How much is too much? The nonlinear link between emotional arousal and review helpfulness

2023 | Decision Support Systems | Citations: 0

Authors: Chou, Yen-Chun

Abstract: Online reviews affect consumer purchase decisions and become prevalent in differ ... Expand

Abstract: Online reviews affect consumer purchase decisions and become prevalent in different sectors. Platforms elicit useful reviews by allowing consumers to vote for helpfulness. The link between review features and review helpfulness hence has been a topic of broad interest in information systems (IS) and Internet commerce. Psy­ chological science studies show that expressed emotions in information – valence and arousal significantly in­ fluence receivers’ engagement and valuation. Unlike valence (negative or positive) that is widely-analyzed, emotional arousal is a less-studied attribute of online reviews. This study presents a careful account of the nonlinear link between emotional arousal and review helpfulness. Following a rigorous procedure of theorizing and testing nonlinear relationships (Haans et al. 2016), we articulate latent mechanisms leading to an inverted Ushaped association and how valence would moderate the nonlinear effect of review arousal. We analyze reviews on experience goods from Yelp.com and find firm support for our hypotheses. The findings are triangulated using reviews on search goods from Amazon.com. While the nonlinear effect of review arousal and interactions with review valence are robust to both types of goods, an alternative moderation path of review valence on the inverted U-shaped relationship is observed. Our empirical study contributes to the literature by shedding lights on the dynamics among arousal, valence, review helpfulness, and product types, which illustrates a prototypical example to IS/e-commerce scholars on rigorously conceptualizing and estimating U-shaped links as well as their moderations. Collapse

Topics: tablet experience good online review user-generated content electronic commerce

Methods: theory development product review triangulation sentiment analysis reference modelling

When Images Backfire: The Effect of Customer-Generated Images on Product Rating Dynamics

2023 | Information Systems Research | Citations: 0

Authors: Guan, Yue; Tan, Yong; Wei, Qiang; Chen, Guoqing

Abstract: Customer-generated images (CGIs) on e-commerce platforms have been widely adopte ... Expand

Abstract: Customer-generated images (CGIs) on e-commerce platforms have been widely adopted as a promotional tool to persuade customers into purchases. Despite their prevalent applications, the effect of CGIs on customer postpurchase satisfaction has not been extensively examined. This study postulates that CGIs could cause expectation disconfirmation and reduce product uncertainty for customers, therefore making their effect on subsequent product ratings complex. We leverage multiple methods and data sets to gain a better understanding of this problem and underlying mechanisms. We employ a difference-in-differences model to empirically test our hypotheses and find that CGIs lead to a decline in subsequent ratings compared with product ratings not exposed to CGIs. Further heterogeneity analyses demonstrate that high CGI review rating and high aesthetic quality exacerbate the negative effect, whereas reviewer face disclosure could alleviate the negative effect. Through cross-product analyses, we find that the negative effect is more prominent for experience goods (e.g., women’s dresses) than for search goods (e.g., lightning cables). Finally, the underlying mechanism is further validated through a laboratory experiment that shows participants experience significantly higher expectation and more negative disconfirmation in the CGI group with high review ratings, whereas uncertainty reduction effect is insignificant, which collectively explains the decline of subsequent product ratings. These findings suggest that platforms and retailers should be aware of the potential negative effect of CGIs on the rating dynamics and take appropriate measures to circumvent it. History: Ravi Bapna, Senior Editor; Gordon Burtch, Associate Editor. Funding: This work was supported in part by National Science Foundation of China [Grants 72202220, 72172070, and 71729001]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2023.1201. Collapse

Topics: online review experience good electronic commerce data breach digital good

Methods: experiment experimental group laboratory experiment computational algorithm product review

Trust antecedents in online reviews across national cultures

2023 | Decision Support Systems | Citations: 0

Authors: Kim, Youngeui; Srite, Mark; Zhao, Huimin

Abstract: When reading an online review, consumers rely on implied trust-building factors ... Expand

Abstract: When reading an online review, consumers rely on implied trust-building factors within it. Trust antecedents have been extensively researched and categorized into argument quality and source credibility. However, there is still a need to investigate how their help for consumers differs across national cultures. Furthermore, while a profile photo has been found to enhance the helpfulness of a review by improving source credibility, little is known about how consumers perceive user appearance in a review picture and no research has compared these two types of visual information. To bridge these gaps, we examine how trust antecedents and visual information help consumers’ decision making differently across national cultures, using reviews collected from Amazon in the US and Germany, respectively. Our results show that information quality is more helpful for consumers in an individualistic and low uncertainty avoidance culture, whereas source credibility is more valued in the opposite culture. Interestingly, the effects of the two types of visual information, user appearance in a profile photo versus in a review picture, also differ across cultures. This research contributes to the online review literature by introducing visual information and national culture with new perspectives of trust. Our findings suggest that multinational e-commerce businesses adopt culture-specific strategies in review systems to better help consumers make informed purchase decisions. Collapse

Topics: national culture online review Vine data quality information retrieval

Methods: robustness check topic model term frequency–inverse document frequency propensity score method natural language processing

Investigating usefulness configurations of online consumer reviews: A Fuzzy-Set Qualitative Comparative Analysis

2023 | HICSS | Citations: 0

Authors: Kwon, B.; Jahng, J.

