scholarly journals Customers’ evaluation of mechanical artificial intelligence in hospitality services: a study using online reviews analytics

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marcello Mariani ◽  
Matteo Borghi
Keyword(s):  
Artificial Intelligence ◽  
Online Reviews ◽  
Service Robots ◽  
Specific Element ◽  
Content Type ◽  
Related Text ◽  
Online Ratings ◽  
Hotel Service ◽  
Hotel Managers ◽  
Service Interactions

Purpose This paper aims to analyze if and to what extent mechanical artificial intelligence (AI)-embedded in hotel service robots-influences customers’ evaluation of AI-enabled hotel service interactions. This study deploys online reviews (ORs) analytics to understand if the presence of mechanical AI-related text in ORs influences customers’ OR valence across 19 leading international hotels that have integrated mechanical AI – in the guise of service robots – into their operations. Design/methodology/approach First, the authors identified the 19 leading hotels across three continents that have pioneered the adoption of service robots. Second, by deploying big data techniques, the authors gathered the entire population of ORs hosted on TripAdvisor (almost 50,000 ORs) and generated OR analytics. Subsequently, the authors used ordered logistic regressions analyses to understand if and to what extent AI-enabled hospitality service interactions are evaluated by service customers. Findings The presence of mechanical AI-related text (text related to service robots) in ORs influences positively electronic word-of-mouth (e-WOM) valence. Hotel guests writing ORs explicitly mentioning their interactions with the service robots are more prone to associate high online ratings to their ORs. The presence of the robot’s proper name (e.g., Alina, Wally) in the OR moderates positively the positive effect of mechanical AI-related text on ORs ratings. Research limitations/implications Hospitality practitioners should evaluate the possibility to introduce service robots into their operations and develop tailored strategies to name their robots (such as using human-like and short names). Moreover, hotel managers should communicate more explicitly their initiatives and investments in AI, monitor AI-related e-WOM and invest in educating their non-tech-savvy customers to understand and appreciate AI technology. Platform developers might create a robotic tag to be attached to ORs mentioning service robots to signal the presence of this specific element and might design and develop an additional service attribute that might be tentatively named “service robots.” Originality/value The current study represents the first attempt to understand if and to what extent mechanical AI in the guise of hotel service robots influences customers’ evaluation of AI-enabled hospitality service interactions.

The role of key online reviews in affecting online hotel booking: an empirical investigation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dong Zhang ◽  
Pengkun Wu ◽  
Chong Wu
Keyword(s):  
Binary Logistic Regression ◽  
Online Reviews ◽  
Limited Attention ◽  
Content Type ◽  
Factors Affecting ◽  
Mediating Role ◽  
Antecedents And Consequences ◽  
Hotel Managers ◽  
Hotel Booking

Purpose The importance of online reviews on online hotel booking has been widely acknowledged. However, not all online reviews affect consumers equally. Compared with common online reviews, key online reviews (KORs) have a greater influence on consumers' decisions and online hotel booking. This study takes the first step to investigate the factors affecting the identification of KORs and the role of KORs in online hotel booking.Design/methodology/approach To test the research hypotheses, this study develops a crawler to obtain 551,600 online reviews of 650 hotels in ten representative large cities in China. This study first uses a binary logistic regression to identify KORs by combining review content quality and reviewer characteristics and then uses a log-regression model to investigate the role of KORs in online hotel booking.Findings This study mined the factors affecting the identification of KORs by analyzing review contents and reviewer characteristics. Our results revealed that KORs play a mediating role in the effects of review content and reviewer characteristics on online hotel booking.Originality/value This study focuses on KORs, which have received limited attention in research but are important to practitioners. Specifically, this study investigates the antecedents and consequences of KORs. Our results enable hotel managers to manage online reviews effectively, particularly KORs.

