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Computational Approach Applications in Housing and Real Estate

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A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 13801

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Dr. Natalija Lepkova

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Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius, Lithuania
Interests: facilities management; BIM applications in facilities management; quality management systems; real estate management; new technologies in facilities management
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Special Issue Information

Dear Colleagues,

Property-related activities are highly diverse and involve, in addition to property management, planning, financing and construction activities, valuation, facilities management, and consultation or brokerage services. The real estate sector has a higher economic importance than other sectors such as the automotive industry and the healthcare sector. It makes a major contribution to GDP in the European Union and provides prosperity and jobs. Real estate represents the majority of the existing real capital and is also particularly relevant because of its additional function as a provision for old age and protection against inflation (European Real Estate Forum, 2022).

According to Eurostat, the real estate activities sector accounted for 1.9 % of total employment in the EU in 2019, and the real estate activities sector accounted for 5.7 % of the total number of enterprises in the EU in 2019 (Eurostat, May 2022).

Housing is a key input in economic, social, and civic development. Many housing-related activities are known to contribute directly to achieving broader socio-economic development goals. Housing investment remains valuable and is a major economic driver in both developed and developing countries.

This Special Issue aims to publish high-quality research papers on the inter-disciplinary field of Computational Applications in Housing and Real Estate.

We look forward to receiving your papers!

Dr. Natalija Lepkova
Guest Editor

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 submissions that pass pre-check are 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. Buildings 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 2600 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

housing
real estate
blockchain
computational approach
computational valuation
data analysis
BIM
facilities management
built environment
maintenance

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Published Papers (6 papers)

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Research

31 pages, 6385 KiB

Open AccessArticle

Dynamics of the Inflation-Hedging Capabilities of Real Estate Investment Portfolios in the Nigerian Property Market

by Akuakanwa Eziukwu Nwosu, Victoria Amietsenwu Bello, Abiodun Kolawole Oyetunji and Chiemela Victor Amaechi

Buildings 2024, 14(1), 72; https://doi.org/10.3390/buildings14010072 - 26 Dec 2023

Cited by 1 | Viewed by 2520

Abstract

There has been a wide belief that real estate is a source of good investment portfolios because it has a hedge against inflation. Considering this notion, the present research examined the dynamics of the inflation-hedging capabilities of real estate investment in Nigeria’s three foremost property markets, Abuja (Maitama and Central Business District), Lagos (Lekki and Victoria Island), and Port Harcourt (Rumu Ibekwe and Aba Road). To achieve this aim, this study was carried out by exploring the returns on different types of commercial properties in the chosen location and investigating the effect of inflation on such returns in order to come up with the hedging capabilities of the assets. Out of the four property prime locations in Nigeria’s market, these selected study sites were purposely selected for investigation because they comprise the most desirable and preferred properties regarding location, standards, aesthetics, and value. From the data collected, a mean return, coefficient of variation, and ordinary least square regression analysis were completed. In terms of the coefficient of variation (CV), the findings reveal that the duplex in Port Harcourt exhibits the most performed investment, with a value of 0.33, compared to other locations. However, in terms of the expected return (ER), the duplex outperformed other property types in the different locations, with a return of 39.56%. Results also show that inflation has an adverse effect on the returns of the office space for the three locations considered, with the expected returns below 1%. The block of flats in Abuja has a complete defence against the three components of inflation, with a coefficient beta of 0.5633, 0.6586, and 0.8440, respectively. Thus, investors should consider inflation and other investment attributes when making decisions among arrays of investments. This will help guard against the widespread perception that real estate has a hedge against inflation. This paper adds to the existing literature on inflation hedging by investigating the effect of inflation on the real estate investment returns of commercial properties. Full article

(This article belongs to the Special Issue Computational Approach Applications in Housing and Real Estate)

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19 pages, 1278 KiB

Open AccessArticle

Prediction of Maintenance Activities Using Generalized Sequential Pattern and Association Rules in Data Mining

by Abbas Al-Refaie, Banan Abu Hamdieh and Natalija Lepkova

Buildings 2023, 13(4), 946; https://doi.org/10.3390/buildings13040946 - 3 Apr 2023

