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Navigating by the Stars: Investigating the Actual and Perceived Validity of Online User Ratings
Abstract
This research documents a substantial disconnect between the objective quality information that online user ratings actually convey and the extent to which consumers trust them as indicators of objective quality. Analyses of a dataset covering 1,272 products across 120 vertically-differentiated product categories reveal that average user ratings (1) lack convergence with Consumer Reports scores, the most commonly used measure of objective quality in the consumer behavior literature, (2) are often based on insufficient sample sizes which limits their informativeness, (3) do not predict resale prices in the used-product marketplace, and (4) are higher for more expensive products and premium brands, controlling for Consumer Reports scores. However, when forming quality inferences and purchase intentions, consumers heavily weight the average rating compared to other cues for quality like price and the number of ratings. They also fail to moderate their reliance on the average user rating as a function of sample size sufficiency. Consumers’ trust in the average user rating as a cue for objective quality appears to be based on an “illusion of validity.”
... Online marketplaces bring together a diverse set of sellers who typically are unknown to potential buyers. Consumers usually evaluate listings according to a variety of attributes to select an item that best suits their needs (de Langhe et al., 2016). However, the uncertainty caused by the online environment, buyers' lack of familiarity with sellers, and the volume of often conflicting information makes decisions potentially complex and cognitively demanding (Wang et al., 2024). ...
... Extensive research on online marketplaces considers the effects of market signals on user behavior, focusing on aspects such as website characteristics, web design features, service feedback, and user ratings (Shah et al., 2023;de Langhe et al., 2016;Mavlanova et al., 2016;Mikalef et al., 2021;Maslowska et al., 2020). In addition, de Langhe et al. (2016) scrutinize the influence of online user ratings on consumer behavior, probing the accuracy with which these ratings depict the genuine quality of the goods or services in question. ...
... Extensive research on online marketplaces considers the effects of market signals on user behavior, focusing on aspects such as website characteristics, web design features, service feedback, and user ratings (Shah et al., 2023;de Langhe et al., 2016;Mavlanova et al., 2016;Mikalef et al., 2021;Maslowska et al., 2020). In addition, de Langhe et al. (2016) scrutinize the influence of online user ratings on consumer behavior, probing the accuracy with which these ratings depict the genuine quality of the goods or services in question. They raise critical questions concerning both actual validity (the correlation of ratings with quantifiable quality measures) and perceived validity (consumers beliefs in the credibility of these ratings). ...
... (2) Rating Bias in Preferences [14]. Research [14] indicates that bidders' average ratings frequently deviate from objective quality metrics, raising concerns about the reliability of directly inferring preferences from ratings surpassing a specific threshold. ...
... (2) Rating Bias in Preferences [14]. Research [14] indicates that bidders' average ratings frequently deviate from objective quality metrics, raising concerns about the reliability of directly inferring preferences from ratings surpassing a specific threshold. Therefore, we seek GPT-4's assistance in generating preferences based on ratings, objective reviews, exchange prices, and other relevant information. ...
Auctions, a fundamental economic mechanism, encompass the valuation of goods or services and the competitive bidding algorithms within a specific framework, serving to uncover the true market value. However, current research predominantly focuses on the bidding algorithms within a given auction mechanism, often overlooking the advantages of incorporating individual bidders' unique preferences and the semantic information related to the items into the valuation process. Our analysis, both theoretical and empirical, shows that imprecise or noisy valuations can significantly affect the overall utility for participants. To bridge this gap, we propose a personalized valuation framework, namely \textbf{S}emantic-enhanced \textbf{P}ersonalized \textbf{V}aluation in \textbf{A}uction (\ours), which integrates Large Language Models (LLMs) to incorporate semantic information into each bidder's unique valuation process. Specifically, SPVA employs a two-stage approach: it first fine-tunes LLMs to encode bidder preferences in personalized valuations, and then constructs a Vickrey auction environment integrated with a bidding algorithm to demonstrate that SPVA's more accurate valuations result in higher profits. Additionally, we have developed a semantic-enhanced dataset comprising over 23,000 samples and introduced new personalized evaluation metrics that reflect both bidder preferences and profit. Through simulations of various auction scenarios, our method demonstrates its ability to provide accurate valuations and capture bidder preferences, affirming the method's effectiveness in real-world auction settings.
... Brown et al. (2023) find that ratings of general practitioners in England significantly affected demand; especially among low income groups that lacked any other means to assess provider quality. More generally, research has shown these ratings affect customer purchase decisions, even if the ratings are not reliable indicators of objective quality (De Langhe et al. 2016). Interestingly, the FDA has been considering implementing a voluntary rating system for manufacturers, the Quality Management Maturity (QMM) rating; it is not yet clear the degree to which any ratings would be made public. ...
... For Study 2, the three attributes are drug price, drug quality and manufacturer location. To operationalize drug quality, we use the common approach of star ratings, one star to five-stars (De Langhe et al. 2016, Schoenmueller et al. 2020. Particularly, we consider three levels of drug quality: not reported (i.e., participants do not see a measure of quality, which mirrors the current status quo), three-stars and five-stars. ...
... contain manipulated reviews. Despite this, average ratings influence perceived product quality more than objective signals such as price (De Langhe et al., 2016), suggesting fake reviews potentially have a large influence on product choice if people do not (or cannot) discount them. ...
... Additionally, these studies usually present stimuli sequentially and rely on participants to infer the distribution from memory, whereas individuals generally see the entire ratings distribution. The mean rating has been found to be the strongest single signal of sales and quality, though it is true that people are also influenced by characteristics of the ratings distribution (e.g., De Langhe et al., 2016;Etumnu et al., 2020). Evidence on ensemble statistics suggests that people can recall summary statistics like the mean, maximum, and minimum when shown a set of stimuli (e.g., Ariely, 2001;Brady & Alvarez, 2011;Putnam-Farr & Morewedge, 2021). ...
The increasing importance of consumer ratings raises the question of whether people adjust for potentially fake or biased extreme opinions when judging products. Two studies tested treatments that trimmed the extremes of rating distributions. Neither removing extreme ratings while preserving the mean, nor flagging suspicious extreme ratings, nor priming individuals about review manipulation significantly affect judged product quality on average. However, judgments for specific distributions may be made less extreme by flagging or trimming. On average, it is difficult to override usage of the mean rating as the strongest proxy for product quality. When a weighted-mean model is fitted, the estimated weighting profile is hump-shaped and asymmetric. Consumers appear to discount 5-star ratings but are particularly susceptible to being misled by disingenuous 1-star ratings. The weights suggest that there is a binary bias with an inflection point at 2-stars for product ratings, meaning that any rating above this broadly sends an equally strong positive signal of quality. Further theoretical work is required to understand how people form weights for ratings, and applied work should continue to search for decision aids that could help consumers to better adjust for review bias.
... Study 3 tests pride of ownership as the mechanism driving the effect of democratization on willingness to purchase. We also examine alternative explanations, including perceived authenticity (Cinelli and LeBoeuf 2020), affordability (De Langhe et al. 2016), exclusivity, quality, and general luxury attitudes. We also manipulate both objective and subjective user status while shifting the industry focus to luxury sunglasses and using an advertisement instead of a story. ...
Luxury brands have traditionally embodied exclusivity and status, yet increasing accessibility is transforming consumers' perceptions. This trend, driven by the rapid democratization of luxury goods, is causing a paradigm shift in how traditional luxury consumers ascribe value to luxury brands. While these strategies may boost short‐term sales, they risk eroding brand positioning and alienating core consumers. Will traditional luxury consumers wear democratized brands with pride as accessibility and availability increase? Will they continue purchasing democratized luxury used by lower‐status consumers? Guided by network effects theory, we show across four mixed‐methods studies that democratization reduces purchase intentions—particularly when low‐status consumers adopt the brand—and increases abandonment intentions. This study advances luxury branding literature by identifying democratization as a novel negative network externality influencing luxury consumption. We reveal consumer's pride of ownership as a psychological mediator which diminishes when democratization erodes exclusivity. Further, we establish boundary conditions by revealing how status‐based consumption and rarity principles influence consumer responses and can moderate democratization's effects on purchase and abandonment intentions. Managerially, our findings will help brands to counteract democratization's potential risks through status and rarity‐driven campaigns, such as scarcity‐based strategies, limited editions or premium‐tier differentiation.
... The message conveyed in presenting Eq. 1 is that even a very simple Binomial model with strong assumptions (e.g. on the stability over time of β u ) would still require the estimation of three parameters. Nevertheless, the most common practices of modellisation of online reviews adopt the sample mean of the received ratesȳ i as an estimator for α i (de Langhe et al., 2016;Santos et al., 2019;Janosov et al., 2020), instead. Compared to Eq. 1, the implicit assumptions behind this practice is that β u is just another source of unbiased error ofȳ i , equivalently to set θ = 1 and¯ = 0. ...
