The influence of online reviews to online hotel booking intentions

2015 ◽  
Vol 27 (6) ◽  
pp. 1343-1364 ◽  
Author(s):  
Xinyuan (Roy) Zhao ◽  
Liang Wang ◽  
Xiao Guo ◽  
Rob Law
Keyword(s):  
Regression Analysis ◽  
Mainland China ◽  
Online Reviews ◽  
Online Review ◽  
Content Type ◽  
Theoretical Contribution ◽  
Review Management ◽  
Marketing Tool ◽  
Booking Intentions ◽  
Hotel Booking

Purpose – This study aims to investigate the impacts of online review and source features upon travelers’ online hotel booking intentions. Design/methodology/approach – This study developed a research model and empirically examined the model by collecting data from business travelers in the Mainland China. Factor analysis was adopted to identify features of online reviews content and source attribute. Regression analysis was used to examine impacts of these attributes upon travelers’ online booking intention. Findings – Six features of online reviews content and one source attribute were identified, namely, usefulness, reviewer expertise, timeliness, volume, valence (negative and positive) and comprehensiveness. Regression analysis results testified positive causal relationships between usefulness, reviewer expertise, timeliness, volume and comprehensiveness and respondents’ online booking intentions. A significantly negative relation between negative online reviews and online booking intentions was identified, whereas impacts from positive online reviews upon booking intentions were not statistically significant. Research limitations/implications – The major limitation of this study is that interrelationships among features of online reviews, which were discussed in other similar studies, were not considered. Still, this study benefited researchers from scrutinizing features of online reviews, rather than several of them. As such, it offered more comprehensive suggestions for practitioners in how to better utilize online reviews as a marketing tool. Practical implications – Hospitality practitioners could enhance consumer review management by applying the six underlying factors of online review in the present study to find out the ways of increasing consumers’ booking intentions in the specific hotel contexts. Originality/value – A major theoretical contribution of this paper is its comprehensiveness in examining features of review content as well as its source simultaneously. This study also offered areas worthy of more research efforts from perspectives of practitioners and researchers.

Perceived credibility of online hotel reviews and its impact on hotel booking intentions

2019 ◽  
Vol 31 (9) ◽  
pp. 3465-3483 ◽  
Author(s):  
Uttam Chakraborty
Keyword(s):  
Structural Equation ◽  
Positive Impact ◽  
Online Reviews ◽  
Equation Modeling ◽  
Measurement Scales ◽  
Content Type ◽  
Perceived Credibility ◽  
Booking Intentions ◽  
Hotel Booking ◽  
The Impact

Purpose This study aims to evaluate the vitality of source, receiver and message factors on credibility assessment of online hotel reviews. Further, the current study determines the effects of perceived credibility of online reviews (PCOR) on hotel booking intentions (HBI). Design/methodology/approach The current study performs reliability analysis to determine the internal consistency of the measurement scales and to ensure the uni-dimensionality of the measurement scales the present study performs exploratory factor analysis. Further, the present study performs structural equation modeling to identify the relationships between the variables. Findings Two-sided online reviews have a more significant positive impact on PCOR as compared to the effects of receiver, review quality, review consistency and negative-sided online reviews. Originality/value This is one of the first study that analyses the impact of source, receiver and message on PCOR. Moreover, the present study offered theoretical justification behind the factors that affect the authenticity of online hotel reviews and its effects on HBI.

An exploratory study of online review management in hospitality services

2018 ◽  
Vol 28 (1) ◽  
pp. 79-98 ◽  
Author(s):  
Run Hong Niu ◽  
Ying Fan
Keyword(s):  
Management System ◽  
Management Practices ◽  
Measurement Model ◽  
Online Reviews ◽  
Online Review ◽  
Theory Approach ◽  
Content Type ◽  
Integrative Framework ◽  
Review Management ◽  
Key Dimensions

Purpose 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. Design/methodology/approach Based on the Grounded Theory approach, the authors conducted a multiple case study by analyzing the interviews with 11 hospitality services. Findings 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. Practical implications 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. Originality/value 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.

