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Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

Mauritius’s residential real estate sector has undergone an increase in foreign investment over the past decades. This study aims to establish if the increasing level of foreign real estate investments (FREI) has increased land demand and land prices. The study also aims to depict whether the relation between FREI and land prices prevails at an aggregate and/ or a regional level.

Data from 26 regions, classified as urban, rural and coastal is collected on an annual basis over the period 2000 to 2019, and a dynamic panel regression framework, namely, an autoregressive distributed lag model, is used to take into account the dynamic nature of land price modeling.

The findings show that, at the aggregate level, in the long-term, FREI does not have a significant influence on land prices, while in the short term, a positive significant relationship is noted between the two variables. A regional breakdown of the data into urban, rural and coastal was done. In the long term, only in coastal regions, a positive significant link was observed, whereas in urban and rural regions FREI did not influence land prices. In the short term, the positive link subsists in the coastal regions, and in rural regions also land prices are positively affected by FREI.

Unlike other studies which have used quite general measures of FREI, the present research has focused on FREI mainly undertaken in the residential real estate market and how these have affected residential land prices. This study also contributes to research on the determinants of land prices which is relatively scarce compared to research on housing prices.

This study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).

The method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units’ price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.

Based on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.

Identifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.

This paper aims to analyze the legal framework of land degradation in Asia and provide market shared liability as a new theory to solve a problem regarding the difficulty for judges to determine the percentage of compensation for corporations responsible for land degradation. This paper aims also presents a theory to solve the problem of the vacuum of legal responsibility theory, which can make corporations proportionally responsible in terms of causing land degradation.

This was done through legal research methods, mainly with systematical interpretation. The approach used in this paper is conceptual, statute and comparative approach.

By analyzing the related legal norms, it can be understood that in Asian countries, such as Indonesia, Thailand and Malaysia, there are regulations regarding land degradation. However, the regulations in these countries are not specific and tend to focus on nature conservation, which has an impact on handling land degradation. Therefore, it needs special regulation to deal with land degradation. One of the things that need to be regulated about land degradation is a market shared liability.

This research is limited to regulation in the Asia region. By analyzing the regulation, this paper will provide an analysis about the land degradation regulation mechanism in Asia and give an analysis about market shared liability as one of the solution to handling land degradation. Having the same ground rules will create synergies between countries in Asia to handle land degradation.

This paper is the first systematic legal research comparing regulations from three nations in Asia on land degradation and the first paper to provide market shared liability as a solution to handling land degradation.

Achieving tenure security is a global challenge impacting cities of the global south. The purpose of this paper is to evaluate the role of technology-enabled solutions as an enabler for the tenure rights of slum dwellers.

In this paper, we adopted a case study approach to analyze the use cases for technologies aiding India’s securitization of land tenure. The flagship state mission of Odisha, named the Jaga Mission, and that of Punjab, named BASERA – the Chief Minister’s Slum Development Program – were used as cases for this paper.

It was found that technologies like drone imagery and digital surveys fast-tracked the data collection and helped in mapping the slums with accuracy, mitigating human errors arising during measurement – a necessary condition for ensuring de jure tenure security. The adoption of a technology-based solution, along with a suitable policy and legal framework, has helped in the distribution of secure land titles to the slum dwellers in these states.

Odisha’s and Punjab’s journey in using technology to enable tenure security for its urban poor residents can serve as a model for the cities of the global south, dealing with the challenges of providing secure tenure and property rights.

This study aims to examine the determinants that influence housing prices in Dammam metropolitan area (DMA), Saudi Arabia, by using the analytic hierarchy process (AHP) model. The study considers determinants such as building age (BLD AG), building size (BLD SZ), building condition (BLD CN), access to parking (ACC PK), proximity to transport infrastructure (PRX TRS), proximity to green areas (PRX GA) and proximity to amenities (PRX AM).

The AHP decision model was used to assess the determinants of housing prices in DMA, using a pair-wise comparison matrix to determine the influence of the investigated factors on housing prices.

