How Review Quality and Source Credibility Interacts to Affect Review Usefulness: An Expansion of the Elaboration Likelihood Model

2023 | Information Systems Frontiers | Citations: 0

Authors: Aghakhani, Navid; Oh, Onook; Gregg, Dawn; Jain, Hemant

Abstract: This study extends our understanding of what makes an online review useful by ex ... Expand

Abstract: This study extends our understanding of what makes an online review useful by examining the effects of review quality (i.e., as a composite variable of review comprehensiveness and review topic consistency) on review usefulness, and the moderating effects of source credibility on the relationship between review quality and review usefulness. The Elaboration Likelihood Model, convergence theory, and cueing effect literature are used to define the variables of review comprehensiveness and review topic consistency. Analyses of 27,517 restaurant reviews from Yelp show that review topic consistency has a positive effect on review usefulness, but, contrary to our hypothesis, review comprehensiveness has a negative effect on review usefulness. We also found source credibility positively moderates the effect of review comprehensiveness on review usefulness, but negatively moderates the effect of review topic consistency on review usefulness. Theoretical and practical implications are discussed. Collapse

Topics: online review user-generated content Python website data breach

Methods: topic model term frequency–inverse document frequency NLTK statistical hypothesis test robustness check

Theories: elaboration likelihood model

Ambivalence as a Predictor of Online Review Helpfulness

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Akgul, Mehmet; MONTAZEMI, Ali Reza

Abstract: Online platforms, such as Yelp and TripAdvisor, have facilitated ubiquitous and ... Expand

Abstract: Online platforms, such as Yelp and TripAdvisor, have facilitated ubiquitous and convenient access to a large number of online reviews about almost any product/service. However, they impose an information load on the consumers due to their large number of reviews. The review star rating is practiced to ameliorate consumers' information load. A review star rating shows the reviewer's overall evaluation of a product/service. Nonetheless, the extant research findings about the relationship between star rating and review helpfulness are mixed. Star rating, being a unidimensional bipolar measure, is unable to correctly capture the underlying evaluations of the review content. Our contention in this research is that the use of review ambivalence is a better predictor of review helpfulness than the traditional star rating. To that end, we provide the theoretical foundation and pertinent methodology to assess our research question. KeywordsOnline review helpfulness, ambivalence, electronic word of mouth, eWoM Collapse

Topics: online word of mouth word of mouth

Methods: natural language processing sentiment analysis

Uniting Through Difference: Rich Cultural-Identity Expression as a Conduit to Inclusion

2023 | Organization Science | Citations: 0

Authors: Arnett, Rachel D.

Abstract: Although previous research suggests that bringing attention to minority cultural ... Expand

Abstract: Although previous research suggests that bringing attention to minority cultural identities in the workplace can lead to professional penalties, this research provides promising evidence that the opposite can occur. I examine how cultural minority employees engaging in rich and meaningful conversations about their racial, ethnic, and national backgrounds (referred to as rich cultural-identity expression) influences majority-group coworkers’ inclusive behaviors, such as majority-group employees’ willingness to socially integrate with and professionally support minority coworkers. Three experiments found evidence of majority-group employees behaving more—not less—inclusively toward minority coworkers who engaged in rich cultural-identity expression, as opposed to small talk that did not bring attention to a minority cultural background. Even when minority employees richly expressed negatively valenced cultural information that could provoke anxiety (such as issues with discrimination), this form of sharing had positive effects on most measures of inclusive behavior in Studies 2 and 3 (although one exception was found in Study 3). No benefits were observed when minority employees engaged in surface-level cultural-identity expression (Studies 2 and 3) and intimate, noncultural self-disclosure (Study 2). The power of rich cultural-identity expression is its ability to increase majority-group individuals’ status perceptions of, feelings of closeness to, and sense of learning potential from minority coworkers. This research provides promising evidence that minority employees may be able to express valued aspects of their cultural identities while gaining—as opposed to jeopardizing—inclusion. Funding: This work was supported by the Wharton Behavioral Laboratory and the Wharton Dean’s Research Fund. Supplemental Material: The e-companion is available at https://doi.org/10.1287/orsc.2022.1648. Collapse

