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【学术报告】Let’s Go to the Movies! Subscription Ticket Services and Box Office Revenue

作者: 日期:2022年06月01日 15:06 来源: 关注:

学术报告会通知

报告题目Let’s Go to the Movies! Subscription Ticket Services and Box Office Revenue

报 告 人:张明月 副教授

报告时间:2022年6月9日14:30

腾讯会议:192 849 177

主 持 人:董雪艳 助理教授

报告摘要:

Subscription-based revenue models have become commonplace for online media services such as digital  music, at-home video streaming, and digital gaming. In offline media, subscription-based movie ticketing services are an emerging and interesting new business model for an established industry that is trying to compete with these online services. Subscribers pay a monthly fee in exchange for admission to a number of movies at various movie theaters. The emergence of these models provides an opportunity to understand how a subscription option disrupts the traditional movie industry. In this paper, we leverage a quasi-natural experiment setting - a sudden policy change in the pricing of a subscription service - to estimate the impact of subscription services on movie box office revenue. We find that the average treatment effect on movies’ box office revenues is positively significant and economically meaningful. Particularly, the weekend box office revenues of an average movie increased 12%~35% in the following six months after consumers adopting subscription service. We also uncover insightful heterogeneous effects that subscription services appear to drive more attendance to low-popularity movies, on the condition that only if movies of low popularity are narrow-appeal and high quality. Movies with broad appeal but lower quality do not benefit from the subscription ticketing service. Managerial implications on subscription-based services are thus provided.

报告人简介:

张明月,上海外国语大学国际工商管理学院副教授、博士生导师。先后在北京理工大学、清华大学取得学士学位和管理学博士学位。曾受国家留学基金委资助赴美国亚利桑那大学进行访问交流。主要研究领域为在线社区、新兴商务模式下的激励机制分析、消费者行为等。主持一项国家自然科学基金项目,作为主要参与人参与上海高校本科重点教改项目、教育部新文科研究与改革实践项目等多项省部级教学项目。在信息管理领域的顶级、权威期刊发表多篇论文,包括MIS Quarterly, Decision Sciences, ACM Transactions on Knowledge Discovery from Data (TKDD), Decision Support Systems,Information & Management等。


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