The Study On Analysis Of The Factors Affecting The R&d Intensity Of Large And Medium-sized Industrial Enterprises In China

21st century, the ear of knowledge economy has appeared. The economic globalization, information technology and high-tech are rapidly developing. Scientific and technological innovation, especially "independent innovation" has been valued by countries all over the world, and it has played an important role in development of economy and society. At present, our country has determined the goal of "enhancing capability of independent innovation, building an innovation-oriented country" as the national strategy. Giving the importance of the technological innovation, studying the impetus of technological innovation and explore how to increase enterprise's R&D investment have great practical significances. This thesis will place perspective on large and medium-sized industrial enterprises, studying the internal determinants of the enterprise's R&D investment.The thesis describes R & D investment, using large amounts of data and charts, including the total financial input, the financial input intensity, the structures of the funding sources, personnel investment, patent applications and other aspects. Then we compare China with other countries in those factors and analyze them. Through the comparison we find the current R&D investment level of our country is still lagging behind the economic development. There are still many problems, compared with other countries. The situation can be roughly summarized as:The R&D expenditure in China grew faster, but less in the total and low in intensity; The enterprise R&D awareness needs to be improved; There are obviously insufficient investment in R&D personnel and the personnel quality gap between us and the developed countries is large; The patents applications accepted and granted are low.Through the comparison and analysis above the former chapters, chapter IV and V do empirical analysis on the R&D intensity of the large and medium-sized industrial enterprises in China, and select sales revenue of new products as a percentage of total revenue from the sale of products, funding for S&T activities (government funds, self-raised funds by enterprises, loans from finance institutions) the number of enterprises' intellectual property, human capital and human capital wage incentives as factors. We use data from 1991 to 2007 to make a regression analysis. The results indicate that R&D intensity of the large and medium-sized industrial enterprises in China has an obvious positive correlation with ales revenue of new products as a percentage of total revenue from the sale of products, funding for S&T activities, the number of enterprises'intellectual property and enterprise human capital wage.The innovation of this paper is mainly reflected in these respects:we make the study of enterprise as the background, doing empirical analysis of the factors affecting the R&D intensity of the large and medium-sized industrial enterprises from the micro-level view. The references are mainly related to the sizes of the enterprises, industries that enterprises owned to, their ownerships and locations and other relevant factors. The objects of the research are primarily the enterprises in a province or a region and the data sources are from large surveys.In this thesis, we use theoretical and empirical research methods, researching on the comprehensive analysis of the factors affecting enterprises' R&D intensity. Although I try my best to gather information and pay attention to use the scientific methods, with the constraints of available information and my limited capacity, there are also disadvantages as followed:1. In the research sample, the paper's overall sample size is relatively limited. In addition, although we selected seventeen years data, but there are also many factors that are not summed up. We just use time-series data of the seventeen years to do some regression analysis on the local factors while doing regression analysis.2. There are also missing variables existed in this problem while choosing the variables in the study. Although the variables have involved funding for S&T activities, sales revenue of new products as a percentage of total revenue from the sale of products, technology infrastructure, human resources, etc., there are many difficulties in data collection, some non-quantifiable variables, the inevitable presence of missing variables. This paper uses time-series data rather than using panel data, owning to this limitation, we can't do a deep research on factors referred to the industries enterprises exist in, the sizes of the enterprises, corporate ownership and geographical location.