Employees as Early Adopters of Robotic Technology: A Self-Identity Approach With Service Improvisation-Generated Outcomes
This research uses a self-identity approach to explore how employees’ self-identity regarding robotic technology influences performance expectancy and effort expectancy, subsequently shaping their willingness to be early adopters. Additionally, the study examines the moderating roles of top management support and personal innovativeness. Data were collected through a survey of 588 full-time employees from three- to five-star hotels in Taiwan that had implemented service robots for at least 6 months. The results revealed that performance expectancy and effort expectancy mediated the relationship between self-identity and adoption willingness. Top management support strengthened the positive relationship between effort expectancy and adoption willingness, whereas personal innovativeness moderated the link between adoption willingness and service improvisation. The findings highlight that the willingness to adopt robotic technology enhances service improvisation, thereby improving service recovery performance.
Authors
- Hung-Sheng Chang (ORCID: https://orcid.org/0009-0007-3750-8704)
- Yao‐Chin Wang (ORCID: https://orcid.org/0000-0001-7949-7977)
- Da-Chian Hu (ORCID: https://orcid.org/0000-0001-6380-563X)
- Sheng-Fang Chou (ORCID: https://orcid.org/0000-0002-8860-0830)
- Jeou‐Shyan Horng (ORCID: https://orcid.org/0000-0003-4411-4328)
- Yung‐Chuan Huang (ORCID: https://orcid.org/0000-0002-3847-1452)
- Chih-Hsing Sam Liu (ORCID: https://orcid.org/0000-0003-3225-864X)
- Tai‐Yi Yu (ORCID: https://orcid.org/0000-0002-3821-7040)
Institutions
- Shih Chien University (TW)
- National Kaohsiung University of Hospitality and Tourism (TW)
- Ming Chuan University (TW)
- University of Florida (US)
- National Kaohsiung University of Science and Technology (TW)
Publication Details
- Journal
- Journal of Hospitality & Tourism Research
- Published
- 2025-05-10
- DOI
- https://doi.org/10.1177/10963480251336988
- Citations
- 1
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- National Science and Technology Council