Sharing network features analysis and dispatching strategy design

• Published in: Industrial management + data systems Vol. 122; no. 10; pp. 2371 - 2392
• Main Authors: Lv, Tong, Lefeng, Shi, He, Weijun
• Format: Journal Article
• Language: English
• Published: Wembley Emerald Publishing Limited 02.11.2022; Emerald Group Publishing Limited
• Subjects: Algorithms; Costs; Design; Influence; Machine learning; Supply & demand; Multi-step random forest reinforcement learning algorithm; Sharing point; Sharing business; Dispatching strategy
• ISSN: 0263-5577; 1758-5783
• DOI: 10.1108/IMDS-01-2022-0019

PurposeA vital job for one sharing business is dynamically dispatching shared items to balance the demand-supply of different sharing points in one sharing network. In order to construct a highly efficient dispatch strategy, this paper proposes a new dispatching algorithm based on the findings of sharing network characteristics.Design/methodology/approachTo that end, in this paper, the profit-changing process of single sharing points is modeled and analyzed first. And then, the characteristics of the whole sharing network are investigated. Subsequently, some interesting propositions are obtained, based on which an algorithm (named the Two-step random forest reinforcement learning algorithm) is proposed.FindingsThe authors discover that the sharing points of a common sharing network could be categorized into 6 types according to their profit dynamics; a sharing network that is made up of various combinations of sharing stations would exhibit distinct profit characteristics. Accounting for the characteristics, a specific method for guiding the dynamic dispatch of shared products is developed and validated.Originality/valueBecause the suggested method considers the interaction features between sharing points in a sharing network, its computation speeds and the convergence efficacy to the global optimum scheme are better than similar studies. It suits better to the sharing business requiring a higher time-efficiency.