Online reviews provide users with the opportunity to rate various types of items such as movies, music, and video games using a combination of numeric scores and textual comments. The study proposes a novel method that applies statistical matching on network-based covariates, with the aim to improve the estimation of the association between words and highly controversial items in online reviews. The application of this method on a sample of 40,665 items from the website Metacritic detects 218 highly controversial items. The application supports the theory that controversies on Metacritic are driven with a sense of self-awareness of participating of an online controversy (‘review bombing’). Typical controversial topics (sexual identities, religious morality, politics) are associated with controversial reviews, too.
... In current business practice, hotel booking platforms usually adopt a single-dimensional rating system or a multidimensional rating system. According to (Archak et al. 2011;De Langhe et al. 2016;Chen et al. 2018), a multidimensional evaluation system (consumers evaluate individual services provided in the accommodation facility 2 of 11 separately) is more important when conveying complex information about a product or service, because multi-dimensional ratings (e.g., service, location, cleanliness, etc.) facilitate information screening and information comparison. This means that potential consumers can evaluate whether a product or service meets their requirements or preferences through individual evaluations of each attribute of the product or service. ...
Customer reviews represent an important aspect when choosing accommodation from the customer’s point of view. The customer assumes that if the facility has a higher number of positive reviews from other customers, his experience with the services of the selected accommodation will be similar. This paper focuses on the importance of customer reviews of accommodation facilities in the context of V4 countries (Czech Republic, Hungary, Poland and Slovakia). The aim of the paper was to analytically evaluate customer reviews of accommodation facilities in V4 countries as an important factor in the selection and reservation of accommodation services, such as gastronomic services, accommodation and additional services. We focused primarily on examining the differences in customer evaluations of accommodation facilities in these V4 countries. The findings highlight the importance of positive and negative reviews in influencing guest satisfaction and loyalty. At the end of the paper, we offer recommendations for accommodation facilities that are focused on positive as well as negative reviews.
... However, most users still need clarification when selecting the optimal antivirus, given the plethora of choices available in the market [11]. Despite numerous articles on various websites discussing the best antivirus options, users continue to question the authenticity and objectivity of the presented data, as issues of data credibility and objectivity often arise [12]. Certain companies might even pay for favorable product reviews, leading to skepticism among users [13]. ...
p>The proliferation of smartphone malware attacks due to a lack of vigilance in app selection raises serious concerns. Built-in smartphone security features often must be improved to protect devices from these threats. Although numerous articles recommend top-tier antivirus solutions, there need to be more reliable data sources that raise suspicions about undisclosed promotional motives. This research endeavors to establish a ranking of antivirus efficacy to provide optimal recommendations for Android smartphone users. The research methodology entails a meticulous comparison of malware detection and labeling outcomes between various antivirus programs within Virustotal and the labeling system employed by the Euphony application. The comparative results are categorized into three groups: antivirus solutions proficient in identifying specific malware types, those detecting malware presence without categorization, and antivirus software failing to detect malware effectively. The experimental findings present the five leading antivirus solutions, ranked from the highest to lowest scores, as Ikarus, Fortinet, ESET-NOD32, Avast-Mobile, and SymantecMobileInsight. Based on the comprehensive assessment conducted in this study, these solutions are recommended as the top antivirus choices. These recommendations are poised to significantly aid users in selecting the most suitable antivirus protection for their Android smartphones.</p
... Online ratings of services are thought to help consumers predict their future level of satisfaction with the product or service (Wulff et al., 2014). If two online services have the same quality, customers will always choose the service that has a higher rating (de Langhe et al., 2016a(de Langhe et al., , 2016b. Users' reviews shape readers' expectations about the quality and performance of the product (Han, 2020). ...
The purpose of this study is to find and analyze factors that can affect Intention to Recommend in online medical consultation field. The research model is adapted from a previous study and then modified. Data were collected from women that are 17 years old and who have ever used the online medical consultation application, Halodoc. The research’s method is a quantitative survey, with cross-sectional data. Respondents’ data were taken by purposive sampling and questionnaires were distributed online. As many as 202 participants have fulfilled the requirements to be analyzed with PLS-SEM. The results showed that five antecedents had a significant influence on Intention to Recommend. Antecedents that were worth noting were Helpfulness Trust, Perceived Benefit, and Reliability Trust, where these factors show a positive impact on Intention to Recommend. Factors that could potentially influence users not using online medical consultation applications were also found, such as Performance Risk and Privacy Risk. From the findings of this study, it can be concluded that there are factors that may need to be considered by online medical consultation service providers to maintain or even to better their quality of care.
... However, most users still need clarification when selecting the optimal antivirus, given the plethora of choices available in the market [11]. Despite numerous articles on various websites discussing the best antivirus options, users continue to question the authenticity and objectivity of the presented data, as issues of data credibility and objectivity often arise [12]. Certain companies might even pay for favorable product reviews, leading to skepticism among users [13]. ...
The proliferation of smartphone malware attacks due to a lack of vigilance in
app selection raises serious concerns. Built-in smartphone security features
often must be improved to protect devices from these threats. Although
numerous articles recommend top-tier antivirus solutions, there need to be
more reliable data sources that raise suspicions about undisclosed promotional
motives. This research endeavors to establish a ranking of antivirus efficacy
to provide optimal recommendations for Android smartphone users. The
research methodology entails a meticulous comparison of malware detection
and labeling outcomes between various antivirus programs within virustotal
and the labeling system employed by the euphony application. The
comparative results are categorized into three groups: antivirus solutions
proficient in identifying specific malware types, those detecting malware
presence without categorization, and antivirus software failing to detect
malware effectively. The experimental findings present the five leading
antivirus solutions, ranked from the highest to lowest scores, as Ikarus,
Fortinet, ESET-NOD32, Avast-M obile, and SymantecM obileInsight. Based
on the comprehensive assessment conducted in this study, these solutions are
recommended as the top antivirus choices. These recommendations are poised
to significantly aid users in selecting the most suitable antivirus protection for
their Android smartphones.
... As a result, agents learn from peers' public disclosures of information (Amador and Weill, 2012;Wang and Wang, 2018), with observational learning being more prevalent among infrequent and inexperienced customers (Cai et al., 2009). Moreover, consumers rely more on average ratings than on other quality cues such as price or number of reviews (de Langhe et al., 2016). In the hospitality industry, subjective ratings have replaced objective classification systems as reputation signals and hotel managers are now monitoring consumer reviews on online platforms (Proserpio and Zervas, 2017). ...
This study investigates the informational content of online reviews. Unlike other studies that have explored the drivers of average rating scores, we examine the factors explaining the variance in individual ratings for the same goods. In particular, we focus on how the length of stay at a hotel, as a measure of consumption span, influences the variance of rating scores. We conduct an empirical analysis using approximately 522,000 individual hotel reviews on Booking.com from five major European cities. Results indicate that the volatility of individual ratings decreases with stay duration, implying that online ratings from short-stayers (short consumption episodes) are noisy signals of the underlying hotel quality. We also present preliminary evidence that greater volatility negatively correlates with perceived usefulness by subsequent consumers. Our findings offer relevant insights for platform design operators about the drivers of rating volatility and how it affects social learning.
... Usually, in these systems, customers provide feedback on services in the form of online reviews either directly on the selling platform (e.g., rating a service booked on Fiverr 1 ) or on specific review platforms (e.g., providing travel reviews on Tripadvisor 2 ) (Schneider et al. 2021). Although online ratings do not necessarily provide an objective measure of service quality (De Langhe et al. 2016), they are highly influential for customer-decision making, which is reflected in sales and consequently in business success (Simonson 2016). Customers' online rating data can even be utilized to predict service business failures months in advance as it has been shown for the hospitality industry (Naumzik et al. 2022). ...
Organizations have to adjust to changes in the ecosystem, and customer feedback systems (CFS) provide important information to adapt products and services to changing customer preferences. However, current systems are limited to single-dimensional rating scales and are subject to self-selection biases. The work contributes design principles for CFS and implements a CFS that advances current systems by means of contextualized feedback according to specific organizational objectives. The authors apply Design Science Research (DSR) methodology and report on a longitudinal DSR journey considering multiple stakeholder values by utilizing value-sensitive design methods. They conducted expert interviews, design workshops, demonstrations, and a four-day experiment in an organizational setup, involving 132 customers of a major Swiss library. In the process, the identified design principles and the implemented software artifact were validated qualitatively and quantitatively, leading to conclusions for their efficient instantiation. The authors found that i) blockchain technology can afford four design principles of effective CFS. Also, ii) combining DSR with value-sensitive design methods explicitly provides rationale for design principles in the form of identified important values. Moreover, iii) combining DSR with value-sensitive design methods makes the construction of software artifacts more efficient it terms of design time by restricting the design space of a software artifact to those options that align with stakeholder values. The findings of this work thus extend the knowledge about the design of CFS and offer both researchers a theoretical contribution to reasoning about design principles and managers and decision makers a guide for the efficient design of software artifacts.
