همایش ملی پژوهش های مدیریت و علوم انسانی در ایران
سال:1400 | دوره:11 |تعداد مقالات:2

This study aimed to predict teachers’ perfectionism and resilience based on their Islamic lifestyles. All male and female teachers in Mashhad in 2019 comprised the statistical population of this study. In this study, based on the statistical population, 113 teachers were selected by multi-stage cluster sampling. To gather data, Perfectionism and Islamic Lifestyle Inventories were used. The validity of the inventories was examined by content validity and the reliability was examined by Cronbach's alpha method. To analyze the data, descriptive statistics, Pearson correlation statistics and multivariate regression were used simultaneously. The findings indicated that the variable of Islamic lifestyle and its ideological and financial components could directly (positively) predict teachers' perfectionism.

Introduction: The aim of this study was to investigate the role of work-family conflict and quality of work life in predicting organizational commitment in education staff. Method: The research was applied in terms of purpose and descriptive-correlational in terms of method. The statistical population included all education staff of Kohgiluyeh and Boyer-Ahmad in 1400, from which a sample of 270 people was selected by stratified random sampling method with the help of Krejcie and Morgan table. For data collection, the Netmeier (1996) Family Conflict of Labor Questionnaire, Walton (1975) Quality of Work Life Questionnaire, and the Allen and Meyer Organizational Commitment Scale (1991) were used. Results: The results of Pearson correlation showed that there is an inverse relationship between work-family conflict and organizational commitment. There is a direct and significant relationship between quality of work life and organizational commitment. The results of multiple regression also showed that through work-family conflict, the organizational commitment of education staff can be inversely predicted. Also, the quality of work life was able to directly predict the level of organizational commitment of employees.