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

Empirical Assessment of Big Data Technology Adoption Factors for Organizations with Data Storage Systems

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Alnafoosi, Ahmad; Steinbach, Theresa A.

Abstract: Many organizations have on-premises data storage systems that are evolving; amo ... Expand

Abstract: Many organizations have on-premises data storage systems that are evolving; among them is Big Data (BD). BD is a data storage system that can analyze large volumes, with velocity, and a variety of data. Per the Economist, data is now the most valuable resource. BD holds the promise of unlocking substantial parts. Many organizations want to implement BD but have not been able to. There is a need to identify key factors affecting adoptions for such organizations. The following factors are identified as (novel): data storage latency, ability to compute, data storage interface compatibilities, open-source software, and enterprisesourced software, or (under-studied): cost, perceived industry pressure, legislation barriers, and market turbulence. These factors were studied empirically with DOI and TOE by conducting a survey and performing quantitative PLS-SEM analysis. This analysis showed that these adoption factors are significant: data storage interface compatibility, open-source, enterprise-source software, cost, industry pressure, and market turbulence. Collapse

Topics: computer data storage decision support system legal context open source social media

Methods: survey partial least squares path modeling partial least squares regression PLS tool survey design

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

Nudging Towards Sustainable Delivery Options: First Insights From an Experimental Study

2023 | European Conference On Information Systems | Citations: 0

Authors: Brylla, Daniel; Walsh, Gianfranco

Abstract: As the e-commerce sector continues to grow, customers are increasingly concerne ... Expand

Abstract: As the e-commerce sector continues to grow, customers are increasingly concerned about the impact of their online orders on working conditions and the environment. In many cases though, online retailers emphasize delivery speed over sustainability and offer delivery options that put a strain on logistics workers and the environment. To promote the choice of more sustainable but slower delivery options, we present a model concerning how message frames affect delivery choice and customer outcomes (order completion, loyalty, word of mouth). An experimental study shows that simple message frames, regarding job conditions, the environment, and customer convenience, increase the choice of more sustainable, slower delivery options and customer outcomes indirectly via delivery choice, and warm glow feelings. Delivery fees dilute the impact of environmental message frames on delivery choice though. Overall, our findings suggest that nudging customers towards sustainable delivery options is possible, yielding positive effects for customers and retailers. Collapse

Topics: electronic commerce logistics management word of mouth website missing data

Methods: experiment theory development experimental design parametric test theoretical contribution

Understanding active participation of online dating services: A mixed methods study

2023 | Decision Support Systems | Citations: 0

Authors: Chen, Qi; Yun, Guobiao; Lu, Jiandong; Wang, Xiaolei

Abstract: Online dating has transformed the way people meet and start relationships. Howev ... Expand

Abstract: Online dating has transformed the way people meet and start relationships. However, online dating platforms typically have many lurkers without active participation. Using a self-regulation framework, this paper aims to study users’ active participation in online dating through a mixed methods study. We first conducted qualitative and quantitative investigations with a machine learning method to explore user active participation and its antecedents. We then developed a theoretical model and conducted a statistical analysis of the model. The empirical findings showed that service quality and trust significantly affected individual active participation in a dating site through attachments to the daters and services. The findings of the study contribute to the extant literature by analyzing user participation in online dating from an attachment perspective. Collapse

Topics: service quality online dating participatory design online dating service Python

Methods: design methodology mixed method qualitative coding machine learning machine learning method

Theories: attachment theory marketing theory

A Bitter Pill to Swallow? The Consequences of Patient Evaluation in Online Health Question-and-Answer Platforms

2023 | Information Systems Research | Citations: 0

Authors: Chen, Chen; Walker, Dylan

Abstract: Online health question-and-answer (Q&A) platforms (OHQPs), where patients post h ... Expand

