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In recent years, with the continuing downturn in international market demand and the continuous increase in cost pressures, coupled with the serious lag in industrial restructuring and upgrading, China's sporting goods manufacturing industry has faced serious crises, especially in the two traditional fields of sportswear and sports shoes, and sales revenue in recent years. In 2013, the sales revenue of major domestic brands of sportswear and sports shoes fell by 23.2% and 19.2% year-on-year, respectively. Leading domestic companies such as Li Ning, Peak, Anta, etc. had to cut off their lives by shutting down their stores under huge inventory pressure. . There are many reasons why China's sporting goods manufacturing industry is in a serious crisis. There are both demand reasons and cost reasons. However, the deepest cause is the backward economic development mode. It mainly depends on the extensive development of factor input and labor cost advantages. It is difficult to support the long-term healthy development of the entire industry. The fundamental way to promote the healthy development of China's sporting goods manufacturing industry lies in accelerating the transformation of economic methods and adopting the intensive development approach, relying mainly on technological innovation and the improvement of total factor productivity to drive industrial development. Then, what is the current situation of the change in total factor productivity of the sporting goods manufacturing industry in China? The fund project that affects the total factor productivity of the sporting goods manufacturing industry: The Jiangsu Provincial Sports Bureau's management topic “Research on the development of relying on private capital to develop the province's sports industry†, project number: TY11318.), male, Yancheng, Jiangsu, associate professor, master's degree, research direction is sports education and sports sociology. What are the key factors and how can we more effectively increase the total factor productivity of the sporting goods manufacturing industry? For the above issues, the current domestic academic community has not made a systematic response. This paper intends to use the Malmquist Productivity Index method based on DE 8 to measure the total factor productivity changes in China's sporting goods manufacturing industry based on panel data from 2004 and 2011, and use dynamic panel data models to analyze the relevant influencing factors, and then explore the promotion of all factors of the sporting goods manufacturing industry. The measures of productivity measures are expected to benefit the healthy development of China's sporting goods manufacturing industry. 1 Research Methods, Indicator Selection and Data Sources 1.1 Research Methods and Retrospectives Total factor productivity refers to the contribution of factors other than tangible elements such as capital and labor to output growth and is an important tool for analyzing the source of economic growth. The main research paradigm of economic development. At present, the mainstream methods for studying total factor productivity include the Solow residual method based on traditional production functions, the stochastic frontier production function method, and the Malmquist productivity index method based on DE 8. This paper selects the Malmquist productivity index method based on DE-VIII. The advantages are: Decomposition of total factor productivity changes into technological changes, technological efficiency changes (including scale efficiency changes and pure efficiency changes), and facilitate analysis of the drivers and influencing factors of total factor productivity changes. The co-linear programming approach to calculate various distance functions for inputs and outputs does not require constraints such as price information, cost minimization, and profit maximization; it can handle multiple input and output variables. At present, the Malmquist productivity index method based on DE-VIII has been widely used in the study of total factor productivity in manufacturing. Generally speaking, from the perspective of the research object, there are mainly two clues: the entire manufacturing industry as the research object. The total factor productivity of the manufacturing industry as a whole is analyzed and its growth momentum is analyzed. For example, Zhao Wei and Zhang Cui (2008) calculated the panel data of 20 industries in 1999 and 2003. The results show that the total factor productivity of China’s manufacturing industry grew by an average annual rate of 12.2%. The growth momentum mainly comes from technological progress, and technical efficiency has a constraining effect. . Tian Zeyong and Jiang Keshen (2010) based on the measured results of industry panel data in 2000 and 2007, the total factor productivity of private manufacturing in Jiangsu increased by an average of 7.7% annually, and the main driving force came from technological progress. Sun Xiaohua, Wang Wei, and Zheng Hui (2012) based on the measured results of the industry panel data in 2000 and 2009, the total factor productivity of China’s manufacturing industry grew by 3.1% annually, and 97% of the growth momentum came from technological progress. Zhang Gongyi, Chen Xiang, and