IDEAS home Printed from https://ideas.repec.org/a/bla/jbfnac/v32y2005i5-6p1083-1105.html
   My bibliography  Save this article

Employee Relations and the Likelihood of Occurrence of Corporate Financial Distress

Author

Listed:
  • Gregory D. Kane
  • Uma Velury
  • Bernadette M. Ruf

Abstract

In this paper, we investigate the association of employee relations with the occurrence of onset of financial distress. We argue that if adverse economic conditions arise, firms that have maintained good employee relations will be more effective in obtaining temporary labor concessions. As a result, firms with good employee relations, to the extent they are dependent on labor in the conduct of business operations, should be more likely to avoid the onset of future financial distress. The empirical findings we document support this prior.

Suggested Citation

  • Gregory D. Kane & Uma Velury & Bernadette M. Ruf, 2005. "Employee Relations and the Likelihood of Occurrence of Corporate Financial Distress," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 32(5‐6), pages 1083-1105, June.
    • Handle: RePEc:bla:jbfnac:v:32:y:2005:i:5-6:p:1083-1105
    DOI: 10.1111/j.0306-686X.2005.00623.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.0306-686X.2005.00623.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.0306-686X.2005.00623.x?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. Gregory D. Kane & Frederick M. Richardson & Patricia Graybeal, 1996. "Recession†Induced Stress and the Prediction of Corporate Failure," Contemporary Accounting Research, John Wiley & Sons, vol. 13(2), pages 631-650, September.
    2. Francis, J & Schipper, K, 1999. "Have financial statements lost their relevance?," Journal of Accounting Research, Wiley Blackwell, vol. 37(2), pages 319-352.
    3. Blum, M, 1974. "Failing Company Discriminant-Analysis," Journal of Accounting Research, Wiley Blackwell, vol. 12(1), pages 1-25.
    4. Kane, Gregory D & Richardson, Frederick M, 2002. "The Relationship between Changes in Fixed Plant Investment and the Likelihood of Emergence from Corporate Financial Distress," Review of Quantitative Finance and Accounting, Springer, vol. 18(3), pages 259-272, May.
    5. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    6. 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.
    7. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    8. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    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. 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.
    2. Bouslah, Kais & Kryzanowski, Lawrence & M’Zali, Bouchra, 2013. "The impact of the dimensions of social performance on firm risk," Journal of Banking & Finance, Elsevier, vol. 37(4), pages 1258-1273.
    3. Boubaker, Sabri & Cellier, Alexis & Manita, Riadh & Saeed, Asif, 2020. "Does corporate social responsibility reduce financial distress risk?," Economic Modelling, Elsevier, vol. 91(C), pages 835-851.
    4. Keishi Fujiyama & Makoto Kuroki, 2017. "Strategic Management Forecasts and Accounting Choices: A Case of Employee Downsizing in Japan," Discussion Paper Series DP2017-06, Research Institute for Economics & Business Administration, Kobe University, revised Sep 2017.
    5. Jing Jia & Zhongtian Li, 2022. "Corporate Environmental Performance and Financial Distress: Evidence from Australia," Australian Accounting Review, CPA Australia, vol. 32(2), pages 188-200, June.
    6. Boonlert Jitmaneeroj, 2024. "Value relevance of multifaceted corporate social performance: how do country-specific factors matter?," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-20, December.
    7. Champagne, Claudia & Coggins, Frank & Sodjahin, Amos, 2022. "Can extra-financial ratings serve as an indicator of ESG risk?," Global Finance Journal, Elsevier, vol. 54(C).
    8. Weetman, Pauline, 2006. "Discovering the ‘international’ in accounting and finance," The British Accounting Review, Elsevier, vol. 38(4), pages 351-370.
    9. Hao, Ying & Zhao, Min & Wei, Zi, 2024. "Can military executives overcome difficulties in corporate value creation? ——Evidence from China," China Economic Review, Elsevier, vol. 84(C).
    10. Lutfi Abdul Razak & Mansor H. Ibrahim & Adam Ng, 2020. "Which Sustainability Dimensions Affect Credit Risk? Evidence from Corporate and Country-Level Measures," JRFM, MDPI, vol. 13(12), pages 1-22, December.
    11. Kanno, Masayasu, 2023. "Does ESG performance improve firm creditworthiness?," Finance Research Letters, Elsevier, vol. 55(PA).
    12. Leng, Aolin & Sun, Yanbing, 2024. "The impact mechanism and breakthrough path of COVID-19 on enterprise financial distress: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 16-31.

