Consumer-generated Product Reviews Research Articles

A Dynamic Structural Model of Endogenous Consumer Reviews in Durable Goods Markets

Consumers commonly seek quality information from product reviews when their perceived quality of new products remains uncertain. However, consumer-generated product reviews are endogenous and may be subject to potential biases that impact consumer's purchase behavior. In this paper, We develop a dynamic structural learning model and a consumer review-reporting model to quantify the causal impacts of critic reviews and consumer reviews biases on forward-looking consumer adoption behavior in the U.S. video-game market. Our datasets consist of a novel component of pre-order sales (sales realized prior to product launch), post-release sales and prices at product level from 2009 to 2012, and individual-level online critics and consumer ratings. Our study includes two parts. First, we leverage pre-order information to separately identify the impacts of critics and consumer's prior expectation on purchase behavior. Second, we find systematic differences between critics and consumer ratings: the average of consumer ratings tends to become lower (higher) when critics are higher (lower). Therefore, a standard Bayesian learning model cannot be directly applied since such systematic differences are not merely driven by sampling errors when quality signals are drawn from distributions of true product quality. We propose that the observed differences could be driven by consumer review biases due to a combination of self-selection effect and reference point effect. We propose a novel review-reporting model that rationalizes the observed discrepancies between critics and consumer ratings. We then implement a joint estimation strategy to estimate the combined model using Bayesian Markov chain Monte Carlo (MCMC) algorithm that is applicable to a non-stationary dynamic discrete choice model with potential price, and consumer review endogeneity problems. Using structural model estimates, we examine the causal impacts of critics and consumer reviews on firms' profits. To assess these impacts, we conduct counterfactual experiments by sequentially eliminating critics and consumer reviews. The results of the proposed model can provide important managerial implications with respect to dynamic pricing and preorder strategies.

Finding eWOM customers from customer reviews

PurposeThe purpose of this paper is to identify electronic word-of-mouth (eWOM) customers from customer reviews. Thus, firms can precisely leverage eWOM customers to increase their product sales.Design/methodology/approachThis research proposed a framework to analyze the content of consumer-generated product reviews. Specific algorithms were used to identify potential eWOM reviewers, and then an evaluation method was used to validate the relationship between product sales and the eWOM reviewers identified by the authors’ proposed method.FindingsThe results corroborate that online product reviews that are made by the eWOM customers identified by the authors’ proposed method are more related to product sales than customer reviews that are made by non-eWOM customers and that the predictive power of the reviews generated by eWOM customers are significantly higher than the reviews generated by non-eWOM customers.Research limitations/implicationsThe proposed method is useful in the data set, which is based on one type of products. However, for other products, the validity must be tested. Previous eWOM customers may have no significant influence on product sales in the future. Therefore, the proposed method should be tested in the new market environment.Practical implicationsBy combining the method with the previous customer segmentation method, a new framework of customer segmentation is proposed to help firms understand customers’ value specifically.Originality/valueThis study is the first to identify eWOM customers from online reviews and to evaluate the relationship between reviewers and product sales.

When in Doubt, Elaborate? How Elaboration on Uncertainty Influences the Persuasiveness of Consumer-Generated Product Reviews When Reviewers Are Incentivized

textabstractOnline consumer-generated reviews contain two types of information: core (the review itself) and auxiliary (information accompanying reviews such as details about the reviewer and the review-generating process). Prior work has focused primarily on the former, despite the latter being commonplace. In this paper, we consider how a common type of auxiliary information — disclosure statements about incentives received by reviewers — affects review persuasiveness. Disclosure likely induces uncertainty about reviewer trustworthiness, leading consumers to discount reviewers’ opinions when forming expectations about product quality. However, we show this is not always the case. Instead, the extent to which disclosing incentives affects review persuasiveness depends on whether consumers deem their disclosure-induced uncertainty to be integral or incidental to judgment formation. This occurs through a metacognitive process in which consumers elaborate on the relevance of their uncertainty. Using a field study and three experiments, we show that when disclosure-induced uncertainty about reviewer trustworthiness is deemed to be integral, product evaluations are affected by this uncertainty. However, when uncertainty is incidental to judgment formation, product evaluations are unaffected.

