Abstract:In recent years, China’s high-tech industry has made remarkable technological progress, but it has also brought serious environmental pollution, which has aroused great concern about its environmental efficiency. Although foreign technology transfer is considered as important ways for technological progress of the high-tech industry, the existing research on what role foreign technology transfer plays in improving the environmental efficiency of the high-tech industry is still lacking. Based on China’s interpr… Show more
“…However, there is also a lack of in-depth research on whether IURC can promote the EE of China's HTM. Second, the existing literature usually uses a two-stage method (such as DEA-Tobit) to study China's industrial EE (Wang et al, 2017;Peng et al, 2022). This method does not separate random factors when analyzing the factors influencing EE, which may lead to errors in the estimates.…”
Section: The Impact Of Iurc On Eementioning
confidence: 99%
“…Production inputs include labor and capital. Labor was reckoned by employment in HTM (Peng et al, 2018). Capital was calculated using the perpetual inventory method (PIM) (Chen et al, 2018).…”
Section: Input-output Indexmentioning
confidence: 99%
“…Capital was calculated using the perpetual inventory method (PIM) (Chen et al, 2018). Take the total output value and the output value of new products as desirable output indicators (Peng et al, 2022). Due to the availability of HTM environmental pollution data, sulfur dioxide emissions and industrial wastewater emissions were selected as undesirable output indicators in this study (Chen et al, 2021).…”
Section: Input-output Indexmentioning
confidence: 99%
“…Some literatures have further empirically tested the role of these factors in China's HTM (Peng et al, 2022). Related studies show that in addition to IURC and RD, marketization level (MAR), enterprise size (ES), human capital (HC), government support (GS), FDI, and regional factors may also be important factors affecting the EE of HTM.…”
Section: Control Variablesmentioning
confidence: 99%
“…However, due to the neglect of environmental efficiency (EE), China's HTM does not present the characteristics of high added value and low pollution, and environmental pollution incidents are frequently reported in the press (Wu Q. et al, 2022). Furthermore, in the increasingly ecologically fragile eastern region, environmental regulation has caused many HTM enterprises to transfer their highly polluting processing and manufacturing links to the central and western regions, intensifying people's concern that these regions will become "pollution refuges" (Peng et al, 2018). Therefore, how to improve EE has become an important practical problem for the sustainable development of Chinese HTM.…”
As one of the important strategic measures to increase the international competitiveness of high-tech manufacturing (HTM), industry-university-research cooperation (IURC) has received increasing attention in China. However, there is little literature to explore the links between IURC and the environmental efficiency (EE) of HTM. To incorporate a variety of environmental pollution indicators into the efficiency analysis framework and reduce the adverse effects of random errors on the estimation results, this article combined the projection pursuit model with the stochastic frontier analysis (SFA) method and proposed a translog stochastic frontier model considering undesirable outputs to analyze the multiple impacts of IURC on the EE of HTM. The results show that IURC has both a significant negative direct effect and a significant positive indirect effect on HTM’s EE. Although IURC cannot directly promote EE, it has a positive impact on EE of HTM through its complementary effect with research and development (R&D) investment. The results also confirm that the average EE of the whole country is only 0.346, while that of the eastern area is 0.595, and that of the central and western areas are 0.199 and 0.171, respectively. Therefore, it is particularly urgent to improve the EE of China’s HTM industry through a variety of measures, such as promoting IURC and increasing R&D investment in environmental technology. This study not only provides an improved SFA method for measuring EE, but also deepens research on the mechanism of the impact of IURC on HTM’s EE.
“…However, there is also a lack of in-depth research on whether IURC can promote the EE of China's HTM. Second, the existing literature usually uses a two-stage method (such as DEA-Tobit) to study China's industrial EE (Wang et al, 2017;Peng et al, 2022). This method does not separate random factors when analyzing the factors influencing EE, which may lead to errors in the estimates.…”
Section: The Impact Of Iurc On Eementioning
confidence: 99%
“…Production inputs include labor and capital. Labor was reckoned by employment in HTM (Peng et al, 2018). Capital was calculated using the perpetual inventory method (PIM) (Chen et al, 2018).…”
Section: Input-output Indexmentioning
confidence: 99%
“…Capital was calculated using the perpetual inventory method (PIM) (Chen et al, 2018). Take the total output value and the output value of new products as desirable output indicators (Peng et al, 2022). Due to the availability of HTM environmental pollution data, sulfur dioxide emissions and industrial wastewater emissions were selected as undesirable output indicators in this study (Chen et al, 2021).…”
Section: Input-output Indexmentioning
confidence: 99%
“…Some literatures have further empirically tested the role of these factors in China's HTM (Peng et al, 2022). Related studies show that in addition to IURC and RD, marketization level (MAR), enterprise size (ES), human capital (HC), government support (GS), FDI, and regional factors may also be important factors affecting the EE of HTM.…”
Section: Control Variablesmentioning
confidence: 99%
“…However, due to the neglect of environmental efficiency (EE), China's HTM does not present the characteristics of high added value and low pollution, and environmental pollution incidents are frequently reported in the press (Wu Q. et al, 2022). Furthermore, in the increasingly ecologically fragile eastern region, environmental regulation has caused many HTM enterprises to transfer their highly polluting processing and manufacturing links to the central and western regions, intensifying people's concern that these regions will become "pollution refuges" (Peng et al, 2018). Therefore, how to improve EE has become an important practical problem for the sustainable development of Chinese HTM.…”
As one of the important strategic measures to increase the international competitiveness of high-tech manufacturing (HTM), industry-university-research cooperation (IURC) has received increasing attention in China. However, there is little literature to explore the links between IURC and the environmental efficiency (EE) of HTM. To incorporate a variety of environmental pollution indicators into the efficiency analysis framework and reduce the adverse effects of random errors on the estimation results, this article combined the projection pursuit model with the stochastic frontier analysis (SFA) method and proposed a translog stochastic frontier model considering undesirable outputs to analyze the multiple impacts of IURC on the EE of HTM. The results show that IURC has both a significant negative direct effect and a significant positive indirect effect on HTM’s EE. Although IURC cannot directly promote EE, it has a positive impact on EE of HTM through its complementary effect with research and development (R&D) investment. The results also confirm that the average EE of the whole country is only 0.346, while that of the eastern area is 0.595, and that of the central and western areas are 0.199 and 0.171, respectively. Therefore, it is particularly urgent to improve the EE of China’s HTM industry through a variety of measures, such as promoting IURC and increasing R&D investment in environmental technology. This study not only provides an improved SFA method for measuring EE, but also deepens research on the mechanism of the impact of IURC on HTM’s EE.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.