The Journal of Society for e-Business Studies (한국전자거래학회지)

Society for e-Business Studies (한국전자거래학회)
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Classification of Performance Types for Knowledge Intensive Service Supporting SMEs Using Clustering Techniques: Focused on the Case of K Research Institute

클러스터링 기법을 활용한 중소기업 지원 지식서비스의 성과유형 분류: K 연구원 사례를 중심으로

  • Lee, Jungwoo (Graduate School of Management Consulting, Hanyang University) ;
  • Kim, Sung Jin (Graduate School of Management Consulting, Hanyang University) ;
  • Kim, Min Kwan (Institution of Knowledge Services, Hanyang University) ;
  • Yoo, Jae Young (Korea Institute of Science and Technology Information) ;
  • Hahn, Hyuk (Korea Institute of Science and Technology Information) ;
  • Park, Hun (Korea Institute of Science and Technology Information) ;
  • Han, Chang-Hee (Department of Business Administration, Hanyang University)
  • Received : 2017.07.12
  • Accepted : 2017.08.08
  • Published : 2017.08.31
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Abstract

In recent years, many small and medium-sized manufacturing companies are making process innovation and product innovation through the public knowledge services. K Research institute provides different types of knowledge services in combination and due to this complexity, it is difficult to analyze the performance of knowledge service programs precisely. In this study, we derived performance items from bottom-up viewpoints, rather than top-down approaches selecting those items as in previous performance analysis. As a result, 74 items were finded from 82 companies in the K Research Institute case book, and the final result was refined to 17 items. After that a case-performance matrix was constructed, and binary data was entered to analyze. As a result, three clusters were identified through K-means clustering as 'enhancement of core competitiveness (product and patent),' 'expansion of domestic and overseas market,' and 'improvement of operational efficiency.'

많은 제조기반의 중소기업들은 프로세스나 제품을 혁신하기 위해 공공 및 사기업의 지식서비스를 아웃소싱하고 있다. 본 연구의 사례인 K 연구원은 여러 지식서비스를 다양한 조합형태로 제공하는데, 이러한 제공형태의 복잡성으로 인해 지식서비스 사업성과를 정확히 분석한다는 것이 어려운 상황이다. 본 연구는 기존에 성과평가 항목을 상향식으로 선정하는 방식이 아닌 하향식 관점에서 성과항목을 도출하였다. K 연구원 지식서비스 수혜기업인 82개 기업사례에서 74개의 성과항목이 도출되었고, 최종적으로 17개 항목으로 정제하였다. 이후 사례-성과 행렬을 구조화하여 기업별 성과의 유무를 조사하여 이진 데이터로 입력하였다. K-means 클러스터링 분석을 통해 3개의 군집을 각각 '핵심 경쟁력 강화(제품 및 특허)', '국내 및 해외시장 확대', '운영 효율성 제고'로 식별할 수 있었다.

Keywords

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