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Econometric Estimation of the Factors That Influence Startup Success

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  • Carlos Díaz-Santamaría

    (Institute of Tourism and Sustainable Economic Development (TIDES), Campus de Tafira, University of Las Palmas de Gran Canaria, 35017 Las Palmas, Spain)

  • Jacques Bulchand-Gidumal

    (Institute of Tourism and Sustainable Economic Development (TIDES), Campus de Tafira, University of Las Palmas de Gran Canaria, 35017 Las Palmas, Spain)

Abstract

Technology startups are important regional economic engines that are recognized as drivers of sustainable economic growth. Understanding the factors that influence their success is of interest both to the scientific community and to practitioners. However, there is currently no consensus in the literature on how to define the success of a technology startup. Startup success has multiple dimensions and different theoretical approaches and empirical contexts. Therefore, in the present work, our aim is to identify ways of measuring the success of a technology startup. Using a review of the literature and interviews with entrepreneurs and venture capital investors, we identified two common success indicators: achieving significant revenue and obtaining financing. We then analyzed the factors that have the greatest impact on startup success using 340 startups. We used a multivariate model based on independent econometric estimates for each of the two ways of defining the success of a technology startup. The main conclusion is that there are four factors that have a significant influence on the two ways of measuring success: the location of the startup, the promoting partners’ dedication, the age of the company, and the existence of nonpromoting partners.

Suggested Citation

  • Carlos Díaz-Santamaría & Jacques Bulchand-Gidumal, 2021. "Econometric Estimation of the Factors That Influence Startup Success," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:2242-:d:502033
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    3. Lele Cao & Vilhelm von Ehrenheim & Sebastian Krakowski & Xiaoxue Li & Alexandra Lutz, 2022. "Using Deep Learning to Find the Next Unicorn: A Practical Synthesis," Papers 2210.14195, arXiv.org, revised Jun 2024.
    4. Jaroslaw Korpysa & Uma Shankar Singh & Swapnil Singh, 2023. "Validation of Decision Criteria and Determining Factors Importance in Advocating for Sustainability of Entrepreneurial Startups towards Social Inclusion and Capacity Building," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    5. Javier Sevilla-Bernardo & Blanca Sanchez-Robles & Teresa C. Herrador-Alcaide, 2022. "Success Factors of Startups in Research Literature within the Entrepreneurial Ecosystem," Administrative Sciences, MDPI, vol. 12(3), pages 1-24, August.
    6. Husam Wahdan & Zeng Rui Tian, 2022. "Assessing the Efficiency of Venture Capital Functioning in the Transforming Economy in UAE and China by a Mathematical Model," SAGE Open, , vol. 12(1), pages 21582440211, January.
    7. Sayed Saghaian & Hosein Mohammadi & Morteza Mohammadi, 2022. "Factors Affecting Success of Entrepreneurship in Agribusinesses: Evidence from the City of Mashhad, Iran," Sustainability, MDPI, vol. 14(13), pages 1-12, June.

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