Studies in Housing and Urban Analysis in Japan

Vacant houses are currently being promoted for use in the resale housing market, and the purchase of resale houses has become an important option in society. This chapter investigates the demand–supply relationship in the resale housing market on the outskirts of the Tokyo metropolitan area. Focusing on the two established market-clearing factors: “price” and “time required to sell a property,” we investigated the manner in which potentially disadvantageous properties–in terms of building and locational characteristics–are sold in the market. In suburbs less than 30 km from central Tokyo, we show that such properties tend to be sold quickly or fetch high prices, suggesting a strong demand for resale houses for young households. In addition, in the outer suburbs (40 km or farther away from central Tokyo), potentially disadvantageous properties required longer time to sell or fetch low prices. Moreover, certain owners were found attempting to dispose their properties quickly at a low price, suggesting that they consider it costly to maintain their unnecessary properties.

Condominiums are important housing stock in Japan, but they often need to be rebuilt. This research investigates the factors and spatial distribution of condominium rebuilding. To this end, data on rebuilt condominiums was integrated with data on old condominiums defined as the ones with old earthquake resistance standards. Using a probit model, the tendency of certain factors to contribute to rebuilding was assessed. Findings reveal that building age, land area, distance to the city center, number of housing units, and floor area possible for expansion are statistically significant, which is consistent with the findings of previous studies on the qualitative analysis of condominium rebuilding in Japan. When the marginal effects of the factors were calculated, a four-year increase in the average building age, for instance, increases the probability of rebuilding by 1.49 percentage point. We also confirmed that condominiums with high rebuild probability are concentrated in the western part of central Tokyo and are also likely to exist in suburban areas.

Japan’s conventional city planning is based on the assumption that population growth and urbanization will continue in the future. However, it is extremely likely that the population growth assumption will no longer hold in the future, so the city planning system is at a critical juncture. Notably, the development of compact cities maintains the quality of life in cities and administrative service efficiency even in the era of population decline. In order to make a city more compact through effective planning, municipalities should formulate policies encouraging relocation, such as developing urban areas with attractive living environments and the introduction of subsidies for relocation-associated expenses. Hence, a quantitative and objective index to assess the living environment of each area from the perspective of whether it corresponds to residents’ preferences is needed.

The living environment score (LES) focuses on various living environment indices and takes into account the magnitude of the influence of these indices on residence selection in order to assess the overall attractiveness of an area as a residence. We analyzed population increases from 2000 to 2010 in the Tokyo metropolitan area and attempted to calculate the LES at both the census grid and local district levels. The results showed that there was a significant expected population increase tendency in regions with a high LES. However, the accuracy rate was around 60%, and further improvements are needed in order to use this as a basis for decision-making.

Indices related to disaster safety have not been considered in the LES. Thus, when we verified the relationship between population-increase tendencies or the LES with disaster risk, it was suggested that population increases might continue in regions with flood risk or risks associated with dense urban areas. Disaster risk is something that people seek to minimize, and this should be considered as a property that is different from other living environment indices that should be pursued to an appropriate level. For the future work, it is imperative to improve the LES calculation method so that disaster risk can be reduced while improving accuracy.

Previous studies have suggested that the closer older adults live to urban facilities, the more likely they are to participate in recreational group activities. However, close proximity can also have a negative effect on participation. This study aimed to investigate the relationship between changes in the density of neighborhood facilities and changes in the participation of older Japanese adults. The data used in this study consisted of two waves of the Japan Gerontological Evaluation Study (JAGES) survey. The survey participants were not eligible for long-term public nursing care. The facilities were categorized as (1) leisure facilities; (2) cafés, pubs, and restaurants; (3) medical and welfare facilities; and (4) food stores. A multilevel ordered logistic model was used for the analysis. The results of this study indicate that several types of neighborhood facilities are associated with increased participation by older adults. However, light-hearted going out, especially during daily use of food stores, may have some limitations in promoting participation.