scholarly journals Exploring the behavioral drivers of review valence

2018 ◽  
Vol 30 (10) ◽  
pp. 3083-3099 ◽  
Author(s):  
Panagiotis Stamolampros ◽  
Nikolaos Korfiatis
Keyword(s):  
Information Content ◽  
Service Providers ◽  
Online Reviews ◽  
The Other ◽  
Three Dimensions ◽  
Spatial Distance ◽  
Bag Of Words ◽  
Content Type ◽  
Online Ratings ◽  
Positive Direct

Purpose Although the literature has established the effect of online reviews on customer purchase intentions, the influence of psychological factors on online ratings is overlooked. This paper aims to examine these factors under the perspective of construal level theory (CLT). Design/methodology/approach Using review data from TripAdvisor and Booking.com, the authors study three dimensions of psychological distances (temporal, spatial and social) and their direct and interaction effects on review valence, using regression analysis. The authors examine the effect of these distances on the information content of online reviews using a novel bag-of-words model to assess its concreteness. Findings Temporal distance and spatial distance have positive direct effects on review valence. Social distance, on the other hand, has a negative direct effect. However, its interaction with the other two distances has a positive effect, suggesting that consumers tend to “zoom-out” to less concrete things in their ratings. Practical implications The findings provide implications for the interpretation of review ratings by the service providers and their information content. Originality/value This study extends the CLT and electronic word-of-mouth literature by jointly exploring the effect of all three psychological distances that are applicable in post-purchase evaluations. Methodologically, it provides a novel application of the bag-of-words model in evaluating the concreteness of online reviews.

The effect of online reviews on restaurant visit intentions: applying signaling and involvement theories

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Leonardo Aureliano-Silva ◽  
Xi Leung ◽  
Eduardo Eugênio Spers
Keyword(s):  
Mobile Devices ◽  
Signaling Theory ◽  
Online Reviews ◽  
Future Research ◽  
Online Behavior ◽  
Content Type ◽  
Customer Involvement ◽  
Online Ratings ◽  
Involvement Theory ◽  
Restaurant Reviews

Purpose The purpose of this study is to investigate the effect of online reviews on consumers’ intention to visit restaurants, with the moderating role of involvement. Design/methodology/approach The research framework was built on signaling theory, message appeals and involvement theory. To test the proposed framework, three experiments were conducted online with real customer samples. T-tests, ANOVA and SPSS PROCESS macro were used for data analysis. Findings The results revealed that online reviews with higher online ratings and emotional appeal led to higher restaurant visit intention. Review appeal significantly moderated the effect of online ratings on restaurant visit intention. Customers with low restaurant involvement were more impacted by emotional comments than by functional comments. Research limitations/implications The present study extends our knowledge on the effects of online reviews moderated by levels of customer involvement. By combining signaling theory with involvement theory, it adds value to the literature on customer online behavior, especially in the foodservice context. The present study has limitations that might provide opportunities for future research. It used evaluations (TripAdvisor scores) and only positive reviews (texts), so customers’ intentions considering negative reviews could not be examined. The level of hedonism concerning consumption in restaurants and prior knowledge regarding restaurant reviews was not controlled for. It is possible that the level of hedonism perceived and prior review knowledge may moderate the customers’ intention to visit the restaurant. Practical implications The present study shows the importance of online comments for the promotion of restaurants that have low evaluation scores. It is essential that restaurant owners and managers encourage potential customers by using comments to elaborate on their marketing strategies and promotion. At the same time, they should invite customers to share their emotional experiences, and not just their views on service efficiency (a functional aspect). During the COVID-19 pandemic, the use of the internet and mobile devices has become more prominent. Managers could therefore use emotional messages on the restaurant’s website or apps to attract customers with low restaurant involvement. Also, a system to identify the involvement of customers with restaurants could be implemented online or on mobile devices to present specific messages. The present study also recommends the use of online tools as virtual tours, photographs taken from different angles, smiling faces, floor plans and sittings and pre-determined emotional expressions. Also, the restaurant could promote lives on cooking different dishes to motive customer’s interaction and comments. These would help to increase customers’ visit intentions. Originality/value This study extends knowledge about the effect of restaurant online reviews (both ratings and appeals) moderated by the level of customer involvement. The present study also adds value to the customer online behavior literature showing that customers with low involvement are more sensitive to emotional content as they use the affective route to process information rather than the central route.

