Study on Re-Evaluation of Technological Innovation Efficiency Based on the C2r Improvement Model in Zhongguancun High-Tech Enterprises Jing-wen An, Sen Zhang, Guang-lin Sui School of Management,China University of Mining & Technology Beijing, Beijing, China E-mail: [email protected] Abstract - To begin with, this paper studied the relative efficiency of the Innovation Efficiency of 10 major High-tech industries in Zhongguancun. The study found that 7 of the 10 high-tech industries in Zhongguancun are relatively effective in their Innovation Efficiency. They are industries of electronic information, advanced manufacturing, new energy, new materials, modern farming, ocean engineering and nuclear application. Then this article introduced the virtual optimization of DMU based on the C2R model, which re-evaluated the relative effectiveness of the abovementioned 7 industries. Then this paper gave some suggestions to improve the innovation efficiency of these industries. Key words - Zhongguancun; High-tech Industries; Data envelopment analysis; DEA; Virtual decision making units I. INTRODUCTION The innovation efficiency of the high-tech industries in Zhongguancun demonstration industrial park is the conversion efficiency of input-output of production factors. It reflects the capacity of the industrial park to utilize technological resources and develop high-tech industries, as well as the quality and standard of the Zhongguancun innovation system. The Zhongguancun National Self-innovation Demonstration Park (hereafter referred to as “Zhongguancun”) is China’s first selfinnovation park, a leading area of high-tech industries and the hotbed of the strategic newly emerging industries. In the new stages of the 21st century, a re-evaluation of the innovation efficiency of the Zhongguancun high-tech industries can help government better plan new industries, utilize resources, raise efficiency and promote industrial restructuring. II. DEA MODEL C2R model Data Envelopment Analysis is a nonparametric comprehensive evaluation method to analyze the relative effectiveness of the DMU featured by high input and ［ ］ output 1 . It has been widely used to assess the efficiency of technology innovation within the same category of ［ ］ DMU 2, 3 . Usually DEA can be divided into C2R model 2 and B C model, both of which conduct horizontal comparison and analysis to different DMUs at the same ［ ］ time. The C2R model is as follows 4 : A. (1) s m min - S S vd i 1 r 1 s.t. n X S X 0 j j ( D ) j 1 n Y j j S Y0 j 1 0, j 1, 2 ,n j S 0,S 0 Within the (D) model, ϴ represents the effective value of DMU0, which is the effective use of the input against output. X j x1 j , x 2 j , , xmj , j 1, 2, T the input of DMU, Y j y1 j , y 2 j , , n represents , ysj , j 1, 2, T ,n represents the output of DMU. S ，S stands for the slack variable, which is supposedly bigger than zero. λj stands for composition ratio of DMUj within the DMU ［ ］ composition 5 . + - B. Improved DEA-C2R model In actual DEA evaluation processes, most of the DMU are relative effective, and only a few of the DMUs are invalid. This is because there are too many indexes and ［ too few DMUs, making the analysis result less practical 6 ］ . In this case, it should be made further analysis to the relative effective DMUs to evaluate the efficiency. There are many ways of sequencing in the DEA evaluation, and ［ ］ this paper adopts the virtual unit method 6,7,8 . Within the virtual unit method, a virtual decision making unit DMUn+1 is introduced to replace the normal DMU0 within the General model of constraint conditions so as to distinguish the different degrees of different DMUs. Suppose the input and output of DMU n+1 is （ xi,n+1,yk,n+1 ） , xi , n 1 min xij (i 1, , m) 1 j n yk ,n 1 max ykj (k 1, , s) . 1 j n The virtual decision making unit DMU n+1 is the best decision making unit among the valid DMUs. It’s compared the efficiency value of virtual DMU with the efficiency value of other DMUs. If the DMU show a value that is approximate to the virtual DMU, then the value is high. The evaluation process can be achieved by inputting valid DMU, or by introducing a virtual DMUn+1.. the result can be calculated ［ ］ through (Dε1) 8 . a result, the paper selected 6 indicators as the evaluation criteria of the innovation efficiency of Zhongguancun high-tech industries. Among these 6 indicators, 3 are ［ ］ input indicators and 3 are output indicators 9,10,11,12 . min[ (eˆ T s eT s )] n +1 s.t. x s x , j 1, 2, , n 1; j j j j 0 0 j 1 n 1 ( D 1 ) j y j s y 0 , j 1, 2, , n 1; j j0 j 1 0, j 1, 2 , n 1 j s (s1 ,s 2 , ,s s ) 0,s (s1 ,s 2 , ,s s ) 0 (2) The sequence of efficiency value from (D)ε is the sequence of quality of the decision making unit DMUj0. If the DMU value ≤1, the bigger the value