비재무정보를 이용한 창업기업의 부실요인에 관한 실증연구

An Empirical Study on the Failure Factors of Startups Using Non-financial Information

  • 투고 : 2019.01.10
  • 심사 : 2019.02.26
  • 발행 : 2019.02.28

초록

본 연구의 목적은 창업기업의 부실에 영향을 미치는 비재무정보 분석을 통해 창업자와 창업지원기관에게 유용한 정보를 제공하여 창업기업의 성공률을 높여 기업부실로 인한 사회적 비용을 최소화하는데 기여하고자 한다. 본 연구는 창업기업을 대상으로 하고 있으며 신용보증기관에서 정의하고 있는 창업기업은 일반적으로 설립 5년이내 기업을 말한다. 연구에 사용된 자료는 2014년 1월부터 12월말까지 창업보증을 지원받은 기업중 2017년 12월말 기준으로 정상기업과 부실기업으로 구분하여 표본을 추출하였으며, 전체 표본기업의 수는 2,826개이며 정상기업 2,267개 (80.2%), 부실기업 559개 (19.8%)이다. 창업기업의 비재무정보를 창업자 특성정보, 창업기업 특성정보, 창업기업 자산정보, 창업기업 신용정보로 구분하여 교차분석과 로지스틱회귀분석을 실시하였다. 단변량분석인 교차분석 결과 개인신용등급, 동업계종사유무, 거주주택보유유무, 종업원보유유무, 재무제표보유유무가 유의한 변수로 선정되었다, 교차분석 결과 선정된 변수를 대상으로 다변량분석인 로지스틱회귀분석을 실시한 결과 개인신용등급, 동업계종사유무, 거주주택보유유무 등 3개 변수가 창업기업의 부실에 영향을 미치는 중요한 요인으로 나타났다. 이러한 결과는 기업경영에 있어 창업자의 개인신용과 경험, 창업기업의 자산의 중요성을 알 수 있었다. 창업지원기관은 이러한 결과를 창업기업 신용평가시스템에 반영하여야 할 것이며, 창업자는 창업교육시 개인신용의 중요성과 관리방안에 대한 연수가 필요하다. 이와 같은 분석결과는 창업자와 창업지원기관에게 유용한 비재무정보를 제공하여 창업기업의 부실을 최소화하는데 기여할 것이다.

The purpose of this study is to contribute to the minimization of the social cost due to the insolvency by improving the success rate of the startups by providing useful information to the founders and the start-up support institutions through analysis of non-financial information affecting the failure of the startups. This study is aimed at entrepreneurs. The entrepreneurs that are defined by the credit guarantee institutions generally refer to entrepreneurs within 5 years of establishment. The data used in the study are sampled from the companies that were supported by the start-up guarantee from January 2014 to December 2013 as the end of December 2017. The total number of sampled firms is 2,826, 2,267 companies (80.2%), and 559 non-performing companies (19.8%). The non-financial information of the entrepreneur was divided into the entrepreneur characteristics information, the entrepreneur characteristics information, the entrepreneur asset information and the entrepreneur 's credit information, and cross-tabulations and logistic regression analysis were conducted. As a result of cross-tabulations, univariate analysis showed that personal credit rating, presence in the industry, presence of residential housing, presence of employees, and presence of financial statements were selected as significant variables. As a result of the logistic regression analysis, three variables such as personal credit rating, occupation in the industry, and presence of residential house were found to be important factors affecting the failure of founding companies. This result shows the importance of entrepreneur 's personal credibility and experience and entrepreneur' s assets in business management. The start-up support institutions should reflect these results in the entrepreneur 's credit evaluation system, and the entrepreneurs need training on the importance of the personal credit and the management plan in the entrepreneurial education. The results of this analysis will contribute to the minimization of the incapacity of startups by providing useful non-financial information to founders and start-up support organizations.

