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•Explores how consumers process information from online consumer reviews.•Explores how consumers assess trustworthiness of online consumer reviews.•Based on interviews with 38 users ...of online reviews having various backgrounds.•Develops a new theoretical framework to explain perceived review trustworthiness.
Online consumer reviews (OCRs) are increasingly used by consumers to make informed decisions about tourism-related products. However, there is an increase in concern about the level of trustworthiness of OCRs. As yet, little is known about how consumers assess trustworthiness and untrustworthiness of OCRs. This study aims to fill this gap by using a grounded theory approach based on 38 interviews with users of OCRs. Results show that consumers primarily use cues related to the message content and style and review extremity and valence to assess trustworthiness. Findings indicate that moderating variables such as consumer involvement and experience as well as the type of website affects the way consumers assess trustworthiness. Reviews perceived as untrustworthy are discounted by consumers.
Past empirical studies have analysed the influence of manifest online review content factors and the reviewer-related factors on online review helpfulness. However, the influence of latent content ...factors, which are implied from the text and that result in the differential helpfulness perceptions of review receivers, have been ignored. Hence, using the lens of the Elaboration Likelihood Model (ELM), we develop a comprehensive model to study the influence of content- and reviewer-related factors on review helpfulness. This study not only includes the manifest content-related and reviewer-related factors, but also the latent content factors consisting of argument quality (comprehensiveness, clarity, readability and relevance) and message valence. The study initially employs a manual content analysis to analyse the argument quality of ~500 TripAdvisor reviews (Study 1). Subsequently, model testing techniques are used to study the holistic and relative influence of these different factors on review helpfulness. In the validation study (Study 2), Machine Learning and Natural Language Processing techniques are used to extract latent content information and test the above model with 50,000 reviews from Yelp.com. The results show that latent review content variables like argument quality and valence influence the helpfulness of the reviews better and beyond the previously studied, manifest review content- and reviewer-related factors.
•Latent content factors (argument quality and review valence) are significant predictors of review helpfulness.•The study operationally defines argument quality which comprises of comprehensiveness, clarity, readability and relevance.•A comprehensive review reduces uncertainty around different product/service attributes.•Enhanced clarity and readability leads to greater adoption of message recommendation in an online review.•Irrelevant content in reviews reduces its helpfulness.•Influence of message valence is complex. Positive reviews are deemed less helpful than negative ones.
•Under a centralized channel, OCRs may increase or decrease the direct price but always lower the retail price.•Under the decentralized channel, the manufacturer has a higher probability to charge a ...higher direct price than under the centralized channel, and the retailer also has the chance to improve the retail price.•It is not necessarily wise for the manufacturer to provide OCRs in the Internet channel unless the information revealed by OCRs is sufficiently favorable, no matter what the channel structure is.
This paper investigates the effects of online consumer reviews (OCRs) in a dual channel where the manufacturer distributes a product through a retail channel and an Internet channel. We develop game-theoretic models to capture both players’ pricing decisions and profits with OCRs, under two different channel structures. In specific, under the centralized channel, OCRs may increase or decrease the direct price but always lower the retail price. Under the decentralized channel, we show that the manufacturer has a higher probability to charge a higher direct price than under the centralized channel, and the retailer also has the chance to improve the retail price. Further, under the two channel settings, it is not necessarily wise for the manufacturer to provide OCRs in the Internet channel unless the information revealed by OCRs is sufficiently favorable.
Peer-to-peer business models rely on interpersonal communication for their success. In this article, we focus on Airbnb - an exemplar of the so-called 'sharing economy' - and more specifically, on ...Airbnb's reciprocal reviewing system, which enables both hosts and guests to review one another. Our study takes a computer-assisted, qualitative approach to explore linguistic patterns of evaluation in Airbnb reviews. Our findings indicate that Airbnb reviews tend to comprise a very restricted set of linguistic resources, establishing the site's norm of highly positive commentary, which in turn makes Airbnb reviews, on the surface, appear to be quite similar to one another. However, a micro-analytic comparison of positive reviews reveals that less-than-positive experiences are sometimes communicated using more nuanced, subtle cues. This study contributes to existing literature on electronic word of mouth in the tourism industry by highlighting how evaluation is communicated, while simultaneously responding to hospitality scholars' calls for analyses which extend beyond the star ratings and also take into account consumers' constructions of experience in the review texts themselves.
