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This is the seventh annual update of the bibliography that was published as a supplement to the first issue of Online Review. It is also the first update to the recently published concatenated bibliography containing the original issue plus the first six updates. This update covers the approximate time period late 1982 through early 1984. It contains 931 references.

This study aims to investigate the influence of the reviewed establishment’s price level and the user’s social network size and reputation status on consumers’ tendency to post more visual imagery content. Furthermore, it explores the moderating effects of user experiences and geographic distance on these dynamics.

This study adopts a multi-method approach to explore both the determinants behind the sharing of user-generated photos in online reviews and their internal mechanisms. Using a comprehensive secondary data set from Yelp.com, the authors focused on restaurant reviews from a prominent tourist destination to construct econometric models incorporating time-fixed effects. To enhance the robustness of the authors’ findings, the authors complemented the big data analysis with a series of controlled experiments.

The reviewed establishments price level and the users reputation status and social network size incite corresponding motivations conspicuous display “reputation seeking” and social approval motivating users to incorporate more images in reviews. “User experiences can amplify the influence of these factors on image sharing.” An increase in the users geographical distance lessens the impact of the price level on image sharing, but it heightens the influence of the users reputation and social network size on the number of shared images.

As a result of this study, high-end establishments can increase their online visibility by leveraging user-generated visual content. A structured rewards program could significantly boost engagement by incentivizing photo sharing, particularly among users with elite status and extensive social networks. Additionally, online review platforms can enhance users’ experiences and foster more dynamic interactions by developing personalized features that encourage visual content production.

This research, anchored in trait activation theory, offers an innovative examination of the determinants of photo-posting behavior in online reviews by enriching the understanding of how the intricate interplay between users’ characteristics and situational cues can shape online review practices.

The purpose of this study is to explore the impact of online reviews on answer adoption in virtual Q&A communities, with an eye toward extending knowledge exchange and community management.

Online reviews contain rich cognitive and emotional information about community members regarding the provided answers. As feedback information on answers, it is crucial to explore how online reviews affect answer adoption. Based on signaling theory, a research model reflecting the influence of online reviews on answer adoption is established and empirically examined by using secondary data with 69,597 Q&A data and user data collected from Zhihu. Meanwhile, the moderating effects of the informational and emotional consistency of reviews and answers are examined.

The negative binomial regression results show that both answer-related signals (informational support and emotional support) and answerers-related signals (answerers’ reputations and expertise) positively impact answer adoption. The informational consistency of reviews and answers negatively moderates the relationships among information support, emotional support and answer adoption but positively moderates the effect of answerers’ expertise on answer adoption. Furthermore, the emotional consistency of reviews and answers positively moderates the effect of information support and answerers’ reputations on answer adoption.

Although previous studies have investigated the impacts of answer content, answer source credibility and personal characteristics of knowledge seekers on answer adoption in virtual Q&A communities, few have examined the impact of online reviews on answer adoption. This study explores the impacts of informational and emotional feedback in online reviews on answer adoption from a signaling theory perspective. The results not only provide unique ideas for community managers to optimize community design and operation but also inspire community users to provide or utilize knowledge, thereby reducing knowledge search costs and improving knowledge exchange efficiency.

The paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a two-part tariff coordination mechanism.

To deal with this pricing conflict problems of dual-channel supply chain consisting of dominant manufacturer and a retailer, considering the fact that online reviews and in-sale service are important factors on consumers’ purchase decisions, the authors establish some basic models and exploit them to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a profit-sharing coordination mechanism.

The results show that the optimal online direct selling price is positively correlated with product perceived quality obtained from online reviews and negatively correlated with the in-sale service. The traditional retail price is positively correlated with the in-sale service and weakly correlated with online reviews. For the manufacturer and retailer, whether decentralized decision or coordination contract, their profits increase with the increase of the in-sale service in a certain range and quality perceived from spontaneous online reviews. Online reviews and in-sale service are important factors on consumers’ purchase decisions. Positive in-sale services and online reviews can provide consumers with a better shopping experience, thereby promoting their enthusiasm for shopping and improving their quality of life. The two-part tariff coordination mechanism improves the profits of the manufacturer and the traditional retailer, respectively, through the transfer fee.

The proposed approach can well analyze the channel conflicts and pricing problems between retailers and manufacturers with respect to product offline price and online price. The analysis and results can inform decision-making for manufacturers and retailers.

This paper aims to investigate textual characteristics of customer reviews that motivate companies to respond (sentiment negativity and sentiment deviation) and how aspects of these company responses (response intensity, length and tailoring) affect subsequent customer review quality (comprehensiveness and readability) over time.

Leveraging a large data set from a leading app website (Shopify), the authors combine text mining, natural language processing (NLP) and big data analysis to examine the antecedents and outcomes of online company responses to reviews.

This study finds that companies are more likely to respond to reviews with more negative sentiment and higher sentiment deviation scores. Furthermore, while longer company responses improve review comprehensiveness over time, they do not have a significant influence on review readability; meanwhile, more tailored company responses improve readability but not comprehensiveness over time. In addition, the intensity (volume) of company responses does not affect subsequent review quality in either comprehensiveness or readability.

