Competitiveness Evaluation of Chinese Dairy Industry Based on Accelerated Genetic Algorithm Projection Pursuit Model

Abstract

Scientific evaluation of the competitiveness of China’s dairy industry is of great significance to the development of regional dairy industry. In view of the fact that the existing evaluation model cannot solve the dynamic nonlinear optimization problem, this paper established a projection pursuit model based on accelerating genetic algorithm and carried on the comprehensive evaluation and dynamic analysis on the competitiveness of dairy industry in China’s 31 provinces and cities (not including Hong Kong, Macao, and Taiwan) from five dimensions, namely, basic factors of production, the industry demand conditions, the enterprise competitiveness and growth force, related and supporting industries, and the natural environmental elements. It was found that firstly, from the perspective of time, the development trend of China’s dairy industry basically shows a positive trend. With the improvement of national living standards, the competitiveness of the dairy industry is also constantly improved. Secondly, from the perspective of space, regional differences in the competitiveness of the dairy industry are significant. Inner Mongolia, Heilongjiang, Shandong, and Hebei are at the forefront of the development of the industry, while the development of the dairy industry in the rest of the region has a big gap with those areas. From the perspective of regional layout, the advantageous region of China’s dairy industry has been preliminarily formed, and the competitive advantage is mainly concentrated in the northern region. Accordingly, the countermeasures and suggestions to enhance the competitiveness of China’s dairy industry were put forward.

Evaluation of Corporate Social Responsibility and Core Competitiveness Based on GA-SVM Model

“…The SVM model does not exceed 5% and meets the prediction accuracy requirements, therefore, it is effective to select the Gaussian radial basis kernel function (RBF) as the kernel function of the GA-SVM intelligent evaluation model [17]. It should be pointed out that the evaluation result value of core competitiveness is a number between (0, 1), according to the different scores, the core competitiveness is comprehensively evaluated and divided into the following five levels: If the score is between (0.9, 1), the core competitiveness is assessed as Level I, that is, the enterprise performs well and has strong core competitiveness; If the score is within (0.7, 0.9), the core competitiveness is assessed as Level II, that is, the enterprise performs well and its core competitiveness is relatively strong; If the score is between (0.5, 0.7), the core competitiveness is rated as Level III, that is, the enterprise's performance is average, the core competitiveness of the enterprise is also general, and there are areas for improvement; If the score is between (0.3, 0.5), the core competitiveness is assessed as Grade IV, that is, the enterprise performs poorly and its core competitiveness is weak, so it needs to further seek targeted effective measures suitable for the enterprise itself to improve; If the score is between (0, 0.3), the core competitiveness is rated as Grade V, that is, the performance of the enterprise is very poor and the core competitiveness of the enterprise is very weak, it is urgent to solve its own problems and seek various effective ways to improve the core competitiveness of the enterprise [18][19][20].…”