Learning Extraction of Chinese Comparative Sentences for Evaluative Text

With the prevalence of Web 2.0, people increasingly prefer to express opinions and exchange information through CGM (consumer-generated media), such as blog, Internet forum and etc. Many studies pay attention to extract and analysis user opinions in consumer reviews. This paper studies how to automatically extract Chinese comparative sentences from consumer reviews. At first, the paper describes a method for solving the class imbalance problem of comparatives and non-comparatives in review data. Then we built a support vector machine learning model to classify comparatives and noncomparatives into different group on a balanced dataset. Experiments were conducted on consumer-generated product reviews, including 9600 sentences, of which 1,624 (16.92% of the total) were comparisons. Experiments show an overall F-score of 87.26%, which presents the effectiveness of the proposed approach.

Listen to Your Customers: Insights into Brand Image Using Online Consumer-Generated Product Reviews

ABSTRACTOnline consumer-generated product reviews are a growing phenomenon and have led to the posting of colossal amounts of data by consumers on the Web. These data include consumers’ thoughts, opinions, and feelings about brands and offer firms the opportunity to “listen in” on consumers to get a better understanding of the topics discussed about their brands. Using the human associative memory model as the theoretical framework, the authors introduce an approach to convert online product reviews into meaningful information about brand images using a novel combination of text mining and network analysis methodologies. Following a network-based understanding of brand image, the authors use online product reviews to extract consumers’ brand associations and their interconnections as well as to depict and characterize the network of brand associations. In an empirical study, the authors test the approach and illustrate its managerial usefulness. The suggested approach allows managers to effectively monitor and detect strengths and weaknesses of brand image. Moreover, the proposed approach is one of the first attempts to measure brand image using consumer-generated content by applying text mining and network analysis.

Following the breadcrumbs: An analysis of online product review characteristics by online shoppers

Consumer-generated product reviews are a driving force behind online purchases; at the same time, unfavorable reviews can discourage interested online shoppers and eventually hurt the brand. The objective of this exploratory study was to analyze a diverse range of characteristics and the valence of online product reviews that would aid in responding to customer dissatisfaction. Product reviews (N = 1982) from Amazon.com were collected and content analyzed. Some of the key findings include the following: (a) price was the most commonly discussed product feature; (b) online shoppers found two-sided reviews to be most informative, contradicting the commonly held assumption that negative reviews were more informative and diagnostic in nature; and (c) ‘no action’ was the most common end action across two-sided and negative reviews, indicating that varying levels of dissatisfaction might not always lead to a negative end action. Implications for marketers are discussed.

Database Submission—Market Dynamics and User-Generated Content About Tablet Computers

Our Tablet Computer data set, collected from various websites, contains market dynamics related to 2,163 products, characteristics of 794 products, more than 40,000 consumer-generated product reviews, and information about 39,278 reviewers. The market dynamic information was collected weekly for 24 weeks starting February 1, 2012. Our Tablet Computer data set comprises four tables: the Market Dynamics of Products, Product Characteristic Information, Consumer-Generated Product Reviews, and Reviewer Information tables. In turn, it offers three unique properties. First, it contains both structured product information and unstructured product reviews. Second, it comprises product characteristic information and market dynamic information. Third, this data set integrates user-generated content with manufacturer-provided content. This integrated data set (available at http://pubsonline.informs.org/page/mksc/online-databases ) is valuable for both academics and practitioners who conduct research related to marketing, information systems, computer science, and other fields using digital data readily available through the Internet.

