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21 – 30 of over 2000Elise Wong, S. Mostafa Rasoolimanesh and Saeed Pahlevan Sharif
This study aims to investigate the relationships between service quality, perceived value and hotel guest satisfaction, drawing upon data from TripAdvisor – an online travel agent…
Abstract
Purpose
This study aims to investigate the relationships between service quality, perceived value and hotel guest satisfaction, drawing upon data from TripAdvisor – an online travel agent (OTA) platform. The study also investigates the mediating role of perceived value on the relationship between service quality and satisfaction, as well as the moderating role of hotel star ratings on all direct and indirect relationships.
Design/methodology/approach
Data for this study were collected via Web scraping from August–October 2018. Data were collected from 192 three- to five star-rated hotels in Kuala Lumpur, Malaysia. Partial least squares – structural equation modeling was used for data analysis. Furthermore, importance-performance map analysis (IPMA) was performed to identify the most important items of service quality and perceived value in improving customer satisfaction.
Findings
The findings of this study provide support for all direct and indirect relationships for three-star and four- and five-star hotels. Moreover, the results indicate that perceived value mediates the relationship between service quality and customer satisfaction. These results support the moderating role of hotel star ratings for the relationship between service quality and perceived value. The results also show that after perceived value, three-star hotels looking to improve customer satisfaction should prioritize improving the quality of their services, sleep quality, cleanliness and rooms. Four- and five-star hotels, on the other hand, should prioritize service, cleanliness, room and sleep quality.
Originality/value
OTA platforms collect a wealth of data pertaining to large number of hotels; nevertheless, few studies to date have drawn on this data to examine a pre-determined conceptual framework developed based on the literature. As such, this study makes a valuable methodological contribution to the tourism and hospitality literature. In terms of theoretical contributions, this study examines the mediating role of perceived value between service quality and satisfaction using OTA data. In addition, this study assesses the moderating role of hotel star ratings for the direct and indirect effects of service quality on satisfaction. Using IPMA, this study compares the importance and performance of service quality indicators to generate satisfaction between three-star and four- and five-star hotels.
研究目的
本论文检测了服务质量、价值感知、和酒店顾客满意度之间的关系, 使用TripAdvisor的数据—OTA。本论文还检测了价值感知对服务质量和满意度之间的中介作用, 以及酒店星级评价对其中直接和间接关系的调节作用。.
研究设计/方法/途径
本论文采样通过网络爬虫技术, 截取了2018年八月至十月之间的数据。研究样本为192家马来西亚Kuala Lumpur地区的三星-五星酒店。样本分析方法为PLS-SEM。此外, 本论文采样IPMA分析法来找出提高顾客满意度中的服务质量和价值感知中最重要的因子。.
研究结果
研究结果指出了三星、四星、五星酒店的直接和间接关系。此外, 研究还显示了服务质量和顾客满意度关系的价值感知中介作用。研究结果还指出了酒店星级评价对服务质量和价值感知关系的调节作用。此外, 研究还指出, 除了价值感知, 如果三星酒店想提高顾客满意度, 那么他们应该优先提高其服务质量、睡眠质量、清洁度、和房间。另一方面, 四星和五星酒店应该优先提高其服务质量、清洁度、房间、和睡眠质量。.
研究原创性/价值
OTA平台搜集大量酒店数据, 但是很少作品研究这些数据, 以检测根据文献提出的理论模型。因此, 本论文在方法论上对旅游酒店文献做出宝贵贡献。理论贡献而言, 本论文使用OTA数据检测了价值感知对服务质量和满意度关系之间的中介作用。此外, 本论文检测了酒店星级评价对服务质量和满意度之间直接和间接关系的调节作用。本论文使用IPMA方法, 比较各种服务质量指标的重要性对在三星、四星、五星酒店的提高满意度的不同作用。.