Li Zan (2013) based on the panel data of 28 sub-sectors in 2000 and 2009 showed that China's manufacturing sector’s total factor productivity increased by an average of 9.6 percent per year, and more than 80 percent of the growth momentum came from technological progress. In general, most of them think that the overall factor productivity of the manufacturing industry in China is growing, and the growth drivers are mainly from technological progress. The second is to study the sub-industry of the manufacturing industry, measure the total factor productivity of the sub-industry, and analyze its growth momentum. For example, Zhao Ran, Luo Le and Han Peng (2008) based on panel data from 12 industries in China's agro-processing industry in 1999 and 2005. The results show that the total factor productivity of China's agro-processing industry is growing at a faster rate. State-owned and state-controlled enterprises and “three†The average annual growth rate of “funded enterprises†is 8.7% and 5.2%, respectively, and the growth of total factor productivity mainly comes from technological progress rather than efficiency change; 7 Zhan Lei and Wang Kai (2012) based on the agricultural products processing industry in Jiangsu Province in 2008 12 The calculation results of the panel data of each industry show that the total factor productivity of the agricultural product processing industry in Jiangsu has been showing an increasing trend, and it has increased by more than 5% in most years, and the main source of power for total factor productivity growth is technological change. 8 Due to the large differences in the sample, it is understandable that there is a significant difference in the overall productivity measurement of the sub-industry. However, if you face the same sub-industry, the results will be very different in the same sample period, and it is worth pondering. For example, in the sporting goods manufacturing industry, there are significant differences in different research findings. Zhang Hongwei and Li Xuedong (20 12) based on the panel data of 18 provinces and districts in 2001 and 2006, the total factor productivity of China's sportswear manufacturing industry showed an average annual negative growth of 19.3%, of which the main driver of decline was the decline in technical efficiency; Chen Po (2014) based on the panel data of 22 provinces and autonomous regions in 2003 and 2010 shows that the total factor productivity of the sporting goods manufacturing industry in China has increased by 11.1% annually, and the growth momentum comes from technological progress (5.7%) and technical efficiency (5.2). %) two-wheel drive. 10 Overall, relative to the overall manufacturing industry and other sub-sector industries, the trend of changes in the total factor productivity of the sporting goods manufacturing industry is not clear. The growth momentum is no longer independent of technical progress, but also different for the sports goods manufacturing industry. There is a very significant difference in the results of TFP research. Under normal circumstances, due to the difference in sample size and indicator selection, it is understandable that there is a certain difference in the total factor productivity measurement results at the numerical level. However, in a three-digit segment industry such as sporting goods manufacturing, total factor productivity measurement results It is somewhat surprising that such a significant contrast has emerged. Therefore, this paper also hopes to respond to this difference through further calculations, and the only two articles on the total factor productivity of sporting goods manufacturing are limited to the measurement and decomposition of total factor productivity and not to total factor productivity. The influencing factors have been empirically tested. This paper intends to do some extended research on the influencing factors. 1.2 Selection of Indicators The most widely criticized issue of the Malmquist Productivity Index based on the DE-VIII problem is the randomness of the choice of variables. The choice of input and output variables has been varied. In order to circumvent the above problems, most of them are used to production. The basic variables of the function method are output value or added value as output variable and capital and labor as input variables. The production function of the neoclassical economic growth theory provides a theoretical basis for the study of the total factor productivity of sporting goods manufacturing by provinces and districts as decision making units. (1) Output variables: This article selects the total industrial output value of enterprises on the scale of sporting goods manufacturing; 2) Input variables: The total fixed assets of the enterprises and the average number of employees in the sports goods manufacturing scale are selected to represent capital and labor. . The selection of input and output variables in this paper is basically the same as that of Zhang Hongwei and Li Xuedong (2012). They use the total output value as the output variable, and the fixed assets and employees as input variables to facilitate comparative analysis. In the analysis of influencing factors, the main focus is on variables such as human capital, technological innovation, firm size, and