The judgment about product quality based on the consumer-generated product reviews in the weblog: A lens model analysis

렌즈모델은 사회판단이론의 개념적인 분석틀로 특정한 생태환경에서 형성되는 인간의 판단과정을 연구하는데 분석적인 힘을 갖고 있다. 연구결과, 판단자는 실제 제품사용자가 제품을 사용한 경험을 게시한 60개의 판단프로필을 제공받았으며 60개의 판단프로필에서 그들이 내린 판단은 실제 블로거가 제품사용 후 내린 판단과 높은 상관을 보였다. 또한 판단자의 판단모델은 제품포장, 사용장면, 세밀한 제품사진, 제품로고나 이미지 등 제품을 실제로 사용한 사진이미지에 가장 큰 가중치를 두었다. 한편 블로그의 제품사용후기를 통해 제품품질을 판단하는데 있어 소비자는 높은 지식수준을 보였다.

Our Brand or Their Brand? Consumers' Responses to Negative Consumer-Generated Product Reviews Regarding Domestic versus Foreign Brands

With the growth of Web 2.0 technologies, more and more consumers share product-related information with many other consumers on various web platforms, such as product review websites (e.g., epinions.com), brand websites (e.g., dell.com), retailer websites (e.g., amazon.com), and social media. However, the question of how credible such product information is has arisen. On the Internet, the anonymous nature of consumer product reviews makes it difficult for consumers to evaluate review quality and credibility. Due to the lack of assurance of product review veracity, consumers often depend on cues to evaluate the review content accurately. One of such cues is the valence of the review: either positive or negative. Between these two valences, negative reviews have been known to be more attention getting and diagnostic than positive reviews. Thus, this study only focused on negative reviews. Another cue can be the consensus level of the review (i.e., the degree to which other consumers agree with the product opinion of the reviewer). Finally, consumers may consult the brand origin of the target brand in product reviews (either domestic or foreign brand). To date, however, little research has focused on the role of consumer ethnocentrism on brand evaluations in the context of online product reviews, despite today's consumers often being exposed to both domestic and foreign brand product reviews in a globalized economy where major firms have multiple international branches. Thus, the purpose of this study is to examine how different cues influence consumers' responses to negative online reviews about domestic and foreign brands. Toward that end, this study explores how a consumer's personality trait (level of ethno-centrism) interacts with brand origin and a property of the medium (consensus information) to influence his or her brand attitude. To test the proposed hypotheses, a 2 (Brand origin: domestic versus foreign) x 2 (Consumers' ethnocentrism: high versus low) x 2 (Consensus level: high versus low) between-subjects experiment was used. As experimental stimuli, four fictitious online retailing web pages including product reviews about a laptop computer (negative review of a domestic brand with high consensus, negative review of a domestic brand with low consensus, negative review of a foreign brand with high consensus, and negative review of a foreign brand with low consensus) were created. An Analysis of Covariance (ANCOVA) was run to test the hypothesized relationships with prior attitude toward target brand and participants' interest in buying a laptop as covariates. The results showed that there was a significant two-way interaction effect between brand origin and consumer ethno-centrism on attitude change. Consistent with predictions, when consumers' ethnocentrism levels were high, consumers exposed to the negative review of the foreign brand exhibited significantly greater attitude change than did those exposed to the negative review of the domestic brand in a less favorable way. In contrast, when consumers' ethnocentrism levels were low, no difference appeared between the negative review of the domestic brand and the negative review of the foreign brand in attitude change. When exposed to the negative review, attitude toward the brand was degraded for less ethnocentric consumers regardless of brand origin. Further, three-way interaction effects among brand origin, consumer ethnocentrism, and consensus level on attitude change were found. Under high-consensus condition, a negative review of the foreign brand led highly ethnocentric consumers' brand attitudes to deteriorate, compared to a negative review of the domestic brand. Contrarily, for less ethnocentric consumers, however, there was no difference between the negative review of the domestic brand and the negative review of the foreign brand in attitude change. Under low-consensus condition, there was no difference between highly and less ethnocentric consumers in attitude change. The findings of this study suggest that the detrimental effect of negative reviews can be buffered under some circumstances. Consumers with prior attitudes toward brands tend to resist negative review of their favored brands even under high-consensus conditions. Practically, this finding implies the importance of retaining existing consumers who already have prior attitudes toward the brand. Additionally, the findings of this study suggest that consensus information, as a heuristic cue, serves as a useful indicator of review credibility. Review web sites can help consumers' product judgments by providing consensus information. Lastly, this study used real brand names rather than fictitious brand names. Since this study takes into account consumers' pre-existing beliefs and attitudes, its findings are applicable more easily to real-market situations than are findings regarding fictitious brand names.

