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Special Issue "Real Estate Economics, Management and Investments"

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: 31 October 2018

Special Issue Editors

Guest Editor
Prof. Pierfrancesco De Paola

Department of Industrial Engineering, Univeristy of Naples “Federico II”, Piazzale Vincenzo Tecchio 80, 80125 Napoli, Italy
Website | E-Mail
Interests: econometric models; mass appraisal; real estate market; risk management; urban and real estate economics; real estate investments; building management; economic valuation of real estate investment projects; environmental economics; transport economics; sustainability; knowledge management; corporate valuation
Guest Editor
Prof. Vincenzo Del Giudice

Department of Industrial Engineering, Univeristy of Naples “Federico II”, Piazzale Vincenzo Tecchio 80, 80125 Napoli, Italy
Website | E-Mail
Interests: econometric models; mass appraisal; real estate market; risk management; urban and real estate economics; real estate investments; building management; economic valuation of real estate investment projects; environmental economics; transport economics; sustainability; knowledge management; corporate valuation

Special Issue Information

Dear Colleagues,

The current difficult situation of production and consumption activities has also determined a weakness of real estate economy. The main problems are the subordination of public decision-making, which is subjected to pressure from big companies, inefficient appraisal procedures, excessive use to financial leverage in investment projects, the atypical nature of markets, income positions in urban transformations, and the financialization of real estate markets with widespread negative effects.

A delicate role in these complex problems is assigned to real estate appraisal activities, called to make value judgments on real estate goods and investment projects, of which prices are often formed in atypical real estate markets.

Recently, theoretical and empirical research on real estate has seen a great expansion, especially using the paradigms and methodologies of finance and economics.

The Special Issue is dedicated, but not only limited, to developing and disseminating knowledge related to most recent real estate evaluation methodologies applied in the fields of architecture and civil, building, and environmental and territorial engineering. Suitable works include studies on econometric models, building management, building costs, risk management and real estate appraisal, mass appraisal methods applied to real estate properties, urban and land economics, transport economics, the application of economics and financial techniques to real estate markets, the economic valuation of real estate investment projects, and the economic effects of building transformations or projects on the environment.

Prof.  Pierfrancesco De Paola
Prof. Vincenzo Del Giudice
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • building management
  • building costs
  • mass appraisal methods
  • econometric models
  • real estate risk management
  • economic valuation of real estate investment projects
  • real estate market
  • property
  • social housing
  • urban economics
  • land
  • transport economics
  • real estate economics
  • real estate finance
  • building transformations and economic effects on environment
  • projects and economic effects on environment

Published Papers (14 papers)

