Influence of Macroeconomy on Enterprise Management Mode

Analysis of input-output efficiency of R&D in China Abstract: R&D activities have played an important role in enhancing the competitiveness of enterprises. This paper makes an empirical analysis of China R&D in 2009 by using the data envelopment analysis method. Input-output efficiency analysis shows that at present, China R&; The overall level of input-output efficiency is high, but there are great differences between industries and regions, and the low level of scientific research ability and management is the reason why R& is in most regions and industries; D one of the important reasons for low input-output efficiency: DEA；; R & ampd； Input output efficiency

China Library ClassificationNo.: F 124.5 Document IdentificationNo.: A DocumentNo.:1003-3890 (2011) 06-001-03.

In today's era of rapid development of science and technology, economic development is increasingly dependent on the improvement of scientific and technological level, and research and development (R&; D) As the innovation core of scientific and technological activities, activities play an important role in enhancing the competitiveness of enterprises. Countries, regions and even enterprises are increasing R&D to gain competitive advantage. D's investment However, how is the input efficiency of R & ampD and whether the input of S&T is surplus or insufficient? It is necessary to study the input efficiency of S&T, find out the factors that affect the input efficiency, and provide a basis for improving the input efficiency of S&T. ..

First, research methods.

Data Envelopment Analysis (DEA) is an analytical method to evaluate the relative efficiency (effectiveness) between departments, which was first put forward by famous American logistics experts A.Charnes, W.W.Cooper and E.Rhodes in 1978. This method uses the observation data of evaluation samples to study the method of multi-input especially multi-output decision-making unit (DMU) which is both "scale effective" and "technology effective". At present, DEA method is widely used to evaluate the operating efficiency of enterprises, schools, hospitals, financial and public welfare institutions. As a relatively new efficiency evaluation method, DEA has the following advantages: it can be used to evaluate the production efficiency of multi-input and multi-output complex decision-making unit systems. Because the index participating in the evaluation does not consider the dimension problem, it avoids many inconveniences caused by seeking the same unit of measurement: the weights of input-output variables are calculated by the planning model according to the actual data, which can avoid the interference of subjective factors in the weight distribution and ensure the objectivity of efficiency evaluation; DEA is a nonparametric evaluation method, which does not need the production function form of input and output, thus simplifying the design of evaluation model.

DEA model can be analyzed from two modes: input-oriented and output-oriented. Input-oriented model discusses efficiency from the perspective of input, that is, it is the most effective to study how much input is under the premise of constant output at present. The output-oriented model is to study efficiency from the perspective of output, that is, to pursue the maximization of output at the same input level. At R & ampd is easier to make investment decisions in the analysis of investment efficiency [www.starlunwen.com].

Control, at the same time, in order to eliminate the influence of the scale gap of various industries. This paper will use the input-oriented "fixed scale income" model to measure the comprehensive efficiency, and use the input-oriented "variable scale income" model to further decompose the comprehensive efficiency, so as to obtain pure technical efficiency and scale efficiency.

Technical efficiency refers to the relative efficiency and effectiveness of a decision-making unit. When the index value is 1, it shows that the decision-making unit is at the forefront of production and the comprehensive efficiency of the decision-making unit reaches the best, that is, DEA is effective; Pure technical efficiency measures the distance between decision-making unit and production frontier under the assumption of variable scale income. When the value is 1, the pure technical efficiency reaches the best, which is called technical effectiveness. Scale efficiency measures the distance between the production frontier under the hypothesis of variable scale return and the production frontier under fixed scale return. When the value is 1, the scale efficiency reaches the best, which is called scale efficiency.

Second, China R&; Input efficiency analysis

(1) research and development; Selection of input efficiency index

In order to study R&; Input efficiency, combined with the second national research and development; D resource inventory data, the paper selects input and output indicators, in which input indicators include human input and financial input, and output indicators include output level and marketization level of technological achievements, including 3 input indicators and 4 output indicators (see table 1 for specific indicators and descriptions).

(2) research and development; D in different industries; Input efficiency analysis

According to the second national r&; D. the results of resource inventory are submitted to the R&D department; 14 Industry D activities are relatively intensive. By calculation, in 2009, 14 industries r&; D The comprehensive www.jingjilunwen.net efficiency of input is 0.90 1 (as shown in Table 2), in which the scale efficiency is lower than the pure technical efficiency, and it is in the stage of diminishing returns to scale. Therefore, the input-output efficiency of science and technology can be improved by appropriately reducing the overall input. According to r&; D input efficiency value, 14 industries can be divided into four categories:

The first category, R &；; D Invest in efficient industries, including agriculture, forestry, animal husbandry, fishery, manufacturing, transportation, warehousing and postal services, information transmission, computer services and software, finance, scientific research, technical services and geological exploration, water conservancy, environmental and public facilities management, education, health, social security and social welfare, accounting for 60% of the total number of industries. These industries r & amp；; The pure technical efficiency and scale efficiency of D investment are greater than 0.9, that is to say, R &；; The input efficiency has reached a high level. In absolute terms, the proportion of capital investment and manpower investment in these industries is above 90%.

In the second category, scale efficiency is more effective and pure technology efficiency is lower. Including mining, electricity, gas and water production and supply, leasing and business services, the scale efficiency of these three industries has reached about 0.9, while the pure technical efficiency is less than 0.8, indicating that the scientific research ability and management level of these industries are not high, and management in this area should be strengthened.

