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A Study on Non-financial Factors Affecting the Insolvency of Social Enterprises

사회적기업의 부실에 영향을 미치는 비재무요인에 관한 연구

  • Yong-Chan, Chun (Dept. of Advanced Industry Fusion, Konkuk University) ;
  • Hyeok, Kim (Dept. of Advanced Industry Fusion, Konkuk University) ;
  • Dong-Myung, Lee (Dept. of Advanced Industry Fusion, Konkuk University)
  • 전용찬 (건국대학교 신산업융합학과) ;
  • 김혁 (건국대학교 신산업융합학과) ;
  • 이동명 (건국대학교 신산업융합학과)
  • Received : 2023.08.03
  • Accepted : 2023.11.20
  • Published : 2023.11.28

Abstract

This study aims to contribute to the reduction of the failure rate and social costs resulting from business failures by analyzing factors that affect the insolvency of social enterprises, as the role of social enterprises is increasing in our economy. The data used in this study were classified as normal and insolvent companies among social enterprises (including prospective social enterprises) that were established between 2009 and 2018 and received credit guarantees from credit guarantee institutions as of the end of June 2022. Among the collected data, 439 social enterprises with available financial information were targeted; 406 (92.5%) were normal enterprises, and 33 (7.5%) were insolvent enterprises. Through a literature review, eight non-financial factors commonly used for insolvency prediction were selected. The cross-analysis results showed that four of these factors were significant. Logistic regression analysis revealed that two variables, including corporate credit rating and the personal credit rating of the representative, were significant. Financial factors such as debt ratio, sales operating profit rate, and total asset turnover were used as control variables. The empirical analysis confirmed that the two independent variables maintained their influence even after controlling for financial factors. Given that government-led support and development policies have limitations, there is a need to shift policy direction so that various companies aspiring to create social value can enter the social enterprise sector through private and regional initiatives. This would enable the social economy to create an environment where local residents can collaborate to realize social value, and the government should actively support this.

본 연구는 우리 경제에서 사회적기업의 역할이 증가함에 따라, 사회적기업의 부실에 영향을 미치는 요인을 분석하여 부실률을 낮추고 기업부실로 인한 사회적 비용을 감소하는데 도움이 되고자 한다. 본 연구에 사용된 데이터는 신용보증기관의 신용보증을 지원받고, 2009년부터 2018년 사이에 설립된 사회적 기업(예비 사회적기업 포함) 중에서 2022년 6월말 기준으로 정상기업과 부실기업으로 분류하였다. 수집된 사회적기업의 수는 재무정보 활용이 가능한 439개를 대상으로 하였으며, 정상기업은 406개(92.5%), 부실기업은 33개(7.5%)이다. 선행연구를 통하여 부실예측에 주로 사용하는 비재무적요인 8개를 선정하였다. 교차분석 결과 4개가 부실에 대하여 유의한 변수로 나타났고. 채택된 4개의 변수를 대상으로 로지스틱 회귀분석을 한 결과로 기업신용등급, 대표자개인신용등급 등 2개 변수가 부실에 유의한 변수로 채택되었다. 또한 부채비율, 매출액영업이익율, 총자산회전율 등 재무요인을 통제변수로 사용하여 분석을 수행하였다. 실증분석 결과, 사회적 기업의 부실에 영향을 미치는 독립 변수들이 재무적 요인을 통제한 상태에서 2개 변수가 영향력을 유지하고 있음이 확인되었다. 지금까지와 같은 정부 주도의 육성·지원 정책으로는 한계가 있어 민간·지역의 자발적인 주도로 다양한 사회적 가치를 지향하는 기업들이 사회적기업으로 유입되고 사회적경제 주체와 지역·주민이 함께 연대하여 사회적가치를 실현할 수 있는 환경을 조성하고 정부는 이를 적극적으로 지원할 수 있도록 정책의 방향을 전환할 필요가 있다.

