Abstract
The aim of the present study was to design a model for the evolution of digital entrepreneurship ecosystems. The research method was qualitative and based on grounded theory. The research field included digital management and entrepreneurship experts in 2024, selected through purposive sampling and snowball technique. Data were collected through semi-structured interviews with 15 participants until theoretical saturation and analyzed using Strauss and Corbin's three-stage coding method using MAXQDA software. The interviews were transcribed and 283 open codes and 16 axial codes were extracted. The findings showed that digital entrepreneurship, as a central phenomenon, based on digital technologies such as artificial intelligence and blockchain, creates value through innovation and agility. Causal factors (organizational factors, technological infrastructure, and human factor), contextual (legal, socio-cultural frameworks), and intervention factors (economic-market, security) dynamically interact to shape this phenomenon. The pivotal relationships include the impact of causal factors on resource creation, the role of contextual factors in sustainability, moderation by intervention factors, and facilitation of development by strategies. The consequences include economic growth, job creation, financial transparency, improved quality of life, and digital justice. It is suggested that the government improve digital infrastructure, develop supportive laws, expand digital education, create venture capital funds, and strengthen public acceptance of digital entrepreneurship through culture building.
Introduction
Digital entrepreneurship has become one of the most powerful engines of economic development, innovation, and job creation in the contemporary world (Kraus et al., 2020; Nambisan & Baron, 2021). In Iran, despite a young and educated workforce (over 60% of the population is under 35 years of age), high smartphone penetration (over 90%), and over 75 million internet users (Arabgari et al., 2024), the digital entrepreneurship ecosystem is still in its infancy and faces numerous structural, legal, cultural, and economic barriers. Previous studies in Iran have mainly examined separate aspects of this phenomenon, such as legal barriers (Azizi et al., 2018), infrastructure bottlenecks (Jahangiri & Hosseini, 2022), financing constraints (Didehkhani et al., 2020), or cultural resistance (Rastgar et al., 2019). To date, no comprehensive indigenous model has been presented that simultaneously integrates causal conditions, contextual and intervening factors, strategies, and outcomes within the specific institutional framework of Iran—especially under international sanctions and domestic policy fluctuations. Global models (Sussan & Acs, 2017; Isenberg, 2016), designed in open and stable economies, cannot be directly transferred to a context where cryptocurrencies are a means of circumventing sanctions and national security considerations dominate digital policymaking. The present study, with a qualitative approach and utilizing the systematic data-driven theory methodology of Strauss and Corbin (Strauss & Corbin, 1998), seeks to fill this theoretical and practical gap by designing a transformative model of the digital entrepreneurship ecosystem in Iran. This research is important in designing a transformation model of digital entrepreneurship ecosystems in Iran for several reasons. First, these ecosystems can contribute to economic growth and job creation, especially under sanctions conditions where the Iranian economy is facing serious challenges (Bloom et al., 2020). Second, digital entrepreneurship improves the quality of products and services by promoting innovation and increasing competitiveness (Martinez, 2022). Third, given Iran’s unique characteristics, such as young human resources and natural resources, a local model can help better exploit these potentials (Jahangiri & Hosseini, 2022). In addition, the lack of a comprehensive model in the domestic literature highlights the need for this research (Didehkhani et al., 2020).
The main research question is: What are the components of the evolution model of digital entrepreneurship ecosystems in Iran? The sub-questions are: What are the components, causal, intervening, contextual factors, strategies, and consequences of designing digital entrepreneurship ecosystems in Iran?
Theoretical Framework
Digital entrepreneurship has rapidly become one of the transformative forces for economic growth, innovation, job creation, and social inclusion in the 21st century (Elia et al., 2020; Ferreira et al., 2024). Unlike traditional entrepreneurship, this type of entrepreneurship fundamentally changes the mechanisms of value creation, delivery, and absorption by leveraging digital technologies, platforms, and data-driven models (Cavallo et al., 2021). In advanced countries, digital entrepreneurship ecosystems are the backbone of sustainable development and competitiveness (Du et al., 2019). However, in Iran, despite its enormous potential, this ecosystem is fragmented and underdeveloped. Iranian digital startups face a unique combination of internal and external barriers: chronic infrastructure shortages (unstable high-speed internet and frequent filtering), severe international sanctions that limit access to global payment gateways, cloud services, and venture capital (Didehkhani et al., 2020), macroeconomic instability, institutional volatility, brain drain, and cultural lag in public trust in online transactions (Jahangiri & Hosseini, 2022). This research gap necessitated the need for data-driven and context-sensitive research to design a transformative model tailored to Iran’s specific institutional environment (Golara et al., 2025; Khaghanizadeh et al., 2025). 
