Study on the Relationship Between R

these sample companies a of ??， and the data come from the GTA database.

2.1 Variable Selection and Characteristics of the Sample Data

This article precluded the method described in the full sample， researched on samples of corporate finance and performance relationship in terms of capital structure， company size， performance indicators， capital intensity， R&D expenditures. Variables are selected as follows. 2.1.1 The Dependent Variable

Financial leverage was taken as the dependent variable with LEV. Its value is represented by the asset-liability ratio， specific formula is expressed as： Asset-liability ratio = Total liabilities ÷ total asset × 100%. 2.1.2 The Independent Variable

Firstly， R&D intensity was taken as a proxy for the innovation variable with INTR&D， specific formula is expressed as： R&D expenditure ÷ sales. The percentage of R&D intensity index reflects the company’s innovative variable. Secondly， corporate performance was taken as independent variables with M： B， specific formula is expressed as： The company’s market value ÷ book value of

total assets. Simons （2000） proposed that there are two typical performance measures to evaluate company

performance： accounting-based and market-based measures. Accounting-based measures can be controlled by managers such as ROE and ROI， these data are more easily manipulated than the market-based tests. Accounting measurement basis maybe underestimate company performance， so there existed a lot of investment in the current period， and expected the accumulation future earnings； while market-based measures of performance usually more objective， and can not be controlled by managers， such as the market value of equity. Therefore， the author uses the ratio of market value and book value to measure corporate performance， including the expected value of future corporate performance. 2.1.3 Control Variables

Firm size is used to measure the size of enterprises with SIZE， calculated by the total assets value of the natural logarithm of the year. The ratio is converted into approximately equivalent natural logarithm， can improve the model fit to maximize. Corporate earnings were calculated by accounting income total assets of PROFIT； Capital intensity was calculated by the total book value of assets ÷ sales revenue of

INTCAPITAL， used to represent enterprise asset utilization efficiency.

Combination of these variables， each variable characteristics of the sample companies were described in Table 1.

Table 1 lists the basic situation of each variable sample company data， and there is a detailed analysis as following empirical results. Based on the above analysis of the literature related to the theory， combined with the above information and data， the author will describe and analysis the basic situation of the study， provide the basis of assumptions and model selection theory for the next part of empirical research. 2.2 Theoretical Assumptions

Financial support has a significant role to promote innovation and development of enterprises. However， existing research shows that the more debt under the circumstances， the less corporate innovation activities； on the other hand， less debt and more equity， the more R&D expenditure. Because there is the risk of bankruptcy for debt， results in cash flow decreased. Bank usually concerned about the usage of funds When lending， namely enterprises how to use and invest funds.

There is always a corresponding burden of the financial costs required to gradually squeeze corporate cash flow because of the higher the proportion of debt in the capital structure. The level of debt ratios will affect their ability to innovate， thus affecting innovation performance. Baysinger and Hoskisson （1989） found that there is a significant negative correlation between R&D expenses and corporate financial leverage. Higher debt levels will force executives to give up high-risk， high-yield investment projects， reduce development costs， reduce the level of innovation capacity and performance of enterprises. Capital structure is the core issue of corporate financing decisions， debt financing costs is lower relative to the cost of equity financing， financial leverage should maximize the earnings per share， and the rational use of financial leverage could increase corporate value. Investment in R&D expenditure will create intangible assets， and the higher risk of intangible assets results in difficult trading in the market， therefore it difficult to support a higher liability. Porter （1996） pointed out that the capital structure can not be seen as irrelevant exogenous variables with respect to strategy， managers must be aware that the appropriate capital structure will promote the effectiveness of corporate

strategy and improve performance. Simerly and Li （2000 ） found that if changes in the capital structure does not match dynamic environment ，there will have a negative impact on the value of company. Leverage and innovation strategy has a negative correlation when considering the impact of the performance for the company. Domestic scholars Jiang and Mao （2011） showed that corporate capital structure and technological innovation performance has a negative correlation ， the companies used innovative strategies tend more relaxed （low debt） financial structure， in order to alleviate the pressure from creditors. Taking these documents， I make the hypothesis as following： Hypothesis 1： R&D intensity and the asset-liability ratio has a negative correlation in Henan listed Companies， that is， companies usually take lower financial leverage when invest more R&D expenditure；

Hypothesis 2： Asset-liability ratio and performance has a negative correlation in Henan listed Companies. 2.3 Results

The sample data were analyzed by use of statistical software SPSS Statistics 19.0 ， and the results were as following.