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What leads to online review helpfulness on e-commerce platform? Examining the moderating effect of high and low prices
Abstract
Using signaling theory, this study unpacked the mechanisms through which online review information quality and reviewer information credibility influence online review helpfulness, in e-commerce context. Conducting a survey with users in Danang having read online reviews on Shopee.vn, 244 valid responses were used to evaluate the research model via PLS-SEM software. The study found that the information quality of online reviews strongly influences the helpfulness of online reviews compared to the information credibility of previous reviewers. Additionally, priced goods have a moderating effect on the relationship between online information credibility and online reviews helpfulness; and that relationship will be significant in high-priced products. This study makes a theoretical contribution to online reviews by elucidating the mechanisms of impact of review/reviewer information on reviews helpfulness and the moderating effect of product prices.
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The purpose of this study was to test the determinants affecting the credibility of online reviews. In this model, the relationships between argument quality and peripheral cue and credibility of online reviews were evaluated. The measurement model and the conceptual model depicting hypothesized relationships were evaluated based on responses from 460 customers using multiple linear regression analysis, accordingly. After the data collection process was completed, all data were put into SPSS 20. The process of checking and analyzing the data sequentially follows: reliability test, EFA factor analysis, Correlation analysis and Multiple linear regression analysis. Initially, the scale was assessed by Cronbach's Alpha and EFA. Then, the correlation coefficient test was used to check the linear relationship between the independent and dependent variables. The results from the study indicated the accuracy, completeness, review quantity, review consistency, product/ service rating, and website reputation were accepted and all of them had positive effects on review credibility. This shows, shoppers are very interested in completeness, the full information as well as necessary evidence to help shoppers assess the truthfulness and accuracy of the information more easily. At the same time, the website reputation also helps increase the credibility of the reviews and buyers tend to believe in online reviews if the website has a good reputation. Basically, the research completed its original purpose of identifying factors that affect the credibility of online reviews.
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.
This study empirically tests and compares the influence of friends’ recommendations on social media and anonymous reviews on shopping websites in the context of online purchase intention. For this purpose, we analyse the impacts of these two platforms based on the components of information adoption model (IAM) which are borrowed as information quality, information credibility, information usefulness and information adoption. We conduct a survey and find anonymous reviews as more influential on consumer’ online purchase intentions than friends’ recommendations on social media. However, as this result was contrary to that expected, we conduct another study through in-depth interviews in order to enlighten our results found in the first study. In Study 2, we find the reasons why consumers prefer anonymous reviews rather than friends’ recommendations. Information quantity, information readiness, detailed information and dedicated information are factors which make shopping websites superior than social media in terms of the impact of electronic word of mouth (eWOM). Academic and managerial implications are discussed.
This paper sheds light on ways travellers' rating patterns in the hotel review website TripAdvisor differ between independent and chain hotels. To delve deeper, travellers were classified according to their profiles, namely, business, couple, family, friend and solo. Besides, hotels straddled across four geographical regions, namely, America, Asia Pacific, Europe as well as Middle East and Africa. A 5 (profiles) × 4 (regions) two-way factorial analysis of variance was conducted separately for independent and chain hotels. A qualitative analysis was further conducted to tease out the findings from the quantitative analyses. Travellers' rating patterns were found to differ substantially between independent and chain hotels across both profiles as well as regions. The paper concludes by highlighting its implications, limitations and potential directions for future research.
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.
Intangibility of products in online environment results in higher information
asymmetry. To overcome this asymmetric information issue, consumers may
rely upon online reviews, i.e. word of mouse as a signal of quality. Two
models were chosen to measure the impact of word of mouse characteristics
on consumer’s decision for this study. An objective data (proxy measures) as
well as subjective data (questionnaire measures) was collected for the
reviews available at Epinions.com. Results revealed that reviewer’s
reputation, expertise and message comprehensiveness are the most
influential characteristics of word of mouse information. Identity disclosure,
message timeliness and message accuracy were not significant predictors of
information usefulness.
Purpose: We present partial least squares (PLS) as an evolving approach to structural equation modeling (SEM), highlight its advantages and limitations and provide an overview of recent research on the method across various fields.