Online reviews exert a considerable influence on consumer purchase behavior, yet there remains ambiguity about the most effective managerial response strategies for positive and negative reviews. ...Addressing this gap, our study introduces a Strategy-Aware, Deep Learning-Based Natural Language Processing (Sa-DLNLP) model designed to optimize firm responses. The proposed model underwent rigorous evaluation through a human-coded study and was subsequently validated by a separate user response study. Our findings reveal that active-constructive responses significantly enhance the impact of positive reviews, whereas passive-constructive strategies are more effective in mitigating the damage from negative reviews. Additionally, the study underscores the importance of concise, personalized, and prompt responses across the board. Interestingly, responses that are overly explanatory, excessively empathetic, or challenge customers were found to be counterproductive when dealing with negative reviews. This study not only demystifies the art of managing online reviews but also offers an advanced deep learning methodology that can directly benefit the disciplines of Information Systems and Management.
This study explores the role of language style in the perceived quality of online reviews. Drawing from research in psychology and sociology, we posit that language style matching (LSM) of a ...review—the degree to which the language style of a review matches the language style of intended customers—directly influences the perceived quality of the review. We also propose that LSM should matter more when processing fluency is greatly needed such as when customers learn about new products and process complicated product information. Using restaurant reviews from Yelp, we calculate the LSM score for every review to measure the distance between the language style of the focal review and the typical language style of the restaurant's intended customers. We find that LSM has a significant and positive effect on the number of useful votes received by a review. In addition, the effect of LSM is more pronounced for less familiar restaurants and for more complicated reviews. We discuss the implications of these findings for online review platforms, restaurant managers, and online review writers and close by identifying several opportunities for further research.
•Yelp review data indicates that the perceived quality of a review is impacted by the degree the review's language style matches that of the intended customer.•The magnitude of the LSM effect critically depends on the restaurant and review characteristics.•LSM's effect is more pronounced for reviews on less familiar restaurants like those mainly attracting travelers and non-chain restaurants.•LSM also matters more for complex reviews that require a higher education level to comprehend and reviews that use many informal words.
The influence of positive online consumer reviews on a traveler's decision making remains unclear. To better understand the perceived usefulness of online reviews, this study conducts two experiments ...using positive and negative online consumer reviews. Study results suggest that high risk-averse travelers find negative online reviews more useful than positive reviews. For positive online reviews, high-risk averse travelers feel expert reviewers' postings, travel product pictures, and well-known brand names enhance usefulness of the positive online reviews. These findings offer interesting implications for both marketing theory and practice.
We examine how open and closed review posting policies play differentiating roles in creating social media bias. As a supplementary method to existing ones detecting fake reviews, we develop a trust ...measure estimating how genuine the review is, based on the frequent usage of strongly positive or negative words. Using the hotel industry as our application context, we empirically demonstrate that our trust measure serves as a correction factor that reduces social media bias. Interestingly, we observe particular hotel service features revealing strong upward manipulation to promote the businesses (for example, positive overall recommendation, interesting surroundings, and personal travel). By contrast, we identify some other features that reveal the presence of strong downward manipulation (for example, negative overall recommendation, disappointing room amenities, and poor atmosphere). From a practical perspective, this research can help both managers and consumers make better informed decisions by reducing the impact attributable to social media manipulation.
•Our trust measure based on extreme terms supplements existing algorithms reducing social media bias.•We empirically support the validity of our extreme-term-based approach.•We identify particular hotel service features vulnerable to upward or downward manipulation.•Overall positive and negative evaluations are reduced after we correct for fake reviews.
This article examines how product and consumer characteristics moderate the influence of online consumer reviews on product sales using data from the video game industry. The findings indicate that ...online reviews are more influential for less popular games and games whose players have greater Internet experience. The article shows differential impact of consumer reviews across products in the same product category and suggests that firms' online marketing strategies should be contingent on product and consumer characteristics. The authors discuss the implications of these results in light of the increased share of niche products in recent years. PUBLICATION ABSTRACT
Consumers are increasingly using online consumer reviews (OCRs) to learn about product quality. It is thus paramount for marketers to understand what makes OCRs helpful to consumers and how this ...evaluation affects their decisions. Dual-process theory has been adopted in this study to investigate the informational and normative predictors of information diagnosticity and its links with consumers' information adoption.
The findings suggest that consumers are primarily influenced by the quality of information and subsequently influenced by customer ratings and overall rankings. These results imply that both of the aforementioned informational and normative cues are critical to consumers in evaluating the quality and performance of products through OCRs. The results show that information quantity and source credibility have a limited effect on information diagnosticity, which ultimately influences consumers' information adoption. This study extends the application of dual-process theory to online settings, the findings are valuable for marketing managers of online organisations.
•Investigates the informational and normative predictors of information diagnosticity•Consumers are primarily influenced by the quality of information in online reviews.•Consumers are also influenced by product ratings and by the overall product ranking.•Source credibility has a limited effect on information diagnosticity.•Information diagnosticity influences consumers' information adoption.
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