DIGITAL ENTREPRENEURSHIP: MATHEMATICAL AND COMPUTATIONAL FOUNDATIONS

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Abstrak:

Digital entrepreneurship has emerged as a dominant driver of economic growth in the knowledge economy, relying heavily on mathematical modeling and computational technologies. This article examines the mathematical and computational foundations that underpin digital entrepreneurial activity, including algorithmic thinking, data analytics, optimization models, and computational complexity. Drawing on established research in economics, computer science, and entrepreneurship studies, the paper analyzes how formal mathematical frameworks and computational tools enable opportunity recognition, resource allocation, and scalable digital business models. The results demonstrate that digital entrepreneurship is not solely a managerial or technological phenomenon, but a structurally mathematical and computational process that depends on formal models, algorithms, and data-driven decision systems.

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Nambisan, S. (2017). Digital entrepreneurship: Toward a digital technology perspective of entrepreneurship. Entrepreneurship Theory and Practice, 41(6), pp. 1029–1055, p. 1031.

Autio, E., Nambisan, S., Thomas, L., & Wright, M. (2018). Digital affordances, spatial affordances, and the genesis of entrepreneurial ecosystems. Strategic Entrepreneurship Journal, 12(1), pp. 72–95, p. 75.

Webster, J., & Watson, R. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS Quarterly, 26(2), pp. 13–23, p. 15.

Shapiro, C., & Varian, H. (1999). Information Rules. Harvard Business School Press, pp. 53–58.

Provost, F., & Fawcett, T. (2013). Data Science for Business. O’Reilly Media, pp. 87–92.

Klemperer, P. (2004). Auctions: Theory and Practice. Princeton University Press, pp. 21–30.

Cormen, T., Leiserson, C., Rivest, R., & Stein, C. (2009). Introduction to Algorithms. MIT Press, pp. 22–28.

Dixit, A., & Pindyck, R. (1994). Investment under Uncertainty. Princeton University Press, pp. 135–142.

Arthur, W. B. (2013). Complexity economics: A different framework for economic thought. Santa Fe Institute Working Paper, pp. 5–11.

Mittelstadt, B., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms. Big Data & Society, 3(2), pp. 1–21, p. 7.

Varian, H. (2019). Artificial intelligence, economics, and industrial organization. NBER Working Paper, pp. 9–14.

Teece, D. (2010). Business models, business strategy and innovation. Long Range Planning, 43(2–3), pp. 172–194, p. 178.