consumer demand. The human capital variable adopts the average years of education of population over 6 years of age, according to the standards of 6 years of primary school, 9 years of junior high school, 12 years of high school, and 16 years of university, and is calculated on the basis of data on the proportion of the population of different levels of education; the scientific and technological innovation variables use patents for inventions. The authorized quantity index; the enterprise scale variable adopts the average asset size index of the enterprise, and is calculated based on the total assets and the number of enterprises in the sports manufacturing industry in each province; the Xiaofu demand variable adopts the per capita cultural and educational entertainment expenditure index of urban residents. As the total factor productivity change data based on the Malmquist productivity index method is the data of the ring change, the data of the relevant influencing factors are also processed in a ring, that is, all indicators adopt the ratio of the current year data to the previous year data. 1.3 Sample selection and data sources The sporting goods manufacturing data used in this paper comes from the three-digit industry data published by the China Statistical Data Application Support System. The data of the "China Statistical Data Application Support System" comes from the National Bureau of Statistics and is authorized by the Statistics Bureau in writing. According to the “Statistical Data Application Support System of Chinaâ€, the data on the sports products manufacturing industry in 2003 and 2011 were reported in 22 provinces and autonomous regions. However, some of these provinces and districts have incomplete data and cannot meet the requirements for balanced panel data. Excluding provinces, districts and years with incomplete statistical data, data from 14 provinces and districts in Anhui, Beijing, Fujian, Guangdong, Hebei, Hunan, Jiangsu, Jiangxi, Liaoning, Shandong, Shanxi, Shanghai, Tianjin, and Zhejiang in 2004 were obtained. Therefore, a total of eight periods of data from 14 sample provinces were obtained. In this paper, we input 1 variable, 2 output variables, and 14 decision-making units (sample provinces and districts), which are fully consistent with the important empirical rules of DE 8 theory proposed by Banker et al. (19 89): The number of decision units (DMU) must be input and output. More than double the sum of the variables, otherwise the difference in DE 8 efficiency will be weaker. 13 Data on the proportion of the population with different levels of education, the amount of patents granted for invention, and per capita cultural, educational, and recreational expenditures of urban households come from the “Statistical Yearbook of China†on the website of the National Bureau of Statistics and relevant years. 2 Analysis of the calculation results of total factor productivity change in sporting goods manufacturing industry This paper is based on the input-oriented CRS model, and uses data analysis and measurement software DEAP 2.1 to measure data from 14 provinces and districts in 2004. The Malmquist Productivity Index of China's sporting goods manufacturing industry, Yang See Table 1 and Table 2. First of all, from the 2004-2011 average, the total factor productivity of China's sporting goods manufacturing industry showed an overall increase, with an average annual increase of 3.1%. According to decomposition indicators, technological changes show a growth trend with an average annual growth of 5.7%, while technological efficiency changes show a downward trend with an average annual decline of 2.5%. Among them, pure efficiency changes show a growth trend with an average annual increase of 1.6%, and scale efficiency declines. The situation shows an average annual decline of 4%. This shows that the main driving force for the growth of total factor productivity in sporting goods manufacturing comes from technological progress, especially the lag in scale efficiency and total factor productivity growth. Although pure efficiency has a certain role in promoting, However, it is unable to compensate for the scale efficiency. Factor productivity growth had a negative effect. Second, during the entire sample period, the total factor productivity of China's sportswear manufacturing industry fluctuates significantly. There are four periods in growth, three periods in decline, and there is a large gap between peaks and troughs. 2005, 2006 The rate of increase was as high as 45.3%, and the rate of decline in 2007 and 2008 was as high as 45.6%. Looking further at the source of change in total factor productivity, technological changes in the four periods of total factor productivity growth were in a state of growth, while total factor productivity fell by three. At the same time, technological changes were in a declining state. This shows that technological change dominates the trend of total factor productivity and is the main driving force for changes in total factor productivity; pure efficiency has been growing for five periods, but its promotion of total factor productivity growth The role is relatively weak, unable to overcome the constraints imposed by the technological recession, and only the three periods in which technological