The symbiosis of scientific and technological innovation efficiency and economic efficiency in China — an analysis based on data envelopment analysis and logistic model

Wang, Song; Zhang, Jianqing; Fei, Fan; Lu, Fei; Yang, Lisheng

doi:10.1080/09537325.2018.1485889

Cited by 61 publications

(41 citation statements)

References 14 publications

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“…And then, it is demonstrated that China's environmental policies are significantly conducive to technological innovation in industry from 2006 to 2015 [47]. Industrial innovation appears to be a shift to green technology innovation [48], and the technology innovation efficiency in China's manufacturing industry shows an upward trend during 2003-2016 [49]. In addition, the innovation efficiency in high-end manufacturing industry has come up to the middle and high levels, and the competitiveness has increased substantially over the period 2012-2017 [50].…”

Section: Benchmark Regression Resultsmentioning

confidence: 99%

Environmental Regulation, Technological Innovation, and Export Competitiveness: An Empirical Study Based on China’s Manufacturing Industry

Liu

Xie

2020

IJERPH

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A current and universal challenge, particularly in developing nations, is the establishment of effective environmental regulation policies that protect the ecological environment without adversely affecting the international competitiveness of the domestic manufacturing industry. To deal with this dilemma, this study investigates the export competitiveness of China’s manufacturing industry from the viewpoint of export value added. The Porter hypothesis is applied for an empirical investigation of the effect of environmental regulation on export competitiveness and to determine the presence of intra-industry heterogeneity. Furthermore, this study seeks to understand the mechanisms through which environmental regulation affects export competitiveness by exploring the two main approaches to technological innovation. The findings reveal that environmental regulation has a promotion effect of approximately 2% on the export competitiveness of China’s manufacturing industry; however, this effect is non-linear and displays a “U-shaped” tendency, indicating that certain prerequisites must be fulfilled to validate the Porter hypothesis. In addition, the effect of environmental regulation displays significant intra-industry heterogeneity, which is evident primarily in heavily polluting sub-industries and to a lesser extent in moderately polluting sub-industries but insignificant in lightly polluting sub-industries. Environmental regulation also differs significantly in the mechanisms through which it affects different approaches to technological innovation. Independent research and development is affected by environmental regulation through the compliance cost effect, which limits export competitiveness, while technology introduction is affected by the innovation offset effect, which favors export competitiveness. These findings offer political implications for the sustainable development of the ecological environment and foreign trade.

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Section: Benchmark Regression Resultsmentioning

confidence: 99%

Environmental Regulation, Technological Innovation, and Export Competitiveness: An Empirical Study Based on China’s Manufacturing Industry

Liu

Xie

2020

IJERPH

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“…The core explanatory variable of this study is innovation efficiency ( E ), and its essence is an input-output ratio. We took the number of scientific research personnel and financial, science, and technology expenditures as innovation inputs [ 30 , 31 ]. The number of large patent applications and the number of scientific papers searched were taken as innovation outputs [ 32 , 33 ].…”

Section: Measurement Model and Index Descriptionmentioning

confidence: 99%

Is Improvement of Innovation Efficiency Conducive to Haze Governance? Empirical Evidence from 283 Chinese Cities

Fei

Cao

2020

IJERPH

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In recent years, haze pollution has had a wide impact in China. This research systematically studies the influence mechanism of haze pollution from a new perspective of urban innovation efficiency. We use a generalised space two-stage least squares method to analyse the correlation between urban innovation efficiency and haze pollution. The periodic and regional influences of urban innovation efficiency on haze pollution is explored using a threshold regression model. Through the mediating effect model, we accurately identify the transmission mechanism of urban innovation efficiency affecting haze pollution. The results show a significant inverted ‘U’ relationship between improvement of urban innovation efficiency and haze pollution. The regional innovation activities of innovative cities differ greatly from those of non-innovative cities. The effect of innovation efficiency improvement in innovative cities on haze governance is better than that of non-innovative pilot cities. In eastern cities with a higher level of economic development, the improvement of innovation efficiency has a stronger impact on haze governance. Industrial structure and population agglomeration have a mediating effect on the impact of urban innovation efficiency on haze pollution, providing directions for the rational formulation and effective implementation of haze governance policies in China, as well as in other countries.

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“…DEA is an analytical method that studies efficiency problems within operational research, drawing from concepts in management and mathematical economics. Charnes, Cooper, and Rhodes (1978) put forward the first DEA model of C 2 R, which had the following advantages: (a) it can be applied to the efficiency evaluation of multi-input and multi-output; (b) it is not affected by the dimensions of input and output elements; (c) as an objective evaluation method, it is less sensitive to human subjectivity.. Due to these advantages, the DEA model is widely used in economic development (Hu, Zhang, & Chao, 2019), ecological construction (Deilmann, Lehmann, Reißmann, & Hennersdorf, 2016), scientific and technological innovation (Wang, Zhang, Fan, Lu, & Yang, 2019), and other fields. However, the traditional DEA model cannot account for the active decision-making units within the RIS, which may lead to incorrect results.…”

Section: Estimation Of Riementioning

confidence: 99%

Can regional collaborative innovation improve innovation efficiency? An empirical study of Chinese cities

2019

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The relationship between collaborative innovation and innovation efficiency has attracted the attention of researchers in recent years. However, few studies have integrated intra‐regional and inter‐regional collaborative innovations (IRCI) into a unified framework to analyze the overall impact of regional innovation efficiency. To fill this gap, this paper uses an improved Data Envelopment Analysis Model to measure the innovation efficiency of Chinese cities from 2003 to 2016 based on the regional innovation capability. Using the Coupling Coordination Degree Model to measure the degree of intra‐regional collaborative innovation, we constructed a Capability Structure Model to measure the degree of IRCI, then used the Spatial Durbin Model to empirically analyze the influence of intra‐regional and IRCI on regional innovation efficiency. The results show that: (a) both intra‐regional and IRCI promote regional innovation efficiency, but the internal factors are the primary influences on regional innovation efficiency; (b) intra‐regional collaborative innovation not only promotes local regional innovation efficiency but also promotes innovation efficiency in other regions effectively, although its driving effect on the local region is higher than on other regions; (c) there is a time lag in promoting regional innovation efficiency through the cooperation and interaction among innovation in knowledge, technological, industrial, and service, and environment capabilities. The regional innovation capacities can result in good collaborative innovation effects only after a certain period of cooperation.

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The symbiosis of scientific and technological innovation efficiency and economic efficiency in China — an analysis based on data envelopment analysis and logistic model

Cited by 61 publications

References 14 publications

Environmental Regulation, Technological Innovation, and Export Competitiveness: An Empirical Study Based on China’s Manufacturing Industry

Environmental Regulation, Technological Innovation, and Export Competitiveness: An Empirical Study Based on China’s Manufacturing Industry

Is Improvement of Innovation Efficiency Conducive to Haze Governance? Empirical Evidence from 283 Chinese Cities

Can regional collaborative innovation improve innovation efficiency? An empirical study of Chinese cities

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