This paper develops logsum-type space-time accessibility measures that consider two-stage decision making and discusses the plausibility of the measures. First, we formulate the accessibility measures, employing a nested logit modeling framework. Then, we investigate the plausibility of our proposed measures through a case study. Specifically, we use the proposed measures to analyze university students' space-time accessibility to shopping opportunities. Based on the results of the case study, we argue that the space-time accessibility measures proposed in this paper can adequately gauge the degree of individuals' space-time accessibility.
This paper argues that the R language and its packages are effective tools for spatial accessibility analysis. To support the argument, it then provides the case study that exploits the functionality of R and analyzes the spatial accessibility to medical clinics. In the case study, we first demonstrate that we can calculate the values of accessibility measures very effectively, using R's matrix function. We also demonstrate that the spatial distribution of the calculated values can be visualized only by some R coding. We further demonstrate that R and some packages enable us to determine whether the inequality of the accessibility to clinics is significant and to detect the ‘cool spots’ of the accessibility, in a reasonable manner. We conclude the paper with suggestions for future work.
Using data from social survey of residents, the present study examined whether some living environments which included commuting routines as well as risk perception and other factors affected fear of crime using hierarchical multiple regression. The main results were summarized as follows. Risk perception affected fear of crime. Incivility and commuting routines as well as female car ownership affected fear of crime, after controlling for the effects of risk perception and other variables on fear of crime. The results implied that outside behaviors including commuting routines explained fear of crime to some extent. Further studies which measure more various types of outside behaviors will be needed for testing the relationship between living environments and fear of crime.
We examine the relationships between spatial patterns of single-mother households and the location and supply of public housing in the Tokyo ward area. Global Moran's I and Local Moran's I statistics using district-level data in 2000, 2005, 2010, and 2015 reveal the spatial clusters of single-mother households as well as their spatial patterns. While spatial clusters are largely located in the northern and eastern regions of the Tokyo ward area, some clusters are found in the central and western regions. The spatial clustering patterns have changed in several areas; between 2010 and 2015, the spatial clusters in Adachi Ward decreased, whereas those in Edogawa Ward increased noticeably. The proportions of single-mother households tend to be high in areas with public housing; however, the correlation between the proportions of single-mother households and the supply of public housing has weakened since 2005.