Designing crowdsourced delivery systems: The effect of driver disclosure and ethnic similarity
研究众包配送系统中司机信息披露和种族相似性如何影响客户信任、满意度和复购意愿，发现只有当客户感知司机与自己种族相似时，披露身份才有效。
Abstract Crowdsourced delivery is a service operations model that has proliferated in recent years, bringing unique opportunities and challenges to online retail operations. In particular, new technology enabled features, such as the disclosure of delivery drivers' identities, introduce a social dimension prior to delivery service encounters that might influence customers' service quality expectations and ultimately impact their attitudes towards the retailers. Building on premises of social identity theory, this research investigates effects of various crowdsourced delivery system designs related to driver disclosure and ethnicity on customers' attitudes towards the drivers and retailers. Using data from a scenario‐based experiment with 761 participants across two studies, we find that crowdsourced delivery designs that disclose drivers' identity increase customers' trust, satisfaction, and repurchase intentions only when customers perceive the drivers to be similar to them, particularly with regard to ethnicity. The designs that offer driver choice options are also found to be highly regarded by customers. In addition, the similarity effects of crowdsourced delivery designs differ depending on certain customer characteristics. Overall, our research shows crowdsourced delivery ‐ as a technology‐driven phenomenon ‐ may portend unexpected and challenging social dilemmas for operations managers. Our findings contribute to emerging research on the intersection of service design, technology management, and the sharing economy.