changes are also in a growth state have contributed to the growth of total factor productivity; the scale efficiency has only grown in three periods, but only in 2006. In the case of technological changes and pure efficiency changes are also growing Next, it only promoted the growth of total factor productivity. In the period when the other two economies of scale were in an increasing state, the improvement in scale efficiency could not overcome the restraint effect of the technological recession. In the other four periods, the decline in scale efficiency directly constrained the total factor. Productivity growth. Year Technical efficiency change Technical change Pure efficiency change Scale Efficiency change Total factor productivity Thirdly, from the 2011 2011 average of the changes in total factor productivity in 14 sample provinces, there are 7 provinces and regions showing a growth trend, and 7 provinces and districts are in Showing declines, each accounting for 50%. Among the 7 provinces and districts where total factor productivity is showing signs of growth, all provinces and regions have experienced a trend of technological change and pure efficiency change. At the same time, only three provinces and districts have experienced a decline in the efficiency of scale. Situation, and the decline rate does not exceed 4%. Only one province has experienced a decline in technological efficiency, but the decline rate is less than 1%. This shows that the growth of TFP in most provinces and regions is based on technological progress and technological efficiency. It is achieved through the dual drive of improvement, but the contribution of scale efficiency is relatively small, with the highest growth rate being only 2.1%. In the seven provinces and districts where total factor productivity is declining, the scale efficiency and technical efficiency of all provinces have declined. The pure efficiency of only one province showed a growth trend, while the technological changes in all provinces and regions showed a growth trend. This shows that all provinces and districts have their own Reduced productivity are particularly subject to technical efficiency scale efficiency recession drag on, and promote technological progress completely offset the restraining effect of technical efficiency recession. Fourth, although China's sporting goods manufacturing industry is mainly concentrated in the eastern coastal areas, only 4 out of the 14 sampled provinces and areas are in the central region, and all of them belong to the eastern coastal areas. However, the total factor productivity of sporting goods manufacturing industry still shows significant changes. With regard to regional differences, the eastern coastal areas are clearly ahead of the central region. Six of the seven provinces with increasing total factor productivity are in the eastern coastal provinces, and three of the four central provinces have declined in total factor productivity. Judging from the geometric mean values ​​of the eastern coastal provinces and the central provinces and autonomous regions, the total factor productivity of the sporting goods manufacturing industry in the eastern coastal provinces and regions generally showed a growth trend with an average increase of 4.6%, while the total factor productivity of the sporting goods manufacturing industry in the central provinces and autonomous regions On the decline, the average decline is 0.8%. From the perspective of regional differences, the trend of total factor productivity in sportswear manufacturing industry has no obvious correlation with the level of regional economic development, but it has a certain correlation with the total regional economic output. The growth rate of total factor productivity in sportswear manufacturing industry was the largest in Guangdong, with an average increase of 17.4%. The largest decline was in Anhui, with an average decrease of 8.3%. The former's GDP and per capita GDP were 3.3 times and 1.8 times that of the latter respectively. . The total GDP of the seven provinces and autonomous regions where the growth rate of total factor productivity in the sports equipment manufacturing industry is 1.4 times that of the seven provinces and districts showing a declining trend, and the per capita GDP is basically the same. The latter is only 228 yuan more than the former. Table 2 2004 2011 Sports Product Manufacturing Area Total Factor Productivity Change and Breakdown Mean Mean Value Region Technical Efficiency Change Technology Change Pure Efficiency Change Scale Efficiency Change Total Factor Productivity Change (DF FPch) Safety Beijing Fujian Guangdong Hebei Hunan Jiangsu Jiangxi Liaoning Shandong Shandong Shanxi The analysis of the factors affecting the change of total factor productivity in the sportswear manufacturing industry in Shanghai Tianjin, Zhejiang, and the average 3 will be determined by the changes of pure efficiency (PEch), scale efficiency change (SEch), and technological change (TEC Hch). 