Issue |
RAIRO-Oper. Res.
Volume 56, Number 5, September-October 2022
|
|
---|---|---|
Page(s) | 3405 - 3428 | |
DOI | https://doi.org/10.1051/ro/2022149 | |
Published online | 26 September 2022 |
Evolutionary game study on information nodes setting in supply chain tracing based on compensation mechanism
School of Economics and Management, Southeast University, No. 2 Sipailou, Nanjing 210096, P.R. China
* Corresponding author: ldzhao@seu.edu.cn
Received:
6
September
2021
Accepted:
23
August
2022
Consumption compensation is the driving force for motivating each supply chain link to set up information nodes, which is of great significance for promoting informatization, modernization, transformation, and upgrading of the supply chain system. This study simulates the evolution process of strategic selection for each supply chain link to set information nodes independently or collectively under the unconstrained government rewards conditions and punishments. The main conclusions are as follows: (1) When each link in the supply chain provides source tracing information independently, the vendor chooses to set up information nodes for the links with large information cost compensation coefficients. (2) When the vendor provides source tracing information cooperatively if the collaborative benefit is less than the cooperation cost, the information node will be set to the link with the large compensation coefficient. If not, information nodes will be set in each link. (3) Under the government incentive mechanism, enterprises are willing to cooperate. The punishment mechanism helps avoid situations where neither side sets up information nodes. The compensation coefficient is a prerequisite for mechanisms to work.
Mathematics Subject Classification: 90B50 / 91A80
Key words: Compensation mechanism / cooperation mechanism / government reward and punishment / traceability information / evolutionary game
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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