| Title |
A supply chain sourcing model at the interface of operations and sustainability |
| ID_Doc |
75802 |
| Authors |
Li, G; Xia, Y |
| Title |
A supply chain sourcing model at the interface of operations and sustainability |
| Year |
2023 |
| Published |
Iise Transactions, 55, 8 |
| DOI |
10.1080/24725854.2022.2111481 |
| Abstract |
In this article, we develop a supply chain sourcing model that incorporates both sustainability and operational performance measures. The model selects suppliers and determines sustainability investments and order allocations among the selected suppliers. High sustainability performance, as well as cost efficiency, is achieved while a high operational performance level is maintained. We formulate the problem as a nonlinear bi-objective integer-programming model, discover the model's special features, and propose an effective and computationally efficient algorithm to solve it. To quantify a supply chain's sustainability performance, we adopt the Environmental, Social, and Governance index. Instead of searching for just one sourcing solution, we find the Pareto-optimal set of effective solutions. Numerical tests verify that our algorithm outperforms an existing sourcing algorithm in terms of computational efficiency. A simulation of Apple's sourcing decisions demonstrates the effectiveness of the model in business practice. Our work also provides managerial insights on how sustainable operations alter traditional supply chain sourcing decisions. It helps practitioners make fast and effective sourcing and investment decisions to implement their sustainability strategies at the operational level. |
| Author Keywords |
Supply chain management; sustainability; nonlinear bi-objective model; sourcing plan; Pareto optimal |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000852200300001 |
| WoS Category |
Engineering, Industrial; Operations Research & Management Science |
| Research Area |
Engineering; Operations Research & Management Science |
| PDF |
|