... Additionally, a lower price indicates less financial risk associated with purchasing the service, creating greater economic incentives, and patients are generally more inclined to choose lowerpriced healthcare services [79]. Secondly, service prices are often considered to represent service quality, and lower-priced services are not typically associated with high service quality [80]. Once lower-priced services involve more knowledge sharing, patients may feel more satisfied because the service exceeds expectations. ...
Grounded in signaling theory, this study explores the influence of user-generated content (UGC) within online healthcare communities on patient purchasing behavior, with the overarching goal of advancing the development of online medical consultation services and contributing to the sustainable evolution of the online healthcare community. Leveraging publicly available data from the “Haodf.com”, we construct an empirical model of online medical consultation purchases, integrating principles from signaling theory and trust theory. Our analysis scrutinizes the effects of various forms of UGC on patient purchasing behavior, alongside the moderating influence of associated signals. The results demonstrate that knowledge-sharing articles authored by doctors and patient ratings positively impact consultation service purchases, whereas public displays of doctors’ past consultation records impede such transactions. Furthermore, external signals were found to moderate the relationship between UGC and consultation service purchases. The implications of these findings offer actionable insights for stakeholders invested in online healthcare communities.
... Thus, the use of viral marketing strategies by increasing viral messages can help consumers in determining purchasing decisions. From the explanation above, the fourth hypothesis is formulated, namely: H4 : There is an influence of viral marketing on purchasing decisions Online consumer reviews are very important in making purchasing decisions (de Langhe et al., 2016). Trusted comments can be decisive in choosing a product. ...
Online shopping in Indonesia will continue to increase along with technological advances, Data collected by APJII and Suara.com shows that "more than 74% of Indonesians choose to shop online." This study aims to examine the mediating role of trust in the influence of viral marketing and online consumer reviews on purchasing decisions through trust. The data obtained by this study through a questionnaire from 100 respondents of Skintific users on TikTok. This research data is processed using SEM (Structural Equation Modeling) using the SmartPLS4 application. The results of this study are Viral Marketing has a significant impact on Trust, Online Consumer Reviews has a significant impact on Trust, Trust has a significant impact on Purchasing Decisions, Viral Marketing has a significant impact on purchasing decisions, Online Consumer Reviews has a significant impact on Purchasing Decisions, Viral Marketing has a significant impact on Purchasing Decisions through Trust, Online Consumer Reviews has a significant impact on Purchasing Decisions through Trust. The implication of this research for the Skintific company is that it is expected to always maintain a good message on Viral Marketing, create a good reputation in consumer perceptions starting from the products sold, the services provided, and other aspects that appear in TikTok media.
... The significance of online reviews as a crucial form of customer feedback is well supported by the literature, with contributions from Raza et al. (2023), Hong and Pittman (2020), and de Langhe et al. (2016) highlighting their essential role. Kaemingk (2022) notes that about 93% of online shoppers peruse reviews before making purchasing decisions, underscoring the necessity for businesses to grasp the substantial influence of online reviews. ...
Feedback mechanisms, such as customer reviews and ratings, are essential for making informed decisions on online platforms, particularly in the presence of asymmetric information. However, the practice of reward‐based reviews is on the rise in online platforms, where sellers incentivise buyers to give biased feedback (e.g., 5‐star ratings) regardless of the quality of the products. This study intends to determine whether financial incentives motivate people to award dishonest ratings and explore the moral heuristics underlying this motivation. Using a hypothetical purchase scenario, responses were elicited from 411 participants and the Philosophical Moral Framework Measure (PMFM) was used to identify the moral frameworks that underlie the reported self‐interested behaviour. The findings reveal that the likelihood of giving fake reviews increases with an increase in financial incentives. The dominant moral framework of those who accepted the cashback offer is utilitarianism and egoism, whereas those who declined the offer primarily have deontology and virtue theory as dominant frameworks. The results also indicate that men and young individuals are more likely to give dishonest feedback. These findings not only advance the understanding of the interplay between financial incentives and self‐interested behaviour but also aid in identifying the moral frameworks underlying self‐interested behaviour.
... To be sure, we are not arguing that customer ratings or certifications fully resolve information asymmetries. Such a claim is beyond the scope of this article (but see De Langhe et al., 2015). What matters is that consumers behave as though they solve the problem, which means that they appear to rely on them as indicators of trustworthiness. ...
In his theory about the role of nonprofit enterprise, Henry Hansmann suggested that nonprofit status provides important information to consumers in low-information environments. In this article, we assess whether consumers use nonprofit status to form purchasing preferences as Hansmann predicted. Using choice-based conjoint analysis, we find that under different types of low-information circumstances, study participants prefer goods and services provided by nonprofits to those offered by businesses. In the absence of additional information (such as customer ratings and third-party certifications), nonprofit status serves as an important value signal to consumers. In the presence of additional information, nonprofit status is still relevant in some cases, although it becomes less so. The findings suggest that additional forms of information do not necessarily displace the value to consumers of information about organization type. We reflect on these findings in light of Hansmann’s thesis.
... Although we do not consider the impact of number of ratings, our findings are broadly in line with previous research (Watson et al. 2018) in showing that the diagnosticity of consensus ratings can vary by context, and we focus attention on the cultural context in influencing how consumers perceive attitudinal consensus. Our Amazon and BAV findings (studies 6-7) also appear consistent with research showing the high levels of trust that consumers overall tend to place in users' attitudinal ratings when judging products (de Langhe et al. 2016). ...
Marketers commonly use consensus cues about others’ behavioral choices (“Best Seller”) or their attitudes (“Top Rated”) when labeling products. This paper suggests that the effectiveness of these types of cues may differ across cultures in ways that carry implications for marketing practice. Prior research shows that in contexts that give rise to an interdependent cultural self-construal, choices are often responsive to social expectations rather than personal preferences. We propose that, because interdependents expect such behavioral conformity, cues that convey consensus about others’ choices may be less diagnostic and, thus, less persuasive than cues that convey consensus about others’ attitudes. Five studies examining cultural self-construal in multiple ways, along with two cross-national industry datasets, offer evidence consistent with this reasoning, suggesting that among interdependents, behavioral consensus cues can actually be less effective than attitudinal ones, reducing persuasion and willingness to pay. However, among independents, because attitudes are assumed to influence behavioral choices, whether the consensus cue is attitudinal or behavioral makes little difference.
... • Validity of Online User Ratings: This stream of research is part of topic 7(consumer reviews and risk). For example, DeLanghe et al. (2016) discuss the disconnect between the objective quality information that online user star ratings convey and the extent to which consumers trust them as indicators of objective quality.The paper utilizes Monte Carlo simulation to validate their model on the discrepancy between Consumer Reports and individual user ratings. Future consumer research can utilize Monte Carlo simulations to validate their star rating findings using narrative reviews by studying the frequency with which consumers read narratives. ...
This study investigates biases introduced when soliciting customer satisfaction survey respondents to post online reviews on different platforms. We examine review nonresponse bias and measurement bias arising when customers post reviews on TripAdvisor or Google Travel. Our findings indicate that platform heterogeneity significantly impacts both the likelihood of posting a review and the ratings provided, leading to biases. Review nonresponse bias occurs when not all survey respondents post reviews, creating a selection bias. Measurement bias arises when posted ratings differ from survey responses. Our analysis reveals that Google Travel users with negative experiences are less likely to post reviews, but those who do post tend to give lower ratings compared to their survey responses. Conversely, TripAdvisor users show less review nonresponse bias, but their posted ratings are more positive when survey responses are negative. Understanding platform-specific biases can help managers adjust opinion weights to ensure reliability. Academically, this research advances the literature by distinguishing review nonresponse bias from measurement bias and encourages further comparative studies across platforms.
Platforms present various certifications to signal the quality of their offerings to prospective consumers. For example, Airbnb.com designates some hosts as “Superhosts” to distinguish properties that provide superior experiences. Platforms also present user-generated ratings—typically elicited and presented as “star ratings”—from their customers for the same purpose. This research investigates the interaction of these signals of quality and suggests a potential downside to platform-provided certifications: They decrease subsequent ratings. In an analysis of over 1,500,000 ratings from Airbnb.com and three follow-up studies, we find that properties with the superhost designation receive lower ratings. We assess the robustness of this result in several ways, including comparing ratings on Airbnb with those for the same property of Vrbo. In three follow-up experiments, we find that the net effect of certifications can lead to reduced choice share: The positive effect of signaling quality is more than offset by the negative effect of reduced ratings. This suggests that consumers are not sufficiently aware of this effect of quality certifications on ratings when choosing.
