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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.

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.

This study aims to investigate key aspects of public ownership of land, expropriation and compensation laws and practices in Ethiopia with special reference to Burayu Town.

A mixed research technique of descriptive and analytic approach is applied in the research. This study used a purposive sampling technique to select case study counties and a systematic method for sampling households. Questionnaire surveys, focus group discussions, interviews and observations were used to collect empirical data. Average, percentage and paired-sample t-test analyses are used for quantitative data analysis.

Significant discrepancies exist between the expropriation laws and how property valuation and compensation are practiced in Ethiopia. The findings include the arbitrariness in designating public interest status to projects; unfair property valuation practice that neglects location factor to determine market value due to a skewed understanding of public ownership of land; and the assignment of property valuators who have no valuation expertise and proper knowledge of expropriation related laws. Findings revealed the socio-economic status of expropriated households has deteriorated due to the expropriation of their landholding.

It was difficult to locate the relocated persons as they were resettled in different localities. Furthermore, the town officers were not forthcoming to provide complete information on the expropriation and compensation procedures they followed. However, this study overcame the limitations through persistent requests and availing time for the data gathering.

The findings indicated the need to redefine relationships between public ownership of land, public interest and expropriation of landholding. A proper understanding of the triad will pave the way for better expropriation practice in Ethiopia and in countries where land is under public ownership.

The social implication of the study revealed that the socio-economic situation of relocated persons was adversely affected due to the poor implementation of laws.

The disparity between public ownership of land and the rights of citizens on landholding is misunderstood by policymakers. Research has shown for the first time the root cause for the discontent of expropriated persons in Ethiopia.

In Family Law Court decisions in Australia, following divorce, the female party is frequently disadvantaged financially in the long term. This paper provides a critical assessment of valuation evidence as a data source in research and discusses valuation accuracy, valuation variation and valuation bias, as well as the Australian family court system and the role of valuers as expert witnesses. In particular, valuation in family law, as it relates to gender inequality, is discussed. The study aims to determine whether the current system of valuation in the Family Law Courts disadvantages women. This paper was important to reveal information that stakeholders in family law cases use on a day-to-day basis.

A database of 658 cases was developed and analysed to examine the influence of valuations of the matrimonial home provided by both the male and female parties on the final decision of the court.

Findings showed that valuations from the female party had marginally more influence on the outcome. However, financial disadvantages for the female party persist despite this. This raises several questions for future research, regarding reasons for this persistent disadvantage.

Research limitations included a time-consuming process.

Further researchers can use the findings from this paper to further research.

Social implications include the ability of the research to impact on society. In this regard, it was the matrimonial home in relation to divorce proceedings.

The originality of this paper stems from the analysis of a database that was created from a large number of cases from Austlii database family law cases.

This paper aims to provide a complete analysis framework and prediction method for the construction of the patent securitization (PS) basic asset pool.

This paper proposes an integrated classification method based on genetic algorithm and random forest algorithm. First, comprehensively consider the patent value evaluation model and SME credit evaluation model, determine 17 indicators to measure the patent value and SME credit; Secondly, establish the classification label of high-quality basic assets; Then, genetic algorithm and random forest model are used to predict and screen high-quality basic assets; Finally, the performance of the model is evaluated.

The machine learning model proposed in this study is mainly used to solve the screening problem of high-quality patents that constitute the underlying asset pool of PS. The empirical research shows that the integrated classification method based on genetic algorithm and random forest has good performance and prediction accuracy, and is superior to the single method that constitutes it.

The main contributions of the article are twofold: firstly, the machine learning model proposed in this article determines the standards for high-quality basic assets; Secondly, this article addresses the screening issue of basic assets in PS.

This case study is related to start-up post-listing investment analysis. Through this case study, students will be able to perform the business analysis guided by the Venture Evaluation Metric tool, perform financial analysis using the discounted cash flow methods and perform investment analysis recommendation with justifications from the business and financial analysis performed above.