Keywords

References

  1. S. J. Oh. (2021). The effect of employee characteristics and organizational characteristics of social enterprises on organizational performance. Doctoral dissertation. Keimyung University, Daegu. 
  2. J. A. Kerlin. (2006). Social Enterprise in the United States and Europe: Understanding and Learning from the Differences. International Journal of Voluntary and Nonprofit Organizations, 17(3), 246-262.  https://doi.org/10.1007/s11266-006-9016-2
  3. G. S. Kim. (2022). A Study on the Sustainability of Social Enterprises: Mediating Effect of Business Performance and Moderating Effect of Social Capital. Doctoral dissertation. Seoul Venture University, Seoul. 
  4. J. M. Park. (2021). A Study on the Types of Social Enterprises in Korea and the Relationships Between the State, Market, and Civil Society. Doctoral dissertation. Korea University, Seoul. 
  5. S. H. Bae. (2019). A Study on the Performance of Social Enterprise. Doctoral dissertation. Dankook University, Yongin Gyeonggi-do. 
  6. Korea Social Enterprise Promotion Agency. (2023). Law on Promotion of Social Enterprises. https://www.socialenterprise.or.kr. 
  7. F. Brouard & S. Larivet. (2020). Essay of Clarifications and Definitions of The Related Concepts of Social Enterprise, Social Entrepreneur and Social Entrepreneurship. handbook of Research on Social Entrepreneurship, 29-56, Chetelham: Edward Elgar Publishing. 
  8. J. S. Moon. (2020). A Study on the Effect of the Corporate Characteristics on Sustainability Mediated by Performance: Focusing on Social Enterprises in Busan City. Doctoral dissertation. Pukyong National University, Busan. 
  9. Ministry of Employment and Labor. (2023). The 3rd Social Enterprise Fostering Basic Plan ('18~'22). https://www.moel.go.kr. 
  10. J. H. Kim. (2021). A Study on the Factors Affecting the Default of Credit Guarantees in Small Business Start-up Companies: Focusing on start-up companies in Seoul . Master's dissertation. Yonsei University, Seoul. 
  11. J. E. Kim. (2015). An empirical study on the factors influencing default of startups: Mainly with youth startups. Master's dissertation. Seoul National University, Seoul. 
  12. G. J. Nam, D. M. Lee & L. Chen. (2019). An Empirical Study on the Failure Factors of Startups Using Non-financial Information. Asia-Pacific Journal of Business Venturing and Entrepreneurship, 14(1), 139-149.  https://doi.org/10.16972/apjbve.14.1.201902.139
  13. W. H. Beaver. (1966). Financial Ratios As Predictors of Failure. Journal of Accounting Research, 4, 71-111.  https://doi.org/10.2307/2490171
  14. J. A. Ohlson. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of accounting research, 109-131. 
  15. M. Zmijewski. (1984). Methodological Issues Related to the Estimation of Financial Distress Prediction Models. Journal of Accounting Research, 22, 59-82.  https://doi.org/10.2307/2490859
  16. T. S. Choi, H. K. Kim & S. H. Kim. (2002) A Comparison of the Discrimination of Business Failure Prediction Models. Journal of the Korean Operations Research and Management Science Society, 27(2), 1-13. 
  17. G. C. Kim. (2011). A Study on Corporate Failure Predictions by Using Audit Opinions and Accounting Firm's Characteristics. Doctoral dissertation. Soongsil University, Seoul. 
  18. K. W. Jung. (2014). A study on the default prediction model of SMES after supporting the credit guarantee. Master's dissertation. Hanyang University, Seoul. 
  19. J. G. Moon. (2015). An Empirical Study on the Failure Prediction of the Manufacturing Firms in KOSDAQ. Doctoral dissertation. Hoseo University, Seoul. 
  20. Y. S. Kim. (2012). An Empirical Study on Predicting the Bankruptcy of SME and Venture Businesses through the Analysis of Non-Financial Factors. Doctoral dissertation. Konkuk University, Seoul. 
  21. W. J. Yoo. (2017). Effects of non-financial factors on SME's financial soundness. Doctoral dissertation. Konkuk University, Seoul. 
  22. S. S. Bahn, K. M. Song & S. T. Kim. (2009). A Study on the Credit Rating as an Indicator of Venture Success. Korea Journal of Business Administration, 22(1), 181-204. 
  23. T. H. Hong & T. S. Shin. (2007). Developing Corporate Credit Rating Models Using Business Failure Probability Map and Analytic Hierarchy Process. Journal of information systems, 16(3), 1-20. 
