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Entrepreneurship support ways after the COVID-19 crisis

Author

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  • Manuel Chaves-Maza

    (Pablo de Olavide University, Spain)

  • Eugenio M. Fedriani Martel

    (Pablo de Olavide University, Spain)

Abstract

The impact of the COVID-19 on Europe economy has been similar to that produced in the 2008 crisis, even with worse long-term consequences. Most governments have implemented recovery plans similar to those that were then implemented. However, there are differences in the economic impact that require different methodologies which focus on the microenvironment. Entrepreneurs’ sponsorship may help to recover the current socio-economic situation. Simultaneously, technological progress in Artificial Intelligence and Big Data allows the analysis of vast amounts of information and support decision making. This paper shows a brief introduction of entrepreneurship policy in twenty countries after the irruption of the Covid-19 to contextualize, and applies Artificial Intelligence to examine factors whose influence is strong in the survival rate of entrepreneurs within a public support program. Specifically, two types of artificial networks are used: self-organizing maps and multilayer perceptron (respectively, SOM and MLP). After the application of neural networks on a data set of 2,221 entrepreneurs from Andalusia (Spain) and with 769 variables taken during the recovery after the crisis from 2008 to 2012, the prediction in the probability of entrepreneurial survival and business success is shown to be realistic in more than 98% of individuals analysed.

Suggested Citation

  • Manuel Chaves-Maza & Eugenio M. Fedriani Martel, 2020. "Entrepreneurship support ways after the COVID-19 crisis," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(2), pages 662-681, December.
    • Handle: RePEc:ssi:jouesi:v:8:y:2020:i:2:p:662-681
    DOI: 10.9770/jesi.2020.8.2(40)
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    References listed on IDEAS

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    Cited by:

    1. Manuel Chaves-Maza & Eugenio M. Fedriani, 2022. "Defining entrepreneurial success to improve guidance services: a study with a comprehensive database from Andalusia," Journal of Innovation and Entrepreneurship, Springer, vol. 11(1), pages 1-26, December.
    2. Sorin-Ciprian Teiusan & Sorin-Constantin Deaconu, 2021. "Artificial Intelligence And Covid-19: An Analysis In Business And Economics," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 5, pages 144-156, October.
    3. Michela Piccarozzi & Cecilia Silvestri & Patrizio Morganti, 2021. "COVID-19 in Management Studies: A Systematic Literature Review," Sustainability, MDPI, vol. 13(7), pages 1-28, March.

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    More about this item

    Keywords

    entrepreneurship; sponsorship; Artificial Neural Networks (ANN); Self-Organizing Maps (SOM); Multilayer Perceptron (MLP);
    All these keywords.

    JEL classification:

    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship
    • L38 - Industrial Organization - - Nonprofit Organizations and Public Enterprise - - - Public Policy
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development

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