Difference Of The Consumer Purchase Decision-making Influence Factors Research

With rapid growth of housing market over past 10 years in urban China, especially in Hangzhou city, urban residents have become more rational in making house purchasing decision, which deserve a more professional and more quality-mind market. The influence of housing consumers on housing market having become stronger, it is an important and practical problem to understand and analyze factors influencing the purchasing decisions of urban house buyers, which would help the housing developers to provide housing products and survive in dog-eat-dog market. Housing market can be subdivided by studying house-purchasing influencing factors, which classified and compared in the level of consumers' characteristic.Based on the data from a special designed survey in Hangzhou city, there are two major purpose of this paper, one is to construct a house-purchasing influencing factors system from overall level and the other is to empirically analyze location choice in house-purchasing decisions. Factor Analysis, paired t test, independent t tests, Logit model, etc. are used to analyze the research questions in the study.There are seven influencing factors, which can be sorted into four groups by the extent of importance. The first group is housing price factor. The second is residential environment factor, construction characteristic factor and income of family. And the last group is housing location factor and the situation of housing market. The empirical results demonstrate that those factors extracted from initial factors have significant difference on individual demographic characteristic such as sex, marital status, age, family income and education, which can be used to subdivide the housing market. Advice on marketing has been presented. In addition, the research uses Logit model to analyze the influencing factors on housing location choice.Factors such as careers, family income, traffic status, increment potential and natural environment have significant influence on location choice decision.These empirical findings have important implications for policy-makers and developers. There is some improvement for further research such as increasing the quantity of samples, optimizing the proportion of different kinds of samples and perfecting the variable and statistic methods.