The importance of sector‐stereotypical images in relation to job pursuit intentions

This study broadens the concept of employer image and demonstrates the relevance of applicants’ sector image when looking for employment in either nonprofit or for‐profit organizations. We apply the Stereotype Content Model to conceptualize image through perceived competence and warmth and use multilevel analyses on data from final‐year Master’s students. Results show the importance of the sector‐stereotypical image and are partially in line with our hypotheses. Job pursuit intentions for specific organizations are predicted by both the organizations’ as well as the respective sectors’ perceived warmth and competence. Pursuit intentions for the for‐profit sector are predicted only by the image of that sector. However, the intention to pursue employment in the nonprofit sector is predicted by both its competence and warmth as well as by the perceived warmth of its organizations. These findings are discussed in view of a trickle‐down effect and compared to previous findings on sector image among consumers.     

Does Gold Price Matter for Divorce Rate in Iran?

The increasing divorce rate has become a major social concern for policy makers in the Islamic government of Iran. The price of gold coin is an important factor in cost-benefit analysis for individuals in their marriage and divorce decisions in Iran. Dowries (Mehrieh) are usually in the form of gold coin and a wife has a legal right to request them from her husband upon both parties signing the marriage contract. Increasing the price of gold coin may intensify the internal stress and struggles within families, leading to a higher probability of divorce. We investigated the long-run relationship between real price of gold coin and divorce rate for the case of Iran over the period 1980–2014. Controlling for other factors such as women’s education, social globalization, economic growth rate, and the war period with Iraq, our regression results showed that there is a positive and significant long-run relationship between real price of gold coin (as well as unanticipated changes in real price of gold coin) and marital instability.     

Phase II monitoring of binary profiles in the presence of within-profile autocorrelation based on Markov Model

This paper introduces a Markov model in Phase II profile monitoring with autocorrelated binary response variable. In the proposed approach, a logistic regression model is extended to describe the within-profile autocorrelation. The likelihood function is constructed and then a particle swarm optimization algorithm (PSO) is tuned and utilized to estimate the model parameters. Furthermore, two control charts are extended in which the covariance matrix is derived based on the Fisher information matrix. Simulation studies are conducted to evaluate the detecting capability of the proposed control charts. A numerical example is also given to illustrate the application of the proposed method.     

Developing a restricted two-parameter Liu-type estimator: A comparison of restricted estimators in the binary logistic regression model

In the context of estimating regression coefficients of an ill-conditioned binary logistic regression model, we develop a new biased estimator having two parameters for estimating the regression vector parameter β when it is subjected to lie in the linear subspace restriction Hβ = h. The matrix mean squared error and mean squared error (MSE) functions of these newly defined estimators are derived. Moreover, a method to choose the two parameters is proposed. Then, the performance of the proposed estimator is compared to that of the restricted maximum likelihood estimator and some other existing estimators in the sense of MSE via a Monte Carlo simulation study. According to the simulation results, the performance of the estimators depends on the sample size, number of explanatory variables, and degree of correlation. The superiority region of our proposed estimator is identified based on the biasing parameters, numerically. It is concluded that the new estimator is superior to the others in most of the situations considered and it is recommended to the researchers.     

On a Skew Bimodal Normal–Normal distribution fitted to the Old-Faithful geyser data

The Bimodal Normal distribution introduced by Alavi (2011) is a symmetric distribution where its variance is three times the variance of the corresponding normal distribution. Azzalini (1985) introduced the univariate Skew Normal distribution to model asymmetry data. In this paper the Skew Bimodal Normal–Normal distribution is introduced as a skew-symmetric distribution generated by the cumulative function of standard normal. Some properties of the distribution and some methods for generating data from this distribution are introduced. The maximum likelihood estimation of parameters is obtained. The distribution is fitted to the Old Faithful Geyser data.     

