Journal of Applied Science and Engineering

Published by Tamkang University Press


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Gengjun GaoThis email address is being protected from spambots. You need JavaScript enabled to view it. and Xu Liu

Institute of Logistics Science and Engineering, Shanghai Maritime University


Received: September 15, 2022
Accepted: October 3, 2022
Publication Date: October 28, 2022

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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In order to explore the income distribution of SME supply chain members under different dominant powers, this paper constructs an evolutionary game model to analyze the optimal decision of the three-level supply chain composed of product manufacturer, third-party logistics enterprise and retailer. The results show that the profit of supply chain under decentralized decision is lower than that under centralized decision. Therefore, by designing a revenue-sharing contract mechanism, the profit of supply chain is higher than that of decentralized decision. The win-win situation of all members of supply chain is realized. The designed revenue sharing contract is flexible, and the profit level depends on the bargaining power of supply chain members.

Keywords: SME; supply chain; evolutionary game model; decentralized decision


  1. [1] M. Matsuda, T. Nishi, M. Hasegawa, and T. Terunuma. “Construction of a virtual supply chain using enterprise e-catalogues”. In: 93. 2020, 688–693. DOI: 10.1016/j.procir.2020.04.093.
  2. [2] O. Durowoju, H. Chan, and X.Wang, (2020) “Investigation of the Effect of e-Platform Information Security Breaches: A Small and Medium Enterprise Supply Chain Perspective" IEEE Transactions on Engineering Management: DOI: 10.1109/TEM.2020.3008827.
  3. [3] S. Yin, H. Li, A. Laghari, S. Karim, and A. Jumani, (2021) “A Bagging Strategy-Based Kernel Extreme Learning Machine for Complex Network Intrusion Detection" EAI Endorsed Transactions on Scalable Information Systems 8(33): e8. DOI: 10.4108/EAI.6-10-2021.171247.
  4. [4] H. Zhang, P. Li, H. Zheng, and Y. Zhang, (2021) “Impact of carbon tax on enterprise operation and production strategy for low-carbon products in a co-opetition supply chain" Journal of Cleaner Production 287: 125058.DOI: 10.1016/j.jclepro.2020.125058.
  5. [5] H. Saleem, Y. Li, Z. Ali, M. Ayyoub, Y. Wang, and A. Mehreen, (2020) “Big data use and its outcomes in supply chain context: the roles of information sharing and technological innovation" Journal of Enterprise Information Management 34(4): 1121–1143. DOI: 10.1108/JEIM-03-2020-0119.
  6. [6] F. Wu, J. Ma, and Y. Li, (2021) “Complex Fluctuation of Power Price in Dual-Channel and Multienergy Supply Chain Based on Sticky Expectation" International Journal of Bifurcation and Chaos 31(14): 2150206. DOI: 10.1142/S0218127421502060.
  7. [7] D. Xu and Y. Long, (2021) “The role of supply chain integration in the transformation of food manufacturers: a case study from China" International Journal of Logistics Research and Applications 24(2): 198–212. DOI: 10.1080/13675567.2020.1729707.
  8. [8] X. Yuan, F. Tang, D. Zhang, and X. Zhang, (2021) “Green remanufacturer’s mixed collection channel strategy considering enterprise’s environmental responsibility and the fairness concern in reverse green supply chain" International Journal of Environmental Research and Public Health 18(7): 3405. DOI: 10.3390/ijerph18073405.
  9. [9] Z.-Y. Liu and P.-T. Guo, (2021) “Supply Chain Decision Model Based on Blockchain: A Case Study of Fresh Food E-Commerce Supply Chain Performance Improvement" Discrete Dynamics in Nature and Society 2021: 5795547. DOI: 10.1155/2021/5795547.
  10. [10] M. Fakhrzad, M. Firozpour, and H. Hosseini Nasab, (2021) “Comparing Supply Chain Risks Ranking in Multi-Attribute Decision-Making Methods Using the Proposed Three-Dimensional Integration Mean Method" Asia-Pacific Journal of Operational Research 38(6): 00068. DOI: 10.1142/S0217595921500068.
  11. [11] D. Liu, L. Shan, L. Wang, S. Yin, H. Wang, and C. Wang, (2021) “P3OI-MELSH: Privacy Protection Target Point of Interest Recommendation Algorithm Based on Multi-Exploring Locality Sensitive Hashing" Frontiers in Neurorobotics 15: 660304. DOI: 10.3389/fnbot.2021.660304.
  12. [12] R. Stekelorum, I. Laguir, and J. ElBaz, (2020) “Can you hear the Eco? From SME environmental responsibility to social requirements in the supply chain" Technological Forecasting and Social Change 158: 120169. DOI: 10.1016/j.techfore.2020.120169.
  13. [13] K. Xia, (2021) “The characteristics of average abundance function of multi-player threshold public goods evolutionary game model under redistribution mechanism" Applied Mathematics and Computation 392: 125733. DOI: 10.1016/j.amc.2020.125733.
  14. [14] D. Pu, F. Xie, and G. Yuan, (2020) “Active Supervision Strategies of Online Ride-Hailing Based on the Tripartite Evolutionary Game Model" IEEE Access 8: 9151168. DOI: 10.1109/ACCESS.2020.3012584.
  15. [15] B. Yang, H. Liu, and X. Li, (2021) “Learning Deep Direct-Path Relative Transfer Function for Binaural Sound Source Localization" IEEE/ACM Transactions on Audio Speech and Language Processing 29: 3491–3503. DOI: 10.1109/TASLP.2021.3120641.
  16. [16] J. Wang, X. Wang, and L. Fu, (2020) “Evolutionary Game Model of Public Opinion Information Propagation in Online Social Networks" IEEE Access 8: 9130698. DOI: 10.1109/ACCESS.2020.3006150.
  17. [17] Y. Liu and X. Yu, (2021) “Research on optimization of feed enterprise supply chain based on Stackelberg game model" Feed Research 44(23):
  18. [18] Y. Espinoza-Vázquez, F. Gómez-Castro, and J. Ponce-Ortega, (2021) “Multi-objective optimization of the supply chain for the production of biofuels and high value-added products in Mexico: importance of the water footprint" Computer Aided Chemical Engineering 50: 7–12. DOI: 10.1016/B978-0-323-88506-5.50002-4.
  19. [19] S. Dara, H. Abdulqader, Y. Al Wahedi, and A. Berrouk, (2020) “Countrywide optimization of natural gas supply chain: From wells to consumers" Energy 196: DOI: 10.1016/
  20. [20] P. Afkhami and N. Zarrinpoor, (2021) “Optimization design of a supply chain for jatropha-based biofuel from a sustainable development perspective considering international resources and demand: A case study" Industrial and Engineering Chemistry Research 60(17): 6188–6207. DOI: 10.1021/acs.iecr.0c06209.



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