Keywords: coordination degree of entropy weight method of regional innovation performance
Taking the connotation and evaluation method of regional innovation performance as the research object, this paper comprehensively defines the basic connotation of regional innovation performance from two aspects of regional innovation efficiency and effect, and based on this, constructs an evaluation model of regional innovation performance, and makes an empirical analysis on the regional innovation performance of Hebei Province in 2008.
Connotation of regional innovation performance
Regional innovation performance is a complex and extensive concept, and there is no consistent view at present. Some researchers at home and abroad have explained the regional innovation performance and its related concepts from different angles and needs. The United States is the first country to carry out research on innovation performance index system; The Organization for Economic Cooperation and Development put forward the guiding principles for collecting and interpreting innovation data; The EU evaluates the innovation ability of member countries from two aspects: scientific and technological input and scientific and technological performance, and the index system highlights the important role of human resources in innovation ability (Yang Zhijiang, 2007). In domestic research, most of them use factor analysis and DEA method to create an index system for quantitative evaluation, but the definitions of some concepts are not completely consistent with international standards, such as R&; D source of funds, definition of large enterprises, etc.
In essence, the regional innovation system is a typical input-output process. The input of regional innovation is represented by personnel, equipment and funds, and the output is represented by patented technology, products and technological methods. The ultimate goal of regional innovation is to promote regional economic and social progress. Therefore, studying the performance of regional innovation is not only the input-output process, that is, the efficiency of regional innovation, but also the contribution of regional innovation to economic and social development, that is, the effect of regional innovation, which is one-sided. Therefore, the connotation of regional innovation performance includes two aspects, namely regional innovation efficiency and regional innovation effect. The input-output efficiency of regional innovation activities should be high, that is, the input resources should be effectively used; Regional innovation activities should be able to promote regional economic and social development, that is, the output results should be effectively used. Regional innovation performance should be a comprehensive reflection of the above two aspects.
Construction of regional innovation performance evaluation model
(A) Model building ideas
According to the meaning of regional innovation performance put forward in this paper, in order to ensure the scientificity and comparability of performance evaluation, this paper uses entropy weight method and collaborative scheduling method to evaluate the efficiency and effect of regional innovation respectively, and then comprehensively evaluates the regional innovation performance. The advantage of entropy weight method is an objective weighting method, which does not add the subjective evaluation of the evaluator, but its conclusion only reflects the relative effectiveness, and the index weight is determined according to the influence of the relative change degree of the index on the whole system; The advantage of coordination degree is that it can detect the coordination among multiple evaluation objects, and get the coordination between innovation investment and economic development in each administrative division, thus reflecting the role of regional innovation investment in each decision-making unit. However, its disadvantage is that the coordination degree makes the meaning of the function unclear, and the evaluation result is greatly influenced by the absolute value of the index. Therefore, this paper combines the two methods, analyzes the effectiveness of regional innovation activities with entropy weight method, analyzes the coordination between regional innovation investment and economic development with coordination degree method, and investigates the effect of regional innovation activities, thus establishing a composite evaluation model based on entropy weight method and coordinated scheduling, as shown in figure 1.
(2) Model introduction
Entropy was originally a thermodynamic concept. Information theory was first introduced by Shennong, and now it has been widely used in engineering technology, social economy and other fields. According to the basic principle of information theory, information is a measure of the degree of system order; Entropy is a measure of the disorder degree of the system; Their absolute values are equal, but their signs are opposite. If there are m evaluation indexes and n units to be evaluated, the entropy of the system can be defined as (I = 1, 2 …, m), where (rij is the normalized matrix of the original data), then the entropy weight of the ith index is (Xie Chi et al., 2002.
)。
The coordination between regional innovation and economic development level is measured by coordination degree and coordinated development degree, which can only reflect the coordination degree between the two systems, while the coordinated development degree can reflect the level of the system at that time. Before determining the coordination mode, the comprehensive level of the two is evaluated by simple linear weighting method, in which the evaluation function of comprehensive innovation ability is: and the comprehensive economic development level function is. The degree of coordination and the degree of coordinated development are defined as formula (1) and formula (2) respectively.
(K=2, k is the discriminant coefficient)
( 1)
(2)
In ...
According to the calculation results, the definition of coordination degree between regional innovation investment and economic development is shown in table 1.
