IDEAS home Printed from https://ideas.repec.org/a/imx/journl/v18y2023i2p9.html
   My bibliography  Save this article

Factores de fracaso en las MiPyME de México evidenciados por el COVID-2019

Author

Listed:
  • Israel Patiño-Galvan

    (Tecnológico de Estudios Superiores de Ecatepec, México)

  • José Alberto Hernández Aguilar

    (Universidad Autónoma del Estado de Morelos, México)

Abstract

Antes de la pandemia el desarrollo económico de las Micro, Pequeñas y Medianas Empresas (MiPyME) en Latinoamérica presentaba indicios paulatinos de recuperación tras los problemas presentados en los años 2009 y 2016. México a partir del 2017 mantuvo una inflación creciente del 5% promedio, el precio de los energéticos aumentó en un 20%, el crecimiento de la deuda externa un 12% y el PIB fue menor al 1.6% anual (Banco Mundial, 2020), (OCDE, 2019), (INEGI, 2018). Para finales del 2019, el SARS-CoV-2 (COVID - 2019) evidenció factores de fracaso que agudizaron la permanencia de las MiPyME ya que cerraron más del 30.6% de ellas (Naciones Unidas, 2021). En esta investigación se discuten dichos factores, para ello, se recopiló información del comportamiento económico, y de estudios cuantitativos de los sectores comerciales, manufactura y servicios. Para identificar estos factores, se encuestaron a 246 MiPyME mexicanas que cerraron entre septiembre del 2019 y diciembre del 2020, las cuales fueron seleccionadas mediante muestreo aleatorio estratificado. Los resultados evidenciaron factores de fracaso asociados a las capacidades del administrador y a aspectos internos de la empresa, entre los que destacan la falta de visión para identificar nuevos negocios y poco conocimiento de las Tecnologías de la Información.

Suggested Citation

  • Israel Patiño-Galvan & José Alberto Hernández Aguilar, 2023. "Factores de fracaso en las MiPyME de México evidenciados por el COVID-2019," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 18(2), pages 1-29, Abril - J.
    • Handle: RePEc:imx:journl:v:18:y:2023:i:2:p:9
    as

    Download full text from publisher

    File URL: https://www.remef.org.mx/index.php/remef/article/view/739
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    2. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    3. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    4. Everett, Jim & Watson, John, 1998. "Small Business Failure and External Risk Factors," Small Business Economics, Springer, vol. 11(4), pages 371-390, December.
    5. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    6. Erkki K. Laitinen & Teija Laitinen, 1998. "Cash Management Behavior and Failure Prediction," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 25(7&8), pages 893-919.
    7. Erkki K. Laitinen & Teija Laitinen, 1998. "Cash Management Behavior and Failure Prediction," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 25(7‐8), pages 893-919, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Şaban Çelik, 2013. "Micro Credit Risk Metrics: A Comprehensive Review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(4), pages 233-272, October.
    2. Fayçal Mraihi, 2016. "Distressed Company Prediction Using Logistic Regression: Tunisian’s Case," Quarterly Journal of Business Studies, Research Academy of Social Sciences, vol. 2(1), pages 34-54.
    3. Fedorova, Elena & Ledyaeva, Svetlana & Drogovoz, Pavel & Nevredinov, Alexandr, 2022. "Economic policy uncertainty and bankruptcy filings," International Review of Financial Analysis, Elsevier, vol. 82(C).
    4. Fernando Zambrano Farias & María del Carmen Valls Martínez & Pedro Antonio Martín-Cervantes, 2021. "Explanatory Factors of Business Failure: Literature Review and Global Trends," Sustainability, MDPI, vol. 13(18), pages 1-26, September.
    5. Philippe Jardin & David Veganzones & Eric Séverin, 2019. "Forecasting Corporate Bankruptcy Using Accrual-Based Models," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 7-43, June.
    6. Fayçal Mraihi & Inane Kanzari & Mohamed Tahar Rajhi, 2015. "Development of a Prediction Model of Failure in Tunisian Companies: Comparison between Logistic Regression and Support Vector Machines," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(3), pages 184-205.
    7. Nandita Mishra & Shruti Ashok & Deepak Tandon, 2024. "Predicting Financial Distress in the Indian Banking Sector: A Comparative Study Between the Logistic Regression, LDA and ANN Models," Global Business Review, International Management Institute, vol. 25(6), pages 1540-1558, December.
    8. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    9. Thomas E. Mckee, 2000. "Developing a bankruptcy prediction model via rough sets theory," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 9(3), pages 159-173, September.
    10. Keijo Kohv & Oliver Lukason, 2021. "What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains," Risks, MDPI, vol. 9(2), pages 1-19, January.
    11. Koen W. de Bock, 2017. "The best of two worlds: Balancing model strength and comprehensibility in business failure prediction using spline-rule ensembles," Post-Print hal-01588059, HAL.
    12. Katarina Valaskova & Dominika Gajdosikova & Jaroslav Belas, 2023. "Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 253-293, March.
    13. Manuel D. N. T. Oliveira & Fernando A. F. Ferreira & Guillermo O. Pérez-Bustamante Ilander & Marjan S. Jalali, 2017. "Integrating cognitive mapping and MCDA for bankruptcy prediction in small- and medium-sized enterprises," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 985-997, September.
    14. Błażej Prusak, 2018. "Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries," IJFS, MDPI, vol. 6(3), pages 1-28, June.
    15. George Giannopoulos & Sophia Ali Sardar & Rebecca Salti & Nicos Sykianakis, 2022. "Analyzing Insolvency Prediction Models in the Period Before and After the Financial Crisis: A Case Study on the Example of US Firms," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 12(3), pages 23-45.
    16. Christian Lohmann & Thorsten Ohliger, 2020. "Bankruptcy prediction and the discriminatory power of annual reports: empirical evidence from financially distressed German companies," Journal of Business Economics, Springer, vol. 90(1), pages 137-172, February.
    17. Paras Arora & Suman Saurabh, 2022. "Predicting distress: a post Insolvency and Bankruptcy Code 2016 analysis," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 604-622, July.
    18. Salwa Kessioui & Michalis Doumpos & Constantin Zopounidis, 2023. "A Bibliometric Overview of the State-of-the-Art in Bankruptcy Prediction Methods and Applications," World Scientific Book Chapters, in: Emilios Galariotis & Alexandros Garefalakis & Christos Lemonakis & Marios Menexiadis & Constantin Zo (ed.), Governance and Financial Performance Current Trends and Perspectives, chapter 6, pages 123-153, World Scientific Publishing Co. Pte. Ltd..
    19. Soo Young Kim, 2018. "Predicting hospitality financial distress with ensemble models: the case of US hotels, restaurants, and amusement and recreation," Service Business, Springer;Pan-Pacific Business Association, vol. 12(3), pages 483-503, September.
    20. Oliver Lukason & Art Andresson, 2019. "Tax Arrears Versus Financial Ratios in Bankruptcy Prediction," JRFM, MDPI, vol. 12(4), pages 1-13, December.

    More about this item

    Keywords

    MiPyME; factores de fracaso; desarrollo económico;
    All these keywords.

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O54 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Latin America; Caribbean

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:imx:journl:v:18:y:2023:i:2:p:9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ricardo Mendoza (email available below). General contact details of provider: https://www.remef.org.mx/index.php/remef/index .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.