IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v63y2012i8p1051-1064.html
   My bibliography  Save this article

Pattern recognition for evaluator errors in a credit scoring model for technology-based SMEs

Author

Listed:
  • S Y Sohn

    (Yonsei University, Seoul, Republic of Korea)

  • M K Doo

    (Yonsei University, Seoul, Republic of Korea)

  • Y H Ju

    (Yonsei University, Seoul, Republic of Korea)

Abstract

A credit scoring model for technology-based small and medium enterprises presupposes evaluator objectivity and evaluation consistency; however, there is always some amount of error in any technology evaluation. This can be due in part to the subjective evaluation attributes that comprise part of the credit scoring model. The evaluated values of subjective attributes can vary among evaluators. In this study, we identified the significant characteristics of both evaluator and evaluation teams in terms of evaluation error using a decision tree analysis. Our results can improve the accuracy of a wide range of evaluation procedures for technology financing.

Suggested Citation

  • S Y Sohn & M K Doo & Y H Ju, 2012. "Pattern recognition for evaluator errors in a credit scoring model for technology-based SMEs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(8), pages 1051-1064, August.
    • Handle: RePEc:pal:jorsoc:v:63:y:2012:i:8:p:1051-1064
    as

    Download full text from publisher

    File URL: http://www.palgrave-journals.com/jors/journal/v63/n8/pdf/jors2011105a.pdf
    File Function: Link to full text PDF
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: http://www.palgrave-journals.com/jors/journal/v63/n8/full/jors2011105a.html
    File Function: Link to full text HTML
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Janne Harkonen & Harri Haapasalo & Kai Hanninen, 2013. "Productisation: A Literature Review," Diversity, Technology, and Innovation for Operational Competitiveness: Proceedings of the 2013 International Conference on Technology Innovation and Industrial Management,, ToKnowPress.
    3. Harkonen, Janne & Haapasalo, Harri & Hanninen, Kai, 2015. "Productisation: A review and research agenda," International Journal of Production Economics, Elsevier, vol. 164(C), pages 65-82.
    4. Francesco Ciampi & Alessandro Giannozzi & Giacomo Marzi & Edward I. Altman, 2021. "Rethinking SME default prediction: a systematic literature review and future perspectives," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2141-2188, March.
    5. Jong Wook Lee & So Young Sohn, 2021. "Evaluating borrowers’ default risk with a spatial probit model reflecting the distance in their relational network," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-11, December.
    6. 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.
    7. Yonghan Ju & So Young Sohn, 2017. "Technology Credit Scoring Based on a Quantification Method," Sustainability, MDPI, vol. 9(6), pages 1-16, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorsoc:v:63:y:2012:i:8:p:1051-1064. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.