Housing shortage in a mega city: a spatio-temporal analysis of NCT-Delhi, 2001–2011

Abhay, Rajesh Kumar; Sharma, Madhuri

doi:10.1007/s10708-022-10597-5

Cited by 5 publications

(3 citation statements)

References 37 publications

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“…This growth is reflected in the decreasing number of rural villages in the territory of Delhi, which fell from 300 in 1961 to 165 in 2001 and finally to 112 in 2011 (Directorate of Census Operations, D, 2011b). The demand for housing has been a driving force behind the city's transformation, which has resulted in significant redevelopment in the urban areas of Delhi Housing market shifts (Abhay and Sharma, 2022;Sharma and Abhay, 2022). In fact, between 2001 and 2011, Delhi experienced the most considerable increase in population density, with an addition of almost 575 households per sq.…”

Section: Housing Prices In Delhimentioning

confidence: 99%

Housing market shifts favouring transit-oriented development in emerging economies: the link between metro rails and housing price dynamics in Delhi

Agnihotri

Paul

2023

IJHMA

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Purpose This paper aims to understand the spatiotemporal influence of metro rail connectivity on housing prices in surrounding areas. The study assesses the average annual price shift for apartments around metro stations in Delhi during the previous decade, specifically from 2010 to 2019. The authors examine the spatiotemporal extents to which housing prices are determined by the prominence of metro stations and spatial development around metro stations. Design/methodology/approach The authors perform the cross-tabulation analysis to calculate chi-square values to test the hypotheses concerning the responsiveness of the housing market in Delhi to the number of locational variables in the areas connected with the mass public transportation system. Findings The empirical findings verify the existence of a housing market overvaluation in Delhi around metro stations until 2013, which was eventually re-adjusted after 2014. The key findings of the study suggest the role of location variables concerning metro rails in the shooting up of the housing prices in the city. In addition, the research establishes the association of annual housing price shifts to the metro rails in the short-term, mid-term and long-term in conjunction with the distance from the metro station. Originality/value In the market, the prices are often overvalued by real estate agents due to better connectivity to the metro stations. The overvaluation eventually causes massive downfalls in housing markets and rollouts as a risk for the investors. However, the effect of mass transportation on housing prices is mixed in nature, limited to a certain extent only and not as influential as frequently portrayed by the market forces. This effect loses colour with time.

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Section: Housing Prices In Delhimentioning

confidence: 99%

Housing market shifts favouring transit-oriented development in emerging economies: the link between metro rails and housing price dynamics in Delhi

Agnihotri

Paul

2023

IJHMA

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“…For instance, a significant amount of research has been conducted on the issue of inadequate housing in India. Abhay [5], while presenting the number of houses built in a recent decade (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011) in Delhi, noted that, although the housing supply is stimulated by the housing shortage problem, low-quality housing is prevalent throughout the city. This was mentioned while Abhay discussed the number of houses built in the studied decade in Delhi.…”

Section: Introductionmentioning

confidence: 99%

Application of Artificial Intelligence for Predicting Real Estate Prices: The Case of Saudi Arabia

et al. 2022

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The housing market is a crucial economic indicator to which the government must pay special attention because of its impact on the lives of freshly minted city inhabitants. As a guide for government regulation, individual property purchases, third-party evaluation, and understanding how housing prices are distributed geographically may be of great practical use. Therefore, much research has been conducted on how to arrive at a more accurate and efficient way of calculating housing prices in the current market. The goal of this study was to use the artificial neural network (ANN) technique to correctly identify real estate prices. The novelty of the proposed research is to build a prediction model based on ANN for predicting future house prices in Saudi Arabia. The dataset was collected from Aqar in four main Saudi Arabian cities: Riyadh, Jeddah, Dammam, and Al-Khobar. The results showed that the experimental and predicted values were very close. The results of the proposed system were compared with different existing prediction systems, and the developed model achieved high performance. This forecasting system can also help increase investment in the real estate sector. The ANN model could appropriately estimate the housing prices currently available on the market, according to the findings of the assessments of the model. Thus, this study provides a suitable decision support or adaptive suggestion approach for estimating the ideal sales prices of residential properties. This solution is urgently required by both investors and the general population as a whole.

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“…Several studies have been undertaken in India related to the problem of housing shortages. In Delhi, Abhay [2], while presenting the number of houses built in the recent decade (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011), pointed out that, although the housing supply is stimulated by the housing shortage problem, low-quality housing is widespread. Kumar [3] pointed out that the large number of obsolescent houses is a fundamental problem that leads to housing shortages.…”

Section: Introduction 1research Backgroundmentioning

confidence: 99%

Diversification of Villa-Type Neighborhoods and Its Impact on Housing Shortages in a Growing Saudi Arabian City: A Case Study of Jeddah

2022

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During the urbanization process in Jeddah, evidenced by an annual population growth rate of 9.5%, vacant lots have existed in developed residential areas in spite of the housing shortage. This study aimed at investigating the housing shortage problem and suggesting future solutions based on a predictive formula through four tasks: (1) examining the issues induced by population growth; (2) assessing the extent to which articles in the Procedure Manual for Preparation of Residential Land Subdivision (PMPRLS) foster diversity within villa-type neighborhoods; (3) clarifying the extent of the applicability of these articles and the contribution of existing neighborhood patterns to the housing shortage problem; and (4) providing recommendations for developing each kind of villa-type neighborhood to contribute to resolving the housing shortage. The proposed development methods for villa-type neighborhoods were derived from a correlation analysis using PMPRLS-related indicators in all such neighborhoods (103 study sites) in Jeddah and from a predictive regression analysis. This study suggests that each neighborhood class can contribute to resolving the housing shortage problem. In conclusion, diversifying lot areas, population density, and lot widths in current villa-type neighborhoods would have a positive impact on the housing shortage problem.

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Housing shortage in a mega city: a spatio-temporal analysis of NCT-Delhi, 2001–2011

Cited by 5 publications

References 37 publications

Housing market shifts favouring transit-oriented development in emerging economies: the link between metro rails and housing price dynamics in Delhi

Housing market shifts favouring transit-oriented development in emerging economies: the link between metro rails and housing price dynamics in Delhi

Application of Artificial Intelligence for Predicting Real Estate Prices: The Case of Saudi Arabia

Diversification of Villa-Type Neighborhoods and Its Impact on Housing Shortages in a Growing Saudi Arabian City: A Case Study of Jeddah

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