Design/methodology/approach: In this review article we merge literatures from the marketing, management, and management information systems fields to present the state-of-the art of PLS-SEM research. Furthermore, we meta-analyze recent review studies to shed light on popular reasons for PLS-SEM usage.
Findings: PLS-SEM has experienced increasing dissemination in a variety of fields in recent years with non-normal data, small sample sizes and the use of formative indicators being the most prominent reasons for its application. Recent methodological research has extended PLS-SEM’s methodological toolbox to accommodate more complex model structures or handle data inadequacies such as heterogeneity.
Research limitations/implications: While research on the PLS-SEM method has gained momentum during the last decade, there are ample research opportunities on subjects such as mediation or multigroup analysis, which warrant further attention.
Originality/value: This article provides an introduction to PLS-SEM for researchers that have not yet been exposed to the method. The article is the first to meta-analyze reasons for PLS-SEM usage across the marketing, management, and management information systems fields. Our cross-disciplinary review of recent research on the PLS-SEM method also makes this article useful for researchers interested in advanced concepts.
Online reviews have received much attention recently in the literature, as their visibility has been proven to play an important role during the purchase process. Furthermore, recent theoretical insight argue that the votes casted on how helpful an online review is (review helpfulness) are of particular importance, since they constitute a focal point for examining consumer decision making during the purchase process. In this paper, we explore the interplay between online review helpfulness, rating score and the qualitative characteristics of the review text as measured by readability tests. We construct a theoretical model based on three elements: conformity, understandability and expressiveness and we investigate the directional relationship between the qualitative characteristics of the review text, review helpfulness and the impact of review helpfulness on the review score. Furthermore, we examine whether this relation holds for extreme and moderate review scores. To validate this model we applied four basic readability measures to a dataset containing 37,221 reviews collected from Amazon UK, in order to determine the relationship between the percentage of helpful votes awarded to a review and the review text’s stylistic elements. We also investigated the interrelationships between extremely helpful and unhelpful reviews, as well as absolutely positive and negative reviews using intergroup comparisons. We found that review readability had a greater effect on the helpfulness ratio of a review than its length; in addition, extremely helpful reviews received a higher score than those considered less helpful. The present study contributes to the ever growing literature on on-line reviews by showing that readability tests demonstrate a directional relationship with average length reviews and their helpfulness and that this relationship holds both for moderate and extreme review scores.
On-line consumer reviews, functioning both as informants and as recommenders, are important in making purchase decisions and for product sales. Their persuasive impact depends on both their quality and their quantity. This paper uses the elaboration likelihood model to explain how level of involvement with a product moderates these relationships. The study produces three major findings: (1) the quality of on-line reviews has a positive effect on consumers' purchasing intention, (2) purchasing intention increases as the number of reviews increases, and (3) low-involvement consumers are affected by the quantity rather than the quality of reviews, but high-involvement consumers are affected by review quantity mainly when the review quality is high. These findings have implications for on-line sellers in terms of how to manage on-line consumer reviews.
Hypothesized that when a persuasive communication was on a topic of (a) high personal relevance, attitude change was governed by issue-relevant arguments, and (b) low personal relevance, peripheral features were more important. 145 undergraduates expressed their attitudes on the issue of comprehensive senior exams after exposure to a counterattitudinal advocacy that was of high or low personal relevance containing either strong or weak arguments that emanated from a source of either high or low expertise. Another 18 Ss were controls who were surveyed but not exposed to a counterattitudinal advocacy. Interactions of the personal relevance manipulation with the argument quality and expertise manipulations revealed that under high relevance (the exams were to be instituted the following year), attitudes were influenced primarily by the quality of the arguments in the message, whereas under low relevance (the exams were to be instituted in 10 years), attitudes were influenced primarily by the expertise of the source. It is suggested that an increase in involvement is associated with an increase in the importance of message arguments because people are motivated to hold "correct" and defensible opinions, and they have a better framework for things that are relevant to the self. (45 ref)
Customer reviews are increasingly available online for a wide range of products and services. They supplement other information provided by electronic storefronts such as product descriptions, reviews from experts, and personalized advice generated by automated recommendation systems. While researchers have demonstrated the benefits of the presence of customer reviews to an online retailer, a largely uninvestigated issue is what makes customer reviews helpful to a consumer in the process of making a purchase decision. Drawing on the paradigm of search and experience goods from information economics, we develop and test a model of customer review helpfulness. An analysis of 1,587 reviews from Amazon.com across six products indicated that review extremity, review depth, and product type affect the perceived helpfulness of the review. Product type moderates the effect of review extremity on the helpfulness of the review. For experience goods, reviews with extreme ratings are less helpful than reviews with moderate ratings. For both product types, review depth has a positive effect on the helpfulness of the review, but the product type moderates the effect of review depth on the helpfulness of the review. Review depth has a greater positive effect on the helpfulness of the review for search goods than for experience goods. We discuss the implications of our findings for both theory and practice.
