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Recent research suggests that more than two-thirds of people use online reviews to find a new primary care physician (PCP). However, it is unclear what role review content plays when a patient uses online reviews to decide about a new PCP. This paper aims to understand how a review's content, related to competence (communication and technical skills) and benevolence (fidelity and fairness), impacts patients’ trusting intentions to select a PCP. The authors build the model around information diagnosticity, construal level theory and valence asymmetries and use review helpfulness as a mediator and review valence as a moderator in this process.

The authors use two experimental studies to test their hypotheses and collect data through prolific.

The authors find that people have a harder time making inferences about the technical and communication skills of a PCP. Reviews about fidelity are perceived as more helpful and influential in building trust than reviews about fairness. Overall, reviews about the communication skills of a PCP have stronger effects on trusting intentions than other types of reviews. The authors also find that positive reviews are perceived as more helpful for the readers than negative reviews, but negative reviews have a stronger impact on patients' trust intentions than positive ones.

The authors identify how online reviews about a PCP’s competency and benevolence affect patients’ trusting intentions to choose the PCP. The implication of findings of this study for primary medical practice and physician review websites is discussed.

This study aims to explore the relationship between the content characteristics of destination online reviews and travel intention under three individual circumstances: temporal distance, social distance and experiential distance.

Based on construal-level theory (CLT), this study divides online travel reviews into concrete and abstract reviews. Three experiments were conducted to test the moderating effects of temporal distance, social distance and experiential distance on the influence of review content characteristics on tourists' travel intentions.

The results show that abstract reviews would lead to higher travel intentions than concrete reviews. Furthermore, tourists' travel intentions differed depending on social distance and were significantly affected by reviews posted by reviewers similar to review recipients. In addition, the study contributes by discovering that the moderating effects of temporal distance, social distance and experiential distance were not significant, which differs from most of the previous research conclusions.

This study focused on review content characteristics, which provided a novel perspective for constructing online travel reviews. Furthermore, this research defined the concept of experiential distance in the context of online travel and expanded the research on psychological distance.

Online reviews are increasingly available for a wide range of products and services in e-commerce. Most consumers rely heavily on online reviews when making purchase decisions, so an important topic is that of understanding what makes some online reviews helpful in the eyes of consumers. Researchers have demonstrated the benefits of the presence of customer reviews to an online retailer, however, few studies have investigated how images in review content and the facial expressions of reviewers’ avatars influence the judgment of online review helpfulness. This study draws on self-construal theory, attribution theory and affect-as-information theory to empirically test a model of the interaction effects of images in review content and the facial expressions of reviewers’ avatars on online review helpfulness. Furthermore, the purpose of this paper is to identify an underlying mechanism of causal attribution toward store performance on the above effects.

This study conducted two online experiments. Study 1 is a 2 (images in review content: one person with a product vs a group of people with a product) ×2 (facial expression of the reviewer’s avatar: happy vs angry) between-subjects design. Study 2 is a 3 (image: product alone vs one person with a product vs a group of people with a product) ×2 (facial expression of the reviewer’s avatar: happy vs angry) ×3 (valence of the review: positive vs negative vs neutral) between-subjects design.

The results indicate that when consumers were exposed to a happy-looking avatar, they were likely to express higher perceptions of online review helpfulness in response to an image showing a group of people in a restaurant than they would for an image of one person in the same situation. In contrast, when consumers were exposed to an angry-looking avatar, their perceptions of online review helpfulness did not differ in response to images of either a group of people or of one person. Furthermore, cause attribution toward store performance mediated the interaction between images in content of reviews and the facial expression of a reviewer’s avatar on the perceptions of online review helpfulness.

The authors provide insights into how to develop guidelines on how online reviews should be written so that readers perceive them to be helpful, and how to design effective reward mechanisms for customer feedback.

Compared with previous studies, this study provides further contributions in three ways. First, it contributes to the literature on review content by showing which images in reviews are deemed to be helpful. Second, it extends previous findings from the literature relating to online peer reviews by demonstrating the importance of facial expressions in reviewers’ avatars (i.e. happy vs angry) when explaining helpfulness, rather than the strength of purchase intent. Third, this study contributes by further highlighting a novel mechanism which shows that a causal attribution toward store performance motivates the perceptions of online review helpfulness.

