Parveen Kumar
Chaudhary Ranbir Singh University

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Modelling Identification of Factors Affecting the Development of Sports Entrepreneurship Opportunities in The Field of Sports Education and Research Ari Tri Fitrianto; Aulia Putri Yuliasti; Andi Kasanrawali; Dessalegn Wase Mola; Parveen Kumar
Journal of Sport Science and Education Vol 10 No 1 (2025)
Publisher : Faculty of Sport and Health Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jossae.v10n1.p47-57

Abstract

Entrepreneurship development is a priority across all sectors, including the field of sports. This study sought to construct a model and determine the key factors that drive the expansion of entrepreneurial opportunities within sports education and research. Employing an exploratory-consequential approach with applied and developmental aims, the study was conducted in two phases. The qualitative phase involved semi-structured interviews with ten experts comprising academics, entrepreneurs, and sports administrators selected through convenience sampling. The quantitative phase included 52 randomly selected participants from the same population. Data collection instruments consisted of semi-structured interviews and a custom-designed questionnaire utilizing a 5-point Likert scale. Data analysis was performed using partial least squares structural equation modeling via SmartPLS 4. Exploratory factor analysis identified 52 items distributed across eight constructs. All constructs demonstrated strong validity and reliability, with factor loadings and AVE values exceeding 0.70. The final structural model exhibited a good overall fit and confirmed a significant positive impact of all eight factors (P < 0.001). The findings underscore the critical role of these dimensions in advancing sports entrepreneurship and suggest that reinforcing them could enhance the entrepreneurial framework within the domain of sports education and research.
A Meta-Analytic Approach to Swimming Performance Prediction: Reviewing Methods, Datasets, and Research Trends Ari Tri Fitrianto; Muhammad Habibie; Parveen Kumar
Indonesian Journal of Kinanthropology (IJOK) Vol 5 No 2 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/ijok.v5n2.p53-71

Abstract

Background: Pico seems likely to be successful in competitive sports, particularly swimming, including the next Olympic swimming competition. The current manuscript offers a detailed insight into research on the prediction of swimming performance, between 2014 and 2024. Methods: This Swimming Performance Prediction research used the Systematic Literature Review (SLR) approach. Furthermore, to narrow down the articles relevant to research topics reviewed, this study adhered to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) when performing the systematic review. We find 21 journal publications from the representative studies for seeking identification and analysis for describing research topics or trends, datasets, techniques, methods, evaluations and problems in this research field. Results: The analyses presented provide detailed information on the topics and trends under investigation in the field of predictions for the prediction of swimming performance, reference to public datasets and the techniques and method often used in comparisons between researchers respectively. Conclusions: Swimming performance prediction plays an important role in improving training programs, guiding athlete selection, and evaluating progress.