حبیب هنری

Health and well-being have become significant dimensions of urban sustainability, particularly in countries with rapid urbanization. Community sports affect the health and vitality of society's population. Although planning for city management has existed throughout history, an integrated structure of the role of sports in urban planning to improve the quality of life and health of citizens has not yet been defined. This study aims to present a community sports planning program in metropolitan areas of Iran. The research was qualitative, and was done using the grounded theory approach based on the systematic approach of Strauss and Corbin (1998). 13 participants were purposefully selected from experts in the field of public sports development for interviewing. The final model was based on 6 categories and 36 factors. Gender and infrastructure were the most contextual factors. Cultural and underlying factors were given more attention than casual factors. Among intervening factors, media, monitoring, and evaluation got more emphasis. The categories of infrastructure and planning were mostly emphasized in the strategies section. While, in the model implementation consequences section, cultural and social consequences were mostly emphasized. Through a participatory approach to sports development, metropolitan municipalities can better understand the needs of their citizens. A bottom-up or company-centric approach allows organizers to reconstruct sports presentation models based on each metropolis. 

Background: Sports facilities are one of the most commonly used services in the city with a significant role in improving the physical and mental health condition of citizens thus a proper procedure is required to locate and distribute them. Aim : The purpose of this study is to design a comprehensive model for the optimal location of sports facilities. Materials and Methods: The research method is descriptive-analytic based on information gathering and is applied research based on objectives. The opinions of 20 experts have been used to design the model using the Delphi method, and weighting the effective criteria in the sports facilities location. The weight of each criterion has been obtained as population density (0.47), access (0.31), development potential (0.14), and adjacency (0.08); furthermore, the Kendall coefficient of concordance (0.74) in the third step of the Delphi method shows the strong agreement between the experts, regarding the proposed model. The proposed model consisted of six steps: 1. Aim; 2. Verification of the functional area of the existing sport facilities and specific restrictions of the area; 3. Introducing and weighting the important criteria in the sports facilities location; 4. Identifying the most suitable locations for constructing the sports facilities; 5. Evaluating the needs of users; 6. Selecting the best spaces and prioritizing them. Results: The results of the model showed that the most important criteria for locating sport facilities are population density, access, development potential, and adjacency. Additionally, it was indicated that the agreement between the experts increased over time. Conclusion: According to the proposed model, it is possible to identify the points that are suitable for constructing the new sports facilities.

The main purpose of this study was to provide a framework of effective components in Iranian championship sports with a data mining approach. The research method was qualitative. The advanced search was performed in the general framework of factors affecting the sports industry and development and integration with data-driven technologies. Based on the literature review, 15 frameworks in the field of sports and 13 frameworks for the development and integration of the sports industry with technology were identified. After the data analysis, a researcher-developed framework for the championship sports industry for the use of data-driven technologies and data mining was presented in three parts. In the first part, nine influential factors including athletes/champion teams, leagues/clubs, stadiums/sports venues, fans/spectators, brands, media, government, academic/research institutions, and technology companies, were identified. In the second part, a strategic plan based on the development and integration of sports industry with data-driven technologies and data mining was presented, which includes four stages: Identifying and selecting talents, pre-game and match preparation, in-game and match activities, and post-match and match analysis. All data-driven activities and data mining in the first and second sections were performed by the IBM data science analysis methodology presented in the third section. Then, a conceptual framework was provided to 7 experts and their opinions were collected through semi-structured interviews and focus group methods. This conceptual framework enables sports managers to plan for their organization and adopt appropriate strategies using data-driven technologies and data mining.