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This paper aims to explore the effects of webcare content type and webcare source credibility on perceived fairness, in the presence of reputation of a reviewer as a moderator.

The experiment used a 2 (Webcare content type: Specific vs Vague) × 2 (Webcare source credibility: High vs Low) × 2 (Reviewer reputation: Good vs Bad) between-subjects design. ANOVA was used to test the hypotheses.

A significant main effect and interaction effect of independent variables was found on perceived fairness. The moderating role of reviewer reputation was also found significant in the relationship between content type and perceived fairness. However, reputation of the reviewer did not moderate the relationship between webcare source credibility and perceived fairness.

Marketers should respond to negative reviews by paying attention toward review and webcare attributes highlighted in the paper because doing so might satisfy the consumer.

This paper attempts to study a combination of webcare and review characteristics together on consumers' perceptions of fairness.

The prevalence of online review websites and the ever-growing difficulty of judging review quality result in the increasing need for consumers to reduce cognitive costs. Thus, the purpose of this study is to find out the determinants of review helpfulness based on a comprehensive theoretical framework and empirical model.

This study applied a comprehensive framework, including both review content quality and reviewer background, to investigate the determinants of review helpfulness. It also presents empirical models to further control factors around product features.

Consumers are more likely to give helpful votes to those informative and readable reviews accompanied by extreme ratings. Reviewers who disclose information, have a high reputation and report a poor experience are always identified as helpful. Consumers also tend to signal suggestions from users with a local cultural background as subjective and useless.

This study focuses on upscale hotels in China. Information registered on TripAdvisor was used presenting a residential address not nationality. Only few controlling factors available because of the limited information are shown on online review websites.

Managers of both hotels and online review websites need to focus on reviews and/or reviewers as KOLs who attract consumers’ attention and affect their subsequent decisions. A dialogue with those KOLs can be by focusing on responding to reviews with certain characteristics. A reward system for reviews and KOLs may benefit review quality on online review websites and reduce cognition costs.

This positivistic research design, with multilevel approach, presenting a comprehensive conceptual framework and empirical model not only considering review- and reviewer-related factors but also controlled factors in product or service level (hotel-related characteristics).

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.

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.

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.

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.

This paper presents a review of the state of the art on the application of blockchain and smart contracts to the peer-review process of scientific papers. The paper seeks to analyse how the main characteristics of the existing blockchain solutions in this field to detect opportunities for the improvement of future applications.

A systematic review of the literature on the subject was carried out in three databases recognized by the research community (IEEE Xplore, Scopus and Web of Science) and the Frontiers in Blockchain journal. A total of 1,967 articles were initially found, and after the exclusion process, the 26 remaining articles were classified according to the following dimensions: System Type, Open Access, Review Type, Reviewer Incentive, Token Economy, Blockchain Access, Blockchain Identification, Blockchain Used, Paper Storage, Anonymity and Maturity of the solution.

Results show that the solutions are normally concerned on offering incentives to the reviewers' work (often monetary). Other common general preferences among the solutions are the adoption of open reviews, the use of Ethereum, the implementation of publishing ecosystems and the use of InterPlanetary File System to the storage of the papers.

There are currently no studies covering the main aspects of blockchain solutions in the field of scientific peer review. The present study provides an overall review of the topic, summarizing important information on the current research and helping new adopters to develop solutions grounded on the existing literature.

In recent years, readers have limited amounts of time to pick the right books to read from a market that is filled with similar types of books. Aiming to read only good books, readers tend to check book reviews written by others. However, it is very difficult to find good book reviews. The aim of this paper is to present a book review recommendation system that collects reviews from heterogeneous sources on the Internet and performs quality judgments automatically. Users can then read the top‐ranked reviews suggested by this recommendation system.

In this paper, a book review recommendation system is constructed to collect, process, and judge the quality of book reviews from various heterogeneous sources. The quality measurement of book reviews uses review‐evaluation techniques. The prediction results were validated with a ranking list produced by experts.

The proposed system is effective and suitable for recommending quality book reviews from heterogeneous sources. The proposed quality measurement method is more effective than other more commonly used methods.

This paper is one of the first to apply review evaluation techniques to the process of book review recommendation. The proposed system can collect and recognize book reviews from different websites with various forms of presentation. This evaluation shows that the quality measurement method produces better results than do other methods, such as ranking by rating score or by the date that the review was posted. Those methods are primarily used by commercial websites.

Online reputation manager has become increasingly important in tourism industry. Managers, regardless of working for a hospitality structure or a tourism destination, are paying more and more attention in respect of the importance of reputational levels. Online reputation, in fact, originates in visitor's user-generated contents (UGCs) but reverberates on the whole web, on successive visitors' attitude and behavior, and on managed organization performances. How to manage online reputation in tourism and destination management anyway mostly stayed an anecdotal topic for many years. While best practices exist, indeed, literature has frequently neglected their systematization. Building on this need, this book will try to improve and organize the existing body of knowledge on this topic to help future hotel and destination managers to better deal with the mounting environmental complexity.

The purposes of this study are to synthesize the current research findings reported in major hospitality and tourism journals and to discuss the knowledge gaps where additional research endeavors are needed.

A systematic review approach was adopted to analyze 67 research articles about online reviews that were published between January 2000 and July 2015 in seven major hospitality and tourism journals.

This study presents a thematic framework of online review research, which was advanced by integrating the interactions among quantitative evaluation features, verbal evaluation features, reputation features and social features of online reviews with important outcomes of consumer decision-making and business performance. The thematic framework helps researchers identify the areas in extant hospitality literature of online reviews and point out possible directions for future studies.

