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

机译:商业失败预测的熵:建筑行业的一种改进的预测模型

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摘要

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.
机译:本文实证检验了信息理论和判别分析相结合的熵测度在建筑施工企业失败预测中的有效性。现代复杂供应链中的这种失败是极具破坏性的力量,它的可能性是对承包商进行资格预评估的关键因素。所描述的工作利用台湾建筑业的财务数据,通过应用香农的信息论来扩展经典方法,以提高其预测能力,并为基于人工智能的新方法提供了替代方法。

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  • 来源
    《Advances in decision sciences》 |2013年第2013期|459751.1-459751.14|共14页
  • 作者

    Jay Bal; Yen Cheung; Hsu-Che Wu;

  • 作者单位

    International Digital Laboratory, University of Warwick, Coventry CV4 7AL, UK;

    Clayton School of IT, Monash University, Melbourne, Vic 3800, Australia;

    Department of Accounting and Information Technology, National Chung Cheng University, 168 University Road, Min-Hsiung, Chia-Yi County 621, Taiwan;

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  • 正文语种 eng
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  • 入库时间 2022-08-18 01:14:28

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