| 1Background and purposesThe Industrial Technology Innovation Alliance of China start later, although the number of Union is increasing every year, success rate is lower, Which one of the main reasons is that Union which implement performance evaluation is few, and only few of the Union develop and use a more formal performance measurement system. Conducting performance evaluation of the Union, in order to maintain the Union’s long-term stability and effectiveness, and ensure the quality of the operation of the Industrial Technology Innovation Alliance. So that a greater range of efficient use of resources to improve innovation and promote the healthy development of Industrial Technology Innovation Alliance. Compared with developed countries, performance evaluation of China’s Industrial Technology Innovation Alliance is still in the preliminary stage of exploration, methods and the performance evaluation system is not perfect. So far, the alliance performance evaluation failed to closely integrate the characteristics of the Industrial Technology Innovation Alliance, and distinguish the main purpose requirements between the different interests of the evaluation, thus the reliability and credibility of the evaluation is lower. Developing a scientific and reasonable performance evaluation index system to further promote the dynamic development and survival of the fittest is imperative in Industrial Technology Innovation Alliance.2Methods1. System analysisWe focus on Industrial Technology Innovation Alliance as a system for research design and pay attention to the relationship and structure of various factors that impact the evaluation of Industrial Technology Innovation Alliance. From the relationship of system environment, system architecture and system functions to study the rules and principles of Industrial Technology Innovation Alliance performance evaluation system. Then the dynamic analysis be presented in the main and minor factors that affect the construction and evaluation of Industrial Technology Innovation Alliance.2. Literature research methodIn this study, we use the journal databases and the Internet, widely accessible to evaluation studies of the Innovation Alliance literature, magazines and books. We familiar with the theory of knowledge and combine the requests of study to understand the research status, learn from the experience of previous studies, and explore the ideas and methods of further research.3. Delphi MethodIn this study, based on the needs of the topics we select three areas of consulting experts. Rely on the knowledge and experience of experts; we screen the initially built evaluation system and its specific evaluation information, and reflect the contribution of different indicators to the overall level by giving index weight. According to expert advices, we repeatedly modify evaluation system, and ultimately system is composed of5firstly level indicators,14secondary indicators and32third indicators.4.AHPAccording to the characteristics of the Industrial Technology Innovation Alliance, The study makes sub-class discussion about evaluation index which impact assessment. In each level of the layer order, through pair-wise factors compared that impact assessment, we determine the importance degree of different factors. Finally, we arrive at the relative value of various factors that affect the performance evaluation of the Industrial Technology Innovation Alliance.5. Statistical AnalysisIn this study, we use the statistical principles, methods and SPSS18.0to sort out and analyze data. We use the correlation analysis method to analyze the relevance of each indicator and judge the independence of the indicators. By calculating the reliability and validity of measured results we analyze the reliability of index system.6. Programming techniquesWe use Visual BASIC computer programming technology to develop the Industrial Technology Innovation Alliance Performance Evaluation Management System software.3Results1. Index system buildingWe use the Delphi and AHP to build the performance evaluation index system of Industrial Technology Innovation Alliance, which is composed of5firstly level indicators-innovation capability, development capacity, effective capacity, and win-win ability and service capabilities,14secondary indicators and32third indicators.2. The reliability analysis of expert consultingWe conduct the statistical analysis of consulting expert feedback with SPSS18.0statistical software. In this study, the expert authority coefficients of the five firstly level indicators as follows:Innovation capacity is0.8797, development capacity is0.8597, effective ability is0.8697, win-win ability is0.8130, service capability is0.7997, and the expert authority has a relatively high degree. In this study, the questionnaire consultation approval rating of the firstly level indicators was100%, the Kendall coefficient of the secondary indicators is0.271(χ2=118.014, P<0.0001), the Kendall coefficient of the third indicators is0.282(χ2=310.307, P<0.0001) Experts endorsed a higher degree of the firstly level index, but the Kendall coefficient of the secondary and the third indicators less than0.3(P<0.0001), lower. The reasons for that are the different research areas of selected experts or lack of communication between experts, lead to experts in institutions of higher learning and research institutes, and business has different emphases. The study conducted two rounds expert consulting; the consultation response rates were both100%, the experts actively higher. Through statistical analysis, the enthusiasm and authority of expert consulting meet the standards.3. Experimental studyTo further verify the objectivity and practicality of the performance evaluation index system of Industrial Technology Innovation Alliance, we used established evaluation index system for experimental study. As a result of statistical analysis, the reliability and validity of the index system are better.Correlation test:using Spearman correlation analysis to examine the independence and compatibility between the various indicators, the correlation coefficient of firstly level indicators is greater than0.362(r(0.05,30)), P<0.05. The correlation coefficient between the secondary indicators is greater than0.362(r0.05,30)), P<0.05, accounting for83.52%. The correlation coefficient between the third indicators is greater than0.362(r (0.05,30)), P<0.05, accounting for31.45%. Explaining the degree of correlation between the three index scores decreased gradually, and the mutual independence between the various indicators also gradually increases.Reliability and validity analysis:All measured indicators in the index system Cronbach’s α value is0.970, reliability higher. The scores of national and provincial industrial technology innovation alliance were respectively calculated, the higher the Union level, the higher the average score, this evaluation system is able to identify the different levels of the overall performance of the Union. Discriminate validity is better. The selection of measured indicators built on the base of experts’wealth practical experience and theoretical basis, ensuring the index system has good content validity. Spearman correlation analysis will be done between all the measured indicators with superior indicators, The correlation index scores at all levels with its higher index scores are larger, but smaller with other indicators, illustrating that the indicators have good construct validity. 4. Developed computer system evaluation software that matches performance evaluation index system of the Industrial Technology Innovation Alliance.4ConclusionsIndustrial Technology Innovation Alliance as an important form of cooperation to promote scientific and technological innovation in the new period plays a role in enhancing the technological innovation capability of China’s key industries; and the construction of the national innovation system with Chinese characteristics. Conducting performance evaluation of the Union in order to maintain the Union’s long-term stability and effectiveness, and ensure the operational quality of the Industrial Technology Innovation Alliance, promoting its healthy development. We need to build a set of specific performance evaluation index system of it.In this study, the integrated use of soft science method, to establish a more scientific performance evaluation index system of Industrial Technology Innovation Alliance. Through statistical analysis, the experts’authoritative is higher and has reliable results. We used established evaluation index system for experimental study of30Industrial Technology Innovation Alliance, as a result of statistical analysis, the reliability and validity of the index system is better. Based on the evaluation index system we designed and developed a set of practical, featured performance evaluation information management system of Industrial Technology Innovation Alliance, Providing conditions for promoting the alliance management normalization. This study is just a preliminary discussion on the establishment of performance evaluation index system and evaluation method of Industrial Technology Innovation Alliance, which is a beneficial attempt. |
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