How old is your soul? Differences in the impact of eWOM on Generation X and millennials

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniel Ruiz-Equihua ◽  
Luis V. Casaló ◽  
Jaime Romero
Keyword(s):  
Generation X ◽  
Behavioral Intentions ◽  
Online Reviews ◽  
Online Review ◽  
Generational Cohort ◽  
Research Attention ◽  
Content Type ◽  
Two Samples ◽  
Booking Intentions ◽  
The Impact

PurposeOnline reviews have received research attention in recent years, as they work as precursors of consumer behaviors. Previous studies have suggested that the influence of online reviews may vary across generations. However, the previous literature has not analyzed yet whether millennials and Generation X react differently to online reviews. This study aims to shed light on this by analyzing whether the attitudes and behavioral intentions generated by online reviews are different for these two generational cohorts.Design/methodology/approachAn experimental procedure was designed to manipulate online review valence; data were collected from 351 respondents in two samples, Generation X and millennial participants.FindingsResults suggested that positive online reviews generate more positive customer attitudes and booking intentions than negative online reviews. In addition, Generation X vs millennials moderates the link among online review valence, attitudes and booking intentions. The resultant behaviors from online reviews are more intense among Generation X than for millennials.Practical implicationsManagers should be aware of online review valence and their customers' generational cohort, that is, whether they are millennials or Generation X, as they react differently to online reviews.Originality/valueThis research examines the moderating role of millennials and Generation X in the relationship between online reviews, consumer attitudes and behavioral intentions. The aim is to explain how millennial and Generation X consumers react to eWOM, that is, whether generational cohort mitigates or enhances the effects of positive vs negative online reviews on consumer reactions.

The impacts of customers’ observed severity and agreement on hotel booking intentions: moderating role of webcare and mediating role of trust in negative online reviews

2016 ◽  
Vol 71 (2) ◽  
pp. 77-89 ◽  
Author(s):  
Sreejesh S. ◽  
Anusree M.R.
Keyword(s):  
Service Failure ◽  
Online Reviews ◽  
Study Data ◽  
Content Type ◽  
Perceived Trust ◽  
Negative Effect ◽  
Booking Intentions ◽  
Hotel Booking ◽  
Agreement Condition

Purpose The purpose of the paper is to examine the conditional role of webcare as a service failure recovery strategy on customers’ hotel booking intentions in presence of different levels of observed severity and review agreement. Furthermore, the study also examines the mechanism through which webcare can shape the adverse effect of observed severity and review agreement on hotel booking intentions. Design/methodology/approach A 2 (severity: high or low) × 2 (agreement: high or low) × 2 (webcare: webcare or no webcare) between-subject experimental design was conducted to collect responses. Analyses of variance and moderated mediation analysis were performed to analyze the study data. Findings Prospective customers who observed high severe service failure from a review reported less booking intention. Further, customers’ observed agreement strengthened these behaviors, i.e. customers who are exposed to high severe service failure in high-agreement condition reported low booking intention, as compared to those who exposed to low review agreement condition. Furthermore, results supported the fact that use of appropriate webcare plays a significant role to shape or mitigate the negative effect of severity and agreement on hotel booking intentions via perceived trust. Originality/value This is the first in its stream of studies that examined how webcare can be used to tackle the adverse effects of observed severity and agreement, so that perceived trust would be formed to create hotel booking intention.

Investigating the influence of regulatory focus on the efficacy of online review volume versus valence

2020 ◽  
Vol 55 (1) ◽  
pp. 297-314
Author(s):  
Elika Kordrostami ◽  
Yuping Liu-Thompkins ◽  
Vahid Rahmani
Keyword(s):  
Regulatory Focus ◽  
Product Category ◽  
Online Reviews ◽  
Online Review ◽  
Target Market ◽  
Prevention Focus ◽  
Promotion Focus ◽  
Content Type ◽  
Review Management ◽  
Volume Effects

Purpose Valence and volume of online reviews are generally considered to influence sales positively. However, existing findings regarding the relative influence of these two components have been inconclusive. This paper aims to explain some of these inconsistencies by examining the moderating role of regulatory focus (both as a chronic disposition and as a situational focus induced by the product category) in the relationship between online review volume/valence and consumers purchase decisions. Design/methodology/approach Two studies were conducted. Study 1 used a 2 (Volume: high/ low) * 3 (Valence: high/medium/low) within-subject experimental design. Study 2 analyzed real-world data from Amazon.com. Logistic and panel regression analyses were used to test the research hypotheses. Findings The studies confirmed the hypothesized effect of regulatory focus on online review valence and volume effects. Specifically, Study 1 showed that online review valence was more impactful for consumers with a promotion focus than for consumers with a prevention focus. The opposite was true for online review volume effects, where consumers with a prevention focus were influenced more by volume in their decision-making compared to consumers with a promotion focus. Study 2 showed that the pattern of results we found in Study 1 also applied to situational regulatory focus induced by the product category. The effect of review volume on sales rank was stronger for prevention-oriented products, whereas the effect of valence was stronger for promotion-oriented products. Research limitations/implications In Study 1, one product category was involved in the study (Digital camera). Involving more different product categories will add reliability to the results of current research. Also, it can offer external validity to current research results. In Study 2, there was no exact measurement for sales, as Amazon.com does not share that kind of information. Instead, Sales Rank was used as a proxy variable. Future research could look into the websites that offer access to the exact sales information. Practical implications The current research findings suggest the need for companies to adapt their consumer review management strategy to the regulatory orientation of their target market and products. When a promotion-focused mindset is targeted, strategies for increasing the favorability of product reviews should be used, in contrast, tactics for increasing the quantity of reviews may be more suitable when a prevention-focused mindset is involved. Originality/value To the best of the authors' knowledge, this research is the first to investigate the interaction between regulatory focus of consumers and products and online review components.