The fusion of live streaming and e-commerce is booming. However, it remains unclear how live streaming affects consumers’ purchase intention (PI) in online markets of clothes and cosmetics. On the basis of signaling theory and uncertainty literature, we propose broadcasters’ physical characteristics conveyed through vicarious product trials and values shared via instant interaction as two signals that can help reduce product uncertainty and cultivate trust for the consumers with similar physical traits and values. The analysis of survey and interview data largely supports the hypotheses. This research contributes to the literature of live streaming commerce, uncertainty literature, and signaling theory.
Product promotions and liberal return policies are two effective signals that can increase customers' repurchase behavior when online shopping, and how these signals work at different stages of market growth for various customer groups is an important topic for research and applications. Thus, to help online merchants make more effective decisions regarding the use of such signals, this paper proposes a multi-stage hidden Markov model (MS-HMM) to explore the motivational process behind customer repurchase behavior through the lens of the Signaling Theory. The customer-merchant relationship (CMR) is represented as the latent state in the hidden Markov model and is coupled with stage-heterogeneity in terms of state transition probabilities and state-dependent choice probabilities. Moreover, extensive experiments with real-world data are conducted to validate the effectiveness of the MS-HMM.
While there is some evidence that review length, review score, and argument frame can impact consumers’ perceptions regarding the helpfulness of online consumer reviews, studies have not yet identified the most appropriate levels of such factors in terms of maximizing perceived helpfulness of these reviews. Drawing on Negativity Bias and Cue-Summation theories, we propose a theoretical model that explains online reviews’ helpfulness based on specific characteristics of these reviews (i.e., length, score, argument frame). The model is empirically validated using two datasets of online consumer reviews related to products and services from Amazon.com and Insureye.com respectively. We also employ ANOVA analyses to reveal the levels of each of these characteristics that result in maximizing perceived helpfulness of online consumer reviews. Further, we employ an artificial neural network approach to predict the helpfulness of a given review based on its characteristics. Our findings reveal that the most helpful online consumer reviews are those that are associated with medium length, lower review scores, and negative or neutral argument frame. Our results also reveal that there is no major difference between the characteristics of the most helpful online consumer reviews related to products or services. Finally, our findings reveal that the most helpful factor in predicting the helpfulness of an online consumer review is the review length. Theoretical and practical contributions are outlined.
This paper extracted discrete emotions from online reviews based on an emotion classification approach, and examined the differential effects of three discrete emotions (anger, fear, sadness) on perceived review helpfulness. We empirically tested the hypotheses by analyzing the “verified purchase” reviews on Amazon.com. The findings of this study extend the previous research by suggesting that product type moderates the effects of emotions on perceived review helpfulness. Anger embedded in a customer review exerts a greater negative impact on perceived review helpfulness for experience goods than for search goods. Fear embedded in a review is identified as an important emotional cue to positively affect the perceived review helpfulness with more persuasive messages. As the level of sadness embedded in a review increases, perceived review helpfulness decreases. These findings contribute to a better understanding of the important role of emotions embedded in reviews on the perceived review helpfulness. This study also provides practical insights related to the presentation of online reviews and gives suggestions for consumers regarding how to select and write a helpful review.
Using sales data from 30,008 books from Amazon.de, this article studies the effects of four distinct online communication practices that e-tailers increasingly use: presenting product networks (recommender systems), social features (electronic word of mouth and various types of user-generated content), free trials, and vivid content. These practices vary greatly in their effectiveness in influencing consumers’ purchase decisions. The author also provides insights into the sales frequencies of popular versus niche products, in response to the selective use of these communication practices. Long-tail theory argues that consumers are particularly attracted to buying niche products, because these products match their personal preferences better than mainstream products do. In contrast, superstar theory predicts increased sales frequencies for popular goods. However, the results from this large sample reveal that both popular and niche products gain sales. The findings specify how different communication practices relatively and differentially affect sales of popular and niche products, which has notable implications for managers’ selective uses of these tools.