The problem of disadvantaged shoppers has become more serious in Japan. People feel difficulties for grocery shopping. Inconvenience of store accessibility is a factor of the difficulties. To address this problem, it is necessary to specify the elements in the concepts. However, few studies have focused on factors other than distance.

Focusing the older adults, this study aims to (1) clarify the characteristics of dissatisfaction with various road environments, (2) clarify what kinds of road environment dissatisfaction affect inconvenience, and (3) to develop decision tree models that estimate people’s dissatisfaction with the objective condition.

A series of analyses were conducted based on data from an online questionnaire survey. First, the results indicated that the degree of tolerance and the amounts of each road elements were related to dissatisfaction. Elderlies tend to avoid several elements. Second, several road element can lead to inconveniences in accessing stores. Additionally, we created decision tree models by combining these data with indicators of objective road conditions. These models provided the threshold values of the objective conditions that significantly changed the subjective evaluation. These results allow us to compare the conditions of regions more efficiently or to identify regions requiring a more detailed survey.

This study aimed to assess the risk of residential burglary by examining factors representing the physical and socio-demographic context of the neighborhoods. Structural equation modeling was employed to establish their relationship. The main findings of this study provide evidence-based insights on crime reduction. Particularly, higher density, a larger family size, and daytime population reduced the risk, potentially enhancing natural surveillance. Conversely, neighborhoods with a high rate of rented houses exhibited a higher risk, while those with a high building coverage ratio demonstrated an increased risk, and those with a high floor area ratio demonstrated low risk. In conclusion, considering community safety as an integral aspect of quality of life, a holistic approach is suggested.

This study explores the relationship between neighborhood socio-economic status (SES) and the crime rate of residential burglaries in the wards of Tokyo, focusing on the spatial heterogeneity of this relationship and the moderating role of SES on the relationship between crime rate and the built environment. The results are as follows: (1) While global model shows that the proportion of high-income neighbors is negatively and significantly associated with the neighborhood residential burglary rate, the local model, calibrated by geographically weighed regression estimation, indicates that there are local variations in this relationship. (2) Significant interactions between neighborhood income composition and physical indicators such as road area ratio and distance to the nearest rail station suggest that the links between the residential burglary rate and the built environment are conditioned by neighborhood SES.

This study identifies the factors affecting the installation of residential solar photovoltaics (PVs) in housing estates in Kakegawa City, Shizuoka Prefecture. Logistic regression analysis of 1327 houses in housing estates revealed that those that were lower, fully rebuilts, newly builts, or larger as well as newly built were more likely to have PV installed. Furthermore, analysis of 1971 houses revealed that—compared to houses in adjacent blocks—those that were without building agreements, lower, fully rebuilt, newly built, or smaller as well as newly built were more likely to have PV installed. Accordingly, full rebuilds, new builds, building heights (measured in meters), and property areas (measured in square meters) were suggested as factors affecting PV installation.

Understanding the structure of cities and facilities in terms of similarity and proximity when considering wide-area or national land planning is crucial. For this purpose, this chapter proposed a novel method to visualize the similarities or various distances of regions, referred to as Bayesian geographical multi-dimensional scaling. Multi-dimensional scaling (MDS) is the fundamental method that is generally used for this purpose; however, its projections are often substantially different from the geographical locations to facilitate appropriate comparison or understanding. Thus, to overcome this weakness, we introduced a geographical penalty for MDS, and its weight was determined using a statistical criterion. This penalty was introduced because dissimilarities or distances should be small if the two regions are geographically close in many cases. Furthermore, this method was applied to visualize the accessibility of public transit in Japan. The obtained results can be easily compared with geographical locations and facilitate an understanding of the transitions that improve accessibility in each prefecture.

