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Nghiên cứu ảnh hưởng của nguồn thông tin đánh giá trực tuyến tới quyết định mua trực tuyến của người tiêu dùng Việt Nam
Abstract
Internet đã cung cấp cho người tiêu dùng phương tiện dễ dàng để có được thông tin sản phẩm từ những người tiêu dùng khác và cũng để chia sẻ kinh nghiệm tiêu dùng sản phẩm của chính họ. Hoạt động của người tiêu dùng đánh giá và xếp hạng sản phẩm trực tuyến, sau đó lan tỏa những nhận định hoặc đánh giá này tới những người tiêu dùng khác được gọi là đánh giá trực tuyến (Chatterjee, 2001). Trong bối cảnh TMĐT nói chung và bán lẻ trực tuyến nói riêng đang có sự phát triển mạnh mẽ, các bài đánh giá trực tuyến cung cấp cho người tiêu dùng trực tuyến những thông tin bổ sung về thương hiệu và sản phẩm, đồng thời thúc đẩy họ tiến tới quyết định lựa chọn mua hoặc không. Trên cơ sở tổng quan các nghiên cứu có liên quan, bài viết đã đề xuất mô hình nghiên cứu ảnh hưởng của nguồn thông tin đánh giá trực tuyến tới quyết định mua trực tuyến của người tiêu dùng tại Việt Nam. Kết quả nghiên cứu đã cho thấy, chất lượng nguồn thông tin đánh giá trực tuyến có tác động đáng kể tới quyết định mua hàng của người tiêu dùng trực tuyến. Thông qua kết quả nghiên cứu, tác giả cũng đưa ra một số thảo luận để làm rõ đặc trưng trong tiêu dùng trực tuyến của người tiêu dùng Việt Nam, đồng thời xác định một số hạn chế trong nghiên cứu và các hướng phát triển của nghiên cứu trong thời gian tới.
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The aim of this study is to identify the factors affecting the credibility of electronic word-of-mouth (eWOM) stimulation through Social Networking Sites (SNSs) through an empirical model providing both theoretical understandings and practical implications. The proposed framework explicates the consumer’s use of SNSs as a tool for information sharing and its effect on brand image and online purchase intentions. The consumer survey was done through a structured questionnaire developed in accordance with the literature. Data was collected from 256 respondents, using both offline and online modes from 4 different cities of India. Structural Equation Modeling was employed to estimate the proposed model and determine the antecedents of consumer eWOM credibility and in turn its effect on brand image leading to consumer purchase intentions. The results show SNS activities play a significant role in creating eWOM credibility, which leads to shaping the brand image and purchase intentions. The findings would help companies to create a positive brand image to enhance their purchase intentions through eWOM aroused via SNSs.
Selecting online the most suitable product or service can be a draining process, and the broad diversity of products on retailers' websites is overwhelming. Following this, there has been a high interest in examining buyers' motivations and recognizing the determinant factors that affect the decision-making process in the case of online shopping. Hence, in this article, we carried out an empirical study and we analyzed to what extent certain factors such as product features, confidence in the online shop, product reviews, product price, consumer evaluations, the trust of the sources, usability of the online shop, convictions and commitment to the brand, product notoriety, consumer loyalty programs, WOM, and eWOM influence the purchasing decision. The findings reveal that the most significant variables determining the acquisition decision are product features, confidence in the online shop, reviews of the product, product price, and evaluations of customers from trusted sources. The most relevant information resources are trustworthy websites that offer specialized product reviews and reliable websites that offer customer product reviews. JEL classification: L81, M31
The electronic word-of-mouth (eWOM) literature supports the robust finding that negative reviews are generally more influential to consumer behavior than positive ones. Moreover, recent studies suggest that much of the negativity bias is driven by the distinct emotions embedded in the content of negative word-of-mouth (NWOM) and the interaction effects between emotions and other source factors. Although the gender of the information source is a common heuristic used in message evaluation, this is the first study to examine the effect of gender stereotypes on emotional NWOM. Two web-based experiments show that when reviewer reputation cues are present, emotional content in NWOM lowers the credibility of male reviewers and the helpfulness of their reviews, but does not affect female-authored reviews. In contrast, when reputation cues are absent, the presence of emotions in NWOM lowers the credibility of female reviewers, but not that of male reviewers. The reputation cue has a positive effect on NWOM credibility and helpfulness. Findings help companies understand the impact of gender stereotypes in online NWOM and detect the most helpful NWOM in order to correct product issues and improve future eWOM.
