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Entropy for Business Failure Prediction : An Improved Prediction Model for the Construction Industry
Joint Authors
Bal, Jay
Wu, Hsu-Che
Cheung, Yen
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-12
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Economics & Business Administration
Business Administration
Abstract EN
This paper examines empirically the effectiveness of entropy measures derived from information theory combined with discriminant analysis in the prediction of construction business failure.
Such failure in modern complex supply chains is an extremely disruptive force, and its likelihood is a key factor in the prequalification appraisal of contractors.
The work described, using financial data from the Taiwanese construction industry, extends the classical methods by applying Shannon's information theory to improve their prediction ability and provides an alternative to newer artificial-intelligence-based approaches.
American Psychological Association (APA)
Bal, Jay& Cheung, Yen& Wu, Hsu-Che. 2014. Entropy for Business Failure Prediction : An Improved Prediction Model for the Construction Industry. Advances in Decision Sciences،Vol. 2013, no. 2013, pp.1-14.
https://search.emarefa.net/detail/BIM-473253
Modern Language Association (MLA)
Bal, Jay…[et al.]. Entropy for Business Failure Prediction : An Improved Prediction Model for the Construction Industry. Advances in Decision Sciences No. 2013 (2013), pp.1-14.
https://search.emarefa.net/detail/BIM-473253
American Medical Association (AMA)
Bal, Jay& Cheung, Yen& Wu, Hsu-Che. Entropy for Business Failure Prediction : An Improved Prediction Model for the Construction Industry. Advances in Decision Sciences. 2014. Vol. 2013, no. 2013, pp.1-14.
https://search.emarefa.net/detail/BIM-473253
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-473253