Online Persuasion: How the Written Word Drives WOM

<h3>ABSTRACT</h3> Consumer-generated product reviews are important sources of information for producers and consumers. This research includes two studies designed to investigate how language style, organizational structure, and other content features affect the perceived helpfulness of online product reviews. In study 1, researchers analyzed a data set of online product reviews regarding a consumer electronic device and identified content characteristics shared by helpful reviews. Study 2 used an experimental approach to probe the boundary conditions under which specific content features may or may not influence review helpfulness.

Examining the Relationship Between Reviews and Sales

Consumer-generated product reviews have proliferated online, driven by the notion that consumers' decision to purchase or not purchase a product is based on the positive or negative information abo...

Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets

Consumer-generated product reviews have proliferated online, driven by the notion that consumers' decision to purchase or not purchase a product is based on the positive or negative information about that product they obtain from fellow consumers. Using research on information processing (Chaiken 1980) as a foundation, we suggest that in the context of an online community, reviewer disclosure of identity-descriptive information is used by consumers to supplement or replace product information when making purchase decisions and evaluating the helpfulness of online reviews. Using a unique dataset based on both chronologically compiled ratings as well as reviewer characteristics for a given set of products and geographical location-based purchasing behavior from Amazon, we provide evidence that community norms are an antecedent to reviewer disclosure of identity-descriptive information. Amazon members rate reviews containing identity-descriptive information more positively, and the prevalence of reviewer disclosure of identity information is associated with increases in subsequent online product sales. In addition, we show that when reviewers are from a particular geographic location, subsequent product sales are higher in that region, thus highlighting the important role of geography in electronic commerce. Taken together, our results suggest that identity-relevant information about reviewers shapes community members' judgment of products and reviews. Implications for research on the relationship between online reviews and sales, peer recognition systems, and conformity to online community norms are discussed.

Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets

Consumer-generated product reviews have proliferated online, driven by the notion that consumers' decision to purchase or not purchase a product is based on the positive or negative information about that product they obtain from fellow consumers. Using research on information processing as a foundation, we suggest that in the context of an online community, reviewer disclosure of identity-descriptive information is used by consumers to supplement or replace product information when making purchase decisions and evaluating the helpfulness of online reviews. Using a unique data set based on both chronologically compiled ratings as well as reviewer characteristics for a given set of products and geographical location-based purchasing behavior from Amazon, we provide evidence that community norms are an antecedent to reviewer disclosure of identity-descriptive information. Online community members rate reviews containing identity-descriptive information more positively, and the prevalence of reviewer disclosure of identity information is associated with increases in subsequent online product sales. In addition, we show that shared geographical location increases the relationship between disclosure and product sales, thus highlighting the important role of geography in electronic commerce. Taken together, our results suggest that identity-relevant information about reviewers shapes community members' judgment of products and reviews. Implications for research on the relationship between online word-of-mouth (WOM) and sales, peer recognition and reputation systems, and conformity to online community norms are discussed.

Internet-facilitated consumer-to-consumer communication: the moderating role of receiver characteristics

This study explores relationships among several factors that may influence the persuasive power of online consumer-to-consumer communication. The results call into question the assumption that consumer remarks posted on an independent online forum will automatically be more persuasive than remarks posted on a corporate website. Instead, the findings suggest that reactions to consumer-generated product reviews are moderated by receiver characteristics such as product involvement and experience with offline consumer-to-consumer communication.