In the online word-of-mouth literature, research has consistently shown that negative reviews have a greater impact on product sales than positive reviews. Although this negativity effect is well documented at theproduct level, there is less consensus on whether negative or positive reviews are perceived to be more helpful by consumers. A limited number of studies document a higher perceived helpfulness for negative reviews under certain conditions, but accumulating empirical evidence suggests the opposite. To reconcile these contradictory findings, we propose that consumers can form initial beliefs about a product on the basis of the product's summary rating statistics (such as the average and dispersion of the product's ratings) and that these initial beliefs play a vital role in their subsequent evaluation of individual reviews. Using a unique panel data set collected from Apple's App Store, we empirically demonstrate confirmation bias-that consumers have a tendency to perceive reviews that confirm (versus disconfirm) their initial beliefs as more helpful, and that this tendency is moderated by their confidence in their initial beliefs. Furthermore, we show that confirmation bias can lead to greaterperceived helpfulness for positive reviews (positivity effect) when the average product rating is high, and for negative reviews (negativity effect) when the average product rating is low. Thus, the mixed findings in the literature can be a consequence of confirmation bias. This paper is among the first to incorporate the important role of consumers' initial beliefs and confidence in such beliefs (a fundamental dimension of metacognition) into their evaluation of online reviews, and our findings have significant implications for researchers, retailers, and review websites.
Helpfulness of online reviews is a multi-faceted concept that can be driven by several types of factors. This study was designed to extend existing research on online review helpfulness by looking at not just the quantitative factors (such as word count), but also qualitative aspects of reviewers (including reviewer experience, reviewer impact, reviewer cumulative helpfulness). This integrated view uncovers some insights that were not available before. Our findings suggest that word count has a threshold in its effects on review helpfulness. Beyond this threshold, its effect diminishes significantly or becomes near non-existent. Reviewer experience and their impact were not statistically significant predictors of helpfulness, but past helpfulness records tended to predict future helpfulness ratings. Review framing was also a strong predictor of helpfulness. As a result, characteristics of reviewers and review messages have a varying degree of impact on review helpfulness. Theoretical and practical implications are discussed.
With the growth of e-commerce, online consumer reviews have increasingly become important sources of information that help consumers in their purchase decisions. However, the influx of online consumer reviews has caused information overload, making it difficult for consumers to choose reliable reviews. For an online retail market to succeed, it is important to lead product reviewers to write more helpful reviews, and for consumers to get helpful reviews more easily by figuring out the factors determining the helpfulness of online reviews. For this research, 75,226 online consumer reviews were collected from Amazon. com using a Web data crawler. Additional information on review content was also gathered by carrying out a sentiment analysis for mining review text. Our results show that both peripheral cues, including review rating and reviewer's credibility, and central cues, such as the content of reviews, influence the helpfulness of reviews. Based on dual process theories, we find that consumers focus on different information sources of reviews, depending on their purposes for reading reviews: online reviews can be used for information search or for evaluating alternatives. Our findings provide new perspectives to online market owners on how to manage online reviews on their Web sites.
A web-based experiment (N = 201) examined (a) how the quality of online product reviews affects the participants’ acceptance of the reviews as well as their evaluations of the sources and (b) how such effects vary depending on the product type and the availability of reviewers’ photos. For the product type, an experience good (computer game) whose quality is difficult to assess before firsthand experience and a search good (vitamin) whose quality can be easily evaluated by reading a product description were compared. After reading overall positive reviews, those exposed to the high-quality (vs. low-quality) reviews evaluated the product more positively, which in turn, led to a stronger purchase intention. However, review quality also had a negative direct effect on the purchase intention for the experience good, with no corresponding effect for the search good. High-quality reviews induced more positive evaluations of the reviewers (primary source), but they enhanced website evaluation (secondary source) only when the reviewers’ photos were present, suggesting that such visual cues may facilitate systematic message processing.
