Technological Innovation Efficiency in China: Comparison
Please note this is a comparison between Version 1 by Oleksii Lyulyov and Version 2 by Vivi Li.

Innovation is the engine and accelerator that drives high-quality economic and enterprise development. In recent years, the output of scientific and technological innovation in China has been high, but the phenomenon of low efficiency and low quality of innovation occurs frequently. UInder the high-intensity systemic investment in this study, first, technological innovation, China’s overall innovation capability continues to rise.According to the National Bureau of Stat efficiency (TIE) was measured. Then, a dynamic evaluation and analysis of spatial-temporal characteristics of China, China ranks first in research and experimental development (R&D) activities in the world’s major economies. From the perspective of innovation output, China is at the forefront of the world regardingefficiency were performed. Lastly, the driving factors of innovation efficiency were explored. TIE was calculated dynamically in 30 provinces of China from 2011 to 2019 based on the improved super-efficiency SBM-DEA model. Then, the kernel density estimation method was adopted to analyse the scale of patent authorisation and the number of international papers published. However, it is puzzlingpatial-temporal differentiation characteristics and dynamic evolution process of provincial efficiency. The findings confirm that China’s national innovation index has always been outside the top 10 in the world (in 2021, it ranked 12th). With the increasingly fierce scientific and tefrom 2011 to 2019, the top five provinces for TIE in China were Beijing (1.0), Shanghai (0.96), Hainan (0.96), Jilin (0.94) and Tianjin (0.91). The provinces with lowest average efficiency were Qinghai (0.77), Ningxia (0.73) and Inner Mongolia (0.73). The significant differences in the level of technological competition between China and the United States of America (USA), the negative list of some core technologies from the USA has highlighted the problem of “sticking neck” in China’s key technologies. It reflects the fact that althoughinnovation in different regions were caused by the long-term and in-depth implementation of the government’s strategy of revitalising science and driving innovation in parts of areas. The findings of kernel function confirm that the TIE in most parts of China has a large amount of innovations, many are low-quality innovations. There are core technologies still controlled by others. The surging output of innovation in China has not been accompanied by the improvement owas gradually polarised. Furthermore, the results show that for every 1 unit of government R&D funding support, the average marginal utility of the expected TIE will reach 0.192, which is more significant in the central and western regions. On this basis, combined with environmental factors of innovation quality, which also shows that China’s technologicalmarket, infrastructure, financing and enterprise innovation is facing the dilemma of innovation inefficiency caused by the input–output mismatch. Technological innovationpotential, the article also extracts the driving factors that affect the differences in provincial efficiency (TIE) is a key indicator to measure the output level of . The findings provide a reference for guiding provinces to carry out innovation input factors per unit time. Compared with other developed countries, China’s innactivities independently and improve innovation quality and efficiency is still far away in terms of TIE.

  • technological innovation efficiency
  • SBM-Tobit model
  • kernel density estimation

1. Introduction

Under the multiple and complex backgrounds of global economics, environmental protection and the difficulties of industrial transformation, the sixth plenary session of the 19th Central Committee of the Chinese Communist Party once again emphasised the core position of innovation in the overall situation of China’s modernisation drive. To make innovation become the first driving force to “achieve high-quality development”, China should adhere to the innovation-driven development strategy and strengthen the national strategic, scientific and technological strength [1]. As a key element in accelerating the transformation of kinetic energy between the new and the old in the new era, promoting regional innovation is the essential intention of the five major development concepts, and it has great significance to the realisation of coordinated development and common prosperity [2][3][4][5][2,3,4,5].
Under the high-intensity systemic investment in innovation, China’s overall innovation capability continues to rise. According to the National Bureau of Statistics of China [6], China ranks first in research and experimental development (R&D) activities in the world’s major economies. Furthermore, China is the leader in both the proportion of government funds and the number of people engaged in R&D. As the main forces engaged in R&D activities, enterprises were invested directly with 76.4% of China’s R&D funds to carry out innovation activities, which is only exceeded by South Korea (80.3%) and Japan (79.4%) in the world. In addition, the intensity of R&D investment in China increased from 0.65% to 2.24% of growth domestic product (GDP) from 1998 to 2019, even higher than the average of 2.12% in the European Union (EU). In the same period, the number of patent applications granted increased from 68,000 to 2.457 million, rapidly growing nearly 35-fold. From the perspective of innovation output, China is at the forefront of the world regarding the scale of patent authorisation and the number of international papers published. However, it is puzzling that China’s national innovation index has always been outside the top 10 in the world (in 2021, it ranked 12th). With the increasingly fierce scientific and technological competition between China and the United States of America (USA), the negative list of some core technologies from the USA has highlighted the problem of “sticking neck” in China’s key technologies. It reflects the fact that although China has a large amount of innovations, many are low-quality innovations. There are core technologies still controlled by others. The surging output of innovation in China has not been accompanied by the improvement of innovation quality, which also shows that China’s technological innovation is facing the dilemma of innovation inefficiency caused by the input–output mismatch. Technological innovation efficiency (TIE) is a key indicator to measure the output level of innovation input factors per unit time. Compared with other developed countries, China’s innovation efficiency is still far away in terms of TIE.