Purpose
This paper provides a comprehensive, yet concise, overview of the considerations and metrics required for PLS-SEM analysis and result reporting. Preliminary considerations are summarized first, including reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, use of secondary data, statistical power, and the need for goodness-of-fit testing. Next, the metrics, as well as the rules of thumb, that should be applied to assess the PLS-SEM results are covered. Besides covering established PLS-SEM evaluation criteria, the overview includes new guidelines for applying (1) PLSpredict, a novel approach for assessing a model’s out-of-sample prediction, (2) metrics for model comparisons, and (3) several complementary methods for checking the results’ robustness.
Design/methodology/approach
This paper provides an overview of previously and recently proposed metrics, as well as rules of thumb, for evaluating the results of research, based on the application of PLS-SEM.
Findings
Most of the previously applied metrics for evaluating PLS-SEM results are still relevant, but scholars need to be knowledgeable about recently proposed metrics (e.g., model comparison criteria) and methods (e.g., endogeneity assessment, latent class analyses, PLSpredict) and when and how to apply them.
Research limitations/implications
Methodological developments associated with PLS-SEM are rapidly emerging. The metrics reported in this paper are useful for current applications, but scholars need to continuously seek the latest developments in the PLS-SEM method.
Originality/value
In light of more recent research and methodological developments in the PLS-SEM domain, guidelines for the method’s use need to be continuously extended and updated. This paper is the most current and comprehensive summary of the PLS-SEM method and the metrics applied to assess its solutions.
We study the effect of the volume of consumer reviews on the purchase likelihood (conversion rate) of users browsing a product page. We propose using the exponential learning curve model to study how conversion rates change with the number of reviews. We call the difference in conversion rate between having no reviews and an infinite number \textit{the value of reviews}. We find that, on average, the conversion rate of a product can increase by 142% as it accumulates reviews. To address the problem of simultaneity of increase of reviews and conversion rate, we explore the natural temporal trends throughout a product's lifecycle. We perform further controls by using user sessions where the reviews were not displayed. We also find diminishing marginal value as a product accumulates reviews, with the first five reviews driving the bulk of the aforementioned increase.
Within categories, we find that the value of reviews is highest for Electronics (increase of 317%) followed by Home Living (increase of 182%) and Apparel (increase of 138%). We infer that the existence of reviews provides valuable signals to the customers, increasing their propensity to purchase. We also infer that users usually don't pay attention to the entire set of reviews, especially if there are a lot of them, but instead they focus on the first few available. Our approach can be extended and applied in a variety of settings to gain further insights.
In an online environment, consumers never touch the product and depend on electronic word-of-mouth (eWOM) to help them making purchase decision. The eWOM becomes one of the most influential channels of communication in the marketplace. This study aims to determine the importance of perceived credibility in an online consumer’s decision-making process. In this empirical study, we verify that a consumer’s perceived eWOM credibility positively influences his or her adoption of eWOM. We also found that source credibility, eWOM quantity, and eWOM quality significantly affect a consumer’s perceived eWOM credibility.
Despite hospitality and tourism researchers’ recent attempts on examining different aspects of online word-of-mouth [WOM], its impact on hotel sales remains largely unknown in the existing literature. To fill this void, we conduct a study to empirically investigate the impact of online consumer-generated reviews on hotel room sales. Utilizing data collected from the largest travel website in China, we develop a fixed effect log-linear regression model to assess the influence of online reviews on the number of hotel room bookings. Our results indicate a significant relationship between online consumer reviews and business performance of hotels.
Structural equation modeling (SEM) has become a quasi-standard in marketing and management research when it comes to analyzing the cause-effect relations between latent constructs. For most researchers, SEM is equivalent to carrying out covariance-based SEM (CB-SEM). While marketing researchers have a basic understanding of CB-SEM, most of them are only barely familiar with the other useful approach to SEM-partial least squares SEM (PLS-SEM). The current paper reviews PLS-SEM and its algorithm, and provides an overview of when it can be most appropriately applied, indicating its potential and limitations for future research. The authors conclude that PLS-SEM path modeling, if appropriately applied, is indeed a "silver bullet" for estimating causal models in many theoretical models and empirical data situations.
