O modelo e-Score de previsão de falências para empresas de internet
Main Article Content
Abstract
This study proposes a binomial logit model to estimate the probability of an event of bankruptcy for Internet companies, i.e. companies dependent on e-business. Sixty-one American companies were selected and divided into two samples: 25, which had filed for petition under the US Bankruptcy Code, between 1999 and 2001, and 36, which had not, for the same period. A training sample was randomly selected to determine the model variables and parameters and a holdout sample has confirmed its high accuracy by correctly classifying 95.1% of the total sample of 61 companies, based on annual financial statements as of one year before the bankruptcy's occurrence; and 88.1%, as of two years prior to the same event. Then, the e-Score Model reveals to be very significant by using only three variables, of 63 first analyzed: (i) INT/TL: Interest Expense (Income) to Total Liabilities; (ii) R&D/EMP: Research & Development Expenses to Number of Employees; e (iii) OCF/CL: Operating Cash Flow to Current Liabilities. While (i) and (iii) can be obtained from conventional financial statements, (ii) is innovative, indicating the company which invests in R&D on a per employee basis has a greater chance of survival. In contrast, companies presenting relatively high Net Interest Expenses and low Operating Cash Flow have less chance for survival.
Downloads
Download data is not yet available.
Download data is not yet available.
Article Details
How to Cite
Pereira, O. M., & Ness Jr., W. L. (1). O modelo e-Score de previsão de falências para empresas de internet. Journal of Contemporary Administration, 8(3), 143-166. https://doi.org/10.1590/S1415-65552004000300008
Section
Articles
Since mid-February of 2023, the authors retain the copyright relating to their article and grant the journal RAC, from ANPAD, the right of first publication, with the work simultaneously licensed under the Creative Commons Attribution 4.0 International license (CC BY 4.0), as stated in the article’s PDF document. This license provides that the article published can be shared (allows you to copy and redistribute the material in any medium or format) and adapted (allows you to remix, transform, and create from the material for any purpose, even commercial) by anyone.
After article acceptance, the authors must sign a Term of Authorization for Publication, which is sent to the authors by e-mail for electronic signature before publication.