  24. I. R. Lee & D. C. Kim. (2015). An Evaluation of Bankruptcy Prediction Models Using Accounting and Market Information in Korea. Asian Review of Financial Research, 28(4), 625-665. 
  25. E. I. Altman. (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
  26. L. R. Gilbert, K. Menon & B. Schwartz. (1990). Predicting bankruptcy for firms in financial distress. Journal of Business Finance & Accounting, 17(1), 161-171.  https://doi.org/10.1111/j.1468-5957.1990.tb00555.x
  27. K. Keasey & P. McGuinness. (1990). Small new firms and the return to alternative sources of finance. Small Business Economics. 2(3), 213-222.  https://doi.org/10.1007/BF00389529
  28. E. I. Altman & P. Narayanan. (1997). Financial Markets, Institutions and Instruments. New York University Salomon Center. 
  29. E. Falkenstein, A. Boral & A. V. Carty. (2000). RiskCaleTM for Private Companies: Moody's Default Model. Moody's Investors Service, May. 
  30. H. J. Lim. (2016). Firm Characteristics and Default Predictability: Relationship-Banking, Age, and Size. Journal of Korean Economic Analysis, 22(1), 81-142. 
  31. W. G. Park. (2017). A Study on the Usefulness of Industry-related Variables in Predicting the Failure of SMEs: Focusing on unlisted SMEs. Doctoral dissertation. Pusan National University, Busan. 
  32. G. J. Nam. (2020). Young Start-ups Using Survival Analysis Method Study on Derivation of Survival Factors. Doctoral dissertation. Konkuk University, Seoul. 
  33. D. H. Cho. (2017). Performance Evaluation and Policy Suggestions of Social Enterprises in Seoul. Seoul Institute Policy Report, 225, 1-20. 
  34. J. Y. Lee. (2021). A Study on the Effect of Internal and External Factors of Self-employed Business in Seoul on the default of Credit Guarantee: Focused on the start-up guarantee of the Seoul Credit Guarantee Foundation. Master's dissertation. Yonsei University, Seoul. 
  35. G. W. Lee, M. S. Kang & S. K. Park. (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. 
  36. I. S. Choo & K. S. Kim. (2015). A Study on Survival Characteristics and Survival Determinants of Guarantee Companies. KODIT REPORT 2015-4. Daegu: Korea Credit Guarantee Fund. 
  37. J. Y. Ryu, J. Nam & C. H. Yi. (2014). Analysis on the Survival Rate and Impact Factors on Survival Duration for Startup Medium and Small-sized Firms in Seoul. Journal of the Korean Urban Management Association, 27(4), 247-271. 
  38. Y. M. Kim & S. J. Kim. (2013). Role of Initial Assets: Entrepreneurs'Attempts to link the Startup Firms to the Environment and their Impacts on firm Survival. Journal of Strategic Management, 16(2), 1-22. 
  39. J. W. Lee & S. H. Lee. (2004). Failure Factors of High-tech Ventures: an Empirical Study. Korean Journal of Management, 12, 229-274. 
  40. G. W. Lee. (2013). A study on survival analysis of small businesses / small enterprises: Focusing on businesses supported by the Gangwon Credit Guarantee Foundation. Master's dissertation. Kangwon National University, Chuncheon Gangwon State. 
  41. T. H. Kim. (2012). Analysis for Survival Factors in the Cultural Contents Industry. The Journal of the Korea Contents Association, 12(2), 255-264.  https://doi.org/10.5392/JKCA.2012.12.02.255
  42. S. Y. Yun, M. S. Kang & H. T. Lee (2016). Is Non-financial Data Important for Credit-rating of Micro-Enterprises?. Korean Management Consulting Review, 16(2), 37-46. 
  43. T. K. Ha. (2013). An Empirical study on Fostering and Drawing Longevity Factors of Small and Medium-sized Enterprises Using Survival Analysis. Doctoral dissertation. Konkuk University, Seoul. 
  44. S. Y. Lee. (2019). A study on analysis of the Influence factors on survival probability of new technology-based start-ups: Focus on IOT industry. Master's dissertation. Pukyong National University, Busan. 
  45. Y. C. Lee. (2010). A Study on the Corporate Insolvency Prediction Model of Technology Guaranteed Firms Using Survival Analysis. Sogang Economic Papers, 39(3), 1-24. 
  46. S. B. Kim, K. J. Jo & P. L. Ji. (2011). The Analysis on the Causes of Corporate Bankruptcy with the Bankruptcy Prediction Model. Sogang Economic Papers, 40(1), 85-106.