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Heejeong Han, Seunghun Shin, Namho Chung and Chulmo Koo
This paper aims to explain a guest’s purchase decision in Airbnb from the perspective of Aristotle’s appeals. In host-created information, the authors investigate which…
Abstract
Purpose
This paper aims to explain a guest’s purchase decision in Airbnb from the perspective of Aristotle’s appeals. In host-created information, the authors investigate which information appeals are significantly considered by guests.
Design/methodology/approach
It is hypothesized that a guest’s purchase would be affected by the host-created information’s ethos, pathos and logos.
Findings
For the ethos, the super host badge and host review have positive impacts on the purchase; for the pathos, the positive impact of the use of social words is significant. For the logos, the authors have determined that although the price, place picture and star-rating have positive impacts on the likelihood of a purchase, the occupancy has a negative impact on it.
Research limitations/implications
The dependent variable, the number of place reviews, cannot represent the exact number of purchases. Other possible influential factors, such as direct communications between hosts and guests, are not examined.
Practical implications
The findings suggest guidelines for Airbnb and its host users. Specifically, the management of normal host users is revealed as a necessary process for Airbnb’s development. For host users, several guidelines on how to attract more guests effectively are provided.
Originality/value
In contrast to other studies on Airbnb, various pieces of information are considered from holistic perspectives, and each piece’s impact on the sharing behavior is understood by means of a unique theoretical model that is based on Aristotle’s appeals.
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Vikas Gupta, Manohar Sajnani, Saurabh Kumar Dixit, Abhinav Mishra and Mohammad Osman Gani
This study aims to find out the influence of green practices used by the five-star hotels on the guest’s online hotel assessment and their revisit intentions. It also evaluated…
Abstract
Purpose
This study aims to find out the influence of green practices used by the five-star hotels on the guest’s online hotel assessment and their revisit intentions. It also evaluated how the use of green practices by the hotels influenced the guest’s willingness to pay a premium price. Apart from the conventional hotel service attributes, this study also identified some new and innovative services offered by the hotels which have an overall effect on the guest’s revisit intentions.
Design/methodology/approach
This study applied focus group interviews from 12 hotel managers and accessed the hotel’s internal database to identify the latest and innovative service attributes offered by the hotels. The information regarding the green practices offered by the hotels was collected through TripAdvisor and LEED-IGBC website. It identified 10 independent and four dependent variables based on previous literature. Guest’s revisit intentions were measured on a five-point Likert scale. Data was analysed using a multi-step hierarchical regression model.
Findings
The use of green practices by the hotels revealed a positive and significant influence on the guest’s revisit-intentions and their intention to pay a premium price. It was also found that the use of new and innovative green practices has a positive influence on the guest’s overall online evaluation of the hotel.
Practical implications
This study suggests that the amalgamation of green practices along with the conventional service attributes may help in the incremental revisit and online hotel assessment intentions, which might be of use for the managers and hotel policymakers.
Originality/value
Although previous studies have explored the conventional hotel service attributes in the context of Indian Hotel industry, this is one of the first studies which discussed the influence of recent and emerging hotel service attributes on the guest’s revisit and pay a premium price intention. Moreover, the influence of green practices on the guest’s overall online evaluation of the five-star hotels in Delhi was discussed in this study which was not performed before.
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Yang Yang, Michael S. Lin and Vincent P. Magnini
Growing health concerns amid the COVID-19 pandemic have led guests to focus on various aspects of hotel cleanliness. This study aims to investigate whether customers’ perceived…
Abstract
Purpose
Growing health concerns amid the COVID-19 pandemic have led guests to focus on various aspects of hotel cleanliness. This study aims to investigate whether customers’ perceived importance of hotel cleanliness during their stay depends on local pandemic severity and moderators of the pandemic–cleanliness relationship.
Design/methodology/approach
Based on TripAdvisor data from 26,519 reviews in 2020 for 2,024 hotels across the USA, this study evaluated the importance of hotel cleanliness using the estimated coefficient of the cleanliness score in a regression of overall hotel rating scores.
