Research On The Evaluation Of The Real Estate Development Land Supply Performance

With the reform of Chinese housing system, it has sped up the urbanization of our country. The management of city has become more important and land resource is an important asset. In recent years, about 300 acres of arable farmland have been occupied due to construction annually, on one hand the reduction of arable land has a serious impact on the output of Chinese grain; on the other hand, our country is still relatively lack of the land for development and construction; From 2006 to 2012, the proportion of the real estate development land remained thirty-three percent around, which is accounted for the construction land supply. the proportion of residential land supply remained only twenty-four percent, which is lower than fifty percent in developed countries. China has currently become the second largest economic entity which is behind the United States in the world, and the land supply structure which is coincident with the economy needs to be optimized, With our economy becoming new normal and the urbanization developing, the real estate market has changed from the stage of the rapid development to the stage of stable development. In this situation, it is significant and meaningful to explore the evaluation of performance for the real estate land supply from the perspective of land use efficiency.It is not only helpful for adjusting the policy.bur also responsive to fit the requirements which are encouraged to use land intensive in the new situation. The research of this paper is about the efficiency of the real estate development land supply. We need to define the connotation of the urban real estate land use efficiency, analyze and influence factors of urban land use efficiency; according to the clear performance evaluation standards and principles, we should establish the objective evaluation of the performance evaluation system. the establishment of the index system should be based on factors, we need to use statistical methods to screen indicators and select them to determine the weight of the index. We decide the calculations for the class of gray by the Grey Clustering Evaluation Model. Finally, the empirical analysis consider Nanchang as case, we make recommendations which are based on the evaluation results for the housing market of Nanchang.