Keywords
innovation diffusion
forecasting
entrepreneurial performance
Logistic model
Gompertz model
How to Cite
Abstract
Unicorn startups have become symbols of entrepreneurial success and fundamental drivers of innovation and wealth creation. This study examines the diffusion process of unicorns across eight countries (the US, China, India, the UK, Germany, France, the Netherlands, and Sweden) and three industries (Fintech, Health, and Transport). The aim of this research is to model and forecast the diffusion of unicorn startups using three- and four-parameter Logistic and Gompertz sigmoid growth models, leveraging data from the Dealroom database. By addressing this research gap, the study seeks to provide valuable information for policymakers and investors regarding the ultimate potential number of unicorns and the time to saturation. The findings indicate that the Gompertz model generates highly optimistic estimates of unicorn saturation levels, while the Logistic model produces more realistic projections for both fitting existing data and forecasting future trends. Specifically, the three- parameter Gompertz model is suited for analyzing unicorn diffusion in China. The three- parameter Logistic model is appropriate for analyzing unicorn diffusion in the USA, the UK, and all studied sectors. Meanwhile, the four-parameter Logistic model is the best model for explaining unicorn diffusion in India, Germany, France, the Netherlands, and Sweden. The results also reveal that India has the highest estimated speed of unicorn diffusion (97%), while the US exhibits the highest saturation level (6,241 unicorns). Sectoral analysis shows that Fintech has the lowest estimated diffusion speed (43.1%), but the highest saturation level (1,630 unicorns). Our forecasting analyses suggest that all selected countries and sectors — except the US and Fintech — are likely to reach unicorn saturation by around 2030. These findings provide critical insights for planning, regulation, policy formulation, and portfolio decision-making.
References
Куценко Е.С., Остащенко Т.В., Тюрчев К.С. (2022) Релокация как драйвер инновационной активности: глобальное исследование международной миграции основателей компаний-единорогов. Форсайт, 16(4), 6–23. https://doi.org/10.17323/2500-2597.2022.4.6.23
Akin E., Pelen N.N., Tiryaki I. U., Yalcin F. (2020) Parameter Identification for Gompertz and Logistic Dynamic Equations. PLoS ONE, 15, 0230582. https://doi.org/10.1371/journal.pone.0230582
Aldrich H.E., Ruef M. (2018) Unicorns, Gazelles, and Other Distractions on the Way to Understanding Real Entrepreneurship in America. Academy of Management Perspectives, 32(4), 458–472. https://doi.org/10.5465/amp.2017.0123
Armstrong J.S. (ed.) (2001) Principles of Forecasting, Dordrecht: Kluwer Academic Publishers.
Burström T., Lahti T., Parida V., Wartiovaara M., Wincent J. (2023) A definition, review, and extension of global ecosystems theory: Trends, architecture and orchestration of global VCs and mechanisms behind unicorns. Journal of Business Research, 157, 113605. https://doi.org/10.1016/j.jbusres.2022.113605
CB Insights (2023) State of Fintech 2023 Report, New York: CB Insights.
El-Dardiry R., Vogt B. (2023) How far do Gazelles run? Growth patterns of regular firms, high growth firms and startups. Applied Economics, 55(37), 4304–4318. https://doi.org/10.1080/00036846.2022.2128184
Gamboa L.F., Otero J. (2009) An estimation of the pattern of diffusion of mobile phones: The case of Colombia. Telecommunications Policy, 33, 611–620. https://doi.org/10.1016/j.telpol.2009.08.004
Guo K., Zhang T. (2021) Research on the Development Path and Growth Mechanism of Unicorn Enterprises. Mathematical Problems in Engineering, 7, 9960828. https://doi.org/ 10.1155/2021/9960828
Huebl S., Does R., Orlova A., Heckova E., Aschauer D., Kojalek M. (2022) The 2022 European Unicorn & Soonicorn Report, San Francisco, CA: 5Invest.
Jha A., Saha D. (2020) Forecasting and analyzing the characteristics of 3G and 4G mobile broadband diffusion in India: A comparative evaluation of Bass, Norton-Bass, Gompertz, and logistic growth models. Technological Forecasting and Social Change, 152, 119885.
