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The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present 4IR era gave birth to big data sets and is beyond real estate professionals' analysis techniques. This has led to a situation where most real estate professionals rely on their intuition while neglecting a rigorous analysis for real estate investment appraisals. The heavy reliance on their intuition has been responsible for the under-performance of real estate investment, especially in Africa.

This study utilised a survey questionnaire to randomly source data from real estate professionals. The questionnaire was analysed using a combination of Statistical package for social science (SPSS) V24 and Analysis of a Moment Structures (AMOS) graphics V27 software. Exploratory factor analysis was employed to break down the variables (drivers) into meaningful dimensions helpful in developing the conceptual framework. The framework was validated using covariance-based structural equation modelling. The model was validated using fit indices like discriminant validity, standardised root mean square (SRMR), comparative fit index (CFI), Normed Fit Index (NFI), etc.

The model revealed that an inclusive educational system, decentralised real estate market and data management system are the major drivers for applying data science techniques to real estate professionals. Also, real estate professionals' application of the drivers will guarantee an effective data analysis of real estate investments.

Numerous studies have clamoured for adopting data science techniques for real estate professionals. There is a lack of studies on the drivers that will guarantee the successful adoption of data science techniques. A modern form of data analysis for real estate professionals was also proposed in the study.

With the increased demand for the application of technology in property activities, there is a growing need for property professionals adept in using digital technology. Hence, it is important to assess the competence of academia in equipping property professionals with digital technology skills. This study, therefore, assesses property academics in Australian universities to identify their level of knowledge and use of digital technology applicable to the property industry.

Online questionnaire surveys were administered to 22 out of 110 property academics contacted through the Australia Property Institute (API) database to achieve this aim. The collected data were analysed using mean score ranking and ANOVA.

The study found that apart from databases and analytics platforms such as Corelogic RP data, price finder and industry-based software such as the Microsoft Office suite and ARGUS software, the academics were not knowledgeable in most identified and sampled proptech tools. Similarly, most proptech tools were not used or taught to the students. It was also found that early career academics (below five years in academia) were the most knowledgeable group about the proptech tools.

Relying on the API database to contact property academics potentially excludes the position of property academics who may not be affiliated or have contacts with API, hence, the findings of this study should be generalised with caution.

The study bears huge implications for the property education sector and industry in Australia; a low knowledge and use of nascent tools such as artificial intelligence, machine learning, blockchain, drones, fintech, which have received intense interest, reveals some level of skill gap of students who pass through that system and may need to be upskilled by employers to meet the current day demand.

In response to the clamour for technology-inclined property professionals, this paper presents itself as the first to assess the knowledge levels and application of digital technology by property academics.

Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.

This paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.

Four domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.

This paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.

The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.

The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.

In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.

Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.

The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.

The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.

This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.

This study aims to merge the world’s proven ways of housing finance, including musharakah mutanaqisah, housing cooperatives and real estate crowdfunding, to present an alternative housing unaffordability solution based on the Islamic finance principle. It is intended to reduce the burden of funding for both sides (consumers and developers) and create win–win chances for all stakeholders, including intermediaries. By moving away from debt financing and merging the features of crowdfunding and cooperative, it is hopeful that the burden of home ownership will no longer be the case.

This paper presents the opinions of potential Chinese homebuyers (minority Muslims and most non-Muslims) and a few industry experts toward the proposed model via a mixed research method.

According to the findings, the majority of respondents agreed with the proposed paradigm. Just concerned that China’s lack of community culture and trust could pose a major threat to implementation. However, this paper argues that Chinese local governments may perform pilot testing in places where Islamic culture is prevalent. Their unique community culture and fundamental understanding of Shariah law may affect the viability of the proposed model.

The proposed model would increase the applicability of Islamic finance as a way of protecting the social order of communities in the spirit of upholding justice and fairness. A new type of housing loan based on musharakah mutanaqisah may squeeze out the real estate bubble and provide stakeholders with a multidimensional investment channel. In particular, the study identifies the impact of Chinese Islamic financing on government and cultural needs. It presents possible challenges for implementing the proposed model in reality and helps bridge the gap between theory and practice.

Over a long period, even low inflation has an impact on portfolio value and households’ purchasing power. In such a context, inflation hedging should remain an important issue for investors. In particular, long-term investors, who are concerned with the protection of their wealth, seek to hold effective hedging assets. This study aims to demonstrate that residential assets in “Grand Paris” are a hedge against inflation and particularly against its unexpected component.

In this study, the physical residential markets in 127 communes in Paris and the Parisian first-ring suburbs are considered as potential asset classes. We simplified the analysis by clustering the 127 communes into five homogenous groups using ascending hierarchical classification (AHC). Then, we test the hedging ability of these groups within a mixed asset portfolios using both correlation and regression analysis.

This paper presents an analysis of the “Grand Paris” housing market and its inflation hedging ability with comparison to other financial asset classes. Results show that the five housing groups act as a highly positive hedge against unexpected inflation. Furthermore, cash and bonds seem to provide, respectively, a partial and an over hedge against unexpected inflation. Stocks act as a perverse hedge against unexpected inflation and provide no significant hedge against expected inflation. Also, indirect listed real estate demonstrates little correlation with inflation, which makes us reject its hedging ability contrary to physical residential real estate.

