The Influencing Factors of Financial Support Efficiency of New Generation High-Tech Industry in China: Evidence from Listed Companies

In order to improve the 
financial support efficiency of new generation 
high-tech industry in China, from the perspective of the 
subject (enterprise) in which financial resources were invested, this paper selected 
192 listed companies in 
quantum communication and artificial intelligence concept plates in Chinese 
stock market as samples. Based on the original data of 2015-2019, the 
influencing factors of financial support efficiency of new generation high-tech 
listed companies were then empirically analyzed by 
using DEA-BCC model and Tobit model. The 
results showed that the ownership concentration, executive compensation and 
regional digital inclusive finance level were main factors affecting the 
financial support efficiency of new generation high-tech listed companies, 
followed by the technological innovation capability and regional economic 
development level. However, the influence of growth and comprehensive leverage were 
limited, and the influence of profitability and capital structure were not 
obvious. Accordingly, the main countermeasures to improve the financial support 
efficiency of new generation high-tech industry were proposed, which included giving 
full play to the advantages and potential of digital inclusive finance, 
actively guiding enterprises to innovate management, improve quality and 
efficiency, etc.


Introduction
With the rapid development of high technology in the fields of electronic information, biology and new medicine, aerospace, new materials, high technology services, new energy and energy conservation, resources and environment, advanced manufacturing and automation, the new generation high technology characterized by intelligent technology and quantum technology has emerged. It has become the frontier of a new round of scientific and technological revolution and industrial change, which is being arranged by the world's major scientific and technological powers, and has become a strategic field related to the national security and high-quality development of society and economy. Following Increasing financial support for the new generation high-tech industry has important practical significance for accelerating the cultivation and development of the new generation high-tech industry. With constraint of financial resources, not only form a sound financial support system for the new generation high-tech industry, but also pay attention to the efficiency of financial support. On the one hand, through government guidance and market operation, give full play to the advantages and potential of digital inclusive finance, improve the financing availability of new generation high-tech enterprises, and reduce the financing cost of enterprises. On the other hand, actively guide the new generation high-tech enterprises to innovate management, improve quality and efficiency, comprehensively improve their technological innovation capability and management level, so as to effectively improve the financial support efficiency of new generation high-tech industry. Therefore, to clarify the influencing factors of financial support efficiency of new generation high-tech industry is helpful to improve the financial support efficiency of new generation high-tech industry and increase the financial support for the new generation high-tech industry.