14 Therefore, the source of power for changes in total factor productivity lies in the efficiency of resource allocation, scale efficiency, and technological progress. Factors related to these three sources of power will all affect the change in total factor productivity, but the final result will depend on the synthesis of multiple factors. effect. As the current development of China's sporting goods manufacturing industry has major problems in terms of technology, scale, talent, and demand, the level of technology has lagged behind that of developed countries. Leading companies cannot compete with transnational giants due to their small size, and the overall quality of the labor force is low and outstanding. Shortage of talent, shortage of international market demand and lack of domestic demand overlap. Therefore, this article focuses on prominent issues in the manufacturing of sporting goods, focusing on the discussion of variables such as invention patents, company size, human capital, and consumer expenditures on total factor productivity of sporting goods manufacturing. Impact. Among them, the amount of invention patent grants affects the manufacturing of sporting goods mainly by affecting the efficiency of technological innovation and technological advancement; the scale of the company affects total factor productivity mainly through affecting the scale efficiency and technological innovation of the production process, and it is expected to have a positive influence; human capital is mainly It is expected that there will be a positive impact by reducing the number of simple labor inputs and promoting the development and application of new technologies and affecting total factor productivity. The Xiao Fei expenditure reflects market demand conditions, mainly affecting the total factor productivity by affecting the efficiency of resource allocation. It is expected that there will be a positive trend. influences. Since the current growth rate of total factor productivity will be affected by the inertia of previous growth rates, we introduce the first-order lagged variable of the dependent variable and establish the following dynamic panel model to examine the amount of invention patent grants (FMZL) and firm size (QYGM). The impact of human capital (RLZB) and consumer expenditure (XFZC) on changes in total factor productivity: Among them, å©, 7 are the underestimate coefficients, and 9 are intercepts, which are random perturbation terms. Because the model contains the first-order lag variable of the dependent variable, this paper selects the System-GMM estimation method in stata12.0 statistical software for regression analysis. The estimated results are summarized in Table 3. Excessive use of Sargan statistics. Recognition Constraints Test, chi2(19)=11.04047, Prob>chi2=0.9225, can not reject the original hypothesis, indicating that the model is set correctly; residual item sequence correlation test using AR(2) statistics difference, AR(2) =1.5143, Prob>Z=0.1300. The original hypothesis cannot be rejected. It means that there is no autocorrelation problem. The coefficient estimate is valid and can be used to explain the economic meaning between variables. From Table 3, the amount of invention patent grants has a significant negative impact on the total factor productivity of the sporting goods manufacturing industry, with a factor of one. 7097128, this is the opposite of theoretical expectations. Under normal circumstances, the amount of invention patent grants reflects the basic level of scientific and technological innovation in a region and is an important condition for promoting technological progress. It should be able to positively promote the growth of total factor productivity driven mainly by technological progress. The main reason for the contrary between the measurement results and theoretical expectations may be that, on the one hand, the overall technical content of China's sportswear manufacturing industry is not high, and the labor-intensive characteristics of the entire industry are more obvious, relying mainly on factor input and labor cost advantages to drive scale expansion. The demand for scientific and technological innovation is relatively weak; at the same time, most of the sporting goods manufacturing enterprises in China are locked in the production and processing links in the entire industry chain, and more are engaged in order production. Creative design and production technologies are mainly derived from external commissioning or introduction. The reflection of the supply of regional technological elements is not sensitive. On the other hand, China's regional innovation system is still not perfect, and the mechanism for transforming scientific and technological achievements lags behind. A large number of invention patents cannot be truly translated into actual productivity. It is difficult for sports products manufacturing industry to obtain sufficient technical support directly from the scientific and technological innovation achievements in the region. The scale of the enterprise has a significant positive impact on the total factor productivity of the sporting goods manufacturing industry, with a coefficient of effect of 0.1084409. This indicates that the larger the average asset size of the enterprise, the more favorable it is to increase total factor productivity. This is in concert with Zhao Dan, Le Le and Han Peng (2008). Lei and Wang Kai (2012) have the same conclusions. The probable reason is that, as the driving force of total factor productivity growth in sporting goods manufacturing