This paper expands on the understanding of online company responses within the digital marketplace – specifically, apps – and provides a new and broader perspective on the motivations and effects of online company responses to customer reviews. The study also extends beyond the short-term focus of prior works and adds to literature on long-term effects of online company responses to subsequent reviews. The findings provide valuable insights for companies (especially those with apps) to enhance their online communication strategies and customer engagement.

This paper aims to evaluate and structure the basic heuristics consumers use in evaluating word-of-mouth (WOM) about luxury hotel brands while analyzing the impact of deception in online consumer reviews.

The research used a two-study mixed-methods approach, using interpersonal deception theory and social proof theory as lenses to conduct our analysis. For the first study, a qualitative conceptual mapping analysis was conducted, examining online consumer reviews to identify key concepts and their relationships in the context of luxury hotel brands. In the second study, the themes were further examined using a fuzzy-set qualitative comparative analysis to analyze their causal complexity and association between variables to determine how they influence the perceived helpfulness of online reviews for luxury hotel brands.

The results underline the importance of functional, objective variables, such as the number of reviews and stars, as social proof heuristics and other factors, including clout, authenticity and analytic tone, as interpersonal communication heuristics. Therefore, consumers use a combination of social and interpersonal communication heuristics to extract information from reviews and manage deception risk.

The paper contributes to the consumer–brand relationship literature by assessing the heuristics consumers use in evaluating online reviews and provides additional information for research in online reputation management.

This study’s results can help marketing practitioners and brand managers manage their online reputations better. It can also aid managers in improving their messaging on hotel websites to entice consumers to complete bookings. Heuristics play an essential role in such messaging and understanding them can help marketers appeal directly to their target market.

This study contributes to the literature on consumer–brand relationships by providing a framework of heuristics that consumers use when evaluating luxury service brands and contributes to WOM and online reputation research by highlighting factors that may make online reviews more helpful.

This chapter presents a summary of the literature on the influence of the Internet and other digital innovations on markets, consumers, and firms. The review leads to a list of topics in need of research in the general areas of big data, online and mobile advertising, consumer search, online privacy, online reviews, social networks, platforms for online transactions, and the impact of the Internet on retail markets, including multi-channel and omni-channel retailing. We discuss the big data approaches that have been applied to problems of targeting and positioning and suggest areas for further development of these approaches. We also discuss the emerging area of mobile advertising, which can further enhance targeting. On the consumer side, the evidence indicates that the Internet has greatly lowered the costs of search and access to retailers. Much of the consumer data are transmitted to sellers, and much of the online advertising is transmitted to consumers, through platforms, such as Google. We conclude that better models of competition among these platform firms are needed and that they need to be examined for anti-trust violations. While online retailing has grown rapidly, it still has a relatively small share of retail sales. Since sellers can combine the advantages of online and offline channels, it has been common for sellers to branch into multi-channel retailing. Given the increased availability of detailed consumer data, omni-channel selling, which emphasizes strategies for the various touchpoints that lead to a transaction, is an area for further development.

The aim of the chapter is to examine the importance and use of reviews in the marketing communication of selected spa tourism enterprises on the Internet. The subject of the research are reviews as an important part of the online reputation of spa tourism enterprises and the object of the research is marketing communication on the Internet. The chapter focuses on spas located in Slovakia. The primary sources are the results of a quantitative survey conducted by standardized observation of the websites and profiles of all spa tourism enterprises in Slovakia under study on the social networks Facebook, Instagram, and YouTube based on predetermined criteria. At the same time, the results of the primary survey are conducted by the method of questioning using the technique of structured interviews. The chapter uses theoretical research methods such as analysis and synthesis, induction and deduction, and generalization. The chapter presents the results of qualitative research using the Sankey diagram, processed by Atlas.ti software. The results of the research point to the fact that spa tourism enterprises in Slovakia use their own websites and social networks to communicate in the online environment, where they monitor both positive and negative reviews. However, they often do not work with reviews systematically enough and do not make use of standardized procedures and available technologies that would enable them to manage their online reputation more effectively.

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.

In this chapter, we introduce a new construct we call “Perceived Deception in Online Consumer Reviews” (PDOCR). Online reviews of products are very important to companies and customers, yet they are vulnerable to unethical representations. Even regardless of whether a deceptive review has been posted or not, we take the position that it is important to understand consumers’ perceptions of deception because it is a consumer’s perception that leads him or her to experience subsequent feelings and opinions and to consider follow-up actions. We draw on the literature and build on the Elaboration Likelihood Model and Cognitive Dissonance Theory to create an overarching framework of antecedents of PDOCR, consequences, and moderators. We also report findings from a sample of in-depth interviews with real consumers about their thoughts on these phenomena and related constructs. We use our framework and theories and the qualitative data to derive Research Questions that we hope will spur future research on these important issues.