The study’s results revealed that building size (BLD SZ) was the most critical determinant affecting housing prices in DMA, with a weight of 0.32, trailed by proximity to transport infrastructure (PRX TRS), with a weight of 0.24 as the second most influential housing price determinant in DMA. The third most important determinant was proximity to amenities (PRX AM), with a weight of 0.18.

This study addresses a research gap by using the AHP model to assess the spatial determinants of housing prices in DMA, Saudi Arabia. Few studies have used this model in examining housing price factors, particularly in the context of Saudi Arabia. Consequently, the findings of this study provide unique insights for policymakers, housing developers and other stakeholders in understanding the importance of building size, proximity to transport infrastructure and proximity to amenities in influencing housing prices in DMA. By considering these determinants, stakeholders can make informed decisions to improve housing quality and prices in the region.

This study aims to test the effect of Seattle’s discontinuous sidewalk requirement, on the number of housing units per construction permit.

This study uses discontinuity linear regression (DLR) on a database of Seattle’s housing construction permits during January-2015 to January-2018, controlled by 51 socioeconomic, planning and geographic variables. The sidewalk requirement is continuous inside the designated urban villages; however, it is spatially and quantitatively discontinuous in the rest of the city: certain blocks at certain locations require sidewalks’ design and construction in permits with six or more housing units. DLR detects the effect of the discontinuity while controlling for a vast array of confounding variables.

The primary finding is that the discontinuous requirement reduces the number of housing units in about 75% of a housing unit per permit, which at the aggregate level amounts to around 335 fewer housing units during the period of analysis.

The database is relatively small, which has limited a more thorough specification process and robustness tests.

Besides directly testing the effect of a discontinuous in-kind development contribution, the research setup allows to discuss a wider, more structural problem: the possibility of contributions avoidance due to spatial substitution. In contrast, spatially continuous (i.e. city-level) contributions cannot be avoided by performing spatial substitution, and they are internalized by the housing supply side (market-neutral).

The purpose of this paper is to examine expropriation, valuation, compensation and rehabilitation practices and their impacts on expropriated households.

This study employed a mixed research approach. The target populations of the study were expropriated households in Debre Markos City from 2019 to 2022. The study uses purposive and systematic random sampling techniques. The data were analyzed using descriptive statistics, narration and thematic clustering.

The findings of this study revealed that the expropriation process was not participatory and the right holders were not treated as what is expected. It is further found that economic losses, moral damage and social disturbance payments were not considered in the compensation package. The displacement compensation given was also inadequate and sometimes delayed and the time value of money was not taken into account for delayed payments. This creates social and economic problems. The rehabilitation and resettlement program was inadequate and ineffective. The expropriation, valuation, compensation and rehabilitation practice in general lack transparency and accountability.

To ensure efficient and effective expropriation, valuation and compensation, there should be a well-organized government system that provides an accurate valuation on the one hand and restores the livelihood of the displaced on the other.

This paper is the first on expropriation, valuation, compensation and rehabilitation within the framework of transparency, accountability, effective rehabilitation and resettlement and institutional arrangements to ensure the sustainable livelihoods of affected households.

Land transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.

Based on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).

The price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.

This paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.

The purpose of the study is to observe the feasibility of missing middle housing’s (MMH) realization under density-based zoning, form-based zoning and a combination of both while simultaneously providing affordable housing, improving quality of life and making efficient use of land.

This study takes a theorist approach and designs three hypothetical cottage court projects that comply with all relevant official local zoning ordinances to showcase design feasibility, followed by an analytical component in the form of a financial model constructed using official local economic and demographic conditions.

MMH, and in particular cottage clusters, can be implemented under rigorous density-based, form-based and hybrid (density-based + form-based) zoning ordinances and provide affordable housing (Atlanta, GA), improve quality of life (Blackpool, UK) and make efficient use of land (Jinan, China). All hypothetical projects are financially feasible under reasonable conditions.

To the best of the author’s knowledge, this paper is the first in the body of knowledge to discuss how the MMH can be integrated into urban density-based zoning rather than converting density-based zoning into form-based so that the MMH can fit. The paper also takes a cross-national perspective and discusses the feasibility of MMH in the resolution of housing issues in the USA, China and the UK. The study also concludes that the issue of housing unaffordability in the UK was caused by high construction cost relative to median income.