Exploring the relationship between robot employees' perceptions and robot-induced unemployment under COVID-19 in the Jordanian hospitality sector
The topic of robots is gaining traction in both academic discourse and popular media due to their growing prevalence in the hospitality sector. The hospitality industry is likely to encounter practical challenges in adopting the increased use of robots. The primary objective of the present...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Growing Science
2023-01-01
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| Series: | International Journal of Data and Network Science |
| Online Access: | http://www.growingscience.com/ijds/Vol7/ijdns_2023_128.pdf |
| Summary: | The topic of robots is gaining traction in both academic discourse and popular media due to their growing prevalence in the hospitality sector. The hospitality industry is likely to encounter practical challenges in adopting the increased use of robots. The primary objective of the present research was to conduct an empirical investigation into a theoretical framework that explores how employees view robot-caused unemployment, with particular attention given to their perceptions of robot adoption. The study utilised structural equation modelling to analyse data obtained from 401 service employees in Jordan through online questionnaires. The findings indicate that the perception of robot-induced unemployment among employees is significantly influenced by their social skills, perceived risk, awareness, and trust in using service robots. The present study established a theoretical framework for investigating user perceptions of robot-induced unemployment within the particular setting of hospitality robots. The findings offer valuable insights for guiding future development and research efforts in the hotel service robot industry as well as informing marketing strategies for hotel managers. Ultimately, these efforts may contribute to the sustainable growth of service robots and associated sectors, including the hotel service sector. |
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| ISSN: | 2561-8148 2561-8156 |