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Research

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Open AccessArticle Tripartite Efficacy Beliefs and Homeowner Participation in Multi-Owned Housing Governance
Sustainability 2018, 10(9), 3338; https://doi.org/10.3390/su10093338
Received: 2 August 2018 / Revised: 13 September 2018 / Accepted: 14 September 2018 / Published: 18 September 2018
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Abstract
Homeowners’ collective actions are essential for effective governance of multi-owned housing (MOH) and a city’s sustainable development. Yet, not all homeowners keenly participate in MOH governance. Unpacking why homeowners decide to participate is thus insightful. So far, little work has been done on
[...] Read more.
Homeowners’ collective actions are essential for effective governance of multi-owned housing (MOH) and a city’s sustainable development. Yet, not all homeowners keenly participate in MOH governance. Unpacking why homeowners decide to participate is thus insightful. So far, little work has been done on how perceived efficacies of property management agents (PMAs) shape collective actions in MOH governance. Founding upon the social cognitive theory and collective interest model, a theoretical model is built to empirically examine how proxy efficacy belief influences participation behaviors of homeowners. Drawing on the findings of a survey of 2035 homeowners in Hong Kong and Macau, this study reveals that participation level correlates positively with self and group efficacy beliefs but negatively with perceived proxy efficacy. Poor performance or incapacity of the PMAs triggers a higher degree of homeowner participation. The research findings have significant policy implications for promoting a better MOH upkeep culture. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
Open AccessArticle A Generalised Model of Ground Lease Pricing
Sustainability 2018, 10(9), 3203; https://doi.org/10.3390/su10093203
Received: 2 August 2018 / Revised: 4 September 2018 / Accepted: 4 September 2018 / Published: 7 September 2018
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Abstract
In this paper, we present a generalization of Mandell’s model for the estimation of ground lease pricing. We adjust the model so that it fits, in particular, the Polish legal regulations and situation of the Polish real estate market. The model involves two
[...] Read more.
In this paper, we present a generalization of Mandell’s model for the estimation of ground lease pricing. We adjust the model so that it fits, in particular, the Polish legal regulations and situation of the Polish real estate market. The model involves two aspects. The first is the perpetual usufruct, a form of owning the ground similar to a long-term lease, but having some specific features. The second is allowing lease rent adjustments after some fixed period, meaning we consider the situation where the payments are fixed during certain periods as defined in the contract. The proposed model determines the minimum lease amount for the owner, which is the rate at which it is beneficial to lease the property, and the maximum for the lessee, which is the amount above which the lease is unprofitable for the leaseholder or perpetual usufruct. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
Open AccessArticle Resampling Techniques for Real Estate Appraisals: Testing the Bootstrap Approach
Sustainability 2018, 10(9), 3085; https://doi.org/10.3390/su10093085
Received: 26 May 2018 / Revised: 13 August 2018 / Accepted: 14 August 2018 / Published: 30 August 2018
PDF Full-text (1462 KB) | HTML Full-text | XML Full-text
Abstract
Applied to real estate markets analysis, the resampling methods aim to contribute to the knowledge growth of real estate market dynamics, overcoming the issues related to the data scarcity and operational limits of traditional statistical theory. Among resampling methods, the Bootstrap technique appears
[...] Read more.
Applied to real estate markets analysis, the resampling methods aim to contribute to the knowledge growth of real estate market dynamics, overcoming the issues related to the data scarcity and operational limits of traditional statistical theory. Among resampling methods, the Bootstrap technique appears to be the most suitable for the interpretation of real estate phenomena. In this study, for residential properties located in Cosenza (Calabria Region, Italy), a Bootstrap approach has been used in order to determine the marginal prices of the real estate characteristics detected, comparing the results with those obtainable with a traditional Multiple Regression Analysis. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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Open AccessArticle Housing Vulnerability and Property Prices: Spatial Analyses in the Turin Real Estate Market
Sustainability 2018, 10(9), 3068; https://doi.org/10.3390/su10093068
Received: 29 June 2018 / Revised: 31 July 2018 / Accepted: 10 August 2018 / Published: 28 August 2018
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Abstract
In the literature, several vulnerability/resilience indicators and indexes are based and assessed by taking into account and combining different dimensions. Housing vulnerability is one of these dimensions and is strictly related to the buildings’ physical features and to the socio-economic condition of their
[...] Read more.
In the literature, several vulnerability/resilience indicators and indexes are based and assessed by taking into account and combining different dimensions. Housing vulnerability is one of these dimensions and is strictly related to the buildings’ physical features and to the socio-economic condition of their occupants. This research aims to study housing vulnerability in relation to the real estate market by identifying possible indicators and spatially analyzing their influence on property prices. Assuming the city of Turin and its territorial segmentation as a case study, spatial analyses were performed to take into account the presence of spatial dependence and to identify the variables that significantly influence the process of property price determination. The results of this study highlighted the fact that two housing vulnerability indicators, representative of fragile buildings’ physical features, were spatially correlated with property prices and had a significant and negative influence on them. In addition, their comparison with two social vulnerability indicators demonstrated that the presence of economical buildings and council houses was spatially correlated with the presence of people with a low education level. The results of the spatial regression model also confirmed that one of the social vulnerability indicators had the highest and most negative explanatory power in the property price determination process. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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Open AccessArticle Values, Memory, and the Role of Exploratory Methods for Policy-Design Processes and the Sustainable Redevelopment of Waterfront Contexts: The Case of Officine Piaggio (Italy)
