Gender in academic STEM: A focus on men faculty

In this study, we explore how men faculty understand the role of gender in shaping faculty experiences in academic science, technology, engineering and mathematics (STEM) and how they position themselves in relation to inequalities disfavouring women. Our data reveal diversity among men in their understandings regarding challenges facing women in STEM. The majority of our participants revealed gender‐blind perspectives and argued that the egalitarian structure of academia does not allow gender to impact attainments in STEM in any significant way. However, a considerable number of them felt privileged compared to women and described subtle ways in which gender shapes opportunities. Our findings show the important implications of men's sensitivity to gender in the ways they perform their professional roles as, for example, mentors, colleagues and teachers in relation to women in STEM. They further call for attention to men's perceptions of gender issues when designing institutional interventions for improving women's conditions in STEM.     

Estimation and Prediction for Exponentiated Family of Distributions Based on Records

In this article, a family of distributions, namely the exponentiated family of distributions, is defined and for the unknown parameters, different point estimates are derived based on record statistics. Prediction for future record values is presented from a Bayesian view point. Two numerical examples and a Monte Carlo simulation study are presented to illustrate the results.     

Designing an economically optimal repetitive group-sampling plan based on loss functions

Acceptance sampling is a quality assurance tool, which provides a rule for the producer and the consumer to make acceptance or rejection decision about a lot. This paper attempts to develop a more efficient sampling plan, variables repetitive group sampling plan, based on the total loss to the producer and consumer. To design this model, two constraints are considered to satisfy the opposing priorities and requirements of the producer and the consumer by using Acceptable quality level (AQL) and Limiting quality level (LQL) points on operating characteristic (OC) curve. The objective function of this model is constructed based on the total expected loss. In order to illustrate the application of the proposed model, an example is presented. In addition, the effects of process parameters on the optimal solution and the total expected loss are studied by performing a sensitivity analysis. Finally, the efficiency of the proposed model is compared with the variables single sampling plan, the variables double sampling plan and the repetitive group sampling plan of Balamurali and Jun (2006) in terms of average sample number, total expected loss and its difference with ideal OC curve.     

Analysis of covariance under inverse Gaussian model

This paper considers the problem of analysis of covariance (ANCOVA) under the assumption of inverse Gaussian distribution for response variable. We develop the essential methodology for estimating the model parameters via maximum likelihood method. The general form of the maximum likelihood estimator is obtained in color closed form. Adjusted treatment effects and adjusted covariate effects are given, too. We also provide the asymptotic distribution of the proposed estimators. A simulation study and a real world application are also performed to illustrate and evaluate the proposed methodology.     

An analysis of major social obstacles affecting human resource development in Iran

ABSTRACT

This study aimed to analyze the major social obstacles affecting the human resource development (HRD) in Iran. The study population included faculty members in Yazd province, Iran (N = 280, n = 162). A survey and a researcher-made questionnaire were used to collect data. The reliability of the questionnaire was confirmed by using Cronbach’s alpha (0.88) and its validity was approved by a panel of experts. The results indicated that the major social obstacles affecting HRD are ‘an increase in the share of foreigners in the labor market’, ‘frustration of native graduates’ and ‘local brain drain’, respectively. Furthermore, the results of exploratory factor analysis indicated that the most important social obstacles affecting HRD can be summarized into six factors including migration, lack of nativism, inclination towards foreigners, gender imbalance, lack of justice in distribution of resources, and lack of meritocracy. These factors altogether could explain 65.45% of the total variance. In the end, some applied recommendations (such as paying more attention to rural youth, fair distribution of facilities towards urban and rural balance, supporting native elites, preference for employment, and applying indigenous peoples based on meritocracy, creating favorable balance at different levels of academic education, avoiding gender inequality) have been presented.     

Designing optimal double-sampling plan based on process capability index

Process capability analysis is applied to monitor the process quality. Process capability can be quantified by process capability index. These indices have wide application in quality control methods and acceptance sampling plans. In this paper, we introduce a double-sampling plan based on process capability index. In this type of scheme, under a decision rule and with the specified rejection and acceptance numbers, the second sample is selected and the decision of rejection or acceptance is made based on the information obtained from two samples. The purpose of this scheme is to reduce the average sample number in order to reduce the time and cost of sampling. A comparison study has been conducted in order to evaluate the performance of proposed method in comparison with classical single sampling plans.     

Poverty and Income Replacement Profile Among EPF Retiree in Malaysia

Social security policies often focus on replacement rates, which indicate retirement income or social security benefits in relation to preretirement income. The higher replacement rate among the pensioners would ensure that the ageing society would have sufficient income to lead a normal life after retirement. This study examined factors that influencing the income replacement rate of Malaysian Employee Provident Fund (EPF) retirees. The analysis was based on a nationwide survey conducted in 2013–2014 among EPF retiree. A logit model was used to evaluate the likelihood of selected socio-demographic and economic factors contributing to income of the retirees. The results indicated that around 62 % of elderly has lower retirement income compared to their preretirement income and it makes them more vulnerable to unpredictable events and financial conditions. The study suggested that the income replacement rate of elderly could be strengthened by investing in ageing workforce, raising retirement age, enhancing educational achievements of low income groups and restructuring employment. These may in turn increase the availability of skilled workers, enhancing the national productivity, increase the income security of retirees, reduce poverty, and develop economic growth of the country.     

A recursive approach for lot sentencing problem in the presence of inspection errors

In this paper, a new sequential acceptance sampling plans in the presence of inspection errors is developed. A suitable profit objective function is employed for optimizing the lot sentencing problem. A backward recursive approach is applied for obtaining the profit of different decisions in each stage of sampling. Required probabilities are obtained using Bayesian rule. A case study is solved for illustrating the application of proposed models and sensitivity analysis are carried out on the parameters of the proposed methodologies and the behaviour of models by changing the parameters are investigated.     

On the ridge regression estimator with sub-space restriction

In the linear regression model with elliptical errors, a shrinkage ridge estimator is proposed. In this regard, the restricted ridge regression estimator under sub-space restriction is improved by incorporating a general function which satisfies Taylor’s series expansion. Approximate quadratic risk function of the proposed shrinkage ridge estimator is evaluated in the elliptical regression model. A Monte Carlo simulation study and analysis based on a real data example are considered for performance analysis. It is evident from the numerical results that the shrinkage ridge estimator performs better than both unrestricted and restricted estimators in the multivariate t-regression model, for some specific cases.