키워드

참고문헌

  1. Altman, E.(1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. Journal of Finance, 23, 589-609. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x
  2. Bahn, S. S., Song, K. M., & Kim, S. T.(2009). A Study on the Credit Rating as an Indicator of Venture Success, Korea Journal of Business Administration, 22(1), 181-204.
  3. Bruderl, J., Preisendorfer, P., & Ziegle, R.(1992). Survival Chances of Newly Founded Business Organizations, American Sociological Review, 57(2). 227-242. https://doi.org/10.2307/2096207
  4. Choi, T. S., Kim, H. G., & Kim, S. H.(2002). A Comparison of the Discrimination of Business Failure Prediction Models, Journal of the Korean Operation Research and Management Science Society, 27(2), 1-13.
  5. Chu, I. S., & Kim, K. S.(2015). Study on the Survival Characteristics and the Survival Characteristics of Guaranteed Companies, KODIT REPORT 2015-4, Korea Credit Guarantee Fund.
  6. Dolinger, M. J.(1995). Entrepreneurship: Strategies and Resources, Austen Press.
  7. Falkenstein, E., Boral, A., & Carty, A. V.(2000). RiskCaleTM for Private Companies: Moody's Default Model, Moody's Investors Service, May.
  8. Hong, T. H., & Shin, T. S.(2007). Developing Corporate Credit Rating Models Using Business Failure Probability Map and Analytic Hierarchy Process, Journal of Information Systems, 16(3), 1-20.
  9. Huang, S. C., Tang, Y. C., Lee, C. W., & Chang, M. J.(2012). Kernel local Fisher discriminant analysis based manifold-regularized SVM model for financial distress predictions, Expert System with Applications, 39, 3855-3861. https://doi.org/10.1016/j.eswa.2011.09.095
  10. JO, Q. G.(2005). A Study on the Prediction Model of Coporate-Failure, Master thesis, Dongeui University.
  11. Kang, K. H.(2012). Developing a Model to Predict the Insolvency of Medium and Small General Contractors, Master thesis, Hanyang University.
  12. Kim, G. C.(2011). A Study on Corporate Failure Predicictions by Using Audit Opinions and Accounting Firm's Characteristics, Doctoral dissertation, Soongsil University.
  13. Kim, J. E.(2015). An empirical study on the factors influencing default of startups: mainly with youth strartups, Master thesis, Seoul National University Graduate School of Public Administration.
  14. Kim, N. H., & Nam, G. J.(2004). A Comparative Study on Analytical Model for Predicting Small and Medium-sized Enterprises, Guarantee Monthly, 285, 3-42.
  15. Kim, S. B., Jo, K. J., & Ji, P. L.(2011). The Analysis on the Causes of Corporate Bankruptcy with the Bankruptcy Prediction Model, Journal of Market Economy, 40(1), 85-106.
  16. Kim, S. H., & Byun, S. H.(2018). The Effect of Pre-entrepreneur's Individual Norm and Start-up Preparation Level on a Start-up Intention: Focusing on a Moderation Effect in Start-up Education, Asia-Pacifix Journal of business Venturing and Entrepreneurship, 13(1), 11-21. https://doi.org/10.16972/apjbve.13.1.201802.11
  17. Kim, Y. S.(2012). An Empirical Study on Predicting the Bankruptcy of SME and Venture Businesses through the Analysis of Non-Financial Factors. Doctoral dissertation, Konkuk University.
  18. Korea Technology Finance Corporation(2014). Analysis of Survival Rate and Influencing Factors of KOTEC-Supported Enterprises, Research in Technology Finance, 4(2), 151-206.
  19. Jang, Y. M., & Ha, K. S.(2018). A study on the Effect of Senior's Entrepreneurial Competency on Entrepreneurial Intention: Focused on the Moderating Effect of Social Support, Asia-Pacific Journal of Business Venturing and Entrepreneurship, 13(3), 13-36. https://doi.org/10.16972/apjbve.13.3.201806.13
  20. Jong, G. W.(2014). A study on the default prediction model of SMES after supperting the credit guarantee, Master thesis, Hanyung University
