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      Expert, Linear Models, and Nonlinear Models of Expert Decision Making in Bankruptcy Prediction: A Lens Model Analysis = 기업도산 예측에서 의사결정의 분석과 모형에 관한 연구

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      https://www.riss.kr/link?id=E687803

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      다국어 초록 (Multilingual Abstract)

      The analysis of human judgment and decision making provides useful methodologies for examining the human decision process and substantive results. One such methodology is a lens model analysis. Using such a model, a study is conducte to determine how well a model of expert decisions can capture a valid strategy in the decision process. The study also addesses the question of whether a model of an expert can be more accurae than the expert.
      Two linear (statistical) models and two nonlinear models of human expers are compared in terms of predictive accuracy (predictive validity). The results indicate that nonlinear models can capture factors (valid nonlinear strategy) that contribute to the experts' predictive accuracy. However, linear models cannot capture the valid nonlinear strategy as well as nonlinear models.
      One linear model and two nonlinear models performed as well as the overall average of a group of experts. However, all of the models were outperformed by the most accurate expert. By combining validity of decision strategy with characteristics of modeling algorithms, it is possible to explain why certain algorithms perform better than others.
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      The analysis of human judgment and decision making provides useful methodologies for examining the human decision process and substantive results. One such methodology is a lens model analysis. Using such a model, a study is conducte to determine how ...

      The analysis of human judgment and decision making provides useful methodologies for examining the human decision process and substantive results. One such methodology is a lens model analysis. Using such a model, a study is conducte to determine how well a model of expert decisions can capture a valid strategy in the decision process. The study also addesses the question of whether a model of an expert can be more accurae than the expert.
      Two linear (statistical) models and two nonlinear models of human expers are compared in terms of predictive accuracy (predictive validity). The results indicate that nonlinear models can capture factors (valid nonlinear strategy) that contribute to the experts' predictive accuracy. However, linear models cannot capture the valid nonlinear strategy as well as nonlinear models.
      One linear model and two nonlinear models performed as well as the overall average of a group of experts. However, all of the models were outperformed by the most accurate expert. By combining validity of decision strategy with characteristics of modeling algorithms, it is possible to explain why certain algorithms perform better than others.

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      목차 (Table of Contents)

      • ABSTRACT
      • Ⅰ. INTRODUCTION
      • Ⅱ. LITERATURE REVIEW
      • ABSTRACT
      • Ⅰ. INTRODUCTION
      • Ⅱ. LITERATURE REVIEW
      • Ⅲ. METHODOLOGY
      • Ⅳ. RESULTS
      • Ⅴ. CONCLUSION
      • REFERENCES
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