Findings
Results of a multilevel ordered logit model confirmed that a more difficult local pandemic situation rendered cleanliness more important during hotel stays. Additionally, the effect of the pandemic was more pronounced among specific groups: men and travelers with more expertise, and guests staying in hotels without COVID-19 protocols for linen cleaning, with a lower average rating, with a larger size and in a more urbanized location.
Originality/value
This study represents a pioneering effort to assess how pandemics shape people’s (perceived) importance of cleanliness during hotel stays based on revealed data. Despite potential managerial relevance, a number of the moderating variables included in this study, such as traveler expertise and hotel location, have never been studied within the context of cleanliness perceptions during a pandemic.
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This research aims to examine whether the facial appearances and expressions of Airbnb host photos influence guest star ratings.
Abstract
Purpose
This research aims to examine whether the facial appearances and expressions of Airbnb host photos influence guest star ratings.
Design/methodology/approach
This research analyzed the profile photos of over 20,000 Airbnb hosts and the guest star ratings of over 30,000 Airbnb listings in New York City, using machine learning techniques.
Findings
First, hosts who provided profile photos received higher guest ratings than those who did not provide photos. When facial features of profile photos were recognizable, guest ratings were higher than when they were not recognizable (e.g. faces too small, faces looking backward or faces blocked by some objects). Second, a happy facial expression, blond hair and brown hair positively affected guest ratings, whereas heads tilted back negatively affected guest ratings.
Originality/value
This research is the first, to the best of the authors’ knowledge, to analyze the facial appearances and expressions of profile photos using machine learning techniques and examine the influence of Airbnb host photos on guest star ratings.
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Seraina C. Anagnostopoulou, Dimitrios Buhalis, Ioanna L. Kountouri, Eleftherios G. Manousakis and Andrianos E. Tsekrekos
The purpose of this study is to quantify the impact of online customer reputation on financial profitability.
Abstract
Purpose
The purpose of this study is to quantify the impact of online customer reputation on financial profitability.
Design/methodology/approach
Online reputation is captured by extracting the most recurring textual themes associated with customer satisfaction and dissatisfaction, expressed within positive vs negative online guest reviews on Booking.com. Latent semantic analysis is used for textual analysis. Proxies of overall financial performance are manually constructed for the sample hotels, using financial data from the Financial Analysis Made Easy (FAME) database. Ordinary least squares is used to gauge the effect of online customer reputation on financial profitability.
Findings
Empirical findings indicate that recurring textual themes from positive online reviews (in contrast to negative reviews) exhibit a higher degree of homogeneity and consensus. The themes repeated in positive, but not in negative reviews, are found to significantly associate with hotel financial performance. Results contribute to the discussion about the measurable effect of online reputation on financial performance.
Originality/value
Contemporary quantitative methods are used to extract online reputation for a sample of UK hotels and associate this reputation with bottom-line financial profitability. The relationship between online reputation, as manifested within hotel guest reviews, and the financial performance of hotels is examined. Financial profitability is the result of revenues, reduced by the costs incurred in order to be able to offer a given level of service. Previous studies have mainly focused on basic measures of performance, i.e. revenue generation, rather than bottom-line profitability. By combining online guest reviews from travel websites (Booking.com) with financial measures of enterprise performance (FAME), this study makes a meaningful contribution to the strategic management of hotel businesses.
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This study aims to explore how attribute performance and hosts’ service quality attributes affect room sales on peer-to-peer (P2P) platforms from the cue congruence perspective.
Abstract
Purpose
This study aims to explore how attribute performance and hosts’ service quality attributes affect room sales on peer-to-peer (P2P) platforms from the cue congruence perspective.
Design/methodology/approach
More than 9.53 million reviews concerning 258,473 listings located in 35 major cities worldwide were collected from Airbnb. Data was collected from December 2019 to December 2020 and was analysed using a generalised linear model.
