DOI QR코드

DOI QR Code

Determinants of Hotel Customers' Use of the Contactless Service: Mixed-Method Approach

호텔 고객의 비대면 서비스 이용의도의 영향요인에 대한 연구

  • Chung, Hee Chung (Smart Tourism Research Center, Kyung Hee University) ;
  • Koo, Chulmo (Smart Tourism Education Platform, Kyung Hee University) ;
  • Chung, Namho (Smart Tourism Education Platform, Kyung Hee University)
  • 정희정 (경희대학교 스마트관광연구소) ;
  • 구철모 (경희대학교 스마트관광원) ;
  • 정남호 (경희대학교 스마트관광원)
  • Received : 2021.08.13
  • Accepted : 2021.09.19
  • Published : 2021.09.30

Abstract

The development of information and communication technology and COVID-19 have caused an unusual change in the hotel industry, and the demand for the contactless services such as service robots from hotel customers has surged. Therefore, this study investigates the perception of hotel customers on contactless services by applying a mixed-method analysis. Specifically, this study identified the causal correlations between variables through the structural equation model, and further applied the fuzzy set qualitative comparison analysis to derive patterns of variables that form the intention to use the non-face-to-face services. As a result of the analysis, it was shown that service experience co-creation, palyfulness, personalization, and trust had a significant effect on intention to use through the contactless service use desire. On the other hand, in the results of fuzzy-set qualitative comparison analysis, playfulness was derived as a core factor in all patterns. Based on these analysis results, this study provides academic basis for in-depth understanding of hotel customers' perception of contactless service and specific guidelines for hotel managers on the contactless service strategies in the era of COVID-19 pandemic.

정보통신기술의 발달과 코로나19는 호텔산업에 이례적인 변화를 불러일으켰고, 호텔 고객들의 서비스 로봇과 같은 비대면 서비스에 대한 수요가 급증하였다. 이에 본 연구는 혼합분석기법을 적용하여 호텔 고객의 비대면 서비스에 대한 인식을 조사하고자 한다. 구체적으로 본 연구는 구조방정식모형을 통해 변수들간의 상관관계를 파악하였으며, 나아가 퍼지셋 질적 비교 분석 기법을 적용하여 비대면 서비스를 제공하는 호텔 이용의도를 형성하는 변수들의 패턴을 도출하였다. 분석결과, 서비스 경험 공동창출, 즐거움, 개인화 그리고 신뢰가 비대면 서비스 이용욕구를 거쳐 이용의도에 유의한 영향을 미치는 것으로 나타난 반면에, 퍼지셋 질적 비교 분석 방법에서는 도출된 모든 패턴에서 즐거움이 핵심 요인으로 도출되었다. 이러한 분석결과를 토대로 본 연구는 호텔 고객의 비대면 서비스에 대한 심도 있는 이해를 위한 학술적 근거를 제시하였으며, 호텔 매니저들에게 위드 코로나 시대에 비대면 서비스 전략에 대한 구체적인 가이드라인을 제시하였다.

Keywords

Acknowledgement

이 논문은 2019년 대한민국 교육부와 한국연구재단의 지원을 받아 수행된 연구임(NRF-2019S1A3A2098438)