Abstract: Online reviews have a significant impact on consumers' purchasing decisions. Ma ... Expand

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

Topics: online review experience good user-generated content mobile phone video game

Methods: conceptual modelling computational algorithm regression analysis method theoretical contribution qualitative content analysis

Theories: complexity theory dual-system theory

The Role of Sentiment Tendency in Affecting Review Helpfulness for Durable Products: Nonlinearity and Complementarity

2023 | Information Systems Frontiers | Citations: 0

Authors: Li, Jin; Zhang, Yulan; Li, Jianping; Du, Jiangze

Abstract: The online review has become an important pillar in the decision-making process ... Expand

Abstract: The online review has become an important pillar in the decision-making process for purchasing experience products, especially durable goods with relatively high prices. Using a rich data set for automobiles, we quantify the sentiment tendency expressed in textual reviews, and empirically examine the nonlinearly inverted U-shaped relationship between customer satisfaction and sentiment tendency. We then investigate the nonlinear influences of review sentiment and depth on helpfulness. Furthermore, we study the relationship between numerical rating and text contents, i.e., sentiment tendency and review depth, in promoting the review helpfulness, and quantitatively identify the complementary effect of sentiment tendency. Our results indicate that both numerical ratings and sentiments expressed in text contents contribute to an increase in review helpfulness. Compared with polarized reviews, the neutral ones better benefit helpfulness and customer satisfaction. We also find that reviews with moderate depth are more helpful. Based on the empirical findings, we discuss several managerial implications for review system designers and consumers in the durable product market. Collapse

Topics: online review customer satisfaction experience good user-generated content website

Methods: sentiment analysis robustness check natural language processing descriptive statistic language model

Personalized Ranking at a Mobile App Distribution Platform

2023 | Information Systems Research | Citations: 0

Authors: Mao, Shengjun; Dewan, Sanjeev; Ho, Yi-Jen (Ian)

Abstract: The ease of customer data collection has enabled the widespread personalization ... Expand

Abstract: The ease of customer data collection has enabled the widespread personalization of content and services in digital platforms. We examine personalization in a hitherto unaddressed context: that of mobile app distribution. Specifically, we develop a comprehensive framework for the personalized ranking of app impressions, leveraging revealed preferences embedded in consumer clickstream data. To improve platform revenues, the framework jointly accounts for consumer utility and cost per action (CPA) margin, which is the revenue earned by the platform per app installation. To this end, we specify a structural model of click and installation choices, jointly estimated as a function of a comprehensive set of numerical (screen rank, quality, and popularity) and textual (titles, descriptions, and reviews) covariates. Our novel data set is at the granular user-impression level and uniquely includes app CPA margins paid to the platform. We conduct a series of policy experiments to quantify the value of personalization. Specifically, we show that a personalized hybrid margin and utility margin ranking scheme outperforms other personalized methods, including those based on utilities alone or a combination of utilities and margins. Overall, our analysis demonstrates how platforms can leverage routine consumer clickstream data to personalize the ranking of app impressions, thereby more effectively monetizing mobile app distribution.History: Param Singh, Senior Editor; Juan Feng, Associate Editor.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1156. Collapse

Topics: mobile application personalization usability search engine accounting

Methods: experiment mathematical model robustness check latent dirichlet allocation Markov chain Monte Carlo

Theories: utility theory

Text Performance on the Vine Stage? The Effect of Incentive on Product Review Text Quality

2023 | Information Systems Research | Citations: 0

Authors: Qiao, Dandan; Rui, Huaxia

Abstract: Incentivized reviews have become increasingly prevalent on product review sites ... Expand

