Artificial intelligence in real estate market analysis

Kabaivanov, Stanimir; Markovska, Veneta

doi:10.1063/5.0041806

Cited by 14 publications

(11 citation statements)

References 13 publications

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“…As observed by Kabaivanov and Markovska (2021), the abundance of information on real estate markets and transactions requires sophisticated machine learning (ML) analytical tools such as artificial intelligence for data optimization and improvement. Conway (2018) expressed that today's real estate market challenges are becoming more complex, the use of artificial intelligence (AI) approach to solving the emerging challenges will help the sector to be more proactive, efficient and data-driven in all aspects including property/project/facility management, valuation/appraisal, investment decision and physical development process.…”

Section: Applications Of Artificial Intelligence (Ai) To Real Estate Market Analyses a Systematic Review Of Literaturementioning

confidence: 99%

“…However, to ensure the security and safety of the huge capital invested, grow expected on return, minimise risk, boost investor's confidence and pull investors across the globe, there is a need for a sustainable real estate market that is strongly driven by real-time data, technology innovations, ICT compliant and sophisticated market analytical model. However, one of the pragmatic approaches of achieving sustainable real estate market analyses is the application of artificial intelligence (AI) analytical tools which have been proved to be reliable, yielding a better and accurate results in the areas of market appraisal, trend analysis and forecasting (Taffese, 2006;Kabaivanov and Markovska, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Application of Artificial Intelligence (AI) Approach to African Real Estate Market Analysis Opportunities and Challenges

Odunfa¹,

Fateye²,

Adewusi³

2021

AIMS Research Publication

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The information on the real estate market is fast growing and becoming more complex to analyse. Therefore there is a need for reliable real estate market analysis for an informed and handsome investment decision making. The study examines the opportunities and challenges of using artificial intelligence (AI) approaches to analyse quantitative / data on the Africa real estate market. A systematic review of the literature was conducted. The study found some opportunities characterised by the usage of AI tools to include a reliable forecasting model, good predictive power, ability to perform complex tasks and analyses of a large number of variables. The major constraints of AI tools application in the study area include knowledge gap, weak political will, unstable economic conditions, low level of market transparency, maturity, openness and lack of availability and reliable data and research on the Africa real estate market analysis (AREMA). The study concluded that the Africa real estate market is yet to be ready for the adoption of hi-tech market analysis devices such as AI and machine learning (ML) due to lack of availability and reliable data. However, the study suggests a strong collaboration and cooperation between the public and private sectors to create enabling real estate business environment that prioritises technology infrastructure, data-driven property market and reliable databank to achieve a sustainable Africa real estate market analysis for an informed investment decision. Keywords: Artificial Intelligence (AI), Africa, Real Estate, Market Analysis, Opportunities, Challenges, Analysis, Data, Environment.

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Section: Applications Of Artificial Intelligence (Ai) To Real Estate Market Analyses a Systematic Review Of Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of Artificial Intelligence (AI) Approach to African Real Estate Market Analysis Opportunities and Challenges

Odunfa¹,

Fateye²,

Adewusi³

2021

AIMS Research Publication

View full text Add to dashboard Cite

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“…Rather, they adopt the variables recognised from current studies that fail to include local contents specific to the Nigerian marketplace such as Oyewole and Ajayi (2016) and Udoekanem et al (2015b). Meanwhile, researchers have acknowledged that price-determining factors fluctuate among real estate sectors (Sanderson, 2015), vary among locations ( € Oven and Pekdemir, 2006b; Bera and Kangalli Uyar, 2019) and vary overtime (Kabaivanov and Markovska, 2021), and hence, they are not static. Thus, there is a need to explore local experts' views towards ascertaining the specific price-influencing variables in northern Nigeria.…”

Section: Introductionmentioning

confidence: 99%

An analysis of the determinants of office real estate price modelling in Nigeria: using a Delphi approach

