“I am served by a Robot!”: internal antecedents of customer acceptance of robotic hotel-service agents

Purpose This study explores how customers' individual characteristics and perceptions affect acceptance of service robots as a hotel workforce. The Interactive Technology Acceptance Model (iTAM) has inspired us to investigate effects of customers' technological self-efficacy, perceived interactivity, sense of utility, and enjoyment-level of acceptance related to hotel-service robots as staff. Design/methodology/approach Data were collected from 224 customers via an online questionnaire conducted in the period April–June 2022 by convenience sampling, and then analyzed by using partial least squares – structural equation modeling (PLS-SEM). Findings The findings show that customers' technological self-efficacy and perceived interactivity with service robots enhances perceived usefulness and perceived enjoyment, serving as functional and emotional value components of service robots. They also demonstrate that robot's interactivity outweighs other robot's value components, such as perceived usefulness and perceived enjoyment for acceptance of service robots as employees in hotels. Originality/value While empirically validating the iTAM, this study emphasizes service robot interactivity as the most important aspect for customers' acceptance, and it adds a new perspective regarding the underexplored role of the customer-robot interface. Combining specific dimensions from different technology acceptance models (functional/socio-emotional/relational; utilitarian/hedonic) the study contributes to the service robot literature currently missing a more holistic understanding of consumers' experience and adoption drivers, and it provides managerial guidance on how to successfully implement service robots in hotel environments.

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Publication Details

Journal
Journal of Organizational Change Management
Published
2024-08-16
DOI
https://doi.org/10.1108/jocm-08-2023-0315
Citations
5
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
1.74
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article

“I am served by a Robot!”: internal antecedents of customer acceptance of robotic hotel-service agents

Sven Dahms, Sladjana Cabrilo, Rosanna Leung, Fu-Sheng Tsai
5 citations
Journal of Organizational Change Management
AI in Service Interactions
1.74
article

“I am served by a Robot!”: internal antecedents of customer acceptance of robotic hotel-service agents

Sven Dahms, Sladjana Cabrilo, Rosanna Leung, Fu-Sheng Tsai
article en
5 citations

Abstract

Purpose This study explores how customers' individual characteristics and perceptions affect acceptance of service robots as a hotel workforce. The Interactive Technology Acceptance Model (iTAM) has inspired us to investigate effects of customers' technological self-efficacy, perceived interactivity, sense of utility, and enjoyment-level of acceptance related to hotel-service robots as staff. Design/methodology/approach Data were collected from 224 customers via an online questionnaire conducted in the period April–June 2022 by convenience sampling, and then analyzed by using partial least squares – structural equation modeling (PLS-SEM). Findings The findings show that customers' technological self-efficacy and perceived interactivity with service robots enhances perceived usefulness and perceived enjoyment, serving as functional and emotional value components of service robots. They also demonstrate that robot's interactivity outweighs other robot's value components, such as perceived usefulness and perceived enjoyment for acceptance of service robots as employees in hotels. Originality/value While empirically validating the iTAM, this study emphasizes service robot interactivity as the most important aspect for customers' acceptance, and it adds a new perspective regarding the underexplored role of the customer-robot interface. Combining specific dimensions from different technology acceptance models (functional/socio-emotional/relational; utilitarian/hedonic) the study contributes to the service robot literature currently missing a more holistic understanding of consumers' experience and adoption drivers, and it provides managerial guidance on how to successfully implement service robots in hotel environments.

Journal of Organizational Change ManagementVol. 37(7)
Abu Dhabi University (AE), National Kaohsiung University of Hospitality and Tourism (TW), Cheng Shiu University (TW), I-Shou University (TW)
Openalex Percentile: Top 13%
AI in Service Interactions
1.74
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