Do same-level review ratings have the same level of review helpfulness? The role of information diagnosticity in online reviews

This research examines whether the written contents of online reviews can generate systematic differences in the review’s perceived helpfulness even with identical ratings. In addition, this research explores which underlying psychological mechanism creates the systemic differences related to helpfulness. Specifically, the results from our two experiments demonstrate that, when an online hotel review has a positive rating, written contents containing both positive and negative information is perceived as more helpful than reviews with only positive written content. In contrast, when an online hotel review has a negative rating, written contents that contain only negative information is perceived as more helpful than reviews with written content containing both positive and negative information. Importantly, our study shows that the degree of information diagnosticity in online reviews behaves as an underlying psychological mechanism in the process. Our findings not only contribute to the extant literature but also provide useful insights and practical implications for travel websites

When consistency matters: the effect of valence consistency on review helpfulness

When evaluating the helpfulness of online reviews, review valence is a particularly relevant factor. This research argues that the influence of review valence is highly dependent on its consistency with the valence of other available reviews. Using both field and experimental data, this paper show that consistent reviews are perceived as more helpful than inconsistent reviews, independent of them being positive or negative. Experiments show that this valence consistency effect is driven by causal attributions, such that consistent reviews are more likely to be attributed to the actual product experience, while inconsistent reviews are more likely to be attributed to some reviewer idiosyncrasy. Supporting the attribution theory framework, reviewer expertise moderates the effect of consumers' causal attributions on review helpfulness

In search of negativity bias:An empirical study of perceived helpfulness of online reviews

A basic tenet of psychology is that the psychological effects of negative information outweigh those of positive information. Three empirical studies show that the negativity bias can be attenuated or even reversed in the context of electronic word-of-mouth (eWoM). The first study analyzes a large sample of customer reviews collected from Amazon.com and concludes that negative reviews are no more helpful than positive ones when controlling for review quality The second study follows up with a virtual experiment that confirms the lack of negativity bias in evaluating the helpfulness of online reviews. The third study demonstrates that the negativity effect can be reversed by manipulating the baseline valences. This work challenges the conventional wisdom of “bad is stronger than good” and contributes to the understanding of the eWoM phenomenon

Understanding the Association between Star Ratings and Review Helpfulness: The Perspectives of Expectation Confirmation Theory and Negativity Bias

Consisting of textual, multimedia, and numerical information elements, online consumer reviews (OCR) have been considered an essential information source of products for prospective consumers. Researchers have made significant efforts to comprehend how these information elements are associated with OCRs’ information value or helpfulness. However, there is a paucity of theoretical evidence on consumers’ perception and evaluation of star ratings and their information, even though star ratings as numerical information cues can imply multiple meanings. In this study, we leverage (1) expectation-confirmation theory to delineate star ratings as the extent of consumer satisfaction and (2) negativity bias to explain the relationship between star ratings and helpfulness. Using 45,621 reviews of 20 products across three categories, we empirically find that our theoretical approaches improve our understanding of the effect of star ratings on helpfulness. Therefore, this study contributes to the extant literature on OCRs by providing the theory-based evaluation of star ratings in relation to helpfulness

The Impact Of The Collective Rating Presence On Consumers’ Perception

In online markets, collective ratings by prior buyers are often displayed in a marked place and influential for later consumers. While the aggregated ratings transfer overall evaluation towards products, they might also bring biases to potential consumers. In this study, we hypothesize that collective rating, as a piece of information, acts as 1) a predisposition which affects people’s perception towards other information; and 2) a risk level of product’s performance which changes the way people perceive consensus or deviant word-of-mouth information from online reviews. Using online reviews of multiple product categories from Amazon.com, our study reveals the impact of collective ratings on consumers’ perception of WOM information and sheds light upon the conflictive results on perception biases of product reviews. Implication for understanding and facilitating consumer perception of online reviews are discussed

Investigating Usefulness Configurations of Online Consumer Reviews: A Fuzzy-Set Qualitative Comparative Analysis

Online reviews have a significant impact on consumers’ purchasing decisions. Many researchers have studied the relationship between review usefulness based on various factors related to online review, but existing studies have focused only on the linear relationship between variables methodologically. Therefore, this study examines the usefulness of online reviews from a configurational perspective derived from the complex interactions between elements, and aims to identify how these configurations differ according to product types. This study developed a conceptual model by combining HSM and ELM based on the theoretical discussion on the information processing and analyzed 7,316 cases collected from Amazon.com using fsQCA. As a result, three configurations affecting online usefulness were derived from search goods and four from experience goods. In short, consumers consume reviews through the complex interaction of various factors related to reviews, and the factors affecting the usefulness of search goods and experience goods are different

How Product Reviews Impact Consumers’ Judgments, Emotions, and Purchase Behaviors

