Business failure prediction using survival analysis

Research output: Contribution to conferencePaperResearchpeer-review

Abstract

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.
Original languageEnglish
Pages318-332
Number of pages15
Publication statusPublished - 2006
EventInternational Conference of Business Economics and Management Disciplines: ICBEMD 2005 - Delta Hotel, Fredericton, Canada
Duration: 19 Aug 200520 Aug 2005
http://www.allconferences.com/conferences/2005/20050118061500

Conference

ConferenceInternational Conference of Business Economics and Management Disciplines
CountryCanada
CityFredericton
Period19/08/0520/08/05
Internet address

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Industry

Cite this

Gepp, A., & Kumar, K. (2006). Business failure prediction using survival analysis. 318-332. Paper presented at International Conference of Business Economics and Management Disciplines, Fredericton, Canada.
Gepp, Adrian ; Kumar, Kuldeep. / Business failure prediction using survival analysis. Paper presented at International Conference of Business Economics and Management Disciplines, Fredericton, Canada.15 p.
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abstract = "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.",
author = "Adrian Gepp and Kuldeep Kumar",
year = "2006",
language = "English",
pages = "318--332",
note = "International Conference of Business Economics and Management Disciplines : ICBEMD 2005 ; Conference date: 19-08-2005 Through 20-08-2005",
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Gepp, A & Kumar, K 2006, 'Business failure prediction using survival analysis' Paper presented at International Conference of Business Economics and Management Disciplines, Fredericton, Canada, 19/08/05 - 20/08/05, pp. 318-332.

Business failure prediction using survival analysis. / Gepp, Adrian; Kumar, Kuldeep.

2006. 318-332 Paper presented at International Conference of Business Economics and Management Disciplines, Fredericton, Canada.

Research output: Contribution to conferencePaperResearchpeer-review

TY - CONF

T1 - Business failure prediction using survival analysis

AU - Gepp, Adrian

AU - Kumar, Kuldeep

PY - 2006

Y1 - 2006

N2 - 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.

AB - 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.

M3 - Paper

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EP - 332

ER -

Gepp A, Kumar K. Business failure prediction using survival analysis. 2006. Paper presented at International Conference of Business Economics and Management Disciplines, Fredericton, Canada.