Designing a Sports Club Marketing Model with an Artificial Intelligence Approach Using Interpretive Structural Modeling

Abstract

The present study aims to design a comprehensive marketing model for sports clubs using artificial intelligence, employing an interpretive structural modeling approach. This study is applied in nature, exploratory-descriptive in type, fundamental in terms of objective, and non-experimental (descriptive) in terms of data collection method. The population of participants included theoretical experts (university professors and researchers in sports management or sports club management) and practical experts (managers and specialists active in sports club management with some familiarity with artificial intelligence). Sampling was conducted purposively, and theoretical saturation was achieved with 10 participants. Data were collected through interviews and a decision-matrix-based questionnaire. The analysis and coding of interview texts were conducted using qualitative grounded theory in MaxQDA 20. In the second phase, to determine the relationships between constructs and design the model, interpretive structural modeling was applied using MicMac software. According to the research model, the components of personalized marketing with artificial intelligence, enhancing fan loyalty with technology, predicting and analyzing fans, intelligent interaction with fans, competitor analysis using AI tools, sports digital marketing specialists, training and fitness planning, and optimization of advertisements and campaigns all have an impact. In the same vein, the findings indicate that applying artificial intelligence tools in competitor and fan behavior analysis enables club managers to design marketing strategies intelligently and allocate resources optimally.