Information asymmetry is an inevitable issue in e-commerce and largely hampers the development of online shopping. The purpose of this paper is to propose a model to investigate the emotional content of online customer reviews, which are considered an efficient way to reduce information asymmetry, as a potential signal of product quality. The moderating effects of perceived empathy and cognitive effort are also explored on the basis of signaling theory.

A laboratory experiment with 120 subjects was used to empirically test the proposed research hypotheses. The subjects were randomly assigned to two treatment groups, with 60 subjects in each group. ANOVA, linear regression and binary logistic regression were used.

The emotional content of online customer reviews positively influences perceived product quality, which subsequently and positively affects purchase decisions. The emotional content of online customer reviews greatly influences perceived product quality when perceived empathy or cognitive effort is high.

This study is the first to extend extrinsic cues to emotional content on the basis of signaling theory and reveals the important role of emotional content of reviews. Moreover, the mediating effect of perceived product quality and the moderating effect of perceived empathy and cognitive effort illustrate the mechanism of the influence of emotional content on purchase decision. Findings demonstrate the positive signal of emotional content and provide important practical implications for sellers and customers.

This article aims to advance a new theoretical perspective on the basis of prosumption theory, namely, that online review platforms can be conceptualized as prosumer communities (and online reviews as prosumer-generated content). This perspective meshes with message tuning research to suggest specific mechanisms through which peer-to-peer prosumption takes place in online review communities. Overall, this article enriches and deepens theoretical understanding of prosumption behavior in the product review context and offers practical advice for inducing high-value, prosumer-generated content in online communities.

Exploratory observations of current practices across a wide spectrum of review platforms were conducted. The observed platforms include independent review sites (e.g. Yelp) and review sites affiliated with e-tailers (e.g. Amazon), general review sites (e.g. Viewpoints) and product-specific review sites (e.g. Healthgrades), large-scale review sites (e.g. TripAdvisor) and review sites of a smaller scale (e.g. Judy’s Book) and review sites based in different geographic regions, including Australia (e.g. Productreview.com.au), China (e.g. Taobao), Europe (e.g. Reevoo), India (e.g. Zomato) and North America (e.g. Foursquare).

Theoretical analysis suggests that high-quality review content is the result of collaborative prosumption characterized by three distinct value-adding processes: history-based message tuning, audience-based message tuning and norm-based message tuning. In-depth observations reveal that today’s review platforms are leveraging these value-adding processes to varying degrees. The overwhelming diversity of the observed platform features points to the need for more research on platform design and management.

This research identifies three distinct dimensions of review quality – novelty, relevancy and congruency – that can be systematically managed through platform design. The exploratory nature of this research necessitates follow-up work to further investigate how high-quality review content emerges in the historical, interpersonal and cultural contexts of online prosumer communities.

The prosumption-inducing mechanisms identified in this research have major consumer welfare and strategy implications. First, they may lead to novel, relevant and congruent consumer reviews. Second, they may enhance the value of brand communities (which rely heavily on collaborative prosumption).

This research addresses two intriguing questions pertinent to marketing theory and practice in the digital era. First, how do high-quality reviews emerge on product review platforms (which consist of ordinary consumers)? Second, what constitutes high-quality review content and how can platform managers facilitate the collaborative creation of high-quality review content by ordinary consumers?

As for academic papers, the customary methods for assessing the impact of books are based on citations, which is straightforward but limited to the coverage of databases. Alternative metrics can be used to avoid such limitations, such as blog citations and library holdings. However, content-level information is generally ignored, thus overlooking users’ intentions. Meanwhile, abundant academic reviews express scholars’ opinions on books, which can be used to assess books’ impact via fine-grained review mining. Hence, this study aims to assess books’ use impacts by conducting content mining of academic reviews automatically and thereby confirmed the usefulness of academic reviews to libraries and readers.

Firstly, 61,933 academic reviews in Choice: Current Reviews for Academic Libraries were collected with three metadata metrics. Then, review contents were mined to obtain content metrics. Finally, to identify the reliability of academic reviews, Choice review metrics and other assessment metrics for use impact were compared and analysed.