Sustainability 2018, 10(9), 2989; https://doi.org/10.3390/su10092989
Received: 15 July 2018 / Revised: 18 August 2018 / Accepted: 20 August 2018 / Published: 22 August 2018
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Abstract
In the last few decades the renewal of waterfront contexts has been especially inspired by neoliberal approaches favoring the creation of residential units and entertainment facilities. However, sustainability frameworks suggest that the economic dimension should be interpreted in a way that goes beyond
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In the last few decades the renewal of waterfront contexts has been especially inspired by neoliberal approaches favoring the creation of residential units and entertainment facilities. However, sustainability frameworks suggest that the economic dimension should be interpreted in a way that goes beyond the profitability of the interventions and that takes into account non-monetary values as well. In light of the complex social value (CSV) theory—which considers as a fundamental value component the intrinsic values attributed by communities to environmental and cultural heritage resources—this article proposes the adoption of exploratory methods to firstly map and then integrate citizens’ points of view into the evaluation and design of redevelopment scenarios, selecting the ex-industrial complex of Officine Piaggio (Italy) as a case study. Survey results highlighted that discrepancies between the new functions advanced by official redevelopment proposals and citizens’ opinions were present, and that values such as memory and collective meaning need to be considered if multidimensional sustainability represents a goal. Coherent with these results, a new project scenario is then envisioned and implications related to the application of exploratory methods in the decision-making and policy-design processes are finally advanced. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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Open AccessArticle Managing Bubbles in the Korean Real Estate Market: A Real Options Framework
Sustainability 2018, 10(8), 2875; https://doi.org/10.3390/su10082875
Received: 16 July 2018 / Revised: 5 August 2018 / Accepted: 10 August 2018 / Published: 13 August 2018
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Abstract
The aim of this paper is to propose a real options framework to measure and manage bubbles in the Korean real estate market. The proposed framework carefully defines and utilizes the unique leasing mechanism in Korea, called the Jeonse system, a tentative contract
[...] Read more.
The aim of this paper is to propose a real options framework to measure and manage bubbles in the Korean real estate market. The proposed framework carefully defines and utilizes the unique leasing mechanism in Korea, called the Jeonse system, a tentative contract for one or two years with a large amount of deposit, to represent the value of residence. Furthermore, the proposed framework applies the volatility with heteroscedasticity to improve the numerical accuracy in comparison to the traditional real options valuation model. The results of the model ultimately suggest the investment strategy that takes into account the measured bubbles in the market. Specifically, given that the Korean real estate market could be regarded as an American option, the investment strategy with early exercise completely eliminates the existing arbitrage opportunities in both long and short positions. In this context, the investment decisions based on the results of the proposed framework are expected to encourage the reflection of bubble-related information in the market, which eventually reduces the formation of bubbles via market mechanism for arbitrage elimination. In conclusion, the bubble-related information obtained from the model is expected to contribute to the stability of the real estate market by reducing the volatility of house price and quick price adjustment to new information. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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Open AccessArticle Research on the Influence of Real Estate Development on Private Investment: A Case Study of China
Sustainability 2018, 10(8), 2659; https://doi.org/10.3390/su10082659
Received: 28 June 2018 / Revised: 19 July 2018 / Accepted: 25 July 2018 / Published: 28 July 2018
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Abstract
Private investment in China, as a developing country, is an important source of financing for Chinese SMEs (Small and Medium-Size Enterprises) and has played a major role in the development of the real economy. However, in 2016, the growth rate of private investment
[...] Read more.
Private investment in China, as a developing country, is an important source of financing for Chinese SMEs (Small and Medium-Size Enterprises) and has played a major role in the development of the real economy. However, in 2016, the growth rate of private investment in China dropped from 10.18% to 3.17%, which had a significant impact on the real economy. At the same time, China’s real estate market has developed rapidly, attracting a large number of capital inflows. The relationship between real estate development and private investment in China is worth considering. This study first, theoretically analyzes the influence mechanism of real estate industry on private investment, pointing out that within a modest development range, the development of real estate industry can promote private investment through the industrial linkage, urbanization, and balance sheet effects, but when real estate is overdeveloped, it has an inhibitory effect on private investment through vampire effect, raising costs and reducing demand effect. In other words, real estate has different effects on private investment in different developmental periods. Therefore, there is a non-linear relationship between the two variables. Second, the relevant provincial panel data of 31 provinces in mainland China from 2003 to 2015 were selected. Using the dynamic panel system Generalized Method of Moments (GMM), this study estimated the correlation between real estate development and private investment. The empirical results showed that the development of the real estate industry has a significant impact on the level of private investment; the two showing an “inverted U-shaped” relationship. At present, in some provinces in China, the real estate industry has exceeded the inverted U-shaped threshold. To boost the vitality of private investment in promoting real economic growth, the development of the real estate industry should be restricted, and house prices should be properly regulated. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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Open AccessArticle Economic–Environmental Sustainability in Building Projects: Introducing Risk and Uncertainty in LCCE and LCCA