Some retailers use stars, while others use Arabic numerals to present product ratings. Do consumers evaluate product ratings differently depending on the format? Which format more accurately represents the true magnitude of ratings? Across 12 experiments, we find that neither format is veridical. Consumers overestimate fractional star ratings (e.g., ⋆⋆⋆⋆⋆) and underestimate fractional Arabic numerals (e.g., 3.5). The overestimation of graphical ratings arises from the visual-completion effect: when the visual system perceives an incomplete image of a star, it instinctively activates the complete image, causing consumers to anchor their magnitude judgments on rounded-up numbers (i.e., evaluation of ⋆⋆⋆⋆⋆ is anchored on ⋆⋆⋆⋆⋆). Importantly, our results show that this overestimation of star ratings can be mitigated by using visually complete stars (e.g., ⋆⋆⋆⋆ ). Conversely, the underestimation of Arabic numeral ratings stems from the left-digit effect, which leads consumers to anchor magnitude judgments on rounded-down numbers (i.e., evaluation of 3.5 is anchored on digit 3). Thus, both star and Arabic numeral ratings are systematically misestimated by consumers, with the extent of misestimation varying based on the fractional value and the star-filling technique employed. These findings demonstrate that prevalent rating formats are misleading, highlighting the need for new industry standards.
Online platforms increasingly utilize technologies like artificial intelligence (AI)-empowered tools to reduce consumers’ search costs and simplify decision making. However, these tools often target specific types of information, leading to what we term "search cost reduction for partial information." Although designed to assist consumers, our study highlights their unintended consequence: these tools can induce "cognitive miser" behavior, where consumers focus on easily accessible information while neglecting other critical details. This behavior can ultimately result in poorer decision making. Using a natural experiment on Yelp, we evaluated the impact of its AI-powered image categorization feature, introduced in 2015 to reduce the search costs of review images. Through a difference-in-differences design and text analysis of consumer complaints, we found that this feature negatively affected decision quality. These findings carry important implications for platform managers and policymakers. Although search cost reduction tools can improve efficiency, they also risk biasing consumer attention toward easily accessible information at the expense of holistic decision making. Online platforms could mitigate these effects by complementing AI-empowered search cost reduction features with tools that emphasize information requiring greater cognitive effort, thereby ensuring balanced consumer awareness. We recommend that platform designers carefully evaluate the broader impacts of such tools to better support consumer decision making.
Human behavior in cyber space is extremely complex. Change is the only constant as technologies and social contexts evolve rapidly. This leads to new behaviors in cybersecurity, Facebook use, smartphone habits, social networking, and many more. Scientific research in this area is becoming an established field and has already generated a broad range of social impacts. Alongside the four key elements (users, technologies, activities, and effects), the text covers cyber law, business, health, governance, education, and many other fields. Written by international scholars from a wide range of disciplines, this handbook brings all these aspects together in a clear, user-friendly format. After introducing the history and development of the field, each chapter synthesizes the most recent advances in key topics, highlights leading scholars and their major achievements, and identifies core future directions. It is the ideal overview of the field for researchers, scholars, and students alike.
We study the impact of consumer heterogeneity on online ratings. Consumers differ in their experience, which can affect both their choices and ratings. Thus, biases in average ratings can arise when the opinions of experienced and novice users are aggregated. We first build a two-period model to characterize the biases’ drivers and consequences. We test our theory combining data from IMDb and MovieLens, two well-known movie ratings platforms. We proxy users’ experience with the total number of ratings posted on the platforms. First, using external measures of quality, such as the Academy awards and nominations, we show that, on both platforms, experienced users, on average, rate movies of higher quality compared with novices. Moreover, they post more stringent ratings than novices for more than 98% of movies. Combined, these imply a compression in aggregate ratings, and thus a bias against high quality movies. We then propose a simple, fixed-point algorithm to debias ratings. Our debiased ratings demonstrate the presence of ranking reversals for more than 8% of comparisons in our sample. As a result, our debiased ratings better correlate with external measures of quality.
This paper was accepted by Eric Anderson, marketing.
Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.03281 .
Purpose
Online patient reviews are of considerable importance on online health platforms. However, there is limited understanding of how these reviews are generated and their impact on patients' choices of physicians. Therefore, this study aims to investigate the antecedents and consequences of online patient reviews on online health platforms.
Design/methodology/approach
This study introduced an online interaction model with multiple stages aimed at examining how physicians' service quality affects patients' review behavior and, consequently, influences patients' choices of physicians.
Findings
The results revealed that technical quality and emotional care significantly influenced the effort that patients exert and their use of positive emotional words when writing reviews, which, in turn, positively influenced patients' selection of physicians. Moreover, it was found that the voice channel had a significant moderating effect on the relationship between physician service quality and patient review behavior.
Practical implications
The study’s findings can help online health platform managers improve the platform system by optimizing the integrated text and voice interaction functions. The findings can also support physicians in improving service quality, managing online reviews and attracting patients’ choices.
Originality/value
This study enriches the literature on physician service quality, patient online reviews and choices in online health platforms. Furthermore, this study offers a novel perspective on the social exchange process in online healthcare settings by highlighting the role of media in shaping physician–patient interactions.
This chapter is designed to provide a thorough examination of the performance metrics used to evaluate the effectiveness of neurosensory marketing strategies. Neurosensory marketing combines the principles of neuroscience with sensory marketing techniques to create compelling consumer experiences. This chapter will focus on identifying and analysing the key performance metrics that marketers can use to assess the success and impact of their neurosensory marketing efforts. This chapter will provide readers with a comprehensive understanding of the various metrics used to evaluate neurosensory marketing strategies. By examining both theoretical and practical aspects, the chapter will offer valuable insights for researchers, marketers, and students interested in the intersection of neuroscience and marketing.
Building on the literature on trust and Persuasion Knowledge Theory, this study examines the mediating role of trust in the relationship between algorithm performance expectancy and impulse buying in online retailing. Furthermore, it examines how impulse buying among online shoppers is influenced by the number of product recommendations displayed on a retailer's website (a small vs. large number of recommendations), along with the presence or absence of recommendation ratings. A survey-based study and an experiment indicated that consumer trust in algorithm-driven product recommendations correlates with heightened impulse buying of a recommended product, particularly when a large number of recommendations are presented. However, the presence (vs. absence) of recommendation ratings had no impact on impulse buying. This study extends literature on the impact of product recommendation design. This contributes to a deeper understanding of how product recommendation formats influence consumer behavior and offers insights for retailers regarding the strategic presentation of personalized product recommendations to enhance impulse buying.
This research explores the role of dual-processing systems in evaluating complex information on online travel agency (OTA) websites, explicitly focusing on the transformative effects of multiple cues considering information sources. Two experimental studies were conducted to explore the processing modes of information using priming in assessing the impact of a controllable cue (brand in study 1 and scarcity in study 2 and an uncontrollable cue (customer ratings). The findings indicate that customer ratings function as a primary cue. With positive priming producing heuristics, the value of a brand offsets the negative impact of low ratings, while it is disregarded with high ratings. The perceived value of scarcity aligns consistently with customer ratings due to its inherent uncertainty with irrelevant priming triggering a systematic mode. This research advances the understanding of customers’ evaluation of complex information and suggests practical guidelines for implementing optimal marketing strategies in OTA settings.
Purpose
This study aims to examine the impact of consumer risk appetite, biases (specifically negative recency bias), and the importance of reviews in enhancing information quality. By analyzing these variables, the authors gain insights into their role in enriching the overall information spectrum available to consumers. The findings contribute to a better understanding of how risk appetite, biases and consumer reviews shape the quality of information.
Design/methodology/approach
The questionnaire assessed the relationship between dependent and independent variables by asking participants to rate their experiences in relevant scenarios. Variance-based structural equation modeling with the ADANCO program was used to examine the data. ADANCO software is used explicitly for variance-based structural equation modeling. To evaluate research models and test hypotheses, partial least square path modeling is used.
Findings
The efficiency of reviews and ratings is greatly influenced by consumer risk appetite. Businesses should focus on clients who are willing to take risks and balance positive and negative feedback. It is essential to comprehend how customers understand reviews. Credibility is increased by taking biases into account and encouraging unbiased criticism. Promoting thorough reviews strengthens influence. Monitoring and making use of these elements improve online reputation and commercial success.
Research limitations/implications
The research has limitations due to the simplicity of the attributes taken into account and the requirement for a larger sample size. Overcoming barriers to promote consistent client feedback is essential, and tailored emails can help with assessment generation. Increased customer participation in writing evaluations can be achieved by removing obstacles and highlighting the advantages of participation.
Originality/value
Businesses and buyers rely on this “organically” generated content as the basis of their promotional strategy and buying decisions. Most of the research is related to consumer reviews, their behavior and the importance of social validation. However, some critical aspects related to this need further investigation.
Purpose
The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.
Design/methodology/approach
Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.
Findings
The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.
Research limitations/implications
The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.
Originality/value
The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.
Average product ratings are displayed on many major websites, including online retailers, search engines, and social media sites. Research in both academia and industry has shown that consumers rely heavily on product ratings when making purchase decisions. Websites may show customer ratings in different shapes, colors, or formats. For example, some websites present their rating in a numerical format (e.g., 4.0/5) while others utilize an analog format (e.g., êêêêê). The present research investigates how a website’s rating presentation may influence magnitude perceptions of the rating, which subsequently affect choices and purchase intentions. We propose and find that when the average customer rating is at or above the midpoint (i.e., .5 - .9) of each rating level (i.e., 1 – 5 on a 5-pt. scale) the numerical (vs. analog) rating format is perceived to be lower in magnitude due to left-digit anchoring, leading to differences in choice likelihood, purchase intent, and ad click likelihood for products and services. Across nine experiments, including an eye tracking study, and a multiple-ad study without holdout, we show robust evidence for our proposed effect.
