Sports Management Evaluation Model as a Reflection of Regional Identity and Excellence

This study aims to evaluate the regional sports management system by emphasizing the relationship between managerial effectiveness and the development of regional sports identity, defined as a distinctive set of characteristics reflecting a region's capacity to develop, manage, and sustain its sports system rooted in local potential, cultural values, and institutional strength. An evaluative approach was applied to six primary dimensions: (1) Athlete–Coach Development and Performance, (2) Referee Quality, (3) Organization and Human Resources, (4) Facilities and Event Management, (5) Partnerships and Funding, and (6) Information Systems. The analysis included descriptive analysis, factor analysis, multiple linear regression, and cluster analysis. The KMO value of 0.686 and Bartlett's Test (p = 0.000) confirmed data suitability. PCA produced two main factors explaining 66.90% of the total variance. Regression analysis yielded an R<sup>2</sup> of 0.987 (p < 0.001). It should be noted that this exceptionally high R<sup>2</sup> value is attributable to the composite nature of the dependent variable (Total Z-Score), which is an aggregation of the same six dimensions serving as predictors; thus, the near-perfect fit reflects a mathematical relationship rather than a purely empirical prediction. The Performance and Technical Management factor showed the strongest effect (β = 0.859), followed by Resource Support and Supporting Systems (β = 0.499). K-Means cluster analysis generated three clusters: high-performing (n = 7), moderate (n = 11) with strengths in partnerships and information systems, and low-performing (n = 12), showing weaknesses across all variables. These findings affirm that higher scores reflect not only management effectiveness but also regional sports identity formed through the integration of athlete development, institutional capacity, and sustainable supporting systems.

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Publication Details

Journal
International journal of human movement and sports sciences
Published
2026-05-01
DOI
https://doi.org/10.13189/saj.2026.140317
Primary Topic
Sport Psychology and Performance
Type
article
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article

Sports Management Evaluation Model as a Reflection of Regional Identity and Excellence

Akbar Kusuma Abadi, Yusuf Hidayat, Fajar Adi Nugroho, Ngadiman Ngadiman
International journal of human movement and sports sciences
Sport Psychology and Performance
article

Sports Management Evaluation Model as a Reflection of Regional Identity and Excellence

Akbar Kusuma Abadi, Yusuf Hidayat, Fajar Adi Nugroho, Ngadiman Ngadiman
article en

Abstract

This study aims to evaluate the regional sports management system by emphasizing the relationship between managerial effectiveness and the development of regional sports identity, defined as a distinctive set of characteristics reflecting a region's capacity to develop, manage, and sustain its sports system rooted in local potential, cultural values, and institutional strength. An evaluative approach was applied to six primary dimensions: (1) Athlete–Coach Development and Performance, (2) Referee Quality, (3) Organization and Human Resources, (4) Facilities and Event Management, (5) Partnerships and Funding, and (6) Information Systems. The analysis included descriptive analysis, factor analysis, multiple linear regression, and cluster analysis. The KMO value of 0.686 and Bartlett's Test (p = 0.000) confirmed data suitability. PCA produced two main factors explaining 66.90% of the total variance. Regression analysis yielded an R<sup>2</sup> of 0.987 (p < 0.001). It should be noted that this exceptionally high R<sup>2</sup> value is attributable to the composite nature of the dependent variable (Total Z-Score), which is an aggregation of the same six dimensions serving as predictors; thus, the near-perfect fit reflects a mathematical relationship rather than a purely empirical prediction. The Performance and Technical Management factor showed the strongest effect (β = 0.859), followed by Resource Support and Supporting Systems (β = 0.499). K-Means cluster analysis generated three clusters: high-performing (n = 7), moderate (n = 11) with strengths in partnerships and information systems, and low-performing (n = 12), showing weaknesses across all variables. These findings affirm that higher scores reflect not only management effectiveness but also regional sports identity formed through the integration of athlete development, institutional capacity, and sustainable supporting systems.

International journal of human movement and sports sciencesVol. 14(3)
Partnerships for the goals
Openalex Percentile: Top 4%
Sport Psychology and Performance
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