Search results

This paper aims to examine the influences of the number of hotel management responses and especially the textual similarity in hotel management responses to online reviews on hotel online booking.

This study used the data from 437 hotels in New York City on Expedia. The data specifically include online reviews, management responses and real-time number of online hotel bookings, which were merged to create one dataset for this study. To calculate the management response similarity, three widely recognized text mining functions of calculating textual similarity were adopted in this model. Fixed-effect panel data model was then used to examine the influence of management response to consumer online reviews on online hotel booking volume.

The empirical results demonstrate that the number of management responses to consumer online reviews does not significantly affect hotel booking; compared to none or only one management response, or management responses with low similarity, management responses with high similarity can significantly reduce the hotel booking on Expedia.

This study suggests that the similarity of management responses influences customers’ hotel booking, and hotel managers should avoid providing too similar management responses.

First, this study, for the first time, proposes the concept of management response similarity and its measurement methods. Second, this study takes an initial attempt to empirically test the influence of response similarity on hotel booking by using secondary data online.

More and more customers refer to online reviews before making any purchasing decisions thanks to the increasing popularity of social media and online shopping. This phenomenon has caught the attention of business managers who are increasingly aware that online reviews provide great opportunities to connect with current and potential customers. However, both practices and research on online review management from the businesses’ perspective are fragmented. The purpose of this paper is to develop an integrative framework that includes the key dimensions of an online review management system.

Based on the Grounded Theory approach, the authors conducted a multiple case study by analyzing the interviews with 11 hospitality services.

The authors found that an online review management system should go beyond the current norm of response management to incorporate key dimensions of formality, centralization, specialization, response customization, integration and review analytics.

The study provides a systematic guideline for online review management practices. The framework can be used as a tool for a business to evaluate existing online review management practices and develop/refine its online review management system.

The study contributes to online review management literature by developing a comprehensive framework to understand the structure and processes of online review management. The key dimensions of an online review management system identified in this study provide an initial measurement model for the online review management construct. Furthermore, the study provides a springboard for future empirical validation and refinement of the key factors for effective online review management.

The purpose of this paper is twofold: to perform a synthesis of academic research published between 2009 and 2016 regarding the changes in tourism consumer behavior brought about by the use of social media (SM); and to suggest a set of strategies for tourism businesses to seize opportunities and deal with resulting challenges.

A volume of 146 peer-reviewed journal articles were retrieved from two major databases. Content analysis of this academic research has been performed, exploring the effects of online reviews on tourism consumers and providers.

The content analysis identified three main research themes that were investigated by scholars and classified into two major categories, namely, consumer perspective and provider perspective: the antecedents (factors motivating and influencing tourists); the influence of online reviews on consumer behaviour; and the impact of these reviews on tourism businesses (providers’ perspective).

This study is based on a literature review and outcomes reported by previous studies; hence, the suggestions are indicative rather than conclusive. Some publication sources were not included.

This paper suggests a range of adequate strategies, along with operational actions, formulated for industry practitioners in the fields of management and marketing.

It provides an update of the state of published academic research into SM and an integrated set of management and marketing strategies for tourism providers in seizing the opportunities and dealing with the challenges raised in a digital context.

Drawing 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).

A 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.

The 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.

The 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.

本论文以TripAdvisor网站上520条关于约翰佩特拉古城五星级酒店的负面评论为样本, 分析豪华酒店如何应对网上负面评论, 具体评估变量包括反应率（RR）,反应时间（RT）,以及应对内容(RC)。

本论文采用由繁入减的方法来文本分析酒店经理应对反馈内容。结合文献综述, 本论文共确立四个变量：（1）感谢；（2）道歉；（3）解释；以及（4）补偿。经理回复内容经过了研读和手动编码等过程进行分析。评论刊登和经理反馈时间差也经过审阅分析。此外, 豪华酒店经理还接受了问卷调查来获得他们关于在线名誉管理的意见和处理措施。

本论文结果呼吁豪华酒店对于网上负面评论的严重影响的重视。其中, 研究结果表明, 不足一半的负面评论获得了经理回复, 而且, 一半以上的回复还是标准回答, 并没有涉及评论中提出的问题。低回复率以及酒店经理对于回复所有网上评论的统一认识表明, 酒店经理对于网上名誉管理的认知和措施存在于不一致性。

本论文主要研究了经理应对在线负面评论的态度和措施, 其研究结果对于酒店业名誉管理方面一直以来存在的争论提供了科学检验。本论文讨论了多个酒店经理人管理理念以及提供了未来科研方向。

Online hotel ratings, a form of electronic word of mouth (eWOM), are becoming increasingly important to tourism and hospitality management. Using sentiment analysis based on the big data technique, this paper aims to investigate the relationship between customer sentiment and online hotel ratings from the perspective of customers’ motives in the context of eWOM, and to further identify the moderating effects of review characteristics.

The authors first retrieve 273,457 customer-generated reviews from a well-known online travel agency in China using automated data crawlers. Next, they exploit two different sentiment analysis methods to obtain sentiment scores. Finally, empirical studies based on threshold regressions are conducted to establish the asymmetric relationship between customer sentiment and online hotel ratings.

The results suggest that the relationship between customer sentiment and online hotel ratings is asymmetric, and a negative sentiment score will exert a larger decline in online hotel ratings, compared to a positive sentiment score. Meanwhile, the reviewer level and reviews with pictures have moderating effects on the relationship between customer sentiment and online hotel ratings. Moreover, two different types of sentiment scores output by different sentiment analysis methods verify the results of this study.