    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. Gregory D. Kane & Frederick M. Richardson & Nancy L. Meade, 1998. "Rank Transformations and the Prediction of Corporate Failure," Contemporary Accounting Research, John Wiley & Sons, vol. 15(2), pages 145-166, June.
    2. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    3. 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.
    4. Yung-Ho Chiu & Yu-Chuan Chen & Yu Han Hung, 2009. "Basel II and bank bankruptcy analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 16(18), pages 1843-1847.
    5. 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.
    6. repec:ctc:sdimse:dime21_01 is not listed on IDEAS
    7. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    8. Josep Patau & Antonio Somoza & Salvador Torra, 2020. "Diagnosis of the Domino Effect in Bankruptcy Situations Through Positioning Maps and Their Evolution 10 Years Later," SAGE Open, , vol. 10(4), pages 21582440209, December.
    9. Róbert Štefko & Jarmila Horváthová & Martina Mokrišová, 2020. "Bankruptcy Prediction with the Use of Data Envelopment Analysis: An Empirical Study of Slovak Businesses," JRFM, MDPI, vol. 13(9), pages 1-15, September.
    10. Alessandro Bitetto & Stefano Filomeni & Michele Modina, 2021. "Understanding corporate default using Random Forest: The role of accounting and market information," DEM Working Papers Series 205, University of Pavia, Department of Economics and Management.
    11. Nisansala Wijekoon & A. Abdul Azeez, 2015. "An Integrated Model to Predict Corporate Failure of Listed Companies in Sri Lanka," International Journal of Business and Social Research, LAR Center Press, vol. 5(7), pages 1-14, July.
    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. Kerstin Lopatta & Mario Albert Gloger & Reemda Jaeschke, 2017. "Can Language Predict Bankruptcy? The Explanatory Power of Tone in 10‐K Filings," Accounting Perspectives, John Wiley & Sons, vol. 16(4), pages 315-343, December.
    14. Francesco Ciampi & Valentina Cillo & Fabio Fiano, 2020. "Combining Kohonen maps and prior payment behavior for small enterprise default prediction," Small Business Economics, Springer, vol. 54(4), pages 1007-1039, April.
    15. Shilpa Shetty H. & Theresa Nithila Vincent, 2024. "Corporate Default Prediction Model: Evidence from the Indian Industrial Sector," Vision, , vol. 28(3), pages 344-360, June.
    16. 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.
    17. Jackson, Richard H.G. & Wood, Anthony, 2013. "The performance of insolvency prediction and credit risk models in the UK: A comparative study," The British Accounting Review, Elsevier, vol. 45(3), pages 183-202.
    18. Bhanu Pratap Singh & Alok Kumar Mishra, 2016. "Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 2(1), pages 1-28, December.
    19. Amer Demirovic & Dylan Thomas, 2007. "The Relevance of Accounting Data in the Measurement of Credit Risk," The European Journal of Finance, Taylor & Francis Journals, vol. 13(3), pages 253-268.
    20. Bhanu Pratap SINGH & Alok Kumar MISHRA, 2019. "Sensitivity of bankruptcy prediction models to the change in econometric methods," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(3(620), A), pages 71-86, Autumn.
    21. Andrzej Geise & Magdalena Kuczmarska & Jarosław Pawlowski, 2021. "Corporate Failure Prediction of Construction Companies in Poland: Evidence from Logit Model," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 99-116.

    More about this item

    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:bla:jbfnac:v:32:y:2005:i:5-6:p:1083-1105. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0306-686X .

    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.