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1 – 10 of over 1000
Article
Publication date: 15 May 2023

Catherine Prentice and Adam Pawlicz

This paper aims to examine the primary supply data sources that have been used for research into the sharing economy, and the advantages and limitations of these sources in the…

Abstract

Purpose

This paper aims to examine the primary supply data sources that have been used for research into the sharing economy, and the advantages and limitations of these sources in the literature.

Design/methodology/approach

To address the research aims, this study conducted a systematic literature review and content analysis of all relevant articles. Following the review, the methodological sections of the selected papers were examined to identify the characteristics and limitations of all data sources used in the papers.

Findings

This study revealed several limitations of the use of three major data sources, namely, web scraping with self-made bots, inside Airbnb and AirDNA, for sharing economy research. The review shows that the majority of the selected papers did not acknowledge any limitations, nor did they discuss the quality of the data sources.

Research limitations/implications

The findings of this paper can serve as guidelines for selecting appropriate data sources for research into the sharing economy and cautions researchers to address the limitations of the data sources used.

Originality/value

To the best of the authors’ knowledge, this is the first study that explores the advantages and limitations of data sources used in short-term rental market research.

Details

International Journal of Contemporary Hospitality Management, vol. 36 no. 3
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 29 July 2022

Sukampon Chongwilaikasaem and Tanit Chalermyanont

Global warming exacerbates sea level rise and extreme weather events that cause severe flooding, resulting in lost productivity and property damage. To reduce the impact of…

Abstract

Purpose

Global warming exacerbates sea level rise and extreme weather events that cause severe flooding, resulting in lost productivity and property damage. To reduce the impact of flooding, residents are avoiding purchasing homes in high-risk areas. There are numerous studies on the relationship between flood hazards and housing prices in developed countries, but few in developing countries. Therefore, this study aims to investigate the relationship between flood hazards and housing prices in Hat Yai, Songkhla, Thailand.

Design/methodology/approach

This study uses spatial-lag, spatial error and spatial autoregressive lag and error (SARAR) models to analyze the effect of flood risk on property prices. The main analysis examines the degree of flood risk and housing rental prices from our survey of 380 residences. To test the robustness of the results, the authors examine a different data set of the same samples by using the official property valuation from the Ministry of Finance and the flood risk estimated by the Southern Natural Disaster Research Center.

Findings

The SARAR model was chosen for this study because of the occurrence of spatial dependence in both dependent variable and the error term. The authors find that flood risk has a negative impact on property prices in Hat Yai, which is consistent with both models.

Originality/value

This study is one of the first to use spatial econometrics to analyze the impact of flood risk on property prices in Thailand. The results of this study are valuable to policymakers for benefit assessment in cost–benefit analysis of flood risk avoidance or reduction strategies and to the insurance market for pricing flood risk insurance.

Details

International Journal of Housing Markets and Analysis, vol. 16 no. 6
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 31 October 2022

Seyedeh Mehrangar Hosseini, Behnaz Bahadori and Shahram Charkhan

The purpose of this study is to identify the situation of spatial inequality in the residential system of Tehran city in terms of housing prices in the year 2021 and to examine…

Abstract

Purpose

The purpose of this study is to identify the situation of spatial inequality in the residential system of Tehran city in terms of housing prices in the year 2021 and to examine its changes over time (1991–2021).

Design/methodology/approach

In terms of purpose, this study is applied research and has used a descriptive-analytical method. The statistical population of this research is the residential units in Tehran city 2021. The average per square meter of a residential unit in the level of city neighborhoods was entered in the geographical information system (GIS) in 2021. Moran’s spatial autocorrelation method, map cluster analysis (hot and cold spots) and Kriging interpolation have been used for spatial analysis of points. Then, the change in spatial inequality in the residential system of Tehran city has been studied and measured based on the price per square meter of a residential unit for 30 years in the 22 districts of Tehran by using statistical clustering based on distance with standard deviation.