is, the better the quality of this DMUj0. The DMU efficiency value (Dε2) can be calculated after the introduction of the virtual DMUn+1. max[ (eˆ T s eT s )] n +1 s.t. x s x , j 1, 2, , n 1; j j j j 0 0 j 1 n 1 ( D 2 ) j y j s y 0 , j 1, 2, , n 1; j j0 j 1 0, j 1, 2 , n 1 j s (s1 ,s 2 , ,s s ) 0,s (s1 ,s 2 , ,s s ) 0 (3) The sequence of efficiency value from (D)ε is the sequence of quality of the decision making unit DMU j0.If the value is 1, the smaller the value is, the smaller the gap between it and the virtual DMU, thus the better the quality of the DMUj0. This paper firstly evaluates the DMU through C2R and B C model within the DEA method. Then the paper introduces the virtual processing unit DMUn+1.The effectiveness of the DMU is calculated through the efficiency evaluation of the valid DMU. 2 III. CASE STUDY OF THE EFFECTIVENESS OF THE INNOVATION EFFICIENCY OF ZHONGGUANCUN HIGH-TECH INDUSTRIES A. establishment of the indicator system This paper studied the innovation efficiency of the Zhongguancun innovation system and the research results of relative scholars, took into consideration the representativeness and accessibility of these indicators. As Among the input indicators are: proportion of technology staff in the industry I1, total expenditure of the technological innovation I2, proportion of technology expenditure in the total revenue I3. I1 stands for the input intensity of technology staff, which is the ratio of technology staff against the total staff. I2 stands for the activity of technological innovation of the industry. I3 stands for the level and intensity of the industry ［ ］ independent innovation 13,14 . Among the Output indicators are: quantity of the patent accredit O1, proportion of new product sales revenue accounted for product sales revenue O2, proportion of new product sales revenue accounted for gross value of industrial output O3. O1 stands for the industry innovation important output value; O2 stands for the rate of new product sales, the contribution degree of industry enterprise technology innovation into new products on enterprise value creating; O3 stands for the transformation ability of the industry technology ［ ］ innovation 15 . B. Selection of data All of the evaluation indicators used in this article in assessing the innovation efficiency of Zhongguancun high-tech industries are objective. The data used here are mainly from the Annual Book of Zhongguancun Hightech Industrial Park and the Annual Book of Zhongguancun National Demonstration Park of Selfinnovation. Part of the data is from statistical data of the website of Zhongguancun National Demonstration Park of Self-innovation from 2006 to 2010(http://www.zgc.gov.cn/tjxx/). And part of the data is through calculation of these existing data. Therefore, these data are highly objective and credible. This paper treats the high-tech industries of Zhongguancun as a high-input and high-output system. Decision variables （DMUj，j=1，2，…，10）are the 10 high-tech industries of Zhongguancun Demonstration Park. Because of the different time-lag between input and ［ ］ output of the innovation 5 , the DEA efficiency analysis only uses the average figure of the indicator data in the Annual Book of the 11th five-year plan period. TABLE 1 STATISTICAL INDICATORS OF THE 10 HIGH-TECH INDUSTRIES OF ZHONGGUANCUN IN THE 11TH TWELFTH FIVE-YEAR PLAN PERIOD. Industries electronic information biomedicine New material Advanced manufacturing aerospace Modern agriculture new energy Environment protection ocean engineering Nuclear application I1（%） 39% 25% 25% 25% 40% 24% 30% 34% 27% 45% I2（billion Yuan） 36.159 1.945 2.493 4.133 1.751 0.427 2.643 1.029 0.075 0.275 I3（%） 13% 8% 7% 6% 37% 6% 4% 15% 14% 12% O1（item） 2764.00 378.20 676.00 1022.00 51.80 71.00 439.80 227.60 11.60 67.20 O2（%） 61% 41% 66% 42% 53% 70% 77% 63% 20% 79% O3（%） 83% 45% 88% 51% 62% 97% 103% 113% 24% 69% TABLE 2 INNOVATION EFFICIENCY VALUE OF ZHONGGUANCUN HIGH-TECH INDUSTRIES field of technology Overall efficiency Pure technical efficiency Scale efficiency Returns to scale Electronic information Biomedicine New material Advanced manufacturing Aerospace Modern agriculture New energy Environment protection Ocean engineering Nuclear application Average value 1.000 0.718 1.000 1.000 0.454 1.000 1.000 0.957 1.000 1.000 0.913 1.000 0.973 1.000 1.000 0.600 1.000 1.000 1.000 1.000 1.000 0.957 1.000 0.738 1.000 1.000 0.757 1.000 1.000 0.957 1.000 1.000 0.945 crs irs crs crs irs crs crs drs crs crs TABLE 3 INDICATORS OF VIRTUAL DMUS I1（%） 24% DMU DMU11 I2（million） 75 I3（%） 4% C. Evaluation of DEA-B2C model This paper utilizes the DEA input-output returns to scale B2C model, puts the data of TABLE 1 into the model and gets the result through DEAP 2.1. The innovation efficiency