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Open Access
Article
Publication date: 27 March 2020

Agostino Valier

In the literature there are numerous tests that compare the accuracy of automated valuation models (AVMs). These models first train themselves with price data and property

2983

Abstract

Purpose

In the literature there are numerous tests that compare the accuracy of automated valuation models (AVMs). These models first train themselves with price data and property characteristics, then they are tested by measuring their ability to predict prices. Most of them compare the effectiveness of traditional econometric models against the use of machine learning algorithms. Although the latter seem to offer better performance, there is not yet a complete survey of the literature to confirm the hypothesis.

Design/methodology/approach

All tests comparing regression analysis and AVMs machine learning on the same data set have been identified. The scores obtained in terms of accuracy were then compared with each other.

Findings

Machine learning models are more accurate than traditional regression analysis in their ability to predict value. Nevertheless, many authors point out as their limit their black box nature and their poor inferential abilities.

Practical implications

AVMs machine learning offers a huge advantage for all real estate operators who know and can use them. Their use in public policy or litigation can be critical.

Originality/value

According to the author, this is the first systematic review that collects all the articles produced on the subject done comparing the results obtained.

Details

Journal of Property Investment & Finance, vol. 38 no. 3
Type: Research Article
ISSN: 1463-578X

Keywords

Open Access
Article
Publication date: 29 April 2020

Niina Leskinen, Jussi Vimpari and Seppo Junnila

Contrary to the traditional technology project perspective, real estate investors see building-specific renewable energy (on-site energy) investments as part of the property and…

3767

Abstract

Purpose

Contrary to the traditional technology project perspective, real estate investors see building-specific renewable energy (on-site energy) investments as part of the property and as something affecting the property’s ability to produce a (net) cash flow. This paper aims to show the value-influencing mechanism of on-site energy production from a professional property investors’ perspective.

Design/methodology/approach

The value-influencing mechanism is presented with a case study of a prime logistics property located in the Helsinki metropolitan area, Finland. The case study results are compared with the results of a survey answered by over 70 property valuation professionals in the Finnish real estate market.

Findings

Current valuation practice supports the presented value-creation mechanism based on the capitalisation of the savings generated by a building’s own energy production. Valuation professionals see benefits beyond decreased operating expenses such as enhanced image and better saleability. However, valuers acted more conservatively than expected when transferring these additional benefits to the cash flows of the case property.

Practical implications

Because the savings in operating expenses can be capitalised into the property value, property investors should consider on-site energy production when the return of on-site energy exceeds the return of the property. This enhances the profitability of on-site energy, especially in urban areas with low initial yields.

Originality/value

This is the first research paper to open the value-influencing mechanism of on-site energy production from a professional property investors’ perspective in commercial properties and to confirm it from a market study.

Open Access
Article
Publication date: 24 June 2019

Pim Klamer, Vincent Gruis and Cok Bakker

Information verification is an important factor in commercial valuation practice. Valuers use their professional autonomy to decide on the level of verification required, thereby…

1976

Abstract

Purpose

Information verification is an important factor in commercial valuation practice. Valuers use their professional autonomy to decide on the level of verification required, thereby creating an opportunity for client-related judgement bias in valuation. The purpose of this paper is to assess the manifestation of client attachment risks in information verification.

Design/methodology/approach

A case-based questionnaire was used to retrieve data from 290 commercial valuation professionals in the Netherlands, providing a 15 per cent response rate of the Dutch commercial valuation population. Descriptive and inferential statistics have been used to test research hypotheses involving relations between information verification and professional features that may indicate client attachment such as an executive job level and brokerage experience.

Findings

The results reveal that valuers acting at partner level within their organisation obtain lower scores on information verification compared to lower-ranked valuers. Also, brokerage experience correlates negatively to information verification of valuation professionals. Both findings have statistical significance.

Research limitations/implications

The results reflect valuers’ reasoning behaviour rather than actual behaviour. Replication of findings through experimental design will contribute to research validity.

Practical implications

Maintaining close client contact in a competitive environment is important for business continuity yet may foster client attachment. The associated downside risks in valuation practice call for higher awareness of (subconscious) client influence and the development of attitudinal scepticism in valuer training programmes.

Originality/value

This paper is one of the few that explore possible sources of valuer judgement bias by relating client-friendly valuer features to a key area of valuation i.e. information verification.

Details

Journal of Property Investment & Finance, vol. 37 no. 6
Type: Research Article
ISSN: 1463-578X

Keywords

Open Access
Article
Publication date: 10 August 2022

Job Taiwo Gbadegesin

The purpose of this paper is to investigate how the pandemic affects tenants’ response to their lease obligations. This paper commences with examining the adopted tenant selection…

1324

Abstract

Purpose

The purpose of this paper is to investigate how the pandemic affects tenants’ response to their lease obligations. This paper commences with examining the adopted tenant selection criteria during the COVID-19 pandemic. Then, this paper statistically tests if there is a relationship between selection criteria and response on whether the pandemic has effects or not. Then, this paper investigates the specific areas of impact on tenants’ ability to adequately keep to lease agreements in the Nigerian rental market. Finally, this paper proceeds to confirm if there is a relationship between selection criteria and the aspects of tenants’ deficiencies in rental obligations because of COVID-19.

