Beyond liking or following: Understanding public engagement on social networking sites in China

Corporate pages on social networking sites (SNSs) have become the key platform where publics interact with companies and organizations around the world. Focusing on one of the most important world economies, China, this study explored the types of public engagement with corporate pages on leading Chinese SNSs as well as the motivations and antecedents that drive such engagement. Given the participatory and communal nature of SNSs, this study proposed a conceptual model incorporating social media dependency and several social relationship factors, including parasocial interaction, perceived source credibility, and community identification, that influenced Chinese publics’ engagement with companies on SNSs. We conducted a web survey with a random sample of 245 Chinese SNS users to test the proposed model. The results confirm that with the exception of perceived credibility, social media usage and relationship-oriented factors played a significant role in inducing public engagement in China.     

Understanding learning behavior using location and prior performance as moderators

This study proposes and validates a research model that examines individuals’ learning behavior. Drawing on social cognitive theory (SCT), this study postulates self-efficacy, outcome expectations, social influence, and facilitating conditions as the key drivers of individuals’ learning behavior. Learners’ residential location and prior performance are also considered as moderators in the proposed model. This study contributes to the education literature by extending traditional SCT models to examine the previously unexplored area of environmental factors containing social influence and facilitating conditions, by validating idiosyncratic drivers of learning behavior and by presenting an operationalization of location and prior performance as two moderators in the learning behavioral formation. Finally, implications and limitations of the research are also provided.     

Acceptance sampling plans under progressive interval censoring with likelihood ratio

The paper investigates the design of life test plans under progressively interval censored test. Based on the likelihood ratio, the proposed life test plans are established so that the required producer and consumer risks can be satisfied simultaneously. The advantage of the proposed method is that the developed sampling procedure depends on the likelihood ratio only so that the method can be applied to any lifetime distribution when only one parameter is unknown. A numerical study is conducted and some of the sampling plans for the Weibull lifetime distribution with different shape parameters are tabulated for illustration. Moreover, the influence of the removal schemes on the proposed sampling plans is discussed.     

Geneticizing Ethnicity: A study on the “Taiwan Bio-Bank”

Taiwan as an island country is an immigrant society where interethnic marriages have been common. In the past centuries, it has not been unusual that people in Taiwan change their ethnic identities for various reasons. Its “four great ethnic groups” (sida zuqun)—the Hoklo, Hakka, Mainlanders, and aboriginal peoples—exist only as a social construction that arose in the 1990s in a specific political–cultural context. In 2005, a major government-sponsored research project, the Taiwan Biological Sample Bank—or Taiwan Bio-Bank (TBB)—was organized by a group of scientists and physicians. The purpose of the project is to collect genetic data from the “four great ethnic groups” of Taiwan in order to build a national database. This paper has three parts. First, I briefly review how the relationship between genetic attribution and the conceptualization of race/ethnicity has been addressed by social scientists and medical researchers since the mid twentieth century. Secondly, I analyze the history of biomedicine in Taiwan and the social and political context of the formation of the TBB project and its precursors. Thirdly, I examine the TBB’s theoretical and methodological assumptions about race/ethnicity in Taiwan. I point out that the rise of biomedicine since the 1990s has contributed to the “ethnicization of biomedicine,” in the sense that scientists have used dubious ethnic/racial categories with increasing frequency in practicing biomedicine.     

Solving unobserved heterogeneity with latent class inflated Poisson regression model

Inflated data and over-dispersion are two common problems when modeling count data with traditional Poisson regression models. In this study, we propose a latent class inflated Poisson (LCIP) regression model to solve the unobserved heterogeneity that leads to inflations and over-dispersion. The performance of the model estimation is evaluated through simulation studies. We illustrate the usefulness of introducing a latent class variable by analyzing the Behavioral Risk Factor Surveillance System (BRFSS) data, which contain several excessive values and characterized by over-dispersion. As a result, the new model we proposed displays a better fit than the standard Poisson regression and zero-inflated Poisson regression models for the inflated counts.KEYWORDS: Inflated data, latent class, heterogeneity, Poisson regression, over-dispersion     

Covariance Matrix Estimation via Network Structure

In this article, we employ a regression formulation to estimate the high-dimensional covariance matrix for a given network structure. Using prior information contained in the network relationships, we model the covariance as a polynomial function of the symmetric adjacency matrix. Accordingly, the problem of estimating a high-dimensional covariance matrix is converted to one of estimating low dimensional coefficients of the polynomial regression function, which we can accomplish using ordinary least squares or maximum likelihood. The resulting covariance matrix estimator based on the maximum likelihood approach is guaranteed to be positive definite even in finite samples. Under mild conditions, we obtain the theoretical properties of the resulting estimators. A Bayesian information criterion is also developed to select the order of the polynomial function. Simulation studies and empirical examples illustrate the usefulness of the proposed methods.     

Does globali zation affect human well-being?

The prevailing theorizing of globalization’s influence of human well-being suggests to assess both the favorable and unfavorable outcomes. This study formulates a dialectical model, adopts a comprehensive globalization measure and uses a three-wave panel data during 1980–2000 to empirically test direct and indirect effects of global flows’ human consequences. The outcomes from random effect modeling reveal significant positive impacts of political globalization, whereas economic and social globalization do not generate favorable influences when development level and regional differences are operated as controls. The overall globalization index is found to generate expected favorable influence on an overall human development index. Within developing countries, globalization’s human influence was not as significant as in industrial countries, however. Several hypotheses about globalization’s potential negative effects through increasing societal instabilities and reducing state power and social spending are not supported in analysis. It is concluded that globalization identified by increased global flows and exchanges contributes rather than hampers progress in human welfare.     

Social messengers as the new frontier of organization-public engagement: A WeChat study

Mobile-based social messengers have overtaken social networking sites as the new frontier for organizations to engage online stakeholders. This study provides one of the earliest empirical investigations on the antecedents and relational outcomes of pubic engagement with companies via WeChat—one of the world’s most popular social messaging apps. Publics’ social messenger dependency and privacy perception of the medium are found to effectively drive public engagement, which in turn enhances organization-public relationships. Strategic guidelines based on the study findings are provided.     

Hold Safety Inventory Before,At, or After the Fan‐Out Point?

We consider a product sold in multiple variants, each with uncertain demand, produced in a multi‐stage process from a standard (i.e., generic) sub‐assembly. The fan‐out point is defined as the last process stage at which outputs are generic (outputs at every subsequent stage are variant‐specific). Insights gained from an analytical study of the system are used to develop heuristics that determine the stage(s) at which safety inventory should be held. We offer a relatively‐simple heuristic that approaches globally‐optimal results even though it uses only two relatively‐local parameters. We call this the VAPT, or value‐added/processing time heuristic, because it determines whether a (local) stage should hold inventory based only on the value added at that local stage relative to its downstream stage, along with the processing time at that local stage relative to its downstream stage. Another key insight is that, contrary to possible intuition, safety inventory should not always be held at the fan‐out point, although a fan‐out point does hold inventory under a wider range of conditions. We also explore when postponement is most valuable and illustrate that postponement may often be less beneficial than suggested by Lee and Tang (1997).