Yakub

Achu

Ali

et al. 2022

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PurposeThere are a plethora of putative influencing variables available in the literature for modelling real estate prices using AI. Their choice tends to differ from one researcher to the other, consequently leading to subjectivity in the selection process. Thus, there is a need to seek the viewpoint of practitioners on the applicability and level of significance of these academically established variables.Design/methodology/approachUsing the Delphi technique, this study collated and structured the 35 underlying micro- and macroeconomic parameters derived from literature and eight variables suggested by 11 selected real estate experts. The experts ranked these variables in order of influence using a seven-point Likert scale with a reasonable consensus during the fourth round (Kendall's W = 0.7418).FindingsThe study discovered that 16 variables are very influential with seven being extremely influential. These extremely influential variables include flexibility, adaptability of design, accessibility to the building, the size of office spaces, quality of construction, state of repairs, expected capital growth and proximity to volatile areas.Practical implicationsThe results of this study improve the quality of data available to valuers towards a fortified price prediction for investors, and thereby, restoring the valuers' credibility and integrity.Originality/valueThe “volatility level of an area”, which was revealed as a distinct factor in the survey is used to add to current knowledge concerning office price. Hence, this study offers real estate practitioners and researchers valuable knowledge on the critical variables that must be considered in AI-based price modelling.

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“…Nanda et al (2021) emphasized the role of technology and digitalization in overcoming the disruptions and risks initiated by the pandemic. Kabaivanov and Markovska (2021) assessed the role of artificial intelligence (AI) in the real estate market, suggesting and testing a three-stage model for market forecasting and real estate valuation that accounts for individual characteristics and global economic factors that influence property prices. Regarding the real estate sector, Nanda et al (2021) emphasized that technology can offer various benefits in addressing the challenges associated with spatial inequalities and urbanization.…”

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confidence: 99%

“…The introduction of mobile technologies and the Internet created massive changes across all sectors. A large quantity of information concerning real estate markets and transactions is available, to which AI and machine learning can offer valuable help in analyzing and processing (Kabaivanov & Markovska, 2021), increasing efficiency, reducing costs, can decrease delays in the planning processes, assist with accurate performance measurement, identify areas and needs of development, reduce the possibility of wild speculation, etc. The development of services, products, and tools with investment in technology can be sustainable and useful concerning revenue and profits (Nanda et al, 2021).…”

mentioning

confidence: 99%

Property Management Enabled by Artificial Intelligence Post Covid-19: An Exploratory Review and Future Propositions

Naz

Upadhyay

Chokshi

et al. 2022

International Journal of Strategic Property Management

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The Covid-19 pandemic outbreak across the globe has disrupted human life and industry. The pandemic has affected every sector, with the real estate sector facing particular challenges. During the pandemic, property management became a crucial task and property managers were challenged to control risks and disruptions faced by their organizations. Recent innovative technologies, including artificial intelligence (AI), have supported many sectors through sudden disruptions; this study was performed to examine the role of AI in the real estate and property management (PM) sectors. For this purpose, a systematic literature review was conducted using structural topic modeling and bibliometric analysis. Using appropriate keywords, the researchers found 175 articles on AI and PM research from 1980 to 2021 in the SCOPUS database. A bibliometric analysis was performed to identify research trends. Structural topic modelling (STM) identified ten emerging thematic topics in AI and PM. A comprehensive framework is proposed, and future research directions discussed.

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Artificial intelligence in real estate market analysis

Cited by 14 publications

References 13 publications

Application of Artificial Intelligence (AI) Approach to African Real Estate Market Analysis Opportunities and Challenges

Application of Artificial Intelligence (AI) Approach to African Real Estate Market Analysis Opportunities and Challenges

An analysis of the determinants of office real estate price modelling in Nigeria: using a Delphi approach

Property Management Enabled by Artificial Intelligence Post Covid-19: An Exploratory Review and Future Propositions

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