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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.

This study aims to determine the contributing factors to technical knowledge valuation at the related quadruple levels of commercialisation, including the idea, benchtop technical knowledge, prototype technical knowledge and commercialised technical knowledge, and then classify the factors by the valuation objectives.

The study method is descriptive-causal, and documentation tools of published scientific research articles in authentic local and international journals were used to extract the contributing factors to technical knowledge valuation. Moreover, the Likert spectrum-based questionnaire is used to determine the weight of each determined component. On the other hand, hierarchical analysis is used based on the extracted results from the distributed classification questionnaire among scholars to determine the allocable weight of each component.

The results indicate that at the idea step, the highest ranks among the contributing factors to technical knowledge valuation are for the indicators of innovation rate enhancement, novelty, creation of new products, profitability growth and dependence decline. In the benchtop technical knowledge step, the indicators of profitability growth, product quality enhancement, novelty, production risk drop, innovation rate enhancement, production costs drop, product price competitiveness and independence from rare machinery have the highest impact coefficients on valuation. Moreover, the prioritisation of factors in prototype technical knowledge shows that the indicators of productive risk decline, infrastructure, decrease in product delivery time, productivity growth and profitability growth are the most critical factors in technical knowledge valuation. Finally, profitability growth factors, production cost drop, productive risk drop, creating a new product, product price competitiveness and dependence decline determine the most valuable technical knowledge in the commercialisation phase.

The most salient innovation of the study involves the development levels of technical knowledge in the commercialisation cycle for determining the contributing factors to technical knowledge valuation and using multivariate decision-making methods to classify the so-called factors. The major limitation can be the context of the study because the paper was carried out by Iranian assessors and specialists using the experiences, opinions and approaches of opinion leaders based on the dominant social, cultural and accounting background of a developing country, not a developed one.

This paper is applicable because it elucidates the technical knowledge valuation factors for managers and owners of technological and knowledge-based companies to facilitate value determination and register the technical knowledge of innovative products in financial statements for the logical presentation of available intangible assets in the economic unit. Besides, in the high-tech area, collecting information from the contributing factors to technical knowledge valuation provides an opportunity to support intellectual property rights and facilitate transaction processes. Finally, in legal areas, in cases of breaching intellectual property rights relative to technical knowledge, the determination of technical knowledge value provides a solid basis for estimating the damage rate.

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.

Given the significant role played by valuers and the evidence of a lack of independence in some property valuation industries, particularly in emerging markets, this study analyses the issue of client influence in property valuation by providing a valuer-client perspective and measuring the interrelationships between the clients' influence factors to identify causal factors of prominence, which can assist in developing solutions to address the clients' influence issue.

The study used a mixed-method approach. Firstly, interviews were conducted with ten property valuers and five financial institution staff in Nigeria, and the data were subject to thematic analysis using Nvivo 12 software. A matrix questionnaire survey was administered to the valuers, and the responses were analysed using the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method.

The results indicate that institutional clients, loan-seeking customers, property valuers and the perception of corruption within the Nigerian environment fuelled the issue of clients' influence. Based on the measurement of the interrelationship between the 14 identified client influence factors, the type of company, perception the public has of the industry, size of the firm, relationship with the client, type of client and regulatory framework were the factors of prominence.

The findings of this study bear huge implications for Nigeria and other similar structured property markets facing the issue of clients' influence in property valuation. With the prominent factors bearing root in a mix of client, valuer and environmental factors such as the valuation structure, process and public perception, there is a need for solutions that level the playing field between institutional clients and valuers, reinforce transparency and establish excellent regulatory standards to address the issue of clients' influence.

This study is the first to measure the interrelationships between the clients' influence factors to identify the prominent causal factors. Accordingly, considering the multi-factors, the research is novel as it focusses on those factors that would likely lead to other factors, thereby providing opportunities to develop solutions that focus on those factors of prominence. Secondly, the study deviates from the narrative on clients' influence in property valuation, which pits it as solely a client or valuer factor, by showing how the interplay of the stakeholders' interests and the environment promotes the issue in a non-transparent property market.

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.

Challenges of property data in developing markets have been reported by several authors. However, a deep understanding of the actual nature of this phenomenon in developing markets is largely lacking as in-depth studies into the actual nature of data challenge in such markets are scarce in literature. Specifically, the available literature lacks clarity about the actual nature of data challenges that developing markets pose to valuers and how this affects valuation practice. This study provides this understanding with focus on the Lagos property market.

This study utilises a qualitative research approach. A total of 24 valuers were selected using snowballing sampling technique, and in-depth semi-structured interviews were conducted. Data collected were analysed using thematic analysis with the aid of NVivo 12 software.

The study finds that the main data-related challenge in the Lagos property market is the lack of database of market property transactions and not the lack or absence of transaction data as it has been emphasised in previous studies. Other data-related challenges identified include weak property rights institution with attendant transaction costs, underhand dealings among professionals, undocumented charges, undisclosed information, scarcity of data relating to specialised assets and limited access to the subject property and required documents during valuation. Also, the study unbundles the factors responsible for these challenges and how they affect valuation practice.

The study has implication for practice in the sense that the deeper knowledge of data challenges could provide insight into strategy to tackle the challenges.

This study contributes to the body of knowledge by offering a fresh and in-depth perspective to the issue of data challenges in developing markets and how the peculiar nature of the real estate market affects the nature of data challenges. The qualitative approach adopted in this study allowed for a deep enquiry into the phenomenon and resulted into an extended insight into the peculiar nature of data challenges in a typical developing property market.

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 paper offers a way of revivifying classical accounting research in the form of a pragmatist neoclassical programme with a sound epistemological underpinning.

The paper draws on a pragmatist perspective on financial accounting and accounting research springing from John Dewey's theory of inquiry.

Although a pragmatist underpinning does not entail specific methodological prescriptions, it can provide fruitful insights in research design. The paper discusses the structure and content of a research programme drawing on a pragmatist underpinning and sets out proposals for a practical research agenda. Although the agenda is shaped around the topic of identifiable intangibles, much of the paper has substantially wider relevance.

The approach justifies a revival in scholarly research employing classical methods and directed at improving accounting methods and standards.

The approach would promote closer engagement between scholarly accounting and practitioners such as standard-setters, making some contribution to closing the widely acknowledged gap between research and practice.

The paper offers a neoclassical programme of research drawing considerably more extensively on pragmatist philosophy than did theorisation in the classical period.

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.