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Corporate governance characteristics and default prediction modeling for small enterprises. An empirical analysis of Italian firms

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  • Ciampi, Francesco

Abstract

The aim of this paper is to analyze how the relationship between corporate governance mechanisms and business failure changes in small enterprises (SEs) compared to larger firms.

Suggested Citation

  • Ciampi, Francesco, 2015. "Corporate governance characteristics and default prediction modeling for small enterprises. An empirical analysis of Italian firms," Journal of Business Research, Elsevier, vol. 68(5), pages 1012-1025.
  • Handle: RePEc:eee:jbrese:v:68:y:2015:i:5:p:1012-1025
    DOI: 10.1016/j.jbusres.2014.10.003
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    References listed on IDEAS

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    Cited by:

    1. BoratyƄska, Katarzyna & Grzegorzewska, Emilia, 2018. "Bankruptcy prediction in the agribusiness sector: Lessons from quantitative and qualitative approaches," Journal of Business Research, Elsevier, vol. 89(C), pages 175-181.
    2. Forgione, Antonio Fabio & Migliardo, Carlo, 2018. "Forecasting distress in cooperative banks: The role of asset quality," International Journal of Forecasting, Elsevier, vol. 34(4), pages 678-695.
    3. Oliver Lukason & Art Andresson, 2019. "Tax Arrears Versus Financial Ratios in Bankruptcy Prediction," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(4), pages 1-13, December.
    4. Song, Zhuo-lin & Zhang, Xiao-mei, 2018. "Lending technology and credit risk under different types of loans to SMEs: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 43-69.
    5. Karminsky, A. & Rybalka, A., 2018. "Negative Net Worth of Manufacturing Companies: Corporate Governance and Industry Expectations," Journal of the New Economic Association, New Economic Association, vol. 38(2), pages 76-103.
    6. Zhu, You & Zhou, Li & Xie, Chi & Wang, Gang-Jin & Nguyen, Truong V., 2019. "Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach," International Journal of Production Economics, Elsevier, vol. 211(C), pages 22-33.

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