IDEAS home Printed from https://ideas.repec.org/a/aml/intbrm/v4y2013i4p132-137.html
   My bibliography  Save this article

An Empirical Case Study on Prediction of Corporate Failure in The Selected Industrial Unit in India

Author

Listed:
  • Krishn Awatar Goyal

    (B.N. (P.G.) College, Udaipur, India)

Abstract

Industrial Sickness has been growing in such large proportions that in the wake of industrial development, a large number of new units covering all types of units in small, medium and large sectors are added in this category. The rapid growth and magnitude of industrial sickness is puzzling issue not only for present time but also for all times to come, especially for India. It has become a matter of serious concern for all; concerned directly or indirectly with the industrial units; not only because Billions of rupees locked up in Millions of sick units but also for the fortunes for numerous classes to be affected. The failure of a unit is an event which brings a lot of mental torture to entrepreneurs, managers and to their families. The society is also affected by the phenomenon of sickness as unemployment spreads widely, availability of goods and services decrease and the prices soar up. The share holders lose their hard-earned savings. Creditors lose their cash and future prospects of business. The socio-economic implications of industrial sickness are so severe that it may disturb the whole industrial climate. Under such scenario this study on “An Empirical Case Study on Prediction of Corporate Failure in the Selected Industrial Unit in India” is an attempt to identify sickness at early stage with help of Altman’s discriminate Analysis model so the corporate failure can be minimized.

Suggested Citation

  • Krishn Awatar Goyal, 2013. "An Empirical Case Study on Prediction of Corporate Failure in The Selected Industrial Unit in India," International Journal of Business Research and Management (IJBRM), Computer Science Journals (CSC Journals), vol. 4(4), pages 132-137, November.
    • Handle: RePEc:aml:intbrm:v:4:y:2013:i:4:p:132-137
    as

    Download full text from publisher

    File URL: https://www.cscjournals.org/manuscript/Journals/IJBRM/Volume4/Issue4/IJBRM-155.pdf
    Download Restriction: no
    File URL: https://www.cscjournals.org/library/manuscriptinfo.php?mc=IJBRM-155
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. C Sathyamoorthi & Christian Mbekomize & Ishmael Radikoko & Lillian Wally-Dima, 2016. "An Analysis of the Financial Performance of Selected Savings and Credit Co-Operative Societies in Botswana," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(8), pages 180-180, August.
    2. Durgaprasad Navulla, 2016. "The Analysis of Industrial Sickness with Reference to the FCIL," GATR Journals jfbr115, Global Academy of Training and Research (GATR) Enterprise.

    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. Barbara Su, 2023. "Banking practices and borrowing firms’ financial reporting quality: evidence from bank cross-selling," Review of Accounting Studies, Springer, vol. 28(1), pages 201-236, March.
    2. Matthew Smith & Francisco Alvarez, 2022. "Predicting Firm-Level Bankruptcy in the Spanish Economy Using Extreme Gradient Boosting," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 263-295, January.
    3. Stephen Brown & William Goetzmann & Bing Liang & Christopher Schwarz, 2008. "Mandatory Disclosure and Operational Risk: Evidence from Hedge Fund Registration," Journal of Finance, American Finance Association, vol. 63(6), pages 2785-2815, December.
    4. Premachandra, I.M. & Bhabra, Gurmeet Singh & Sueyoshi, Toshiyuki, 2009. "DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique," European Journal of Operational Research, Elsevier, vol. 193(2), pages 412-424, March.
    5. José Carlos Trejo García & Humberto Ríos Bolívar & Francisco Almagro Vázquez, 2016. "Actualización del modelo de riesgo crediticio, una necesidad para la banca revolvente en México," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 8(1), pages 17-30, March.
    6. C, Loran & Eckbo, Espen & Lu, Ching-Chih, 2014. "Does Executive Compensation Reflect Default Risk?," UiS Working Papers in Economics and Finance 2014/11, University of Stavanger.
    7. Shaikh, Ibrahim A. & O'Brien, Jonathan Paul & Peters, Lois, 2018. "Inside directors and the underinvestment of financial slack towards R&D-intensity in high-technology firms," Journal of Business Research, Elsevier, vol. 82(C), pages 192-201.
    8. Mikel Bedayo & Gabriel Jiménez & José-Luis Peydró & Raquel Vegas, 2020. "Screening and Loan Origination Time: Lending Standards, Loan Defaults and Bank Failures," Working Papers 1215, Barcelona School of Economics.
    9. Kavčáková, Michaela & Kočišová, Kristína, 2020. "Using Data Envelopment Analysis in Credit Risk Evaluation of ICT Companies," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 10(3), December.
    10. Ch. Piette & M.-D. Zachary, 2015. "Sensitivity to the crisis of SME financing in Belgium," Economic Review, National Bank of Belgium, issue iii, pages 31-45, December.
    11. Ruey-Ching Hwang & Jhao-Siang Siao & Huimin Chung & C. Chu, 2011. "Assessing bankruptcy prediction models via information content of technical inefficiency," Journal of Productivity Analysis, Springer, vol. 36(3), pages 263-273, December.
    12. Ruey-Ching Hwang, 2013. "Forecasting credit ratings with the varying-coefficient model," Quantitative Finance, Taylor & Francis Journals, vol. 13(12), pages 1947-1965, December.
    13. Beck, Thorsten & Laeven, Luc, 2006. "Resolution of failed banks by deposit insurers : cross-country evidence," Policy Research Working Paper Series 3920, The World Bank.
    14. Antonio Davila & George Foster & Xiaobin He & Carlos Shimizu, 2015. "The rise and fall of startups: Creation and destruction of revenue and jobs by young companies," Australian Journal of Management, Australian School of Business, vol. 40(1), pages 6-35, February.
    15. Jonas Heese, 2017. "The Role of Overbilling in Hospitals’ Earnings Management Decisions," Harvard Business School Working Papers 18-026, Harvard Business School.
    16. Masahiro Enomoto, 2018. "Effects of Corporate Governance on the Relationship between Accounting Quality and Trade Credit: Evidence from Japan," Discussion Paper Series DP2018-12, Research Institute for Economics & Business Administration, Kobe University, revised Dec 2023.
    17. Chen, Peimin & Wu, Chunchi, 2014. "Default prediction with dynamic sectoral and macroeconomic frailties," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 211-226.
    18. Knyazeva, Anzhela & Knyazeva, Diana, 2012. "Does being your bank’s neighbor matter?," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1194-1209.
    19. Barth, Mary E. & Beaver, William H. & Landsman, Wayne R., 2001. "The relevance of the value relevance literature for financial accounting standard setting: another view," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 77-104, September.
    20. Bonfim, Diana, 2009. "Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 281-299, February.

    More about this item

    Keywords

    Industrial Sickness; Corporate Failure; Prediction Models.;
    All these keywords.

    JEL classification:

    • M0 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General

    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:aml:intbrm:v:4:y:2013:i:4:p:132-137. 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: Nabeel Tahir (email available below). General contact details of provider: .

    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.