Findings
Results show that when attribute performance and hosts’ service quality attributes give positive signals, Airbnb room sales are significantly higher than when the two kinds of cues give inconsistent or negative signals; when attribute performance gives positive signals and hosts’ service quality attributes give negative signals, room sales are higher than when the former gives negative signals and the latter give positive signals; surprisingly, when both kinds of cues give negative signals, room sales are higher than when attribute performance gives positive signals and hosts’ service quality attributes give negative signals.
Research limitations/implications
This paper adds useful insights on understanding of cue congruence (incongruence) effect on room sales of P2P accommodation platforms. This study has practical implications for hosts, online platform managers and guests regarding how to use online strategies and promotions on the Airbnb platform.
Originality/value
This study is an early attempt to explore how the combination of attribute performance and hosts’ service quality attributes affects Airbnb room sales under the conditions of consistency and inconsistency.
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This study aims to understand the satisfaction and needs of eastern and western travelers as hotel guest, based on their experiences as seen in guest reviews and review topics.
Abstract
Purpose
This study aims to understand the satisfaction and needs of eastern and western travelers as hotel guest, based on their experiences as seen in guest reviews and review topics.
Design/methodology/approach
Considering 2,965 and 1,035 western and eastern traveler reviews, respectively, from 47 countries, obtained from TripAdvisor listed-hotel in Phnom Penh and Siem Reap city in Cambodia, this study investigates the differences in hotel guest satisfaction and needs by using topic modeling (i.e. latent Dirichlet allocation [LDA]).
Findings
The results reveal differences in the online preferences, experiences, expectations and behaviors of hotel guests from different cultural backgrounds. Though western and eastern travelers appear to place similar emphasis on service, location, room and destination. The westerners more likely focus on meal and online reservation, whereas the easterners focus on hotel facility.
Research limitations/implications
Reviews were obtained from only two cities in Cambodia, which is not an adequate representation of the diverse travelers visiting the country.
Practical implications
The comparison highlighting the similarities and dissimilarities between western and eastern traveler perspectives enable hoteliers to understand guests’ preferences and their hidden changes in (dis)satisfaction and leverage it to improve hotel service quality, increase occupancy and, thereby, maximize profits.
Originality/value
This study contributes to the literature on hotel guests’ experiences by presenting the difference in perceptions of service experience of western and eastern travelers, through topic modeling.
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Qiang Ye, Sai Liang, Zaiyan Wei and Rob Law
From the perspective of two-sided review systems, this study aims to investigate how guests’ prior reputation influences their subsequent satisfaction on Airbnb.
Abstract
Purpose
From the perspective of two-sided review systems, this study aims to investigate how guests’ prior reputation influences their subsequent satisfaction on Airbnb.
Design/methodology/approach
This study applied a conceptual framework based on social capital theory to explain the effect of guests’ reputation decided by hosts’ prior evaluations on their subsequent satisfaction. The authors collected 96,204 guest reviews posted for 17,325 properties on Airbnb and used the review polarity to measure guest satisfaction. All historical evaluations generated by hosts for each guest were collected and treated as a proxy of guest reputation. Ordinary least squares regressions were conducted to estimate the effect of guests’ reputation on their subsequent satisfaction.
Findings
Results show that guests whose historical evaluations have higher valences or larger variations tend to be more satisfied in their subsequent bookings. However, the number of reviews that guests received from hosts in the past does not influence their subsequent satisfaction.
Research limitations/implications
This study provides new insights into the hospitality literature by identifying the influencing factors of guest satisfaction on peer-to-peer rental platforms from the perspective of two-sided review systems. Results also present practical implications to property owners and website designers to gain a deeper understanding of the determinants of guest satisfaction and the consequences of social interactions between hosts and guests.
Originality/value
This study is a novel attempt that analyzes the effect of guests’ reputation on their satisfaction with subsequent bookings based on two-sided review systems on peer-to-peer rental platforms. Thus, this study provides a starting point for investigating how two-sided review systems affect use behavior on peer-to-peer rental platforms.
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Marcello Mariani and Matteo Borghi
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…
Abstract
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.
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