Exploring the Attractiveness of Service Robots in the Hospitality Industry: Analysis of Online Reviews

Author(s):  
Hyunsun Park ◽  
Shan Jiang ◽  
One-Ki Daniel Lee ◽  
Younghoon Chang
Author(s):  
Jifei Wu ◽  
Xiangyun Zhang ◽  
Yimin Zhu ◽  
Grace Fang Yu-Buck

The purpose of this study was to examine the effect of the COVID-19 pandemic on customer–robot engagement in the Chinese hospitality industry. Analysis of a sample of 589 customers using service robots demonstrated that the perceived risk of COVID-19 has a positive influence on customer–robot engagement. The positive effect is mediated by social distancing and moderated by attitudes towards risk. Specifically, the mediating effect of social distancing between the perceived risk of COVID-19 and customer–robot engagement is stronger for risk-avoiding (vs. risk-seeking) customers. Our results provide insights for hotels when they employ service robots to cope with the shock of COVID-19 pandemic.


2020 ◽  
Vol 63 ◽  
pp. 101423
Author(s):  
João Reis ◽  
Nuno Melão ◽  
Juliana Salvadorinho ◽  
Bárbara Soares ◽  
Ana Rosete

2017 ◽  
Vol 8 ◽  
pp. 40-54
Author(s):  
Julia Beck ◽  
Margarita Danilenko ◽  
Laura Sperber ◽  
Brenda Wiersma ◽  
Roman Egger

The impact of online reviews on guests, hotel owners and other parties is growing in importance. In reference to online reviews, service quality plays a crucial role in hotel diff erentiation and influencing the choice of accommodation made by travellers. Thus, online reviews represent a valuable source of information about perceived service, that has not been fully exploited yet. This research paper attempts to look more closely at this extensive body of data. The authors have conceptualized a tool that assists governmental institutions, DMOs and investors in decision making. This tool accumulates intelligent data and provides a comprehensive overview of the Austrian hospitality industry and its service quality standards. It allows the user to conduct specific queries on how a certain dimension of service quality is perceived. The results can be either visualized on a density map or extracted as a structured .csv file for further analysis.The GAZE Journal of Tourism and Hospitality Vol. 8, 2017, page: 40-54


2018 ◽  
Vol 60 (3) ◽  
pp. 216-232 ◽  
Author(s):  
Robin Chark ◽  
Lawrence Hoc Nang Fong ◽  
Candy Mei Fung Tang

We examine how consumers’ desire to be different reduces their reliance on others’ suggestions and thus increases their tendency to diverge from the average opinion. While the extant literature focuses on the role of need for uniqueness in attitude formation and choice behavior, not much has been done to test the effect of uniqueness seeking on reactions to persuasive, word of mouth (WoM) messages. In four studies, we find converging evidence for a uniqueness effect. Specifically, the uniqueness motivation interacts with the valence of the average opinion such that when uniqueness motivation is low, consumers follow others’ advice and thus their attitudes depend primarily on the valence of the average opinion; meanwhile, the uniqueness seekers rely less on the valence and are more likely to form less favorable attitudes after reading positive reviews and to hold less unfavorable ones when the reviews are negative. These effects are found when trait need for uniqueness is measured as well as when situational need for uniqueness is manipulated. We further examine the process through which uniqueness motivation results in nonconformist attitudes. Uniqueness seekers perceive minority opinions as more diagnostic. Thus, these minority opinions are disproportionately represented in uniqueness seekers’ nonconformist views. These findings are important to the hospitality industry as consumers often rely on others’ experiences by reading online reviews to help make decisions concerning their own hospitality needs, which are highly experiential in nature.


2021 ◽  
Vol 10 (2) ◽  
pp. 13
Author(s):  
Ayse Begum Ersoy ◽  
Ziqi Cui

Since the coronavirus disease 2019(COVID-19) has had brought severe impact on all aspects of the world. A series of interpersonal distancing methods such as ensuring effective and safe social distancing among people, wearing masks, and traffic lockdown measures are also continuing to take effect to curb the continuing outbreak of the COVID-19 (“Advice for the public on COVID-19”, 2020). In response to the globally spread of COVID-19, many advanced technologies in the field of Artificial Intelligence (AI) were applied rapidly and played an essential role in the operation for several months. There are many different leading technology categories in the field of artificial intelligence and many different sub-categories within each main technology categories. Moreover, since the AGI technology does not yet reach the basic human intelligence level, this study will focus on the impact of service robots, which are already widely used in the NAI application category, on hospitality marketing in the current situation in China. In this paper the aim is to assess the effectiveness of use of service robots in Marketing Hospitality Industry during the pandemic through a quantitative study.


Author(s):  
Ana Rosete ◽  
Barbara Soares ◽  
Juliana Salvadorinho ◽  
João Reis ◽  
Marlene Amorim

2019 ◽  
Vol 10 (4) ◽  
pp. 493-511 ◽  
Author(s):  
Victor Ho

Abstract The present study explores the discursive practice of the hospitality industry in addressing competence-based, benevolence-based, and integrity-based accusations of trust violation made by dissatisfied customers on TripAdvisor. Authentic negative online reviews written by dissatisfied customers and the corresponding responses by hotel management downloaded directly from TripAdvisor are analyzed qualitatively with Nvivo10. Results show that hotel management has the strongest preference for apology, followed by implicit denial and then explicit denial when dealing with the three different types of accusations of trust violation. The findings will enhance our understanding of trust and its repair, and benefit hospitality practitioners responsible for handling online criticisms and complaints.


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