Two-Piece location-scale distributions based on scale mixtures of normal family

In this work, we study the maximum likelihood (ML) estimation problem for the parameters of the two-piece (TP) distribution based on the scale mixtures of normal (SMN) distributions. This is a family of skewed distributions that also includes the scales mixtures of normal class, and is flexible enough for modeling symmetric and asymmetric data. The ML estimates of the proposed model parameters are obtained via an expectation-maximization (EM)-type algorithm.     

Estimation of the parameters of Downton's bivariate exponential distribution using ranked set sampling scheme

The parameters of Downton's bivariate exponential distribution are estimated based on a ranked set sample. Parametric and nonparametric methods are considered. The suggested estimators are compared to the corresponding ones based on simple random sampling. It turns out that some of the suggested estimators are significantly more efficient than the ones based on simple random sampling.     

Predictive analysis for joint progressive censoring plans: a Bayesian approach

Comparative lifetime experiments are of particular importance in production processes when one wishes to determine the relative merits of several competing products with regard to their reliability. This paper confines itself to the data obtained by running a joint progressive Type-II censoring plan on samples in a combined manner. The problem of Bayesian predicting failure times of surviving units is discussed in details when parent populations are exponential. Two real data sets are analyzed in order to illustrate all the inferential procedures developed here. When destructive experiments under a censoring scheme finished, the researchers are usually interested to estimate remaining lifetimes of surviving units for sequel experiments. Findings of this paper are useful for these purposes specially when samples are non-homogeneous such as those taken from industrial storages.     

Sexual and Reproductive Health Knowledge Among Men and Women Aged 15 to 49 Years in Metropolitan Tehran

Sexual and reproductive health (SRH) knowledge is an important predictor of an individual’s sexual behavior; however, little is known regarding this issue among Iranians. This study assessed sexual and reproductive health knowledge among men and women aged 15 to 49 years in Tehran. A total of 755 men and women aged 15 to 49 years were recruited using multistage, random cluster sampling in June 2014. An illustrative anonymous questionnaire endorsed by the World Health Organization (WHO) was used to collect the data. Bivariate and multivariate analyses were performed. The results showed that men and women were moderately knowledgeable about sexual and reproductive health (mean score of SRH knowledge = 39, range: 26 to 52); however, myths and misperceptions prevailed in different aspects of SRH. For example, only 45% of women and 38.7% of men accurately knew that a person infected with human immunodeficiency virus (HIV) can look healthy. Friends were identified as the primary or secondary source of knowledge about puberty and sex-related issues. A multivariate analysis showed that being female (coefficient = 0.139, p < 0.001) and being married (coefficient = 0.180, p < 0.001) were significant predictors of better SRH knowledge, while being young (age group 15 to 24) was a significant determinant of poor SRH knowledge (coefficient = ?0.161, p < 0.001) when other influencing factors were controlled. Culturally appropriate and age-specific comprehensive education is recommended, particularly for men, the unmarried, and the younger generation in Iran.     

An approach to setting up a national customer satisfaction index: the Jordan case study

The aim of this paper was to develop a national customer satisfaction index (CSI) in Jordan and to derive its theory using generalized maximum entropy. During the course of this research, we conducted two different surveys to complete the framework of this CSI. The first one is a pilot study conducted based on a CSI basket in order to select the main factors that comprise the Jordanian customer satisfaction index (JCSI). Based on two different analyses, namely nonlinear principal component analysis and factor analysis, the explained variances in the first and second dimensions were 50.32 and 16.99% respectively. Also, Cronbach coefficients α in the first and second dimensions were 0.923 and 0.521, respectively. The results of this survey suggests the inclusion of loyalty, complaint, expectation, image and service quality as the main CS factors of our proposed model. The second study is a practical implementation conducted on the Vocational Training Corporation in order to evaluate the proposed JCSI. The results indicated that the suggested components of the proposed model are significant and form a good fitted model. We used the comparative fit index and the normed fit index as goodness-of-fit measures to evaluate the effectiveness of our proposed model. Both measures indicated that the proposed model is a promising one.