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A Novel Intensive Distribution Logistics Network Design and Profit Allocation Problem considering Sharing Economy

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  • Mi Gan
  • Shuai Yang
  • Dandan Li
  • Mingfei Wang
  • Si Chen
  • Ronghui Xie
  • Jiyang Liu

Abstract

The rapid growth of logistics distribution highlights the problems including the imperfect infrastructure of logistics distribution network, the serious shortage of distribution capacity of each individual enterprise, and the high cost of distribution in China. While the development of sharing economy makes it possible to achieve the integration of whole social logistic resources, big data technology can grasp customer’s logistics demand accurately on the basis of analyzing the customer’s logistics distribution preference, which contributes to the integration and optimization of the whole logistics resources. This paper proposes a kind of intensive distribution logistics network considering sharing economy, which assumes that all the social logistics suppliers build a strategic alliance, and individual idle logistics resources are also used to deal with distribution needs. Analyzing customer shopping behavior by the big data technology to determine customer’s logistics preference on the basis of dividing the customer’s logistics preference into high speed, low cost, and low pollution and then constructing the corresponding objective function model according to different logistics preferences, we obtain the intensive distribution logistics network model and solve it with heuristic algorithm. Furthermore, this paper analyzes the mechanism of interest distribution of the participants in the distribution network and puts forward an improved interval Shapley value method considering both satisfaction and contribution, with case verifying the feasibility and effectiveness of the model. The results showed that, compared with the traditional Shapley method, distribution coefficient calculated by the improved model could be fairer, improve stakeholder satisfaction, and promote the sustainable development of the alliance as well.

Suggested Citation

  • Mi Gan & Shuai Yang & Dandan Li & Mingfei Wang & Si Chen & Ronghui Xie & Jiyang Liu, 2018. "A Novel Intensive Distribution Logistics Network Design and Profit Allocation Problem considering Sharing Economy," Complexity, Hindawi, vol. 2018, pages 1-15, April.
  • Handle: RePEc:hin:complx:4678358
    DOI: 10.1155/2018/4678358
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    References listed on IDEAS

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    2. Fuqiang Lu & Liying Wang & Hualing Bi & Zichao Du & Suxin Wang, 2021. "An Improved Revenue Distribution Model for Logistics Service Supply Chain Considering Fairness Preference," Sustainability, MDPI, vol. 13(12), pages 1-30, June.
    3. Kexin Bi & Mengke Yang & Latif Zahid & Xiaoguang Zhou, 2020. "A New Solution for City Distribution to Achieve Environmental Benefits within the Trend of Green Logistics: A Case Study in China," Sustainability, MDPI, vol. 12(20), pages 1-25, October.
    4. Yingyan Zhao & Yihong Zhou & Wu Deng, 2020. "Innovation Mode and Optimization Strategy of B2C E-Commerce Logistics Distribution under Big Data," Sustainability, MDPI, vol. 12(8), pages 1-13, April.
    5. Jiekun Song & Xiaoping Ma & Rui Chen, 2021. "A Profit Distribution Model of Reverse Logistics Based on Fuzzy DEA Efficiency—Modified Shapley Value," Sustainability, MDPI, vol. 13(13), pages 1-20, June.
    6. Shobhana Chandra & Sanjeev Verma, 2023. "Big Data and Sustainable Consumption: A Review and Research Agenda," Vision, , vol. 27(1), pages 11-23, February.
    7. Hongqiang Fan & Yichen Sun & Lifen Yun & Runfeng Yu, 2023. "A Joint Distribution Pricing Model of Express Enterprises Based on Dynamic Game Theory," Mathematics, MDPI, vol. 11(19), pages 1-17, September.

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