The moderating effects of reviewer level and reviews with pictures offer new insights for hotel managers to make different customer service policies and for customers to select a hotel based on reviews from the online travel agency.

This paper contributes to the literature by applying big data analysis to the issues in hotel management. Based on the eWOM communication theories, this study extends previous study by providing an analysis framework for the relationship between customer sentiment and online hotel ratings from the perspective of customers’ motives in the context of eWOM.

The present study develops a conceptual model that shows how the manipulation attributes of word choice, sentence fluency, convention of meaning, and organization of sentence structure in online hotel reviews are connected to linguistic errors, such as spelling and grammar and argument errors, how such errors intensify the likelihood that messages will be misunderstood, and how these misunderstandings affect customers' responses.

A structured questionnaire was employed to collect data from 591 inbound tourists in Beijing, China. Data analysis was conducted using SPSS 25.0 and Amos Graphics 23.0. Descriptive analysis was performed to explain the sociodemographic characteristic of respondents. Structural equation modeling was performed to examine hypothesized relationships.

Results demonstrate that manipulation attributes increase linguistic errors, and two linguistic errors have profound positive effects on customers' understanding of meaning, which influence their responses in the form of negative online ratings and low purchase intentions.

The study's findings contribute to the literature on hospitality, linguistics, and consumer behavior, and have managerial implications for online review websites, online travel agents, and hotel management. Research limitations lead to suggestions for future research for hospitality scholars.

This 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.

Partial 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.

This 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.

Based 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.

Based 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.

The purpose of this study is to present a systematic review of the online service failure (OSF) literature and conduct an exhaustive analysis of academic research on this emerging research area.

The current study has adopted a structured systematic literature review approach to synthesize and assess the OSF literature. Further, the study uses the Theory-Context-Characteristics-Methodology (TCCM) framework to propose future research directions in the OSF domain.

This systematic review shows that OSF research is still developing and remains mainly incoherent. Further, the study develops a conceptual framework integrating the frequently reported antecedents, mediators, moderator and consequences in the extant literature. This review also synthesizes the theoretical perspectives adopted for this domain.

The study followed specific inclusion and exclusion criteria to shortlist articles. Further, articles published only in the English language were considered. Hence, the findings of this review cannot be generalized to all OSF literature.

This systematic review has classified antecedents into customers' and service providers' roles which will enable online service providers to understand all sets of factors driving OSF. It also synthesizes and presents service recovery strategies and emphasizes the role of online customer support to fix OSF.

The OSF literature is still developing and remains highly incoherent, suggesting that a synthesized review is needed. This study has systematically reviewed and synthesized the OSF literature to study its development over time and proposes a framework which provides a comprehensive understanding of OSF.

The purpose of this paper is to investigate how hotels respond to online reviews on a third-party Web site (such as TripAdvisor) based on the hotel’s star rating.

Content analysis was used to compare responses to online hotel reviews at five different levels of hotel based on a star-rating system ranging from one star to five stars.

Most hotel managers’ response rates were low, and they paid the most attention to positive comments. Managers at four- and five-star hotels more often responded to negative online reviews. Guest service manager was the most common job title of managers who responded to guests’ reviews.

This paper is limited to an analysis of ten hotels, two for each of the five-star ratings. More hotel cases with long-term data collection involving the use of the star-rating system may provide more insights on this discussion.

The exploratory study sought to identify strategies for managing online reviews in the lodging industry. Hotel managers should respond to negative online reviews with appreciation, apology and an explanation of what went wrong. Moreover, hotels may need a designated person to observe and respond to guest comments on their Web sites and third-party Web sites. A designated person is also needed to monitor online comments and communicate with guests to better manage the hotel’s online reputation.

As an exploratory research project, this paper expands the understanding of hotel managers’ responses to their guests’ online reviews in an attempt to identify best practices for the industry.

Based on more than 2.7 million online reviews (ORs) collected with big data analytical techniques from Booking.com and TripAdvisor.com, this paper aims to explore if and to what extent environmental discourse embedded in ORs has an impact on electronic word-of-mouth (e-WOM) helpfulness across eight major destination cities in North America and Europe.

This study gathered, by means of Big Data techniques, 2.7 million ORs hosted on Booking.com and TripAdvisor, and covering hospitality services in eight different destinations cities in North America (New York City, Miami, Orlando and Las Vegas) and Europe (Barcelona, London, Paris and Rome) over the period 2017–2018. The ORs were analysed by means of ad hoc content analytic dictionaries to identify the presence and depth of the environmental discourse included in each OR. A negative binomial regression analysis was used to measure the impact of the presence/depth of online environmental discourse in ORs on e-WOM helpfulness.

The findings indicate that the environmental discourse presence and depth influence positively e-WOM helpfulness. More specifically those travelers who write explicitly about environmental topics in their ORs are more likely to produce ORs that are voted as helpful by other consumers.

Implications highlight that both hotel managers and platform developers/managers should become increasingly aware of the importance that customer attach to environmental practices and initiatives and therefore engage more assiduously in environmental initiatives, if their objective is to improve online review helpfulness for other customers reading the focal reviews. Future studies might include more destinations and other operationalizations of environmental discourse.

This study constitutes the first attempt to capture how the presence and depth of hospitality services consumers’ environmental discourse influence e-WOM helpfulness on multiple digital platforms, by means of a big data analysis on a large sample of online reviews across multiple countries and destinations. As such it makes a relevant contribution to the area at the intersection between big data analytics, e-WOM and sustainable tourism research.