Conceptualising Willingness to Accept Social Robot’s Recommendations
(A2023-114135)

AUTHORS

Isha Kharub, Western Sydney University; Michael Lwin, Western Sydney University; Omar Mubin, Western Sydney University; Aila Khan, Western Sydney University

ABSTRACT

It is estimated that social robots (SR) will fuel the growth of the service sector over the next 30 years (Wirtz et al., 2018). Current studies have predominantly explored the use of social robots to fulfil simple service tasks such as guides, hosts and porters. For social robots to solve complex consumer problems, it requires a higher level of cognitive and affective abilities. However, it is unclear whether customers are willing to accept recommendations from a machine (Byrd et al., 2021). An extensive literature review shows there is a lack of a conceptual definition for willingness to accept SR’s recommendations (WASRR) and a theoretical model that helps explain the factors that drive WASRR. Thus, this research aims to fulfil these research gaps. The research has identified attitudes, the inferences of manipulative intent, source credibility and empathy as variables that will impact WASRR and ultimately, adopting the recommendations. It will help managers integrate social robots in customer service roles and provide a more human-like interaction.