公共交通的最佳动态定价考虑消费者社会学习
1Liuzhou Railway Vocational Technical College, Liuzhou, Guangxi, China.
PloS one
|January 31, 2024
概括
公共交通 (包括地铁,公共汽车和公共交通工具) 的动态定价是通过游戏和社交学习模型进行优化. 消费者行为和服务质量投资影响可持续城市发展的市场份额和定价.
科学领域:
- 城市规划和交通经济学 城市规划和交通经济学
- 行为经济学和网络理论.
- 计算社会科学 计算社会科学
背景情况:
- 有效的公共交通运输定价对于管理城市交通拥堵和促进可持续发展至关重要.
- 了解消费者选择和运营商战略是优化公共交通系统的关键.
- 社会学习显著影响消费者采用不同运输方式.
研究的目的:
- 开发和模拟一个动态的游戏定价模型,将社会学习纳入城市公共交通.
- 分析消费者敏感性和社会学习如何影响地铁,公共汽车和交通工具的市场份额和定价.
- 为优化公共交通价格策略和服务改进提供见解.
主要方法:
- 为公共交通运输运营商构建一个动态游戏定价模型.
- 用于消费者行为分析的社会学习网络模型的开发.
- 强化学习算法的应用用于模型模拟和结果分析.
主要成果:
- 消费者对旅行方式的敏感性增加导致市场份额和价格的调整.
- 消费者社会学习行为保持了高地铁市场份额,而公共汽车和交通工具市场份额仍然较低.
- 提高消费者敏感性激励运营商投资服务质量,影响定价.
结论:
- 该研究为理解公共交通中的定价,消费者行为和服务质量之间的相互作用提供了一个框架.
- 最佳的定价策略可以通过考虑社会学习动态和消费者感知来告知.
- 调查结果支持为可持续的城市流动和高效的公共交通管理做出决策.
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