Comprehensive analysis is made about the factors that affect the Real Estate price. Main factors are summarized such as supply and demand, economy, cost, administration, society, environment and others. Because it is difficult to quantify the influence of social, administrative and other factors, factors such as supply and demand, economy, cost, environment are considered as main target of our study. Based on the data between 2000~2004 in Shenzhen, Grey incidence analysis is made about the main factors influencing the Real Estate price, which are given as results: The construction level of municipal infrastructure, consumption level per capita and cost of housing are principal factors that influence of the Real Estate price in Shenzhen, secondly land price, income level per capita, population size and dwelling level per capita, etc. again speed of economic development, price level and supply level of housing, etc.

All over the world, government intervention in housing market is a routine to maintain economic sustainable development and improve housing conditions, even in market economic countries. Housing policy, as an exogenous variable, will have many effects on housing market. So, we should analyze the effects dynamic of housing policies on housing market to insure accomplishment of housing policy’s prospective purposes. Housing policy includes housing supply policy and housing demand policy. The effects primarily involve efficiency, fairness, market effect and externality. The principal theme of this paper is market effects of housing policy. We find land supply constraint will tend to increase housing price and decline the housing affordability. And the government regulation and rental control will decrease the affordable housing stock for low-income households by market filtering up. Housing subsides on low-income households will give an incentive for developers to build the low-end housing in longer run. Finally, some suggestions are provided for housing policymakers.

Real estate industry as the third industry of national economy, it plays the important role strengthening service management, decreasing the possibility of service failure and making the service recovery work better. It can guarantee the continuity of real estate industry offering service, circulation of the supply and demand chain and stability of profit chain. On the basis of qualitative analysis of the service recovery system (SRS), the study takes Chinese real estate industry as the design object, analyzes the affecting service failure factors from the customer view, realizes the anticipative aim according to the input-output principle and designs the SRS in term of the time series. Through the questionnaire of real estate enterprise executing the SRS, the results show that the solved problem ratio is increasing and time space shorten. And the different culture background of different enterprise, the attitude of enterprise employee and whether taking the immediate measures are the subjective and uncertain factors. These are the main factors affecting the overall system execution.

Building energy efficiency (BEE) economic incentive system is an enormous system of multi-agent, which includes government departments, design institutes, construction units, real estate development enterprises, purchasers and energy service companies etc. It has a widely internal relationship and a character of multi-layer, multi-function, dynamic, open and mutually learning, so it is conformed that this system has the basic character of complex system. As a rational method to solve the problem of complex system, Cellular Automata (CA) can analyze the grid dynamic model which is not only discrete in temporal and spatial aspects but also partial in temporal consequence and spatial mutual relationship. Under some certain simple units and regulations, CA can simulate the complex system veritably. With the bottom-up modeling method of CA, this study establishes an evolutionary model of multi-agent for BEE economic incentive system in China through analyzing the complex character of this system. Based on the analytic result of evolving processes, it is recognized that the influence factors of promoting BEE economic incentive policy involves behavior preference, macro environment factors and different actual conditions of local regions.

The purpose of the public investment is to serve society and improve people’s living standard, so the social and environmental benefits became the highest standard weighing public investment benefit and a basic starting point of evaluation the public investment project. In this paper, fuzzy mathematics theory was adopted for the comprehensive evaluation on the social, environmental and economic benefits of Land Fund expenditure in Shenzhen，and the process of comprehensive evaluation was improved in order to evaluate the benefits of public investment more efficiently. The calculation result indicated: the proportion change of direct benefit to indirect benefit has negligible effect on total evaluation result; weight and evaluation grade of the social benefit are the highest in 3 types of benefits, the result accords with the tenet of the social benefit that local public investment pursues; weight and evaluation grade of municipal engineering are the highest, accessory facilities—the lowest, the result indicates that the accessory facilities construction of Shenzhen is in the relatively backward.