درخت حوزه‌های تخصصی

Purpose: In this research, the influencing factors on the behavior of human resources in the marketing department and human resource management policies and their relationship with the strategies of this department have been examined in order to identify the factors that are related to the superior performance of this department. Methodology: The data collection tool was semi-structured interviews were conducted using a combination of purposive (judgmental and quota) and theoretical sampling. In this regard, there were 36 elites in the statistical population of this research. Data analysis was done in three stages open coding, axial coding, and selective coding, and based on that, a qualitative research model was presented. Findings: The results of the research led to the extraction of 669 open codes, 160 concepts and 40 categories in the form of a paradigm model include the central category (strategic management of human resources in marketing, culture, improvement and correction, coherent and aligned systems), causal conditions (control of destructive effects), strategies (job satisfaction, commitment, trust, perceived organizational support, motivation, justice, reward, employee participation, loyalty, empowerment, empowerment, green insight into human resources and marketing), the prevailing context (demographic characteristics, psychological characteristics, organizational structure, strategy, organizational culture and supply, technology in use). Conclusion: finally outcomes (superior performance, organizational citizenship behavior, key work behaviors and production axis, the effects of human resource strategies, environmental thinking and green performance) were presented.

Purpose: The monitoring system in sports organizations plays an important role in improving their quality. Therefore, the aim of this study was to provide a comprehensive model for improving the monitoring system in sports organizations with a mixed approach. Methodology: In terms of purpose, the research was applied and in terms of the data collection method, it was mixed and exploratory. In the qualitative phase, the sample was 16 faculty members and experts related to the field of sports management, who were selected by purposive sampling. In the quantitative phase, the sample was 200 employees of sports organizations who were selected by multi-stage cluster sampling method. Data were collected by semi-structured interviews and researcher-made questionnaires and analyzed by coding methods and structural equation modeling. Findings: The findings of the qualitative phase showed that the comprehensive model for improving the monitoring system in sports organizations has 69 open codes in the form of 10 main categories, including productivity, administrative health, individual platforms, transparency, superstructure, infrastructure, continuous evaluation, intra-organization, extra-organization, general supervision, special And he was smart. The findings of the quantitative phase showed that for the comprehensive model of the improvement of the monitoring system in sports organizations, 9 components including productivity, administrative health, individual platforms, transparency, superstructure, infrastructure, continuous evaluation, intra-organizational, extra-organizational, were identified, the factor loadings of which were all higher than 0.40, the average The extracted variance was all higher than 0.50 and the reliability was higher than 0.80. Also, the mentioned model had a good fit and the effects were significant. Conclusion: The identified categories and components for the comprehensive model of improving the monitoring system in sports organizations can help the officials of sports organizations in providing solutions to improve the activities of the organization.