The use of the WWW as a venue for voicing opinions, complaints and recommendations on products and firms has been widely reported in the popular media. However little is known how consumers use these reviews and if they subsequently have any influence on evaluations and purchase intentions of products and retailers. This study examines the effect of negative reviews on retailer evaluation and patronage intention given that the consumer has already made a product/brand decision. Our results indicate that the extent of WOM search depends on the consumer's reasons for choosing an online retailer. Further the influence of negative WOM information on perceived reliability and purchase intentions is determined largely by familiarity with the retailer and differs based on whether the retailer is a pure-Internet or clicks-and-mortar firm. Managerial implications for positioning strategies to minimize the effect of negative word-of-mouth have been discussed.
Online consumer product reviews, a form of electronic word-of-mouth (eWOM), have attracted increased attention from researchers. This paper examines the persuasiveness of eWOM. Drawing on regulatory focus theory, the authors propose that the consumption goals that consumers associate with the reviewed product moderate the effect of review valence on persuasiveness. Data from lab experiments and actual online retailers suggest that consumers who evaluate products associated with promotion consumption goals perceive positive reviews to be more persuasive than negative ones (i.e., a positivity bias). Conversely, consumers who evaluate products associated with prevention consumption goals perceive negative reviews to be more persuasive than positive ones (i.e., a negativity bias).
This paper focuses on the cultural effect of gender on the relationship of online word of mouth and trust in e-commerce. To encourage online commerce, many online retailers use online word-of-mouth systems, where consumers can rate products offered for sale. To date, how such ratings affect trust and adoption of e-commerce across genders has been relatively unexplored. We assess whether the effect of online trust on intention to shop online is moderated by gender. Our results show that the effect of trust on intention to shop online is stronger for women than for men. In addition, we find that men value their ability to post content online, whereas women value the responsive participation of other consumers to the content they have posted. Finally, we find that online word-of-mouth quality affects online trust differently across genders.
Addresses one of the fundamental issues of e-marketing: how to attract and win over the consumer in the highly competitive Internet marketplace. Analyses the factors affecting the online consumer's behavior and examines how e-marketers can influence the outcome of the virtual interaction and buying process by focusing their marketing efforts on elements shaping the customer's virtual experience, the Web experience. Identifying the Web experience components and understanding their role as inputs in the online customer's decision-making process are the first step in developing and delivering an attractive online presence likely to have the maximum impact on Internet users. Click-and-mortar firms delivering superior Web experience influence their physical clients’ perceptions and attitudes, driving additional traffic to traditional sales outlets. Provides a contribution to the theoretical debate around the factors influencing the online consumer's behavior and outlines some noticeable similarities and differences between the traditional and virtual consumers.
The recent failure of a large number of e-tail companies epitomizes the challenges of operating through virtual channels and underscores the need to better understand key drivers of online consumer behavior. The objective of this study is to provide a comprehensive review of the extant information systems (IS) literature related to online consumer behavior and integrate the literature in order to enhance our knowledge of consumer behavior in electronic markets and provide clear directions for future research. This paper introduces a framework that integrates research findings across studies to develop a coherent and comprehensive picture of the online consumer behavior research conducted in the IS field. The integrative framework proposes system quality, information quality, service quality, and vendor and channel characteristics as key factors that impact online consumer behavior, achieving their effects by altering the perceptions of usefulness, ease of use, trust, and shopping enjoyment.
With increased online activities associated with the purchase of restaurant services, online reviews have become important among potential customers due to the advantages in communicating past consumers’ candid experiences and feelings. The purpose of this study is to examine the relationship between online reviews and purchase intention, while simultaneously investigating the effects of trust and food image. A 2(rating: high vs. low) x 2(price: high vs. low) x 2(picture: with vs. without) factorial experimental design was used to attain this objective. Results show that there are significant differences in purchase intentions depending on the level of ratings and price. Trust was influenced by picture, where reviews containing a picture are found to be more effective. In particular, online reviews with high ratings and pictures culminated in the highest trust perceptions. Accordingly, this study confirmed the moderated mediating effects of trust on purchase intention.
Purpose
The relationship between online reviews and purchase intention has been studied in previous research. However, there was little knowledge about the effect of information quality and the social presence of online reviews on purchase intention based on the stimulus-organism-response ( S - O - R ) framework. The purpose of this study is to explore the intrinsic relationship between the stimulus (perceived information quality and social presence) generated from online reviews and the response (purchase intention).