Design/methodology/approach

Survey data, backed with interviews, is elicited from practicing estate surveyors and valuers and licensed property managers in Lagos, the largest property market in Nigeria and sub-Sahara Africa. Policy solutions and implications were solicited from personnel at the ministry of housing and senior professionals in the property sector. Data were analyzed using descriptive statistics, factor analysis and computer-aided qualitative data analysis, Atlas.ti.

Findings

Tenant’s health status is now accorded a priority together with others. Numbers of tenants are challenged with keeping to the prompt-rent-payment rule. Other areas of slight breaches included livestock rearing, subletting, alteration and repair covenants. Except for tenant reputation and tenant family size, there was no significant relationship between tenant’s health status consideration and the COVID-19 effect on tenant non-compliance with lease obligation. Tenants’ non-compliance with tenancy obligations has a connection with the tenants’ affordability, reputation, ability to sign an undertaking and health conditions during the pandemic. This paper recommends rental housing policy review.

Practical implications

It is recommended that the rental policy should be reviewed to give room for rental allowance or palliatives, private rental market regulation, exploration of the national housing fund and, if possible, social housing adoption policy in Nigeria.

Originality/value

This paper draws policymakers’ attention to the need to prepare for the future safety net that caters to citizenry welfare in challenging times.

Details

Journal of Facilities Management , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1472-5967

Keywords

Open Access
Article
Publication date: 2 May 2017

Berna Keskin, Richard Dunning and Craig Watkins

This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market.

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Abstract

Purpose

This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market.

Design/methodology/approach

The paper uses a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows the isolation of the effects of earthquake risk and explores the differential impact in different submarkets in two study periods – one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey served to alter the perceptions of risk through the wider geographic region.

Findings

The analysis shows that there are variations in the size of price discounts in submarkets resulting from the differential influence of a recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values.

Research limitations/implications

The robustness of the models would be enhanced by the addition of further spatial levels and larger data sets.

Practical implications

The methods introduced in this study can be used by real estate agents, valuers and insurance companies to help them more accurately assess the likely impacts of changes in the perceived risk of earthquake activity (or other environmental events such as flooding) on the formation of house prices in different market segments.

Social implications

The application of these methods is intended to inform a fairer approach to setting insurance premiums and a better basis for determining policy interventions and public investment designed to mitigate potential earthquake risk.

Originality/value

The paper represents an attempt to develop a novel extension of the standard use of hedonic models in event studies to investigate the impact of natural disasters on real estate values. The value of the approach is that it is able to better capture the granularity of the spatial effects of environmental events than the standard approach.

Details

Journal of European Real Estate Research, vol. 10 no. 1
Type: Research Article
ISSN: 1753-9269

Keywords

Open Access
Article
Publication date: 25 February 2021

Bo Nordlund, Johan Lorentzon and Hans Lind

The purpose of this article is to study how fair values in financial reports are audited.

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Abstract

Purpose

The purpose of this article is to study how fair values in financial reports are audited.

Design/methodology/approach

The study is a qualitative case study based on in-depth interviews.

Findings

One important finding is that auditors anchor in the figure presented by the company, and despite the auditing efforts, there is a substantial risk of management bias in the fair values reported. There is a risk for confirmation bias.

Research limitations/implications

Relatively, few respondents were employed in this study, but their background and competence lead to the assessment that the study provides a representative picture of what is being investigated.

Practical implications

Auditors may need to develop ways of performing auditing of fair values to reduce the risks identified in this study.

Social implications

This study presents a perspective of the auditing process enabling an evaluation of the quality of fair value estimates regarding investment properties in the financial reports. This study also provides users of financial reports as investors, bankers and other institutions with an enhanced understanding of reported estimates of fair (market) values.

Originality/value

Very few studies have investigated how auditors evaluate fair values of investment properties. This study contributes by giving users of financial reports an enhanced understanding of the quality of reported estimates of fair (market) values.

Details

Journal of Property Investment & Finance, vol. 40 no. 1
Type: Research Article
ISSN: 1463-578X

Keywords

Open Access
Article
Publication date: 15 March 2022

Katarzyna Reyman and Gunther Maier

The purpose of the article is to improve the understanding of the role of institutional factors in real estate development. The authors take into account zoning (existence and…

1116

Abstract

Purpose

The purpose of the article is to improve the understanding of the role of institutional factors in real estate development. The authors take into account zoning (existence and type), type of right of disposal and type of buyer and seller of property in a multivariate econometric estimation. Dependent variable of the analysis is the time between acquisition of empty land and the application for a building permit, a period when many important development decisions have to be made. This indicator is closely related to debated phenomena like land hording and speculation.

Design/methodology/approach

The authors estimate a Cox proportional hazard model with the time between acquisition and application for a building permit as dependent variable and institutional indicators and a number of control variables as explanatory variables. Study area is the GZM Metropolis in the South of Poland. This region shows enough variability in institutional arrangements to allow for this type of analysis.

