Foreign Direct Investment Spillovers and the Geography of Innovation in Chinese Regions: The Role of Regional Industrial Specialization and Diversity

Abstract:Social networking has become a crucial factor affecting regional economic activities. Employing the panel data of the Yangtze River Delta and the Pearl River Delta in China, we examine the influence of environmental regulation on industrial structure and the role that social networks play in the spillover effect. Using the social media data from the Weibo API and the geo-information of enterprises, we construct the Weibo network and the enterprise network, then we analyze the network structures by employing a social network analysis method. The empirical results find the evidence of the spillover effects of environmental regulation through the above two networks by using network linkages as weight matrices in spatial econometric regressions.

Section: The Results Of the Benchmark Modelsupporting

confidence: 54%

Environmental Regulation and Industrial Structure Change in China: Integrating Spatial and Social Network Analysis

Chong

Cheng-lin

2017

“…Among those channels, some knowledge is transferred intentionally through formal mechanisms from the knowledge owner to the recipient (e.g., technology transfer from foreign and domestic technology market), but a large proportion of knowledge spillovers take place as unintentional knowledge leakage [31]. These sourcing channels can contribute to innovation of domestic enterprises in several ways such as learning through labor mobility whereby employees of foreign firms migrate to domestic enterprises, leakage of intellectual property, and imitation (e.g., reverse engineering) of foreign firms' products and technologies by domestic enterprises, or vertical linkages whereby foreign firms bring local suppliers in their supply value chains [32]. In brief, those types of channels and interaction with foreign firms may contribute to innovation and knowledge creation of domestic enterprises.…”

Section: Theory and Hypothesesmentioning

confidence: 99%

“…The reason of collecting data over the period 2001-2009 is that the technological learning process of China could be grouped into four stages: 1949~1960, 1960~1978, 1979~1991, 1992~2000, and 2001 onward [26]. Since entering the WTO in 2001, the Chinese government began to establish a series of policies to foster domestic enterprises to compete in both domestic and global markets and encourage them to acquire the technology developed by foreign companies [32]. In November of 2008, China prompted a four trillion yuan ($585 billion USD) stimulus plan to offset the decline in market demand abroad caused by financial crisis.…”

Section: The Moderating Role Of Technology Development Speedmentioning

confidence: 99%

How Knowledge Acquisition Diversity Affects Innovation Performance during the Technological Catch-Up in Emerging Economies: A Moderated Inverse U-Shape Relationship

Guo

Liu

et al. 2020

Many domestic enterprises in emerging economies are concerned with the question of how to better utilize the portfolio of technology sourcing channels to achieve rapid economic growth by technological innovation. This paper looks at this issue by exploring the impacts of knowledge acquisition diversity (KAD) on innovation performance of domestic enterprises in China and the technological contexts (in terms of technology gap and technology development speed) under which KAD is most likely to contribute. Using panel data of the manufacturing industry in China over the 2001–2009 period, the results show that KAD has an inverse U-shaped relationship with innovation performance in terms of both product-related innovation performance (NPS) and knowledge-related innovation performance (PAT). Specifically, it reveals that the capability to generate technological innovation over time is dependent on how domestic enterprises manage their portfolio of knowledge sourcing channels to learn from foreign enterprises. Moreover, it is shown that the technology gap significantly moderates the inverted U-shaped relationship between KAD and both NPS and PAT. Technology development speed has a moderating effect on the inverted U-shaped relationship between KAD and innovation only in terms of NPS. The results of this study can help us to understand the relationships among technological contexts, KAD and innovation performance of domestic enterprises in emerging countries.

“…Foreign direct investment (FDI) will bring market competition pressure and a spillover effect of technology innovation, which will invigorate the innovative vitality of local enterprises [26,27]. However, FDI also will take some domestic market share, when the crowding out effect predominates, and the development and technology innovation of local enterprise will be restrained [28,29].…”

Section: Literature Review and Hypothesesmentioning

confidence: 99%

The Influencing Factors, Regional Difference and Temporal Variation of Industrial Technology Innovation: Evidence with the FOA-GRNN Model

Zhang

Niu

et al. 2018

Technology innovation is a motivating force for sustainable development. The recognition and measurement of influencing factors are a basic prerequisite of technology innovation research. In response to the gaps and shortages of existing theories and methods, this paper builds the impact indicators of technology innovation, the proposed FOA-GRNN model, and analyzes the influencing factors, regional differences and temporal variations of technology innovation based on industrial above-scale enterprises of 31 provinces in China from 2008 to 2015. The empirical results show that innovation investment is a determinant of technology innovation in China, and is more and more significant; meanwhile a wide gap of innovation resource between Eastern China and Western China exists. In general, the enterprise scale has a negative effect: with enlargement of enterprise in China, the innovation efficiency of enterprise will decline, while the effect has regional disparity, with positive influence in Central and Western China, and negative influence in Eastern China. Government support has negative effects on technology innovation: indirect equity investment contributes more to technology innovation than direct fund support. Innovation environment has positive and weak effects on technology innovation, but it is the biggest obstacle in Western China, and the innovation environment in China has improved continuously. This paper provides new evidence that can shine some light on determining the factors affecting technology innovation, and also presents a novel approach, which comprises characteristics of nonlinear function approximation, high accuracy and a small sample.