Findings

The result of spatial autocorrelation analysis with a score of 0.873872 and a p-value equal to 0.000000 indicates a cluster distribution of housing prices throughout the city. The results of hot spots show that the highest concentration of hot spots (the highest price) is in the northern part of the city, and the highest concentration of cold spots (the lowest price) is in the southern part of Tehran city. Calculating the area and estimating the quantitative values of data-free points by the use of the Kriging interpolation method indicates that 9.95% of Tehran’s area has a price of less than US$800, 17.68% of it has a price of US$800 to US$1,200, 25.40% has the price of US$1,200 to US$1,600, 17.61% has the price of US$1,600 to US$2,000, 9.54% has the price of US$2,000 to US$2,200, 6.69% has the price of US$2,200 to US$2,600, 5.38% has the price of US$2,600 to US$2,800, 4.59% has the price of US$2,800 to US$3,200 and finally, the 3.16% has a price more than US$3,200. The highest price concentration (above US$3,200) is in five neighborhoods (Zafaranieh, Mahmoudieh, Tajrish, Bagh-Ferdows and Hesar Bou-Ali). The findings from the study of changes in housing prices in the period (1991–2021) indicate that the southern part of Tehran has grown slightly compared to the average range, and the western part of Tehran, which includes the 21st and 22nd regions with much more growth than the average price.

Originality/value

There is massive inequality in housing prices in different areas and neighborhoods of Tehran city in 2021. In the period under study, spatial inequality in the residential system of Tehran intensified. The considerable increase in housing prices in the housing market of Tehran has made this sector a commodity, intensifying the inequality between owners and non-owners. This increase in housing price inequality has caused an increase in the informal living for the population of the southern part. This population is experiencing a living situation that contrasts with the urban plans and policies.

Details

International Journal of Housing Markets and Analysis, vol. 17 no. 2
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 3 October 2023

Umar Lawal Dano

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…

Abstract

Purpose

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).

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 28 July 2023

Vivek Agnihotri and Saikat Kumar Paul

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…

Abstract

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.

Details

International Journal of Housing Markets and Analysis, vol. 17 no. 1
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 12 March 2024

Aimin Wang, Sadam Hussain and Jiying Yan

The purpose of this study is to conduct a thorough empirical investigation of the intricate relationship between urban housing sales prices and land supply prices in China, with…

Abstract

Purpose

The purpose of this study is to conduct a thorough empirical investigation of the intricate relationship between urban housing sales prices and land supply prices in China, with the aim of elucidating the underlying economic principles governing this dynamic interplay.

Design/methodology/approach

Using monthly data of China, the authors use the asymmetry nonlinear autoregressive distributed lag (NARDL) model to test for nonlinearity in the relationship between land supply price and urban housing prices.

Findings

The empirical results confirm the existence of an asymmetric relationship between land supply price and urban housing prices. The authors find that land supply price has a positive and statistically significant impact on urban housing prices when land supply is increasing. Policymakers should strive to strike a balance between safeguarding residents’ housing rights and maintaining market stability.

Research limitations/implications

Although the asymmetric effect of land supply price has been identified as a significant contributor in this study, it is important to note that the research primarily relies on time series data and focuses on analysis at the national level. Although time series data offer a macroscopic perspective of overall trends within a country, they fail to adequately showcase the structural variations among different cities.

Practical implications

To ensure a stable housing market and meet residents’ housing needs, policymakers must reexamine current land policies. Solely relying on restricting land supply to control housing prices may yield counterproductive results. Instead, increasing land supply could be a more viable option. By rationally adjusting land supply prices, the government can not only mitigate excessive growth in housing prices but also foster the healthy development of the housing market.

