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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2022.2
- 수록면
- 163 - 178 (16page)
- DOI
- 10.37272/JIECR.2022.02.22.1.163
이용수
초록· 키워드
오류제보하기
In recent years, in the manufacturing sector, smart factories have emerged as an indispensable phenomenon worldwide. Globally, the industrial structure is shifting from the manufacturing industry to the service industry due to the global long-term economic downturn, labor costs, rising raw materials, and the avoidance of the manufacturing industry. Meanwhile, with the introduction of smart factories through information and communication technology (ICT) convergence, the manufacturing industry is changing into a different paradigm from the past. Above all, the development of various technologies such as Big Data, Artificial Intelligence (AI), Internet of Things (IoT), and 5G is changing all management paradigms. It has been argued that this will become a very important factor in determining the competitiveness of a company in the future. Therefore, this study aims to empirically verify the effect of smart factory quality factors on acceptance intention and intelligence promotion intention for small and medium-sized manufacturing enterprises that are currently using smart factories.
This study, in particular, was analyzed to be affected by the perceived usefulness of the system of field workers through the use of smart factories in the manufacturing field in this study. It was confirmed that there is a close correlation between education and field-specific customization. In addition, it was confirmed that if field workers" satisfaction with the quality of the smart factory system is high, it can have a great influence on the acceptance intention. Lastly, unlike previous studies on smart factories, this study focused on how smart factory system service factors affect the intention to pursue through which pathways.
This study, in particular, was analyzed to be affected by the perceived usefulness of the system of field workers through the use of smart factories in the manufacturing field in this study. It was confirmed that there is a close correlation between education and field-specific customization. In addition, it was confirmed that if field workers" satisfaction with the quality of the smart factory system is high, it can have a great influence on the acceptance intention. Lastly, unlike previous studies on smart factories, this study focused on how smart factory system service factors affect the intention to pursue through which pathways.
목차
Abstract
Ⅰ. Introduction
Ⅱ. Previous research
Ⅲ. Research model
Ⅳ. Methodology
Ⅴ. Results
Ⅵ. Conclusion and future research
Reference
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