The effect of transport cost on housing affordability: Experiences from the Bandung Metropolitan Area, Indonesia

Dewita, Yulia; Yen, Barbara T.H.; Burke, Matthew

doi:10.1016/j.landusepol.2018.08.043

Cited by 34 publications

(17 citation statements)

References 52 publications

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“…The results of [Survey A -2] show that the travel distance to public facilities has actually shortened and the travel costs have reduced after moving. These reductions in travel distance and costs due to moving to a downtown area are consistent with a previous study [50] that confirmed that there is high accessibility in the downtown area and a resulting low cost of movement. These survey results suggest that the downtown area is more convenient than suburban high-rises that offer a high level of safety against tsunamis, making the residents satisfied with the surrounding environment.…”

Section: Discussionsupporting

confidence: 92%

Sustainable Downtown Development for the Tsunami-Prepared Urban Revitalization of Regional Coastal Cities

et al. 2019

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Regional cities in Japan are facing a decline in the downtown area owing to urban expansion and a decrease in the population. Promoting downtown living is indispensable for the realization of downtown revitalization. Since many coastal cities originally developed outward from a port, their downtown areas are located near the coast and are at high risk of tsunamis. The purpose of this research is to reveal the effectiveness of dealing with the above two issues in parallel by evaluating the Deae-ru Saiwai estate, a public housing relocation project in downtown Kushiro, Hokkaido, Japan that incorporates a tsunami evacuation facility with questionnaires and a GIS survey. Placing public housing in the downtown area shortens the distance to public facilities and improves the convenience of the surrounding environment for many residents. Installing the tsunami evacuation facility improves the feeling of reassurance of residents who would feel anxiety about immigration with regards to tsunamis. This research has clarified the synergistic effect of dealing with the daily and emergency issues in parallel for promoting downtown living. Planning downtown revitalization and disaster prevention concurrently, which has been separated so far, is a fundamental planning approach for urban revitalization in regional coastal cities.

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Section: Discussionsupporting

confidence: 92%

Sustainable Downtown Development for the Tsunami-Prepared Urban Revitalization of Regional Coastal Cities

et al. 2019

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“…Therefore, this may also lead to long distance commuting and traffic congestion (Zhao and Hu, 2019), and cause air pollution, particularly for people who travel by private vehicles (Cao et al, 2017). To some extent, these results also reflect the combined issue of car dependence and housing affordability (Cao and Hickman, 2018;Dewita et al, 2018Dewita et al, , 2020, as well as inferring potential issues associated with transport-related social inequity (Cao, 2019;Cao andHickman, 2019, 2020;Zhao and Cao, 2020;Zhang et al, 2018). On the other hand, the expansion of jobs from the typical employment area to the surrounding area has relieved traffic congestion in the city.…”

Section: Spatial Distributionmentioning

confidence: 99%

Identifying Urban Functional Areas and Their Dynamic Changes in Beijing: Using Multiyear Transit Smart Card Data

Wang

Liu

Zhu

et al. 2021

J. Urban Plann. Dev.

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A growing number of megacities have been experiencing changes to their landscape due to rapid urbanisation trajectories and travel behaviour dynamics. Therefore, it is of great significance to investigate the distribution and evolution of a city's urban functional areas over different periods of time. Although the smart card automated fare collection system (SCAFC) is already widely used, few studies have used smart card data to infer information about changes in urban functional areas, particularly in developing countries. Thus, this research aims to delineate the dynamic changes that have occurred in urban functional areas based on passengers' travel patterns, using Beijing as a case study. We established a Bayesian framework and applied a Gaussian mixture model (GMM) derived from transit smart card data in order to gain insight into passengers' travel patterns at station level and then identify the dynamic changes in their corresponding urban functional areas. Our results show that Beijing can be clustered into five different functional areas based on the analysis of corresponding transit station functions, namely: multimodal interchange hub and leisure area; residential area; employment area; mixed but mainly residential area; and a mixed residential and employment area. In addition, we found that urban functional areas have experienced slight changes between 2014 and 2017. The findings can be used to inform urban planning strategies designed to tackle urban spatial structure issues, as well as guiding future policy evaluation of urban landscape pattern use.

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“…Finding a strategic land located at a decent rate is the most critical step in the development of affordable housing schemes (Mulliner and Algrnas, 2018). Land cost is the single biggest factor that majorly affects the costing of a housing project (Dewita et al , 2018). Commonly, low-price lands are located far from the infrastructural facilities such as transportation, hospitals, schools, shopping centres and employment (Opoku and Abdul-Muhmin, 2010).…”

Section: Model For Framework Of Factual Situation In Housing Supply and Demandmentioning

confidence: 99%

Housing attributes affecting buyers in India

Ghumare

Chauhan

Yadav

2019

IJHMA

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Purpose The purpose of this paper is to provide affordable housing to low- and middle-income groups. The gravity of India’s housing affordability problem has led us to study and analyse the attributes hindering affordable housing for economically weaker section (EWS) and low-income group (LIG). The attributes such as viable parameters, economic parameters, location and communication, regulatory, source of finance, construction, services and infrastructure parameters affect the supply and demand of affordable housing in Indian urban areas for EWS and LIG with an annual household income below 2 lakhs. Design/methodology/approach The judgement sampling is used amongst housing and planning professionals working in five different sectors, including local authorities, housing developers, housing sectors, town planning and property/affordable housing consultant. The Analytical hierarchy process method of multi-criteria decision-making was used to analyse the data collected. Findings A detailed analysis of the data collected reveals that a viable parameter is the most governing attribute in the supply and demand process of developing affordable housing. Major reforms can be implemented at various levels of housing development in the urban area that can help in reducing the affordability gap for EWS/LIG. The suggested approach will be helpful for developers, urban planners and decision makers while designing an affordable housing project. Originality/value The model being proposed in this paper seeks for a proficient allotment of policies and assets, to some extent, by remedying the current market distortions and different inconsistencies that negatively influence the incentive structure of the affordable housing section in India. This paper offers a plan for a housing procedure that is applicable to all measurements of housing poverty and the groups that sustain it. In this way, the current study is, to a greater extent, a facilitator, and not an immediate solution of affordable housing.

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The effect of transport cost on housing affordability: Experiences from the Bandung Metropolitan Area, Indonesia

Cited by 34 publications

References 52 publications

Sustainable Downtown Development for the Tsunami-Prepared Urban Revitalization of Regional Coastal Cities

Sustainable Downtown Development for the Tsunami-Prepared Urban Revitalization of Regional Coastal Cities

Identifying Urban Functional Areas and Their Dynamic Changes in Beijing: Using Multiyear Transit Smart Card Data

Housing attributes affecting buyers in India

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