Originality/value

First, the authors have comprehensively evaluated the impact of land supply prices in China on urban housing sales prices, examining whether they play a facilitating or mitigating role in the fluctuation of these prices. Second, departing from traditional linear analytical frameworks, the authors have explored the possibility of a nonlinear relationship existing between land supply prices and urban housing sales prices in China. Finally, using an advanced NARDL model, the authors have delved deeper into the asymmetric effects of land supply prices on urban housing sales prices in China.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 20 September 2022

Adeyosoye Babatunde Ayoola, Adejoke Rashidat Oladapo, Babajide Ojo and Abiodun Kolawole Oyetunji

This paper aims to examine the impact of coastline on the rental value of residential property in proximity to the coastline, using the hedonic pricing model from two…

Abstract

Purpose

This paper aims to examine the impact of coastline on the rental value of residential property in proximity to the coastline, using the hedonic pricing model from two perspectives. First, Model 1A–C accounted for estimating the influence of coastal amenities while controlling for other housing attributes influencing rent. Second, Model 2A–C accounted for the interaction between coastal amenities/disamenities and other housing attributes influencing rent.

Design/methodology/approach

A survey approach was adopted for the data collection process. For both models, property values were measured in proximity to coastline using 0–250 m, 251–500 m and 0–500 m.

Findings

Findings revealed that property rental value increases as we move away from the coastline when disamenities are not controlled. The results suggested that for a mean-priced home (N2,941,029 or $8,170) at the mean distance from the coastline (301.83 m), a 1% increase in distance from the coastline would result in a 0.001% or N9.77 ($0.03) increase in rental value.

Practical implications

The implication to real estate valuers is that varying premiums should be considered when valuing a property depending on the distance to the coastline while considering other housing attributes.

Originality/value

This research introduces a novel approach to the hedonic model for determining property values in proximity to coastal environment by estimating the influence of coastal amenities while controlling for other housing attributes influencing rent, on the one hand, and accounting for the interaction between coastal amenities/disamenities and other housing attributes influencing rent, on the other.

Details

International Journal of Housing Markets and Analysis, vol. 16 no. 6
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 26 July 2023

Valery Yakubovsky, Oleksiy Bychkov and Kateryna Zhuk

This paper aims to examine the influence of Covid-19, current war and other factors on the dynamics of real estate prices in Ukraine from 2019Q2 to 2022Q4. More specifically, the…

Abstract

Purpose

This paper aims to examine the influence of Covid-19, current war and other factors on the dynamics of real estate prices in Ukraine from 2019Q2 to 2022Q4. More specifically, the authors examine the extent of the influence of Covid-19 and war on the real estate market in Ukraine.

Design/methodology/approach

The authors monitor and accumulate information flows from the existing real estate market with their subsequent in-depth math-stat processing to examine dynamics and drivers of Ukrainian real estate prices evolution.

Findings

The study finds that the Ukrainian residential property market has experienced an average growing trend from June 2019 to December 2022, despite the strong influence of pandemic and war. The analysis shows that the impact of these factors varies across different regions and property types, with some areas and property types being more affected than others. The study also identifies the main drivers of the market evolution, including cost-sensitive factors such as floor level, overall area, housing conditions and geographical location.

Research limitations/implications

This research is oriented to analyze evolution of residential property market in Ukraine in 2019–2022 years characterized by influence of such disturbing factors as pandemic and military actions.

Practical implications

Results gained are essential for any type of Ukrainian residential market analytics implementation including but not limited to investment analysis, valuation services, collateral, insurance and taxation purposes, etc. In broader sense, it can be also useful for comparison with same type market development in other geographical arears.

Social implications

Initial data base collected and constantly monitored covers all different regions of the country that gives a broad view on the overall market development influenced by pandemic and war.

Originality/value

The lack of a reliable database of the purchase and sale of residential properties remains one of the biggest obstacles in obtaining reliable data on their market value. This considerably complicates the process of carrying out a valuation and reduces the accuracy and reliability of the results of such work. This is especially important for market which evolves in times of unrest being influenced by such strongly disturbing factors as pandemic and military actions. The originality of the study lies in the development of a complete probabilistic processing of the initial database, which provides a reliable and accurate assessment of the market evolution. The results achieved could be used by various stakeholders, such as property owners, investors, valuers, insurers, regulators and other interested customers, to make informed decisions and mitigate risks in the turbulent Ukrainian real estate market.

