​ “Digital Convergence Capacity of SMEs in Manufacturing: Driving Factors, Determinants and Conditions” the National Natural Science Fund of China [grant number 72002008] (Principal Investigator)

Release time:2022-08-17Views:18


 

Abstract: Providing answers to all these questions of increasing/expanding digital convergence capacity is a highly chalalenging job. In the present project, we will limit our endeavor to achieving four research objectives: driving factors, the determinants, moderation effects and operational functioning of the digital convergence. The impact of antecedents and determinants factors on digital convergence performance, even in the world has never been more considerable. There are an abundance of manpower, material and finical resources that can be devoted to building digital platforms by large corporations. The digital attribution gives Internet companies like Baidu, Alibaba and Tencent and other digital companies an inherent advantage, whereas manufacturing small and medium-sized enterprises (SMEs), which accounts for more than 90% of enterprise quantity, find themselves in the digital convergence predicament. However, they would become nimbler and more adaptable to changing market trends, compared with large businesses. It’s hard to play catch-up once they are on the leading edge of technology. Therefore, it’s vital to improve the digital convergence efficiency and effectiveness by making use of their own advantages as well as strong endorsement and empowerment of large corporations. Our aim is to establish a theoretical framework with integrating firm-level and customer level and empirically test it by addressing four fundamental questions: (1) what are the determinants of digital convergence deeply and effectively? (2) how many determinant factors interact and jointly determine digital convergence performance? (3) Which factors are the possible moderating role of in the effect of both digital market relationship and customer orientation on digital convergence performances? (4) What are the best paths for heterogeneous manufacturing SMEs (small and medium-sized enterprises). Both Structural Equation Modeling (SEM), Information Entropy and Hierarchical Regression were used in data

analyses. The theoretical and managerial implications of the research are

discussed.