IDEAS home Printed from https://ideas.repec.org/a/vrs/poicbe/v13y2019i1p241-253n22.html
   My bibliography  Save this article

The Enterprise Risk Profile Model and Its Implementation in Reorganised Companies

Author

Listed:
  • Stroie Cristina

    (Bucharest University of Economic Studies, Romania)

  • Duţescu Adriana

    (Bucharest University of Economic Studies, Romania)

Abstract

Globalization, as a response to the accelerated developments in recent decades, has shifted the world economy to a direction in which the adaptation to uncertainty conditions has been one of the most important manifestations of rational behavior. Human activity has always been subject to risks and uncertainty, and environmental pressure naturally generates selection and adaptation. The risk profile analysis in insolvency proceedings, as an indicator of managerial and financial health, represents a challenge to complement the gaps in the literature, given the limited studies in the field, compared to the bibliography in the field of risk management, for the companies in the economic circuit. This topic is of major importance for all business environments, having in view the disasters generated by economic crises on companies. In terms of judicial reorganization and insolvency proceedings, the situation in Romania proves to be different from the practices in the countries with tradition in this field and we are referring here to the USA, Germany and France. Comparative studies have indicated dysfunctions in the reorganization procedures in Romania, related to the lack of a coercive system to remove the insolvency debtors from the economic circuit, and the lack of models for analyzing the reorganization capacity of companies in insolvency proceedings. Regarding a possible reorganization of a company, creditors do not have approved analysis models in order to vote on reorganization plans and most of the time, at least as far as public creditors are concerned, their vote is negative and unfounded. The purpose of this research is to generate a model of internal risk analysis specific to the companies undergoing insolvency proceedings and of external risks related to the activity sector, a model able to predict the possibility of reorganizing a company undergoing insolvency proceedings. The main tool used is the interview, conducted on a sample of insolvency experts in Romania, with an average experience of approx. 10-20 years in insolvency and reorganization activities. Based on the analysis of the obtained results, we will refine and restructure a model, and then we will test it on a sample of companies undergoing insolvency proceedings.

Suggested Citation

  • Stroie Cristina & Duţescu Adriana, 2019. "The Enterprise Risk Profile Model and Its Implementation in Reorganised Companies," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 13(1), pages 241-253, May.
    • Handle: RePEc:vrs:poicbe:v:13:y:2019:i:1:p:241-253:n:22
    DOI: 10.2478/picbe-2019-0022
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/picbe-2019-0022
    Download Restriction: no
    File URL: https://libkey.io/10.2478/picbe-2019-0022?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Xavier Giné & Inessa Love, 2010. "Do Reorganization Costs Matter for Efficiency? Evidence from a Bankruptcy Reform in Colombia," Journal of Law and Economics, University of Chicago Press, vol. 53(4), pages 833-864.
    2. Robert E. Quinn & Kim Cameron, 1983. "Organizational Life Cycles and Shifting Criteria of Effectiveness: Some Preliminary Evidence," Management Science, INFORMS, vol. 29(1), pages 33-51, January.
    3. Marioara Mirea & Cristina Stroie, 2016. "Concrete Aspects Regarding the Imputation of Current Tax Receivables in Insolvency Proceedings," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 554-558, February.
    4. 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.
    5. 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.
    6. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    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. Chen, Peimin & Wu, Chunchi, 2014. "Default prediction with dynamic sectoral and macroeconomic frailties," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 211-226.
    2. Sandrine Lardic & Claire Gauthier, 2003. "Un modèle multifactoriel des spreads de crédit : estimation sur panels complets et incomplets," Économie et Prévision, Programme National Persée, vol. 159(3), pages 53-69.
    3. Andres, Christian & Cumming, Douglas & Karabiber, Timur & Schweizer, Denis, 2014. "Do markets anticipate capital structure decisions? — Feedback effects in equity liquidity," Journal of Corporate Finance, Elsevier, vol. 27(C), pages 133-156.
    4. Wen Su, 2021. "Default Distances Based on the CEV-KMV Model," Papers 2107.10226, arXiv.org, revised May 2022.
    5. Chen, An-Sing & Chu, Hsiang-Hui & Hung, Pi-Hsia & Cheng, Miao-Sih, 2020. "Financial risk and acquirers' stockholder wealth in mergers and acquisitions," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    6. Ahsan Habib & Mabel D' Costa & Hedy Jiaying Huang & Md. Borhan Uddin Bhuiyan & Li Sun, 2020. "Determinants and consequences of financial distress: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 1023-1075, April.
    7. Giesecke, Kay & Longstaff, Francis A. & Schaefer, Stephen & Strebulaev, Ilya, 2011. "Corporate bond default risk: A 150-year perspective," Journal of Financial Economics, Elsevier, vol. 102(2), pages 233-250.
    8. Lambrinoudakis, Costas & Skiadopoulos, George & Gkionis, Konstantinos, 2019. "Capital structure and financial flexibility: Expectations of future shocks," Journal of Banking & Finance, Elsevier, vol. 104(C), pages 1-18.
    9. Ferreira Filipe, Sara & Grammatikos, Theoharry & Michala, Dimitra, 2016. "Pricing default risk: The good, the bad, and the anomaly," Journal of Financial Stability, Elsevier, vol. 26(C), pages 190-213.
    10. Agarwal, Vineet & Taffler, Richard, 2008. "Comparing the performance of market-based and accounting-based bankruptcy prediction models," Journal of Banking & Finance, Elsevier, vol. 32(8), pages 1541-1551, August.
    11. Sigrist, Fabio & Leuenberger, Nicola, 2023. "Machine learning for corporate default risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1390-1406.
    12. Giulio Bottazzi & Marco Grazzi & Angelo Secchi & Federico Tamagni, 2011. "Financial and economic determinants of firm default," Journal of Evolutionary Economics, Springer, vol. 21(3), pages 373-406, August.
    13. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
    14. Lorenzo Casavecchia & Ja Young Suh, 2017. "Managerial incentives for risk-taking and internal capital allocation," Australian Journal of Management, Australian School of Business, vol. 42(3), pages 428-461, August.
    15. Andreou, Christoforos K. & Lambertides, Neophytos & Panayides, Photis M., 2021. "Distress risk anomaly and misvaluation," The British Accounting Review, Elsevier, vol. 53(5).
    16. Mark Clintworth & Dimitrios Lyridis & Evangelos Boulougouris, 2023. "Financial risk assessment in shipping: a holistic machine learning based methodology," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(1), pages 90-121, March.
    17. Chengru Hu & Wei Jiang, 2019. "Managerial risk incentives and accounting conservatism," Review of Quantitative Finance and Accounting, Springer, vol. 52(3), pages 781-813, April.
    18. Charitou, Andreas & Dionysiou, Dionysia & Lambertides, Neophytos & Trigeorgis, Lenos, 2013. "Alternative bankruptcy prediction models using option-pricing theory," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2329-2341.
    19. Bergman, Nittai K. & Jenter, Dirk, 2007. "Employee sentiment and stock option compensation," Journal of Financial Economics, Elsevier, vol. 84(3), pages 667-712, June.
    20. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.

    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:vrs:poicbe:v:13:y:2019:i:1:p:241-253:n:22. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    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.