Performance evaluation indicators for independent innovation
Independent innovation is divided into original independent innovation, synthetic innovation, and digestion and absorption innovation. Innovation is a complex system. It refers not only to the discovery of a theory or technology invention but also to the entire process from the theory proposed to the R&D experiment and the large-scale applications, which also involves scientific research organizations, process improvement and improvement of management, and other aspects. Here, we extract the three aspects, including innovation performance indicators of technological theory, innovation performance indicators of product technology, and innovation performance indicators of process technology and management, which are fully or partially reflected in the performance evaluation of an independent innovation project.
Independent innovation performance evaluation has a total of 24 indicators. Among them, the innovation performance indicators in technological theory include: (1) intellectual property indicators, including the number of patents approved and papers published; (2) theoretical innovation and impact, including degree of similarity to past technology development or introduced technology, and the degree of impact of innovative theory on practical application and subsequent research and expansion; (3) improvement of capabilities in learning and R&D, including benefits to accumulation of technical experience and tracking, updating, and exchanging technical information.
Innovation performance Indicators of product technology include: (1) time performance, including speed from development of new product to mass production and speed of gradient promoting of subsequent new products and commercialization; (2) quality performance—quality of the product compared with the products the enterprise has developed before and quality of the product compared with the new products developed by the competitors; (3) comprehensive performance, including domestic market share one year after the listing of the new product and the sales volume of the new product relative to the competitors; and (4) financial performance, including the return on investment (ROI) of the new products and the growth rate on investment (GROI) as well as the payback period for research and development of new product.
The innovation performance indicators of process technology and management include: (1) simplification and efficiency, including reduction of operating time, reduction of streamlining of new technology relative to the original technology, and increase of automation and the improvement of capacity; (2) coordination and conservation, including improvement of production conditions for staff, improvement of the degree of coordination between production capacity and demand, and decrease of pollution and energy dissipation; and (3) overall efficiency, including increase of self-made rate or replacement rate, decrease of overall cost and improvement of the mechanism of internal control, as well as improvement of image and corporate brand value of the enterprise (Figures 2.1-2.4).
Figure 2.1 Overall performance indicators of independent innovation.
Figure 2.2 Technology theory innovation performance indicators.
Figure 2.3 Product technology innovation performance indicators.
Figure 2.4 Process and management innovation performance indicators.
Determination of weight of indicators
Overview of weight determination methods and a brief evaluation
Weight refers to the share or importance of elements in the entire system. The heavier the weight, the greater the relative importance of the element in the whole system; and vice versa. Most of the indicator systems in the evaluation are required to determine the weight of the indicator, which is an important part of the comprehensive evaluation of enterprises and has a direct impact. Objective weight value is the basis and premise for obtaining the correct evaluation result. Therefore, the correct way and means of determining the weight of indicators is extremely important.
The methods for determining the weights can be roughly divided into two categories. The first category is subjective weighting. That is to say, the appraiser’s understanding of the importance of each of the participating indicators plays a major role in determining the size of the weights, including Delphi, Expert Conference Method, Weighted-Point Method, Comprehensive Score Method, Analytic Hierarchy Process, and Fuzzy-analytical
Method. The second type is objective weighting, which is to determine weights according to their own function and influence, including Entropy Weight Method, Principal Component Analysis, Factor Analysis, Cluster Analysis, Discriminant Analysis, and Multivariate Analysis Methods.
Analytic hierarchy process
The Analytic Hierarchy Process (AHP), also known as the Systemic Hierarchy Discovery Method, was proposed by famous operational researcher Satty in the 1970s. It is a semi-qualitative analysis method. First, the system is hierarchized and decomposed into different components according to the nature and overall goal of the system. The AHP is divided into different levels according to the interrelation and affiliation among the factors so as to form a multilevel system structure model, then calculate the weights of the relative importance of the lowest level factors relative to the highest level (the total goal of the system), and finally determine the ranking of the advantages and disadvantages of the schemes.
Entropy weight method
The Entropy Meight Method in determination of weights is also an objective method. “Entropy” is the concept of thermodynamics, which was first introduced by Claude Shannon into information theory. Generally speaking, the smaller the entropy E of an indicator, the greater the degree of variation of the indicator value, the greater the amount of information provided, and thus the greater the role it played in the overall evaluation and the greater its weight. Conversely, the larger the entropy E of an indicator, the smaller the degree of variation of its indicator, the smaller the amount of information provided, and thus the smaller its contribution to comprehensive evaluation and the smaller its weight should be. Therefore, the size of indicator weights can be inversely measured by entropy.
The Subjective Weighting Method may be contrary to objective reality due to its subjective influence. In the process of subjective weighting, a large number of judges usually allocate weights independently to each index, and then, through statistical calculation, determine the final weight of the indicator. Therefore, in order to meet the requirements of the randomized trial results and the statistical regularity, the Subjective Weighting Method must have a sufficient number of participants to ensure the accuracy of the evaluation. The Subjective Weighting Method applies to qualitative indicators.
The Objective Weighting Method is based on a large number of quantitative data. The weight of objective weighting is isolated from the sample data. As long as the sample data are the same and the number reaches the statistical requirement, regardless of the evaluator, the weights derived from the data are always the same, and the result obtained can be close to the actual situation to the maximum extent. Therefore, the Objective Weighting
Method is suitable to quantitative indicators and is more reasonable than the Subjective Weighting Method.
However, in the construction of the actual evaluation indicator system, there are often both qualitative and quantitative indicators. Therefore, in the determination of the weight, a combination of both the subjective method and the objective method should be adopted to ensure the accuracy of the weight determination.