Supply And Demand Analysis Of City Public Facilities In Hefei Based On Heterogeneous Demand

Since the reform and opening up, China has experienced a massive population movements, resulting in the big public facilities supplying pressure in big cities. The pressure is not only at the total level, but also at the structural level. Urban space data shows that China’s urban public facilities have a strong agglomeration trend in city centers, in a way causing the "spatial mismatch" phenomenon, namely the mismatch of supply and demand. "Spatial mismatch" will not only bring additional commuting, reducing the efficiency of the city, it will also put pressure on housing prices of high-quality region due to the presence of sorting effect, which means the same type of individuals tend to gather together, resulting more severe residential segregation and social differentiation problems. In this context, the measurement and evaluation of supply and demand structure of city public facilities are important basis to avoid "mismatch" on the allocation of public resources.Current academic studies on the supply and demand structure have been carried out. On the supply side, the calculation method based on accessibility is more refined; On the demand side, according to some studies, heterogeneous demand has been gradually emphasized; At the side of matching supply and demand, however, the consideration of demand is limited on the total indexes like population density or the ratio of groups, lacking the measurement of demand heterogeneity. Thus, this paper studies Hefei case, discussing the evaluation methods of supply and demand matching, designing to incorporate demand heterogeneity into the existing evaluation system.Firstly, based on spatial data, paper measures the supply of public facilities of different locations in Hefei using methods of potential accessibility model and buffer analysis. The results shows that there is a common trend of agglomeration for five facilities (entertainment, sports, health, education and shopping), and the agglomeration degree is highest in medical facilities while lowest in recreational facilities; Then, paper carries out measurements of demand, on the one hand, based on price data, paper uses hedonic pricing method to analyze residents’ preferences for different facilities. Results shows that ratio of residents’willingness-to-pay for five facilities are 18:5:29:41:-15, wherein the negative sign indicates that the facility increases, residents’willingness-to-pay decreases; On the other hand, based on survey data, paper uses discrete choice models (Multinomial Logit model and Ordered Logit model) to analyze residents’different preferences for behavior of using facilities (transportation, frequency), the results show that residents of different ages, gender, income and education level have significant differences in transportation choices, and residents of different gender, age, income, education, household type, household place, with or without young children and retired parents have significant differences in frequency of using facilities.On the basis of different geographical supply and different residential groups, paper launches the match of supply and demand, constructing transportation index TI and frequency index FI, wherein, TI reflects the difference of actual accessibility based on different travel mode; FI reflects the difference of actual demand based on difference of frequency. Using original matching index to multiple TI and divide FI, then we get the adjusted index. Results of individual facility shows that the level of match degree is higher in center districts and southwest region. Comparing different types of facilities, the degree of spatial variations are the highest in education facilities and the lowest in medical facilities. Results of comprehensive index show that the level of match degree is highest in ShuShan district, which locates in the southwest of Hefei, meanwhile, the level of center districts is higher than suburban districts.Differences in residents’behavior not only reflects their accessibility towards facilities, but also reflect their actual needs of specific facility. Thus, based on the heterogeneity of preferences to adjust the relationship between supply and demand has a strong practical significance. This paper attempts to expand original index by considering residents’ heterogeneous preferences, measuring the relationship between supply and demand more accurately and providing evaluation and decision support for facility provision.