Designing the Structural Equations Model of The Digital Entrepreneurship Ecosystem Based on Launching Sports Startups

Subject Areas : Management and health

Pejman Golara ¹ , Fahimeh AdibSaber ² , Mehran Nasiri ³

1 - Department of Physical Education, Rasht Branch, Islamic Azad University, Rasht, Irann
2 - Department of Physical Education, Rasht Branch, Islamic Azad University, Rasht, Iran
3 - Department of Physical Education, Bandar Anzali Branch, Islamic Azad University, Bandar Anzali, Iran. Email

Received: 2024-09-26 Accepted : 2026-02-09 Published : 2025-04-09

Keywords: sports ecosystem, entrepreneurial ecosystem, digital entrepreneurship, sports startups, sports businesses,

Abstract :

Introduction

Digital technology has expanded the boundaries and changed the processes, outcomes of entrepreneurship and the evolution of the players of the entrepreneurial ecosystem (Nelson & Bayer, 2010).  Changes in sports have increased through access to the Internet and technology. Therefore, there is value and positive outcomes associated with entrepreneurship in sports, which is due to the increasing convergence of business and technology in sports (Jenny et al., 2016).  Startups can exist in different sectors of the sports industry from manufacturing sports equipment to developing new online services. The greatest growth of sports businesses has been related to digital and social media. This is due to people’s desire to experience sports in a new way based on technological advances (Ratten, 2021). Sports startups, as part of the digital entrepreneurship ecosystem, face several challenges. Several factors such as technological infrastructure, investment, interactive networks, and government support play a role in the success of these startups, but the relationships between these factors are not fully understood (Ramzaninezhad et al., 2019). Based on the above, it can be said that in Iran, start-up businesses can provide a suitable environment for creating employment. In the current decade, one of the biggest challenges and most important problems of the country’s sports industry is entrepreneurship and employment. Sports, as a developing industry, has many entrepreneurial opportunities. Previous studies have not presented a suitable model for new businesses in the field of digital sports entrepreneurship. The present study, while helping to properly guide new businesses and new sports startups in the country, can also be a background and model for other research. Methodology

The present study is descriptive-correlational and based on the structural equation model. The statistical population of the study included university lecturers and researchers in the field of digital entrepreneurship, members of the management team of startups and sports businesses, managers and experts in sports and digital businesses, consultants and analysts in the field of digital entrepreneurship. A sufficient number of statistical samples were selected and surveyed in a purposeful and accessible manner to test the model (167 people). Given the lack of face-to-face access to the research samples, an electronic questionnaire was created to collect data and was provided to the research samples in a purposeful manner. The research tools were a researcher-made questionnaire based on the qualitative survey phase of the research. The questionnaire included 9 main factors: technology and innovation, research and development, digital sports entrepreneurship ecosystem, government support and laws, access to capital, acceptance of failure and learning culture, networking and strategic partnerships, marketing and customer acquisition, digital entrepreneurship and launching startups (9 main variables, 30 dimensions and 76 items). To assess the content and face validity, expert professors and researchers (PhD in Sports Management) with a background in digital entrepreneurship and startups were consulted. After confirming the content validity, the tool was first distributed in a pilot study among 30 people from the statistical community, and the Cronbach's alpha coefficient was calculated to be 0.75. After fixing the problems related to questions with low alpha, the questionnaire was distributed and collected in the main stage, and composite reliability was calculated and approved in SmartPLS software. The Kolmogorov-Smirnov test was used to test the normality of the data, and the results showed that most of the values ​​of the variables were less than 0.05 and non-normal; as a result, the structural equation model method was used to examine the relationship between the statistical hypotheses using SmartPLS software (Hair et al., 2019).

Results

The results of factor analysis of the dimensions of the research variables showed that the dimensions of information collection and data analysis tools, artificial intelligence and customer management and digital platforms were significantly explaining technology and innovation with coefficients of 0.85, 0.82 and 0.77 respectively. The dimensions of product innovation, market studies and development of new technologies were significantly explaining research and development with coefficients of 0.85, 0.84 and 0.83 respectively. The dimensions of digital sports coaching and mentoring and workshops and networking events and digital entrepreneurship business training were significantly explaining the digital sports entrepreneurship ecosystem with coefficients of 0.86, 0.86 and 0.74 respectively. The dimensions of innovation support policies, tax and incentive supports, and business simplification regulations significantly explained government support and laws with coefficients of 0.90, 0.85, and 0.84, respectively. The dimensions of government subsidies and budgets, technology-related investment, and crowdfunding significantly explained access to capital with coefficients of 0.87, 0.83, and 0.80, respectively. The dimensions of failure analysis, environments encouraging continuous learning (0.88), and support structures for failures significantly explained failure acceptance and learning culture with coefficients of 0.91, 0.88, and 0.81, respectively. The dimensions of academic interactions, industry alliances, and international partnerships significantly explained networking and strategic collaborations with coefficients of 0.95, 0.94, and 0.90, respectively. The dimensions of digital marketing, user experience and user interface, and digital branding strategies significantly explained marketing and customer acquisition with coefficients of 0.91, 0.89, and 0.86, respectively. The dimensions of gaining experience, community building, changing attitudes, creating motivation, flexibility in employment, culture building, and welfare and better life significantly explained the development of digital entrepreneurship and launching startups with coefficients of 0.86, 0.82, 0.79, 0.79, 0.70, 0.68, and 0.63, respectively.

Also, based on path analysis, it was found that the effect of technology and innovation (0.18), research and development (0.66) on the digital sports entrepreneurship ecosystem was positive and significant. The effect of the digital sports entrepreneurship ecosystem on networking and strategic partnerships (0.69) and marketing and customer acquisition (0.37) was positive and significant. The effect of government support and laws with a coefficient of (0.16), access to capital (0.65) and acceptance of failure and learning culture (0.61) on networking and strategic partnerships was positive and significant. The effect of acceptance of failure and learning culture (0.45) on marketing and customer acquisition was positive and significant. The effect of networking and strategic partnerships (0.70) and customer acquisition and acquisition (0.66) on the development of digital entrepreneurship and startup launch was positive and significant.

Discussion and Conclusion

In general, to develop and expand the sports startup market in the digital entrepreneurship ecosystem, it is necessary for the private and public sectors to interact with each other, provide the necessary financial support and simplify the rules for sports entrepreneurs, and enable entrepreneurs, physical education students, universities, and sports organizations in the country to offer joint services to their customers through synergy and interaction. In the meantime, technological infrastructures should also be used creatively and based on customer needs, so that, while creating a suitable business environment for sports graduates, the ground for creating new businesses and trades is provided, and in this way, the path to employment in the field of sports and sustainable economic growth is paved.

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