The inflation topic: although several researches exist that question the hedging property of real estate, very few concentrate on physical residential assets and to the best of the authors’ knowledge, this study is the only one that targets the “Grand Paris” area. Residential assets of the “Grand Paris” communes are confirmed to be a hedge against inflation and particularly against its unexpected component thanks to its capital appreciation rather than income one. Also, we show that the listed real estate in France (Sociétés d’Investissement Immobilier Cotée) does not provide the same hedging properties contrary to the US real estate investment trusts (REITs) who demonstrate this ability. Listed real estate could thus not be used interchangeably with housing to protect from inflation in the French market.

Protection of investors against inflation and in particular in the face of its return to France in 2022. Reassuring promoters and investors of the interest of residential investment projects in “Greater Paris” and of the potential that this holds.

Inflation takes a chunk out of the purchasing power of money and thereby erodes the real value of people’s finance. Investors and households who seek protection from inflation erosion should invest in direct housing, and in particular within areas that are experiencing an effective metropolization process.

The originality of the study is precisely relative to the geographical area studied. The latter has experienced favorable economic conditions for several years and offers interesting fundamentals to explore and exploit in investment strategies that prove capable of protecting against imminent inflation. The database is specific to this project and has been built through the compilation of several sources and with the support of BNP Paribas Real Estate.

This study aims to enrich our understanding of the characteristics of non-urban coworking spaces (CSs) that focus on corporate users, as well as the benefits that companies expect to gain from incorporating those CSs into their corporate real estate (CRE) portfolios.

This study leverages a series of in-depth interviews with owners and managers of CSs in non-urban locales that focus on serving corporate clients.

The research reveals various CS characteristics and forms within non-urban areas, focusing on corporate clients. It suggests that implementing a CS in corporate premises is perceived to enhance CRE use-value strategies with a focus on the employee's well-being, innovation and the attraction of talents. Moreover, exchange-value strategies with a focus on portfolio flexibility may benefit from the implementation of a CS. However, strategies related to life-cycle cost optimization or gains are not perceived to be supported. Social events for the surrounding neighborhood and the choice of location emerge as critical success factors for non-urban CSs. Besides infrastructure and connectivity, non-urban corporate-centric CSs built their location decisions rather on a personal connection to the location and place of residence of potential users than on lower rental prices.

This research pioneers in providing a comprehensive understanding of non-urban CSs, particularly in the context of their perceived implications for corporate real estate management. The nuanced perspectives it offers are invaluable for stakeholders looking to leverage CSs as part of their corporate strategies.

The purpose of this paper is to describe an innovative approach to overcoming a common dilemma in designing negotiation simulations – that of situating a simulation in a real-life or fictitious context. This binary choice, which the authors call the negotiation designer’s dilemma, has profound implications for the types of learning activities and outcomes that can be integrated into the overall learning experience. As a way of overcoming the trade-offs inherent in this dilemma, the authors developed what they term hybrid simulations, which blend elements of fact and fiction in its contextual design in a particular way.

The authors were part of a negotiation simulation design team that used Design Thinking to understand the negotiation designer’s dilemma and to prototype and test a corresponding solution.

This paper demonstrates the benefits, potential applications and the how-to of hybrid simulations within the context of two such simulations the authors have designed at two different Swiss business schools. This paper concludes by discussing the potential and limitations for the application of hybrid simulations, as well as areas of potential further development.

The concept of a hybrid negotiation is a novel design trick that can be used in a variety of negotiation simulation contexts.

The study's objective was to address the factors impacting the employability attributes of fresh graduates in the Kingdom of Bahrain while considering the various challenges. This study used a quantitative approach which employed the questionnaire tool, and data were collected by using a convenience sampling method. The study sample comprised n = 385 respondents from different industries, including manufacturing, banking and finance, hospitality, healthcare, oil and gas, and real estate sectors of Bahrain. Data gathered from questionnaire were analyzed using Statistical Package for the Social Sciences (SPSS), where descriptive and inferential statistics was used to analyze the data. The results of the study showed for the major Hypothesis 1 that the demographic variables have no significant statistical impact on employment attributes of the new fresh graduates. Moreover, findings suggest that null hypothesis for major Hypothesis 2 has been rejected as applied academic skills and critical thinking skills have no significant impact on employability attribute of fresh graduates in the Kingdom of Bahrain. Null hypothesis for major Hypothesis 3 has been accepted as findings suggest that technology use skills (β ₁ = 0.080), system thinking skills (β ₂ = 0.210), communication skills (β ₃ = 0.402), and information skills (β ₄ = −0.100) which are an antecedent of workplace skills, have significant statistical impact on employability attribute of fresh graduates in Kingdom of Bahrain. Lastly, null hypothesis for major Hypothesis 4 has been accepted as findings suggest that interpersonal skills (β ₅ = 0.229) which are an antecedent of effective relationship have significant statistical impact on employability attribute of fresh graduates in the Kingdom of Bahrain.