Tit for tat: understanding the responding behavior of property hosts on peer-to-peer rental platforms

2021 ◽  
Vol 33 (3) ◽  
pp. 1105-1126
Author(s):  
Sai Liang ◽  
Xiaoxia Zhang ◽  
Chunxiao Li ◽  
Hui Li ◽  
Xiaoyu Yu
Keyword(s):  
Service Providers ◽  
Online Reviews ◽  
Peer To Peer ◽  
Theoretical Development ◽  
Effective Response ◽  
Content Type ◽  
Starting Point ◽  
Tit For Tat ◽  
Hotel Managers ◽  
The Impact

Purpose Due to their very different contexts, the responses made by property hosts to online reviews can differ from those posted by hotel managers. Thus, the purpose of this study is to investigate the determinants of the responding behavior of hosts on peer-to-peer property rental platforms. Design/methodology/approach This study applied a comprehensive framework based on the theory of planned behavior. Empirical models are constructed based on 89,967 guest reviews with their associated responses to reveal the responding pattern of property hosts. Findings Unlike hotel managers, property hosts are more likely to reply to positive than to negative reviews; moreover, when they do choose to respond to negative reviews, they are likely to do so negatively, in a “tit-for-tat” way. This study also finds that one reason for the difference of responding patterns between property hosts and hotel managers is the hosts’ lack of experience of consumer relationship management and service recovery. Research limitations/implications This study provides a good start point for future theoretical development regarding effective responding strategy on peer-to-peer property rental platforms, as well as some useful implications for practitioners. Originality/value This study is an early attempt to analyze the impact of the particularity of emerging platforms on the responding behavior of service providers based on a comprehensive conceptual framework and empirical model thus provides a good starting point for the further investigation of effective response strategies on these emerging platforms.

Negative Customer Experience in Lifestyle Hotels

2021 ◽  
pp. 126-157
Author(s):  
Manoel Vitor Santos ◽  
Amélia M. P. C. Brandão
Keyword(s):  
Social Networks ◽  
Text Mining ◽  
Consumer Behaviour ◽  
Online Reviews ◽  
Customer Experience ◽  
Customer Complaints ◽  
Online Platforms ◽  
Hotel Service ◽  
Hotel Managers

The primary purpose of the present research is to develop a methodology which can accurately analyse online public reviews on Google using Netnography studies combined with text mining analyses. By analysing the current techniques applied to a lifestyle hotel brand in nine properties in different countries and carefully studying how negative reviews are expressed online by costumers, this study aims to create a pattern of lifestyle customer complaints. This research seeks to demonstrate patterns of consumer behaviour that are not fully satisfied with the hotel service and how it can negatively affect the brand. This study identifies the areas that five stars lifestyle hoteliers and hotel managers need to pay attention to improve services, considering online reviews on online platforms, such as social networks and other tourism sites. Today, online reviews and customer experiences have a significant impact on the choice of a hotel.

Construction and empirical research on acceptance model of service robots applied in hotel industry

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lina Zhong ◽  
Xiaoya Zhang ◽  
Jia Rong ◽  
Hing Kai Chan ◽  
Jinyu Xiao ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Technology Acceptance ◽  
Empirical Research ◽  
Hotel Industry ◽  
Perceived Value ◽  
Service Robots ◽  
Content Type ◽  
Hotel Service ◽  
Acceptance Model ◽  
Robot Selection