References

  1. 김동준, 최현준, 조환기, 김광용 (2020). 코로나팬더믹 이후 관광산업 발전방안 연구. 호텔경영학연구, 29(4), 129-144.
  2. 배영임, 신혜리 (2020). 코로나 19, 언택트 사회를 가속화하다. 이슈 & 진단, 416, 1-26.
  3. 손맥, 조은영, 김희웅 (2014). e 러닝 성공 평가에 관한 연구. 지식경영연구, 15(2), 67-88.
  4. 윤혜정, 전택준, 이중정 (2014). SNS 소외감과 애착이 능동적 사용에 미치는 영향: 페이스북 사용자를 중심으로. 지식경영연구, 15(4), 171-187. https://doi.org/10.15813/kmr.2014.15.4.009
  5. 이현애, 정희정, 함주연, 정남호 (2019). 퍼지셋 질적 비교 분석 (fsQCA) 을 활용한 관광지 거주민들의 삶의 질 저하에 영향을 미치는 요인 연구. Information Systems Review, 21(1), 113-133. https://doi.org/10.14329/isr.2019.21.1.113
  6. 전유정 (2018). 항공사 셀프 체크인 서비스품질이 사용 의도에 미치는 영향: 웹.모바일 체크인을 중심으로. e-비즈니스연구, 19(1), 93-106.
  7. 조호현 (2021). 서비스 생태시스템 관점에서의 비대면서비스에 관한 탐색적 연구. 한국항공경영학회지, 19(1), 3-19. https://doi.org/10.30529/AMSOK.2021.19.1.001
  8. Ahn, J. A., & Seo, S. (2018). Consumer responses to interactive restaurant self-service technology (IRSST): The role of gadget-loving propensity. International Journal of Hospitality Management, 74, 109-121. https://doi.org/10.1016/j.ijhm.2018.02.020
  9. Bae, S. Y., & Chang, P. J. (2021). The effect of coronavirus disease-19 (COVID-19) risk perception on behavioural intention towards 'untact'tourism in South Korea during the first wave of the pandemic (March 2020). Current Issues in Tourism, 24(7), 1017-1035. https://doi.org/10.1080/13683500.2020.1798895
  10. Chen, T., Guo, W., Gao, X., & Liang, Z. (2020). AI-based self-service technology in public service delivery: User experience and influencing factors. Government Information Quarterly, 101520.
  11. Cho, S. H., & Park, K. H. (2014). A study on service process modeling for the performance of the non-face-to-face call center. Journal of Digital Convergence, 12(1), 149-161. https://doi.org/10.14400/JDPM.2014.12.1.149
  12. Glushko, R. J., & Nomorosa, K. J. (2013). Substituting information for interaction: A framework for personalization in service encounters and service systems. Journal of Service Research, 16(1), 21-38. https://doi.org/10.1177/1094670512463967
  13. Jeong, M., & Shin, H. H. (2019). Tourists' experiences with smart tourism technology at smart destinations and their behavior intentions. Journal of Travel Research, 0047287519883034.
  14. Le, D., & Phi, G. (2021). Strategic responses of the hotel sector to COVID-19: Toward a refined pandemic crisis management framework. International Journal of Hospitality Management, 94, 102808. https://doi.org/10.1016/j.ijhm.2020.102808
  15. Lee, C. K., Song, H. J., Bendle, L. J., Kim, M. J., & Han, H. (2012). The impact of non-pharmaceutical interventions for 2009 H1N1 influenza on travel intentions: A model of goal-directed behavior. Tourism Management, 33(1), 89-99. https://doi.org/10.1016/j.tourman.2011.02.006
  16. Liu, C., & Hung, K. (2021). A multilevel study on preferences for self-service technology versus human staff: Insights from hotels in China. International Journal of Hospitality Management, 94, 102870. https://doi.org/10.1016/j.ijhm.2021.102870
  17. McCartney, G., & McCartney, A. (2020). Rise of the machines: Towards a conceptual service-robot research framework for the hospitality and tourism industry. International Journal of Contemporary Hospitality Management, 32(12), 3835-3851. https://doi.org/10.1108/IJCHM-05-2020-0450
  18. Moon, H. G., Lho, H. L., & Han, H. (2021). Self-check-in kiosk quality and airline non-contact service maximization: How to win air traveler satisfaction and loyalty in the post-pandemic world? Journal of Travel & Tourism Marketing, 38(4), 383-398. https://doi.org/10.1080/10548408.2021.1921096
  19. Olya, H. G., Shahmirzdi, E. K., & Alipour, H. (2019). Pro-tourism and anti-tourism community groups at a world heritage site in Turkey. Current Issues in Tourism, 22(7), 763-785. https://doi.org/10.1080/13683500.2017.1329281
  20. Piccoli, G., Lui, T. W., & Grun, B. (2017). The impact of IT-enabled customer service systems on service personalization, customer service perceptions, and hotel performance. Tourism Management, 59, 349-362. https://doi.org/10.1016/j.tourman.2016.08.015
  21. Sollner, M., & Pavlou, P. A. (2016). A longitudinal perspective on trust in IT artefacts. Research Paper, ECIS Proceedings.
  22. Tan, F. B., & Chou, J. P. (2008). The relationship between mobile service quality, perceived technology compatibility, and users' perceived playfulness in the context of mobile information and entertainment services. International Journal of Human-Computer Interaction, 24(7), 649-671. https://doi.org/10.1080/10447310802335581
  23. Tung, V. W. S., & Law, R. (2017). The potential for tourism and hospitality experience research in human-robot interactions. International Journal of Contemporary Hospitality Management, 29(10), 2498-2513. https://doi.org/10.1108/IJCHM-09-2016-0520
  24. Weijters, B., Rangarajan, D., Falk, T., & Schillewaert, N. (2007). Determinants and outcomes of customers' use of self-service technology in a retail setting. Journal of Service Research, 10(1), 3-21. https://doi.org/10.1177/1094670507302990
  25. Wu, H. C., & Cheng, C. C. (2020). Relationships between experiential risk, experiential benefits, experiential evaluation, experiential co-creation, experiential relationship quality, and future experiential intentions to travel with pets. Journal of Vacation Marketing, 26(1), 108-129. https://doi.org/10.1177/1356766719867371
  26. 김민선 (2019, 1월 16일). 4년 전 로봇 고용한 日 호텔, 절반 해고. ZDnet Korea, https://zdnet.co.kr/view/?no=20190116094545
  27. 홍승주 (2021, 5월 16일). 로봇 직원, 호텔리어들의 서비스 동료로 떠오르다-호텔업계 속 로봇. 호텔&레스토랑, https://hotelrestaurant.co.kr/news/article.html?no=9001