Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly in financial investment and lending. Recently, there has been a significant increase in interest in business failure prediction, from both industry and academia. Statistical business failure prediction models attempt to predict the failure or success of a business. Discriminant and logit analyses have been the most popular approaches, but there are also a large number of alternative techniques available. In this paper, a comparatively new technique known as survival analysis has been used for business failure prediction. Overall, the results suggest that survival analysis techniques provide more information that can be used to further the understanding of the business failure process.
|Number of pages||15|
|Publication status||Published - 2006|
|Event||International Conference of Business Economics and Management Disciplines: ICBEMD 2005 - Delta Hotel, Fredericton, Canada|
Duration: 19 Aug 2005 → 20 Aug 2005
|Conference||International Conference of Business Economics and Management Disciplines|
|Period||19/08/05 → 20/08/05|
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Gepp, A., 10 Oct 2015
Supervisor: Kumar, K. (Supervisor) & Bhattacharya, S. (External person) (Supervisor)
Student thesis: Doctoral ThesisFile