درخت حوزه‌های تخصصی

The present study is implemented to identify indicators and to provide an optimal evaluation method in recreational-sports pools. The present study is considered practical in purpose, and survey in collecting data. Firstly, by bibliometric research and five professional experts’ interviews, 91 indicators were identified for evaluating recreational-sports pools. Secondly, in terms of 4 components or perspectives in the Balanced Scorecard, 57 indicators were established (internal processes (10 indicators), customer (22 indicators), growth and learning (19 indicators), and financial (6 indicators)), from focal group’s output which was comprised of 4 prominent professors. The structure was confirmed based on 333 individuals’ opinions in the statistical population by employing factor analysis. In order to rate the pools studied, the gray clustering analysis method was applied followed by the structure of the balanced scorecard confirmed. Principally, 20 homogenous recreational-sports pools were investigated in 15 city regions and boundaries of provinces in Isfahan, Sepahan Shahr, and Baharestan. Based on data analysis and rating of each case study, Araman, Absar, Enghelab, Morvarid, and Golsar pools were ranked first to fifth, respectively. Furthermore, the main purpose of the present study based on calculated indicators is to propose a practical method to provide an accurate evaluation of sports pools. 

Justice as a basic necessity of social life, plays a critical role in administration of sport teams and sport organization. The aim of the present study was to investigate the relationship between Perceived Organizational Justice in Collegiate Sport Teams and Sport Achievement Motivation. In this descriptive –correlative study, 102 student athletes (56 males, 46 females) who were selected as statistical sample from Northern Khorasan and Razavi Khorasan provinces responded to Organizational Justice Questionnaire developed by Niehoff & Moorman (1993) and sport achievement motivation Questionnaire developed by Gill et al. (1983). Conducting correlation coefficient for data analysis revealed that perceived organization justice and its subscales significantly correlated to sport achievement motivation in collegiate sport teams. Moreover, the results of the stepwise regression revealed that, among perceived organization justice subscales, interactional justice was the strongest predictor of sport achievement motivation.

The present study aimed to propose a revenue model for hosting the sports events in Iran. 220 university professors, sports experts, staffs of sports federations, and management agents of international sporting events participated in this study. A researcher-developed questionnaire was used for data collection. Factor analysis was conducted to verify the structure validity. SPSS 22 and PLS software were applied for data analysis. Based on the findings, 12 factors were found to be significant in the monetizing from hosting the sporting events. Sponsors, human resources, politics, governmental institutions, law, sport fields, scientific, security, government support, media, Facility development, and fans were the most important factors for revenue generation in hosting sports events. Managers, organizations, and the organizers of sporting events can use appropriate strategies in the fields of media, sponsors, security of the country, investment, fans, governmental institutions, development of sporting facilities and places, and policy by utilizing the results and model provided in the present study in order to generate money from sporting events.

The aim of this mixed-methods study is to develop a model for the development of insurance fields in the sports industry in Iran with a systematic data-based approach in the qualitative phase and a survey approach in the quantitative section. The data collection tools included document review, experts’ interviews, and questionnaires, which its reliability and validity were validated. The participants in the qualitative section consisted of 21 university professors in sports management familiar with insurance issues and insurance industry experts familiar with the sports industry selected by purposive sampling approach in 2022. The statistical population in the quantitative section consisted of insurance sales networks and sports executive bodies. Based on the Morgan table, 384 individuals were selected through the available sampling. Data analysis was performed using NVIVO, Smart PLS software. The coding results led to the extraction of 88 primary codes, 20 axial codes, and 10 selective codes. The results showed that the core factors of casual conditions of the model of developing insurance fields in the sports industry included the external conditions, the background factors, the intervention conditions, the strategies, and the outcomes. Based on the research findings, the strengthening of the economic infrastructure and constructive marketing strategies had the most significant impact on the research model.