The adoption, diffusion & categorical ambiguity trifecta of social robots in e-health – Insights from healthcare professionals. (May 2021)

• Record Type: Journal Article
• Authors: Kalisz, David E.; Khelladi, Insaf; Castellano, Sylvaine; Sorio, Rossella
• Is Part Of: Futures. Volume 129(2021)
• Publication Date: 2021-05
• Subjects: Social robots -- e-health -- Categorical ambiguity -- Adoption -- Hybrid products; Economic forecasting -- Periodicals; Technological forecasting -- Periodicals; Economic policy -- Periodicals; Prévision économique -- Périodiques; Prévision technologique -- Périodiques; Politique économique -- Périodiques; Economic forecasting; Economic policy; Technological forecasting; Periodicals; Electronic journals; 330.0112
• DOI: 10.1016/j.futures.2021.102743
• Languages: English
• ISSNs: 0016-3287

Abstract

Highlights: Social robots are hybrid products, combining product, service, and software elements. Social robots have features of more than one category. Social robots' categorical ambiguity explains the different diffusion processes of such innovation. Social robots' ambiguous nature acts as a barrier and an opportunity to their acceptance. An increase of social robots' ambiguity creates new interaction experiences, impacting their categorization. Abstract: Social robots are artificial agents communicating in a human-like way. These assistive technologies are surging particularly to address personal healthcare shortages while allowing aging people to stay in their homes. Social robots belong to a rapidly changing AI industry. Such innovation may adopt different diffusion and adoption processes due to the categorical ambiguity of these products; their features vary from those typical of an object (i.e., delivering food) to those typical of a human being (i.e., speaking with and answering to patients). Social robots combine product, service, and software elements, making them hybrid products categorized into alternative categories, fluctuating users' attitudes towards these products. The paper draws on prior research on social robots, categorization, and innovation adoption and diffusion. The aim is to explore healthcare professionals' perception of social robots' adoption and diffusion, allowing us to understand how they view and handle their categorical ambiguity feature. Using the Delphi technique targeting experts with extensive knowledge of social robots and e-health practice, the results emphasize that even if the ambiguous nature of social robots may represent a barrier to their adoption, their categorical ambiguity is an opportunity to create interactive experiences that ultimately increase their acceptance and diffusion.