mainly comes from technological progress, efficiency changes have played a restrictive role. According to the view of big companies represented by Schumpeterism, the larger the company's scale, the stronger it will be. Willingness and ability to promote technological innovation, therefore, the advantages of large enterprises in technological innovation can better compensate for the loss of efficiency caused by rising bureaucracy and management communication costs, and can obtain higher total factor productivity growth rate. In addition, people pay much attention to the brand image when they consume sports goods. Enterprises with well-known brands can rely on brand marketing and intangible asset management to obtain more development opportunities and higher profit levels. Usually, the scale of the company is the strong backing force of the brand's competitiveness. Therefore, large enterprises can often rely on intangible factor inputs to obtain more returns. Obviously, this income from intangible factor input is one of the sources of total factor productivity growth. The human capital represented by the average level of education has a significant positive effect on the total factor productivity of sporting goods manufacturing industry. The coefficient of action is 5.718866, which indicates that the higher the level of regional human capital is, the more favorable it is to increase total factor productivity. This is in line with theoretical expectations. Consistent with the research findings of Xia Liangke (2010). The possible reason is that, on the one hand, a higher level of human capital means a higher quality of laborers and a higher productivity of labor. In addition, China’s sporting goods manufacturing industry still belongs to a labor-intensive industry and the level of human capital increases. It will reduce the input of general labor factors and promote the improvement of total factor productivity from the perspective of labor supply. On the other hand, sports consumption that is closely related to sporting goods is a high-level spiritual demand, and the higher the degree of education, the greater the number of sports consumption. And the higher the level, the higher the level of sports consumption will derive a higher level of demand for sporting goods, which in turn motivates companies to strengthen technological innovation, improve production efficiency, and improve product quality, thereby stimulating the dynamics of demand from the demand level. Increased productivity. Cultural, educational and entertainment expenditure has a significant positive effect on the total factor productivity of sporting goods manufacturing industry. The coefficient of action is 1.25847, which indicates that the improvement of market demand conditions will contribute to the improvement of total factor productivity. This is in contrast to Chen Fenglong and Xu Kangning (2012) “Land market. The scale is positively related to total factor productivity." The possible reason is that, on the one hand, the increase in residents-related consumer spending will increase the demand for sporting goods, so that companies have better conditions to expand the scale of production, resulting in the improvement of scale efficiency, while the scale efficiency is lagging behind the sporting goods manufacturing industry. The biggest bottleneck in the growth of total factor productivity; on the other hand, currency votes in the hands of residents are the development indicators of the industry. The increase in the amount of cultural, educational, and entertainment consumer spending and structural changes will promote the optimal allocation of resources in the sporting goods manufacturing industry, resulting in pure efficiency improvements. Under the background that technological efficiency changes have a significant negative effect on the growth of total factor productivity in sporting goods manufacturing, the scale efficiency and pure efficiency improvement caused by the increase in cultural and educational entertainment consumption expenditure are of special significance. In addition, a significant proportion of cultural, educational, and entertainment consumer spending falls into the category of human capital investment. The increase in the scale of expenditure can increase the total factor productivity of sports equipment manufacturing through the intermediary role of human capital. Note: *, * are significant at the statistical levels of 10%, 5%, and 1%, respectively. 4 Conclusions and Policy Recommendations Based on the panel data of 14 provinces and autonomous regions in the year of 2011, the Malmquist Productivity Index method was used to measure the total factor productivity and decomposition indicators of China's sportswear manufacturing industry. The results showed that the total factor productivity of China's sporting goods manufacturing industry. In general, it showed a growth trend with an average annual increase of 3.1%. The main driving force for growth came from technological progress, and technical efficiency, especially scale efficiency, had a restrictive effect. In the trend of changes in total factor productivity of sporting goods manufacturing, the calculation results in this paper are consistent with those of Chen Po (2014) and the main drivers of changes