Abstract: Online health question-and-answer (Q&A) platforms (OHQPs), where patients post health-related questions, evaluate advice from multiple doctors, and direct a bounty (monetary reward) to their most preferred answer, have become a prominent channel for patients to receive medical advice in China. To explore the quality of medical advice on these platforms, we analyzed data on patients’ evaluation of ∼497,000 answers to ∼114,000 questions on one of the most popular OHQPs, 120ask.com, over a three-month period. We assembled a panel of independent physicians and instructed them to evaluate the quality of ∼13,000 answers. We found that the quality of medical advice offered on the platform was high on average, and that low-quality answers were rare (6%). However, our results also indicate that patients lacked the ability to discriminate advice quality. They were as likely to choose the best answer as the worst. The medical accuracy of patient evaluation was worse in critical categories (cancer, internal medicine) and for vulnerable subpopulations (pediatrics). Given that millions of patients seek medical advice from OHQPs in China annually, the social and economic implications of this finding are troubling. To understand how patients evaluate advice, we trained deep neural networks to think like patients, allowing us to identify patients’ positive and negative responses to different heurist cues. Although our results indicate that OHQPs perform well, we identified several concerns that should be addressed through platform design and policy changes. Because the Q&A process lacks peer review mechanisms, signals of advice quality are not conveyed to patients, forcing them to rely on heuristic cues, which cannot effectively guide them toward the best advice. We also found that the platform reputation metric was not correlated with the quality of the advice giver’s advice, may effectively encourage patients to select lesser quality medical advice, and increased the risk of moral hazard for malicious players to intentionally provide less accurate but more agreeable advice for personal gain. Our analysis revealed bad actors on the platform, including drug promoters and spammers. Finally, we found that OHQPs exacerbated care avoidance. We discuss several potential policy changes to address these shortcomings. History: Param Singh, Senior Editor; Idris Adjerid, Associate Editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1158. Collapse

Topics: decision making local interpretable model agnostic explanation digital platform health information system pandemic

Methods: artificial neural network psychometrics survey deep learning natural language processing

Theories: lemon market theory

An Innovation Resistance Perspective on Seller Resistance to Digital Device Recycling Platforms

2023 | HICSS | Citations: 0

Authors: Chen, Leida; Tang, Zhenya

Abstract: Digital device recycling platforms (DDRP), popularized by the resale commerce (r ... Expand

Abstract: Digital device recycling platforms (DDRP), popularized by the resale commerce (reCommerce) movement, allows users to sell, trade-in, and recycle used digital devices online. Although DDRPs offer new opportunities for commerce and sustainability, challenges exist to usher in their wide adoption. This study aims to develop a deeper understanding of the reasons underlying seller resistance to the DDRP that is grounded in the innovation resistance theory (IRT). The research model of this study is validated using data collected from 307 potential sellers of used digital devices. Collapse

Topics: innovation management privacy word of mouth user resistance green IS

Methods: survey structural equation modeling factor analysis data transformation theoretical contribution

Significance of Visual Realism – Eeriness, Credibility, and Persuasiveness of Virtual Influencers

2023 | HICSS | Citations: 0

Authors: Cornelius, Samia; Leidner, Dorothy; Bina, Saman

Abstract: Though human-like design can increase favorable social behaviors like familiarit ... Expand

Abstract: Though human-like design can increase favorable social behaviors like familiarity and acceptance, it can also question the technology’s effectiveness, rationality, and functionality. With capabilities that allow technology to become more and more human-like, researchers and practitioners continue to delve over the efficacy and deployment of humanness in design. In this research paper, we measure positive and negative perceptions towards different levels of humanness among an emerging form of digital character: the virtual influencer. In doing so, we assess the efficacy of human-like design among virtual influencers by manipulating their visual realism and measuring the effect of this manipulation on their credibility and persuasiveness. Our experimental design also allows us to explore the existence of the uncanny valley in a novel technological context. Collapse

Topics: Instagram social media digital media logistics management word of mouth

Methods: experiment Wald test parametric test logistic regression binomial logistic regression

Theories: uncanny valley theory

The “holiday effect” in consumer satisfaction: Evidence from review ratings

2023 | Information & Management | Citations: 0

Authors: Deng, Lingfei; Ye, Qiang; Xu, DaPeng; Sun, Fangfang

Abstract: This study explores whether and how a holiday effect exists in consumers’ review ... Expand

Abstract: This study explores whether and how a holiday effect exists in consumers’ review rating behavior, which is well explained by expectancy-disconfirmation theory (EDT). After utilizing the secondary data of online restaurant reviews and conducting an online experiment, we find that consumers have the tendency to form high expec­ tations before holidays, thus leading to more negative disconfirmation and bad moods, which finally induce their negative review rating behavior on holidays. The consumer heterogeneity analyses provide evidence that con­ sumers who are tourists, tourists with less travel experience, and male natives are more likely to post lower review ratings on holidays. Collapse

Topics: online review service quality user-generated content consumer behavior website

Methods: experiment experimental group regression analysis method product review survey