How does the way companies elicit ratings from consumers affect the ratings that they receive? In 10 pre-registered experiments, we find that consumers rate subpar experiences more positively overall when they are also asked to rate specific aspects of those experiences (e.g., a restaurant’s food, service, and ambiance). Studies 1–4 established the basic effect across different scenarios and experiences. Study 5 found that the effect is limited to being asked to rate specific features of an experience, rather than providing open-ended comments about those features. Studies 6–9 provided evidence that the effect does not emerge because rating positive aspects of a subpar experience reminds consumers that their experiences had some good features. Rather, it emerges because consumers want to avoid incorporating negative information into both the overall and the attribute ratings. Lastly, study 10 found that asking consumers to rate attributes of a subpar experience reduces the predictive validity of their overall rating. We discuss implications of this work and reconcile it with conflicting findings in the literature.
Among the various aspects of a firm’s digital presence, the firm’s online reviews are now a common and increasingly important source of information. Extant online reviews literature has extensively examined the downstream impacts of online review rating, in which a firm’s rating signals the firm’s quality to its downstream end-users and consequently drives the firm’s downstream sales. However, little is known about the implications that a firm’s online rating may have for other channel members, such as the firm’s upstream supplier. Combining signaling theory with power–dependence literature, I investigate the upstream impact of a firm’s online rating on the financial outcomes of the firm’s supplier. Contrary to the common expectation, I find that under certain conditions, an increase in a firm’s online rating leads to a decrease in the supplier’s sales to that firm. I theorize that a supplier’s sales to a firm are determined not only by how much the firm sells downstream, which tends to increase with a higher rating, but also by how the firm handles its purchases upstream from the supplier. The findings suggest important implications for managers of both the firm and supplier companies in utilizing publicly available online information such as a firm’s online rating to manage the upstream firm-supplier relationship.
Amaç –Çevrimiçi alışverişin arttığı günümüzde tüketiciler, satın alma kararı vermeden önce satın almayı düşündükleri ürünlerle ilgili daha önceden alışverişi deneyimleyen tüketicilerin yorumlarını ve satıcının alışveriş puanlarını inceleyerek satın alma kararlarını vermektedir. Bu bağlamda hem tüketiciler hem de satıcılar için yorumlar ve değerlendirme puanlamaları oldukça önemli hale gelmiştir. Bu araştırmayla Z kuşağındaki tüketicilerin çevrimiçi yorum ve değerlendirme puanlarına yönelik tutumlarının çevrimiçi tüketici davranışlarına etkisinin ortaya çıkarılması amaçlanmaktadır.Yöntem –Çalışmada veri toplama yöntemi olarak yüz yüze anket yöntemi tercih edilmiştir. Burdur Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Meslek Yüksekokulu (MAKÜ SBMYO) öğrencileri Z Kuşağını temsil etmesi açısından örneklem olarak alınmıştır. Zaman ve maliyet açısından kolayda örnekleme yöntemi seçilmiştir. Toplam 364 gönüllü öğrenci araştırmaya katılmıştır. Araştırma verileri Mayıs-Ağustos 2022 tarihleri arasında toplanmıştır. Analiz yöntemi olarak Frekans Analizi, Doğrulayıcı Faktör Analizi ve Yapısal Denklem Modeli kullanılmıştır. Bulgular –Araştırma sonucunda çevrimiçi yapılan alışverişlerde mal ve hizmete yapılan yorum ve değerlendirme puanlarının tüketici davranışını etkilediği tespit edilmiştir.Tartışma –Çevrimiçi yorum ve değerlendirme puanlarının çevrimiçi tüketici davranışlarını etkiledi sonucuna ulaşılmıştır. Bu sonucun hem tüketiciler hem de çevrimiçi ticaret yapan işletmeler için önemli olduğu düşünülmektedir. Çevrimiçi ticaret yapan işletmeler, bu çevrimiçi yorum ve değerlendirme puanlarından yola çıkarak mal politikaları ve müşteri ilişkileri yönetimlerini daha etkin bir şekilde yürütebilirler.
Many online platforms are now offering free samples to seasoned reviewers, hoping to get feedback. While these reviewers are given free samples to review, they also buy and review products themselves. The regular ratings for the purchased products are the majority. This brings up the question: Does receiving free products make them rate their personal purchases more positively? And if so, why? We explored two possibilities. First, uncertainty reduction mechanism: The idea that trying free samples makes buyers more confident in their purchases, leading to greater satisfaction and higher ratings for the purchased products; Second, reciprocity mechanism: The idea that reviewers might feel obliged to give better ratings as a “thank you” for the free samples or with the expectations of getting more free samples, which could introduce bias. Our research indicates that giving free samples mainly helps in reducing purchase uncertainty, making customers genuinely happier with their subsequent purchases. So, online platforms can benefit from this strategy, as it seems to uplift genuine positive reviews rather than create biased ones. However, it is still essential to monitor for any undue bias to maintain trustworthiness in reviews.
Purpose
In this paper the authors aim to review the state-of-the-art literature on online review systems and their impacts on consumer behavior and retailers' performance with the aim of identifying research gaps related to different design features of review systems and developing future research agenda.
Design/methodology/approach
The authors conducted a systematic review based on PRISMA 2020 protocol, focusing on studies published in the domains of retailing and marketing. This procedure resulted in 48 selected papers investigating the design features of retailer online review systems.
Findings
The authors identify eight design features that are controllable by retailers in an online review system. The design features have been researched independently in previous literature, with some features receiving more attention. Most selected studies focus on the design features adapted metrics and review presentations, while other features are generally neglected (e.g. rating dimensions). Previous literature argues that design features affect consumer behaviors and retailers' performance. However, the interactions among the features are still neglected in the literature, creating a relevant gap for future research.
Originality/value
This paper distinguishes between different types of retailer online review systems based on how they are implemented. The authors summarize the state-of-the-art of relevant literature on design features of online review systems and their effects on consumer- and retailer-related outcome variables. This systematic literature review distinguishes between online reviews provided on websites controlled by retailers (internal systems) and third-party websites (external systems).
Evidence from past research and insights from an exploratory investigation are combined in a conceptual model that defines and relates price, perceived quality, and perceived value. Propositions about the concepts and their relationships are presented, then supported with evidence from the literature. Discussion centers on directions for research and implications for managing price, quality, and value.
Simonson (2015a) addresses marketing scholars trained in psychology who focus on behavioral decision theory. He encourages those scholars to shift some attention from traditional BDT topics to analyze substantive issues such as how the Internet changes consumer decision making. I agree with and I expand upon his call to action. I analyze sociology of science forces that I expect to cause those young BDT researchers to be resistant to wise Uncle Itamar's generally excellent advice.
In some product categories, low-priced brands are consistently of low quality, but high-priced brands can be anything from terrible to excellent. In other product categories, high-priced brands are consistently of high quality, but quality of low-priced brands varies widely. Three experiments demonstrate that such heteroscedasticity leads to more extreme price-based quality predictions. This finding suggests that quality inferences do not only stem from what consumers have learned about the average level of quality at different price points through exemplar memory or rule abstraction. Instead, quality predictions are also based on learning about the covariation between price and quality. That is, consumers inappropriately conflate the conditional mean of quality with the predictability of quality. We discuss implications for theories of quantitative cue learning and selective information processing, for pricing strategies and luxury branding, and for our understanding of the emergence and persistence of erroneous beliefs and stereotypes beyond the consumer realm.
Quality is a central element in business strategy and academic research. Despite important research on quality, an opportunity for an integrative framework remains. The authors present an integrative framework of quality that captures how firms and customers produce quality (the quality production process), how firms deliver and customers experience quality (the quality experience process), and how customers evaluate quality (the quality evaluation process). The framework extends the literature in several ways. First, the authors describe important linkages between the three processes, including links reflecting the role of co-production. Second, they point to overlooked aspects of the quality processes that influence how quality is conceptualized and should be managed. These include customer heterogeneity in measurement knowledge and motivation; the role of emotion in quality production, experience, and evaluation; and a new typology of attributes. Third, they propose a quality state residing within each quality process and describe what gives rise to these states, which will enhance decision makers' ability to measure and manage quality processes. Finally, they offer theoretical and managerial implications derived from their integrative quality framework including 20 strategies to increase customer satisfaction.
A growing body of research has emerged on online product reviews and their ability to elicit performance outcomes desired by retailers; yet, a common understanding of the performance implications of online product reviews has eluded us. Scholars continue to navigate an array of studies assessing different design elements of online product reviews, and various research settings and data sources. We undertake a meta-analysis of 26 empirical studies yielding 443 sales elasticities to examine how these variables relate to retail sales. Building on well-established meta-analytical methods, we address the following questions: How does review valence influence the elasticity of retailer sales? What about review volume? For which product types and usage situations do online product reviews have a greater impact on retailer sales elasticity? Which types of online reviewers and websites exert the greatest influence on retailer sales elasticity? Our study answers these important questions and provides a much needed quantitative synthesis of this burgeoning stream of research.