Topics: electronic mail accounting identity management IT career pandemic

Methods: experiment survey ANOVA parametric test data transformation

Gratitude with Expectations: Exploring the Role of Restaurant Delivery and Food Availability on Online Customer Reviews During the COVID-19 Pandemic

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Avery, Atiya; Xu, Pei

Abstract: Online reviews have become a popular tool for understanding consumers' percepti ... Expand

Abstract: Online reviews have become a popular tool for understanding consumers' perceptions of service and product quality. The COVID-19 pandemic has significantly impacted the restaurant industry, including negative impacts on profitability. This study utilizes gratitude theory and expectation confirmation theory to investigate how food delivery and food desert status moderated the impact of the pandemic on consumers' perceptions of restaurant quality. We find that consumers still held expectations for restaurants despite the COVID-19 pandemic crisis and their lack of food availability. Our findings also highlight the importance of food accessibility and availability, particularly in underprivileged communities during a crisis. This study has broader implications for businesses operating during crisis events providing insights into how they can improve their service and product quality to meet the needs of their consumers. Collapse

Topics: pandemic service quality online review website geographic information system

Methods: product review robustness check

Theories: expectation confirmation theory

The Consequences of Rating Inflation on Platforms: Evidence from a Quasi-Experiment

2023 | Information Systems Research | Citations: 0

Authors: Aziz, Arslan; Li, Hui; Telang, Rahul

Abstract: Informative online ratings enable digital platforms to reduce the search cost fo ... Expand

Abstract: Informative online ratings enable digital platforms to reduce the search cost for buyers to find good sellers. However, rating inflation, a phenomenon in which average rating increases and rating variance across listings decreases, threatens the informativeness of ratings. We empirically identify the consequences of rating inflation by conducting a quasi-experiment with a digital platform that exogenously changed its rating display rule in a treated neighborhood, which resulted in rating inflation. Using a differences-in-differences approach, we find that platforms benefit from one aspect of rating inflation: user purchases and seller sales increase because of the increased average rating. However, they also face negative consequences: rating inflation causes a decrease in user trial and a greater concentration of sales among popular restaurants. Overall, our results illustrate the potential consequences of rating inflation that platforms need to consider when designing and managing their rating system.History: Xiaoquan (Michael) Zhang, Senior Editor; Gordon Burtch, Associate Editor.Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.1134. Collapse

Topics: digital platform mobile application word of mouth ease of use consumer behavior

Methods: experiment pilot experiment experimental group robustness check quasi experiment

A Theory-Driven Deep Learning Method for Voice Chat–Based Customer Response Prediction

2023 | Information Systems Research | Citations: 0

Authors: Chen, Gang; Xiao, Shuaiyong; Zhang, Chenghong; Zhao, Huimin

Abstract: As artificial intelligence and digitalization technologies are flourishing real- ... Expand

Abstract: As artificial intelligence and digitalization technologies are flourishing real-time, online interaction–based commercial modes, exploiting customers’ purchase intention implied in online interaction processes may foster huge business opportunities. In this study, we target the task of voice chat–based customer response prediction in an emerging online interaction–based commercial mode, the invite-online-and-experience-in-store mode. Prior research shows that satisfaction, which can be revealed by the discrepancy between prior expectation and actual experience, is a key factor to disentangle customers’ purchase intention, whereas black-box deep learning methods empirically promise us advantageous capabilities in dealing with complex voice data, for example, text and audio information incorporated in voice chat. To this end, we propose a theory-driven deep learning method that enables us to (1) learn customers’ personalized product preferences and dynamic satisfaction in the absence of their profile information, (2) model customers’ actual experiences based on multiview voice chat information in an interlaced way, and (3) enhance the customer response prediction performance of a black-box deep learning model with theory-driven dynamic satisfaction. Empirical evaluation results demonstrate the advantageous prediction performance of our proposed method over state-of-the-art deep learning alternatives. Investigation of cumulative satisfaction reveals the collaborative predictive roles of theory-driven dynamic satisfaction and deep representation features for customer response prediction. Explanatory analysis further renders insights into customers’ personalized preferences and dynamic satisfaction for key product attributes. History: Yong Tan, Senior Editor; Jingjing Zhang, Associate Editor. Funding: This work was supported in part by the National Natural Science Foundation of China [Grants 71971067 and 72271059] and the China Postdoctoral Science Foundation [Grant 2022M722394]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1196. Collapse

Topics: customer satisfaction willingness to pay decision making marketing information system customer service

Methods: deep learning experiment machine learning BERT theory development

The bright side of emotional extremity: Evidence from tipping in live streaming platform

2023 | Information & Management | Citations: 0

Authors: Chen, Xingyu; Ji, Li; Jiang, Ling; Huang, Justin T.

