China's Outward Direct Investment in the United States: From the perspective of agglomeration economies.

Over most of the last two decades, China's Outward Direct Investment (CODI) has reshaped the global economic landscape and attracted considerable attention. Although extensive research shows that CODI features agglomeration, there is limited research from the perspective of different patterns of agglomeration economies at the subnational level. It is unclear which patterns of agglomeration economies play a role in the location choice of CODI, especially with the variations of CODI in terms of entry mode and ownership. Therefore, based on the data of the CODI in the United States in the period 2000-2016, we use a conditional logit model to investigate the influence of specialized and diversified agglomeration of local firms as well as industry-specific and industry-diverse agglomeration of Chinese investors on the location choice of CODI, and further explore the heterogeneous influence concerning the entry mode and ownership. Our results show that among a variety of agglomeration economies, the specialized agglomeration of local firms is the premier factor influencing the location choice of CODI, even exceeding the influence of industry-specific agglomeration of CODI in the same industry. Industry-diverse agglomeration of CODI plays a weak role, while diversified agglomeration of local firms has no effect. Moreover, the location choice of acquisition is more sensitive to the specialized agglomeration of local firms than that of greenfield investment, and the influence of the industry-diverse agglomeration of CODI has no effect on the location choice of acquisition. In terms of the ownership, the location choice of state-owned enterprises (SOEs) is more sensitive to the specialized agglomeration of local firms and industry-specific agglomeration of CODI than that of private investment, and the industry-diverse agglomeration of CODI has no significant impact on the location choice of SOEs' offshoring subsidiaries.

Spatio-temporal evolution and mechanism of regional innovation efficiency: Evidence from Yangtze River Delta Urban Agglomeration of China.

Regional innovation is an important research topic in economic geography, the spatio-temporal evolution and mechanism of regional innovation efficiency have recently become a hot for economic geographers. From the perspective of input and output efficiency, this paper constructs evaluation indicator of regional innovation, with the help of Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) models, and Malmquist indicator method of Data Envelopment Analysis (DEA), to analyze regional innovation performance, evolution trend, spatial differentiation, and evolution mechanism of Yangtze River Delta Urban Agglomeration (YRDUA) of China. The results show that: (i) Innovation efficiency of YRDUA is generally low, most of which is less than 80 percent of optimal efficiency; however, it kept rising from 2000 to 2015. (ii) Spatial inequality of regional innovation in YRDUA is significant, with a spatial pattern in the shape of "Z", composed by Hefei, Nanjing, Shanghai, Hangzhou and Ningbo, innovation efficiency of Shanghai is higher than Zhejiang, Anhui and Jiangsu. (iii) Technology progress is the most important influencing factor, all kinds of changing indicator show a trend of rise, and the total factor productivity is changing significantly. This research can provide theoretical reference for the YRDUA to achieve high-quality integration.

The effects of external knowledge source heterogeneity on enterprise process and product innovation performance.

As a global manufacturing centre, China is transitioning from a 'Made in China' to 'Create in China' perspective. An ever-increasing number of companies are developing new competitive advantages and improving their innovation levels by acquiring external knowledge. Yet, studies rarely discuss the influence of various sources of knowledge on process and product innovation performance in China's manufacturing enterprises. Based on the Pavitt industry classification, we use a bivariate Probit model to investigate the influence of external knowledge sources on innovation performance, and test it by using Enterprise Survey data for China, published by the World Bank in 2013. Our empirical analysis indicates that external sources of knowledge, with the exception of suppliers, have a significantly positive influence on process and product innovation performance. Specifically, in the process of technological innovation, peers have a positive effect on enterprise process improvement, especially in the science-based sector. In product innovation, close technical cooperation with users accelerates the commercial manifestation of products, especially in the specialized supplier sector.