| Title |
Integrating and extending data and decision tools for sustainable third-party reverse logistics provider selection |
| ID_Doc |
76244 |
| Authors |
Bai, CG; Sarkis, J |
| Title |
Integrating and extending data and decision tools for sustainable third-party reverse logistics provider selection |
| Year |
2019 |
| Published |
|
| DOI |
10.1016/j.cor.2018.06.005 |
| Abstract |
Third-party reverse logistics provider (3PRLP) selection plays an important role in the operation and implemention of reverse logistics or reverse supply chains. Economic and cost based partner relationships are no longer acceptable for 3PRLPs or for organizations that seek to introduce sustainable supply chain management. Recent emphasis on sustainability has made 3PRLP evaluation and selection more complex. In order to advance this area of research and to help further incorporate sustainability into 3PRLPs selection modeling, a novel multi-stage, multi-method, multi-criteria approach is developed. Methodologically, this is the first time that neighborhood rough set (NRS) theory is integrated with TOPSIS and VIKOR techniques. Neighborhood rough set, as a data management and soft computation tool, can help reduce the number of 3PRLP to be evaluated and ranked using TOPSIS combined with VIKOR's compromise conception decision tools. A conceptual application is developed using business, environmental, and social factors within the context of reverse logistics management decisions. A sensitivity analysis evaluating various neighborhood rough set parameters is also introduced to investigate robustness of solutions using the multi-stage methodology. Methodological implications and future research and application directions conclude the paper. (C) 2018 Elsevier Ltd. All rights reserved. |
| Author Keywords |
Reverse logistics; Sustainability; Third-party provider; Neighborhood rough set; TOPSIS; VIKOR; Multiple criteria decision making |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000474309800014 |
| WoS Category |
Computer Science, Interdisciplinary Applications; Engineering, Industrial; Operations Research & Management Science |
| Research Area |
Computer Science; Engineering; Operations Research & Management Science |
| PDF |
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