PurposeRobots, as the crystallization of new artificial intelligence, are being applied in various fields, especially the hotel industry. They are seizing the opportunities, using technology to improve the overall quality and comprehensive competitiveness. However, they also cause many problems due to practical limitations. The purpose of this paper is to study customers' recognition and acceptance of hotel service robots to guide the successful promotion of this technology.Design/methodology/approachThis paper proposed a comprehensive model based on the theory of planned behavior, the technology acceptance model and then the perceived value-based acceptance model. Exploratory factor analysis, confirmatory factor analysis, grouped regression analysis and path analysis was adopted to validate the impacts of each variable to obtain the final reliable model using data collected from hotel guests using a self-designed questionnaire.FindingsThe empirical research based on the theoretical model shows that the constructed conceptual model can thoroughly explain the influencing factors of hotel robot acceptance, enrich the acceptance theory and provide academic support for the use and popularization of hotel service robots. Among all variables, attitude, usefulness and perceived value are the factors that have the greatest impact on acceptance. They have significant differences in the effects of adjustment variables such as gender, educational level, whether hotel robots have been used, and whether other robot services have been experienced on different paths in the model.Practical implicationsThis paper explored the customer acceptance of service robots in hotels, helped to understand the process of decision-making on service robot selection and contributed to the theoretical extension of the hospitality industry. The work guides hotel management to promote better-personalized products and services of robot technology in the hospitality industries.Originality/valueThe acceptance study on hotel service robots provides insight into the hotel industry to understand customers' attitudes and acceptance of emerging technology.

Reputation management in cyberspace: evidence from Jordan’s luxury hotel market

2019 ◽  
Vol 10 (1) ◽  
pp. 107-120 ◽  
Author(s):  
Zaid Alrawadieh ◽  
Mithat Zeki Dincer
Keyword(s):  
Response Rate ◽  
Online Reviews ◽  
Reputation Management ◽  
Future Research ◽  
Content Type ◽  
Luxury Hotels ◽  
Hotel Managers ◽  
Online Reputation ◽  
Luxury Hotel ◽  
Managerial Response

PurposeDrawing on a sample of 520 negative reviews posted on TripAdvisor against all five-star hotels operating in Petra, Jordan, the purpose of this paper is to evaluate the response of luxury hotels to negative online reviews by considering the Response Rate (RR), the Response Time (RT) and the Response Content (RC).Design/methodology/approachA deductive content analysis was used on hotels’ managerial responses. Based on the literature review, a four-construct scheme was identified to guide the analysis including Appreciation; Apology; Explanation; and Incentive. The managerial responses were carefully read and manually coded based on the four-construct scheme. The time between the review posting date and the date of the managerial response was also recorded. Luxury hotel managers were also surveyed to obtain insights into their perceptions and practices with respect to online reputation management.FindingsThe findings call into question luxury hotels’ awareness of the harmful impact of negative online reviews. Specifically, the findings suggest that less than half of the negative reviews received a managerial response, and that more than half of these were standardized and did not refer to the issues raised in the reviews. The low response rate coupled with the hotel managers’ consensus on the importance of answering all online reviews indicates inconsistency between hotel managers’ perceptions and practices with regard to online reputation management.Originality/valueThe paper adds to the ongoing debate on reputation management in the hospitality industry by considering the managerial response to negative online reviews. The paper discusses several managerial implications for hotel managers as well as avenues for future research.

Hotels’ online reputation management: benefits perceived by managers

2019 ◽  
Vol 31 (2) ◽  
pp. 615-632 ◽  
Author(s):  
Javier Perez-Aranda ◽  
María Vallespín ◽  
Sebastian Molinillo
Keyword(s):  
Measurement Model ◽  
Online Reviews ◽  
Customer Relationship ◽  
Reputation Management ◽  
Content Type ◽  
Order Construct ◽  
Using Data ◽  
Hotel Managers ◽  
Relationship Benefits ◽  
The Impact

PurposeThis study aims to develop a measurement model to help hotels manage their reputation within the context of online reviews and ratings platforms and evaluate the impact of this reputation management on the benefits derived by the hotels, as perceived by their managers.Design/methodology/approachPartial least squares was used to assess the model and make a causal predictive analysis, using data from a survey of a random sample of 335 Spanish hotel managers and personnel involved in reputation management.FindingsThis study shows the operationalization of hotel reputation management as a superordinate second-order construct affecting six individual first-order dimensions, strongly impacting on three key benefits as perceived by hotel managers (i.e. financial benefits, customer relationship benefits and customer-based brand benefits), within the context of online review platforms.Practical implicationsBased on the results of this study, hotel managers can improve the effectiveness of their management of ratings and reviews. They can also learn which aspects they should focus on when managing ratings and reviews.Originality/valueBased on the opinions of hotel managers, a causal model for managing online reviews was developed and validated. This study shows how reputation management affects the benefits derived by hotels as perceived by their managers.