Sustainability 2018, 10(6), 1901; https://doi.org/10.3390/su10061901
Received: 10 May 2018 / Revised: 31 May 2018 / Accepted: 1 June 2018 / Published: 6 June 2018
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Abstract
The aim of this paper is to propose a methodology for supporting decision-making in the design stages of new buildings or in the retrofitting of existing heritages. The focus is on the evaluation of economic–environmental sustainability, considering the presence of risk and uncertainty.
[...] Read more.
The aim of this paper is to propose a methodology for supporting decision-making in the design stages of new buildings or in the retrofitting of existing heritages. The focus is on the evaluation of economic–environmental sustainability, considering the presence of risk and uncertainty. An application of risk analysis in conjunction with Life-Cycle Cost Analysis (LCCA) is proposed for selecting the preferable solution between technological options, which represents a recent and poorly explored context of analysis. It is assumed that there is a presence of uncertainty in cost estimating, in terms of the Life-Cycle Cost Estimates (LCCEs) and uncertainty in the technical performance of the life-cycle cost analysis. According to the probability analysis, which was solved through stochastic simulation and the Monte Carlo Method (MCM), risk and uncertainty are modeled as stochastic variables or as “stochastic relevant cost drivers”. Coherently, the economic–financial and energy–environmental sustainability is analyzed through the calculation of a conjoint “economic–environmental indicator”, in terms of the stochastic global cost. A case study of the multifunctional building glass façade project in Northern Italy is proposed. The application demonstrates that introducing flexibility into the input data and the duration of the service lives of components and the economic and environmental behavior of alternative scenarios can lead to opposite results compared to a deterministic analysis. The results give full evidence of the environmental variables’ capacity to significantly perturb the model output. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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Open AccessArticle Optimal Cost–Quality Trade-Off Model for Differentiating Presale Housing Quality Strategies
Sustainability 2018, 10(3), 680; https://doi.org/10.3390/su10030680
Received: 14 January 2018 / Revised: 27 February 2018 / Accepted: 27 February 2018 / Published: 2 March 2018
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Abstract
Housing quality (HQ) has been a long-standing concern for both developers and homebuyers. Currently, HQ depends on the expected profit and subjectivity of the developers, and homebuyers only have a passive choice of whether to accept housing with such quality. Asian housing supply
[...] Read more.
Housing quality (HQ) has been a long-standing concern for both developers and homebuyers. Currently, HQ depends on the expected profit and subjectivity of the developers, and homebuyers only have a passive choice of whether to accept housing with such quality. Asian housing supply markets have largely adopted the presale housing system. Under this system, developers are able to verify future occupants before commencing construction, enabling them to provide customized designs and differentiated quality items in order to meet user demands and value. Consequently, HQ can be enhanced. A cost–quality trade-off model was developed using a genetic algorithm to help decision-makers identify the optimal HQ differentiation strategy that simultaneously satisfies homebuyers’ expectations of quality and developers’ expectations of profits. The findings showed that the presale housing system effectively improves HQ. A 6% increase in homebuyers’ budgets can achieve the optimal quality improvement effect, while an 8% or more increase in developers’ construction costs in order to improve HQ can generate an additional premium for the developers. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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Open AccessArticle A Methodology for the Selection of Multi-Criteria Decision Analysis Methods in Real Estate and Land Management Processes
Sustainability 2018, 10(2), 507; https://doi.org/10.3390/su10020507
Received: 15 December 2017 / Revised: 9 February 2018 / Accepted: 10 February 2018 / Published: 13 February 2018
Cited by 2 | PDF Full-text (562 KB) | HTML Full-text | XML Full-text
Abstract
Real estate and land management are characterised by a complex, elaborate combination of technical, regulatory and governmental factors. In Europe, Public Administrators must address the complex decision-making problems that need to be resolved, while also acting in consideration of the expectations of the
[...] Read more.
Real estate and land management are characterised by a complex, elaborate combination of technical, regulatory and governmental factors. In Europe, Public Administrators must address the complex decision-making problems that need to be resolved, while also acting in consideration of the expectations of the different stakeholders involved in settlement transformation. In complex situations (e.g., with different aspects to be considered and multilevel actors involved), decision-making processes are often used to solve multidisciplinary and multidimensional analyses, which support the choices of those who are making the decision. Multi-Criteria Decision Analysis (MCDA) methods are included among the examination and evaluation techniques considered useful by the European Community. Such analyses and techniques are performed using methods, which aim to reach a synthesis of the various forms of input data needed to define decision-making problems of a similar complexity. Thus, one or more of the conclusions reached allow for informed, well thought-out, strategic decisions. According to the technical literature on MCDA, numerous methods are applicable in different decision-making situations, however, advice for selecting the most appropriate for the specific field of application and problem have not been thoroughly investigated. In land and real estate management, numerous queries regarding evaluations often arise. In brief, the objective of this paper is to outline a procedure with which to select the method best suited to the specific queries of evaluation, which commonly arise while addressing decision-making problems. In particular issues of land and real estate management, representing the so-called “settlement sector”. The procedure will follow a theoretical-methodological approach by formulating a taxonomy of the endogenous and exogenous variables of the multi-criteria analysis methods. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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Open AccessArticle Immigration and the Housing Market: The Case of Castel Volturno, in Campania Region, Italy