This case study sets out the study of a scalable start-up, Zomato, which is a successfully listed start-up firm in India. Despite the start-up development success in the pre-listing, the firm has exhibited a continuous unprofitable finance performance in the post-listing and has further experienced a volatile share price performance, both of which have puzzled existing and potential investors. In addition, some analysts are in the opinions that the firm share price valuation have been inflated with overvaluation since in the initial public offering stage and remain traded with overvaluation in the market. Notably, considering the negative indicators mentioned above, investors are concerned about long-term sustainability of the firm business and financial performance. In the context of post-listing investment, the following questions are material to investors: What is the realistic growth trajectory for Zomato in the medium term? What is Zomato’s share fair value in the medium term? Can one see opportunities or risks ahead of investing in Zomato’s shares? What will be the investment strategy for new investors?

This case study is suited to bachelor’s and master’s level in business schools studying entrepreneurial finance analysis.

Teaching notes are available for educators only.

CSS 1: Accounting and finance.

This study aims to examine the implementation of International Financial Reporting Standards (IFRS) in Saudi Arabia. It investigates how the adoption of IFRS has affected four critical areas in the financial statements of publicly listed companies: profit and loss statement, balance sheet, cash flow statement and retained equity statement in Saudi Arabia. The paper also explores the essential factors/drivers that influence the adoption of IFRS and its implication in Saudi Arabia.

Data was obtained from Saudi Stock Exchange (Tadawul) listed companies from eleven industries in Saudi Arabia. This cross-sectional study analyses critical financial data across eleven distinctive industries. To identify the impact of adopting IFRS, the researchers use a paired t-test to evaluate seven key elements of financial statements underlying the critical areas: non-current asset, current asset, total assets, shareholders equity, non-current liability, current liability and total liability. The sample captures cross-sectional data from well-developed global industries in Saudi Arabia, pre- and post-implementation of IFRS. Thus, the analysis of the sample data gives a representative picture of the population of the Saudi Arabian industry.

The results reveal significant differences between GAAP and IFRS reporting standards in the measurement, recognition and classification of non-current assets and liabilities. The differences are expressed in the variance between the GAAP and IFRS. Specifically, the differences between GAAP and IFRS demonstrated by the t-value are significant and reliable (respectively, 5.3 and 4.1). Additionally, the t-value is validated by the p-value, which in both was significant.

The outcomes of this research will benefit accounting information users, practitioners, researchers and regulators. Since Saudi Arabia’s policymakers have mandated the full adoption of IFRS in financial reporting, the study contributes to the adoption of IFRS practices throughout the Saudi industry. Adopting full IFRS standards requires widespread IFRS expertise to cope with the transition.

This study advances research into the perennial issues associated with changes in reporting towards IFRS standards, especially in Saudi Arabia. The contribution to theory and practice enters new and fruitful areas.

The purpose of this paper is to engage in a systematic examination of previous scholarship on the relationship between Sharia governance (SG), which is represented by the Sharia Supervisory Board (SSB), and the Internal Sharia Review (ISR), to determine whether the ISR can minimize financing risk in Islamic banking.

The literature search consisted of two steps: a randomized and systematic literature review. The methodology adopted in this article is a systematic literature review.

To reduce the risk of financing in Islamic banking, SG must be implemented optimally by making rules regarding the role of the SSB in supervising customer financing. In addition, it is a necessary to establish an entity that assists the SSB in the implementation of SG, namely, the ISR section, but there is still very little research on the role of the SSB and ISR in minimizing financing risk.

Establishing an ISR to assist the SSB in carrying out its duties has direct practical implications for Islamic banking: minimizing financing risks and compliance with Islamic Sharia principles. In addition, new rules regarding the role of SSBs and the ISR in reducing credit risk include monitoring customers to ensure that they fulfill their financing commitments on time. This new form of regulation and review can be used as a reference by the Otoritas Jasa Keuangan or Finance Service Authority to create new policies or regulations regarding SG, especially in Indonesia.

Subsequent research may introduce other more relevant variables, such as empirically testing the competence, independence or integrity of SSB and the ISR team as it attempts to minimize the risk of financing in Islamic banks. In addition, further research is expected to examine whether the SSB or the ISR team has a positive or negative influence on the risk of financing Islamic banks with secondary data.

Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala.

The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys.

Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region.

This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.