Theoretical Analysis and Research Hypothesis
Profitability refers to the ability of an enterprise to obtain operating profits, which is usually expressed as the amount and level of income obtained by enterprise in a certain period. In general, the stronger the profitability of enterprise is, the higher the efficiency of financial support is. Wang (2016) found that the operating cost profit margin is significantly positively correlated with the financial support efficiency of strategic emerging industry. Li, Zhang & Zhou (2015) found that there is a low positive correlation between the return on equity (ROE) and the capital market financing efficiency of strategic emerging industry.
The empirical results of Jiang (2020) showed that the ROE is positively correlated with the financing efficiency of artificial intelligence industry. Based on the above analysis, we propose the hypothesis: H1: the profitability has a significant positive impact on the financial support efficiency of new generation high-tech listed companies.
Capital structure refers to the composition and proportion of all kinds of long-term capital (such as long-term debt capital and equity capital). Reasonable capital structure can reduce the comprehensive capital-cost rate, obtain financial leverage income, and improve enterprise value, so as to improve the efficiency of financial support. The empirical results of Wu & Yao (2015) and Li & Yang (2017) etc. showed that the asset liability ratio and the shareholder's equity ratio are significantly positively correlated with financial support efficiency of strateg- H2: the capital structure has a significant positive impact on the financial support efficiency of new generation high-tech listed companies.
Executive compensation means that in order to eliminate the conflict of interests between the executives and the shareholders, the shareholders implement compensation incentive plan for the executives to achieve incentive compatibility. Reasonable executive compensation can improve the company performance, so as to improve the efficiency of financial support. The empirical results of Kaplan (1994), Canarella & Gasparyan (2008), Sigler (2011), Li, Sun & Zhang (2008, Liu & Wan (2013) and Shi et al. (2019) etc. showed that the executive compensation level is significantly positively correlated with the company performance. However, Main (1991), Li (2000) and Wei (2000) etc. found that there is no significant correlation between the executive compensation and the company performance. Considering that the new generation high-tech industry is still in the growth stage, we propose the hypothesis: H3: the executive compensation has a significant positive impact on the financial support efficiency of new generation high-tech listed companies.
Growth is a quantitative description of the growth state of an enterprise. It refers to the sustainable development ability of an enterprise and reflects the development status of an enterprise' operation ability in a certain period. High growth is an important feature of the new generation high-tech enterprises, the growth level will have an important impact on the future business performance and development of enterprises, as well as the efficiency of financial support. Jin & Huang (2018) found that the growth rate of main business income is significantly positively correlated with the financing efficiency of new third board enterprises. The empirical results of Jiang (2020) showed that there is a significant positive correlation between the growth rate of operating income and the financing efficiency of artificial intelligence industry. Based on the above analysis, we propose the hypothesis: H4: the growth has a significant positive impact on the financial support efficiency of new generation high-tech listed companies.
Technological innovation is the source of the competitiveness of new generation high-tech enterprises, the accelerator to improve the economic benefits of new generation high-tech enterprises, and the basis for the survival and development of new generation high-tech enterprises. Enterprise's technological innovation capability is the overall function of product and process innovation capability. It is a systematic capability, which is an explicit capability expressed through technological innovation. The stronger the technological innovation M. Zhang, Z. Y. Lv DOI: 10.4236/tel.2021.114050 775 Theoretical Economics Letters capability of enterprise is, the better the enterprise performance is, so that the higher the efficiency of financial support is. The empirical results of Wang & Tu (2012), Tang et al. (2014), Chen, Zou & Liu (2015) and Lu & Zhang (2021) etc.
showed that the technological innovation capability has a significant positive impact on the performance of high-tech enterprises. Based on the above analysis, we propose the hypothesis: H5: the technological innovation capability has a significant positive impact on the financial support efficiency of new generation high-tech listed companies.
Ownership concentration refers to the degree of ownership concentration shown by all shareholders of a company due to different shareholding ratios, which is a quantitative indicator reflecting the distribution of ownership, company stability and company structure. Appropriate ownership concentration can improve the company performance to a certain extent, thereby improving the efficiency of financial support. The empirical results of Huang & Wen (2017) showed that the shareholding ratio of top ten shareholders has a significant positive correlation with the financial support efficiency of energy conservation and environmental protection industry. Jin & Huang (2018) found that the shareholding ratio of the largest shareholder has a significant positive correlation with the financing efficiency of new third board enterprises. However, Wu & Yao (2015) reached the opposite conclusion. Considering that the new generation high-tech industry is still in the growth stage, we propose hypothesis: H6: the ownership concentration has a significant positive impact on the financial support efficiency of new generation high-tech listed companies.
Comprehensive leverage reflects the comprehensive effect of operating leverage and financial leverage. The effect of comprehensive leverage is generally measured by comprehensive leverage coefficient (= change rate of net profit/change rate of main business income). Enterprise risk includes operational risk and financial risk. The higher the comprehensive leverage coefficient is, the higher the total risk is, which has a negative impact on the efficiency of financial support. The empirical results of Zhou (2018) showed that the financial leverage has a significant negative correlation with the enterprise performance. Zeng & Shao (2018) believed that in general, there is a significant positive correlation between the operating leverage and the operating risk. Yu & Ye (2020) found that in the period of economic downturn, the financial leverage and the profitability of enterprises with low profitability present the characteristics of negative sensitivity, while the superposition and resonance of operating leverage and financial leverage form the "mystery of negative sensitivity". Based on the above analysis, we propose the hypothesis: H7: the comprehensive leverage has a significant negative impact on the financial support efficiency of new generation high-tech listed companies.
Digital inclusive finance "generally refers to all actions to promote inclusive finance through the use of digital financial services" (G20 Advanced Principles H8: the regional digital inclusive finance has a significant positive impact on the financial support efficiency of new generation high-tech listed companies. The level of regional economic development represents the status of natural conditions, socio-economic conditions and technical and economic policies in a certain region. The new generation high-tech industry needs to gather in the areas with perfect infrastructure, good industrial supporting conditions, strong ecological carrying capacity and rich scientific and technological resources to build characteristic industrial clusters. The high level of regional economic development and the strong basic support ability of industrial development help to improve the efficiency of financial support. Ma (2013) found that the location of listed companies in strategic emerging industry has a significant positive correlation with the financial support efficiency. The empirical results of Chen et al. (2020) showed that the location of listed companies in strategic emerging industry is positively correlated with the comprehensive efficiency, pure technical efficiency and scale efficiency of financial support. Based on the above analysis, we propose the hypothesis: H9: the level of regional economic development has a significant positive impact on the financial support efficiency of new generation high-tech listed companies.

