東京23区内の私立保育所等の立地と定員に与える影響の要因

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  • FACTORS INFLUENCING THE LOCATION AND CAPACITY OF PRIVATE NURSERY SCHOOLS IN THE WARDS OF TOKYO
  • トウキョウ 23 クナイ ノ シリツ ホイクジョ トウ ノ リッチ ト テイイン ニ アタエル エイキョウ ノ ヨウイン

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 1. Purpose<br> More private nursery schools are needed because many children are on waiting lists. Private companies are, however, unlikely to open new schools in places that offer little profit. To boost the availability of nursery services, this paper looks into the factors that influence their locations. Our study region is the wards of Tokyo, where many private companies open nursery schools.<br><br> 2. Methods and Results<br> First, L, which is the standardized function of Ripley's K, is calculated to determine the degree to which nursery school locations are clustered. The L(ts) of private nursery schools is greater than that of public nursery schools (Fig. 1). This means that private nursery schools cluster more closely than public nursery schools. The L(ts) of private nursery schools has its maximum when ts equals 800 m; therefore, private nursery schools tend to cluster within 800 m.<br> Second, kernel density estimation gives both the density of school locations and the density weighted by their capacities. The standard deviation of the normal distribution is set to 800 m from the L function result. The reference grid is generated at 15 m intervals. The densities are high around railway stations (Figs 3 and 4).<br> Third, we use multiple regression analysis in which the dependent variable is the density or weighted density. The R2 is 0.632 and 0.577 when the dependent variable is the density and the weighted density, respectively. The F-test rejects the null hypothesis at the 0.001 significance level.<br> The number of households is the most effective independent variable for explaining variations in density. The densities are positively influenced by the number of households and employees, and negatively influenced by the distance between private nursery schools and the nearest railway station. Private companies tend to open nursery schools in places that have many households and employees. The densities are high in the vicinity of railway stations, which is useful for leaving children in nursery schools.<br> A nursery school close to a park can be approved, even if it lacks a playground. Multiple regression analysis also shows that the distance between private nursery schools and the nearest park has a negative influence on the densities.<br> The law and the ordinance oblige a nursery school to have floor space according to its capacity. Multiple regression analysis also shows that land price has a negative influence on the densities. High land price lowers the densities.<br> Zoning districts also significantly influence the densities. Private companies are especially reluctant to open nursery schools in industrial district in which the heavy traffic of industrial cars disturbs children's safety. Some residents in a quiet residential area feel children's voices to be noisy, and object to opening nursery schools. Multiple regression analysis also shows that the density weighted by capacities is negatively influenced by the category 1 low-rise exclusive residential district.<br><br> 3. Conclusion<br> The locations of private nursery schools are unevenly distributed. They are influenced by the number of households, the number of employees, proximity to railway stations, nearness to parks, land prices and zoning districts. Consideration of these factors is required in addressing regional demand for nursery services.

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