International technology spillovers and innovation quality: Evidence from China

Wei, Feng; Li, Jiajia

doi:10.1016/j.eap.2021.09.003

Cited by 47 publications

(28 citation statements)

References 41 publications

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“…This index may engender the overestimation or underestimation of policy effects and inefficient utilization of resources. As a supplementary measure, innovation quality reflects the value difference between innovations (Feng & Li, 2021; Hu et al, 2021). Hence, innovation policy effectiveness should be evaluated from a more comprehensive perspective.…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

Quantity or quality? Policy effects on innovations in the wind power industry in China

Jiang

Shi

2023

Manage Decis Econ

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This study evaluates the effects of policy on the quantity and quality of innovations based on microdata collected from Chinese enterprises from 2006 to 2020 and then identifies the moderating effect of technological opportunity. The results indicate that while policy significantly increases the quantity of innovation, it inhibits its quality, and when technological opportunities are added to this mix, it does not significantly moderate the impact of policy on innovation quantity but does weaken its negative effect on innovation quality.

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Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

Quantity or quality? Policy effects on innovations in the wind power industry in China

Jiang

Shi

2023

Manage Decis Econ

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“…Therefore, to prove China's innovation capability, it is necessary to conduct research from the perspective of China's innovation quality performance (Tseng and Wu, 2007;Liu and Buck, 2007;Chin et al, 2021). For a transitional economy, such as China, improving the quality of innovation is key to implementing an innovation-driven development strategy (Feng and Li, 2021). Improving national innovation quality starts with improving enterprise innovation quality.…”

Section: Note(s)mentioning

confidence: 99%

The impact of FDI technology spillover on the innovation quality of Chinese enterprises: a microperspective based on geographic proximity

Huang

Cao

2022

EJIM

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PurposePrevious studies have reached inconsistent conclusions on foreign direct investment (FDI) technology spillovers and corporate innovation. The main purpose of this paper is to explore the technological spillover effects of FDI from the microperspective of firm linkages induced by geographic distance. Further analysis is conducted on the impact and mechanism of this spillover on the innovation quality of Chinese enterprises. The conclusions drawn from this paper can guide Chinese enterprises' foreign capital utilization and innovation strategy choices.Design/methodology/approachUsing the data of China's A-share listed companies from 2009 to 2019, this paper explores the role of FDI technology spillover in enterprise innovation quality through a two-way fixed-effect model. The robustness of the results is proven by substituting variables, adding industry fixed effects and excluding high-profit groups, and further using the two-stage least squares (2SLS) method to alleviate the empirical endogeneity problem.FindingsThese findings indicate that FDI technology spillover based on geographic proximity has a positive impact on the innovation quality of Chinese enterprises. However, there are different impacts for different types of enterprises. FDI technology spillover has a positive impact on the innovation quality of non-state-owned enterprises (non-SOEs) and small- and medium-sized enterprises (SMEs), while it has no effect on state-owned enterprises (SOEs) and large enterprises. The authors also find that the degree of financing constraints and R&D investment are important transmission mechanisms between FDI technology spillover and enterprise innovation quality.Research limitations/implicationsThis study ignores industry characteristics when considering foreign enterprises around Chinese enterprises. In fact, technology spillover effects differ across industries. When the authors matched microdata to regions, only the provincial level was considered. Therefore, there is still room for further research. In future research, the authors should consider industry characteristics and group foreign enterprises and Chinese enterprises in the same industry and in different industries to explore industry differences in technology spillover. In addition, when matching corporate data to regions, the authors can match to the city level and draw city-level conclusions.Practical implicationsThis study is different from previous studies that focus on the quantity of enterprise innovation or innovation output. The authors focus on the role of technological spillovers in the quality of Chinese enterprise innovation, enriching research in the field of enterprise innovation quality. In addition, the current FDI technology spillover indicators are technically difficult to measure at the micro level. The authors draw inspiration from the theory of the geographical structure of financial supply and combine the creation methods of macro and micro indicators in existing articles in other fields. The authors ingeniously construct a new FDI technical spillover indicator. This indicator combines the commonly used regional FDI technology spillover with the geographic proximity of enterprises at the microlevel by constructing an interaction term between the two. This indicator not only alleviates the endogeneity problem to a certain extent but also has implications for future research in the field of FDI technology spillovers at the micro level.Social implications(1) FDI technology spillovers are an effective way to improve the innovation quality of local enterprises, especially for non-SOEs and SMEs. Therefore, The authors suggest that in the context of dual circulation, the Chinese government should continue to open wider to the outside world and encourage foreign enterprises to invest in China. (2) In future development, managers of SOEs and large enterprises should create an innovation incentive mechanism. Moreover, they should change their vertical management structure and make full use of their policy advantages and budget advantages to increase innovation activities. In the process of acquiring technology spillovers, enterprises need to solve their own financing constraints.Originality/valueFirst, this study solves a technical problem. It is technically difficult to measure the current FDI technical spillover indicators at the micro level. This study innovatively constructs a new FDI technology spillover indicator that combines regional FDI technology spillovers with the microperspective of the geographical proximity of enterprises. This approach not only alleviates certain endogeneity problems in the empirical evidence but also enriches relevant research in the field of technology spillover. In addition, this study focuses on the impact and mechanism of this spillover, which addresses the current research gap among previous studies that mainly focus on innovation quantity and ignore innovation quality.

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“…In these limited studies, scholars focused on the linear impact of environmental regulation on GETI, ignoring the possible nonlinear impact. Meanwhile, innovation activities are often accompanied by knowledge spillover effect, but it also has not received sufficient attention [49,50]. Therefore, this paper attempts to fill the gap by incorporating environmental regulation and GETI into the same analytical framework and constructing a dynamic spatial econometric model to reveal the spatialtemporal relationship between them.…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of Environmental Regulation on Green Energy Technology Innovation—Evidence from China

2022

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Green energy technology innovation (GETI) is a crucial path to achieve sustainable development. However, few studies have examined the determinants of GETI, especially from the perspective of environmental regulation. To fill this gap, this study investigates the impact of environmental regulation on GETI using the panel data of 30 provinces in Mainland China from 2001 to 2018. We first measure GETI by the latest IPC codes and patent data, and then adopt a dynamic spatial Durbin model (DSDM) to examine the relationship between environmental regulation and GETI. The main conclusions are summarized as follows: (1) There is a significant inverted U-shaped relationship between environmental regulation and GETI; (2) heterogeneity analysis shows that the inverted U-shaped correlation not only exists between environmental regulations and different types of GETI, but also exists between environmental regulations and GETI in different regions. Moreover, the results also show that the spatial spillover effect and path-dependent effect exist in all cases. The findings can provide reference for policymakers to formulate more precise environmental policies. That is, environmental policies in a province should be formulated based on its position on the inverted U-shaped curve. More specifically, when it is on the left side of the inflection point, it is reasonable to strengthen environmental policies, and when it is on the right side of the inflection point, appropriate relaxation of environmental policies should be considered.

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International technology spillovers and innovation quality: Evidence from China

Cited by 47 publications

References 41 publications

Quantity or quality? Policy effects on innovations in the wind power industry in China

Quantity or quality? Policy effects on innovations in the wind power industry in China

The impact of FDI technology spillover on the innovation quality of Chinese enterprises: a microperspective based on geographic proximity

The Impact of Environmental Regulation on Green Energy Technology Innovation—Evidence from China

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