2. TLitechnological Innovation Efficiencyrature Review

In general, efficiency is the ratio between outputs and the costs required to produce them [7][10]. The study [8][11] applied a DEA model to analyse the technological innovation efficiency of China’s high-tech industries. The scientists working on [8][11] confirmed that required resourses (capital, labour, knowledge, etc.) for innovations are less than the generated output when comparing similar technologies in the sector. Furthermore, in the papers [9][10][12,13], the innovative activity of companies was analysed as a goal-directed process. Such an approach allows simultaneous estimating of initial, intermediate and output data during the entire period of industrial production. The paper [11][14] defined the TIE as the capability to maximize the results from innovations compared to innovation cost. The study [12][15] confirmed that industry technological innovation efficiency was the core driver of sustainable development of the mining industry in China. The authors developed a DEA model to confirm that technological innovation efficiency impacted sustainable development of the mining industry. Thus, within the investigation, the TIE was analysed as the proportion changes between input and output of the production process. In recent years, a large number of low-efficiency or even ineffective innovation behaviours (such as dormant patents and innovation bubbles) have emerged under the guidance of existing innovation policies [13][16]. Promoting technological innovation being more efficient and high-quality has become the fundamental way to solve the lack of stamina of current economic and social development [14][17] as well as curb the unchecked spread of innovation bubbles. However, before improving TIE, increasing the level of innovation efficiency has become the first concern that should be addressed. From the perspective of method, the non-parametric DEA method is generally used to separate the technical efficiency from the production efficiency. The Solow residual method is also used to analyse its regression residual to characterise technological progress [15][18]. The super-efficiency SBM-DEA model can better consider the unexpected output. It allows comparison of an effective decision-making unit (DMU) whose efficiency is not less than 1, which solves the problem that the previous DEA model may cause deviation in the radial selection and angle selection, and has become a reliable method to measure efficiency. From the selection of indicators, the existing research mainly uses a single index to measure enterprises’ innovation capability or performance, such as R&D investment, the number of patent applications or patents authorised and the number of science and technology employees [16][17][19,20]. Patents, especially invention patents, have become common indicators when measuring micro-subject innovation output. Generally, the number of invention patents is used to measure the number of innovations, and the citation of invention patents is used to measure the quality of innovation [16][19]. Although patent data can more accurately measure the output of innovation activities rather than input, only using patent citation to measure patent quality is not accurate enough. Worse, some enterprises often misquote or over-quote patents to better cater to the examination of patent examination institutions. Therefore, there are still many drawbacks to only taking the number of patent citations as patent quality and then regarding it as the innovation output. After completing the efficiency measurement, some scholars use the two-stage Tobit model to explore the factors that affect the efficiency of TIE and finally give targeted countermeasures and suggestions. For example, the study [18][21] used the non-radial and non-angle DEA model, including unexpected output, to measure the ecological efficiency of urban agglomerations in the Yangtze River Economic Belt from 2005 to 2015, and it empirically analysed the impact of green-technology innovation on ecological efficiency through the Tobit model. The paper [19][22] analysed the effect of material and energy consumption reduction on innovation efficiency, considering both innovation inputs and outputs, and then utilised data of 388 manufacturing enterprises in Korea and performed DEA and Tobit regression analysis. The study [20][23] used the two-stage network DEA model to measure the green innovation efficiency of China’s local high-tech manufacturing industry and established a Tobit regression model to analyse the role of different technology transfer modes in improving green innovation efficiency. The study [21][24] used the Bootstrap-modified DEA–Tobit model to evaluate the green-technology innovation efficiency of 21 biomass power generation enterprises in 2018 and analysed the influencing factors.

3. Conclusions

3.1. For Government

China should increase the government support for technological innovation and endowment of regional innovation resources. This could be realised by providing financial subsidies and taxation, which was also proposed by [22][51]. The government should become the main body of the top-level design in the innovation system. As the leaders in innovation, high-tech enterprises play an essential role. The government should develop policy for high-tech enterprises’ development. The number of high-tech enterprises will help invigorate regional resources and improve the allocation efficiency of input resources, as well as the efficiency of regional technological innovation. Economic globalisation is an irreversible trend of this era, and General Secretary Xi Jinping has stressed that China should persist in opening its doors for construction. The higher the degree of economic opening to the outside world, the higher TIE might be. Some studies have shown that opening wider to the outside world is more conducive to the improvement of China’s industrial environmental performance rather than deterioration [20][23], which also means that further opening to the outside world is a reliable way to promote sustainable economic and social development in China’s backward areas.

3.2. For Practice

Some regions should build a sharing cooperation mechanism and scientific and technological innovation platform. They could enhance the regional original innovation capability and promote the diffusion and transformation of innovation achievements. It is necessary to improve the construction of information infrastructure and provide a good hardware environment for cultivating innovation. As the material basis and information guarantee of technological innovation, information infrastructure has become a significant force in promoting regional innovation. The innovation spillover effect led by the Internet should be taken seriously. At present, society has entered the era of the digital economy. As the primary carrier of knowledge and information, the Internet and other infrastructure is of great significance to speed up the construction of modern information networks and further promote technological innovation.

3.3. For Society

Increasing of TIE allowed achieving direct and indirect effects. Thus, the penetrating of effective innovations among society lead to improving quality of life, accessibility to the knowledge, providing well-being, etc. Furthermore, technological innovation reduces destructive impacts on the environment [23][47], which subsequently reduces morbidity and mortality. Notably, the ability of society to implement innovations determines the level of social, cultural and economic development of a country. Despite the actual findings pertaining to the drivers of TIE, thereis study are had several limitations. In further investigation, it would be necessary to consider the cointegration analysis between all variables that impact TIE. Furthermore, the number of drivers should be extended (social, digital, ecological, etc). This allows for identifying the relevant and significant drivers for boosting countries’ innovative development.
Video Production Service