Follow the Leader?
The Internet has increased the likelihood that our decisions will be influenced by those being made around us. On the one hand, group decision-making can lead to better decisions, but it can also lead to “herding effects” that have resulted in financial disasters. Muchnik et al. (p. 647 ) examined the effect of collective information via a randomized experiment, which involved collaboration with a social news aggregation Web site on which readers could vote and comment on posted comments. Data were collected and analyzed after the Web site administrators arbitrarily voted positively or negatively (or not at all) as the first comment on more than 100,000 posts. False positive entries led to inflated subsequent scores, whereas false negative initial votes had small long-term effects. Both the topic being commented upon and the relationship between the poster and commenter were important. Future efforts will be needed to sort out how to correct for such effects in polls or other collective intelligence systems in order to counter social biases.
Evidence from past research and insights from an exploratory investigation are combined in a conceptual model that defines and relates price, perceived quality, and perceived value. Propositions about the concepts and their relationships are presented, then supported with evidence from the literature. Discussion centers on directions for research and implications for managing price, quality, and value.
Hypothesized that information which is disproportionately available in memory will have a correspondingly disproportionate impact on evaluative judgments. In a mock jury decision, the availability of selected information in memory was varied according to the relative vividness of the evidence (prosecution evidence more vivid or defense evidence more vivid) and the favorableness of the defendant ("good guy" or "bad guy"). 54 university students judged the defendant's guilt immediately and after 48 hrs; in addition, they recalled the evidence after the 48-hr interval. Ss recalled more vivid evidence and more evidence that disagreed with the defendant's favorableness. Their judgments of apparent guilt paralleled their differential recall of the prosecution and defense evidence. These availability differences occurred only after the retention interval and did not affect judgments given immediately after reading the arguments. Results support a model in which judgments are based on the availability and the diagnosticity of the information. (26 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
[enter Abstract Body]This research investigates the effects of the amount of information presented, information organization, and concern about closure on selective information processing and on the degree to which consumers use price as a basis for inferring quality. Consumers are found to be less likely to neglect belief-inconsistent information and their quality inferences less influenced by price when concern about closure is low (vs. high) and information is presented randomly (vs. ordered) or asmall amount of information is presented. Results provide a picture of a resource-constrained consumer decision maker who processes belief-inconsistent information only when there is motivation and opportunity.
Based upon a recently developed multiattribute generalization of prospect theory's value function (Tversky and Kahneman 1991), we argue that consumer choice is influenced by the position of brands relative to multiattribute reference points, and that consumers weigh losses from a reference point more than equivalent sized gains (loss aversion). We sketch implications of this model for understanding brand choice.
We develop a multinomial logit formulation of a reference-dependent choice model, calibrating it using scanner data. In addition to providing better fit in both estimation and forecast periods than a standard multinomial logit model, the model's coefficients demonstrate significant loss aversion, as hypothesized.
We also discuss the implications of a reference-dependent view of consumer choice for modeling brand choice, demonstrate that loss aversion can account for asymmetric responses to changes in product characteristics, and examine other implications for competitive strategy.
We present an analysis of equilibrium in markets with asymmetrically informed consumers. Some consumers know both price and quality of all sellers, whereas others know neither but may search among sellers. The equilibrium correlation between price and quality generally increases with the level of information in the market and can be negative when this level is sufficiently small. A meta-analysis of the available empirical studies strongly supports the model's predictions.
Online consumer product review is an emerging market phenomenon that is playing an increasingly important role in consumers' purchase decisions. This paper examines a fundamental issue concerning online consumer review, i.e., the functions such reviews have for an online marketer. We argue that online consumer reviews, a type of product information created by users based on personal usage experience, can serve as a new element of marketing communications mix and work as free sales assistants to help consumers identify the products that best match their idiosyncratic usage conditions. For many products, this marketing function is impossible or very costly for traditional marketing communications to achieve. However, this new communication mode does not come without cost because it eliminates a seller's control over the content of product information accessible to consumers, and because consumer reviews may not be fully informative.We examine four specific strategic issues: (1) when an online seller should provide consumer reviews to its customers, (2) how a seller's decision to supply consumer reviews interacts with its product assortment strategy, (3) how the seller's strategy regarding the supply of consumer reviews interacts with its traditional marketing communication strategy, and (4) what timing is best for the seller to offer consumer review information for a product.Our results show that supplying online consumer reviews can benefit or hurt an online seller depending on product characteristics, the informativeness of the review, the seller's product assortment strategy, the seller's product value for the partially matched consumers, and consumer heterogeneity in product consumption expertise. We also show that the seller's decision to provide consumer reviews will increase its incentive to offer more complete product information to consumers through its traditional marketing communications. Finally, we discover that offering consumer review information too early leads to a lower profit.An empirical study based on data from online sellers in different product categories provides some preliminary support for our theory.
Behavioral pricing research has shown consumers to have lower and upper price thresholds, represented by an inverted U-shaped price acceptability function. We propose another basic reaction to price, namely, "lower price is better," represented by a decreasing acceptability function without a lower price threshold. A set of variables is hypothesized to predict consumer reaction to price. Price consciousness, price-quality relation, and product involvement are shown to influence the shape of the price acceptability function. A procedure and model to scale price acceptability and obtain acceptability functions are introduced and applied. The cumulative results suggest reliable acceptability scales along with evidence for convergent and construct validity. Copyright 2004 by the University of Chicago.
The issue of the sensitivity of weighted linear composites to attribute-importance weights has attracted researchers from various disciplines, including marketing, psychology, and statistics. At issue is how sensitive a weighted scale is to a particular choice of weights. Scale sensitivity is defined by a negative correlation between two scales. By considering the general case of "n" attributes and using an algebraic approach, the authors specify the precise sufficiency conditions under which two scales correlate negatively and thus be sensitive to the weights chosen. These sensitive conditions are derived in the context of the computation of an overall product-quality scale, which is simply a special case of the general multiattribute problem. They illustrate these conditions for the case of two quality scales using examples from "Test" (1983), a German magazine similar to "Consumer Reports," and from "Places Rated Almanac" (1987). Copyright 1992 by the University of Chicago.
This article develops a model of how customers with prior experiences and expectations assess service performance levels, overall service quality, and service value. The model is applied to residential customers' assessments of local telephone service. The model is estimated with a two-stage least squares procedure through survey data. Results indicate that residential customers' assessments of quality and value are primarily a function of disconfirmation arising from discrepancies between anticipated and perceived performance levels. However, perceived performance levels also were found to have an important direct effect on quality and value assessments. Copyright 1991 by the University of Chicago.
The cognitive tradeoff between price and product quality is used as a basis for hypothesizing interrelationships between two individual difference variables and two price-related responses. Results of a correlational study support the hypothesis of an inverse relationship between price consciousness and product involvement and the hypotheses that price consciousness and product involvement have opposite implications for several price-related constructs. Results also indicate a positive relationship between price acceptability level and the width of the latitude of price acceptance.
This paper examines the influence of advertising on how and what consumers learn from product experience. A hypothesis-testing framework is adopted where consumers treat advertisements as tentative hypotheses that can be tested through product experience. Two experiments were conducted using product categories that provided either ambiguous or unambiguous evidence about product quality. The first experiment showed that when consumers have access to unambiguous evidence, judgments of product quality are dependent only on the objective physical evidence and unaffected by advertising. However, advertising had dramatic effects on perceptions of quality when consumers saw ambiguous evidence; judgments and product inspection behavior protocols showed that advertising induced consumers to engage in confirmatory hypothesis testing and search. The second experiment showed that advertising influenced quality judgments by affecting the encoding of the physical evidence; retrieval of ad-consistent evidence also appeared to occur, though to a lesser degree.
Two experiments examined public and private responding in a multiple-audience context-a context in which members have varying opinions. I propose and find that posters (those communicating their experience to others) are influenced only by another's negative opinion because it triggers such social concerns as appearing indiscriminate. Consequently, they adjust their public attitudes downward. Self-presentational concerns appear to cause this negativity bias: lurkers (those not posting their opinion) were less affected by another's negative opinion. Furthermore, posters presented more than one side when publicly explaining their attitudes. These effects persisted despite posters' favorable product experiences and commitment to these attitudes. (c) 2005 by JOURNAL OF CONSUMER RESEARCH, Inc..
The author reports some empirical results on the strength of the quality-price relation. For many products, the relation between quality and price appears to be very weak; hence, for many products, higher prices appear to be poor signals of higher quality.
