Employees' perception of robots and robot-induced unemployment in hospitality industry under COVID-19 pandemic

M Omar Parvez; Ali Öztüren; Cihan Cobanoglu; Huseyin Arasli; Kayode K Eluwole

doi:10.1016/j.ijhm.2022.103336

Employees' perception of robots and robot-induced unemployment in hospitality industry under COVID-19 pandemic

Int J Hosp Manag. 2022 Oct:107:103336. doi: 10.1016/j.ijhm.2022.103336. Epub 2022 Sep 6.

Authors

M Omar Parvez¹, Ali Öztüren², Cihan Cobanoglu^{1

3}, Huseyin Arasli⁴, Kayode K Eluwole⁵

Affiliations

¹ Muma College of Business, University of South Florida, USA.
² Faculty of Tourism, Eastern Mediterranean University, TRNC, Famagusta, Turkey.
³ National Kaohsiung University of Hospitality and Tourism, Taiwan.
⁴ University of Stavanger, Norway.
⁵ Department of Gastronomy and Culinary Arts, Faculty of Fine Arts, Istanbul Gelisim University, Turkey.

Abstract

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.

Keywords: Hospitality; Perception of robots; Robot-induce unemployment; Service robots; Tourism.