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확장된 혁신저항모델을 활용한 스마트 팩토리 도입 수준 제고에 대한 연구

A study on Improving the Level of Introduction of Smart Factories Using the Extended Innovation Resistance Model

  • 박찬권 (경북대학교 건설환경에너지융합기술원)
  • Park, Chan-Kwon (Institute of Construction Environment Energy Convergence Technology, Kyoungpook National University)
  • 투고 : 2020.10.25
  • 심사 : 2021.03.20
  • 발행 : 2021.03.28

초록

본 연구는 중소 제조 기업들의 스마트 팩토리 관련 기술의 도입 및 사용과 관련하여 발생할 수 있는 혁신저항에 대한 연구이다. 확장된 혁신저항모델을 활용하여 혁신저항 선행요인들이 혁신저항에 미치는 영향 및 혁신저항이 사용의 도에 미치는 영향을 연구하는 것이다. 총 176부의 설문데이터를 연구에 활용하였으며, SPSS 25와 Smart PLS 2.0을 활용하여 연구를 진행하였다. 상대적 이점, 적합성, 지각된 위험, 사회적 영향, 조직특성은 혁신저항에 유의한 영향을 미치며, 혁신저항은 사용의도에 유의한 영향을 미치는 것으로 검정되었다. 연구에 따른 시사점으로서 확장된 혁신저장모델을 활용하여 스마트 팩토리 도입 및 사용의 수준을 제고하기 위한 방안을 긍정적인 요인과 부정적인 요인을 구분하여 제시하였으며, 이를 통해 제고하여야 하는 요인과 감소시켜야 하는 요인들을 구체적으로 제시하였다.

This study is a study on the innovation resistance that may arise in connection with the introduction and use of smart factory-related technologies by SMEs. It is to study the effect of the leading factors of innovation resistance on innovation resistance and the effect of innovation resistance on use intention by using the extended innovation resistance model. A total of 176 survey data were used for the study, and the study was conducted using SPSS 25 and Smart PLS 2.0. Relative advantage, suitability, perceived risk, social impact, and organizational characteristics have a significant effect on innovation resistance, and innovation resistance was tested to have a significant effect on the intention to use. As an implication according to the research, a plan to improve the level of introduction and use of smart factories using the expanded innovative storage model was presented by dividing positive and negative factors, and factors that should be improved and factors that should be reduced are presented. It was specifically presented.

키워드

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