  21. Laras, M., & Reznakova, M.(2015). Predicting bankruptcy under alternative conditions: the effect of a change in industry and time period on the accuracy of the model, Social and Behavioral Sciences, 213, 397-403.
  22. Lee, G. W., Kang, M. S., & Park, S. K.(2015). A Study on Survival Analysis of Small Business/Small Enterprises: Focusing on Businesses Supported by the Gangwon Credit Guarantee Foundation, Asia Pacific Journal of Small Business, 37(1), 57-75.
  23. Lee, S. J.(2014). An Emprical Study and Factor Analysis of Start-up Quality for Senior's Successful Start-up, Doctorial dissertation, Seokyeong University.
  24. Lee, S. R.(2016). An study on the impact of insolvency of start-ups that Founder characteristic and information, Master thesis, Hansung University
  25. Lin, T. H.(2009). A Cross Model Study of Corporate Financial Distress Prediction in Tawiwan: Multiple discriminant analysis, logit, probit and neural networks model, Neurocomputing, 72, 3507-3516. https://doi.org/10.1016/j.neucom.2009.02.018
  26. Moon, J. G.(2015), An Empirical Study on the Failure Prediction of the Manufacturing Firms in KOSDAQ, Doctoral dissertation, The Graduate School of Venture, Hoseo University.
  27. Nam, G. J., & Lee, D. M.(2018). An Empirical Study on Survival Characteristics of Young Start-up Entrepreneurs(20-30s), Asia-Pacific Journal of Business Venturing and Entrepreneurship, 13(5), 63-72.
  28. Ohlson, J. A.(1980). Financial Ratios and the Probabilistic Prediction of Bankruptcy, Journal of Accounting Research, 18(1), 109-131. https://doi.org/10.2307/2490395
  29. Park, M. H.(2012). Factors affecting survival probability of self-employment at older ages: comparison of self-employment start-ups before and after age 50, Doctoral dissertation, Ewha University.
  30. Park, S. H.(2014). Analysis of spatial features and determinants of survival period of company gone out of business, Doctoral dissertation, Pusan University.
  31. Park, W. G.(2017). A Study on the Usefulness of Industry-related Variables in Predicting the Failure of SMEs: Focusing on unlisted SMEs, Doctoral dissertation, Busan University.
  32. Preisendorfer, P., & Voss, T.(1990). Organizational Mortality of Small Firms: The Effects of Entrepreneurial Age and Human Capital, Organizational Studies, 11(1), 107-129. https://doi.org/10.1177/017084069001100109
  33. Tseng. F. M., & Hu, Y. C.(2010). Comparing four bankruptcy prediction models: Logit, quadratic interval logit, neural and fuzzy neural networks, Expert Systems with Application, 37, 1846-1853. https://doi.org/10.1016/j.eswa.2009.07.081
  34. Vesper, K. H.(1980). New venture strategies. Englewood Cliffs, NJ: Prentice-Halp.
  35. Wang. G. Z.(2015). A Study on the Prediction to Failure of medium and small sized Enterprises in China, Master thesis, Paichai University.
  36. Yoo, W. J.(2017). Effects of Non-financial Factors on SME's Financial Soundness, Doctoral dissertation, Konkuk University.
  37. Yoon, B. S., & Seo, Y. W.(2016). An Empirical Analysis of the Effects of Startup' Activities of Preparatory Stage and Early Stage on Performmance, Asia-Pacific Journal of Business Venturing and Entrepreneurship, 11(4), 1-15.
  38. Yun, S. Y., Kang, M. S., & Lee, H. T.(2016). Is Non-finacial Data Important for Credit-rating of Micro-Enterprises?, Management Consulting Research, 16(2), 37-46.
  39. Zavgren, C.(1985). Assessing the Vulnerability to Failure of American Inderstrial Firms: A Logistic Analysis, Journal of Business Finance & Accounting, 12(1), 19-45. https://doi.org/10.1111/j.1468-5957.1985.tb00077.x
  40. 왕관주(2012). 중국 중소기업의 부실예측 모형에 관한 연구: 석유, 화학, 플라스틱업을 중심으로, 석사학위논문. 배재대학교.