Abstract: Live streaming has enabled viewers to interact with broadcasters and peer viewer ... Expand

Abstract: Live streaming has enabled viewers to interact with broadcasters and peer viewers, as well as tip the broadcaster based on their emotional state. While most tips are small, a minority of viewers tip extremely large. To uncover such unique tipping patterns, we draw on the emotion literature and competitive arousal theory to examine how viewers’ emotional extremity affects tipping behavior and how broadcaster’s emotional response moderates the baseline effect. This study contributes to the emerging live streaming literature by revealing the differential effects of emotional extremity on tipping amount and frequency and provides practical implications for broad­ casters and platforms to steer tipping behavior. Collapse

Topics: live streaming platform marketing management accounting digital platform artificial intelligence

Methods: statistical hypothesis test computational algorithm psychometrics machine learning longitudinal research

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

The double-edged effects of data privacy practices on customer responses

2023 | International Journal of Information Management | Citations: 0

Authors: Chen, Shijiao (Joseph); Tran, Khai Trieu; Xia, Zhenhua (Raymond); Waseem, Donia; Zhang, Jing A.; Potdar, Balkrushna

Abstract: Requesting personal information in frontline service encounters raises privacy c ... Expand

Abstract: Requesting personal information in frontline service encounters raises privacy concerns among customers. The proximity contact tracing that occurred during the COVID-19 pandemic provides an intriguing context of in­ formation requests. Hospitality venues required contact tracing details from customers, and customer coopera­ tion varied with concerns about privacy. Drawing on gossip theory, we investigate the roles of businesses’ data privacy practices and government support in driving customers’ responses to contact tracing. Our findings show that perceived transparency of a business’s privacy practices has a positive effect on customers’ commitment to the business, while perceived control exerts a negative effect on commitment. These effects are mediated by customers’ information falsification rather than disclosure, because the former is a sensitive behavioral indicator of privacy concerns. The results also reveal the moderating roles of government support. This research con­ tributes to the customer data privacy literature by demonstrating the distinct effects of perceived transparency and control on commitment and revealing the underlying mechanism. Moreover, the research extends the conceptual understanding of privacy practices from online contexts to face-to-face contexts of frontline service. The findings offer implications for the management of customer data privacy. Collapse

Topics: privacy information privacy concern pandemic unintended consequence behavioral intention

Methods: qualitative interview survey conceptual modelling statistical hypothesis test structural equation modeling

Exploring Privacy Attitudes and Accurate Information Disclosure in Healthcare Contexts

2023 | International Conference on Information Systems | Citations: 0

Authors: Clark, Autumn; Keith, Mark; Masters, Tamara

Abstract: Patients lie to their doctors for a variety of reasons such as judgement, embar ... Expand

Abstract: Patients lie to their doctors for a variety of reasons such as judgement, embarrassment, and financial concerns. These reasons are different from consumer contexts where information disclosure risks include the loss of data to unknown third parties. Yet, the same theories are commonly used to frame both settings. This overextension of theory leads to important differences in the results of these studies. We propose that additional theorizing is needed to reconceptualize privacy calculus to more accurately explain healthcare patient disclosure. Using a hybrid methodology based on both a grounded theory approach and construal level theory, this study explores the perceived risks and benefits of health data and consumer data disclosure. The results reveal significant differences in psychological distance and construal levels between the two contexts which can improve future theorizing. This deeper understanding could help improve the accuracy of patient disclosure and reduce harm in clinical systems. Collapse

Topics: healthcare data mobile application data breach privacy mobile business

Methods: survey grounded theory qualitative coding theory development computational algorithm

Theories: privacy calculus theory construal level theory