Different Pathways from Transformational Leadership to Job Satisfaction

Transformational leaders are known to inspire and motivate their followers, thereby leading to enhanced job satisfaction. Job satisfaction is an intellectual concept regarding individuals’ attitudes toward their jobs. This study asserts that the underlying mechanisms for transformational leadership to affect employee satisfaction are trust in the community, including the leader (that is, organization) and trust in the self, namely self‐efficacy. Leadership is specifically associated with continual transformations in the higher educational context, and collectivist cultures may manifest different processes underlying the transformational leadership–satisfaction relationship. This study investigated the mediating effects of trust and self‐efficacy on the relationship between transformational leadership and job satisfaction. The study sample included academicians from a nonprofit higher education institution in Turkey. The data were analyzed using structural equation modeling. The results showed that the relationship between transformational leadership and job satisfaction is fully mediated by both trust and self‐efficacy. The mediator effect of trust was shown to be stronger than self‐efficacy, which is assumed to be the result of the cultural context. The results are discussed in the context of employee satisfaction and cultural determinants of employee satisfaction.     

Stochastic Bounds with a Low Rank Decomposition

We investigate how we can bound a discrete time Markov chain (DTMC) by a stochastic matrix with a low rank decomposition. In the first part of the article, we show the links with previous results for matrices with a decomposition of size 1 or 2. Then we show how the complexity of the analysis for steady-state and transient distributions can be simplified when we take into account the decomposition. Finally, we show how we can obtain a monotone stochastic upper bound with a low rank decomposition.     

Robust confirmatory factor analysis based on the forward search algorithm

A key concept of the forward search algorithm in confirmatory factor analysis is ordering of the data on the basis of observational residuals. These residuals are computed under the proposed model and measure the discrepancy between the observed and predicted response for each unit of the sample. Regression-type factor scores are used to estimate model predictions. Informative forward plots are created for indexing influential observations and to show the dynamics of the estimates throughout the search. The detailed influence of each observation on the model parameters and fit indices is analyzed and a robust model inference is achieved. Real and simulated data sets with known contamination schemes are used to demonstrate the performance of the forward search algorithm.     

Parental Support for Basic Psychological Needs and Happiness: The Importance of Sense of Uniqueness

Past empirical research relying on self-determination theory (SDT) has consistently shown that parental support of basic psychological needs (BPN) is associated with adolescent happiness. Yet, the specific mechanisms accounting for this link are still undetermined. The present study aimed to address this gap in the literature by testing a theoretical model proposing that adolescents’ satisfaction of BPN in life and sense of uniqueness mediate the association of parental support for BPN and happiness. The analyses relied on structural equation modeling and bootstrapping procedures and found support for the model. The theoretical implications of the model for SDT and applied considerations to improve the well-being of adolescents are discussed. Also, suggestions for future research that could further improve our understanding of the dynamic interplay between BPN, sense of uniqueness and happiness are presented.     

Modification of Tukey's additivity test

In this paper we discuss testing for an interaction in the two-way ANOVA with just one observation per cell. The known results are reviewed and a simulation study is performed to evaluate type I and type II risks of the tests. It is shown that the Tukey and Mandel additivity tests have very low power in case of more general interaction scheme. A modification of Tukey's test is developed to resolve this issue. All tests mentioned in the paper have been implemented in R package Additivity Tests.     

Fertility Decline in Czechoslovakia During the Last Two Centuries

The decline of fertility in Czechoslovakia on the territory of the Czech Socialist Republic began with a rise in the age at marriage; the decline of marital fertility began only after 1860. On the territory of the Slovak Socialist Republic marital fertility began to decline after 1900 without previous significant changes in the age at marriage. The differences between the demographic behaviour in the two parts of Czechoslovakia have persisted, although they are now gradually disappearing. There are other significant regional differences in the fertility decline caused by the overall process of economic and social development. The end of the demographic transition in the Czech Socialist Republic came during the 1930's and in the Slovak Socialist Republic during the 1960's.     

A Spatial-temporal Model for Temperature with Seasonal Variance

We propose a spatial-temporal stochastic model for daily average surface temperature data. First, we build a model for a single spatial location, independently on the spatial information. The model includes trend, seasonality, and mean reversion, together with a seasonally dependent variance of the residuals. The spatial dependency is modelled by a Gaussian random field. Empirical fitting to data collected in 16 measurement stations in Lithuania over more than 40 years shows that our model captures the seasonality in the autocorrelation of the squared residuals, a property of temperature data already observed by other authors. We demonstrate through examples that our spatial-temporal model is applicable for prediction and classification.     

Goodness-of-fit tests for Pareto distribution based on a characterization and their asymptotics

In this paper we present a new characterization of the Pareto distribution and consider goodness-of-fit tests based on it. We provide an integral and Kolmogorov–Smirnov-type statistics based on U-statistics and we calculate Bahadur efficiency for various alternatives. We find locally optimal alternatives for those tests. For small sample sizes, we compare the power of those tests with some common goodness-of-fit tests.     

NGO Failure: A Theoretical Synthesis

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - An extensive literature identifies conditions under which markets and states work efficiently and effectively toward their...