Identifying Early Adopters of Information Systems by Inductive Learning Using Decision Tree Method

의사결정나무법을 이용한 귀납적 학습방법에 의한 정보시스템 수용자 세분화

  • 이민수 (농촌진흥청 농촌자원개발연구소) ;
  • 최영찬 (서울대학교 농업생명과학대학 농경제사회학부) ;
  • 유병준 (고려대학교 경영대학 경영학과)
  • Published : 2007.04.30

Abstract

In diffusing an information systems(IS), the provider of the IS can be more effective if they can identify user groups who can adopt the system early. By focusing on the user groups, system providers can encourage them to adopt the IS. After the early adopters adopt an IS, the diffusion of the system to other groups can be easier by early adopters' voluntary advertisement and help in adopting the IS. Instead of discrete choice methods which are usually used for this purpose, we suggest a decision tree method. Compared to discrete choice methods, this method is more accurate for prediction and can easily identify non-linear segments of groups. By testing the data of adopters of an IS in agricultural business, we show the excellence of this method in identifying target groups to focus on. This method would help system providers to diffuse their systems by starting from early adopters.

한 정보시스템을 소개 및 전파 시에, 만약 정보시스템의 공급자가 조기 수용성향을 가진 사용자 집단을 식별해낼 수 있다면, 그 집단에 대한 집중적인 권장 및 홍보를 통하여 더욱 효율적으로 시스템을 전파할 수 있을 것이다. 또한, 도입 이후 그 조기수용자들은 타 수용대상 집단들에 대한 시스템의 자발적 홍보와 수용 시의 도움들을 통해 시스템 도입을 더욱 용이하게 하는 효과를 가져오게 할 수 있다. 이와 같은 조기 수용자군 식별 목적을 위하여, 본 논문은 기존 주로 사용되어 온 이산선택기법 대신, 의사결정나무를 이용한 식별기법을 제안한다. 기존의 이산선택기법에 비하여 이 기법은 집단 예측에 있어서 더욱 정확하며, 비선형적으로 세분화된 그룹을 식별할 수 있는 장점도 가지고 있다. 이와 같은 효과의 검증을 위하여, 본 논문은 농업분야의 한 정보시스템 도입시의 실증데이터를 이용하여 목표집단 식별상의 의사결정나무기법의 우수성을 입증하였다. 본 기법은 앞으로 조기 수용자 집단 식별목적에 실질적으로 시스템 개발 공급자에게 이용될 수 있을 기법으로 기대된다.

Keywords

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