scholarly journals How Does the Location of Urban Facilities Affect the Forecasted Population Change in the Osaka Metropolitan Fringe Area?

2020 ◽  
Vol 13 (1) ◽  
pp. 110
Author(s):  
Haruka Kato
Keyword(s):  
Network Analysis ◽  
Bayesian Network ◽  
Public Housing ◽  
Causal Relationship ◽  
Population Change ◽  
Residential Areas ◽  
New Town ◽  
Location Optimization ◽  
The Future ◽  
Future Population

This study aims to clarify the statistical causal relationship between the locations of urban facilities and forecasted population changes according to types of residential clusters in the Osaka Metropolitan Fringe areas. This paper’s background is the location optimization plan policy formulated by the Japanese MLIT (Ministry of Land, Infrastructure, Transport, and Tourism) in 2015. The methods combined urban ecological analysis, cohort analysis, and Bayesian network analysis. Using the Bayesian network analysis, the causal relationship between the forecasted population change ratio and the urban facility location was analyzed. The results suggest the location of urban facilities for each residential cluster that will prevent a rapid population decline in the future. Specifically, in the sprawl cluster, this study found that residential areas closer to medical facilities will sustain the future population, while in the old new-town cluster, this study found that residential areas closer to train stations will best sustain the future population. However, in the public housing cluster, residential areas more distant from regional resources will best sustain the future population. Therefore, it is worth considering different urban designs in the old new-town and public housing clusters, rather than the location optimization plan policy.

scholarly journals Bayesian Network Analysis for the Questionnaire Investigation on the Needs at Fuji Shopping Street Town

2018 ◽  
Vol 9 (2) ◽  
pp. 46
Author(s):  
Tsuyoshi Aburai ◽  
Akane Okubo ◽  
Daisuke Suzuki ◽  
Kazuhiro Takeyasu
Keyword(s):  
Sensitivity Analysis ◽  
Network Analysis ◽  
Bayesian Network ◽  
Causal Relationship ◽  
Back Propagation ◽  
The Future

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city (two for Fuji Shopping Street Town and two for Yoshiwara Shopping Street Town). Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. There is a big difference between Fuji Shopping Street Town and Yoshiwara Shopping Street Town. Therefore we focus Fuji Shopping Street Town in this paper. These are analyzed by using Bayesian Network. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. Sensitivity analysis is performed by back propagation method. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.

scholarly journals Bayesian Network Analysis for the Questionnaire Investigation on the Impression at Fuji City

2018 ◽  
Vol 9 (6) ◽  
pp. 1
Author(s):  
Daisuke Suzuki ◽  
Akane Okubo ◽  
Tsuyosi Aburai ◽  
Kazuhiro Takeyasu
Keyword(s):  
Sensitivity Analysis ◽  
Network Analysis ◽  
Bayesian Network ◽  
Causal Relationship ◽  
The Future

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city. Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. In this paper, we mainly focus the impression the visitors feel and analyze them. These are analyzed by using Bayesian Network. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.

scholarly journals Bayesian Network Analysis for the Questionnaire Investigation on the Needs at Yoshiwara Shopping Street in Fuji City

2018 ◽  
Vol 9 (1) ◽  
pp. 211
Author(s):  
Kazuhiro Takeyasu ◽  
Tsuyosi Aburai ◽  
Akane Okubo ◽  
Daisuke Suzuki
Keyword(s):  
Sensitivity Analysis ◽  
Network Analysis ◽  
Bayesian Network ◽  
Causal Relationship ◽  
Back Propagation ◽  
The Future

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city (two for Fuji Shopping Street and two for Yoshiwara Shopping Street). Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. There is a big difference between Fuji Shopping Street and Yoshiwara Shopping Street. Therefore we focus Yoshiwara Shopping Street in this paper. These are analyzed by using Bayesian Network. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. Sensitivity analysis is performed by back propagation method. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.

scholarly journals Demogeographic Analysis To Support the Optimum Realization of the Strategy of Regional Development in the Administrative District of Municipality of Valašské Meziříčí

