The Queue Behind the Curtain: Information Disclosure in Omnichannel Services
研究全渠道服务中是否向App用户披露排队长度信息，分析其对等待敏感和质量敏感用户的渠道选择、系统吞吐量及各方福利的影响。
ABSTRACT With evolving mobile technologies, an increasing number of service providers are running multiple channels by offering apps to serve customers. In this article, we evaluate whether providing an online ordering option through an app is necessarily beneficial for the firm and customers. In particular, we study the implications of queue‐length information disclosure on the channel choice strategy of wait‐sensitive and quality‐sensitive app users. We adopt a game‐theoretic, discrete‐time queuing framework to model customers' strategic channel choice behavior in omnichannel systems. When provided with queue‐length information in an omnichannel system, app users follow a dual‐threshold policy where they order online for moderate queue lengths and choose the offline option when the queue length is either too short or too long. If non‐app users are relatively more wait‐sensitive, the overall throughput might be lower in the omnichannel system compared to the single‐channel benchmark. On the other hand, if app users are relatively more wait‐sensitive, then the omnichannel system increases throughput. From the customer's perspective, whether or not providing online ordering benefits her depends on the relative market size and the relative wait‐sensitivities of the non‐app user and app user segments. While non‐app users are consistently worse off in omnichannel systems, app users certainly benefit from omnichannel systems when queue‐length information is disclosed. It is indeed possible that both segments might be worse off in an omnichannel system. The firm may use information disclosure in an omnichannel system as an operational lever to increase throughput when app users are either highly quality‐sensitive or highly wait‐sensitive, or when the system is highly congested. Evaluating the overall performance of an omnichannel firm requires a careful calibration of customer primitives and consideration of the relative proportions of non‐app users and app users in the system.