محمد پوررنجبر

The current study was conducted to identify the impact of artificial intelligence on sports marketing (applications and limitations). This research is a sequential mixed-methods study (qualitative-quantitative). The participants in qualitative phase consisted of 15 sport management experts who were interviewed. In the quantitative section, the statistical population included members of the sports management academic community that was selected through random sampling approach. Kolmogorov-Smirnov test, confirmatory factor analysis, and path analysis were used in the quantitative part of the study. The structural equation method with partial least squares method was used to measure the validity of the model, and the research hypotheses. According to the results of the study, there are 8 effective factors of artificial intelligence applications in sports marketing, including predicting sales and prices of sports products/services, identifying revenue growth opportunities, automating sales processes of sports products/services, personalized recommendation systems through analyzing customer behavior of sports products/services, tracking satisfaction with sports products/services, and advertising. Additionally, there are 5 factors identified as limitations of artificial intelligence in sports marketing, including limited understanding of human elements, concerns about data privacy, costs, and technical issues. The findings can help sports marketers to better utilize artificial intelligence for better delivery and customer satisfaction of sports products and services.

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.