Navigating the Physical Frontier: Mastering Implementation and Privacy in Service Robot Projects

Numerous projects involving physically embodied service robots fail to achieve their intended outcomes. Existing research has predominantly focused on customer perspectives, leaving a significant gap in our understanding of service robot implementation from an organizational standpoint. Moreover, while evidence indicates that privacy concerns significantly influence user adoption, research remains ambiguous regarding whether these concerns translate into corresponding behaviors. This dissertation addresses these gaps through two empirical research studies that derive generalizable insights into effective service robot implementation and examine employees’ paradoxical privacy behavior. By incorporating both manager-level (macro) and employee-level (micro) perspectives, this dissertation offers a holistic understanding of service robot implementation and usage. Specifically, the first research study employs a grounded theory approach to identify six critical factors for successful service robot implementation, two of which involve inherent trade-offs. As a result, organizations should (1) start with a viable use case, (2) balance a marketing-driven innovator strategy with a productivity-oriented follower strategy, (3) balance the timing and scope of implementation projects in legacy and greenfield environments, (4) prioritize employee acceptance and engage them early, (5) redesign processes using a holistic approach, and (6) select appropriate technology solutions. Additionally, a three-stage framework, comprising ‘initiating’, ‘piloting’, and ‘scaling’, is developed to integrate these theoretical findings and offer practical guidance for managers. These conclusions are drawn from a multi-case theory-building approach encompassing 14 cases across seven industries in three countries, enabling more generalized insights than most previous research. The second research study draws on task-technology fit theory and the Computers-as-Social-Actors paradigm to examine the privacy paradox in workplace interactions with service robots through two consecutive empirical studies. A mixed-method design is applied that extends the privacy paradox to real-world human-service robot interactions, demonstrating that privacy concerns do not necessarily translate into corresponding information-sharing behaviors. Furthermore, task complexity is identified as an important moderator of this paradox, contributing to service robot design research by demonstrating that the type of service robot (i.e., humanoid versus android) significantly affects employees’ privacy behavior. Overall, this dissertation contributes both scientifically and practically by extending established theoretical frameworks (including the innovation diffusion curve, task-technology fit theory, and the Computers-as-Social-Actors paradigm) to the context of service robot implementation and usage. It offers actionable guidelines for managers and underscores the importance of addressing both organizational challenges and employee privacy to achieve successful and sustainable integration of service robots in modern workplaces.