Success Factors of the Adoption of Smart Factory Transformation: An Examination of Korean Manufacturing SMEs
A smart factory is a fully automated production system enabled with novel digital technologies. Numerous studies consider its emergence as the arrival of a new wave of production innovation. However, research is scant on why its adoption rate has lagged behind the expectations of investors and polic...
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Published in | IEEE access Vol. 11; p. 1 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Piscataway
IEEE
01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | A smart factory is a fully automated production system enabled with novel digital technologies. Numerous studies consider its emergence as the arrival of a new wave of production innovation. However, research is scant on why its adoption rate has lagged behind the expectations of investors and policymakers. Thus, this study examined the effect of top management support for information systems, the existing production systems, the perceived usefulness of smart factories, and outsourcing experiences on firms' intention to adopt smart factories. Using the data of 1,067 Korean manufacturing small and medium-sized enterprises and structural equation modeling, this study finds that the performance of the existing production systems significantly increases the benefits expected from smart production systems, thus strengthening firms' intention to adopt smart factories. It also finds that the top management's support for information systems does not have a significant impact on the benefits expected from smart production systems. Furthermore, the overall mechanism of smart factories' adoption is strengthened when firms develop their production systems in-house. The results of this study provide useful insights for practitioners seeking to transform traditional production systems into smart factories. They also provide a strategic guideline regarding outsourcing experiences. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2022.3233811 |