Four studies were conducted to assess the accuracy with which consumers perceive objective price-quality relationships. Results across four studies indicate that, overall, consumers perceive objective price-quality relationships with only a modest degree of accuracy. However, findings also suggest that the accuracy of consumers’ perceptions is moderated by product type; that is, price-quality perceptions are more accurate for nondurable products than for durable products. The authors conclude that consumers’ price-quality perceptions appear to be a function of general or product-type-specific schemas, rather than independent evaluations of price-quality relationships for individual product categories.
The authors investigate whether movement in a firm's stock price, that is, a measure of firm value, is associated with information contained in perceived quality measures. In a model that also allows for the effect of economywide factors and a firm's return on investment, they find a positive relationship between stock return and changes in quality perceptions. These results imply that the quality measure contains information, incremental to that reflected by current-term accounting measures, about future-term business performance. They suggest that managers should convey information to the stock market, such as the brand's quality image, useful in depicting the long-term prospects of the business. By doing so, the stock market will rely less on short-term measures of business performance, and managers will be freer to undertake strategies necessary for ensuring the long-term viability of their firms.
Many companies have been disappointed by a lack of results from their quality efforts. The financial benefits of quality, which had been assumed as a matter of faith in the “religion of quality,” are now being seriously questioned by cost-cutting executives, who cite the highly publicized financial failures of some companies prominent in the quality movement. In this increasingly results-oriented environment, managers must now justify their quality improvement efforts financially. The authors present the “return on quality” approach, which is based on the assumptions that (1) quality is an investment, (2) quality efforts must be financially accountable, (3) it is possible to spend too much on quality, and (4) not all quality expenditures are equally valid. The authors then provide a managerial framework that can be used to guide quality improvement efforts. This framework has several attractive features, including ensured managerial relevance and financial accountability.
As a company tries to find the factors accounting for strong and weak markets, typical consumer explanations for both tend to be in terms of the physical attributes of the product. Carling Brewing Company used a relatively inexpensive experiment to help dichotomize contributing influences as being either product or marketing oriented and, also, to indicate the magnitude of the marketing influence for various brands. The experiment involved the use of groups of beer drinkers that tasted (drank) and rated beer from nude bottles and from labeled bottles.
People often draw social inferences and render social judgments on the basis of relevant information they can recall from memory. Having known John for many years, we may unexpectedly be asked by an adoption agency whether he would make a good father. To decide, we may search our historical knowledge of John for evidence both consistent and inconsistent with our conception of a good father. Does John like children? Does he interact well with them? In answering such questions, we recall a sample of facts from the population of potentially recallable facts relevant to assessing John's fatherhood potential. Having recalled a sample of relevant facts, we use these, perhaps in some Bayesian weighting scheme, to decide whether or not John would be a good father.
Many companies have been disappointed by a lack of results from their quality efforts. The financial benefits of quality, which had been assumed as a matter of faith in the ''religion of quality,'' are now being seriously questioned by cost-cutting executives, who cite the highly publicized financial failures of some companies prominent in the quality movement. In this increasingly results-oriented environment, managers must now justify their quality improvement efforts financially. The authors present the ''return on quality'' approach, which is based on the assumptions that (1) quality is an investment, (2) quality efforts must be financially accountable, (3) it is possible to spend too much on quality, and (4) not all quality expenditures are equally valid. The authors then provide a managerial framework that can be used to guide quality improvement efforts. This framework has several attractive features, including ensured managerial relevance and financial accountability.
The authors document that approximately 5% of product reviews on a large private label retailer's website are submitted by customers with no record of ever purchasing the product they are reviewing. These reviews are significantly more negative than other reviews. They are also less likely to contain expressions describing the fit or feel of the items and more likely to contain linguistic cues associated with deception. More than 12, 000 of the firm's best customers have written reviews without confirmed transactions. On average, these customers have each made more than 150 purchases from the firm. This makes it unlikely that the reviews were written by the employees or agents of a competitor and suggests that deceptive reviews may not be limited to the strategic actions of firms. Instead, the phenomenon may be far more prevalent, extending to individual customers who have no financial incentive to influence product ratings.
The growth of the Internet has led to a dramatic increase in the number of consumer or “user” product ratings, which are posted online by individuals who have consumed a good, and are available to other individuals as they make decisions about which products to purchase. These ratings have the potential to substantially improve the match between products and consumers, however the extent to which they do so likely depends on whether the ratings reflect actual consumer experiences. This paper evaluates one potential source of bias in consumer ratings: mimicry of the reviews of experts. Using a rich dataset on consumer product ratings from the brewing industry and a regression discontinuity empirical framework, I show that expert reviews influence consumer ratings. Consumer ratings fall in response to negative expert reviews and increase in response to positive expert reviews. The results are most pronounced for strongly negative or strongly positive expert reviews. This mimicry limits the extent to which information on product quality from actual consumer experiences diffuses to the population. I suggest that “nudges” could be implemented to limit the extent to which mimicry affects ratings.
Online chatter, or user-generated content, constitutes an excellent emerging source for marketers to mine meaning at a high temporal frequency. This article posits that this meaning consists of extracting the key latent dimensions of consumer satisfaction with quality and ascertaining the valence, labels, validity, importance, dynamics, and heterogeneity of those dimensions. The authors propose a unified framework for this purpose using unsupervised latent Dirichlet allocation. The sample of user-generated content consists of rich data on product reviews across 15 firms in five markets over four years. The results suggest that a few dimensions with good face validity and external validity are enough to capture quality. Dynamic analysis enables marketers to track dimensions) importance over time and allows for dynamic mapping of competitive brand positions on those dimensions over time. For vertically differentiated markets (e.g., mobile phones, computers), objective dimensions dominate and are similar across markets, heterogeneity is low across dimensions, and stability is high over time. For horizontally differentiated markets (e.g., shoes, toys), subjective dimensions dominate but vary across markets, heterogeneity is high across dimensions, and stability is low over time.
As a company tries to find the factors accounting for strong and weak markets, typical consumer explanations for both tend to be in terms of the physical attributes of the product. Carling Brewing Company used a relatively inexpensive experiment to help dichotomize contributing influences as being either product or marketing oriented and, also, to indicate the magnitude of the marketing influence for various brands. The experiment involved the use of groups of beer drinkers that tasted (drank) and rated beer from nude bottles and from labeled bottles.
Four studies were conducted to assess the accuracy with which consumers perceive objective price-quality relationships. Results across four studies indicate that, overall, consumers perceive objective price-quality relationships with only a modest degree of accuracy. However, findings also suggest that the accuracy of consumers' perceptions is moderated by product type; that is, price-quality perceptions are more accurate for nondurable products than for durable products. The authors conclude that consumers' price-quality perceptions appear to be a function of general or product-type-specific schemas, rather than independent evaluations of price-quality relationships for individual product categories.
The original idea for this handbook of attitude and personality measures came from Robert Lane, a political scientist at Yale University. Like most social scientists, Lane found it difficult to keep up with the proliferation of social attitude measures. In the summer of 1958, he attempted to pull together a broad range of scales that would be of interest to researchers in the field of political behavior. Subsequently, this work was continued and expanded at the Survey Research Center of the University of Michigan under the general direction of Philip Converse, with support from a grant by the National Institute of Mental Health. The result was a three-volume series, the most popular of which was the last, Measures of Social Psychological Attitudes. That is the focus of our first update of the original volumes. Readers will note several differences between this work and its predecessors. Most important, we have given responsibility for each topic to experienced and well-known researchers in each field rather than choosing and evaluating items by ourselves. These experts were also limited to identifying the 10 or 20 most interesting or promising measures in their area, rather than covering all available instruments. This new structure has resulted in more knowledgeable review essays, but at the expense of less standardized evaluations of individual instruments. There are many reasons for creating a volume such as this. Attitude and personality measures are likely to appear under thousands of book titles, in dozens of social science journals, in seldom circulated dissertations, and in the catalogues of commercial pub-lishers, as well as in undisturbed piles of manuscripts in the offices of social scientists. This is a rather inefficient grapevine for the interested researcher. Too few scholars stay in the same area of study on a continuing basis for several years, so it is difficult to keep up with all of the empirical literature and instruments available. Often, the interdisciplinary investigator is interested in the relation of some new variable, which has come to attention casually, to a favorite area of interest. The job of combing the literature to pick a proper instrument consumes needless hours and often ends in a frustrating decision to forego measuring that characteristic, or worse, it results in a rapid and incomplete attempt to devise a new measure. Our search of ihe literature has revealed unfortunate replications of previous discoveries as well as lack of attention to better research done in a particular area. The search procedure used by our authors included thorough reviews of Psychologi-cal Abstracts as well as the most likely periodical sources of psychological instruments (e.g., Journal of Personality and Social Psychology, Journal of Personality Assessment, Journal of Social Psychology, Personality and Social Psychology Bulletin, Child Devel-opment, and the Journal of Applied Psychology) and sociological and political measures (Social Psychology Quarterly, American Sociological Review, Public Opinion Quarterly, and American Political Science Review). Doctoral dissertations were searched by examin-ing back issues of Dissertation Abstracts. Personal contact with the large variety of empirical research done by colleagues widened the search, as did conversations with researchers at annual meetings of the American Sociological Association and the Ameri-can Psychological Association, among others. Papers presented at these meetings also served to bring a number of new instruments to our attention. Our focus in this volume is on attitude and personality scales (i.e., series of items with homogeneous content), scales that are useful in survey or personality research set-tings as well as in laboratory situations. We have not attempted the larger and perhaps hopeless task of compiling single attitude items, except for ones that have been used in large-scale studies of satisfaction and happiness (see Chapter 3). While these often tap important variables in surveys and experiments, a complete compilation of them (even for happiness) is beyond our means. Although we have attempted to be as thorough as possible in our search, we make no claim that this volume contains every important scale pertaining to our chapter headings. We do feel, however, that our chapter authors have identified most of the high quality instruments.