Design/methodology/approach
This study developed a research model by applying the S - O - R framework to test the proposed hypotheses. A combination of a web-based experiment and an online survey was employed to collect data. Hypotheses were empirically tested using Smart PLS.
Findings
The PLS analysis shows that both perceived information quality and the social presence of online reviews positively affect trust. Moreover, satisfaction with online reviews affects purchase intention, whereas trust has a positive impact on satisfaction, playing a mediating role between two stimuli and satisfaction. Besides, perceived information quality of positive online reviews is found to have a more significant impact on trust, satisfaction and purchase intention.
Originality/value
The results of this study are of great value for expanding both theoretical research and practical applications of online reviews in relation to purchase intention. This study with a new research model reveals the understanding of how the purchase intention will be motivated by online reviews. Meanwhile, the moderating effects and the mediating effects are also discussed.
The purpose of this study is to investigate online purchase intention in emerging markets focusing on the impact of perceived usefulness of online reviews, trust and perceived risk. The results were obtained by an online survey answered by 380 online shoppers in Mexico City. Results from partial least squares structural equation modeling (PLS-SEM) using SmartPLS indicate that perceived usefulness of online reviews influences in trust and online purchase intention. Trust has an inverse relationship with perceived risk and influences positively in online purchase intention. The authors did not find perceived risk to influence directly in online purchase intention. The results suggest that companies should seek to enhance customers to share their positive online opinions in order to improve trust and encourage online purchases. This paper contributes to a more comprehensive understanding of the influence on online purchase intention in emerging markets.
Abundant research has investigated the impact of review valence on purchase decisions, but has reported mixed findings. To reconcile these mixed findings, this study unearths the understanding of review valence from the perspective of the emotional content in online customer reviews. To explore the effect of emotional content on purchase decisions and the moderating role of emotional content on non-emotional content and purchase decisions based on a heuristic-systematic model, a laboratory experiment with 106 subjects was used to empirically test the research hypotheses. The results show that pleasant online customer reviews lead to a higher purchase likelihood compared to unpleasant ones. Perceived credibility and perceived diagnosticity have significant influence on purchase decisions, but only in the context of unpleasant online customer reviews. The findings demonstrate positive emotion bias for online customer reviews, and carry important practical implications for both sellers and customers.
Consumers frequently rely on online reviews in forming purchase intentions, but at the same time have increas-ingly expressed reservations with regard to the credibility of online reviews in recent years. Given the lack of empirical research investigating how consumers assess the credibility of online reviews, this study examines determinants of online review credibility and its effect on consumers' purchase intentions. Drawing upon elaboration likelihood the-ory, we develop a research model and empirically test it by means of structural equation modeling with data collected from 282 users of the online review website Yelp. Our findings suggest that factors based on argument quality, in-cluding accuracy, completeness and quantity of online reviews, as well as peripheral cues, including reviewer exper-tise, product/service rating and website reputation, both significantly impact online review credibility, which in turn positively influences consumers' purchase intentions.
The value and credibility of online consumer reviews are compromised by significantly increasing yet difficult-to-identify fake reviews. Extant models for automated online fake review detection rely heavily on verbal behaviors of reviewers while largely ignoring their nonverbal behaviors. This research identifies a variety of nonverbal behavioral features of online reviewers and examines their relative importance for the detection of fake reviews in comparison to that of verbal behavioral features. The results of an empirical evaluation using real-world online reviews reveal that incorporating nonverbal features of reviewers can significantly improve the performance of online fake review detection models. Moreover, compared with verbal features, nonverbal features of reviewers are shown to be more important for fake review detection. Furthermore, model pruning based on a sensitivity analysis improves the parsimony of the developed fake review detection model without sacrificing its performance.
The proliferation of fake and paid online reviews means that building and maintaining consumer trust is a challenging task for websites hosting consumer-generated content. This study tests a model of antecedents and consequences of trust for consumer-generated media (CGM). Five factors are proposed for building consumer trust towards CGM: source credibility, information quality, website quality, customer satisfaction, user experience with CGM. Trust is expected to predict recommendation adoption and word of mouth. Data from 366 users of CGM were analyzed through structural equation modeling and the findings show that all the aforementioned factors with the exception of source credibility and user experience influence consumer trust towards CGM. Trust towards a CGM website influences travel consumers' intentions to follow other users' recommendations and fosters positive word of mouth. Findings also show that information quality predicts source credibility, customer satisfaction, and website quality.
