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The purpose of this paper is to add to the existing research about how corporate performance is influenced by their basic research (BR) investment. On this basis, the…
The purpose of this paper is to add to the existing research about how corporate performance is influenced by their basic research (BR) investment. On this basis, the authors examined the moderating effect of human capital structure (HCS) on the relationship between BR investment and corporate performance.
Hypotheses were tested using static and dynamic models to analyze a large-scale data of Chinese A-share listed companies.
This study provides empirical evidence that contributes to the research about how private BR investment influences corporate performance in the digital age. In addition, human resource is an important dynamic ability for enterprise development. Based on the dynamic capability theory, further research finds that the human resources practice on the knowledge stock can enhance the company’s dynamic capability, thereby enhancing the company’s core competitiveness.
The results may be affected by the context of the data set. This study considers the influence of private research investment type on corporate performance, further studies considering the influence of specific contextual variables, such as corporate industry differences, could yield richer insights that would help validate the results of this study.
This study provides useful information for managers. As well as increasing the investment in the BR of enterprise and creating the necessary conditions to increase the competitiveness of enterprise, they should strive to adjust the structure and quality of researchers involved in BR projects.
This research contributes to the enterprise’s BR investment and the management of human capital resource. It points that the investment of BR positively influences the corporate performance. In addition, the increasing of high-skilled labor’s proportion positively promotes the promotion of BR investment on corporate performance.
The purpose of this paper is to develop a double mechanism model to separate two foreign direct investment (FDI) intra-industry spillovers mechanisms: spillovers by FDI…
The purpose of this paper is to develop a double mechanism model to separate two foreign direct investment (FDI) intra-industry spillovers mechanisms: spillovers by FDI intensity and by FDI efficiency. This paper seeks to illustrate the potential use of the double mechanism model rather than provide precise estimates of spillovers. The evidence on the links between technology and the nature, size and mechanisms of FDI spillovers effects in economically developing countries is mixed.
A model is developed and tested, in principle. Empirical testing was conducted in two steps. In the first step, the authors examined the effect of each influencing factor to FDI spillovers separately. To complete this step, the authors divided the whole sample industry into sub-groups and tested them with the double-mechanism using ordinary least squares regression. This study applies Chinese National Bureau of Statistics manufacturing industry level data, for the years 2000, 2001 and 2002, including the food industry, beverage industry, textile industry, textiles and garments, chemicals and chemical products industry, overall manufacturing equipment, special equipment, computer and other electronic equipment manufacturing industries.
The analysis suggests significant differences between types of spillovers: export orientation of domestic firms mainly influences FDI spillovers by intensity; the capability gap between local and foreign firms influences spillovers by efficiency; and the growth of local firms influences both types of spillovers. This paper develops existing models of FDI and suggests that disaggregating spillovers types may provide important theoretical and policy insights.
This study has found, first, that compared with the classic single mechanism model, the double mechanism model is more appropriate for testing FDI intra-industry spillovers, as it is able to separate spillovers by intensity and spillovers by efficiency, which are shown as two distinct mechanisms for FDI spillovers. This allows a deeper analysis into each mechanism and the identification of relevant influencing factors.