Diversifying configurational paths for athlete data protection.

In the digital era, data has become a core resource driving the development of the global sports industry. With the increasing awareness of athlete data protection, ensuring the security of this sensitive information worldwide has become a significant issue. This study employs configurational theory and Fuzzy-set Qualitative Comparative Analysis to investigate the various factors affecting athlete data protection. The research reveals three key configurational pathways: "Single Organization Support Type," "Organization-Environment Support Type," and "Organizational Support Absent Type." The "Single Organization Support Type" pathway emphasizes the role of a single organizational condition in athlete data protection, while the "Organization-Environment Support Type" considers the interaction between organizational and external environmental factors. In contrast, the "Organizational Support Absent Type" pathway reveals viable paths for data protection in the absence of effective organizational support. These findings not only provide valuable insights for policymakers to construct a more comprehensive framework for athlete data protection but also offer strategic support for the sustainable development of the global sports industry. They promote the safe use of sports data and the overall progress of the industry. Moreover, with the worldwide focus on sustainable development goals, the sports industry, as an essential component, plays an increasingly prominent role in promoting coordinated development of society, economy, and environment. The rational protection and utilization of sports data will contribute to achieving this global goal, especially in promoting healthy lifestyles, gender equality, and inclusive social construction. Therefore, the conclusions of this study are not only instructive for data governance within the sports domain but also provide practical contributions to global sustainable development.