On-Demand, Long-Term, or Hybrid? An Economic Analysis of Optimal Rental Models on Sharing Platforms

• 成果类型: Article; Early Access
• 署名作者: Chen, Jianqing; Feng, Nan; Guo, Zhiling; Zhang, Wenyi
• 署名单位: University of Texas System; University of Texas Dallas; Tianjin University; University of North Texas System; University of North Texas Denton
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2022.0441
• 发表日期: 2024
• 关键词: strategic analysis

摘要

The rapidly growing sharing economy is characterized by improved resource utilization through peer -to -peer transactions. Sharing platforms usually adopt one of three rental models, long-term, on -demand, and hybrid, where the long-term rental requires full dedication of resources to market over a predefined period, the on -demand rental allows resources to be exchanged for a fraction of the period, and the hybrid rental model provides both options. We develop an analytical model consisting of a monopolistic sharing platform that connects renters with owners who have heterogeneous asset utilization and incur different setup and transaction costs of participation under different rental models. We identify the conditions under which each of the three rental models can emerge as the platform's optimal rental strategy and further examine their impacts on social welfare and consumer surplus. We find that the relative setup cost and the relative transaction cost between owners and renters play a crucial role in shaping the equilibrium market price and optimality of the three rental models, whereas the total costs determine the equilibrium transaction volume and sustainability of the three rental models. Only when the total cost is low can all three models be sustainable, and each model could emerge to be optimal in the presence of a moderately high relative transaction cost on the owners' side. Specifically, when the owners' setup cost is significantly higher than the renters', the on -demand model is optimal. When the owners' setup cost is significantly lower than the renters' and the renter's setup cost is low, the long-term model is optimal. Only when their setup costs are comparable or when the owners' setup cost is significantly lower than the renters' and the renter's setup cost is high can the hybrid model be optimal. When the platform optimally chooses the long-term or hybrid model, it also generates the highest social welfare, and in a wide range of parameter regions, it also yields the highest consumer surplus, leading to a win-win outcome. Overall, our results offer important new insights into the platform's optimal rental -model choice in the sharing economy and its implications for consumers and society.