Empirical Model Setting
In this study, we use DEA method to measure the financial support efficiency of new generation high-tech listed companies. Therefore, the explained variable is a limited dependent variable, whose value is greater than 0 and less than or equal to 1. If the ordinary least squares (OLS) method is used to estimate the coefficients, it may cause inconsistency and bias. Tobit model belongs to dependent variable constrained model, it uses maximum likelihood method to estimate coefficients, which can better avoid the inconsistency and bias of coefficients estimation (Kalwij, 2003). Therefore, this paper uses the Tobit model to analyze the influencing factors of financial support efficiency of new generation high-tech listed companies. The specific form is as follows: where i represents the sample enterprise; t represents the year; it y * is the latent variable. it y is the observed actual explained variable; jit x is the j-th explana- [2020] No. 7), based on the relevant research results, and following the principles of selecting indicators, such as scientific, objective, systematic, functional, dynamic, relative independence, feasibility (or operability), comparability and so on, this paper selected bank loans (the sum of long-term and short-term loans in the enterprise balance sheet), stock financing (the sum of the amount of IPO and the amount of allotment and additional issuance in the financial report), bond financing (the sum of long-term and short-term bonds in the enterprise balance sheet), government subsidies (the amount of government subsidies in the notes to the enterprise's financial statement) and venture capital (the product of the number of equity of venture capital institutions and IPO price) as the input indicators to measure the financial support efficiency of new generation high-tech listed companies (note: due to the low amount of enterprise property insurance, this paper did not consider insurance). In addition, this paper selected the enterprise net profit (the net profit in the enterprise profit statement) and tax amount (the sum of various taxes in the notes to the enterprise financial statement) as the output indicators to measure the financial support efficiency of new generation high-tech listed companies.

Variable Selection
In order to meet the requirements of DEAP Version 2.1 software for input data, before measuring the efficiency of financial support, the original data were standardized. The calculation formula is:  (Banker, Charnes, & Cooper, 1984). Where SE = TE/PTE. Referring to Bi & Li (2019), the DEA evaluation value was divided into four intervals from low to high: (0, 0.5), [0.5, 0.8), [0.8, 1) and 1, so as to obtain the distribution of comprehensive technical efficiency, pure technical efficiency and scale efficiency as shown in Tables 1-3 (specific data backup).

2) Explanatory variable
This paper selected the profitability, capital structure, executive compensation, growth, technological innovation capability, ownership concentration, comprehensive leverage, regional digital inclusive finance level and regional economic development level of new generation high-tech listed companies as Where the profitability was measured by the profit margin of main business (PMMB). The capital structure was measured by the asset liability ratio (ALR). The top three executives' total compensation (TTEC) was used to measure the executive compensation. The growth was measured by the net profit growth rate (NPGR). The technological innovation capability was measured by the intangible assets (IA). The shareholding ratio of top five shareholders (SRTFS) was used to measure the ownership concentration. The comprehensive leverage level was measured by the comprehensive leverage coefficient (CLC). The regional digital inclusive finance index (DIFI) was used to measure the level of regional digital inclusive finance. In addition, the level of regional economic development was measured by the regional per capita GDP (PCGDP).  Table 4.

Hausman Test
Hausman test is an econometric method to select fixed-effects model and random-effects model when using panel data (Hausman, 1978

