Employees’ perception of robots and robot-induced unemployment in hospitality industry under COVID-19 pandemic
The impact of the pandemic is driving the recent upsurge in service automation and the adoption of service robots in the hospitality industry. As service paradigm and customer expectations shift from conventional customized and personalized services towards a digitalized service environment, such cu...
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Veröffentlicht in: | International journal of hospitality management 2022-10, Vol.107, p.103336-103336, Article 103336 |
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Sprache: | eng |
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Zusammenfassung: | The impact of the pandemic is driving the recent upsurge in service automation and the adoption of service robots in the hospitality industry. As service paradigm and customer expectations shift from conventional customized and personalized services towards a digitalized service environment, such customer orientation may favor using service robots at scales that could render service employees redundant. This study aims to answer the above question by investigating service employees’ perceptions of service robots. Data solicited from 405 service employees in the United States of America via Amazon’s MTurk were analyzed using structural equation modeling. The result revealed that employees’ awareness of adopting and using service robots significantly impacts their perception of robot-induced unemployment. Further, results indicated that the perception of robots’ social skills significantly influences service employees’ perception of robot-induced unemployment. Employee status was found to moderate the relationships mentioned above. Specifically, entry-level employees perceive the unemployment risk more than managers.
•Technological expansion and pandemic disruption has distressed employees psychologically.•Employees attitudes toward robots designate the employees perceived (positive or negative) experience.•Pandemic disruption may accelerate the use of service robots in hospitality but upsurge the robot induce-unemployment.•Entry-level employees have been extremely obstructed by the use of service robots and other technical devices. |
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ISSN: | 0278-4319 1873-4693 |
DOI: | 10.1016/j.ijhm.2022.103336 |