A Study of Antecedents of Sense of Presence in Virtual World: Virtual Presence vs. Social Presence

Virtual World as an electronic artificial environment, enables users to have an identity while interacting with others is one of the new instances of Computer-Mediated Communications environment. Our study aims to elaborate the two types of presence in virtual world and their effects on users’ satisfaction and loyalty in second life. In addition we try to elaborate the factors that affect virtual and social presence. We used survey in order to collect data from a student sample frame. Our samples are students who at least have three weeks experience with second life in order to measure our model. Results of the research suggested that cognitive absorption positively influence virtual presence and sense of belonging positively influence social presence. In addition our results suggested that sense of presence in virtual world increase satisfaction and loyalty among virtual world users

A Study of the Effect of Privacy Assurance Mechanisms on Self-disclosure in Social Networking Sites from the View of Protection Motivation Theory

Because of the predominant and rampant of social networking sites (SNSs), users’ information privacy issue becomes an important challenge not only for SNS users but also for the SNS service providers and governing organizations. This study’s objectives are: (1) to study how assurance mechanisms affect SNS users’ self-disclosure intention by applying protection motivation theory (PMT), and (2) to empirically test the perceived privacy concern as part of the PMT in order to predict self-disclosure on SNS. There are a number of expected contributions for this study. First, this study applies PMT in order to understand how assurance mechanisms applied by SNSs affect users to disclose their personal information. Second, we introduce the customizing privacy as an assurance mechanism which has not been studied in previous literature. Finally, we consider fear component of PMT which has not been studied by previous researchers who applied PMT in this context

A Study of the Effect of Privacy Assurance Mechanisms on Self-disclosure in Social Networking Sites from the View of Protection Motivation Theory

Along with recent advancement of web technologies, social networking sites (SNSs) affect people’s life styles by enabling them to perform different activities which are not easy to do before. Predominant uses of SNSs allow users to quickly access and easily share personal information. In turn, users’ information privacy issues become important challenge. Drawing upon Protection Motivation Theory, this research investigates the effect of privacy assurance mechanisms (i.e., privacy assurance statements and privacy customization) on privacy concern and disclosure behavior. The results show that privacy assurance statements significantly influence SNS users’ privacy concern by affecting users’ assessment of threat susceptibility and effectiveness of assurance mechanisms; privacy customization features significantly influence users’ self-efficacy and perceived effectiveness of assurance mechanisms; SNS users’ privacy concern results form a risk calculus process in which users assess the threat and available coping mechanisms; and the effect of privacy concern on self-disclosure mediates by users’ protection motivation

Continued Usage and Location Disclosure of Location-Based Applications: A Necessity for Location Intelligence

Location-based applications (LBA) have been widely accepted and used for different purposes ranging from navigation to dating or gaming. Most LBAs ask users to provide access to location data for more efficient and personalized location-based services. Location intelligence as an emerging area of business intelligence relies heavily on disclosing location information by users. This research builds a continuance usage and location disclosure model from the expectation-confirmation perspective. The effect of benefit expectations on usefulness and satisfaction is hypothesized. In addition, the positive effect of usefulness on satisfaction and continuance intention is postulated. After collecting survey data from main LBA users, the results of the analysis support the proposed model. Findings contribute to the current literature in business intelligence by focusing on location disclosure behavior in the context of LBAs and the necessity of this type of information for location intelligence

Antecedents of Online Customers Reviews’ Helpfulness: A Support Vector Machine Approach

Online customer reviews (OCRs) have become an important part of online customers’ decision making and People use online reviews to make decision to buy or not to buy products and services. This study aims to answer two research questions: (1) what are the antecedents of helpfulness of online reviews based on their contents? (2) How do content-based cues on OCRs influence their helpfulness? We posit a research model to study the effect of peripheral and central cues in OCRs on online review helpfulness. Online review web pages will be collected from Amazon website using a web crawler. This article will be one of the first studies that investigate OCRs helpfulness based on the central cues in the text of the review. In addition, this research will be the first study that applied the support vector machine as a machine learning method to analyze the text of OCRs

A Recommender System for Online Consumer Reviews

Online consumer reviews have helped consumers to increase their knowledge about different products/services. While most previous studies try to provide general models that predict performance of online reviews, this study notes that different people look for different types of reviews. Hence, there is a need for developing a system that that is able to sort reviews differently for each user based on the ratings they previously assigned to other reviews. Using a design science approach, we address the above need by developing a recommender system that is able to predict the perceptions of each user regarding helpfulness of a specific review. In addition to addressing the sorting problem, this study also develops models that extract objective information from the text of online reviews including utilitarian cues, hedonic cues, product quality, service quality, price, and product comparison. Each of these characteristics may also be used for sorting and filtering online reviews

Dissonance Reduction Strategies in Ride-Sharing Apps- A Case of Uber

Ride-sharing apps have both positive and negative impact in our daily lives. To study the negative impacts especially personal safety issues, this study explores the reaction of ride-sharing app users to such safety issues. We contextualize our study using a scenario-based survey. We found empirical support to all the hypotheses by surveying 421 individuals. This study contributes to the information systems literature in providing ways to apply dissonance reduction techniques that are a strong predictor of satisfaction. In addition, this study also addresses the safety issues faced by riders using ride-sharing apps and how co- creation would help address these issues

A comparison of hedonic and utilitarian digital products based on consumer evaluation and technology frustration

This study explores how hedonic mobile applications (apps) compare to utilitarian apps in consumer evaluation. We posit that achieving a set of passionate consumers is a pre-cursor to product success in markets, whereas technology frustration is a negative hindrance to the product success. Also, we argue that technology frustration may act as a negative complementing factor to consumer passion, and this effect is higher for hedonic products than utilitarian products. We contextualize our study to the android apps, and used a dataset that tracked 19,121 apps in the android market for three months and coded our variables from this dataset. We conducted empirical analysis and found support for our hypotheses. This study contributes to the information systems and marketing literature in providing a new dimension associated with consumer evaluation of digital products, and draws evaluative comparisons between hedonic and utilitarian digital products

The Effect of Central and Peripheral Cues on Online Review Helpfulness: A Comparison between Functional and Expressive Products

Online customer reviews (OCR) have become an important part of online customers’ decision making. People also use OCR to get better understanding of the characteristics of the product and also learn about other customers’ experience with the product. Drawing upon Elaboration Likelihood Model, this research investigates the predictors of readership and helpfulness of OCR. Our findings show that longer reviews as well as those with extreme star ratings receive more readerships. Moreover, the amount of hedonic and utilitarian cues in a review and its sentiment significantly influence perceptions of online consumers regarding its helpfulness. We also show how product type moderates the effect of utilitarian and hedonic cues on helpfulness. We discuss the implications of our study and provide directions for future research

A Study of News Credibility and Trust on Social Media – A Multi-Cultural Evaluation

Information sharing is an important motivation for individuals to join social networking websites (SNSs). One source for the shared information are the posts that are shared in SNS. In this study, we propose a research model that represents antecedents of trust in posts in the SNS and the impact of culture. We plan to gather data from two countries- China and USA. We expect to find that content credibility and source credibility as antecedents of trust. In addition, we expect to find that involvement in the post moderates the effect of source credibility and content credibility on trust. Finally, we expect that source credibility and content credibility have the greatest impact on trust in the USA