Previous researchers have explained how offline word of mouth (WOM) influences consumer behaviour. Increasingly, however, consumers are turning to online WOM, especially online forums. In an online context, the research discussed in this article replicates the approaches taken to studying offline WOM. Grounded in social comparison theory, social network analysis and the theory of reasoned action, a mall intercept survey of consumers in Hong Kong showed that both similarity between a user's interests and a forum's topic and user attitudes towards the forum strongly predict purchase intentions as well as having an indirect effect through helping determine the forum's persuasiveness. Theoretical implications are discussed as well as practical implications for marketers and recommendations for further research. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Advertising is the property of Warc LTD and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Online reviews, a form of online word-of-mouth (eWOM), have recently become one of the most important sources of information for modern consumers. Recent scholarship involving eWOM often focuses on the transmission and impact of online reviews but sheds less light on the underlying processes that drive consumers’ receptions of them. Similarly, few studies have explored the recipients’ perspectives in the context of various services. This study addresses the aforementioned gaps in extant literature. The research model in this study is built upon the rich stream of literature related to how people are influenced by information and is tested on reviews collected from Yelp.com, a popular online advisory website dedicated to services businesses throughout the United States. The results of the study show that a combination of both reviewer and review characteristics are significantly correlated with the perceived usefulness of reviews. The study also finds several results that are anomalous to established knowledge related to consumers’ information consumption, both offline and online. The authors present the results of the study and discuss their significance for research and practice.
This study examines how processes of external influence shape information technology acceptance among potential users, how such influence effects vary across a user popula- tion, and whether these effects are persistent over time. Drawing on the elaboration-likelihood model (ELM), we com- pared two alternative influence processes, the central and peripheral routes, in motivating IT acceptance. These pro- cesses were respectively operationalized using the argument quality and source credibility constructs, and linked to per- ceived usefulness and attitude, the core perceptual drivers of IT acceptance. We further examined how these influence pro- cesses were moderated by users' IT expertise and perceived job relevance and the temporal stability of such influence effects. Nine hypotheses thus developed were empirically validated using a field survey of document management system acceptance at an eastern European governmental agency. This study contributes to the IT acceptance literature by introducing ELM as a referent theory for acceptance research, by elaborating alternative modes of influence, and by specifying factors moderating their effects. For prac- titioners, this study introduces influence processes as policy tools that managers can employ to motivate IT acceptance within their organizations, benchmarks alternative influence strategies, and demonstrates the need for customizing influence strategies to the specific needs of a user population.
Although many models of ad processing and response have been developed, most experimental tests of these models have exposed subjects only to advertising stimuli. In the marketplace, however, consumers often receive negative brand information in addition to advertising. In this study, we explored whether traditional models accurately predict ad processing and response when consumers integrate advertising with negative word-of-mouth (WOM) communications about the brand. A test was conducted using four experimental groups: ad only, negative WOM only, advertising then negative WOM, and negative WOM then advertising. Results show that (a) advertising mitigates the detrimental cognitive effects of negative WOM communication (when the ad is processed first) and the detrimental affective and conative effects (when the ad is processed last), (b) integrating ad content with negative WOM communication causes significant changes in the message processing of both, (c) negative WOM communication significantly reduces the perceived credibility of advertising as well as brand attitudes and purchase intentions, and (d) the effect of attitude toward the ad on brand attitude becomes nonsignificant when subjects process both types of information. Implications for marketing research and practice are discussed.
Online reviews, as one kind of quality indicator of products or service, are becoming increasingly important in influencing purchase decisions of prospective consumers on electronic commerce websites. With the fast growth of the Chinese e-commerce industry, it is thus indispensable to design effective online review systems for e-commerce websites in the Chinese context, by taking into account cultural factors. In this paper, we conduct two empirical studies on online reviews. Firstly, we study how culture differences across countries (i.e., China and the USA) impact the way in which consumers provide online reviews. Secondly, we investigate the impact of online reviews on product sales in the Chinese context, and show that directly copying the ideas of successful online review systems in the USA will deteriorate the effectiveness of the systems in China. Finally, we propose several suggestions for the development of effective online review systems in the Chinese context based on the results of our two empirical studies and the findings in previous studies.