value of the 10 key high-tech industries is shown in TABLE 2. Since the DEA method is a relative evaluation method, the DEA value in TABLE ［ ］ 2 just stands for its degree of the relative effectiveness 16 . It can be seen from TABLE 2 that the biggest overall DEA value is 1, the smallest being 0.454 and the average value being 0.913. Among the innovation efficiency evaluation of Zhongguancun high-tech industries, 7 industries (electronic information, advanced manufacturing, new energy, new material, and modern agriculture, ocean engineering and nuclear application) have an innovation efficiency value of 1. This means that 70% of the DMUs are effective while 30% (environment protection, biomedicine and aerospace) of these are not. Generally speaking, most of the high-tech industries are relative effective in terms of innovation efficiency. D. Evaluation of the improved DEA-C2R model It can be seen from the results of the C2R and B2C model that industries with relative effective innovation efficiency account for a bigger share. In order to O1（item） 2764 O2（%） 79% O3（%） 103% distinguish the efficiency value of these industries, a virtual unit DMU11 was introduced to re-evaluate the innovation efficiency, as is shown in TABLE 3. Suppose ε=10-6, a C2R model based on the input of Archimedes infinitesimal C2R model is established. The C2R model of DMU1 is as follows: min[ (s1- +s2- +s3- s1+ s2+ s3+ )] s.t.0.391 +0.252 +0.253 +0.244 +0.35 +0.276 +0.457 0.248 s1 0.24 361.591 +24.932 +41.333 +4.274 +26.435 +0.756 +2.757 0.758 s2 0.75 0.13 +0.07 +0.06 +0.06 +0.04 +0.14 +0.12 0.04 s 0.04 1 2 3 4 5 6 7 8 3 ( D 1 ) + 27641 +6762 +10223 +714 +439.85 +11.66 +67.27 27648 s1 2764 0.61 +0.66 +0.42 +0.7 +0.77 +0.2 +0.79 0.79 s + 0.79 1 2 3 4 5 6 7 8 2 0.831 +0.882 +0.513 +0.974 +1.035 +0.246 +0.697 1.038 s3+ 1.03 j 0, j 1,2 ,8，s (s1 ,s2 ,s3 ) 0,s (s1 ,s 2 ,s3 ) 0 (4) After calculation by Matlab, the following results are innovation efficiency of Zhongguancun high-tech industries. See TABLE 4. TABLE 4 EVALUATION OF DEA EFFICIENCY C2R WHEN COMBINED WITH VIRTUAL DMUS DMU ϴ(Initial) ϴ（after improvement） 1~4 5 6~7 8 9 1 n j 1 Electronic information 1 0.615 0.000 1.000 1.000 1.626 New material 1 0.820 0.000 0.854 0.854 1.042 Advanced manufacturing 1 0.510 0.000 0.532 0.532 1.042 Modern agriculture 1 0.942 0.000 0.942 0.942 1.000 New energy 1 0.999 0.187 0.813 1.000 1.000 Ocean engineering 1 0.253 0.000 0.253 0.253 1.000 j Nuclear application 1 0.533 TABLE 5 VALUE OF INPUT-OUTPUT SLACK VARIABLES S1- S2- S3- Electronic information 0.61 0.31 New material 0.05 0.18 0.61 Advanced manufacturing 0.06 0.07 0.16 Modern farming 0.01 0.15 0.92 0.07 0.00 0.68 0.03 0.00 DMU New energy 0.13 Ocean engineering 0.02 Nuclear application 0.06 S1+ S2+ S3+ 0.30 0.24 0.02 0.00 0.05 0.19 0.25 0.03 0.18 0.98 0.41 It’s known that virtual evaluation unit is the best decision making unit. Therefore, we can rank the innovation efficiency of Zhongguancun high-tech industries in the following sequence: new energy > modern agriculture > new material> electronic information > nuclear application > advanced manufacturing > ocean engineering. In terms of economies of scale, industries of new energy, modern agriculture and ocean engineering are in the best condition, while all other industries have witnessed an increasing trend of returns to scale. Based on the DEA-C2R, it can get the invalid input indicator slack variable value and output indicator slack variable value of the 7 high-tech industries in Zhongguancun Demonstration Park. See TABLE 5(the input residual value and insufficient output value is zero, which is nothing in the TABLE). According to the projection analysis theory, it got the input residual value and the insufficient output value of the 7 high-tech industries of Zhongguancun Demonstration Park, which is relatively invalid. See TABLE 6 (the input residual value and insufficient output value is zero, which is nothing in the TABLE). IV. CONCLUSION Through the DEA analysis of innovation efficiency of the high-tech industries in the Zhongguancun industrial park, It can be seen that: A. Electronic information The efficiency value of the electronic information industry is 0.615 as evaluated through the DEA, ranking the 4th in the seven high-tech industries, with an economy of scale of 1.626 and an increasing trend. In 0.000 1.000 1.000 1.876 2010, electronic information industry accounted for 46.29% of the Demonstration Park. It also accounted for the largest proportion of technological expenditure in the 11th five-year plan period, almost 2.5 times as the other 9 fields. This shows that electronic information industry is No.1 pillar industry of Zhongguancun Industrial Park, with the most active innovation but relatively low innovation