The authors investigate whether movement in a firm's stock price, that is, a measure of firm value, is associated with information contained in perceived quality measures. In a model that also allows for the effect of economywide factors and a firm's return on investment, they find a positive relationship between stock return and changes in quality perceptions. These results imply that the quality measure contains information, incremental to that reflected by current-term accounting measures, about future-term business performance. They suggest that managers should convey information to the stock market, such as the brand's quality image, useful in depicting the long-term prospects of the business. By doing so, the stock market will rely less on short-term measures of business performance, and managers will be freer to undertake strategies necessary for ensuring the long-term viability of their firms.
The author reports some empirical results on the strength of the quality-price relation. For many products, the relation between quality and price appears to be very weak; hence, for many products, higher prices appear to be poor signals of higher quality.
The authors integrate previous research that has investigated experimentally the influence of price, brand name, and/or store name on buyers' evaluations of prod¬uct quality. The meta-analysis suggests that, for consumer products, the relation¬ships between price and perceived quality and between brand name and perceived quality are positive and statistically significant. However, the positive effect of store name on perceived quality is small and not statistically significant. Further, the type of experimental design and the strength of the price manipulation are shown to significantly influence the observed effect of price on perceived quality.
Proper linear models are those in which predictor variables are given weights such that the resulting linear composite optimally predicts some criterion of interest; examples of proper linear models are standard regression analysis, discriminant function analysis, and ridge regression analysis. Research summarized in P. Meehl's (1954) book on clinical vs statistical prediction and research stimulated in part by that book indicate that when a numerical criterion variable (e.g., graduate GPA) is to be predicted from numerical predictor variables, proper linear models outperform clinical intuition. Improper linear models are those in which the weights of the predictor variables are obtained by some nonoptimal method. The present article presents evidence that even such improper linear models are superior to clinical intuition when predicting a numerical criterion from numerical predictors. In fact, unit (i.e., equal) weighting is quite robust for making such predictions. The application of unit weights to decide what bullet the Denver Police Department should use is described; some technical, psychological, and ethical resistances to using linear models in making social decisions are considered; and arguments that could weaken these resistances are presented. (50 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
This study explores the relationship between price and reliability in the used car market. Some of the measurement concerns, expressed by others in price-quality studies of new products, are absent because of the choice of the secondary data sources from which the relationships were derived. The finding that depreciation is independent of reliability performance raises a number of public policy issues regarding the information efficiency of the used car market.
Do online consumer reviews affect restaurant demand? I investigate this question using a novel dataset combining reviews from the website Yelp.com and restaurant data from the Washington State Department of Revenue. Because Yelp prominently displays a restaurant's rounded average rating, I can identify the causal impact of Yelp ratings on demand with a regression discontinuity framework that exploits Yelp’s rounding thresholds. I present three findings about the impact of consumer reviews on the restaurant industry: (1) a one-star increase in Yelp rating leads to a 5% to 9% increase in revenue, (2) this effect is driven by independent restaurants; ratings do not affect restaurants with chain affiliation, and (3) chain restaurants have declined in market share as Yelp penetration has increased. This suggests that online consumer reviews substitute for more traditional forms of reputation. I then test whether consumers use these reviews in a way that is consistent with standard learning models. I present two additional findings: (4) consumers do not use all available information and are more responsive to quality changes that are more visible and (5) consumers respond more strongly when a rating contains more information. Consumer response to a restaurant’s average rating is affected by the number of reviews and whether the reviewers are certified as “elite” by Yelp, but is unaffected by the size of the reviewers’ Yelp friends network.
The Theory of Industrial Organization is the first primary text to treat the new industrial organization at the advanced-undergraduate and graduate level. Rigorously analytical and filled with exercises coded to indicate level of difficulty, it provides a unified and modern treatment of the field with accessible models that are simplified to highlight robust economic ideas while working at an intuitive level. To aid students at different levels, each chapter is divided into a main text and supplementary section containing more advanced material. Each chapter opens with elementary models and builds on this base to incorporate current research in a coherent synthesis. Tirole begins with a background discussion of the theory of the firm. In part I he develops the modern theory of monopoly, addressing single product and multi product pricing, static and intertemporal price discrimination, quality choice, reputation, and vertical restraints. In part II, Tirole takes up strategic interaction between firms, starting with a novel treatment of the Bertrand-Cournot interdependent pricing problem. He studies how capacity constraints, repeated interaction, product positioning, advertising, and asymmetric information affect competition or tacit collusion. He then develops topics having to do with long term competition, including barriers to entry, contestability, exit, and research and development. He concludes with a "game theory user's manual" and a section of review exercises.
We examine the relationship between objective and perceived quality for 241 products in 46 product categories over a period of 12 years. On average, we find that the effect of a change in objective quality is not fully reflected in customer perceptions of quality until after about six years. In the first year after a quality change, only about 20% of the total effect over time is realized. These effects are significantly larger and quicker for a decrease in quality relative to an equivalent increase. Interestingly, we also find that brand reputation has a “double” advantage. High-reputation brands are rewarded three years quicker for an increase in quality and punished one year slower for a decrease in quality compared to low-reputation brands. These differences in response time are a meaningful measure of brand equity. Finally, we examine the differences in quality effects across several product- and category-specific variables and discuss the implications of our findings.
This paper investigates when the reported average of online ratings matches the perceived average assessment of the population as a whole, including the average assessments of both raters and non-raters. We apply behavioral theory to capture intentions in rating online movie reviews in two dissimilar countries – China and the United States. We argue that consumers’ rating behaviors are affected by cultural influences and that they are influenced in predictable ways. Based on data collected from IMDB.com and Douban.com, we found significant differences across raters from these two different cultures. Additionally, we examined how cultural elements influence rating behavior for a hybrid culture – Singapore. To study whether online consumer reviews are subjected to under-reporting bias, which is, consumers with extreme opinions are more likely to report their opinions than consumers with moderate reviews causing online reviews to be a biased estimator of a product’s true quality, we compare the consumer reviews posted online with those from an experimental study. Our results shows that under-reporting is more prevalent among US online network, thus online reviews are a better movie perceived quality proxy in China and Singapore than in the US.
This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness,
which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process
B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a
class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical
prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead
to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could
improve judgements and decisions in situations of uncertainty.
Economic literature contains several sometimes contradictory hypotheses concerning the relationships among quality, price, and advertising. We investigate the impact of published quality ratings on these relationships and find that quality and advertising are much more likely to be positively related in the presence of quality ratings.
We show how motivation affects reasoning through reliance on a biased set of cognitive processes. We manipulate the level of brand preference experimentally and expose subjects to a message that is either consistent or inconsistent with their manipulated preference. Further, the message contains either strong or weak arguments. In two experiments, we find that preference-inconsistent information is processed more systematically and is counter argued more than preference-consistent information. In addition, experiment 2 shows that strong arguments are more persuasive than weak arguments in the preference-inconsistent condition. We employ the heuristic-systematic model of persuasion and its sufficiency principle as a framework to understand the psychological mechanism that underlies the biased processing of preference-inconsistent information. Copyright 2000 by the University of Chicago.
Past research suggests that marketing communications create expectations that influence the way consumers subsequently learn from their product experiences. Since postexperience information can also be important and is widespread for established goods and services, it is appropriate to ask about the cognitive effects of these efforts. The postexperience advertising situation is conceptualized here as an instant source-forgetting problem where the language and imagery from the recently presented advertising become confused with consumers' own experiential memories. It is suggested that, through a reconstructive memory process, this advertising information affects how and what consumers remember. Consumers may come to believe that their past product experience had been as suggested by the advertising. Over time this postexperience advertising information can become incorporated into the brand schema and influence future product decisions. Copyright 1999 by the University of Chicago.
In theories and studies of persuasion, people's personal knowledge about persuasion agents' goals and tactics, and about how to skillfully cope with these, has been ignored. We present a model of how people develop and use persuasion knowledge to cope with persuasion attempts. We discuss what the model implies about how consumers use marketers' advertising and selling attempts to refine their product attitudes and attitudes toward the marketers themselves. We also explain how this model relates to prior research on consumer behavior and persuasion and what it suggests about the future conduct of consumer research. Copyright 1994 by the University of Chicago.
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.