Cited by 8 | Viewed by 2103

Abstract

This study proposed a data mining framework for predicting sequential patterns of maintenance activities. The framework consisted of data collection, prediction of maintenance activities with and without attributes, and then the comparison between prediction results. In data collection, historical data were collected regarding maintenance activities and product attributes. The generalized sequential pattern (GSP) and association rules were then applied to predict maintenance activities with and without attributes to determine the frequent sequential patterns and significant rules of maintenance activities. Finally, a comparison was performed between the sequences of maintenance activities with and without attributes. A real case study of washing machine products was presented to illustrate the developed framework. The results showed that the proposed framework effectively predicted the next maintenance activities and planning preventive maintenance based on product attributes. In conclusion, the data mining approach is found effective in determining the maintenance sequence that reduces downtime and thereby enhancing productivity and availability. Full article

(This article belongs to the Special Issue Computational Approach Applications in Housing and Real Estate)

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22 pages, 5329 KiB

Open AccessArticle

A Proposed eFSR Blockchain System for Optimal Planning of Facility Services with Probabilistic Arrivals and Stochastic Service Durations

by Abbas Al-Refaie and Ahmad Al-Hawadi

Buildings 2023, 13(1), 240; https://doi.org/10.3390/buildings13010240 - 14 Jan 2023

Cited by 6 | Viewed by 1776

Abstract

This research developed a framework for electronic planning and management of facility services utilizing blockchain technology. In this framework, an electronic Facility Service Record (eFSR) in blockchain form was developed to manage and control service orders received by its main service center from university facilities via an electronic system. Mathematical models were formulated to determine the optimal schedule and sequence of facility services under probabilistic service order arrivals and stochastic service durations. Each task of a facility service is treated as a block. The scheduling model then assigned blocks (service tasks) to skilled technicians on each scheduling period at a minimal total cost of delay, undertime, and overtime costs, while the sequencing model determined the start and finish times of each block during the planning period. The optimal information of blocks was then confirmed and shared through an electronic network among all relevant facilities and the service center. The developed framework was implemented in university facilities to plan and manage 47 service orders for a total of 140 tasks over a period of twelve days. The results showed that the proposed eFSR is effective in managing optimal service tasks and efficient in improving the utilization and performance of the service center resources. In conclusion, the proposed eFSR with the optimal facility service planning provides real-time assistance and decentralized technology to facilities managers when planning service tasks over multiple periods. These advantages will result in the effective management of facilities and a considerable savings in maintenance resources. Full article

(This article belongs to the Special Issue Computational Approach Applications in Housing and Real Estate)

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31 pages, 5874 KiB

Open AccessArticle

Dynamics, Risk and Management Performance of Urban Real Estate Inventory in Yangtze River Delta

by Ping Zhang, Hua Chen, Kaixu Zhao, Sidong Zhao and Weiwei Li

Buildings 2022, 12(12), 2140; https://doi.org/10.3390/buildings12122140 - 5 Dec 2022

Cited by 5 | Viewed by 2057

Abstract

(1) Background: Inventory management is a key point in the achievement of the virtuous cycle and sustainable development of the real estate industry. In response to the practical needs of city-based policies, this paper constructs a new research approach of “evolution dynamics—risk analysis—performance evaluation—policy design” of real estate inventory, and conducts a case study on the Yangtze River Delta. (2) Methods: This paper studies the change characteristics, trends and spatial patterns of real estate inventory changes in the Yangtze River Delta based on Geographic Information System software, and quantitatively evaluates the risk level and management performance of real estate inventory by introducing the Boston Consulting Group Matrix for corporate management and the Super- Data Envelopment Analysis Model for operations research, providing a basis for policy design. (3) Results: First, the “destocking” policy has gained results to some extent and diversified the inventory evolution, thus alleviating or curbing the negative trend in most cities. Second, the real estate inventory in the Yangtze River Delta is divided into high, low, potential and zero pressure zones by risk levels, and the proportion of cities with increased, decreased and unchanged risk levels is essentially the same. Third, the average real estate inventory management performance index has been steadily improving, but overall, it is still unsatisfactory, with cities in an effective state accounting for 40% and below for a long time. Fourth, real estate inventory and its management performance both show significant spatial effects, with cold and hot spot cities characterized by a “center-periphery” spatial pattern in geographical distribution, and the cities in the study area are classified into four types: super-efficiency, efficiency, inefficiency, and super-inefficiency. Fifth, the real estate inventory in most cities is continuing to grow positively, and a small number of cities have been in the high-risk zone for a long time or become new members of the high-risk zone, making the government and enterprises still faced up with great pressure and challenges in inventory management with the risk level further increased but management performance growing slowly. (4) Conclusions: The study area is divided into four types of policy areas, that is, red key area, yellow important area, green auxiliary area, and path-dependent area, and suggestions for optimization are made from the perspectives of risk control, performance improvement, benchmarking recommendation, and redundancy governance, providing a basis for the government’s real estate inventory management policy design and the enterprise’s high-quality development decision. Full article