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 Which cues influence the perceived usefulness and credibility of an online review? A conjoint analysis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ana Isabel Lopes ◽  
Nathalie Dens ◽  
Patrick De Pelsmacker ◽  
Freya De Keyzer
Keyword(s):  
Conjoint Analysis ◽  
Product Category ◽  
Online Reviews ◽  
Perceived Usefulness ◽  
Online Review ◽  
Large Set ◽  
Relative Importance ◽  
Writing Quality ◽  
Content Type ◽  
Argument Strength

PurposeThis study aims to assess the relative importance of the argument strength, argument sidedness, writing quality, number of arguments, rated review usefulness, summary review rating and number of reviews in determining the perceived usefulness and credibility of an online review. Additionally, the authors use insights from the elaboration likelihood model (ELM) to explore the effect of consumers' product category involvement on the cues' relative importance.Design/methodology/approachA conjoint analysis (N = 287) is used to study the relative importance of the seven previously mentioned attributes. A balanced orthogonal design generated eight cards that correspond to individual reviews. Respondents scored all eight cards in a random order for perceived usefulness and credibility.FindingsOverall, argument strength is the most important cue, while summary review rating and the number of reviews are the least important for perceived review usefulness and credibility. The number of arguments is more important for people who are more highly involved with the product, while writing quality and rated review usefulness are relatively more important for the low-involvement group.Originality/valueThis study provides a comprehensive test of how consumers perceive online reviews, as it the first to the authors’ knowledge to simultaneously investigate a large set of cues using conjoint analysis. This method allows for the implicit valuation (utility) of the individual cues, revealing the cues' relative importance, in a setting that comes close to a real-life context. Besides, insights of the ELM are used to understand how the relative importance of cues differs depending on the level of review readers' product category involvement.

FLORA: a hierarchical fuzzy system for online accommodation review analysis

2019 ◽  
Vol 21 (3) ◽  
pp. 347-367
Author(s):  
Thara Angskun ◽  
Jitimon Angskun
Keyword(s):  
Sentiment Analysis ◽  
Semantic Analysis ◽  
Online Reviews ◽  
Online Review ◽  
Probability Weighting ◽  
Content Type ◽  
Analysis Process ◽  
Review Analysis ◽  
Accuracy Comparison ◽  
Hierarchical Fuzzy System