Social networking sites (SNSs) are one of the Web 2.0's most utilized services, and the influential force of electronic word of mouth (eWOM) on SNSs deserves our unequivocal attention. This study aims to explore how users of SNSs adopt information embedded in eWOM reviews shared by other users. Using the stimulus-organism-response model and affect-as-information theory, we devised and tested a theoretical framework linking both a cognitive path and an affective path to approach eWOM adoption on SNSs. Two curiosity constructs—informational deprivation epistemic curiosity (D-EC) and interest-type epistemic curiosity (I-EC)—are regarded as moderators of the cognitive path and the affective path, respectively. Data collected from 445 respondents support all of our hypotheses. The results show that beyond the conventional cognitive path (cognitive stimuli and the credibility of eWOM), the affective path (affective stimuli and arousal) can also contribute to eWOM adoption. We also find that SNS users focus on different stimuli of SNSs, depending on their levels of D-EC and I-EC. Our findings provide new perspectives to SNS designers and users on how to manage eWOM reviews on SNSs.
The emergence of social media has demonstrated the empowerment of end-users with a transfer of power from sellers to buyers. Consumers have become able to generate content and share this in their networks with peers. Digital content generated by individuals has an economic value. Economic implications in the form of product sales through social interaction of individuals must now be taken into account by businesses. This has seen the emergence of social commerce, an important evolution in e-commerce. This paper draws on social support theory, social commerce constructs and information systems concepts, and proposes a conceptual model. This proposed model investigates the role of social media in facilitating online communication between consumers through social commerce constructs, leading to online social support. A survey has been conducted to examine the structural model. Data analysis using SEM-PLS reveals important factors indicating the role of social media in facilitating online communication through social commerce constructs, generating online social support and affecting consumers' behaviour, the value of social commerce for the market. Theoretical implications and practical implications of this study are explained in the end of the paper.
A large number of online customer reviews greatly influences consumer purchasing decisions. Whether positive or negative, consumers regard online customer reviews as providing useful information. Based on the elaboration likelihood model (ELM), this study focuses on the factors of the central and peripheral route in online customer reviews that make readers feel they are trustworthy and helpful. In addition, the researchers are interested in the impact of social factors in the reviews on consumers. Using content analysis, the study analyzes 983 customer reviews from restaurant review websites. Results show that the larger reviewer's number of followers, the higher level of expertise of the reviewer, the larger image count and word count also make readers feel the review is more practical and useful. Further, the influence of the peripheral route, the social factors, on readers is higher than that of central route factors.
With the rapid growth of the Internet, the ability of users to create and publish content has created active electronic communities that provide a wealth of product information. However, the high volume of reviews that are typically published for a single product makes harder for individuals as well as manufacturers to locate the best reviews and understand the true underlying quality of a product. In this paper, we reexamine the impact of reviews on economic outcomes like product sales and see how different factors affect social outcomes such as their perceived usefulness. Our approach explores multiple aspects of review text, such as subjectivity levels, various measures of readability and extent of spelling errors to identify important text-based features. In addition, we also examine multiple reviewer-level features such as average usefulness of past reviews and the self-disclosed identity measures of reviewers that are displayed next to a review. Our econometric analysis reveals that the extent of subjectivity, informativeness, readability, and linguistic correctness in reviews matters in influencing sales and perceived usefulness. Reviews that have a mixture of objective, and highly subjective sentences are negatively associated with product sales, compared to reviews that tend to include only subjective or only objective information. However, such reviews are rated more informative (or helpful) by other users. By using Random Forest-based classifiers, we show that we can accurately predict the impact of reviews on sales and their perceived usefulness. We examine the relative importance of the three broad feature categories: “reviewer-related” features, “review subjectivity” features, and “review readability” features, and find that using any of the three feature sets results in a statistically equivalent performance as in the case of using all available features. This paper is the first study that integrates eco- - nometric, text mining, and predictive modeling techniques toward a more complete analysis of the information captured by user-generated online reviews in order to estimate their helpfulness and economic impact.
