TITLE:
Customers Satisfaction on Robots, Artificial Intelligence and Service Automation (RAISA) in the Hotel Industry: A Comprehensive Review
AUTHORS:
Fei Wu, Nadezda Sorokina, Eka Diraksa Putra
KEYWORDS:
Robots, Artificial Intelligence, Service Automation, Customer Satisfaction, Hotel Industry
JOURNAL NAME:
Open Journal of Business and Management,
Vol.11 No.3,
May
31,
2023
ABSTRACT: Due to the 4th Industrial Revolution, Artificial
Intelligence and other internet technologies such as RAISA (Robots, Artificial
Intelligence and Service Automation) have been adopted in various industries,
including the hospitality and tourism industry. As the industry traditionally
offers services through manual labor force, more companies adopt RAISA through
a commercial service in the form of chatbots, delivery robots, robot concierge,
conveyor restaurants, self-service information/check-in/check-out kiosks, and
many others. The current academic resources mainly focus on customer perception
or evaluation of robots themselves, and few studies link robot services with
customers’ overall experience of hospitality services. This study aims to evaluate the current status of RAISA studies in the
hotel industry and propose directions for future research. Thirty-seven articles were identified from Google Scholar. These articles were
reviewed from four perspectives, namely, journal/year distribution,
methodology, research context, theoretical foundation. Findings reveal that most studies on RAISA in the hotel industry focus on RAISA’s impacts on
the hotel industry, RAISA service quality, customer acceptance of RAISA
service, customer satisfaction and factors influencing Customers’ Satisfaction
on RAISA Service and quantitative approach is the dominant research method. To
this end, five research directions cover outstanding themes as follows: 1)
strategic assessment of RAISA performance, 2) hotel financial impacts on RAISA
employment, 3) customers’ satisfaction and RAISA service quality, 4) macro
environment impacts on RAISA in hotels, and 5) premium determinants on
customers’ acceptance on RAISA.