Asia-Pacific Journal of Business Venturing and Entrepreneurship (벤처창업연구)

The Korean Society of Business Venturing (한국벤처창업학회)
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Design Thinking Methodology for Social Innovation using Big Data and Qualitative Research

사회혁신분야에서 근거이론 기반 질적연구와 빅데이터 분석을 활용한 디자인 씽킹 방법론

  • Park, Sang Hyeok (Gyeongnam National University of Science and Technology) ;
  • Oh, Seung Hee (Gyeongnam National University of Science and Technology) ;
  • Park, Soon Hwa (Gyeongnam National University of Science and Technology)
  • 박상혁 (경남과학기술대학교 창업대학원) ;
  • 오승희 (경남과학기술대학교 창업대학원) ;
  • 박순화 (경남과학기술대학교 창업대학원)
  • Received : 2018.05.14
  • Accepted : 2018.08.06
  • Published : 2018.08.31
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Abstract

Under the constantly intensifying global competition environment, many companies are exploring new business opportunities in the field of social innovation using creating shared value. In seeking social innovation, it is a key starting point of social innovation to clarify the problem to be solved and to grasp the cause of the problem. Among the many problem solving methodologies, design thinking is getting the most attention recently in various fields. Design Thinking is a creative problem solving method which is used as a business innovation tool to empathize with human needs and find out the potential desires that the public does not know, and is actively used as a tool for social innovation to solve social problems. However, one of the difficulties experienced by many of the design thinking project participants is that it is difficult to analyze the observed data efficiently. When analyzing data only offline, it takes a long time to analyze a large amount of data, and it has a limit in processing unstructured data. This makes it difficult to find fundamental problems from the data collected through observation while performing design thinking. The purpose of this study is to integrate qualitative data analysis and quantitative data analysis methods in order to make the data analysis collected at the observation stage of the design thinking project for social innovation more scientific to complement the limit of the design thinking process. The integrated methodology presented in this study is expected to contribute to innovation performance through design thinking by providing practical guidelines and implications for design thinking implementers as a valuable tool for social innovation.

지속적으로 심화되고 있는 글로벌 경쟁 환경 하에서 많은 기업들은 공유가치 창출 (CSV, Creating Shared Value)을 통해 사회혁신 분야에서 새로운 사업 기회를 모색하고 있다. 사회혁신을 추구함에 있어 해결하고자 하는 문제를 명확히 도출하고, 문제의 원인을 파악하는 것이 사회혁신의 핵심 출발점이다. 수많은 문제해결 방법론 중에 최근 다양한 분야에서 가장 많은 관심을 받는 것은 디자인 씽킹 (Design Thinking)이다. 디자인 씽킹은 인간의 필요에 공감하고 대중도 인식하지 못하는 잠재적 욕구를 발굴하여 해결하는 창의적 문제해결 방법론으로 비즈니스 혁신도구로도 사용되지만 사회 문제를 해결하는 사회혁신을 위한 도구로서 활발히 이용되고 있다. 그러나 디자인 씽킹 프로젝트를 수행하는 많은 주체들이 겪는 어려움 중의 하나가 관찰 데이터의 효율적 분석이 어렵다는 것이다. 오프라인 방식으로만 데이터를 분석할 경우 대량의 데이터를 처리하는데 시간이 오래 걸리며, 비정형데이터의 경우 처리가 어려워 관찰을 통해 어렵게 수집한 데이터로부터 문제점을 발견하는데 어려움을 호소한다. 이에 본 연구는 디자인 씽킹 프로세스의 한계점을 보완하고자 사회혁신을 위한 디자인 씽킹 프로젝트의 관찰단계에서 수집한 데이터 분석이 보다 과학적으로 이루어질 수 있도록 질적 자료 분석과 양적 자료 분석 방법을 균형 있게 사용하는 통합방법론을 제시하고자 한다.

Keywords

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