Sustainability 2018, 10(2), 343; https://doi.org/10.3390/su10020343
Received: 16 December 2017 / Revised: 24 January 2018 / Accepted: 26 January 2018 / Published: 29 January 2018
Cited by 2 | PDF Full-text (4631 KB) | HTML Full-text | XML Full-text
Abstract
According to Eurostat, Italy is the fifth country of the European Union per immigrant population. The complexity of the phenomenon, as it has evolved in recent years, leads to analyzing it from a specific point of view, that of the real estate market.
[...] Read more.
According to Eurostat, Italy is the fifth country of the European Union per immigrant population. The complexity of the phenomenon, as it has evolved in recent years, leads to analyzing it from a specific point of view, that of the real estate market. The article represents the early stage of research on the housing condition of the immigrant population in the Southern Italy and its effect on the housing market. First, we describe the spatial segregation phenomenon affecting the immigrant population in Campania Region; then we analyze data of the municipality of Castel Volturno, which has one of the greater migratory pressure throughout the whole region. We provide statistical regressions correlating housing prices and socio-economic features from 2006 to 2016. The results confirm the findings of the current literature on the subject: there is a specific phenomenon associated with the presence of an immigrant population residing in conjunction with a reduction of housing prices. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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Open AccessArticle Have Housing Prices Gone with the Smelly Wind? Big Data Analysis on Landfill in Hong Kong
Sustainability 2018, 10(2), 341; https://doi.org/10.3390/su10020341
Received: 9 November 2017 / Revised: 16 January 2018 / Accepted: 24 January 2018 / Published: 29 January 2018
Cited by 2 | PDF Full-text (269 KB) | HTML Full-text | XML Full-text
Abstract
Unlike many other places around the globe, Hong Kong is a small city with a high population density. Some housing units are built near the sources of an externality, such as a landfill site. As the blocks of buildings are particularly tall, many
[...] Read more.
Unlike many other places around the globe, Hong Kong is a small city with a high population density. Some housing units are built near the sources of an externality, such as a landfill site. As the blocks of buildings are particularly tall, many are walled buildings that block the bad odor from the landfill. Thus, the wind blowing from a landfill site may not affect the entire building estate. Some buildings are more heavily affected than others, partly because walled buildings built near landfills are rare. Only a few studies currently examine the correlation between wind direction and the prices of walled buildings. In this paper, we aim to bridge this research gap by illustrating Hong Kong as a case study. Most previous research studies only examine a few factors affecting housing prices. Modern big data is characterized by its large volume of data, which includes various types of data that analysts would not necessarily sample, but instead merely observe to track what happens. Therefore, another innovative point of our paper, is that we adopt a big data approach to study this issue. In this aspect, this paper is the first of its kind. There are 53,071 observations in the 1999 to 2014 dataset, with 2,175,911 data entries. Our results reflect that when more municipal solid waste is sent to the South East New Territories Landfill, residents’ complaints in Tseung Kwan O increase. However, entire property prices in the region also increase, which rejects our hypothesis. We speculate that as more people become aware of the housing estate due to complaints, with only a limited number of housing units affected by the smell, since the wind usually only blows in certain directions, the “advertisement effect” originating from complaints about the bad smell boosts the property prices of the unaffected units. That is, people become aware of the existence of the property, visit the site, and discover that only specific units facing one particular direction are affected. Then, they purchase units that are unaffected by the smelly wind, leading to an overall increase in property prices. The study’s results may provide a new perspective on urban planning, and possible implications for other cities in view of the constant increase in population and expansion of landfill sites. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
Open AccessArticle Real Estate Appraisals with Bayesian Approach and Markov Chain Hybrid Monte Carlo Method: An Application to a Central Urban Area of Naples
Sustainability 2017, 9(11), 2138; https://doi.org/10.3390/su9112138
Received: 15 August 2017 / Revised: 12 November 2017 / Accepted: 15 November 2017 / Published: 21 November 2017
Cited by 4 | PDF Full-text (401 KB) | HTML Full-text | XML Full-text
Abstract
This paper experiments an artificial neural networks model with Bayesian approach on a small real estate sample. The output distribution has been calculated operating a numerical integration on the weights space with the Markov Chain Hybrid Monte Carlo Method (MCHMCM). On the same
[...] Read more.
This paper experiments an artificial neural networks model with Bayesian approach on a small real estate sample. The output distribution has been calculated operating a numerical integration on the weights space with the Markov Chain Hybrid Monte Carlo Method (MCHMCM). On the same real estate sample, MCHMCM has been compared with a neural networks model (NNs), traditional multiple regression analysis (MRA) and the Penalized Spline Semiparametric Method (PSSM). All four methods have been developed for testing the forecasting capacity and reliability of MCHMCM in the real estate field. The Markov Chain Hybrid Monte Carlo Method has proved to be the best model with an absolute average percentage error of 6.61%. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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Review