2016 ◽  
Vol 64 (4) ◽  
pp. 1311-1323
Author(s):  
Vendula Drápelová ◽  
Nahanga Verter ◽  
Dana Hübelová
Keyword(s):  
Regional Development ◽  
Economic Activity ◽  
Regional Differences ◽  
Population Change ◽  
Community Services ◽  
Demographic Development ◽  
Administrative District ◽  
Demographic Indicators ◽  
The Future ◽  
Future Population

Regional development represents the society efforts geared towards reducing regional disparities, optimizing the development and mitigating any social problems. People play a highly significant role that triggers certain demographic development and spatial specifics of demographic indicators, in particular, and regional development, in general. Against this backdrop, this article assesses some demographic indicators in the municipality of Valašské Meziříčí. The results from the statistical analysis of spatial and temporal series show that the administrative district of the municipality of Valašské Meziříčí demonstrated (micro) regional differences and outlined the future population change. The identified adverse effects include: the declining of the population in the administrative headquarters; distinctive dynamics of aging and the low level of economic activity in certain municipalities; underdevelopment of community services; and distribution of the age structure of the disproportion between the peripheral facilities and administrative headquarters. There is an urgent need for policy decisions that could avert the unfavorable development of some demographic indicators (economic and social) in the future.

scholarly journals Exploring the Future Population and Educational Dynamics in the Arctic: 2015 to 2050

2019 ◽  
Vol 53 ◽  
pp. 1-24
Author(s):  
Anastasia Emelyanova
Keyword(s):  
Population Change ◽  
The United States ◽  
The Arctic ◽  
Educational Structure ◽  
Medium Development ◽  
The North ◽  
The Future ◽  
Alternative Scenarios ◽  
Geographical Space ◽  
Future Population

The Arctic is a geographical space surrounding the North Pole. It encompasses dozens of sub-national entities north of eight Arctic countries: Russia, Canada, Denmark, the United States, Iceland, Norway, Sweden, and Finland. It is 20 million square kilometers land coverage settled with only 10 million people (2015). In the desire to learn more about the Arctic overall profile in population change, we aimed at producing cross-regional dataset covering all parts of the Arctic, and using it as a baseline for the cohort- component population projection. In this way, we model the future changes in the age, sex, and educational structure of sub-national populations, the latter reflecting the regional human capital. The projections are based on three alternative scenarios, taking into account regional characteristics (“Medium development”, “Arctic Boost”, and “Arctic Dip”). The results might be informative for those interested in the future dynamics of the Arctic population from 2015 forward to 2050.

scholarly journals Predicting the Future Chinese Population using Shared Socioeconomic Pathways, the Sixth National Population Census, and a PDE Model

2019 ◽  
Vol 11 (13) ◽  
pp. 3686 ◽  
Author(s):  
Guo ◽  
Ding ◽  
Zhong ◽  
Cheng ◽  
Huang
Keyword(s):  
Chinese Population ◽  
Census Data ◽  
Population Change ◽  
Population Census ◽  
Population Development ◽  
Development Environment ◽  
National Population ◽  
The Future ◽  
The Impact ◽  
Future Population

：A precise multi-scenario prediction of future population, based on micro-scale census data and localized interpretation of global scenarios, is significant for understanding long-term demographic changes. However, the data used in previous research need to be further refined. Few studies have focused on predicting the sex ratio at birth, which is vitally important for estimating the future size and structure of the population. It is also important to interpret and set parameters for China's future population development in line with the framework for global shared socioeconomic pathways. This paper, therefore, used the structural population data for provinces, prefectures, and counties from the Sixth National Population Census of China. It comprehensively considered the impact of China’s economic development level, specific population policies, and loss of an only child on key parameters, and localized the population change parameters for different scenarios. A population–development–environment model was used to explain the population change parameters. The population of 340 districts was refined, forecast, and aggregated to the national scale. The results show that the Chinese population is expected to first increase then decrease under the five paths from 2010 to 2050. The aging demographic structure is not reversed under any paths, and the increase or decrease in the urban and rural populations between adjacent node years is closely related to the fertility rate and urbanization speed. We suggest that measures should be taken to encourage childbearing, manage the aging population problem, and reduce the pressure on young and middle-aged people.

scholarly journals Which Residential Clusters of Walkability Affect Future Population from the Perspective of Real Estate Prices in the Osaka Metropolitan Area?

