Construction and empirical research on acceptance model of service robots applied in hotel industry

Abstract

PurposeRobots, as the crystallization of new artificial intelligence, are being applied in various fields, especially the hotel industry. They are seizing the opportunities, using technology to improve the overall quality and comprehensive competitiveness. However, they also cause many problems due to practical limitations. The purpose of this paper is to study customers' recognition and acceptance of hotel service robots to guide the successful promotion of this technology.Design/methodology/approachThis paper proposed a comprehensive model based on the theory of planned behavior, the technology acceptance model and then the perceived value-based acceptance model. Exploratory factor analysis, confirmatory factor analysis, grouped regression analysis and path analysis was adopted to validate the impacts of each variable to obtain the final reliable model using data collected from hotel guests using a self-designed questionnaire.FindingsThe empirical research based on the theoretical model shows that the constructed conceptual model can thoroughly explain the influencing factors of hotel robot acceptance, enrich the acceptance theory and provide academic support for the use and popularization of hotel service robots. Among all variables, attitude, usefulness and perceived value are the factors that have the greatest impact on acceptance. They have significant differences in the effects of adjustment variables such as gender, educational level, whether hotel robots have been used, and whether other robot services have been experienced on different paths in the model.Practical implicationsThis paper explored the customer acceptance of service robots in hotels, helped to understand the process of decision-making on service robot selection and contributed to the theoretical extension of the hospitality industry. The work guides hotel management to promote better-personalized products and services of robot technology in the hospitality industries.Originality/valueThe acceptance study on hotel service robots provides insight into the hotel industry to understand customers' attitudes and acceptance of emerging technology.

Technology Adoption in Small-Medium Enterprises based on Technology Acceptance Model: A Critical Review

“…3. This improvement model is, therefore, more prevailing in explaining the adoption behaviour [24]. Fig.…”

“…2. TAM has been applied in different types of technologies, but some scholars believed external variables were not explored by this model, thereby, leading to uncertainty [24]. This led [25] to construct an improved version of technology acceptance model (TAM2) with the addition of voluntariness, subjective norms and image as the new social forces, also four cognitive instrumental processes i.e., job relevance, output quality, result demonstrability, and System Perceived Ease of Use Perceived Usefulness Attitude Toward Using Actual System Use Link Hypothesized insignificant but found significant X1 PEOU as indicated in Fig.…”

The Effect of Perceptions on Service Robot Usage Intention: A Survey Study in the Service Sector

“…While the concept was formerly used to mean stupid machines that perform trivial, repetitive tasks, it has evolved to describe intelligent anthropomorphic robots in popular culture [28]. Robots are characterized as "reprogrammable multifunctional" devices that are programmed to move materials, parts, tools, or specialized equipment to execute a variety of activities [30]. Robots can perform a commonly complex set of actions.…”

A meta-analysis of consumer innovation resistance: is there a cultural invariance?

“…Forth, because of the pro-innovation bias, even after three decades, Cornescu and Adam (2013) assert that the number of empirical research on resistance to innovation has been less active compared to research on adoption theories such as Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), Diffusion of Innovation (DOI), Technology Acceptance Model (TAM), Information System Success Model (ISSM), Unified Theory of Acceptance and Use of Technology (UTAUT), Expectation Confirmation Model (ECM) (Chong et al , 2012; Hew and Kadir, 2016; Leong et al , 2019; Limayem and Cheung, 2008; Pu et al , 2020; Zhong et al , 2020). Therefore, the current meta-analysis would further enrich our understanding of innovation resistance.…”