This dissertation explores the effect product reviews have on consumer emotions, judgments, and decisions. Especially with the continued growth of e-commerce, product reviews play an important role in consumer decisions. More than 90% of consumers in the United States have used online reviews to help them make a purchase (Kaemingk, 2020). The majority of consumers trust these online reviews at least as much as they trust personal and expert recommendations (Galante, 2018; Statista, 2021). Given the extensive use of review information, it is critical for marketers and researchers to understand how these reviews impact consumers. Chapter 1 examines how summary information about reviews for a product influences perceptions of individual reviews. Specifically, we study how manipulating the mean rating influences subsequent judgments of review helpfulness and search behavior. We find evidence of confirmation bias (Nickerson, 1998). Reviews with ratings close to or at the mean (i.e., confirmed the mean) are rated as more helpful, lead to more extreme belief updating, and are more likely to be searched than reviews with ratings further from the mean. We also find process evidence that suggests the mean rating significantly influences how consumers weight the information in reviews, with greater weight being placed on information that confirms the mean rating. Lastly, we find participants are more likely to search for reviews near the mean when they could freely select which reviews to read. Taken together, these results suggest there is significant confirmation bias in consumers’ judgments and behaviors when they are exposed to a product’s mean rating. Chapter 2 examines the role of emotion in product reviews and the effect it has on purchase behavior. Consumers consider the content or text of a review to be a highly influential feature of online reviews, above and beyond star ratings and total number of reviews (Podium, 2017). Additionally, sentiment analysis tools have surged in popularity, especially in marketing. However, these tools often provide a simplistic view of the emotional content and how it may impact consumers. Thus, Chapter 2 studies how the emotional content of a review influences the emotions experienced by consumers as they read the review, as well as their eventual product evaluations. First, we find the emotion experienced by the consumer reading the review to be a stronger predictor of perceived product quality than the emotion expressed by the author of the review. Second, we demonstrate the need to measure positive and negative emotion on separate scales, as opposed to treating them as opposite ends of a single scale. When measured with a single scale, it is ambiguous whether the midpoint refers to a review that is fairly bland or one with a high degree of conflicting emotions. Lastly, we establish the need to consider arousal as an additional dimension when measuring emotions in reviews. Valence and arousal jointly impact product evaluations by influencing the amount of positive and negative emotion felt by the reader. These results highlight the advantage of going beyond a single, unidimensional scale when measuring emotion in product reviews

Mobile word of mouth (m-WOM): analysing its negative impact on webrooming in omnichannel retailing

Purpose: The purpose of this research is to analyse the influence of mobile word of mouth (m-WOM), received at the physical store, which “challenges” the consumer's preferences in a webrooming experience. The impacts of the social relationship between the sender and the receiver of the m-WOM and product category (electronics versus fashion accessories) are examined. Design/methodology/approach: An online experiment was carried out which manipulated the presence and type of challenging m-WOM, and product category, in a 3 × 2 between-subjects factorial design. The participants were 204 consumers recruited through a market research agency. Their perceptions about the helpfulness of the m-WOM, and their product preferences and choices, were analysed. Findings: Receiving in-store m-WOM was perceived as helpful by webroomers and affected their preferences and choices. For electronics online reviews posted by anonymous customers were more influential than friends' opinions, whereas the opposite was the case with fashion accessories. The trustworthiness and expertise of the m-WOM source may explain the effects of m-WOM. Practical implications: m-WOM entails challenges and opportunities for retailers in the omnichannel era. The findings suggest that allowing customers to access m-WOM may be beneficial; however, retailers must consider the type of m-WOM that may be most suitable for their businesses. Recommendations for referral and review sites are also offered. Originality/value: This study examines the impact of challenging m-WOM on shopping experiences, combining online, mobile and physical channels. The results revealed the importance of the information source and product category in the determination of consumers' perceptions of helpfulness, preferences and choice

A Recommender System for Online Consumer Reviews

Online consumer reviews have helped consumers to increase their knowledge about different products/services. While most previous studies try to provide general models that predict performance of online reviews, this study notes that different people look for different types of reviews. Hence, there is a need for developing a system that that is able to sort reviews differently for each user based on the ratings they previously assigned to other reviews. Using a design science approach, we address the above need by developing a recommender system that is able to predict the perceptions of each user regarding helpfulness of a specific review. In addition to addressing the sorting problem, this study also develops models that extract objective information from the text of online reviews including utilitarian cues, hedonic cues, product quality, service quality, price, and product comparison. Each of these characteristics may also be used for sorting and filtering online reviews

Do Human Faces Matter? Evidence from User-Generated Photos in Online Reviews

The importance of online reviews in e-commerce cannot be overstated, but few studies have focused on user-generated photos (UGPs) in reviews, especially human faces in UGPs. In this study, using Amazon online review data, we divide online reviews into text with UGPs, UGPs with faces, and UGPs with multiple faces based on the presence and number of faces, and discuss their effects on review helpfulness. Drawing on media richness theory and emotional contagion effects, we argue that faces provide a richness of information that can increase the effectiveness of photos as information mediators. Moreover, we argue that facial expressions and emotional states, as read-in and read-out devices that convey individual emotions, affect other consumers\u27 perceived review helpfulness. This study contributes to the literature on online reviews, media richness theory, and emotional contagion effects, while providing practical insights for e-commerce sites and consumers seeking to write effective online reviews