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Regarding the fact that there are significant differences in the developing process of China's regional construction industry, on the basis of the existing research results, we combine the DEA-DA model and PLS structural model to make the empirical research on the spatial differences in Chinese construction industry competitiveness formation mechanism. We find that regional economic development and factors of production greatly contribute to the upgrading of competitiveness, but their impact is a sort of differences; building auxiliary industries, innovation status and industrial organization also have different mechanisms to enhance construction industry competitiveness in different regions; there are different relationships between effectiveness and efficiency in different regions. We realize the innovation both in theory and method as to the industry competitiveness under the spatial dimension; and lay the foundations for further study on the regulation of the joint development of Chinese construction industry competitiveness. [ABSTRACT FROM AUTHOR]

In order to improve the objectivity of selecting input, output indicators and determining their weights, based on systematic review of the development of DEA model, SEM constraint cone and a DEA model bound with SEM restraint cone were introduced in this paper, which also contributed to solve problems such as existence of hidden variables in the input and output indicators and measures of correlation or causal relation among indicators. The DEA model first used SEM to analyze independent and dependent variables, determining weights of each indicator. Then the selecting of weights in DEA model was restricted by means of SEM. In the end, an empirical research on the validity of construction industry competitiveness of Chinese provinces was done by using this model, and the results show that the model reduces the deviation between the analytical results and the actual situation, while improving the accuracy of the analysis. [ABSTRACT FROM AUTHOR]

It screens the input and output indicators of the total factor productivity of Chinese regional construction industry with the method of added value. On this basis, it uses the super-efficiency DEA method to analyze the Malmquist productivity index of construction industry in 31 Chinese provinces from 2006 to 2009. Finally, it identifies the key factors affecting the productivity of China's construction industry, with the method of analysis of variance. With the effective combination of the above three methods, we successfully achieve the objective study in three aspects, that is, the measurement model for productivity, the selection of indicators and the identification of factors, so as to shape a more scientific structure for studying the change of productivity. It finds that the main reason for the steady increase in total factor productivity is technological progress and the improvement in the scale efficiency is just a kind of short-term behavior which is not the key issue. And one key issue to be solved is the improvement of pure technology efficiency. Three indicators, "science and technology investment", "human capital of construction industry", "economy level", exert a great influence on the improvement of the productivity of Chinese regional construction industry. [ABSTRACT FROM AUTHOR]