Document Type : Original Article

Authors

• elaheh khoeeni ¹
• firouzeh hajialiakbari ²
• homa doroudi ³
• ahmad naghiloo ⁴

¹ Department of Business Administration, Faculty of Humanities, Islamic Azad University, Zanjan, Iran

² Associate Professor, Department of Business Administration, Zanjan Branch, Islamic Azad University, Zanjan, Iran

³ Full Professor, Department of Business Administration, Zanjan Branch, Islamic Azad University, Zanjan, Iran

⁴ Associate Professor, Department of Economics, Zanjan Branch, Islamic Azad University, Zanjan, Iran

Abstract

This research aims to optimize sports fans’ purchasing behavior to enhance sports marketing strategies. The scope of the study includes modeling the dynamic interaction among key variables such as advertising effectiveness, pricing, team performance, fan experience, and loyalty. A system dynamics (SD) approach was employed to simulate fan behavior over an 8-month period, followed by a genetic algorithm (GA) used to optimize key influencing parameters. The simulation and optimization results showed that a 10% increase in advertising effectiveness (σ) led to a 7.3% growth in purchase rate and a 5.1% reduction in customer churn rate. Moreover, a 10% increase in word-of-mouth power resulted in a 6.2% increase in customer loyalty. Validation metrics confirmed the model's accuracy. The findings demonstrate that combining system dynamics with intelligent algorithms can predict and optimize fan purchasing behavior, revenue stream, and loyalty with acceptable accuracy and provide an effective solution for analyzing attrition and improving marketing strategies in the sports industry.

Keywords

• Sports Marketing
• System Dynamics
• Fan Purchase Behavior
• Optimization marketing strategy
• Simulation