Findings

The analysis shows that institutional factors significantly influence the real estate development process. In areas that have not issued a zoning plan, the period until the building permit application is significantly longer. When the state is involved in a transaction (as purchaser or seller), it also takes longer until the building permit application is submitted. Although the instrument is usually intended to speed up development, perpetual usufruct implies a longer period until building permit application. Because of the results the authors get for control variables and for robustness checks, the authors are confident of the results of the analysis.

Originality/value

To the authors’ knowledge, this is the first study that deals with the question how institutional factors influence the timing of real estate development. By using data for a region in Poland, the authors also add to knowledge about real estate development in CEE countries.

Details

Journal of European Real Estate Research, vol. 16 no. 1
Type: Research Article
ISSN: 1753-9269

Keywords

Open Access
Article
Publication date: 7 December 2021

Luca Rampini and Fulvio Re Cecconi

The assessment of the Real Estate (RE) prices depends on multiple factors that traditional evaluation methods often struggle to fully understand. Housing prices, in particular…

2963

Abstract

Purpose

The assessment of the Real Estate (RE) prices depends on multiple factors that traditional evaluation methods often struggle to fully understand. Housing prices, in particular, are the foundations for a better knowledge of the Built Environment and its characteristics. Recently, Machine Learning (ML) techniques, which are a subset of Artificial Intelligence, are gaining momentum in solving complex, non-linear problems like house price forecasting. Hence, this study deployed three popular ML techniques to predict dwelling prices in two cities in Italy.

Design/methodology/approach

An extensive dataset about house prices is collected through API protocol in two cities in North Italy, namely Brescia and Varese. This data is used to train and test three most popular ML models, i.e. ElasticNet, XGBoost and Artificial Neural Network, in order to predict house prices with six different features.

Findings

The models' performance was evaluated using the Mean Absolute Error (MAE) score. The results showed that the artificial neural network performed better than the others in predicting house prices, with a MAE 5% lower than the second-best model (which was the XGBoost).

Research limitations/implications

All the models had an accuracy drop in forecasting the most expensive cases, probably due to a lack of data.

Practical implications

The accessibility and easiness of the proposed model will allow future users to predict house prices with different datasets. Alternatively, further research may implement a different model using neural networks, knowing that they work better for this kind of task.

Originality/value

To date, this is the first comparison of the three most popular ML models that are usually employed when predicting house prices.

Details

Journal of Property Investment & Finance, vol. 40 no. 6
Type: Research Article
ISSN: 1463-578X

Keywords

Open Access
Article
Publication date: 4 August 2023

Christopher Amoah

In addressing the housing deficits for the less privileged citizens, the South African government began constructing social housing after coming to power in 1994. However, the…

Abstract

Purpose

In addressing the housing deficits for the less privileged citizens, the South African government began constructing social housing after coming to power in 1994. However, the construction of these houses is bedevilled with many issues; prominent among them are poor quality of the constructed houses. This study seeks to develop a quality management framework for achieving quality and efficiency in public-sector housing construction, a hallmark of the country's procurement goals.

Design/methodology/approach

Telephone interviews were conducted with construction professionals involved in constructing government social houses across South Africa, chosen randomly. The data gathered were analysed using the content analysis method.

Findings

The study found that the most significant cause of poor quality government-constructed social housing is multifaceted, categorised into project management-related, procurement-related, contractor-related, corruption-related and political-related.

Practical implications

Failure to develop and implement a quality management framework on government-constructed social housing leads to poor quality social housing.

Originality/value

The study has identified quality-related issues and has developed a Quality Management (QM) framework for the stakeholders involved in the construction of the houses to guide them in the project implementation process to ensure project success and quality standards.

Details

International Journal of Building Pathology and Adaptation, vol. 41 no. 6
Type: Research Article
ISSN: 2398-4708

Keywords

Open Access
Article
Publication date: 22 March 2021

Mateusz Tomal

This study aims to identify clusters amongst the county housing markets in Poland, taking into account the criteria of size and quality of the housing stock, as well as price…

1683

Abstract

Purpose

This study aims to identify clusters amongst the county housing markets in Poland, taking into account the criteria of size and quality of the housing stock, as well as price level. In addition, this work is intended to detect the socio-economic factors driving the cluster formation.

Design/methodology/approach

To group the studied housing markets into homogeneous clusters, this analysis uses a proprietary algorithm based on taxonomic and k-means++ methods. In turn, the generalised ordered logit (gologit) model was used to explore factors influencing the cluster formation.

Findings

The results obtained revealed that Polish county housing markets can be classified into three or four homogeneous clusters in terms of the size and quality of the housing stock and price level. Furthermore, the results of the estimation of the gologit models indicated that population density, number of business entities and the level of crime mainly determine the membership of a given housing market in a given cluster.

Originality/value

In contrast to previous studies, this is the first to examine the existence of homogeneous clusters amongst the county housing markets in Poland, taking into account the criteria of size and quality of the housing stock, as well as price level simultaneously. Moreover, this work is the first to identify the driving forces behind the formation of clusters amongst the surveyed housing markets.

Details

International Journal of Housing Markets and Analysis, vol. 14 no. 5
Type: Research Article
ISSN: 1753-8270

Keywords

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