What influences patients' continuance intention to use AI-powered service robots at hospitals? The role of individual characteristics

Xiaohui Liu, Xiaoyu He, Mengmeng Wang and Huizhang Shen

Technology in Society, 2022, vol. 70, issue C

Abstract: AI-powered service robots have gradually developed into popular self-service agents in the health care industry. Though prior research has investigated what affects individuals' adoption of AI-powered service robots in the service industry, few have considered patients' continuance intention for AI-powered service robots at hospitals from the perspective of patients' characteristics. Drawing on the Technology Adoption Model and individual characteristics (i.e., trust in technology and independent personality), we develop a framework testing the factors influencing patients' continuance intention (CI) for AI-powered service robots at hospitals with Intelligent Guide Robots as an example. The model is validated using PLS-SEM analysis and data from 543 patients of a 3-A hospital in Eastern China. The study finds that patients' trust in AI techniques and independent personality positively influence their perception of usefulness (PU), ease-of-use (PEOU), and enjoyment (PE), respectively. Moreover, PU, PEOU, and PE are significant predictors of CI toward AI-powered service robots. PEOU and PE partially mediate the relationship between trust/independent personality and CI. The findings imply that organizations in the healthcare could try their best to increase users' trustworthiness toward AI techniques. In addition, developers could continuously upgrade AI-powered service robots to improve patients’ PE and PEOU.

Keywords: AI-powered service robots; Trust in AI techniques; Independent personality; TAM; Continuance intention (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:70:y:2022:i:c:s0160791x22001373

DOI: 10.1016/j.techsoc.2022.101996

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