The analysis results reveal that fine-grained mining of academic reviews can help users quickly understand multi-dimensional features of books, judge or predict the impacts of mass books, so as to provide references for different types of users (e.g. libraries and public readers) in book selection.

Book impact assessment via content mining can provide more detail information for massive users and cover shortcomings of traditional methods. It provides a new perspective and method for researches on use impact assessment. Moreover, this study’s proposed method might also be a means by which to measure other publications besides books.

Content analysis was used to determine how a sample of 32 gay and lesbian novels for young adults were treated in 158 reviews from five prominent reviewing journals. Findings indicate that most reviews (84.8 percent) were favourable, many (79.7 percent) contained clear reference to the homosexual content, and there were few differences between the individual reviewing journals. Some reviews contained cautions and warnings about the gay and lesbian content, some denied or downplayed it, some justified the content if it was used to teach a lesson, and most described these stories as “problem” novels. Analysis also showed that gay and lesbian fiction is now regarded as a distinct genre of young adult literature. While librarians wishing to identify gay and lesbian fiction for collection development will be able to do so through the reviewing media, ambivalence about this literature and the young adults it represents was also evident in the reviews.

Drawing on attribution theory, the current paper aims to examine the effects of review content structures on online review helpfulness, focusing on three pertinent variables: review sidedness, information factuality, and emotional intensity at the beginning of a review. Moreover, the moderating roles of reviewer reputation and review sentiment are investigated.

The review sentiment of 144,982 online hotel reviews was computed at the sentence level by considering the presence of adverbs and negative terms. Then, the authors quantified the impact of variables that were pertinent to review content structures on online review helpfulness in terms of review sidedness, information factuality and emotional intensity at the beginning of a review. Zero-inflated negative binomial regression was employed to test the model.

The results reveal that review sidedness negatively affects online review helpfulness, and reviewer reputation moderates this effect. Information factuality positively affects online review helpfulness, and positive sentiment moderates this impact. A review that begins with a highly emotional statement is more likely to be perceived as less helpful.

Using attribution theory as a theoretical lens, this study contributes to the online customer review literature by investigating the impact of review content structures on online review helpfulness and by demonstrating the important moderating effects of reviewer reputation and review sentiment. The findings can help practitioners develop effective review appraisal mechanisms and guide consumers in producing helpful reviews.

The purpose of this paper is to advance in research on consumer psychology of hospitality, since it investigates how online search behavior of users (particularly, information search and choice) is influenced by the opinions of other people in a new context characterized by the generalized use of Web 2.0 applications.

Empirical research was carried out in the hotel sector in Iberian Peninsula, where two Web 2.0 applications are especially relevant for users: the review Web sites and the hotel interactive Web sites. A qualitative method (in-depth interviews with hotel managers) and a quantitative technique (personal surveys to a sample of 830 users) were used to conduct this research.

The results indicates that the perceived influence on behavior of the user-generated content on these Web 2.0 applications is determined, in both cases, by the value of the information, the credibility of the sources and the degree of similarity between the user and the creators of content.

Firms should have an active presence in the review Web sites and the hotel interactive Web sites, and use these platforms for market research and communication. Firms should engage users to post content, support their credibility and facilitate the evaluation of the content generators’ similarity.

This paper is the first study in the hospitality literature that develops and empirically tests an integrative model explaining the perceived influence on behavior of user-generated content on Web 2.0 applications.

We investigate the joint impacts of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of reviews and attitude toward the product/service reviewed.

We performed three studies to test our research model, presenting participants with scenarios involving product reviews and prior users' helpful and unhelpful votes across experimental settings.

A high helpfulness ratio boosts users’ trust and influences behaviors in both positive and negative reviews. This effect is more pronounced in attribute-based reviews than emotion-based ones. Unlike the ratio effect, helpfulness magnitude significantly impacts only negative attribute-based reviews.

Future research should investigate voting systems in various online contexts, such as Facebook post likes, Twitter microblog thumb-ups and up-votes for article comments on platforms like The New York Times.

Our findings have significant implications for voting system-providers implementing information techniques on third-party review platforms, participatory sites emphasizing user-generated content and online retailers prioritizing product awareness and reputation.

This study addresses an identified need; that is, the helpfulness votes as an additional trust cue and the joint effects of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of customers in reviews and their consequential attitude toward the product/service reviewed.