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기계학습 기반 고성장기업 예측모형 구축 및 실증에 관한 연구

Predicting High Growth Firm based on Machine Learning Technique

장훈
한국중소기업학회|2023.03|중소기업연구|제45권 제1호|pp. 55-75

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참고문헌

키워드

혁신기업기계학습중소기업Machine Learning예측모형고성장기업High Growth FirmInnovative FirmSmall and Medium Enterprises Prediction model
주제분류경영학

초록

저성장 기조가 고착화되는 뉴노멀 시대가 본격화되며, 지속 가능한 성장과 일자리 창출에 크게 기여할 수 있는 고성장기업을 발굴하고 육성하려는 니즈가 점점 커지고 있다. 이에 따라, 본 연구에서는 사전에 고성장기업으로 성장할 가능성이 높은 기업을 선별하기 위해 기계학습 기반 예측모형을 구축하고, 성능을 평가해보았다. 특히, 본 연구에서는 기업의 국가연구개발사업 참여 여부가 예측모형 구축에 미치는 영향을 확인해보고자, 기업의 국가연구개발사업 데이터를 확보하여 기업 재무 데이터와 병합 후 분석에 활용하였다. 그리고, 분류 문제에 널리 활용되는 다양한 기계학습 기법을 적용해보고 모형별 성능을 종합적으로 비교 분석하였다. 그 결과, 가장 나은 예측력을 보여준 모델의 성능은 AUC 기준 0.85 수준으로 우수하였으며, 고성장기업 예측에는 기업의 성장성과 효율성을 나타내는 지표가 다른 지표보다 중요한 역할을 한다는 사실을 발견하였다. 저자는 본 연구가 추후 데이터 기반의 고성장기업 식별 및 지원시스템 구축에 기여할 수 있는 토대가 되기를 기대한다.

Abstract

As the new normal era is in full swing, there is a growing need to discover and nurture high-growth firms that contribute to sustainable economic growth and job creation. Motivated by this, we built a machine-learning based prediction model to select firms that are likely to grow into high-growth firms. Specifically, we employed both firms’ financial and national R&D participation data and applied various machine-learning techniques that are widely used in solving classification problems. As a result of empirical analysis, we achieved a reasonable performance of around 0.85 in terms of AUC from the best-performing model that we used. We also confirmed that firm’s financial characteristics play a more important role in predicting high growth than other factors. We believed that this study will shed light on further studies on the establishment of a data-based high-growth firm support system.

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