The Effect of Online Customer Reviews on Product Sales and Prices – A Longitudinal Study

As e-commerce prospers, increasing interests are gained in online customer reviews and its application to the theory and practice. However, there are many controversies around the effect of the online customer reviews. This study will use a longitudinal analysis approach to find the impact of online customer reviews on the price strategy and the product sales, which will add more solid application of effective use of e-WOM to the theory and the practice

Custom-made: Information system for managing a restaurant chain

Sometimes there are some apprehensions when we talk about Information Systems (IS) in business, connected to restaurants, which have been categorized as something negative. The true problem is detected when the IS does not reveal to be the most adequate to the business in question. It is in this context that is referred the necessity of personalize a management information system (MIS) in this type of business. Preferably the users should be involved in the development process of a MIS. The main goal of this article is to model and sketch an IS in order to help the managers of the establishments of a restaurant chain in the current management and information control needed to the right function. In methodological terms, it was made a qualitative study in the form of an interview to the managers of the restaurants to define the necessary requisites to the next MIS. The purpose of this project is to develop and implement the MIS prototype during a master's study which will be improved in the future.info:eu-repo/semantics/acceptedVersio

Predicting online e-marketplace sales performances: a big data approach

To manage supply chain efficiently, e-business organizations need to understand their sales effectively. Previous research has shown that product review plays an important role in influencing sales performance, especially review volume and rating. However, limited attention has been paid to understand how other factors moderate the effect of product review on online sales. This study aims to confirm the importance of review volume and rating on improving sales performance, and further examine the moderating roles of product category, answered questions, discount and review usefulness in such relationships. By analyzing 2,939 records of data extracted from Amazon.com using a big data architecture, it is found that review volume and rating have stronger influence on sales rank for search product than for experience product. Also, review usefulness significantly moderates the effects of review volume and rating on product sales rank. In addition, the relationship between review volume and sales rank is significantly moderated by both answered questions and discount. However, answered questions and discount do not have significant moderation effect on the relationship between review rating and sales rank. The findings expand previous literature by confirming important interactions between customer review features and other factors, and the findings provide practical guidelines to manage e-businesses. This study also explains a big data architecture and illustrates the use of big data technologies in testing theoretical framework

Chinese Online Reviews for Tourism Attractions: An Affective Computing System based on Data Mining

Based on the excessive online reviews of tourism spot and related research status, this paper attempts to design an affective computing system to provide a comprehensive analysis of affective inclination toward multiple products/services in specific tourism spots, thus transforming complex and unstructured review texts into structured attitudinal information. The designing process consists of three parts: firstly, the author puts forward the framework of affective computing system of online tourism spot reviews based on modular design; secondly, build and modify a feature-oriented domain dictionary through association algorithm for feature mining; thirdly, conduct the mining of adverbs of degree, polarity and negative words grounded on the dependency under syntactic analysis; last of all, come up with the calculation method of online tourism spot reviews’ affective inclination, construct and display the basic affective computing system. Key words: tourism spot; online review; syntactic analysis; feature mining; affective computing

THE ROLE OF SOCIAL NETWORKS IN ONLINE REVIEWING

Online reviews are a dominant resource for consumer decisions but what leads users to write reviews remains largely unexamined. Extant research on user content generation has primarily focused on what motivates users to contribute content, and less on the effects of informational and social environment surrounding these users. The aim of this study is to examine how a user’s contribution to an online review platform is affected by reviews of his/her friends from both informational and social perspectives. We expect that information, reciprocity, and social comparison are primary drivers for contribution. Among friends who wrote reviews, we predict that those who carry redundant information have less effect on the focal user’ contribution, whereas those who are strong-tie friends of the focal user have a stronger effect. Furthermore, we expect that users’ status moderates these effects such that an elite user responds more positively to friends who carry redundant information, and more negatively to those who are strong-tie friends, compared to non-elite users. Our expected findings hold implications for online review platforms in terms of highlighting the most relevant reviews generated by one’s peer

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

Using Platform-Generated Content to Stimulate User-Generated Content

This work intends to study the implication of an editorial review program where a review platform starts to supplement the user-generated reviews on its website with editorial review articles that are written by the platform. Our research question is whether platform-generated content (i.e., editorial reviews) influence subsequent user- generated content (i.e., online reviews) both in terms of the quantity and quality of those reviews. We obtain the dataset through a partnership with a restaurant review platform in Asia. Our preliminary analysis suggests that platform-generated content has a positive net effect on subsequent user-generated content. Specifically, users post more reviews for restaurants that have editorial reviews and these reviews tend to be longer on average

What Doctors Wish They Knew: Treatment Compliance in an Online Health Community for Chronic Patients

Treatment compliance for patients with chronic health problems is important for the management of their illness due to the long-term nature of their conditions. In this study, we examine how evaluations of different types of treatments provided by members of an online health community are associated with treatment evaluations and compliance. We use self-reported data on evaluation and compliance of over 270 different treatments from over 20,000 patients in a prominent online health community. We find that other community members’ treatment evaluation valence is positively associated with patient treatment evaluation and treatment compliance. Similarly, other community members’ treatment compliance is positively associated with patient treatment compliance. We also find these relations are moderated by community size and ratings variance. We discuss the theoretical implications of these results for the online health communities’ literature, as well as the practical implications for patients, healthcare providers, and policy makers

THE INFLUENCE OF EWOM AND EDITOR INFORMATION ON INFORMATION USEFULNESS IN VIRTUAL COMMUNITY

Information Usefulness, eWOM Information, Editor Information, Sense of Belonging

How to Meet the Diverse Needs of Consumers: Big Data Mining based on Online Review

This article applied Word2vec and image mining on OCRs analysis. Data from Dianping.com showed that in Beijing, good taste is the primary factor for customers to choose a restaurant. Unlike the general opinion, careers and locations have little influence on cuisine choice in Beijing. Hot pot is the most popular one all over the city. Warm color, medium dark light and saturation with certain amount of grey are three key aspects for an enjoyable dining environment. Offline mouth to mouth recommendation is the most useful way to spread a restaurants reputation. So making the antecedent consumer satisfy is the most applied way to appeal new ones. This findings can help restaurant owners to run a better business and promote the satisfactory