A Cross-Country Comparison of Institutional Functions and Innovation Diffusion in National Innovation Systems: the Case of Taiwan and China
|關鍵字:||國家創新系統;機構功能;創新擴散;網絡分析;台灣;中國;National innovation system;Institutional function;Innovation diffusion;Network analysis;Taiwan;China|
Since the appearance of Freeman’s work on the technological development of Japan, national innovation systems (NIS) have become a popular concept among policy-makers seeking to develop the innovation and competitiveness of national or regional economies, while also attracting the attention of numerous researchers working on institutional economics and innovation. NIS is generally recognized as comprising complex functions and interactions among various institutions involved in the generation, diffusion, and utilization of innovations. When institutions and interactions organized appropriately, NISs are a powerful engine of economic progress, and otherwise poorly organized and connected they may seriously inhibit the progress of innovation. Therefore, the study of NISs offers new rationales and new approaches for the technology policies of governments. Since the Chinese Civil War in 1949, Taiwan and China have been separated into two independent economies. However, the Taiwan’s government allowed its citizens to travel to Mainland China to visit relatives in 1987, opening up interplay between the two sides not only in the part of visiting relatives and traveling but also in the part of business activities. Given their common language, culture, race and history, plus their geographical proximity, Taiwan and China have been and will continue to influence and even cooperate with each other in science and technology activities. The concept of a “national” innovation system is becoming less meaningful as cross-border linkages and information flows increase along with the internationalization of corporate R&D. Therefore, the objectives of this study are to examine the similarities and differences in the innovation systems of Taiwan and China, to compare their advantages and disadvantages, and finally to propose relevant policy implications based on the results of these comparisons for the policymakers of the two sides. The critics of NISs research argue that the size and linkages of NISs is too complicated to be measured, and therefore, this study employs two complementary approaches to examine and compare the innovation systems of Taiwan and China. First, this study presents a qualitative analytical framework to study and compare the innovation systems of Taiwan and China in order to get an overall examination. For recognizing the structural characteristics of innovation systems, six major functions of generic types of institutions involved in the systems are examined: policy formulation, performing R&D, financing R&D, promotion of human resource development, technology bridging, and promotion of technological entrepreneurship. Not only does it describe the role and performance of particular institutions, but this framework also explores four major interactions among these institutions for illustrating the dynamics and efficiency of innovation systems, that is, R&D collaboration, informal interaction, technology diffusion, and personnel mobility. Although qualitative approaches can separately describe the actual situations of a system, it is difficult to display the essential conditions of a system in an integrated manner. In addition, the innovation diffusion is the main driving force for Taiwanese and Chinese NISs because of their economic nature of catch-up and manufacturing orientation. Therefore, this study employs a quantitative examination as a second approach to address the innovation diffusion within industries and between industrial and institutional/foreign sub-systems of the two economies. In the first part of the quantitative examination, this study compares the structure of intersectoral innovation diffusion in the Taiwanese and Chinese innovation systems. The network of intersectoral innovation diffusion is constructed and proxied by the product-embodied R&D flow matrices calculated by the use of data on input-output tables and sectoral R&D expenditure. The two networks are structurally compared with the help of methodologies derived from the network analysis, which are conducted at the national, cluster and sectoral levels to thoroughly examine the multi-embededness of the sectors situated in a technological diffusion network. In the second part, this study employs the above techniques to compare the network characteristics of innovative interaction between industrial and institutional/foreign sub-systems in both innovation systems. The results show that the two systems have similar distributions of key industries, including the cores, i.e. machinery and equipment, electronic parts and components, and the sources, i.e. chemicals and basic metals, of innovation flows. However, significant differences also exist. For example, the Taiwanese industrial system is characterized by higher degrees of systemic connection and hierarchy, as well as appears capable of more efficient innovation diffusion among vertically related industries due to its more effective clusters, while the Chinese industrial system has lower density, less centralization, and looser clusters. However, China’s looser industrial innovation sub-system is substituted by higher density of institutional and foreign sub-systems. In addition, it also reveals that the developing trajectory of Chinese economy exist a time lag behind Taiwan. On the one hand, Chinese government can benefit from referring to the Taiwanese technological development experience. On the other hand, Taiwanese enterprises can expand their business territories into mainland China to achieve economies of scale. All of these research results reflect that they both have unique characteristics, while also sharing numerous complementary features. Consequently, these phenomena suggest the possibility of future cooperation between the two innovation systems, and then this study proposes possible approaches to achieving cooperation for the two sides. It can offer innovation policy-makers on both sides valuable insights based on the underlying similarities/differences and comparative advantages/disadvantages between the two innovation systems.