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The rising concern for the accuracy of residential valuations in Nigeria has created the need for key stakeholders in the residential property markets in the study areas to know the level of accuracy of valuations in order to make rational residential property transactions, amongst other purposes.

A blend of descriptive and causal designs was adopted for the study. Data were collected via structured questionnaire administered to 179 estate surveying and valuation (ESV) firms in the study areas using census sampling technique. Analytical techniques such as median percentage error (PE), mean and relative importance index (RII) analysis were employed in the analysis of data collected for the study.

The study found that valuation accuracy is greater in the residential property market in Abuja than in Minna, with inappropriate valuation methodology as the most significant cause of valuation inaccuracy.

The practical implication of this study is that a reliable databank should be established for the property market to provide credible transaction data for valuers to conduct accurate valuations in these cities. Strict enforcement of national and international valuation standards by the regulatory authorities as well as retraining of valuers on appropriate application of valuation approaches and methods are the recommended corrective measures.

No study has comparatively examined the accuracy of valuations in two extremely different residential property markets in the country using actual valuation and transaction prices.

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.

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.

This study aims to investigate the effects of board cultural diversity (BCD) and board gender diversity (BGD) of the board of directors on environmental, social and governance (ESG) performance in the European banking sector using resource-based view (RBV) theory. In addition, this study analyses the linkages between BCD and BGD and knowledge sharing on the board of directors to improve ESG performance.

This study selected a sample of European-listed banks covering the period 2021. ESG and diversity variables were collected from Refinitiv Eikon and analysed using the ordinary least squares model. This study was conducted in the European context regulated by Directive 95/2014/EU, which requires sustainability disclosure. The original population was represented by 250 banks; after missing data were excluded, the final sample comprised 96 European-listed banks.

The findings highlight the positive linkages between BGD, BCD and ESG scores in the European banking sector. In addition, the findings highlight that diversity contributes to knowledge sharing by improving ESG performance in a regulated sector. Nonetheless, the combined effect of BGD and BCD negatively impacts ESG performance.

To the best of the authors’ knowledge, this is the first study to measure and analyse a regulated sector, such as banking, and the relationship between cultural and gender diversity for sharing knowledge under the RBV theory lens in the ESG framework.

The purpose of this paper is to investigate a distinct set of characteristics that influence Muslim customers’ intentions to purchase Ar-Rahnu Islamic financing contract in Malaysia.

The study studied the impact of perceived value, perceived quality, perceived financial advantages, religious commitment and product knowledge on the purchase intention Ar-Rahnu Islamic financing contract using a quantitative research approach. A Google Form-based online survey was created and distributed through Twitter, Facebook and Instagram, among others. The survey data were analysed using structural equation modelling with a partial-least-square estimation property (PLS-SEM).

The study results suggested that Muslim customers in Malaysia had a greater propensity to buy Ar-Rahnu Islamic financing contract. Analysis of the data revealed that perceived value, perceived quality, perceived financial benefits and religious commitment had direct effects on the desire to buy Ar-Rahnu Islamic financing contract in Malaysia. In addition, the results reveal that religious commitment, perceived quality and perceived financial benefit are the top three important factors in explaining Ar-Rahnu Islamic financing contract buying intentions in this country.

Muslim customers may use Ar-Rahnu Islamic financing contract as a short-term credit alternative to enhance their financial standing. Ar-Rahnu Islamic financing contract generates a substantial quantity of credit demand and supply, which not only allows Muslim customers to adhere to Islamic standards but also contributes to the expansion of the economy. The result would aid and advise Ar-Rahnu finance resources and legislators in measuring the efficacy of the program in Malaysia, especially among Muslim customers.

Ar-Rahnu Islamic financing contract as a financing alternative has been explored extensively, but this study takes a whole new approach to the subject by looking at dimensions of perceived value, perceived quality and perceived financial benefit along with individual product knowledge and religious commitment. Consequently, this study will contribute to the understanding of how Muslim customers will respond to the Ar-Rahnu Islamic financing contract and will assist financial institutions in increasing the possibility that Muslim consumers would acquire Ar-Rahnu Islamic financing contract.

This study aims to investigate the impact of consumer ethnocentrism on consumers' evaluation of blockchain-based traceability information. It also examined how the use of quick response (QR) codes for traceability affects consumers' evaluation of traceable food products.

An online choice experiment was conducted to determine consumers' evaluation of the blockchain-based traceability of Feta cheese with a quota sample of 715 Greek consumers. Pearson bivariate correlation and mean comparison were used to examine the relationship between consumer ethnocentrism and QR use behaviour. Random parameter logit models were employed to examine consumers’ valuation of the examined attributes and interaction terms.

