Herding Behavior in Online Restaurant Ratings: Moderating Effects of Reviewer Popularity and Observed Review Volume

Understanding the generation of online reviews is fundamental work for retailers to better utilize them. Review rating is the most important component of an online review; therefore, our study tries to investigate the antecedents of online reviews by figuring out the relationship between a reviewer’s observed review rating and his/her rating. More specifically, this study aims to answer the following three research questions: (1) Does herding behavior exist in online ratings, i.e., is a reviewer’s rating affected by his/her observed ratings given by other reviewers? (2) Does the observed review number moderate the direct effect of observed review ratings on a reviewer’s rating behavior? (3) Does a reviewer’s popularity moderate the direct effect of observed review ratings on his/her rating behavior? To answer these research questions, we conduct multiple empirical analyses using online restaurant reviews obtained from the most popular review platform in China. The results show that herding behavior does exist in online rating behavior. To be more specific, a reviewer’s observed review rating while authoring reviews are positively related to his/her review rating; The observed review volume of the rated restaurant can mitigate the positive relationship between a reviewer’s observed review rating and his/her rating. A reviewer’s popularity can also mitigate the positive relationship between his/her observed review rating and his/her own rating. Our study makes contributions to both academic literature and managerial practice by demonstrating the presence of herding behavior in online review ratings. Our findings offer important implications for online review platform managers, product retailers, and consumers

Auxiliary field approach to effective potentials

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 1995.Includes bibliographical references (leaves 124-126).by Dapeng Xu.Ph.D

An Empirical Investigation of Culture’s Influence in Online Service Ratings: From the Perspective of Uncertainty Avoidance

In order to figure out the influence of consumers’ cultural background on their online review generation behavior, this study aims to investigate how consumers’ uncertainty avoidance values influence their online ratings. Utilizing data collected from a major travel review website, TripAdvisor, we find a negative relationship between uncertainty avoidance degree and online review rating. Consumers’ travel type and hotel star are found to have a moderating effect between consumers’ uncertainty avoidance and their online ratings. Moreover, the negative effect of uncertainty avoidance value on review rating is weaker for consumers on business travel, and this effect also decreases for upscale hotels. The results are further confirmed by a robustness check using another method. From a theoretical perspective, our study enriches existing literature dealing with online reviews. From a practical perspective, our research findings provide helpful insights to hotel practitioners

Travel and Online Review Behavior

Understanding the generation of online reviews is a fundamental issue for firms to gain benefits from online reviews. Our study tries to investigate the antecedents of online review characteristics by figuring out the following two research questions: (1) Will travel influence consumers’ post-consumption behavior (i.e., consumers’ review behavior)? And if so, (2) will consumers’ social capital moderate the influence of travel on consumers’ review behavior? The results show that consumers on travel tend to give higher review ratings and are more possible to post pictures while writing online reviews; consumers’ social capital level exacerbates the positive influence of travel on review ratings and mitigates the positive impact of travel on review richness

The Influence of “Likes” on User Content Generation in Online Investment Communities

Investors increasingly rely on investment advice in online investment communities (OICs). This study analyzes the influence of the “ likes” function on the content generation in OICs. Based on the data collected from Seeking Alpha, we perform a series of analyses from the perspectives of both authors and readers. From the angle of authors, we find that authors express the logic of the articles more seriously by increasing the use of negative words, and reducing the frequency of writing articles. The reader-level analyses show that “likes” and “comments” are complementary to each other, and readers do not reduce their “comments” after the introduction of the “likes” function. In general, the launch of the new function affects the content generated by both authors and readers. Our study can enrich the research on user-generated content (UGC) and provide helpful suggestions to OIC managers in motivating users to make feedbacks and contributions in such communities

SERVICE CATEGORY SYSTEM IN LOW-POWER AND LOSSY NETWORKS

Presented herein are novel techniques to resolve cache capacity issues in Low-Power and Lossy Networks (LLNs) by utilizing border router edge computing. Following deployment of a network, such as an information-centric networking (ICN) network, a border router will generate a bitmap for all support services through negotiations with a cloud service (CS) and low-power devices. The border router will then cache data that satisfies specific service criteria for low-power devices that have registered for such data. The border router will further publish the service bitmap to a sleep proxy. A given low-power device can periodically examine the service bitmap via beacons to determine whether there may be any service(s) in which it is interested and, if so, respond to the border router

A Meta-Analysis on the Determinants of Online Review Helpfulness

Online consumer reviews can help customers decrease uncertainty and risk faced in online shopping. However, information overload and conflicting comments in online reviews can get consumers confused. Therefore, it is important for both researchers and practitioners to understand the characteristics of helpful reviews. But studies examining the determinants of perceived review helpfulness produce mixed findings. We review extant research about the determinant factors of perceived helpfulness. Conflicting findings exist for six review related factors, namely review extremity, review readability, review total votes, linear review rating, quadratic review rating, and review sentiment. We conduct a meta-analysis to reconcile the contradictory findings on the influence of review related factors over perceived review helpfulness. The meta-analysis results confirm that review extremity, readability, total votes, and positive sentiment have a negative influence on helpfulness, but review rating is positively related to helpfulness. We also examine those studies whose findings are contradictive with the meta-analysis results. Measure discrepancy and reviewed product type are the two main reasons why mixed findings exist in extant research