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Digitalization and new SME formation: A regional analysis

Author

Listed:
  • Evgeniya Shenkman

    (HSE University, Perm, Russian Federation)

  • Anastasia Kireecheva

    (HSE University, Perm, Russian Federation)

  • Irina Maksimova

    (HSE University, Perm, Russian Federation)

Abstract

The article examines the impact of regional digitalization on the formation of new small and medium-sized enterprises (SMEs) in Russia over the period 2018–2022. Despite the growing role of digital technologies in business, their direct impact on the creation and development of new SMEs remains understudied. This study aims to fill this gap by providing a scientifically grounded basis for developing effective state support policies and strategies for sustainable growth in the entrepreneurial sector. The chosen methodology is CS-ARDL, which eliminates cross-sectional dependence in the data and allows for the estimation of both short-term and long-term effects. The empirically validated results confirm that digitalization contributes to an increase in the number of new SMEs in both the short and long run, particularly in regions with moderate or high levels of digital business development. The findings suggest specific measures to enhance regional digitalization through a differentiated approach, ensuring a more uniform impact of digital transformation and improving the effectiveness of SME support policies.

Suggested Citation

  • Evgeniya Shenkman & Anastasia Kireecheva & Irina Maksimova, 2026. "Digitalization and new SME formation: A regional analysis," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), vol. 83, pages 92-115.
  • Handle: RePEc:ris:apltrx:023601
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    References listed on IDEAS

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    JEL classification:

    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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