Regression Results and Analysis of Tobit Model
According to the Hausman test results, using Stata16.1 software, this paper used respectively comprehensive technical efficiency, pure technical efficiency and scale efficiency as explained variable, the coefficients of Equation (1) were estimated by using correspondingly fixed-effects model, random-effects model and fixed-effects model, and the regression results of Tobit model were obtained as shown in Table 5.
The regression coefficient of the top three executives' total compensation to the comprehensive technical efficiency is significantly positive at the level of 1%, where the regression coefficient to the scale efficiency is significantly positive at the level of 1%, but the regression coefficient to the pure technical efficiency is not significant, which indicates that the top three executives' total compensation has a significant positive impact on the financial support efficiency to a certain extent. Therefore, the original hypothesis H3 is accepted.
The regression coefficient of the net profit growth rate to the comprehensive technical efficiency is not significant, where the regression coefficient to the pure technical efficiency is significantly positive at the level of 5%, but the regression coefficient to the scale efficiency is not significant, indicating that the net profit growth rate has only a certain positive impact on the financial support efficiency.
This may be related to the fact that the new generation high-tech listed companies pay more attention to improving their management and technical level at this stage. Therefore, the original hypothesis H4 is rejected.
The regression coefficient of the intangible assets to the comprehensive technical efficiency is significantly positive at the level of 10%, where the regression coefficient to the pure technical efficiency is significantly negative at the level of 5%, but the regression coefficient to the scale efficiency is not significant, indi-DOI: 10.4236/tel.2021.114050 782 Theoretical Economics Letters cating that the intangible assets have a significant positive impact on the financial support efficiency to a certain extent. Therefore, the original hypothesis H5 is accepted.
The regression coefficients of the shareholding ratio of top five shareholders to the comprehensive technical efficiency, pure technical efficiency and scale efficiency are significantly positive at the level of 1%, which indicates that the shareholding ratio of top five shareholders has a significant positive impact on the financial support efficiency. Therefore, the original hypothesis H6 is accepted.
The regression coefficient of the comprehensive leverage coefficient to the comprehensive technical efficiency is not significant, where the regression coefficient to the pure technical efficiency is significantly negative at the level of 5%, but the regression coefficient to the scale efficiency is not significant, indicating that the comprehensive leverage coefficient has only a certain negative impact on the financial support efficiency. This may be related to the fact that the new generation high-tech listed companies pay more attention to control management and technology risks at this stage. Therefore, the original hypothesis H7 is rejected.
The regression coefficient of the regional digital inclusive financial index to the comprehensive technical efficiency is significantly positive at the level of 1%, where the regression coefficient to the scale efficiency is significantly positive at the level of 1%, but the regression coefficient to the pure technical efficiency is not significant, which indicates that the regional digital inclusive financial index has a significant positive impact on the financial support efficiency to a certain extent. Therefore, the original hypothesis H8 is accepted.
The regression coefficient of the regional per capita GDP to the comprehensive technical efficiency is significantly positive at the level of 10%, where the regression coefficients to the pure technical efficiency and scale efficiency are not significant, which indicates that the regional per capita GDP has a significant positive impact on the financial support efficiency to a certain extent. Therefore, the original hypothesis H9 is accepted.
To sum up, the top three executives' total compensation, intangible assets, shareholding ratio of top five shareholders, regional digital inclusive financial index and regional per capita GDP have a significant impact on the resource al-

Robustness Test
In order to test the robustness of the regression results of

Conclusions
According to the regression results and analysis of Tobit model in Section 4.2, we can obtain the following conclusions: 1) The ownership concentration has a significant positive impact on the financial support efficiency of new generation high-tech listed companies, which is consistent with the empirical conclusions of Huang & Wen (2017) and Jin & Huang (2018).
2) The executive compensation has a significant positive impact on the financial support efficiency of new generation high-tech listed companies, but has no significant impact on the pure technical efficiency, which is generally consistent with the empirical conclusions of Kaplan (1994), Canarella & Gasparyan (2008), Sigler (2011), Li, Sun & Zhang (2008, Liu & Wan (2013) and Shi et al. (2019).
3) The level of regional digital inclusive finance has a significant positive impact on the financial support efficiency of new generation high-tech listed companies, but has no significant impact on the pure technical efficiency, which is generally consistent with the empirical conclusions of Yu & Dou (2020), Liao, Hu & Xiang (2020) and Ren (2020).
4) The technological innovation capability has a significant positive impact on the financial support efficiency of new generation high-tech listed companies, but has no significant impact on the scale efficiency, which is generally consistent with the empirical conclusions of Wang & Tu (2012), Tang et al. (2014), Chen, Zou & Liu (2015) and Lu & Zhang (2021).
5) The level of regional economic development has a significant positive impact on the financial support efficiency of new generation high-tech listed companies, but has no significant impact on the pure technical efficiency and scale efficiency, which is consistent with the empirical conclusions of Ma (2013) and Chen et al. (2020). Therefore, using the DEA Malmquist index model to measure the dynamic changes of the financial support efficiency of new generation high-tech enterprises, and investigating their influencing factors, which is worthy of further study in the future. In addition, this paper proposed nine hypotheses, and tested nine factors that affect the financial support efficiency of new generation high-tech listed companies. However, this leads to the research of this paper is too broad.
Therefore, reducing the hypotheses to conduct more in-depth research remains to be completed in the future.
According to the above research conclusions, we can put forward the following policy recommendations: