平衡拼车个性化票价中的利润与乘客接受度
Balancing Profit and Traveller Acceptance in Ride-Pooling Personalised Fares
AI总结：
针对拼车系统，提出个性化票价方法，通过考虑乘客接受度平衡利润与满意度，实验显示里程减少4.5%，每英里利润提升超20%。
摘要：
在拼车系统中，乘客因绕路和更长的出行时间而感到不适，这种不适通过共享折扣来补偿。大多数研究假设乘客获得固定折扣，或者少数情况下，获得与不便程度成比例的折扣。我们表明，系统受益于个性化票价。我们认为，如果票价包含乘客的接受度，那么优化运营商预期利润的票价也能提高系统整体性能。我们的定价方法设定在异质人群中，乘客具有不同的时间价值水平和共享意愿，这些对运营商来说是未知的。高票价会阻止客户使用服务，而低票价会降低利润率。值得注意的是，共享行程只有在所有同行乘客都接受时才能实现（决策由潜在行为因素驱动）。我们的方法揭示了共享性拓扑的有趣特性。它不仅识别出对系统高效的行程并通过降低票价来支持它们（以提高其实现概率），还识别出对系统缺乏吸引力的乘客（例如，由于与其他乘客不兼容），并通过高票价有效地将他们转移到私人行程。与以往方法不同，这种方法自然地平衡了乘客满意度和利润最大化。通过在纽约市进行的实验，我们表明这比固定折扣基线有显著改进：里程（环境外部性的代理指标）减少了4.5%，运营商每英里产生的利润增加了超过20%。我们认为，如果包含乘客满意度，最大化盈利能力的拼车系统票价更可持续和高效。关键词：拼车，个性化定价，个人折扣。
英文摘要：
In a ride-pooling system, travellers experience discomfort associated with a detour and a longer travel time, which is compensated with a sharing discount. Most studies assume travellers receive either a flat discount or, in rare cases, a proportional to the inconvenience. We show the system benefits from individually tailored fares. We argue that fares that optimise an expected profit of an operator also improve system-wide performance if they include travellers' acceptance. Our pricing method is set in a heterogeneous population, where travellers have varying levels of value-of-time and willingness-to-share, unknown to the operator. A high fare discourages clients from the service, while a low fare reduces the profit margin. Notably, a shared ride is only realised if accepted by all co-travellers (decision is driven by the latent behavioural factors). Our method reveals intriguing properties of the shareability topology. Not only identifies rides efficient for the system and supports them with reduced fares (to increase their realisation probability), but also identifies travellers unattractive for the system (e.g. due to incompatibility with other travellers) and effectively shifts them to private rides via high fares. Unlike in previous methods, such approach naturally balances the travellers satisfaction and the profit maximisation. With an experiment set in NYC, we show that this leads to significant improvements over the flat discount baseline: the mileage (proxy for environmental externalities) is reduced by 4.5% and the operator generates more profit per mile (over 20% improvement). We argue that ride pooling systems with fares that maximise profitability are more sustainable and efficient if they include travellers' satisfaction. Keywords: ride-pooling, personalised pricing, individual discounts
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