efficiency. According to TABLE 6, on condition that the input does not change, it should reduce the technological expenditure by 22.1767 billion Yuan, and the input intensity be reduced by 40%. And while maintaining a constant input, it should raise the proportion of sales revenue of new products in total sales revenue and total industrial output by 18% and 20% respectively, an effective efficiency. B. Advanced manufacturing As the second largest industry in Demonstration Park, the advanced manufacturing industry has an evaluation efficiency of 0.51 after DEA evaluation, ranking the 6th with a scale efficiency value of 1.042 and a growing scale. Its revenue accounts for 11.89% of the Zhongguancun Demonstration Park. Therefore, it should, in accordance with the plan of upgrading manufacturing industrial clusters, with the output unchanged, cut technological expenditure by 269.5 million Yuan, or reduce 90% of its input intensity. And while maintaining a constant input, it should increase 447.468 items of patents and raise the proportion of new products sales revenue in total sales revenue by 38%. C. New energy As a growth point of the industries in the Demonstration Park, the new energy industry has an efficiency value of 0.999 after DEA evaluation, ranking the first, with a scale efficiency of 1 and a constant return to scale. In 2010, the revenue of the new energy industry accounts for 10.93% of the industrial park. Therefore, in accordance with the plan of developing new energy, with the output unchanged, it should reduce the proportion of technological staff by 60%, cut the technological budget by 2.568 billion Yuan. While remaining a constant input, it should increase the patent authorization by 2324.2 pieces and the proportion of new products sales revenue by 20%. TABLE 6 INPUT RESIDUAL VALUE AND INSUFFICIENT OUTPUT VALUE S2-(billion Yuan) S3-（%） Electronic information 22.1767 40% New material 1.987 23% 1685.476 Advanced manufacturing 0.2695 90% 447.468 Modern agriculture 0.3315 19% 2531.99 44% 2324.2 20% DMU S1-（%） New energy 60% Ocean engineering 80% 2.568 25% S1+（item） 688.147 S2+（%） S3+（%） 18% 20% 15% 38% 21% Nuclear application 0.0717 D. New material As a fast growing industry, the new material industry gets an efficiency evaluation value by 0.820% after DEA evaluation, ranking the third, with a scale efficiency of 1.042 and increasing trend. In 2010, the new material industry accounted for 6.73% of the total revenue in the industrial park. So, while maintaining a constant output, it should cut the technological budget by 1.987 billion Yuan; reduce the budget input intensity by 23%. And while maintaining a constant input, it should increase patent authorization by 1685.476 items and the proportion of new products sales revenue by 15%. E. The modern agriculture industry The modern agriculture industry gets an efficiency evaluation value by 0.942, ranking the second, with a scale efficiency of 1 and a constant return to scale. In 2010, modern agriculture industry accounted for 0.76% of the total revenue in the Demonstration Park. Though the proportion is small, this industry is essential to the people’s wellbeing. So, while maintaining a constant output, it should cut the technological budget by 331.5 million Yuan; reduce the budget input intensity by 19%. And while maintaining a constant input, it should increase patent authorization by 2531.99 items and the proportion of new products sales revenue by 44%. F. Nuclear application The nuclear application industry gets an efficiency evaluation value by 0.533, ranking the 7th, with a scale efficiency of 1 and an increasing return to scale. In 2010, modern agriculture industry accounted for 0.17% of the total revenue in the Demonstration Park. Despite a tiny proportion, this industry is strategically important to the national economy. So enough attention should be paid to this industry. While maintaining a constant output, it should cut the technological budget by 71.7 million Yuan; reduce the budget input intensity by 25%. And while maintaining a constant input, it should increase patent authorization by 2696.8 items and the proportion of new products sales revenue by 34%. G. Ocean engineering The ocean engineering industry gets an efficiency evaluation value by 0.253, ranking the 8th (the last place) with a scale efficiency of 1 and a constant returns to scale. In 2010, modern agriculture industry accounted for 0.17% of the total revenue in the Demonstration Park. Given its strategic importance, enough attention should be paid to this industry. While maintaining a constant output, it should cut the proportion of the technological staff by 80%; reduce the budget input intensity by 24%. 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