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 product review networks help to transmit information that customers can use to evaluate product quality. The prior literature has found that, in the aggregate, better product reviews lead to higher sales. However, product review networks increasingly include an explicit social component that allows consumers to evaluate individual reviews based on the status of the reviewer and on the "helpfulness" of the review to the community. In this research, we extend this literature by analyzing the impact of reviews at a disaggregate level. We find that reviews that the community finds helpful have a stronger influence on consumers' purchase decisions than other reviews do. Moreover, these reviews have a stronger impact on less popular books than on more popular books, where consumers may be able to use other outside information sources to form an opinion of the product. Overall, our results suggest that the micro-level dynamics of community interactions are valuable in signaling quality over-and-above aggregate-level scores. One implication of this result is that the micro-level dynamics of reputation communities make it harder for self-interested parties to manipulate reviews versus an environment where consumers only have aggregate quality measures.
Whereas in brick and mortar stores quality and seller reliability can be effectively communicated through a variety of quality cues, in the online world different mechanisms help sellers establish reputation and trust. Among the commonly used mechanisms by infomediaries that screen and rate sellers are customer-feedback reputation mechanisms where buyers provide seller ratings and feedback. The success of such mechanisms and their impact on prices in electronic markets are described and empirically investigated in this work. Specifically, we investigate both theoretically and empirically (1) whether seller ratings affect consumer valuations, particularly in the presence of insurance; (2) whether seller ratings are indicative of future default likelihood; and (3) whether a seller who is terminal (about to go out of business) is more likely to default prior to exiting.
Consumers shopped for compact disks in a simulated Internet mall in a successive-choice procedure over 10 sessions. The procedure extended that of two previous consumer behavior experiments [DiClemente & Hantula, Psychol. Market. (in press); Rajala & Hantula, Managerial Decis. Econom. 21 (2000) 145] by assessing the influence of pricing on consumer preferences. Across five virtual stores, mean CD prices were 9.99, 11.99, 13.99, 15.99, and 4 range around the mean. Preference was measured as the total proportion of purchases made within each store. Consistent with previous studies of delay manipulations, a hyperbolic function provided the best fit to the store preference data. The results offer evidence of congruence between the effects of price and delay on consumer preferences, and support the contention that the price of goods may be interpretable as contributing to total delay time to primary reinforcement. Integrating evolutionary theory and the procedures of operant psychology, this research contributes to the development of a behavioral ecology of consumption and advances the experimental analysis of consumer behavior.
This article reviews selected literature related to the credibility of information, including (1) the general markers of credibility, and how different source, message and receiver characteristics affect people's perceptions of information; (2) the impact of information medium on the assessment of credibility; and (3) the assessment of credibility in the context of information presented on the Internet. The objective of the literature review is to synthesize the current state of knowledge in this area, develop new ways to think about how people interact with information presented via the Internet, and suggest next steps for research and practical applications. The review examines empirical evidence, key reviews, and descriptive material related to credibility in general, and in terms of on-line media. A general discussion of credibility and persuasion and a description of recent work on the credibility and persuasiveness of computer-based applications is presented. Finally, the article synthesizes what we have learned from various fields, and proposes a model as a framework for much-needed future research in this 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.
This essay presents a model of a single market in which goods of different qualities are sold and sellers advertise. Sellers advertise noncooperatively, knowing rivals' outlays and buyers' behavior patterns. Buyers react plausibly but not optimally to experience gained by purchasing and to sellers' advertising. Various properties of equilibria are analyzed. For some parameter values, the lowest-quality brands have the largest equilibrium market shares, advertising budgets, and profits. This is especially likely if buyers' behavior indicates confidence that better brands spend more on advertising.
We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight from emerging markets) prior to and during the 2008 financial crisis. In addition to widely used VaR and ES models, we also study the behavior of conditional and unconditional extreme value (EV) models to generate 99 percent confidence level estimates as well as developing a new loss function that relates tail losses to ES forecasts. Backtesting results show that only our proposed new hybrid and Extreme Value (EV)-based VaR models provide adequate protection in both developed and emerging markets, but that the hybrid approach does this at a significantly lower cost in capital reserves. In ES estimation the hybrid model yields the smallest error statistics surpassing even the EV models, especially in the developed markets.
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- C A Wicklund
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- J Hair
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