With the rapid growth of Chinas real estate industry, the consumer behavior in housing market has become one of the issues with greatest concern to developers and the local government. Because of the problem of data, researches on housing choice behavior from the micro level are limited. In this paper, the author built the Logit model about housing choice of urban resident in Hangzhou, selected three main categories of family characteristics, house characteristics and psychological factors, and with division of the housing location in two ways: concentric urban districts and administrative division. The results show that residential location choice decision is largely affected by most of family characteristics, house characteristics and psychological factors. The administrative division of location has more practical significance than concentric urban districts division. The studys conclusion can provide advices for the government, enterprises, as well as residents making decisions.

Box-Cox transformation allows functional forms more flexible. On the basis of the principle of model optimization, an empirical study is made for housing market of Hangzhou City. By collecting 2417 housing data in Hangzhou City, a housing hedonic price model with Box-Cox transformations is set up with 18 factors as housing characteristics. The model is estimated after the grid-search procedure by using MATLAB and SPSS software, and the statistical test shows that the logarithmic function is the optimal form. The model comparisons in the fitness and forecasting performance indicate that the logarithmic model is superior to other three models of the linear, semi-logarithmic and inverse semi-logarithmic. Empirical analysis suggests that the Box-Cox transformation is valid and feasible in choosing functional forms, can be used to optimize hedonic price models.