Purpose This paper aims to introduce a hierarchical fuzzy system for an online review analysis named FLORA. FLORA enables tourists to decide their destination without reading numerous reviews from experienced tourists. It summarizes reviews and visualizes them through a hierarchical structure. The visualization does not only present overall quality of an accommodation, but it also presents the condition of the bed, hospitality of the front desk receptionist and much more in a snap. Design/methodology/approach FLORA is a complete system which acquires online reviews, analyzes sentiments, computes feature scores and summarizes results in a hierarchical view. FLORA is designed to use an overall score, rated by real tourists as a baseline for accuracy comparison. The accuracy of FLORA has achieved by a novel sentiment analysis process (as part of a knowledge acquisition engine) based on semantic analysis and a novel rating technique, called hierarchical fuzzy calculation, in the knowledge inference engine. Findings The performance comparison of FLORA against related work has been assessed in two aspects. The first aspect focuses on review analysis with binary format representation. The results reveal that the hierarchical fuzzy method, with probability weighting of FLORA, is achieved with the highest values in precision, recall and F-measure. The second aspect looks at review analysis with a five-point rating scale rating by comparing with one of the most advanced research methods, called fuzzy domain ontology. The results reveal that the hierarchical fuzzy method, with probability weighting of FLORA, returns the closest results to the tourist-defined rating. Research limitations/implications This research advances knowledge of online review analysis by contributing a novel sentiment analysis process and a novel rating technique. The FLORA system has two limitations. First, the reviews are based on individual expression, which is an arbitrary distinction and not always grammatically correct. Consequently, some opinions may not be extracted because the context free grammar rules are insufficient. Second, natural languages evolve and diversify all the time. Many emerging words or phrases, including idioms, proverbs and slang, are often used in online reviews. Thus, those words or phrases need to be manually updated in the knowledge base. Practical implications This research contributes to the tourism business and assists travelers by introducing comprehensive and easy to understand information about each accommodation to travelers. Although the FLORA system was originally designed and tested with accommodation reviews, it can also be used with reviews of any products or services by updating data in the knowledge base. Thus, businesses, which have online reviews for their products or services, can benefit from the FLORA system. Originality/value This research proposes a FLORA system which analyzes sentiments from online reviews, computes feature scores and summarizes results in a hierarchical view. Moreover, this work is able to use the overall score, rated by real tourists, as a baseline for accuracy comparison. The main theoretical implication is a novel sentiment analysis process based on semantic analysis and a novel rating technique called hierarchical fuzzy calculation.

scholarly journals The Interaction Effects of Online Reviews, Brand, and Price on Consumer Hotel Booking Decision Making

2020 ◽  
pp. 004728752091233 ◽  
Author(s):  
Ji Wen ◽  
Zhibin Lin ◽  
Xin Liu ◽  
Sarah Hong Xiao ◽  
Yina Li
Keyword(s):  
Online Reviews ◽  
Interaction Effects ◽  
Perceived Quality ◽  
Brand Names ◽  
Mediation Effect ◽  
Online Review ◽  
Multiple Cues ◽  
Customer Reviews ◽  
Randomized Controlled Experiment ◽  
Hotel Booking

When searching and booking a hotel online, consumers are exposed to multiple cues such as customer reviews, price, and brand names. This study aims to examine the level of diagnosticity and simultaneous effects of the three important decision cues: online review, price, and brand on consumer quality evaluation and hotel booking intention. Study 1 is a randomized controlled experiment of 2 (high vs. low price) × 2 (positive vs. negative online review) × 2 (familiar vs. unknown brand). Study 2 replicates and extends study 1 by further examining the three cues’ effects on both perceived quality and booking intention, and the mediation effect of perceived quality. The results reveal three-way interaction effects of multiple cues in consumers’ decision processes and indicate that negative reviews have a dominating effect on hotel booking intention, and the level of cue diagnosticity from high to low is as follows: online review, brand familiarity, and price.

Culture as a moderator of cognitive age and travel motivation/perceived risk relations among seniors

2017 ◽  
Vol 34 (5) ◽  
pp. 455-466 ◽  
Author(s):  
Delphine Le Serre ◽  
Karin Weber ◽  
Patrick Legohérel ◽  
Karim Errajaa
Keyword(s):  
Cultural Differences ◽  
Perceived Risk ◽  
Mainland China ◽  
Two Dimensions ◽  
Subjective Age ◽  
Content Type ◽  
Theoretical Contribution ◽  
Western Countries ◽  
Cognitive Age ◽  
New Research

Purpose This study contributes to greater understanding of the senior market and the cultural differences regarding aging in Western and Asian cultures. The review of the literature highlights the cultural differences toward the concept of aging in Asian and Western countries and describes a useful age concept for investigating senior consumers, namely, that of subjective age. The purpose of this study is to investigate the influence of subjective age dimensions on seniors’ behavior and to assess the role of culture as a moderator of this influence. Design/methodology/approach Data were collected in France and Mainland China and consisted of answers to 300 questionnaires for the French seniors and 264 questionnaires for the Chinese seniors. Two dimensions of subjective age were measured: cognitive age and ideal age, along with travel motivations and travel perceived risk. Findings The study provides valuable information regarding the Western and Asian senior markets. Subjective age dimensions prove to be related with seniors’ behaviors (perceived travel risks). The present study also demonstrates that nationality has a moderating role on this relation. This theoretical contribution will have to be confirmed by other studies in Asian and Western countries; it opens the door to new research on Chinese/Asian seniors involving these age variables. Originality/value The study gives academics and managers insights on the influence of subjective age on seniors’ behaviors in European and Asian cultural contexts.

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