In the third category, the pure technical efficiency is relatively effective, but the scale efficiency of industries with low scale efficiency, including culture, sports and entertainment 1 industries, is only 0.24 1, indicating that the scale of scientific research is not appropriate. In R& amp, because it is in the stage of increasing returns to scale, it can be improved by expanding R & D. the scale of investment to realize R&D of such industries; The input is valid.

The fourth category, industries with ineffective pure technical efficiency and scale efficiency, including 1 industry in construction, has pure technical efficiency and scale efficiency of 0.679 and 0.798 respectively. It can be seen that the effect of R &:D investment in construction industry is not good, not only because of the low scientific research ability and management level, but also because of R&: The scale of the research is not appropriate. Because the construction industry is in the stage of diminishing returns to scale, the scale of investment in science and technology should be appropriately reduced.

(3) research and development; In different regions; Input efficiency analysis

Similarly, according to the results of efficiency evaluation, R&: D input-output efficiency is divided. Because there is no area where pure technical efficiency and scale efficiency are invalid (as shown in Table 3), R&: Input-output efficiency is divided into the following three categories:

The first category, R &；; D The regions with overall effective input efficiency include Tianjin, Shanghai, Jiangsu, Zhejiang, Shandong, Hubei, Hunan, Hainan, Guizhou and Yunnan 10. These areas are effective in both pure technical efficiency and scale efficiency, which shows that under the current output level, R&: D input is valid.

The second category is the areas with relatively effective scale but low pure technical efficiency, including Hebei, Shanxi, Inner Mongolia, Liaoning, Jilin, Heilongjiang, Fujian, Jiangxi, Henan, Chongqing, Sichuan, Shaanxi, Gansu and Qinghai. The pure technical efficiency of Inner Mongolia and Hebei has not reached 0.6. The main reasons for the low comprehensive efficiency of this kind of areas are the low pure technical efficiency and the input-output efficiency level D.

The third category, areas with relatively effective pure technical efficiency and low scale efficiency, includes Beijing, Anhui, Guangdong, Guangxi, Tibet, Ningxia and Xinjiang. Among these seven regions, six regions except Tibet are in the stage of diminishing returns to scale. Therefore, we should reduce R &；; Invest in scale to improve the level of research and development. D in these six regions; D input-output efficiency, as far as Tibet is concerned, R&; Invest in science and technology to improve economies of scale.

Third, relevant suggestions.

By analyzing the data of R & ampd resource inventory in China, the author finds that R & AMPD in China; D The overall input-output efficiency is at a high level, but there is still a big gap between different regions and different industries. R & in some industries and regions; D input efficiency needs to be further improved. In view of the above analysis of www.starlunwen.net, this paper analyzes China R&; Put forward the following suggestions.

(1) Further strengthen R&D in China while ensuring the necessary investment scale; Research ability

According to r&; Input efficiency analysis shows that the input efficiency of China R& is at a high level. But specifically, in the 3 1 region analyzed, 17 region is in the stage of diminishing returns to scale, that is, the current R&: D investment is relatively surplus, that is, compared with the current R&: Insufficient investment scale, research and management capabilities, and research and development; Input-output efficiency, first of all, to improve China R&; The research level of d.

(2) Strengthen and promote exchanges and cooperation among local governments.

In view of the current research and development situation; D In various industries and regions of China; D there is still a big difference in input efficiency, so it is suggested to strengthen the exchange of research and management experience between industries and regions and improve R&; D. improve scientific research ability and management level, and improve input-output level.

(3) Gradually establish R&D based on efficiency; Input mechanism

Further strengthen the R&D of all industries, regions and even enterprises in China; D input-output efficiency evaluation, forming an input mechanism based on efficiency, thus promoting a more rational allocation of scientific research investment. Give more support to units with high input efficiency, find out the influencing factors according to the evaluation results for units with low input efficiency, and put forward targeted rectification measures to make limited resources play a greater role.

References:

[1] Albert, M.& Efficiency of Australian universities: Data Envelopment Analysis. Review of Educational Economics, 2003, (22): 89-97.

[2] Lu, Liu Lei. Research on the efficiency and development trend of natural science research in universities directly under the Ministry of Education [J]. Research on Higher Engineering Education, 2006, (1).

[3] Yan Dou, Shi Ping. Enterprises based on DEA R&; Input performance analysis [J]. Industrial Technology and Economy, 2006, (5).

[4] Shi Xiaofeng, DEA method in the performance evaluation of non-profit scientific research institutions [J]. journal of the hebei academy of sciences, 2006, (2).

Editor and Proofreader: Qin Xueshi

Analysis of R&D Input-Output Efficiency in China: Resources

Original address of Luo Yanping:/article/html/53010.html.

Department of Statistics and Accounting, Information Center, Bureau of Science, Technology and Industry for National Defense,

Beijing 10008 1, China)

Abstract: R&D activities play an important role in the competitiveness of enterprises. Based on the data envelopment analysis method, the author analyzes the resources of R & ampd 2009. At present, the overall level of input-output efficiency of scientific research in China is not high; D resources are relatively high. However, there are some differences between industries and regions. The low learning ability and management level are the important factors affecting the low input-output efficiency of R&D; D resources.

Keywords: dear & Input output efficiency