A meta-analysis of online trust : examining main and moderating effects

textThe purpose of this study was (1) to conduct a meta-analysis on the antecedents and consequences of online trust; (2) to test for seven moderating variables involving online trust; and (3) to use the pooled correlation matrix to fit the research model. The data for the meta-analytic procedure involved 120 papers reporting 150 independent studies. Results showed statistically significant relationships involving online trust and its various antecedents (e.g., perceived security) and consequences (e.g., behavioral intention). The relationships were heterogeneous across studies and the variances for the reported effect sizes were partially explained by certain methodological characteristics. The meta-analytic structural equation modeling analysis indicated that online trust mediates the effect of various antecedents on behavioral intention. A discussion of results, implications, limitations, and future research is provided.Informatio

A Meta-Analysis of Construct Reliability Indices and Measurement Model Fit Metrics???

The present research examined the distributional properties of construct reliability indices and model fit metrics, explored relationships between and among the indices and metrics, and investigated variables influencing the relative magnitudes of the indices and metrics in structural equation measurement models. A broad-based meta-analysis of reported construct reliability indices and selected model fit metrics revealed modest relationships among reliability indices, minimal relationships among model fit metrics, and a virtual absence of relationships between reliability indices and model fit metrics. Differences in magnitudes of selected reliability indices and model fit metrics were found to primarily be a function of the (total) number of items employed in a measurement model. The implications of the findings suggest that the current practice of indiscriminately computing and reporting of reliability indices and model fit metrics based only on arbitrary heuristics should be abolished and replaced by theoretically justified indices and metrics. ?? This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License, CC BY 4.0, which permits unrestricted use, distribution, and reproduction, provided the original work is properly cited

Count models : with applications to price plans in mobile telecommunication industry

textThis research assesses the performance of over-dispersed Poisson regression model and negative binomial model with count data. It examines the association between price plan features of mobile phone services and the number of people who adopt the plan. Mobile service data is used to estimate the model with a sample of one million customers running from February 2006 to September 2009. Under three main categories, customer type, age, and handset price, we run the model based on price plan features. Estimates are derived from the maximum likelihood estimation (MLE) method. Root mean squared error (RMSE) is used to observe the statistical fits of all the regression models. Then, we construct four estimation and holdout samples, leaving out one, three, six, and twelve months. The estimation constitutes the in-sample (IS) and the holdout represents the out-sample (OS). By estimating the IS, we predict the OS. Root mean squared error of prediction (RMSEP) is checked to see how accurate the prediction is. Results generally suggest that academic year start (AYS), seasonality, duration of months since launch of price plan (DMLP), basic fees, rate with no discount (RND), free call minutes (FCM), free data (FD), free text messaging (FTM), free perk rating (FPR), and handset support all show significant effect. The significance occurs depending on the segment. The RMSE and RMSEP show that the over-dispersed Poisson model outperforms the negative binomial model. Further implications and limitations of the results are discussed.Mathematic

A Meta-analysis of Online Trust Relationships in E-commerce

A meta-analysis examined the role of online trust in business-to-consumer e-commerce. The analysis of 16 pairwise relationships derived from 150 empirical studies involving online trust revealed that online trust exhibits significant relationships with selected antecedents (e.g., perceived privacy, perceived service quality) and consequences (e.g., loyalty, repeat purchase intention). Even so, additional analyses demonstrated that methodological characteristics such as study design, website type, and type of items used to measure the trust construct moderated certain online trust relationships. These additional analyses indicated that the relationships between online trust and its respective antecedents and consequences are simultaneously more idiosyncratic, complex, and subtle than previously envisioned. Implications of the analyses for theory, practice, and future research are discussed.clos

Exploring the relationship between mobile application use and political information seeking and political discussion

This study examines the relationships between the use of mobile applications and two types of political behavior: political information seeking and political discussion. Based on a 2012 national survey of smartphone users in South Korea, this study found positive relationships between (a) the use of e-commerce, information, literacy, and utility apps and (b) political information seeking and political discussion. By contrast, this study found that the use of relational apps was negatively related to political information seeking and not related to political discussion. The use of entertainment apps was not associated with either behavior. This study provides a starting point for examination of mobile apps as they continuously grow and develop toward user engagement, and furthermore shed light on their effect on political participation.clos

Brand Exploration in Metaverse: Effects of User-Avatar Resemblance on Engagement and Brand Attitude

Brand metaverse, which refers to the brand in a virtual world, has become an important medium for brands to communicate with customers. In this study, we investigate the influence of user-avatar resemblance on brand metaverse engagement and brand attitude. Specifically, we propose that user-avatar resemblance affects brand attitude by virtue of the engagement with the brand metaverse. Furthermore, we posit that copresence, the simultaneous presence of multiple avatars in the brand metaverse, acts as a moderator that strengthens the mediation. We conducted an experiment using a fashion brand???s virtual world in a popular metaverse platform. Our hypotheses were supported for the main and interaction effects. The findings provide meaningful implications for marketing practitioners who have intentions to implement ???metaverse marketing.??

Brand Exploration in Metaverse: Effects of Avatar Resemblance on Brand Attitude

Recently, the metaverse (i.e., a virtual world with avatar interaction) has been widely used as a marketing tool in various fields to enhance user engagement. However, few studies have examined the effects of avatar-self resemblance on user attitude and intention in the metaverse. In this sense, this study examines the mechanism by which avatar-self resemblance influences brand attitude and virtual item purchase intentions in the brand-oriented metaverse. In particular, we identify the role of virtual item purchase intention as a mediator and the number of concurrent users as a moderator. The main venue for the experiment is Zepeto???s ???Ralph Lauren brand world.??? This research provides several implications. Theoretically, this study complements the adoption of the metaverse as a virtual technology in the marketing field. As a practical implication, this study also provides marketing managers with valuable insights for designing an effective brand-oriented metaverse