Research Methodology
This study used a qualitative design using Strauss & Corbin’s (1998) systematic data-driven theory methodology. The study was conducted between March and September 2024. The research population included experts and those with experience in the Iranian digital entrepreneurship ecosystem: founders of successful and unsuccessful startups, platform CEOs, angel investors, and university professors specializing in entrepreneurship and information technology, and senior consultants. Sampling was initially purposive and then continued with a snowball method until theoretical saturation was reached at the fifteenth interview (a sample size consistent with qualitative grounded theory studies in the field of entrepreneurship; Golara et al., 2025; Arabgari et al., 2024). Data were collected through 60- to 90-minute in-depth semi-structured interviews (in person or online with encrypted platforms). Simultaneous analysis with data collection was performed with MAXQDA 2022 software and three-stage coding (open, axial, and selective) was performed, resulting in the extraction of 283 open codes and 16 axial codes. Research validity was ensured by Lincoln & Guba (1985) criteria: validity through extended interaction, member review, and triangulation; transferability through thick descriptions; reliability and confirmability through a full audit trail, peer review, and reflective note-taking.
Research findings
The central phenomenon of the “digital entrepreneurship” model was defined as the creation and scaling of technology-based, platform-driven, and data-driven businesses that create value through innovation, organizational agility, and diverse revenue models (in-app payments, digital advertising, sharing, gig economy, and blockchain transactions). Causal conditions include three main categories: organizational factors (management innovation, informal partnerships with foreign companies, a culture of agility, and strategic use of cryptocurrencies to circumvent sanctions), technological infrastructure (access to high-speed internet, artificial intelligence, big data, domestic cloud computing, and development of native APIs), and human factors (high skills of the younger generation, entrepreneurial motivation due to unemployment, but the severe challenge of brain drain). The broader context includes legal-political frameworks (fragmented government protections against heavy bureaucracy, filtering, and sudden changes in laws) and socio-cultural developments (increased digital consumption among Generation Z alongside traditional resistance to trusting online payments). Intervening factors also fall into two categories: economic-market dynamics (rapid growth of online markets, new revenue models, and the negative impact of inflation and devaluation of the rial) and credit-security concerns (cyber threats, weak e-trust mechanisms, and lack of a comprehensive data protection law). To accelerate development, five key strategies emerged: improving digital infrastructure, legal and structural reforms (reducing bureaucracy, intellectual property law, and digital free zones), culture and education (media campaigns and digital literacy education in schools), diversifying financing (stock market venture capital funds, crowdfunding, and low-interest loans), and systematically developing digital entrepreneurship competencies (training in artificial intelligence, blockchain, and agile management). The final outcomes emerged at two levels: economic outcomes (sustainable growth, widespread job creation, especially in freelancing and the gig economy, earning foreign exchange, reducing dependence on oil, and financial transparency through blockchain) and Social (improving the quality of life, expanding digital justice, developing online education, and forming an entrepreneurial culture in the younger generation.
Discussion and Conclusion
The presented transformational model is the first comprehensive and completely indigenous framework that is derived solely from the lived experiences of Iranian stakeholders and extends global theories to an institutional environment under sanctions (Elia et al., 2020; Ferreira et al., 2024). While organizational agility, technological infrastructure, and human capital are consistent with international findings (Kraus et al., 2020; Martinez, 2022), the distinctly Iranian elements such as “strategic use of cryptocurrencies as a survival tool,” “filtering as a permanent but creative obstacle to circumvention,” “brain drain as an existential threat,” and “the moderating role of geopolitical insecurity” show why general models (Sussan & Acs, 2017) are ineffective in Iran. This model is also consistent with recent domestic studies but goes beyond them because it integrates all dimensions into a dynamic paradigmatic structure (Golara et al., 2025; Arabgari et al., 2024; Khaghanizadeh et al., 2025).
In practical terms, policymakers should prioritize the deployment of nationwide high-speed internet and 5G in the Seventh Development Plan, launch secure national payment gateways independent of SWIFT, enact a comprehensive law on data protection and intellectual property by the end of 1404, create specialized digital venture capital funds on the stock exchange, and implement a national digital literacy program from primary school to university. Universities should launch interdisciplinary courses in AI-entrepreneurship, blockchain, and digital marketing, and strengthen industry-university linkages through university accelerators. Entrepreneurs should focus on scalable business models with near-zero marginal costs, establish a startup alliance for Lobby and use informal networks to access global technologies.
Despite the depth of the field, the qualitative nature, and the purposive sampling, statistical generalizability is limited. Future research should quantitatively validate the model by structural equation modeling on larger samples, conduct longitudinal comparisons with similar countries (Turkey, UAE, Russia), and examine the impact of new policies (such as possible sanctions relief or filtering changes). Finally, the proposed model provides policymakers, universities, investors, and entrepreneurs with an operational and localized roadmap to transform Iran’s demographic and digital potential into a regionally competitive ecosystem, thereby achieving sustainable economic diversification, sustainable youth employment, and social progress in the digital age.