Abstract: Incentivized reviews have become increasingly prevalent on product review sites such as Amazon. Whereas outright fake reviews are clearly unacceptable and should be removed from review platforms, reviews by incentivized consumers with otherwise authentic product experiences fall into a gray area. On the one hand, many critics and researchers have warned of their harm by pointing out their biased ratings. On the other hand, these reviews might complement organic reviews with review text of higher quality. The current paper studies whether incentivized reviews on Amazon are more coherent and offer richer detail. We use Amazon’s platform-incentivized reviews, known as Vine reviews, for our primary sample and use seller-incentivized reviews for checking robustness. Estimations from a two-way fixed-effect model consistently show that incentivized reviews do compensate for their reduced impartiality through better text quality, measured by discourse coherence and level of relevant detail. This finding is further supported by a randomized experiment using Amazon Mechanical Turk. Hence, current literature findings on the poor quality of text of incentivized reviews, based on review length and lexical complexity, portray only an incomplete picture of incentivized reviews. Given that numerical ratings for products via incentivized reviews are likely biased whereas their text content is of high quality, a natural way to embrace incentivized reviews is to keep their text content, suppress their numerical ratings, and always highlight the label of “incentivized reviews.”History: Juan Feng, Senior Editor; Jianqing Chen, Associate Editor.Funding: This work was supported by Singapore Ministry of Education Tier 1 Research Grant [Grant A-0008174-00-00].Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1146. Collapse

Topics: Vine experience good online review DVD video game

Methods: experiment qualitativ observational study product review experimental group robustness check

How product review voting is influenced by existing votes, consumer involvement, review valence, and review diagnosticity

2023 | Decision Support Systems | Citations: 0

Authors: Tseng, Shih-Lun; Lu, Shuya; Weathers, Danny; Grover, Varun

Abstract: Websites that allow consumers to post online reviews often allow others to signa ... Expand

Abstract: Websites that allow consumers to post online reviews often allow others to signal the value of the reviews by voting for them as being helpful (i.e., an upvote) or unhelpful (i.e., a downvote). Although a review's content should drive votes, herd behavior may also be operative if consumers discount their own judgments of the review based on signals others provide. Using a field study of online product reviews from Amazon, a longitudinal experiment, and two cross-sectional experiments, we find evidence for herd behavior: consumers' voting de­ cisions and intentions are influenced by others' votes. However, this effect is complex with multiple moderating factors, including consumer involvement, review valence, and review diagnosticity. We discuss the theoretical and practical implications of these findings for reducing the potential negative effects of herd behavior in the context of online reviews. Collapse

Topics: online review Reddit Twitter electronic commerce user-generated content

Methods: computational algorithm longitudinal research longitudinal experiment statistical hypothesis test parametric test

Theories: signaling theory

A Theory of Information Compression: When Judgments Are Costly

2023 | Information Systems Research | Citations: 0

Authors: Watson, Richard Thomas; Plangger, Kirk; Pitt, Leyland; Tiwana, Amrit

Abstract: A theory of information compression (TIC) conceptualizes how anticipated judgmen ... Expand

Abstract: A theory of information compression (TIC) conceptualizes how anticipated judgment costs can affect decision quality. We theorize—inductively from decision making in medicine, energy pricing, auditing, and financial analytics—how judgment networks can exacerbate financial and nonfinancial judgment costs that compress information. Information compression occurs when a process intended to inform decision making generates information that has little variation. This can reduce decision quality and market efficiency. We offer potential remedies to mitigate its adverse societal consequences. We use complementary theoretical perspectives to nomologically contextualize how information compression arises. We introduce an information compression measure based on information entropy. TIC’s theoretical crux is that the expansion of a judgment network’s publicness exacerbates information compression by increasing judgment costs for some entities in a judgment network. We close with future research ideas on TIC’s core propositions and its broader theoretical implications for information systems research. History: Yulin Fang, Senior Editor; Robert Gregory, Associate Editor. Collapse

Topics: social media societal evaluation criteria social influence price management decision making

Methods: theory development theoretical contribution econometric modeling

Theories: punctuated equilibrium theory agency theory technology acceptance model mathematical theory of communication theory of information

More than watching: An empirical and experimental examination on the impacts of live streaming user-generated video consumption

2023 | Information & Management | Citations: 0

Authors: Zhang, Yuan; Hua, Lei; Jiao, Yue; Zhang, Jie; Saini, Ritesh

Abstract: Live streaming user-generated video (UGV), a nascent format of crowdsourced cont ... Expand

Abstract: Live streaming user-generated video (UGV), a nascent format of crowdsourced content, has grown massive popularity among social media users and is believed to have substantial potential business influences. However, industry practitioners express concerns regarding this new form on social media platforms and the influences of live streaming UGV consumption lack research. Motivated such, through a uniquely merged dataset from the video game industry, we conduct a series of panel time-series empirical analyses to investigate the business value of live streaming UGV consumption. Further, we propose a conceptual framework based on the sense of com­ munity literature to understand the consequences of live streaming UGV consumption and verify it through several online experiments. This research contributes to the IS literature by shedding light on the influences of emergent crowdsourced content, providing a conceptual framework to existing literature, and offering rich managerial implications and guidelines to managers regarding utilizing live streaming UGVs. Collapse

Topics: video streaming service digital service marketing management organizational value crowdsourcing

Methods: experiment survey parametric test Student's t-test nonparametric test