Introduction
While product review systems that collect and disseminate opinions about products from recent buyers (Table 1) are valuable forms of word-of-mouth communication, evidence suggests that they are overwhelmingly positive. Kadet notes that most products receive almost five stars. Chevalier and Mayzlin also show that book reviews on Amazon and Barnes & Noble are overwhelmingly positive. Is this because all products are simply outstanding? However, a graphical representation of product reviews reveals a J-shaped distribution (Figure 1) with mostly 5-star ratings, some 1-star ratings, and hardly any ratings in between. What explains this J-shaped distribution? If products are indeed outstanding, why do we also see many 1-star ratings? Why aren't there any product ratings in between? Is it because there are no "average" products? Or, is it because there are biases in product review systems? If so, how can we overcome them?
The J-shaped distribution also creates some fundamental statistical problems. Conventional wisdom assumes that the average of the product ratings is a sufficient proxy of product quality and product sales. Many studies used the average of product ratings to predict sales. However, these studies showed inconsistent results: some found product reviews to influence product sales, while others did not. The average is statistically meaningful only when it is based on a unimodal distribution, or when it is based on a symmetric bimodal distribution. However, since product review systems have an asymmetric bimodal (J-shaped) distribution, the average is a poor proxy of product quality.
This report aims to first demonstrate the existence of a J-shaped distribution, second to identify the sources of bias that cause the J-shaped distribution, third to propose ways to overcome these biases, and finally to show that overcoming these biases helps product review systems better predict future product sales.
We tested the distribution of product ratings for three product categories (books, DVDs, videos) with data from Amazon collected between February--July 2005: 78%, 73%, and 72% of the product ratings for books, DVDs, and videos are greater or equal to four stars (Figure 1), confirming our proposition that product reviews are overwhelmingly positive.
Figure 1 (left graph) shows a J-shaped distribution of all products. This contradicts the law of "large numbers" that would imply a normal distribution. Figure 1 (middle graph) shows the distribution of three randomly-selected products in each category with over 2,000 reviews. The results show that these reviews still have a J-shaped distribution, implying that the J-shaped distribution is not due to a "small number" problem. Figure 1 (right graph) shows that even products with a median average review (around 3-stars) follow the same pattern.
Deals with three issues in the area of perceived service quality. First, it compares the gap model with the performance model. Second, it investigates the direction of causality between service quality and satisfaction. Finally, it examines whether the influences of some dimensions of service quality vary across service industry types. Three service firms were selected and respondents were interviewed in each firm. As hypothesized, the performance model appeared to be superior to the gap model. In addition, the result shows that perceived service quality is an antecedent of satisfaction, rather than vice versa. Finally, tangibles appeared to be a more important factor in the facility/equipment-based industries, whereas responsiveness is a more important factor in the people-based industries. Managerial implications and future research directions are discussed.
This paper 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 paper 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.
Online reputation mechanisms harness the bi-directional communication capabilities of the Internet in order to engineer large-scale word-of-mouth networks. They are emerging as a promising alternative to more established assurance mechanisms, such as branding and formal contracting, in a variety of settings ranging from online marketplaces to Internet search engines. At the same time, they are transforming a concept that had traditionally fallen within the realm of the social sciences into an engineering design problem. This paper surveys our progress in understanding the new possibilities and challenges that these mechanisms represent. It discusses some important dimensions in which Internet-based reputation mechanisms differ from traditional word-of-mouth networks and surveys the most important issues related to designing, evaluating and using them. It provides an overview of relevant work in game theory and economics on the topic or reputation. It further discusses how this body of work is being extended and combined with insights from computer science, information systems, management science and psychology in order to take into consideration the special properties of online mechanisms such as their unprecedented scalability, the ability to precisely design the type of feedback information they solicit and distribute, and challenges associated with the volatility of identities and the absence of many familiar contextual cues in online environments.
Word-of-mouth (WOM) study is extended to the on-line context (eWOM) by examining the informational and normative determinants of the perceived credibility of on-line consumer recommendations. A survey of users of an on-line consumer discussion forum in China substantiated the effects of the determinants, although post-hoc analyses revealed that prior knowledge and involvement level moderate some of them. Implications for research and practice are discussed.
Electronic word-of-mouth (eWOM) communication has been one of the most exciting research areas of inquiry. There is an emerging attention on the effectiveness of eWOM communication. The scope of published studies on the impact of eWOM communication is rather broad and the studies appear relatively fragmented and inconclusive. In this study, we focused on the individual-level eWOM research. We conducted a systematic review of eWOM research and identified key factors that are specific to the context of eWOM communication. We believe that this literature analysis not only provides us with an overview of the current status of knowledge within the domain of eWOM communication, but also serves as a salient guideline for future research directions.