Korkmaz M. (2020) A study over with four-parameter Logistic and Gompertz growth models. Numerical Methods for Partial Differential Equations, 37(3), 2023–2030. https://doi.org/10.1002/num.22641
Kuckertz A., Bernhard A., Berger E.S.C., Dvouletý O., Harms R., Jack S., Kibler E. (2023) Creating and maintaining hope through social entrepreneurship in light of humanitarian crises. Journal of Business Venturing Insights, 19, e00356. https://doi.org/10.1016/j.jbvi.2022.e00356
Kuckertz A., Brandle L., Gaudig A., Hinderer S., Reyes C.A.M., Prochotta A., Steinbrink K.M., Berger E.S.C. (2020) Startups in times of crisis – A rapid response to the COVID-19 pandemic. Journal of Business Venturing Insights, 13, e00169. https://doi.org/10.1016/j.jbvi.2020.e00169
Kuratko D.F., Audretsch D.B. (2021) The future of entrepreneurship: The few or the many? Small Business Economics, 59, 269–278. https://doi.org/10.1007/s11187-021-00534-0
Lee S., Marcu M., Lee S. (2011) An empirical analysis of fixed and mobile broadband diffusion. Information Economics and Policy, 23(3–4), 227–233. https://doi.org/10.1016/j.infoecopol.2011.05.001
Leendertse J., Schrijvers M., Stam E. (2022) Measure Twice, Cut Once: Entrepreneurial Ecosystem Metrics. Research Policy, 51(9), 104336. https://doi.org/10.1016/j.respol.2021.104336
Meade N., Islam T. (2015) Forecasting in telecommunications and ICT-A review. International Journal of Forecasting, 31(4), 1105–1126. https://doi.org/10.1016/j.ijforecast.2014.09.003
Meek S., Cowden B.J. (2023) Strategies of Unicorn startups: How these positive deviants compare to early-stage and Fortune 500 ventures. Journal of Small Business and Enterprise Development, 30(6),1109–1128. https://doi.org/10.1108/JSBED-02-2023-0069
Michalakelis C., Dimitris V., Sphicopoulos T. (2008) Diffusion models of mobile telephony in Greece. Telecommunications Policy, 32(3–4), 234–245. https://doi.org/10.1016/j.telpol.2008.01.004
OECD (2021) Understanding Firm Growth: Helping SMEs Scale Up, Paris: OECD.
Pelinovsky E., Kokoulina M., Epifanova A., Kurkin A., Kurkina O., Tang M., Kirillin M. (2022) Gompertz model in COVID-19 spreading simulation. Chaos, Solitons and Fractals, 154, 111699. https://doi.org/10.1016/j.chaos.2021.111699
Retterath A., Braun R. (2020) Benchmarking Venture Capital Databases (SSRN Paper 3706108). https://doi.org/10.2139/ssrn.3706108
Rodrigues C.D. Noronha M.E.S.D. (2023) What companies can learn from unicorn startups to overcome the COVID-19 crisis. Innovation & Management Review, 20(3), 211–226. https://doi.org/10.1108/INMR-01-2021-0011
Rogers E.M. (1962) Diffusion of Innovations, New York: Free Press.
Rossi M., Martini E. (2019) Venture capitalists and value creation: The role of informal investors in the growth of smaller European firms. International Journal of Globalisation and Small Business, 10(3), pp. 233–247. https://doi.org/10.1504/IJGSB.2019.100123
Satoh D. (2021) Discrete Gompertz equation and model selection between Gompertz and logistic models. International Journal of Forecasting, 37(3),1192–1211. https://doi.org/10.1016/j.ijforecast.2021.01.005
Schumpeter J.A. (1943) Capitalism, Socialism and Democracy, London, New York: Routledge.
Shahid Y. (2023) Can Fast Growing Unicorns Revive Productivity and Economic Performance?, Washington, D.C.: Center for Global Development.
Shane S. (2009) Why encouraging more people to become entrepreneurs is bad public policy. Small Business Economics, 33(2), 141–149. https://doi.org/10.1007/s11187-009-9215-5
Stafeev A. (2024) What makes a successful unicorn startup founder. International Journal of Professional Business Review, 9(5), 4638. https://doi.org/10.26668/businessreview/2024.v9i5.4638
Startup Genome (2022) The Global Startup Ecosystem Report 2022, San Francisco, CA: Startup Genome.
Testa G., Compañó R., Correia A., Rückert E. (2022) In search of EU unicorns – What do we know about them?, Luxembourg: Publications Office of the European Union. https://doi.org/10.2760/843368
Trabucchi D., Talenti L., Buganza T. (2019) How do Big Bang Disruptors look like? A Business Model perspective. Technological Forecasting and Social Change, 141, 330–340, https://doi.org/10.1016/j.techfore.2019.01.009
Urbinati A., Chiaroni D., Chiesa V., Frattini F. (2018) The Role of Business Model Design in the Diffusion of Innovations: An Analysis of a Sample of Unicorn-Tech Companies. International Journal of Innovation and Technology Management, 16(1), 1950011. https://doi.org/10.1142/S0219877019500111
Van Meeteren M., Trincado-Munoz F., Rubin T.H., Vorley T. (2022) Rethinking the digital transformation in knowledge-intensive services: A technology space analysis. Technological Forecasting and Social Change, 179, 121631. https://doi.org/10.1016/j.techfore.2022.121631
Venâncio A., Picoto W., Pinto I. (2023) Time-to-unicorn and digital entrepreneurial ecosystems. Technological Forecasting and Social Change, 190, 122425. https://doi.org/10.1016/j.techfore.2023.122425
Veugelers R., Amaral-Garcia S. (2025) Financing EU Health Innovation: The Role of Venture Capital, Seville: JRC.
WIPO (2023) Global Innovation Index 2023: Innovation in the Face of Uncertainty, Geneva: World Intellectual Property Organization. https://doi.org/10.34667/tind.48220