Evolutionary game-based warehousing resources sharing strategy for logistics industry under product-service system paradigm
Efficient warehousing resources distribution is essential for reducing logistics costs and improving supply chain performance. With advancements in information technology and the rise of the sharing economy, many enterprises are adopting the product-service system (PSS) to support cleaner production (CP) and circular economy (CE) strategies. However, logistics stakeholders face many challenges in developing effective sharing strategies under dynamic markets and personalized demands. To address these challenges, an evolutionary game-based approach to warehousing resource sharing (WRS) under the PSS paradigm to maximize stakeholder benefits is proposed in this paper. By using double auction mechanisms, a utility functions for suppliers and demanders are designed, after which the replicator dynamics equations and Jacobian matrices are applied to identify the evolutionarily stable strategies (ESS). Finally, a case study with numerical simulations are carried out to confirm the feasibility of the proposed approach. The results highlighted three key findings: (1) low cloud platform operating costs are vital for enabling unsupervised management; (2) suppliers exhibit sensitivity to initial sharing probabilities and subsidy rates; and (3) demanders can achieve enhanced flexibility and redundancy reduction through high information resource saturation. These insights can inform the formulation of effective WRS strategies to foster sustainable and competitive logistics ecosystems.
Authors
- Chengying Liang
- Jin Wang (ORCID: https://orcid.org/0000-0001-5462-5370)
- Chuang Wang (ORCID: https://orcid.org/0000-0002-3081-9776)
- Yang Liu (ORCID: https://orcid.org/0000-0001-8006-3236)
- Shan Ren
Institutions
- Linköping University (SE)
- Xi’an University of Posts and Telecommunications (CN)
- Comprehensive Clinical Research (US)
- University of Oulu (FI)
Publication Details
- Journal
- Advanced Engineering Informatics
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1016/j.aei.2025.103560
- Citations
- 4
- Primary Topic
- Advanced Manufacturing and Logistics Optimization
- Type
- article
- Field-Weighted Citation Impact
- 4.97
Funders
- National Social Science Fund of China