(This article belongs to the Special Issue Computational Approach Applications in Housing and Real Estate)

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20 pages, 5108 KiB

Open AccessArticle

Blockchain Design with Optimal Maintenance Planning

by Abbas Al-Refaie, Ahmad Al-Hawadi and Natalija Lepkova

Buildings 2022, 12(11), 1902; https://doi.org/10.3390/buildings12111902 - 6 Nov 2022

Cited by 7 | Viewed by 1837

Abstract

Rapid advancement of data management and sharing technology has urged organizations to develop effective maintenance management systems. This research, therefore, proposes and implements an Electronic Repair Records (ERR) system for the blockchain of maintenance planning and management. In ERR, this research develops two optimization models for scheduling and sequencing failure repairs from different types over multiple periods. Each failure repair is treated as a block, for which the data, current hash, and previous hash are obtained from failure repair parameters, resources availability information, and the optimal values of the start and finish times of the assigned failure repairs. The scheduling model assigns failure repairs to technicians and in maintenance shops on each scheduling period at a minimal total cost of delay, undertime, and overtime costs, while the sequencing model sequences the assigned failure repairs at minimal total overtime costs and minimum total repair start times. Once the blocks are confirmed, the blockchain is then shared through an electronic network among all maintenance departments. The developed ERR system was implemented to manage the repairs of 36 failures from different failures in six maintenance shops over a period of three days. The results showed that this system is found to be effective in managing optimal repairs and efficient in improving the utilization of available resources in maintenance shops. These advantages may result in significant savings in maintenance costs and better utilization of resources. In conclusion, the developed ERR system including the optimization models can provide in real-time assistance and de-centralized technology to planning engineers when managing maintenance activities over multiple periods in a wide range of business applications. Full article

(This article belongs to the Special Issue Computational Approach Applications in Housing and Real Estate)

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28 pages, 3222 KiB

Open AccessArticle

Dynamics and Driving Mechanism of Real Estate in China’s Small Cities: A Case Study of Gansu Province

by Hua Chen, Sidong Zhao, Ping Zhang, Yong Zhou and Kerun Li

Buildings 2022, 12(10), 1512; https://doi.org/10.3390/buildings12101512 - 23 Sep 2022

Cited by 12 | Viewed by 2682

Abstract

(1) Background: China is beginning to see increasingly complex real estate development dynamics as urbanization, industrialization and globalization advance. As a key driver of economic and social development in China’s cities, real estate has created prosperity while facing the risk of capitalization and a “hard landing”, making it increasingly difficult to bring it under control. (2) Methods: a new approach that integrates “evolution dynamics–driving mechanism–policy design” is constructed based on the Boston Consulting Group matrix, exploratory spatial data analysis, GIS and Geodetector, and this paper empirically studies the dynamics and driving mechanism of real estate development based on the case study of small county-level cities in Gansu, China. (3) Results: Firstly, real estate development in Gansu is characterized by significant spatial differentiation, heterogeneity and autocorrelation, and its distribution pattern comes into being from unsynchronized macroeconomic, population, social, industrial, institutional and policy development interweaved with the real estate control. Secondly, the real estate is diversified in spatiotemporal evolution models, and the cold and hot cities of different models are in quite different geographical patterns with high spatial agglomeration. Thirdly, there are many driving factors affecting the distribution patterns in real estate. These factors are in complex relationships and they are classified into three categories of “Scale–Contribution–Comprehensive”-oriented driving factor and three sub-categories of “Key–Important–Auxiliary” factors. Fourthly, the factors show large differences in the interaction effects, with the real estate industry scale influencing factors being dominated by bifactor enhancement and the economic contribution influencing factors being dominated by non-linear enhancement. Notably, factors such as permanent resident population, urbanization and government revenue have a strong direct influence on the industry scale and economic contribution of real estate, and factors such as expenditure, output value of industry, urbanization rate and number of secondary schools all have a strong interactive influence. (4) Conclusions: The cities are divided into four policy areas of comprehensive development, contribution improvement, scale growth and free decision. Furthermore, differentiated and adaptive measures are proposed for each zoning, which significantly improves the accuracy and synergy of urban real estate management. Full article

(This article belongs to the Special Issue Computational Approach Applications in Housing and Real Estate)

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