Abstract
Robots are being implemented in many frontline services, from waiter robots in restaurants to robotic concierges in hotels. A growing number of firms in hospitality and tourism industries introduce service robots to reduce their operational costs and to provide customers with enhanced services (e.g. greater convenience). In turn, customers may consider that such a disruptive innovation is altering the established conditions of the service-provider relationship. Based on attribution theory, this research explores how customers’ attributions about the firm motivations to implement service robots (i.e. cost reduction and service enhancement) are affecting customers’ intentions to use and recommend this innovation. Following previous research on robot’s acceptance, our research framework analyzes how these attributions may be shaped by customers’ perceptions of robot’s human-likeness and their affinity with the robot. Structural equation modelling is used to analyze data collected from 517 customers evaluating service robots in the hospitality industry; results show that attributions mediate the relationships between affinity toward the robot and customer behavioral intentions to use and recommend service robots. Specifically, customer’s affinity toward the service robot positively affects service improvement attribution, which in turn has a positive influence on customer behavioral intentions. In contrast, affinity negatively affects cost reduction attribution, which in turn has a negative effect on behavioral intentions. Finally, human-likeness has a positive influence on affinity. This research provides practitioners with empirical evidence and guidance about the introduction of service robots and its relational implications in hospitality and tourism industries. Theoretical advances and future research avenues are also discussed.
Highlights
This article is part of the Topical Collection on Artificial Intelligence (AI) and Robotics in Travel, Tourism and LeisureResponsible Editor: Ulrike GretzelRobots are replacing employees in many tasks (Huang and Rust 2018; Hofmann et al 2020)
Following previous research on customers’ attributions toward self-service technology introduction (Nijssen et al 2016), we propose that customers attribute service enhancement or cost reduction as the principal firm motivations to introduce service robots
Structural equation modeling is able to analyze simultaneously a series of relationships in which a dependent variable becomes an independent variable in subsequent relationships, while examining multiple dependent variables at the same time too (Jöreskog et al 1999)
Summary
This article is part of the Topical Collection on Artificial Intelligence (AI) and Robotics in Travel, Tourism and LeisureResponsible Editor: Ulrike GretzelRobots are replacing employees in many tasks (Huang and Rust 2018; Hofmann et al 2020). Robotic applications are widely employed in manufacturing, military forces, medicine, home-care services and are increasingly common in hospitality and tourism (Murphy et al 2017). Some of these robots perform basic and routine tasks in hotels and restaurants (e.g. robotic floor cleaners [Murphy et al 2017]), a growing number of them are performing more advanced frontline tasks that involve engaging customers at the social level (e.g. talking, serving food [Belanche et al 2020a]). As one of the latest advances in smart technologies with a disruptive nature, these robots are reshaping frontline services and the way they are managed (Gretzel et al 2015; van Doorn et al 2017)
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