(3) Comprehensive judgment and comparison of performance
Taking entropy weight as the abscissa and coordinate value as the ordinate, a two-dimensional coordinate plane is formed, and the horizontal axis and the vertical axis are divided into two parts to distinguish the effectiveness and effect of the regional innovation activities of the evaluation unit, thus forming a four-quadrant coordinate map, as shown in Figure 2. The entropy weight and coordination value of evaluation units in region A are high, which shows that the evaluation units in this region have high efficiency in regional innovation activities, good coordination with economic development and good performance in regional innovation activities; In the evaluation unit of area B, the coordination value between regional innovation activities and economic development is high, but the entropy weight is low, which shows that the efficiency of regional innovation activities is low and the performance of regional innovation activities belongs to the middle level; The entropy weight of the evaluation unit in Area C is high, indicating that the regional innovation activities are efficient, but the coordination value between regional innovation investment and economic development is low, and the regional innovation performance is also at a medium level. The entropy weight and collaborative scheduling value of evaluation unit in D region are low, which shows that the efficiency and effect of regional innovation activities are poor and the performance of regional innovation activities is low. Multiple evaluation units in the same area can be compared and analyzed according to their relative positions.
empirical analysis
(A) entropy weight method evaluation
1. Indicators and data. Entropy weight evaluation index system This paper selects four input indexes, namely, the number of scientific and technical personnel (0. 125), the number of scientists and engineers (0. 125), and R&; D internal expenditure (0. 125), R &；; D ratio of funds to GDP (0. 125). The three output indicators are: the number of scientific papers (0. 125), the number of patents granted (0. 125), and the contract value of technology market (0.25). (The data in brackets are the initial weights of indicators determined by experts' scoring).
2. Entropy weight evaluation and analysis. Due to the limitation of space, this paper omits the calculation results of other 27 provinces and some intermediate steps. The entropy weight of Hebei Province is shown in Table 2. According to the evaluation results of entropy weight, the comprehensive entropy value of Hebei Province is 0.05 16, ranking 2 1 among the 28 evaluated provinces, indicating that the overall regional innovation efficiency of Hebei Province is low, belonging to the middle and lower reaches level.
Coordinated evaluation
1. Indicators and data. The index is selected by frequency statistics and weighted by AHP, as shown in Table 3.
2. Evaluation and analysis of coordination degree. The Z-score method is used to standardize the original data, and the coordination degree and coordinated development degree of Hebei Province are calculated by the coordination degree evaluation method, as shown in Table 4.
Judging from the evaluation results of coordination degree, the coordination degree of Hebei Province is 0.9202 and the coordination development degree is 0.8756. According to the degree of coordination, regional innovation activities and economic development in Hebei Province belong to the category of good coordinated development. Because the economic comprehensive function value F(E) is less than the regional innovation comprehensive function value F(ST), Hebei Province belongs to the coordinated development type with economic lag. This shows that the economic development of Hebei province lags behind the innovation input for two reasons: first, the output efficiency of the existing regional innovation input is not high, and second, the regional innovation output has not been effectively transformed into productivity.
(C) Comprehensive evaluation of regional innovation performance in Hebei Province
According to the above method, the evaluation results of empirical analysis in 28 provinces and cities (excluding Hong Kong, Macao and Taiwan) are excluded from Qinghai, Ningxia and Tibet where data collection is limited. We take entropy value and coordinated development degree as abscissa and ordinate, respectively, and get the comprehensive performance judgment chart (see Figure 3).
As can be seen from the figure, the entropy value of Hebei Province is 0.
05 16, and the coordinated development value is 0.8756, which is in the D area with low performance. Therefore, it is judged that the performance of regional innovation system in Hebei Province is at the lower-middle level. Its specific characteristics are: low efficiency of regional innovation investment; Innovation activities and economic development belong to coordinated development, but economic development lags behind.
Regional innovation is an important strategy and measure for the government to promote the development of science and technology. A scientific and comprehensive evaluation of its performance will help the government to understand and improve the deficiencies in innovation investment and use, and better promote the all-round development of science and technology, economy and society. This paper innovatively defines the connotation of regional innovation performance from two aspects: efficiency and effect. Based on this connotation, a comprehensive evaluation model of regional innovation performance is constructed by using entropy function and co-scheduling method. Due to the limitation of space, this paper mainly makes an empirical analysis of regional innovation performance in Hebei Province.
References:
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