2021 ◽  
Vol 13 (23) ◽  
pp. 13413
Author(s):  
Haruka Kato ◽  
Atsushi Takizawa
Keyword(s):  
Real Estate ◽  
Urban Areas ◽  
Structural Equation ◽  
Population Change ◽  
Equation Modeling ◽  
Walkability Index ◽  
The Future ◽  
Real Estate Prices ◽  
The Impact ◽  
Future Population

In Japan, where the population is declining and aging significantly, walkability has attracted attention as a way to improve residents’ lifestyles. Therefore, it is essential to identify the residential clusters where walkability improvement would contribute to the maintenance of the population in order to select urban areas for the implementation of walkable designs. This study aimed to identify the residential clusters in which walkability affects the future population from the perspective of real estate prices. The reason for focusing on real estate prices is that they are expected to be a confounding factor connecting walkability and the future population. The method we used was to analyze the structural equation modeling of the impact of walkability index, real estate prices, and future population change ratio. This analysis was based on the neighborhood association scale. This study clarified that effective residential clusters are the business center cluster and the sprawl cluster. In the business center cluster and the sprawl cluster, the price of apartments for sale is the real estate value, through which the walkability index positively impacts the future population change ratio. This means that it is expected to contribute to the maintenance of the future population through a combination of walkable designs and housing policies that encourage people to change their residence types to apartments for sale when rebuilding old building stock using the location optimization plan policy.

scholarly journals Questionnaire Investigation on the Needs at Fuji City and its Sensibility Analysis Utilizing Bayesian Network

2019 ◽  
Vol 11 (2) ◽  
pp. 125
Author(s):  
Tsuyoshi Aburai ◽  
Akane Okubo ◽  
Daisuke Suzuki ◽  
Kazuhiro Takeyasu
Keyword(s):  
Sensitivity Analysis ◽  
Bayesian Network ◽  
Causal Relationship ◽  
Surrounding Area ◽  
Network Sensitivity ◽  
The Future ◽  
Sensibility Analysis

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city. Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. These are analyzed by using Bayesian Network. Sensitivity analysis is also conducted. As there are so many items, we focus on “The image of the surrounding area at this shopping street” and pick up former half and make sensitivity analysis in this paper. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.

How influential factors affect aviation networks: A Bayesian network analysis

2021 ◽  
Vol 91 ◽  
pp. 101995
Author(s):  
Yue Wang ◽  
Collin Wai Hung Wong ◽  
Tommy King-Yin Cheung ◽  
Edmund Yangming Wu
Keyword(s):  
Network Analysis ◽  
Bayesian Network ◽  
Influential Factors

Perception and Reality—Economic Inequality as a Driver of Populism?

2019 ◽  
Vol 41 (2) ◽  
pp. 337-358 ◽  
Author(s):  
Michael Hüther ◽  
Matthias Diermeier
Keyword(s):  
Economic Development ◽  
Income Distribution ◽  
Welfare State ◽  
Causal Relationship ◽  
Economic Inequality ◽  
Public Officials ◽  
Middle Classes ◽  
The Future ◽  
General Criticism ◽  
The Welfare State

Abstract Can the rise of populism be explained by the growing chasm between rich and poor? With regard to Germany, such a causal relationship must be rejected. Income distribution in Germany has been very stable since 2005, and people’s knowledge on actual inequality and economic development is limited: inequality and unemployment are massively overestimated. At the same time, a persistently isolationist and xenophobic group with diverse concerns and preferences has emerged within the middle classes of society that riggers support for populist parties. This mood is based on welfare chauvinism against immigration rather than on a general criticism of distribution. Since the immigration of recent years will inevitably affect the relevant indicators concerning distribution, an open, cautious but less heated approach is needed in the debate on the future of the welfare state. In order to address and take the local concerns of citizens seriously, an increased exchange with public officials on the ground is needed.

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