in the rate of Zhang Hongwei and Li Xuedong (2012). This article judges Zhang Hongwei and Li Xuedong (2012). ) The conclusions are basically the same. This paper analyzes the main influencing factors of total factor productivity in China's sportswear manufacturing industry based on the dynamic panel model. The results show that the amount of invention patent grants has a significant negative impact on the growth of total factor productivity, while the enterprise scale, human capital, and per capita cultural and educational entertainment consumption expenditure. There is a significant positive effect. Based on the above research conclusions, this paper proposes the following policy recommendations for improving the total factor productivity of China's sporting goods manufacturing industry: First, improve the regional innovation system, increase investment in R&D, increase the enthusiasm for enterprises to carry out independent innovation in science and technology, accelerate the conversion of scientific and technological achievements, and improve effective inventions. The proportion of patents strengthens the support of local technological innovation achievements in sports product manufacturing; see the stage, China's sports goods manufacturing industry should pay particular attention to the introduction of technological achievements to digest and re-innovation, and strive to overcome key technical difficulties in some industries. The gap in world-class technology level has increased the contribution rate of technological progress to the development of sports product manufacturing. The second is to speed up the cultivation of sporting goods industry clusters in some areas where conditions permit. On the one hand, relying on the advantages of clusters to expand industrial scale and average enterprise size, continue to rely on scale efficiency improvement to drive total factor productivity growth; on the other hand, give full play to industrial clusters The advantages of innovation and incubation have overcome the innovation inertia and path dependence effects of sports equipment manufacturing, improved the efficiency of resource allocation, and opened up new power sources for total factor productivity growth. Third, taking a new round of comprehensively deepening reforms as an opportunity to clear the system barriers to corporate mergers and acquisitions, encouraging enterprises to carry out scale operations, relying on market mechanisms to strengthen resource integration, and fostering a group of local leading enterprises with international competitive advantages. At the same time, local leading enterprises are encouraged to strengthen brand marketing, continue to extend the industrial chain, support new types of sports products, strengthen the integration of sports equipment manufacturing and service industries, continuously innovate business models, and open up new profit growth points for sporting goods companies. 23 Fourth, increase human capital investment, develop a comprehensive education system, improve the efficiency of regional education resources allocation, and improve the overall human capital quality of the region; meanwhile, strengthen the cultivation and introduction of high-end talents, and gradually break the household registration and social security system against outstanding talents. Restricting the flow, creating a regional gathering of talent resources, and improving the talent support for the transformation and upgrading of the manufacturing of sports products. Fifth, improve the residents’ social security system, reduce residents’ worries about education, medical care, housing, and pensions, reduce marginal saving tendencies, and expand consumer spending. At the same time, advocate the concept of scientific consumption and guide the consumption of consumer spending to human capital consumption. Improving the market demand conditions for sporting goods manufacturing. (turned to page 105) Li Hong, He Lei. The Role of Early Childhood Movement Development in Cognitive Development. Advances in Psychological Science, 2003, 11(3):315-320. Gagne. Learning conditions and teaching theory. Shanghai: Qin Anlan published by East China Normal University. The theory of embodied cognition and its enlightenment to early childhood education. Education Wang Zejun, Ji Liu, Hao Yu. The Influence of Exercise on Cognitive Ability and Its Neurobiological Mechanism Chinese Journal of Sports Medicine, 2011, 11:1039-40. Pan Chunyan. The effect of basic athletic ability training on the intellectual development of children with intellectual disabilities...... Journal of Shanghai University of Sport, 2006, 4:54-57. Wei Mengtian, Wei Shengmin. Discussion on Physical Activities of Middle and Primary School Students and Improving Learning Efficiency . Journal of Hengshui Teachers College, 2003, 5(3): 84-86. Chen Yuguo, Yin Hengshen, Yan Jun. Let Children Win in Physical Education: Enlightenment from Brain Scientific Research to Sports. Global Education Outlook, 2013, (continued from page 72)
Study on the Changes of Total Factor Productivity and Its Influencing Factors in Sports Manufacturing Industry in China
Research on Changes of Total Factor Productivity and Its Influencing Factors in Sports Manufacturing Industry in China Date:2015-11-07 14:38