In the central commercial zones of Tokyo, the importance of city-block restructuring has been strongly emphasized. The predictability of the building development in city blocks is crucial for their planning. This study classifies city blocks by the difference in influential factors of the building location and examines if the city blocks have steady tendencies of building locations. Furthermore, the probability of building coverage for each point in a block is visualized to grasp the spatial image. For our analysis, we used 205 city blocks as reference blocks. Results show influential factors of building location, such as the presence of a wide road and its adjacent direction, the north-south length of city blocks, and the same use of buildings. Further, the study visualizes the probability that each point covered by buildings in a given block and judged for classes has a steady tendency of building location.

The hedonic pricing method is an effective technique for estimating land and building prices. Nonetheless, numerous analysts have expressed concerns regarding the potential for multicollinearity to inflate the variance of the estimated coefficients. Hedonic pricing often involves spatially situated objects, and so strong correlations between two or more variables frequently arise. There are several diagnostics for evaluating multicollinearity, although most—sourced from explanatory variables—only measure the severity of this condition. To assess the risk of multicollinearity in a comprehensive manner, it is imperative to develop diagnostics that consider both the probability of occurrence and the severity of multicollinearity. This paper presents a numerical method for evaluating the influence of multicollinearity from these two perspectives.

A theoretical investigation into the relationships between building setback, plot frontage, and plot depth in terms of building density (number of buildings per unit area) and road-network density (total length of road networks per unit area) is sparsely documented. Hence, in this study, we constructed a mathematical model to analyze the above relationship and maximize the average plot frontage. We found that (1) the average plot frontage is inversely proportional to the gross building density and is a convex upward quadratic function of the road-network density; (2) the average plot depth and setback allowance do not depend on the building density and are a monotonically decreasing function of the road-network density; and (3) the ratio of average plot depth to frontage is proportional to the gross building density and is a monotonically decreasing function of the road-network density. Based on the above findings, we developed a criterion for determining whether the average plot frontage is longer than the average plot depth. Further, the model was validated via an empirical analysis of the Tokyo metropolitan region. The results revealed that the modes of the average plot frontage, average plot depth, and ratio of plot depth to frontage were 11 m, 16 m, and 1.4, respectively. The mode of setback allowance was 5 m. The ratio of building setback to the setback allowance was in the range 0.4–0.6, which indicated that typically approximately half of the allowance is assigned to building setback. The findings of this study will provide urban planners and practitioners with a firm theoretical foundation for understanding the relationship between building setbacks, plot shape, building density, and road-network density in the district scale.

Urban commercial facilities significantly influence neighborhood residents, with changes like store closures disrupting their routines. Especially for the elderly, proximity to these facilities is crucial. Although introducing well-known brands can rejuvenate areas, they might also lead to overcrowding, potentially diminishing the quality of life for locals. It is imperative in urban planning to understand these dynamics and their implications. This chapter delves into the formation of commercial clusters in urban zones and introduces techniques for analyzing and visualizing these trends. Utilizing data from Shibuya Ward, Tokyo, the study demonstrates the efficacy of these methods. The analysis focuses on the expansion direction of commercial clusters using spatiotemporal point data. By tracking when each store opened, the research identifies how new establishments influence the growth trajectory of existing commercial conglomerates. Using a circular statistical method, the study visualizes the expansion of commercial clusters.

The increasing popularity of ride-sharing services, car sharing, and other transportation options has led to a growing diversification of local public transportation services for short-distance travel. In this study, we aimed to understand how an appropriate public transportation system evolves based on density and travel impedance of passengers using an analytical model. Initially, we developed a model representing five typical transportation systems, each characterized by the presence of fixed routes and varying requirements for access and egress time. Subsequently, we analyzed the influence on expenses that satisfy the service level condition, focusing on the effect of demand density and travel distance. Furthermore, we investigated the current status of the introduction of local transportation in eastern Japan and compared the results with the calculation results of the model. Notably, we observed that increasing the number of buses and demand-responsive transit (DRT) operated by the local government led to enhanced effectiveness of car sharing, particularly in areas where DRT services were introduced.