Designing a Human Resource Management Ecosystem Model in Sport Organizations

Abstract

Human resource management in sport organizations is increasingly shaped by interdependence among federations, clubs, public agencies, universities, professional associations, technology providers, coaches, referees, medical staff, volunteers, and other specialist actors. Traditional organization-centered HRM approaches do not fully explain how knowledge, talent, professional capability, and employment relationships move across these boundaries. This study aimed to develop a human resource management ecosystem model for sport organizations and obtain preliminary empirical support for its proposed structure. An applied-developmental exploratory sequential mixed-methods design was used. In the qualitative phase, systematic grounded theory was conducted with 15 experts in sport management and human resource management selected through purposive and theoretical sampling. Semi-structured interviews continued until theoretical saturation and were analyzed through open, axial, and selective coding. The qualitative analysis generated 120 initial codes, 30 subcategories, and 15 main categories. In the quantitative phase, a researcher-developed 120-item questionnaire was administered online to 400 respondents drawn from sport organizations and related professional groups. Content validity was examined by 15 experts, a pilot reliability assessment was conducted with 30 respondents, and the measurement and structural models were examined using partial least squares structural equation modeling (PLS-SEM). The model included causal conditions (sport workforce complexity and institutional fragmentation), a core phenomenon (human capital networking and sport value co-creation), contextual conditions (sport institutional environment and sport performance culture), intervening conditions (sport transformation readiness and strategic sport support), strategies (professional sport empowerment, talent-cycle engineering, and ecosystem performance steering), and outcomes (flourishing professional capital, empowered sport organizations, excellent sport services, and sustainable sport development). The specified structural relationships were positive and statistically significant in the study sample. Causal conditions were strongly associated with the HRM ecosystem (beta = 0.95, t = 120.95, R2 = 0.917). The HRM ecosystem (beta = 0.96), contextual conditions (beta = 0.78), and intervening conditions (beta = 0.95) were associated with strategies, explaining 93.7% of their variance; strategies were strongly associated with outcomes (beta = 0.96, t = 183.84, R2 = 0.936). Because these coefficients and R2 values are unusually high for organizational research and the instrument was derived directly from the qualitative categories, the quantitative findings should be interpreted as preliminary internal support rather than independent external validation. The findings support a provisional conceptualization of HRM in sport organizations as a networked and multi-actor ecosystem rather than a set of isolated intra-organizational functions. The proposed model emphasizes coordination of specialist actors, shared capability development, strategic support, digital readiness, trust, talent-cycle integration, and multi-level performance governance. Independent psychometric replication and additional discriminant-validity and predictive assessments are required before the model can be considered externally validated.