Search Results (2)

This study investigates the relationship between digital transformation and the substantive innovation of single champion manufacturing enterprises (SCMEs). Using panel data from listed SCMEs between 2017 and 2022, we applied a double fixed-effects model to analyze the effects of digital transformation on substantive innovation performance. The findings indicate that digital transformation significantly enhances SCMEs’ innovation performance, exhibiting a positive linear relationship. However, as the degree of transformation increases, the effect gradually diminishes, following an inverted U-shaped pattern. Furthermore, we introduced a theoretical framework of enterprise niche resilience and examined the moderating roles of niche resource resilience and niche structural resilience in the relationship between digital transformation and innovation performance. The results show that factors such as human resource resilience, capital resource resilience, supply chain resilience, and shareholder governance resilience play critical roles in enhancing innovation capabilities and supporting the digital transformation process. Finally, from the perspectives of macro-, meso-, and microenterprise niche positioning, we further discussed the heterogeneity across different regions, industrial chains, and lifecycle stages. This research provides new insights into innovation theory, niche theory, and resilience theory, offering valuable practical implications for policymakers and SCME managers to respond to global risks and drive domestic industrial upgrades. Full article

As a representative of potential “hidden champions”, a concept originating in Germany, specialized and innovative Little Giant Enterprises (LGEs) have become exemplary models for small and medium-sized enterprises (SMEs) in China. These enterprises are regarded as crucial support for realizing the strategy of building a strong manufacturing country and addressing the weaknesses in key industrial areas. This paper begins by examining urban agglomerations, which serve as the main spatial carriers for industrial restructuring and high-quality development in manufacturing. Based on data from LGEs in the Yangtze River Delta (YRD) and Pearl River Delta (PRD) urban agglomerations from 2019 to 2023, the study employs the Random Forest (RF) and Multi-scale Geographically Weighted Regression (MGWR) methods to conduct a comparative analysis of their spatial patterns and influencing factors. The results are as follows: (1) LGEs exhibit spatial clustering in both the YRD and PRD regions. Enterprises in the YRD form a “one-axis-three-core” pattern within a distance of 65 km, while enterprises in the PRD present a “single-axis” pattern within a distance of 30 km, with overall high clustering intensity. (2) The YRD is dominated by traditional manufacturing and supplemented by high-tech services. In contrast, the PRD has a balanced development of high-tech manufacturing and services. Enterprises in different industries are generally characterized by a “multi-point clustering” characteristic, of which the YRD displays a multi-patch distribution and the PRD a point–pole distribution. (3) Factors such as industrial structure, industrial platforms, and logistics levels significantly affect enterprise clustering and exhibit scale effects differences between the two urban clusters. Factors such as industrial platforms, logistics levels, and dependence on foreign trade show positive impacts, while government fiscal expenditure shows a negative impact. Natural geographical location factors exhibit opposite effects in the two regions but are not the primary determinants of enterprise distribution. Each region should leverage its own strengths, improve urban coordination and communication mechanisms within the urban cluster, strengthen the coordination and linkage of the manufacturing industry chain upstream and downstream, and promote high-tech industries, thereby enhancing economic resilience and regional competitiveness. Full article