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Green Supplier Selection Mechanism Based on Information Environment of Z-Numbers

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Abstract

In the green procurement management of firms, by rigorously evaluating and selecting suppliers, firms can effectively reduce the operation risk and improve the sustainable value-added capacity of supply chain. This paper designs a novel green supplier selection mechanism based on an uncertain information environment. First, a new green supplier evaluation index system is designed by considering the economic, environmental, and social drivers from the perspective of sustainable development. Then, the Z-numbers are applied to describe the fuzziness degree of the decision information and the reliability degree of the fuzzy attribute values. We re-define the possibility degree of trapezoidal fuzzy numbers, and on that basis, we define the possibility degree of Z-numbers. A ranking method based on the possibility degree of Z-numbers is applied to select the green suppliers. Finally, the implementation, applicability, and feasibility of the proposed mechanism are highlighted by providing a decision-making example of green supply selection together with the comparison analysis with the existing methods. From the comparison analysis and discussion, the information processing method in our proposed mechanism can effectively avoid the information loss caused by the direct aggregation of fuzzy information, which shows that the proposed mechanism is more feasible and effective than other congeneric methods. The results suggest that the proposed mechanism of green supplier selection can handle multi-attribute decision-making problems in an uncertain cognitive information environment with Z-numbers, consistent with human cognition.

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Funding

This work is supported by the National Natural Science Foundation of China (nos. 72071150, 71671135, 71871174).

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Authors and Affiliations

  1. School of Science, Wuhan University of Technology, Wuhan, 430070, People’s Republic of China

    Congjun Rao & Xinping Xiao

  2. School of Information Management, Central China Normal University, Wuhan, 430079, People’s Republic of China

    Mingyun Gao

  3. NUS Business School & The Logistics Institute-Asia Pacific, National University of Singapore, Singapore, 119623, Singapore

    Mark Goh

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  1. Congjun Rao
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Correspondence to Mingyun Gao.

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Rao, C., Gao, M., Goh, M. et al. Green Supplier Selection Mechanism Based on Information Environment of Z-Numbers. Cogn Comput 15, 520–533 (2023). https://doi.org/10.1007/s12559-022-10055-x

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