The systematic review approach has a qualitative nature, where relevant literature was interpreted based on the authors’ domain knowledge and expertise.

Practitioners can gain a comprehensive understanding of the dynamic relationships among the key influential factors in online reviews, as presented in the thematic framework of online review research. Accordingly, managers will be able to develop effective strategies to leverage the positive impacts of online reviews to the business outcomes.

This systematic review synthesizes the findings reported in most recent publications (January 2000-July 2015; also including “Online First” articles) in seven major hospitality and tourism journals and develops an integrated research framework, anchoring on four meta-research questions and showing the dynamic relationships among the key players/factors/themes in online review research. This framework provides a visual diagram to practitioners for a better understanding of the relevant literature and assists researchers in developing new research questions for future studies.

This study aims to uncover how heuristic information cues (HIC) and systematic information cues (SIC) of online reviews influence review helpfulness and examine a moderating role of social influence in the process of assessing review helpfulness. In particular, this study conceptualizes a theoretical framework based on dual-process and social influence theory (SIT) and empirically tests the proposed hypotheses by analyzing a broad set of actual customer review data.

For 4,177,377 online reviews posted on Yelp.com from 2004 to 2018, this study used data mining and text analysis to extract independent variables. Zero-inflated negative binomial regression analysis was conducted to test the hypothesized model.

The present study demonstrates that both HIC and SIC have a significant relationship with review helpfulness. Normative social influence cue (NSIC) strengthened the relationship between HIC and review helpfulness. However, the moderating effect of NSIC was not valid in the relationship between SIC and review helpfulness.

This study contributes to the extant research on review helpfulness by providing a conceptual framework underpinned by dual-process theory and SIT. The study not only identifies determinants of review helpfulness but also reveals how social influences can impact individuals’ judgment on review helpfulness. By offering a state-of-the-art analysis with a vast amount of online reviews, this study contributes to the methodological improvement of further empirical research.

本论文旨在揭示网络评论的启发性信息源和系统性信息源对于评论有用性的影响, 以及检验社会影响在评论有用性的调节作用。其中, 本论文基于双重历程理论和社会影响理论来构建理论模型, 并且利用实际数据来验证假设, 通过分析一系列实际客户评论数据。

本论文样本数据为2004年至2018年Yelp.com上面的4,177,377网络评论。本论文采用数据挖掘和文本分析的方法来提取自变量。本论文采用零膨胀负二项回归模型来验证假设。

研究结果表明, 启发性和系统性信息源都对网络评论有用性有着显著作用。规范性社会影响加强了启发性信息源对评论有用性的作用。然而, 规范性社会影响对系统性信息源与评论有用性的关系并未起到有效的调节作用。

本论文对现有评论有用性的文献有着补充贡献, 其采用双重历程理论和社会影响理论来构建理论模型。本论文不仅指出评论有用性的影响因素, 而且展示了社会影响如何影响个人对评论有用性的判断。本论文的样本数据庞大, 数据分析夯实, 这对于进一步的实际测量研究有着方法改进方面的贡献。

The experiential nature of travel and tourism services has popularized the importance of electronic word-of-mouth (EWOM) among potential customers. EWOM has a significant influence on hotel booking intention of customers as they tend to trust EWOM more than the messages spread by marketers. Amid abundant reviews available online, it becomes difficult for travelers to identify the most significant ones. This questions the credibility of reviewers as various online businesses allow reviewers to post their feedback using nickname or email address rather than using real name, photo or other personal information. Therefore, this study aims to determine the factors leading to reviewer credibility.

The paper proposes an econometric model to determine the variables that affect the reviewer’s credibility in the hospitality and tourism sector. The proposed model uses quantifiable variables of reviewers and reviews to estimate reviewer credibility, defined in terms of proportion of number of helpful votes received by a reviewer to the number of total reviews written by him. This covers both aspects of source credibility i.e. trustworthiness and expertness. The authors have used the data set of TripAdvisor.com to validate the models.

Regression analysis significantly validated the econometric models proposed here. To check the predictive efficiency of the models, predictive modeling using five commonly used classifiers such as random forest (RF), linear discriminant analysis, k-nearest neighbor, decision tree and support vector machine is performed. RF gave the best accuracy for the overall model.

The findings of this research paper suggest various implications for hoteliers and managers to help retain credible reviewers in the online travel community. This will help them to achieve long term relationships with the clients and increase their trust in the brand.

To the best of authors’ knowledge, this study performs an econometric modeling approach to find determinants of reviewer credibility, not conducted in previous studies. Moreover, the study contracts from earlier works by considering it to be an endogenous variable, rather than an exogenous one.

In this paper the authors aim to review the state-of-the-art literature on online review systems and their impacts on consumer behavior and retailers' performance with the aim of identifying research gaps related to different design features of review systems and developing future research agenda.

The authors conducted a systematic review based on PRISMA 2020 protocol, focusing on studies published in the domains of retailing and marketing. This procedure resulted in 48 selected papers investigating the design features of retailer online review systems.

The authors identify eight design features that are controllable by retailers in an online review system. The design features have been researched independently in previous literature, with some features receiving more attention. Most selected studies focus on the design features adapted metrics and review presentations, while other features are generally neglected (e.g. rating dimensions). Previous literature argues that design features affect consumer behaviors and retailers' performance. However, the interactions among the features are still neglected in the literature, creating a relevant gap for future research.

This paper distinguishes between different types of retailer online review systems based on how they are implemented. The authors summarize the state-of-the-art of relevant literature on design features of online review systems and their effects on consumer- and retailer-related outcome variables. This systematic literature review distinguishes between online reviews provided on websites controlled by retailers (internal systems) and third-party websites (external systems).