fuzzy ensemble learning model |
| Year | 2020 |
| Published | |
| Abstract | With the increasing demands on businesses to operate more sustainably, firms must ensure that the performance of their whole supply chain in sustainability is optimized. Because partner selection is critical to supply chain management, focal firms now need to select supply chains partners that can offer a high level of competence in sustainability. This paper proposes a novel multi-partner classification model for the partner qualification and classification process, combining ensemble learning technology and fuzzy set theory. The proposed model enables potential partners to be classified into one of four categories (strategic partner, preference partner, leverage partner and routine partner), thereby allowing distinctive partner management strategies to be applied for each category. The model provides for the simultaneous optimization of both efficiency in its use of multi-partner and multi-dimension evaluation data, and effectiveness in dealing with the vagueness and uncertainty of linguistic commentary data, in the partner evaluation process. Compared to more conventional methods, the proposed model has the advantage of offering a simple classification and a stable prediction performance. The practical efficacy of the model is illustrated by an application in a listed electronic equipment and instrument manufacturing company based in southeastern China. (C) 2020 Elsevier Ltd. All rights reserved. |
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