Emotional intelligence and counterproductive work behavior: The mediating role of organizational climate

ABSTRACT

This research investigates the impact of emotional intelligence on counterproductive work behavior through examining the mediating role of organizational climate. Data were collected from 304 administrative employees working in nine private universities in Amman, Jordan. Validity and reliability tests were conducted using factor analysis and Cronbach’s alpha. Research hypotheses were tested through multiple regression analysis and structural equation modeling methods. Outcomes of the analysis indicate that there is a significant impact on the relationship between emotional intelligence and counterproductive work behavior. The research proposes several recommendations for managers to apply specifically in private universities, and/or in any type of sector in Amman- Jordan. It also laid the groundwork for future research.     

Inference for Type II bivariate Pólya–Aeppli distribution

In this article, we discuss the estimation of model parameters of the Type II bivariate Pólya–Aeppli distribution using the method of moments and the maximum likelihood method. We also compare some interval estimation methods. We then carry out a Monte Carlo simulation study to evaluate the performance of the proposed point and interval estimation methods. Finally, we present an example to illustrate all the inferential methods developed here.     

Children’s Deliberate Control of Facial Action Units Involved in Sad and Happy Expressions

Few attempts have been made since the pioneer work of Ekman et al. (1980) to examine the development of the deliberate control of facial action units in children. We are reporting here two studies concerned with this issue. In Study 1, we investigated children’s ability to activate facial action units involved in sadness and happiness expressions as well as combinations of these action units. In Study 2, we examined children’s ability to pose happiness and sadness with their face, without telling them which action unit to activate. The children who took part in this study were simply asked to portray happiness and sadness as convincingly as possible. The results of Study 1 indicate a strong developmental progression in children’s ability to produce elementary facial components of both emotions as well as in their ability to produce a combination of the elements in the case of happiness. In agreement with prior research in motor development, several non-target action units were also activated when children performed the task. Their occurrence persisted throughout childhood, indicating limitations in the finer motor control achieved by children across age. The results obtained in Study 2 paralleled those obtained in Study 1 in many respects, providing evidence that the children used the technique of deliberate action to pose the two target emotions.     

Decision Makers as Statisticians: Diversity,Ambiguity, and Learning

I study individuals who use frequentist models to draw uniform inferences from independent and identically distributed data. The main contribution of this paper is to show that distinct models may be consistent with empirical evidence, even in the limit when data increases without bound. Decision makers may then hold different beliefs and interpret their environment differently even though they know each other's model and base their inferences on the same evidence. The behavior modeled here is that of rational individuals confronting an environment in which learning is hard, rather than individuals beset by cognitive limitations or behavioral biases.     

Nonparametric Tests for Comparing Several Coefficients of Variation

We consider the problem of comparing (k + 1) coefficients of variation. We are interested in testing the null hypothesis that the coefficients of variation are equal against each of the alternatives: (a) some populations have different coefficients of variation and (b) the coefficients of variation are ordered. Three nonparametric test statistics are proposed and their asymptotic theory is developed. We compared the proposed tests together with another parametric test using two Monte Carlo studies to estimate their probabilities of Type I error and powers. An illustration of the proposed tests using a real data set is given.     

Modeling a cross-sectional response variable with longitudinal predictors: an example of pulse pressure and pulse wave velocity

We wish to model pulse wave velocity (PWV) as a function of longitudinal measurements of pulse pressure (PP) at the same and prior visits at which the PWV is measured. A number of approaches are compared. First, we use the PP at the same visit as the PWV in a linear regression model. In addition, we use the average of all available PPs as the explanatory variable in a linear regression model. Next, a two-stage process is applied. The longitudinal PP is modeled using a linear mixed-effects model. This modeled PP is used in the regression model to describe PWV. An approach for using the longitudinal PP data is to obtain a measure of the cumulative burden, the area under the PP curve. This area under the curve is used as an explanatory variable to model PWV. Finally, a joint Bayesian model is constructed similar to the two-stage model.     

Comparative Testing of Experts

We show that a simple “reputation‐style” test can always identify which of two experts is informed about the true distribution. The test presumes no prior knowledge of the true distribution, achieves any desired degree of precision in some fixed finite time, and does not use “counterfactual” predictions. Our analysis capitalizes on a result of Fudenberg and Levine (1992) on the rate of convergence of supermartingales. We use our setup to shed some light on the apparent paradox that a strategically motivated expert can ignorantly pass any test. We point out that this paradox arises because in the single‐expert setting, any mixed strategy for Nature over distributions is reducible to a pure strategy. This eliminates any meaningful sense in which Nature can randomize. Comparative testing reverses the impossibility result because the presence of an expert who knows the realized distribution eliminates the reducibility of Nature's compound lotteries.     

Comments on the Mixture Detection Rule Used in SPC Control Charts

When calculating independently the false alarm rate of the eight usual runs rules used in SPC control chart, it appears that the proposed rule designed to detect mixture patterns corresponds to a Type-I error strongly lower than the seven other rules. This discrepancy is underlined and the mixture rule is showed to be useless both for in-control and out-of-control processes. Thus a modification of the mixture detection rule is proposed and the impact of this new mixture rule is then illustrated and discussed using Monte Carlo calculations.