Intelligent manufacturing is the main direction of manufacturing transformation and upgrading in developing countries. However, the issue of how to systematically improve the level of intelligent manufacturing in enterprises has not been effectively solved. The analyses in this study are based on data collected from a sample of 45 manufacturing companies in China from 2016 to 2018, and fuzzy set qualitative comparative analysis (fsQCA) was used to explore the impact of R&D, policy support, and enterprise characteristics on the level of intelligent manufacturing. The results find that three modes and four configurations for enterprises achieve high-level intelligent manufacturing. Specifically, firstly, enterprises with larger scale and better benefits can achieve high-level intelligent manufacturing with less R&D investment. Secondly, large enterprises with a high leverage ratio and high R&D capital investment can sacrifice short-term profitability and complete intelligent transformation through lower human capital investment. With the help of policy support, we maintain a high human capital investment and accelerate the completion of the intelligent upgrade. Thirdly, small companies can use higher R&D human capital investment to achieve the goal of intelligence. These findings provide valuable insights for enterprises to effectively achieve intelligent transformation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.