Details

International Journal of Housing Markets and Analysis, vol. 17 no. 1
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 29 November 2023

Huthaifa Alqaralleh

This study explores the interconnectedness and complexity of risk-varied climate initiatives such as green bonds (GBs), emissions trading systems (ETS) and socially responsible…

116

Abstract

Purpose

This study explores the interconnectedness and complexity of risk-varied climate initiatives such as green bonds (GBs), emissions trading systems (ETS) and socially responsible investments (SRI). The analysis covers the period from September 2011 to August 2022, using six indices: three representing climate initiatives and three indicating uncertainty.

Design/methodology/approach

To achieve this, the study first examines dynamic lead-lag relations and correlation patterns in the time-frequency domain to analyse the returns of the series. Additionally, it applies an innovative approach to investigate the predictability of uncertainty measurements of climate initiatives across various market conditions and frequency spillovers in the short, medium and long run.

Findings

The findings indicate changing relationships between the series, increased linkages during turbulent market periods and strong co-movements within the network. The ETS is recommended for diversification and hedging against uncertainty indices, whereas the GB may be suitable for long-term diversification.

Practical implications

This study highlights the role of climate initiatives as potential hedges and contagion amplifiers during crises, with implications for policy recommendations and the asymmetric effects on market connectedness.

Originality/value

The paper answers questions that previous studies have not and contributes to the literature regarding financial risk management and social responsibility.

Details

The Journal of Risk Finance, vol. 25 no. 1
Type: Research Article
ISSN: 1526-5943

Keywords

Article
Publication date: 13 October 2022

Garima Negi and Smita Tripathi

The paper intends to review academic research on peer to peer (P2P) accommodation sharing, notably Airbnb, for 2010–2022 and to identify the knowledge gaps for future research…

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Abstract

Purpose

The paper intends to review academic research on peer to peer (P2P) accommodation sharing, notably Airbnb, for 2010–2022 and to identify the knowledge gaps for future research directions.

Design/methodology/approach

Numerous databases were searched using keywords. Based on the central theme of the research papers, the papers were divided into eight segments—consumer behavior, host behavior, host–guest relationship (HGR), trust in Airbnb, dominant theories in Airbnb, Airbnb regulation, Airbnb and hotels and macro impacts of Airbnb. In-depth content analysis resulted in the final 101 papers for inclusion.

Findings

The review advances comprehension of the Airbnb phenomenon by enriching the literature with new and most recent studies. Most existing Airbnb research has been conducted in Europe, USA/Canada, followed by Asian countries like China, Singapore, S. Korea and India. Future studies should include South America, Africa and other developing nations. More cross-cultural studies are required to understand consumer and host behavior in different cultural settings. Numerous proposals to fulfill the research gaps identified by the paper are discussed.

Practical implications

The study will give better insights into the spiraling P2P accommodation economy. The study will be useful to researchers, scholars, Airbnb, the hotel industry, vacation rental players and destination marketing organizations by relating the study findings to practical competition analysis. The study provides deeper insights into the decision-making process of both guests and hosts by examining the relevant motivators and constraints. It will also assist the Airbnb platform in identifying its strength over the traditional hotel industry and other vacation rentals. The findings will also assist policymakers in better controlling the Airbnb phenomena by providing a comprehensive view of the micro and macro environment.

Originality/value

The paper includes the most recent studies from Asian countries like India, Singapore, China, Korea and Taiwan, not covered by earlier reviews. Prior studies mainly focused on European and American countries. Also, the paper tried to cover the macro impacts of Airbnb in-depth and the effects of COVID-19.

Details

Journal of Hospitality and Tourism Insights, vol. 6 no. 5
Type: Research Article
ISSN: 2514-9792

Keywords

1 – 10 of over 1000