User Acceptance of Hotel Service Robots Using the Quantitative Kano Model

Abstract

With today’s rapid technological developments, many have applied artificial intelligence and robot technology to the tourism and hotel industries, with hotel service robots (HSRs) being gradually developed. At present, more technology development companies have focused their attention on improving HSRs’ different attributes to improve their acceptance by users, thereby enhancing market competitiveness and improving customer loyalty. Understanding consumer acceptance of HSRs is important. Based on a literature review of the user’s acceptance of HSR attributes and HSRs’ current development status, some factors and attributes were extracted. For the questionnaire’s design and data extraction, the quantitative Kano model was used. The data obtained were compiled and analyzed using Microsoft Excel and SPSS. This study aims to (1) qualitatively apply the perceived value theory to develop specific HSR attributes and (2) quantitatively examine these attributes concerning public acceptance. By integrating the Kano model with the perceived value theory, this study provides empirical evidence of a nonlinear relationship between HSRs’ perceived value and user acceptance by exploring various attributes affecting the user’s acceptance of HSRs and the degree of change brought by the different attributes. The research result reveals the multidimensional impacts of perceived value, prompting users to embrace newer HSR technologies.