Sports organizations

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.

Background: The aim of this study has been to investigate the relationship between social factors and the promotion of women to management position in sport organizations in Iran . Method: Regarding the objective, this study is practical and regarding the method of implementation, it is descriptive, the population of this research in 2021, includes all the staff of the Youth and Sports Office of West Azerbaijan of Iran up to 216 people. Using Morgan’s tables 136 subjects were selected through stratified random sampling as the sample. In order to collect data, the questionnaires of social factors of the promotion of women to management positions were used, the validity of which was confirmed by experts and its reliability was obtained to be 0.86 through Cronbach's alpha test . Results: The results indicate that there is a positive significant relationship between gender and gender discrimination and women’s promotion to the position of management in sport organizations. In addition, there is also a positive significant relationship between the elimination of conflict between work and family and also family support and women’s promotion to manage mint positions in sports organizations . Conclusions: However, it appears that women are still faced with gender equity issues in sports governance, athletic media representation, and perception in sports. Therefore, the field of sport management should continue to work towards a level of quality that truly treats women as equals, offers them equal opportunity, and permits them to feel equal in sport management and athletic participation .

This paper deals with the development of a financial management maturity model for sports organizations based on artificial intelligence. We jointly consider enhancing financial transparency, oversight and control, risk management, and using advanced technologies in sports organizations. The proposed scheme relies on a constructivist grounded theory approach. The research process involved data collection through in-depth interviews with five AI language models, ChatGPT, Claude, Google Gemini, Mistral, and LLaMA. In addition, these models were utilized as an alternative to traditional experts. Finally, extensive simulations were conducted to validate that 209 initial codes were identified, which were then refined to 44 codes and eventually consolidated into 11 key themes. These themes include financial transparency, oversight and control, budget planning, risk management, and the use of advanced technologies. Numerical results show the efficiency that these themes are interlinked in a chain-like manner and contribute to enhancing the financial efficiency of sports organizations.