The results show that ethnocentric consumers are willing to pay more for blockchain-based traceability information. Ethnocentric consumers tend to scan QR codes with traceability information. Spending more time reading traceability information embedded in QR codes does not lead to a higher willingness-to-pay (WTP) for traceable food products.

The findings suggest that patriotic marketing messages can draw consumers' attention to blockchain-based traceability information. The modest WTP for and low familiarity with blockchain-based traceability systems raise the need for educating consumers regarding the benefits of blockchain in traceability systems.

This is the first study to provide timely empirical evidence of a positive WTP for blockchain-based traceability information for a processed dairy product. This study is the first to attempt to distinguish the effects of the intention to scan QR codes and reading information embedded in QR codes on consumers’ valuation of food attributes.

Through the case of Blanca Sinchi, the following analysis presents valuation criteria that have resulted in the invisibility of social actors and cultural patrimony (cultural heritage) elements, and some contradictions in their acknowledgment process. In addition, the paper explains how architecture, among other historic assets, has made women and their contributions invisible.

Bibliographic analysis and semi-structured interviews were carried out to theorize about the thermodynamic system of lime to propose a matri-lineal system category and expand the understanding of the participation of women in the receipt, management and transmission of what is called patrimony.

In heritage places, such as Cuenca (Ecuador), cultural richness extends from the Historic Center to the rest of the territory and its actors. However, there are intrinsic elements, such as unknown, but fundamental, oral or family traditions associated with the role of women. The case of Blanca Sinchi and lime is evidence of this, as it shows the typical scenario affected by gender and by disparate power dynamics that do not consider desirable attributes (authenticity, integrity, identity, bequest, option, existence, among others) in the conservation of architectural patrimony. A deep redefinition process, or even a change in the valuation system, is needed. Also, the history behind built heritage items must be explored to find the contributions made by women.

Proposing a matri-lineal system category to expand the understanding of the participation of women in the receipt, management and transmission of what is called patrimony, allows redefining and rewriting local and global history, acknowledging the role of women. In this way, the proposal questions not only the hegemony of the term “cultural patrimony” pigeonholed in paternal legacy but also the term “cultural heritage” as a synonym and framework that, while expanding material values, it does not effectively include, at least for Ibero-Romance language territories, the broad set of tangible and intangible values, as well as the know-how and skills of artisans.

This study aims to examine whether and how the experience of specialized external governance mechanisms mandated by the Employee Retirement Income Security Act of 1974 – the actuary and auditor – affect pension plan funding.

This study uses data from annual pension plan regulatory reports (Form 5500), Form 10-K filings, Form DEF 14A filings (company proxy statements) and publicly available data sources. The hand-collected data include information related to the pension plan’s actuary and auditor and various pension plan data disclosed in the company’s financial statement footnotes.

The author finds that more experienced actuaries and auditors are associated with better funded pension plans, especially when the company has higher financial risk or lower board independence. Additional analyses indicate that companies with more experienced actuaries and pension plan auditors are more likely to make higher annual pension plan contributions and hold fewer Level 3 fair value assets.

The dearth of pension plan governance research generally focuses on whether and how internal governance mechanisms affect pension plan funding. To the best of the author’s knowledge, this is the first empirical study of the relationship between external pension plan governance mechanisms and pension plan funding.

The heritage and tourist attractiveness of Heritage Cities have aroused interest in establishing mechanisms to enhance their value based on the development of sustainability policies. The socioeconomic and socioenvironmental valuation of these heritage sites has become a necessary tool for decision-making.

Following the recommendations of International Council on Monuments and Sites – ICOMOS, this paper proposes a series of indicators and an exploratory model to define the factors that contribute to their valuation. Following the partial least squares structural equation modelling methodology, information was obtained from 363 intramural residents in the three Heritage Cities that currently have management plans in Spain.

The results show the importance of specifying indicators of sustainable mobility and socioeconomic and socioenvironmental sustainability for an adequate valorisation of heritage sites.

To this end, it is necessary to follow the guidelines of international bodies such as ICOMOS in relation to the management plans.

Unstructured data such as images have defied usage in property valuation for a long time. Instead, structured data in tabular format are commonly employed to estimate property prices. This study attempts to quantify the shape of land lots and uses the resultant output as an input variable for subsequent land valuation models.

Imagery data containing land lot shapes are fed into a convolutional neural network, and the shape of land lots is classified into two categories, regular and irregular-shaped. Then, the intermediate output (regularity score) is utilized in four downstream models to estimate land prices: random forest, gradient boosting, support vector machine and regression models.

Quantification of the land lot shapes and their exploitation in valuation led to an improvement in the predictive accuracy for all subsequent models.

The study findings are expected to promote the adoption of elusive price determinants such as the shape of a land lot, appearance of a house and the landscape of a neighborhood in property appraisal practices.