Competitive spatial pricing for urban parking systems: Network structures and asymmetric information
Competitive spatial pricing for urban parking systems: Network structures and asymmetric information
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DOI：
10.1080/24725854.2021.1937755
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发表时间：
2021-06
期刊：
影响因子：
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通讯作者：
Yuguang Wu;Qiaochu He;Xin Wang
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文献类型：
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作者：
Yuguang Wu;Qiaochu He;Xin Wang
问题/方法。借助新技术来监控停车位占用率（可用性）并处理市场信号，我们的目标是扩大收益管理在停车行业的应用。在本文中，我们考虑内生不对称信息结构下停车系统的竞争性空间定价。我们考虑一个通用的图形霍特林模型，其中每个车库都有其自身停车需求的信息（预测）。结果/学术相关性。我们关注城市网络结构对信息共享激励的影响。有趣的是，我们的分析表明，在循环网络城市中，车库的状况总是更好，而在星形网络城市的郊区，车库的状况可能会更糟。尽管如此，在这两种情况下，车库的整体收入和客户的总公用事业在信息共享的情况下都得到了提高。当进一步考虑不准确的需求预测时，信息共享可能是不可取的。从信息系统设计者的角度来看，我们将最优市场信息分配确定为二次约束二次规划。我们还考虑了一个信息交换平台，其中车库形成两阶段博弈，并发现完全的信息共享在任何市场上都是纳什均衡。实际相关性/管理意义。使用旧金山的数据，我们凭经验证实了信息共享的价值。特别是，价格需求弹性较高、需求方差较小的车库往往能通过信息共享获得更大的收益。直观上，这些车库代表了位于繁华市中心的停车场，对价格竞争敏感，信息共享有助于这些车库更好地预测竞争对手的费率。
Problem/Methodology. Empowered by new technologies to monitor parking occupancy (availability) and process market signals, we aim to expand the application of revenue management in the parking industry. In this paper, we consider competitive spatial pricing in parking systems under endogenous asymmetric information structure. We consider a general graphical Hotelling model wherein each garage has information (forecast) for its own incoming parking demand. Results/Academic Relevance. We focus on the impact of urban network structure on the incentive of information sharing. Interestingly, our analyses suggest that the garages are always better off in a circular-networked city, while they could be worse off in the suburbs of a star-networked city. Nevertheless, in both scenarios, the overall revenue for garages and the aggregate utilities for customers are improved under information sharing. When inaccurate demand forecasting is further considered, information sharing can be undesirable. From an information system designer’s perspective, we identify the optimal market information assignment as a quadratically constrained quadratic program. We also consider an information exchange platform where garages form a two-stage game, and find that complete information sharing is a Nash equilibrium in any market. Practical Relevance/Managerial Implications. Using San Francisco data, we empirically confirmed the value of information sharing. In particular, garages with higher price-demand elasticity and lower demand variance tend to enjoy larger benefits via information sharing. Intuitively, these garages represent the parking lots located in busy downtown areas which are sensitive to price competition, and information sharing helps these garages better predict their competitors’ rates.