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James Xiaolong Wang

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#generative ai Review Open access Sep 2026

Youth Entrepreneurship in the Digital Era: A Systematic Review and Capability Formation-Activation Framework

Many young people express interest in becoming entrepreneurs, but far fewer go on to start and sustain a venture. This review examines why by synthesizing 115 peer-reviewed articles from three related areas often studied separately: young people’s entrepreneurial motivation, entrepreneurship education, and the role of digital platforms and AI in starting ventures. Using the Search, Appraisal, Synthesis, and Analysis (SALSA) framework, the review finds that entrepreneurial intention matters but does not reliably predict action. Instead, whether intention becomes action depends on access to finance, networks, institutional legitimacy, and opportunities to test ideas at manageable risk. Entrepreneurship education, in turn, can build self-efficacy, opportunity recognition, and decision-making skills, particularly through experiential learning, but its effect on venture creation remains unclear because most existing studies end before later entrepreneurial activity can be observed. Digital platforms and generative AI may relax some of these constraints by reducing the costs of information, experimentation, and market access. However, they can also create reliance on platforms and encourage young founders to trust AI outputs they cannot yet assess. Drawing these findings together, the review develops a capability formation-activation framework that treats intention as revisable and separates the capabilities young people develop from the conditions needed to use them. The framework clarifies why capability does not consistently lead to action, and suggests that programs and digital tools should be judged not only by whether they raise entrepreneurial intention or technology use, but by whether they help young people persist, adapt, and decide responsibly when to stop.

J. Wang · 0 citations
Aug 2026

AI: The scientific revolution that risks being undermined by the digital divide

Artificial Intelligence (AI) is reshaping scientific discovery, industrial organization, labor, and governance, with major implications for international development. AI can accelerate innovation in areas key to international development, yet the same systems can also reproduce bias, unsafe automation, environmental burdens, dependency, and unequal exposure to harms. Because the compute, data, infrastructure, and expertise needed to develop and govern advanced AI remain concentrated, the AI digital divide concerns not only who gains access, but who bears costs, who gives consent, and who shapes priorities short and long-term. This article argues that AI's developmental value, when applied to the most critical international development challenges humanity faces, still depends on the geopolitical, institutional, environmental, labor, and ethical conditions that determine how AI development and deployment benefits and risks are distributed.

Marta Koch, James Xiaolong Wang, Shreya Ravikumar et al. · 1 citation

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