Jump to: Research

Open AccessReview A Systematic Review of Smart Real Estate Technology: Drivers of, and Barriers to, the Use of Digital Disruptive Technologies and Online Platforms
Sustainability 2018, 10(9), 3142; https://doi.org/10.3390/su10093142
Received: 15 August 2018 / Revised: 28 August 2018 / Accepted: 30 August 2018 / Published: 3 September 2018
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Abstract
Real estate needs to improve its adoption of disruptive technologies to move from traditional to smart real estate (SRE). This study reviews the adoption of disruptive technologies in real estate. It covers the applications of nine such technologies, hereby referred to as the
[...] Read more.
Real estate needs to improve its adoption of disruptive technologies to move from traditional to smart real estate (SRE). This study reviews the adoption of disruptive technologies in real estate. It covers the applications of nine such technologies, hereby referred to as the Big9. These are: drones, the internet of things (IoT), clouds, software as a service (SaaS), big data, 3D scanning, wearable technologies, virtual and augmented realities (VR and AR), and artificial intelligence (AI) and robotics. The Big9 are examined in terms of their application to real estate and how they can furnish consumers with the kind of information that can avert regrets. The review is based on 213 published articles. The compiled results show the state of each technology’s practice and usage in real estate. This review also surveys dissemination mechanisms, including smartphone technology, websites and social media-based online platforms, as well as the core components of SRE: sustainability, innovative technology and user centredness. It identifies four key real estate stakeholders—consumers, agents and associations, government and regulatory authorities, and complementary industries—and their needs, such as buying or selling property, profits, taxes, business and/or other factors. Interactions between these stakeholders are highlighted, and the specific needs that various technologies address are tabulated in the form of a what, who and how analysis to highlight the impact that the technologies have on key stakeholders. Finally, stakeholder needs as identified in the previous steps are matched theoretically with six extensions of the traditionally accepted technology adoption model (TAM), paving the way for a smoother transition to technology-based benefits for consumers. The findings pertinent to the Big9 technologies in the form of opportunities, potential losses and exploitation levels (OPLEL) analyses highlight the potential utilisation of each technology for addressing consumers’ needs and minimizing their regrets. Additionally, the tabulated findings in the form of what, how and who links the Big9 technologies to core consumers’ needs and provides a list of resources needed to ensure proper information dissemination to the stakeholders. Such high-quality information can bridge the gap between real estate consumers and other stakeholders and raise the state of the industry to a level where its consumers have fewer or no regrets. The study, being the first to explore real estate technologies, is limited by the number of research publications on the SRE technologies that has been compensated through incorporation of online reports. Full article
(This article belongs to the Special Issue Real Estate Economics, Management and Investments)
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