Case Study on the Inherent Mechanisms Driving Industrial Innovation through Data Empowerment
Year: 2024
Type: article
Abstract: In the context of the profound integration of big data, artificial intelligence technologies, and industries, both data resources and digital technologies became crucial pillars supporting the development of industrial innovation. They played key roles in enhancing the innovation capabilities of industries. In this regard, the present study employed the specific case of the intelligent brain of the Taizhou Machine Tool Industry. Utilizing grounded theory, the research integrated relevant data through coding analysis and category extraction to construct a comprehensive theoretical model of the intrinsic mechanisms driving industrial innovation through data empowerment. The study revealed that the realization of data-empowered industrial innovation followed a logical path of 'data resource services data capability spillover industrial innovation achievement.' Specifically, data empowerment operated across three dimensions: industrial resources, production, and ecology, effectively propelling the realization of industrial innovation. From a systematic perspective, this research analyzed the intrinsic mechanisms of data-empowered industrial innovation, deepening the theoretical understanding of industrial innovation. In the context of past industrial digitization transformation, these findings provided valuable insights for guiding industrial innovation development.
Authors: Xuecheng Yang, Yijun Zhou, Jing Guo
Institution: Beijing University of Posts and Telecommunications
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4403356790