Digital Transformation Drives Sustainable Innovation Capability Improvement in Manufacturing Enterprises: Based on FsQCA and NCA Approaches

In recent years, digital technologies represented by the Internet, cloud computing, big data, the Internet of Things, and artificial intelligence have developed rapidly and become a strong driving force for economic development. They have effectively driven manufacturing enterprises to innovate their production methods and management models and enhance their innovation capabilities. The improvement of the sustainable innovation capability of manufacturing enterprises is a complex system, which requires various types of collaborative coupling of digital transformation. Therefore, this paper constructs a comprehensive framework of sustainable innovation capability based on Complex System View, using 20 manufacturing enterprises in Dalian, China, as a sample to analyze the driving effects of digital transformation on the improvement of the sustainable innovation capability of manufacturing enterprises by using a mixture of NCA and QCA methods. The findings are: (1) A single type of digital transformation does not constitute a necessary condition for high sustainable innovation capacity, and the digital transformation of service, model and organization play a more universal role in generating high sustainable innovation capability in manufacturing enterprises; and (2) The combination of three paths can make various types of digital transformations couple and interact to achieve the high sustainable innovation capability of manufacturing enterprises in Liaoning Province, including the Pure Product Digital Transformation Driving Path, Model + Organization Digital Transformation Driving Path, and Comprehensive Digital Transformation Driving Path. In this paper, four conditional configurations are found to lead to non-high sustainable innovation capability, which can be summarized as the Process Digitalization Deficiency Type and Organization Digitalization Limitation Type. The findings of this paper have important theoretical and practical implications for making scientific and reasonable digital transformation decisions to improve the sustainable innovation capability of manufacturing enterprises.