درخت حوزه‌های تخصصی

Purpose: The aim of the present research was to present a model of sociological factors affecting employment on the attitude towards unemployment status of children of devotees. Methodology: This was an applied correlational cross-sectional study. The study population included 835 unemployed children of devotees of Bushehr province in 2020. The sample size was estimated 332 people who were selected by multi-stage cluster random sampling method and based on Cochran's formula. The data were collected using demographic information form and a researcher-made questionnaires of sociological factors of employment and attitude towards unemployment and were analyzed using Pearson correlation coefficients and path analysis in SPSS and AMOS software. Findings: The results showed that the model of sociological factors affecting employment the attitude towards unemployment status in the children of devotees had a good fit. Also, all six sociological factors, including increasing young population, social class, government measures, social environment, self-employment bank facilities, and religious and cultural backgrounds, had a direct and significant effect on the attitude towards unemployment status in the children of devotees (P<0.05). Conclusion: The results revealed that the authorities in charge of planning jobs for the children of devotees can provide appropriate conditions to improve the sociological factors affecting employment in order to improve their attitude towards unemployment status.

Huge economic, social, political, and technological changes in recent decades have brought increasing complexity and decreasing predictability of organizations' environments. One of the solutions offered to deal with such environments is the agile approach to human resources. This research was conducted with the aim of investigating the driving factors in human resource agility based on government policies. The current research is developmental in terms of purpose and descriptive survey in terms of the method with a combined (qualitative and quantitative) approach. The research community in the qualitative part included professors, experts in the field of human resources, and senior managers of the human resources department, and in the quantitative part, the senior and middle managers of the country's tax affairs organization who had a bachelor's degree or higher. Relevant data were extracted from theoretical literature and semi-structured open interviews in the qualitative section. The tool for data collection was a researcher-made questionnaire in the quantitative part. The results of the qualitative part led to the identification of 13 main categories, which are categorized into four main clusters (The propellants of human resource agility, Human resource agility policies, operational components of human resource agility, and Results and Functions of human resource agility) and became a five-point Likert scale questionnaire. The results of confirmatory factor analysis showed that all items have a significant relationship with the structure and the proposed structural model has a good fit. The results of the path analysis showed that the operational components of human resource agility have a mediating role in the relationship between the drivers of human resource agility and the results and functions of human resource agility. Human resource agility policies have a mediating role in the relationship between the propellants of human resource agility and the results and performance of human resource agility.

Green information technology is in the spotlight for organizations, helping them save money by using information technology (IT) to achieve the highest efficiency and thus reduce environmental impacts. One of the ways that can help organizations planning for deploying green IT is to evaluate green information technology maturity (GITM). Previous studies have referred to various criteria for green IT evaluation, most of which are qualitative criteria that are difficult to measure and evaluate in ambiguous conditions. The main objective of this study is to identify crucial criteria that affect the GITM level and to design a fuzzy inference system to assess the GITM level in any organization. While using a Mamdani Inference system, inputs can be verbal expressions or crisp values, and the output shows the level of maturity of green information technology. Since green IT knowledge is not modeled in previous studies, modeling it in the current study is a valuable step for organizations confused about various factors they should consider for going green. The main system criteria are the conditions of the data center, office environment, work practice, procurement, and corporate citizenship. Due to the generality of the model used for the knowledge base system development, organizations can use this system for the green IT maturity level determination. The presented inference system helps organizations understand their status of being IT green and plan for the following steps to accomplish their desired maturity level. The proposed inference system has been tested, validated, and used to determine the maturity level of Tehran municipality.