Guests’ perceptions of robot concierge and their adoption intentions

2020 ◽  
Vol 32 (8) ◽  
pp. 2613-2633 ◽  
Author(s):  
Hyejo Hailey Shin ◽  
Miyoung Jeong
Keyword(s):  
Design Methodology ◽  
Hotel Industry ◽  
Service Robots ◽  
Service Encounter ◽  
Design Experiment ◽  
Service Encounters ◽  
Content Type ◽  
Hotel Service ◽  
Factorial Design Experiment ◽  
Different Levels

Purpose The hotel industry has witnessed an increasing number of service automation through service robots such as robot concierges. However, few studies have documented how to identify how hotel guests perceive a robot concierge for their service encounter. Therefore, the purpose of this study is to examine the effects of robot concierges on hotel guests’ attitudes and adoption intentions of robot concierges. Design/methodology/approach This study investigated the effects of robot concierges’ morphology and their level of interactivity with guests at different levels of hotel service on guests’ attitudes and their intentions to adopt robot concierges. To achieve the study’s objectives, this study conducted a 3 × 2 × 3 between-subjects factorial design experiment. Moreover, the survey asked questions about subjects’ preferences of their service encounters (e.g. human employees, robot concierges and/or no preference) and reasons for their selected preference. Findings The results demonstrated that the robot’s morphology significantly influenced guests’ attitudes toward robot concierges. In particular, the caricatured robot was the most preferred morphology of robot concierges. The findings showed that even if guests had favorable attitudes toward robot concierges, they preferred human employees to robot concierges because of humans’ sincere and genuine interactions. Originality/value This study contributes to the literature by investigating the causal impacts of the morphology of robot concierges, level of interactivity and level of hotel service on guests’ attitudes toward robot concierges. The thematic analysis of service encounter preference provides an overview of the factors that guests expect for their service encounters in a hotel setting.

Dimensions of wine hotel experiences shared online

2019 ◽  
Vol 32 (1) ◽  
pp. 59-77 ◽  
Author(s):  
Ana Brochado ◽  
Mike Troilo ◽  
Helena Rodrigues ◽  
Fernando Oliveira-Brochado
Keyword(s):  
Market Segmentation ◽  
Food Service ◽  
Online Reviews ◽  
Tourism Industry ◽  
Content Type ◽  
Wine Tourism ◽  
Tourism Experience ◽  
Hotel Managers ◽  
Practical Implications ◽  
Present Understanding

Purpose The purpose of this study sought to identify the main themes linked with wine hotel experiences, based on tourists’ narratives shared online, and to investigate whether these narratives vary according to traveler type. Design/methodology/approach Content analysis was carried out on 4,114 online reviews of 52 wine hotels located in 27 wine regions across 11 nations in both the Old and New World. Findings The analysis of these web reviews revealed that narratives can be grouped under 11 themes organized into 7 main dimensions as follows: wine, lodging (i.e. hotel, area and room), food service (i.e. restaurant and breakfast), scenery (i.e. views and vineyards), staff, transportation and recommendation. The main narratives vary according to traveler type. Practical implications Improving the present understanding of wine tourists’ experiences should help wine hotel managers find new approaches to enhancing visitors’ satisfaction. As the dimensions of wine tourism experiences shared online vary according to traveler type, wine managers can design their offer to target families, couples, friends, solo and corporate clients. Originality/value Prior research has identified the need for market segmentation in the wine tourism industry. This research addresses this need by specifying the wine tourism experience according to traveler type. The breadth of the data, and the method of using travelers’ own testimony as opposed to more common surveying are additional contributions for both academics and managers.

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