Online user-generated product reviews have become an indispensible tool for consumers and thus for retailers who want to attract and retain consumers. Yet, relatively little is known about what causes consumers to find an online peer review helpful to their shopping tasks. Prior research examines mostly the effects of product reviews on consumer product attitude, product choice, and product sales. This paper, however, provides an analysis of the determinants of review helpfulness. In two studies, we examine the effects of review characteristics, product type, and reviewer characteristics on perceived review helpfulness. With data collected from a real online retailer, we provide empirical evidence to support our conceptual predictions. Specifically, both review valence and length have positive effects on review helpfulness, but the product type (i.e., experiential vs. utilitarian product) moderates these effects. Using content analysis of reviews, we develop a measure of expressed reviewer innovativeness (i.e., the predisposition toward new products as revealed in review content). A curvilinear relationship exists between expressed reviewer innovativeness and review helpfulness. These findings lead to pertinent managerial implications.
textlessptextgreaterThe authors investigate the conceptualization and measurement of service quality and the relationships between service quality, consumer satisfaction, and purchase intentions. A literature review suggests that the current operationalization of service quality confounds satisfaction and attitude. Hence, the authors test (1) an alternative method of operationalizing perceived service quality and (2) the significance of the relationships between service quality, consumer satisfaction, and purchase intentions. The results suggest that (1) a performance-based measure of service quality may be an improved means of measuring the service quality construct, (2) service quality is an antecedent of consumer satisfaction, (3) consumer satisfaction has a significant effect on purchase intentions, and (4) service quality has less effect on purchase intentions than does consumer satisfaction. Implications for managers and future research are discussed.
The research described in this study replicates and extends the Cronin and Taylor [Cronin JJ, Taylor SA. Measuring service quality: a reexamination and extension. J Mark 1992:55–68 (August).] study suggestion that service quality be measured using a performance-only index (SERVPERF) as opposed to the gap-based SERVQUAL scale. The intent of the research was to examine the ability of the performance-only measurement approach to capture the variance in consumers' overall perceptions of service quality across three studies. For the first study, the original Cronin and Taylor data were obtained and a replication of their study was undertaken using a recursive form of their non-recursive model in an effort to avoid the abnormal parameter estimates they reported. The replication successfully duplicated their finding as to the superiority of the performance-only measurement of service quality. The second and third studies included new data in which different measures of the constructs examined in Cronin and Taylor were employed in order to enhance the validity of the findings. The results from these two studies lent strong support again for the superiority of the performance-only approach to the measurement of service quality. In addition, both the replication and the two new studies were used to extend Cronin and Taylor's investigation of the service quality–consumer satisfaction relationship. The results of all three studies indicate that service quality is properly modeled as an antecedent of satisfaction.
The definition and measurement of service quality as a 5-dimensional construct, as in SERVQUAL, appears to suffer from a number of methodological shortcomings. A review of the potential problems and the findings from an empirical study are presented in this article. The findings suggest that the dimensionality of service quality may depend on the type of services under study. The use of mixed-item wording and the current operationalization of service quality on the basis of gap scores appear in the process of using SERVQUAL, the results of this study suggest to exercise caution. Suggestions are provided with implications for theory development and measurement in the service marketing area.
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.
The creation of online consumer communities to provide product reviews and advice has been touted as an important, albeit somewhat expensive component of Internet retail strategies. In this paper, we characterize reviewer behavior at two popular Internet sites and examine the effect of consumer reviews on firms' sales. We use publicly available data from the two leading online booksellers, Amazon.com and BarnesandNoble.com, to construct measures of each firm's sales of individual books. We also gather extensive consumer review data at the two sites. First, we characterize the reviewer behavior on the two sites such as the distribution of the number of ratings and the valence and length of ratings, as well as ratings across different subject categories. Second, we measure the effect of individual reviews on the relative shares of books across the two sites. We argue that our methodology of comparing the sales and reviews of a given book across Internet retailers allows us to improve on the existing literature by better capturing a causal relationship between word of mouth (reviews) and sales since we are able to difference out factors that affect the sales and word of mouth of both retailers, such as the book's quality. We examine the incremental sales effects of having reviews for a particular book versus not having reviews and also the differential sales effects of positive and negative reviews. Our large database of books also allows us to control for other important confounding factors such as differences across the sites in prices and shipping times.
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