Virtual Governance Networking Policies: A Comparative Analysis

Networks have become an increasingly important mode of public governance. ICT mechanisms, especially virtual systems will potentially establish this idea. This paper is based on a comparative analysis of three cases which are chosen to be particularly illustrative of the three virtual governance networking policies. In light of case study results, we have demonstrated that it is possible to devise a theoretically acceptable prospect of world countries concerning virtual governance networking policies.     

On Estimating the Residual Rényi Entropy under Progressive Censoring

In this article, the residual Rényi entropy (RRE) as a measure of uncertainty is considered in progressively Type II censored samples and some properties of it are investigated. The RRE of sth order statistic from a continuous distribution function is represented in terms of the RRE of the sth order statistic from uniform distribution. In general, we do not have a closed form for RRE of order statistics in most of distributions. This gives us a motivation for obtaining some bounds for RRE in progressively censored samples. In addition, two estimators are proposed for RRE. The performance of these estimators is compared using simulation studies.     

On a hybrid data cloning method and its application in generalized linear mixed models

The data cloning method is a new computational tool for computing maximum likelihood estimates in complex statistical models such as mixed models. This method is synthesized with integrated nested Laplace approximation to compute maximum likelihood estimates efficiently via a fast implementation in generalized linear mixed models. Asymptotic behavior of the hybrid data cloning method is discussed. The performance of the proposed method is illustrated through a simulation study and real examples. It is shown that the proposed method performs well and rightly justifies the theory. Supplemental materials for this article are available online.     

Education and time investment in domestic and parental activities in urban areas of Iran

Journal of Population Research - Education is considered one of the most important determinants of population change; operating through cultural change, enhancing negotiating powers or increasing...     

An exploratory study of subjective well-being in organizations–A mixed method research approach

ABSTRACT

Subjective well-being (SWB) has been widely found to have a profound impact on the individual, yet the process of its occurrence in public organizations remains unexplored. So the primary purpose of this paper is to explore the determining factors affecting the process of employee’s subjective well-being in public organizations using mixed methods research. Qualitative analysis using the grounded theory methodology reveals the effective factors that affect the process of employee’s subjective well-being in public organizations. Quantitative hypotheses are then developed based on a qualitative investigation. Survey data were collected from employees of public organizations in one of the provinces of Iran. Analysis of Moment Structure is used for data analysis. The results of the research revealed that both individual and organizational factors (as causal factors) influence the employees’ subjective well-being process (life satisfaction and positive affect). This phenomenon leads to the use of strategies which are affected by intervening and contextual factors. The consequences of this process are to change the attitude and behavior of individuals and improve the efficiency and effectiveness of the organization. This paper is among the first known to examine subjective well-being in public organizations using mixed methods research. The mixed methods approach offers a better insight to understanding effective factors affecting subjective well-being compared to the use of either a qualitative or quantitative method alone.     

Using Liu estimator for detection of influential observations in linear measurement error models

Abstract

In this paper, we introduce Liu estimator for the vector of parameters in linear measurement error models and discuss its asymptotic properties. Based on the Liu estimator, diagnostic measures are developed to identify influential observations. Additionally, the analogs of Cook’s distance and likelihood distance are proposed to determine influential observations using case deletion approach. A parametric bootstrap procedure is used to obtain empirical distributions of the test statistics. Finally, the performance of the influence measures have been illustrated through simulation study and analyzing a real data set.     

Multiple Conceptualizations of Small Business Web Use and Benefit*

Small businesses play an important role in the U.S. economy and there is anecdotal evidence that use of the Web is beneficial to such businesses. There is, however, little systematic analysis of the conditions that lead to successful use of and thereby benefits from the Web for small businesses. Based on the innovation adoption, organizations, and information systems (IS) implementation literature, we identify a set of variables that are related to adoption, use, and benefits of information technology (IT), with particular emphasis on small businesses. These variables are reflective of an organization's contextual characteristics, its IT infrastructure, Web use, and Web benefits. Since the extant research does not suggest a single theoretical model for Web use and benefits in the context of small businesses, we adopt a modeling approach and explore the relationships between “context‐IT‐use‐benefit” (CIUB) through three models—partial‐mediator, reduced partial‐mediator, and mediator. These models posit that the extent of Web use by small businesses and the associated benefits are driven by organizations’ contextual characteristics and their IT infrastructure. They differ in the endogeneity/exogeneity of the extent of IT sophistication, and in the direct/mediated effects of organizational context. We examine whether the relationships between variables identified in the literature hold within the context of these models using two samples of small businesses with national coverage, including various sizes, and representing several industry sectors. The results show that the evidence for patterns of relationships is similar across the two independent samples for two of these models. We highlight the relationships within the reduced partial‐mediator and mediator models for which conclusive evidence are given by both samples. Implications for small business managers and providers of Web‐based technologies are discussed.