Impact of consumer foresight on efficient overselling

IF 1.9 4区 管理学 Q3 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Man Yu, Wei Shi Lim
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引用次数: 0

Abstract

Abstract Overselling is commonly adopted in the travel and hospitality sectors where a good or service is sold in excess of actual supply. We examine the impact of consumer foresight on efficient overselling when there are two dimensions of uncertainty, namely, early consumers are uncertain about their service valuations and the seller is uncertain about late demand arrival. We show that when consumers are naïve and have no foresight to anticipate future events, the seller resorts to the use of partial refunds and involuntary cancellation when the mandatory compensation for seller‐initiated cancellation is low, resulting in efficiency loss. When consumers are sophisticated and have perfect foresight on future events, efficiency is achieved when the seller sells the entire capacity in advance and relies solely on voluntary cancellation to re‐sell units when late demand warrants it. Refund complements overselling both by improving allocation efficiency in involuntary cancellation and by mitigating the cost of overselling when consumers have limited foresight. Unlike the social planner, the seller may suffer from consumer foresight. Our findings pinpoint the mandatory compensation in involuntary cancellation as a strategic tool for the social planner to tilt the seller's preference in the seller‐initiated cancellation policy to achieve efficient overselling.
消费者预见对有效超售的影响
过度销售通常用于旅游和酒店行业,在这些行业中,商品或服务的销售超过了实际供应。当存在两个维度的不确定性时,即早期消费者对其服务价值的不确定性和卖方对需求延迟到达的不确定性,我们研究了消费者前瞻对有效超售的影响。我们表明,当消费者是naïve并且没有预见未来事件时,当卖方发起的取消的强制赔偿较低时,卖方诉诸于使用部分退款和非自愿取消,从而导致效率损失。当消费者成熟且对未来事件有完美的预见时,当卖方提前出售全部产能,并在后期需求需要时完全依靠自愿取消来转售单位时,效率就会实现。退款通过提高非自愿取消的分配效率和在消费者缺乏远见的情况下降低过度销售的成本来补充过度销售。与社会规划师不同,卖家可能会受到消费者远见的影响。我们的研究结果指出,非自愿取消中的强制性补偿是社会计划者在卖方发起的取消政策中倾斜卖方偏好以实现有效超额销售的战略工具。
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来源期刊
Naval Research Logistics
Naval Research Logistics 管理科学-运筹学与管理科学
CiteScore
4.20
自引率
4.30%
发文量
47
审稿时长
8 months
期刊介绍: Submissions that are most appropriate for NRL are papers addressing modeling and analysis of problems motivated by real-world applications; major methodological advances in operations research and applied statistics; and expository or survey pieces of lasting value. Areas represented include (but are not limited to) probability, statistics, simulation, optimization, game theory, quality, scheduling, reliability, maintenance, supply chain, decision analysis, and combat models. Special issues devoted to a single topic are published occasionally, and proposals for special issues are welcomed by the Editorial Board.
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