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Technology credit rating system for funding SMEs

Author

Listed:
  • T H Moon

    (Yonsei University)

  • Y Kim

    (Yonsei University)

  • S Y Sohn

    (Yonsei University)

Abstract

Technology evaluation has played a crucial role in selecting and supporting companies with innovative technology. Previous studies have focused on developing technology evaluation methods such as scorecard. However, technology credit rating is rarely applied, despite its convenient usage for technology financing. In this paper, we propose a technology credit rating system, called cross matrix, based on empirical data obtained from the technology scoring model and examine their properties. The proposed rating system is expected to provide valuable information for effective management of the technology credit fund.

Suggested Citation

  • T H Moon & Y Kim & S Y Sohn, 2011. "Technology credit rating system for funding SMEs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(4), pages 608-615, April.
  • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:4:d:10.1057_jors.2010.15
    DOI: 10.1057/jors.2010.15
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    References listed on IDEAS

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    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. Crouhy, Michel & Galai, Dan & Mark, Robert, 2001. "Prototype risk rating system," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 47-95, January.
    3. Wang, Juite & Hwang, W.-L., 2007. "A fuzzy set approach for R&D portfolio selection using a real options valuation model," Omega, Elsevier, vol. 35(3), pages 247-257, June.
    4. Laitinen, Ek, 1993. "Financial predictors for different phases of the failure process," Omega, Elsevier, vol. 21(2), pages 215-228, March.
    5. H J Jeon & S Y Sohn, 2008. "The risk management for technology credit guarantee fund," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(12), pages 1624-1632, December.
    6. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2007. "Ratings-based credit risk modelling: An empirical analysis," International Review of Financial Analysis, Elsevier, vol. 16(5), pages 434-451.
    7. Shin, Yoon S. & Moore, William T., 2003. "Explaining credit rating differences between Japanese and U.S. agencies," Review of Financial Economics, Elsevier, vol. 12(4), pages 327-344.
    8. Bangia, Anil & Diebold, Francis X. & Kronimus, Andre & Schagen, Christian & Schuermann, Til, 2002. "Ratings migration and the business cycle, with application to credit portfolio stress testing," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 445-474, March.
    9. Hu, Yen-Ting & Kiesel, Rudiger & Perraudin, William, 2002. "The estimation of transition matrices for sovereign credit ratings," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1383-1406, July.
    10. Heslop, Louise A & McGregor, Eileen & Griffith, May, 2001. "Development of a Technology Readiness Assessment Measure: The Cloverleaf Model of Technology Transfer," The Journal of Technology Transfer, Springer, vol. 26(4), pages 369-384, October.
    11. Thomas Astebro & John L. Michela, 2005. "Predictors of the Survival of Innovations," Post-Print hal-00476886, HAL.
    12. Grunert, Jens & Norden, Lars & Weber, Martin, 2005. "The role of non-financial factors in internal credit ratings," Journal of Banking & Finance, Elsevier, vol. 29(2), pages 509-531, February.
    13. Treacy, William F. & Carey, Mark, 2000. "Credit risk rating systems at large US banks," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 167-201, January.
    14. Y Kim & S Y Sohn, 2007. "Technology scoring model considering rejected applicants and effect of reject inference," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(10), pages 1341-1347, October.
    15. Pierre Dussauge & Stuart Hart & Bernard Ramanantsoa, 1992. "Strategic Technology Management," Post-Print hal-00708987, HAL.
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    Cited by:

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    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. Won Sang Lee & So Young Sohn, 2017. "Identifying Emerging Trends of Financial Business Method Patents," Sustainability, MDPI, vol. 9(9), pages 1-21, September.
    4. 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.
    5. Pranith K. Roy & Krishnendu Shaw, 2023. "A credit scoring model for SMEs using AHP and TOPSIS," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 372-391, January.
    6. Ju, Yonghan & Jeon, Song Yi & Sohn, So Young, 2015. "Behavioral technology credit scoring model with time-dependent covariates for stress test," European Journal of Operational Research, Elsevier, vol. 242(3), pages 910-919.
    7. 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.

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