Entropy for Business Failure Prediction : An Improved Prediction Model for the Construction Industry

Joint Authors

Bal, Jay
Wu, Hsu-Che
Cheung, Yen

Source

Advances in Decision Sciences

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