| In the era of Knowledge Economy, to vigorously develop high-tech industry is a strategic choice for China to seize the commanding heights of a new round of international competition. However, there exist significant gaps among China’s provinces as regards technology innovation efficiency of high-tech industry. It’s a continuation of China’s long-term region pattern that Eastern China is far ahead of Western China in development performance. As the development of high-tech industry becomes an increasingly powerful booster of economic growth, the spatial dissimilarity of its technology innovation efficiency will worsen the widening provincial gaps. Therefore, to study the impact factors and the spatial dissimilarity mechanism of technology innovation efficiency of high-tech industry, is helpful to get some policy implications about accelerating the transformation of economic growth and the construction of a socialist harmonious society. Both theory and practice suggest that spatial agglomeration is an important location characteristic of high-tech industry, and has an intrinsic relationship with technology innovation. Thus, industrial agglomeration is an unavoidable premise and starting point for the investigation of the impact factors and the spatial dissimilarity mechanism of technological innovation efficiency of China’s high-tech industry. Based on the above thinking and the related theories of spatial economics and innovation economics, this paper has tried to constructed an agglomeration-innovation model of high-tech industry, for the purpose of revealing the influence mechanism of industrial agglomeration on technology innovation efficiency, then has empirically examined it by some analysis methods.In the background of China’s economic trans formation and opening to the outside world, the agglomeration motives of high-tech industry include entrepreneurs with the spirit of innovation and entrepreneurship, localized tacit-knowledge spillover, vertical connection effect, innovation resources advantage, cost-saving effect, foreign direct investment and government’s role. Through the self-organization mechanism of industrial agglomeration, these motives further develop three effects, that is, generalized capital accumulation, knowledge local spillovers and innovation environment optimization, through which industrial agglomeration influences technology innovation efficiency and its spatial dissimilarity. As to the applicability of the above theoretical framework, this paper has provided empirical evidence from the provincial panel data during1997-2011, not including Tibet, Qinghai, Xinjiang, Hong Kong, Macao and Taiwan. The conclusions show, firstly, the interaction of physical capital and entrepreneur human capital has a "1+1>2" effect on innovation efficiency improvement, but only does physical capital and labor human capital match each other, innovation efficiency can be significantly improved; secondly, knowledge-spillover factors, such as foreign R&D, foreign technology acquisition, university R&D and technology assimilation are all conductive to enhance innovation efficiency, but domestic technology acquisition plays a reverse role, weakness in technology assimilation has led to its inadequate role in promoting innovation efficiency; thirdly, technology commercialization and consumption potential for new products of domestic and foreign markets, local horizontal competition and the development of productive service industry are all beneficial to upgrade innovation efficiency, but the role of government’s supports isn’t significant; fourthly, the innovation environment optimization effect and the interaction of the three agglomeration effects make the greatest contribution to the variance in innovation efficiency nationwide, the knowledge local spillovers effect and the innovation environment optimization effect are two main contributors to the variance in innovation efficiency in eastern China, the interaction of the three agglomeration effects is the biggest contributor to the variance in innovation efficiency in central China, the knowledge local spillovers effect and the interaction of the three agglomeration effects make the greatest contribution to the variance in innovation efficiency in western China; last but not the least, the innovation efficiency gaps between eastern, central and western parts of China and the innovation efficiency gaps within eastern China are the main composition of the variance nationwide, the three parts all have conditional β convergence, there exists a positive spatial association pattern that provinces with high innovation efficiency adjacent to each other, while provinces with low innovation efficiency adjacent to each other, confirming the existence of a two-club convergence of provincial innovation efficiency nationwide.In the normative analysis, existing literature lacks systematization while selecting the impact factors on technology innovation efficiency of high-tech industry, but this paper introduced industrial agglomeration into the analysis framework, and inducted three influence mechanisms, that is, generalized capital accumulation, knowledge local spillovers and innovation environment optimization derived from the agglomeration motives of high-tech industry, thus to make conclusions more systematic. In the empirical analysis, firstly, existing literature often lags one period while processing time-lag problem, but this paper is to lag four periods based on the Granger causality test, thus to make conclusions more objective; secondly, existing literature often uses coefficient of variation to investigate the trend of spatial dissimilarity of technology innovation efficiency of China’s high-tech industry, but this paper comprehensively used traditional growth convergence criteria and spatial correlation criteria, thus to make conclusions more robust. |
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