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Technology scoring model for reflecting evaluator's perception within confidence limits

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  • Moon, Tae Hee
  • Sohn, So Young

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  • Moon, Tae Hee & Sohn, So Young, 2008. "Technology scoring model for reflecting evaluator's perception within confidence limits," European Journal of Operational Research, Elsevier, vol. 184(3), pages 981-989, February.
    • Handle: RePEc:eee:ejores:v:184:y:2008:i:3:p:981-989
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    2. Fernandez-Castro, A & Smith, P, 1994. "Towards a general non-parametric model of corporate performance," Omega, Elsevier, vol. 22(3), pages 237-249, May.
    3. Fuller-Love, N. & Rhys, H. & Tippett, M., 1995. "Harmonic analysis, time series variations and the distributional properties of financial ratios," Omega, Elsevier, vol. 23(4), pages 419-427, August.
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    5. Chen, E. Jack & Kelton, W. David, 2006. "Quantile and tolerance-interval estimation in simulation," European Journal of Operational Research, Elsevier, vol. 168(2), pages 520-540, January.
    6. Hanson, Samuel & Schuermann, Til, 2006. "Confidence intervals for probabilities of default," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2281-2301, August.
    7. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    8. Stein, Roger M., 2005. "The relationship between default prediction and lending profits: Integrating ROC analysis and loan pricing," Journal of Banking & Finance, Elsevier, vol. 29(5), pages 1213-1236, May.
    9. Barniv, Ran & Mehrez, Abraham & Kline, Douglas M., 2000. "Confidence intervals for controlling the probability of bankruptcy," Omega, Elsevier, vol. 28(5), pages 555-565, October.
    10. Uster, Halit & Love, Robert F., 2003. "Formulation of confidence intervals for estimated actual distances," European Journal of Operational Research, Elsevier, vol. 151(3), pages 586-601, December.
    11. Westgaard, Sjur & van der Wijst, Nico, 2001. "Default probabilities in a corporate bank portfolio: A logistic model approach," European Journal of Operational Research, Elsevier, vol. 135(2), pages 338-349, December.
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    Cited by:

    1. T H Moon & S Y Sohn, 2010. "Technology credit scoring model considering both SME characteristics and economic conditions: The Korean case," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(4), pages 666-675, April.
    2. Yonghan Ju & So Young Sohn, 2017. "Technology Credit Scoring Based on a Quantification Method," Sustainability, MDPI, vol. 9(6), pages 1-16, June.
    3. Kim, Hong Sik & Sohn, So Young, 2010. "Support vector machines for default prediction of SMEs based on technology credit," European Journal of Operational Research, Elsevier, vol. 201(3), pages 838-846, March.
    4. So Sohn & Yoon Kim, 2013. "Behavioral credit scoring model for technology-based firms that considers uncertain financial ratios obtained from relationship banking," Small Business Economics, Springer, vol. 41(4), pages 931-943, December.
    5. Ju, Yong Han & Sohn, So Young, 2014. "Updating a credit-scoring model based on new attributes without realization of actual data," European Journal of Operational Research, Elsevier, vol. 234(1), pages 119-126.
    6. Yonghan Ju & So Young Sohn, 2015. "Stress test for a technology credit guarantee fund based on survival analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(3), pages 463-475, March.
    7. T H Moon & S Y Sohn, 2011. "Survival analysis for technology credit scoring adjusting total perception," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1159-1168, June.
    8. Bo Kyeong Lee & So Young Sohn, 2017. "A Credit Scoring Model for SMEs Based on Accounting Ethics," Sustainability, MDPI, vol. 9(9), pages 1-15, September.

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