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This paper examines gender diversity in the Australian valuation industry from the perspective of valuers in senior management and leadership roles and discusses gender diversity policies and practices in their organisations. Then, it explores the initiatives that can be implemented to improve gender diversity in the Australian valuation industry.

A focus group discussion was conducted with valuers in senior management and leadership roles from selected large valuation firms and government valuation agencies in Melbourne, Australia. Data collected through the focus group discussion was combined with secondary data sourced from journals, online articles and archival materials.

The findings reveal that whilst gender diversity in the Australian valuation industry has improved over the years, females remain underrepresented. Nonetheless, whilst some valuation companies have recognised the need to address the underrepresentation of women and introduced specific gender-focussed human resource policies and practices, these initiatives are not streamlined and implemented across the industry.

The study highlights the need for closer collaboration between key stakeholders such as universities, professional associations, valuation companies and government agencies in devising strategies to attract female talents into the valuation industry.

The paper is the first empirical study to assess gender diversity in the Australian valuation industry from the perspective of valuers in management and leadership roles. The proposed policies can inform future initiatives to improve gender diversity in the valuation industry.

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 viewpoint article explores the transformative capabilities of large language models (LLMs) like the Chat Generative Pre-training Transformer (ChatGPT) within the property valuation industry. It particularly accentuates the pivotal role of prompt engineering in facilitating valuation reporting and advocates for adopting the “Red Book” compliance Chain-of-thought (COT) prompt engineering as a gold standard for generating AI-facilitated valuation reports.

The article offers a high-level examination of the application of LLMs in real estate research, highlighting the essential role of prompt engineering for future advancements in generative AI. It explores the collaborative dynamic between valuers and AI advancements, emphasising the importance of precise instructions and contextual cues in directing LLMs to generate accurate and reproducible valuation outcomes.

Integrating LLMs into property valuation processes paves the way for efficiency improvements and task automation, such as generating reports and drafting contracts. AI-facilitated reports offer unprecedented transparency and elevate client experiences. The fusion of valuer expertise with prompt engineering ensures the reliability and interpretability of valuation reports.

Delineating the types and versions of LLMs used in AI-generated valuation reports encourage the adoption of transparency best practices within the industry. Valuers, as expert prompt engineers, can harness the potential of AI to enhance efficiency, accuracy and transparency in the valuation process, delivering significant benefits to a broad array of stakeholders.

The article elucidates the substantial impact of prompt engineering in leveraging LLMs within the property industry. It underscores the importance of valuers training their unique GPT models, enabling customisation and reproducibility of valuation outputs. The symbiotic relationship between valuers and LLMs is identified as a key driver shaping the future of property valuations.

The purpose of the study is to examine the efficiency of linear, nonlinear and artificial neural networks (ANNs), in predicting property prices.

The present study uses a dataset of 1,468 real estate transactions from 2020 to 2022, obtained from the Department of Property Taxes of Republic of Kosovo. Beginning with a fundamental linear regression model, the study tackles the question of overlooked nonlinearity, employing a similar strategy like Peterson and Flanagan (2009) and McCluskey et al. (2012), whereby ANN's predictions are incorporated as an additional regressor within the ordinary least squares (OLS) model.

The research findings underscore the superior fit of semi-log and double-log models over the OLS model, while the ANN model shows moderate performance, contrary to the conventional conviction of ANN's superior predictive power. This is notably divergent from the prevailing belief about ANN's superior predictive power, shedding light on the potential overestimation of ANN's efficacy.

The study accentuates the importance of embracing diverse models in property price prediction, debunking the notion of the ubiquitous applicability of ANN models. The research outcomes carry substantial ramifications for both scholars and professionals engaged in property valuation.

Distinctively, this research pioneers the comparative analysis of diverse models, including ANN, in the setting of a developing country's capital, hence providing a fresh perspective to their effectiveness in property price prediction.

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.

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.

There is a long-standing debate about the relationship between land title registration and tenure security. Studies in the developing world point to a tenuous link between land registration and stable land tenure. The reason why people continue to register therefore becomes a mystery if tenure security is not entirely assured. This article focuses on the increase in property value as one such factor that induces title registration. Previous studies have quantified the economic impact of title registration on property values. However, the impact varies from city or country to another. The authors seek to investigate the extent of property value increment in Accra attributable to land title registration.

The authors statistically analyzed a data set from two institutions (First National Bank and the Lands Commission) in Ghana using a quantitative technique.

The authors discovered that, holding all other factors constant, the value of the land in Accra increases by 22.6% due to land title registration. This shows that lessees must register to enhance property values, even though the essential due diligence must be done to make sure the acquisition is free from liens and legal disputes.

This article highlights the implication of the findings for land administration as well as the practice of property valuation, development and brokerage in Ghana and Global South more broadly.

This is one of the first studies in Ghana to investigate the specific premium that housing markets put on land title registration.

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 paper examines rent determinants and their relationship with commercial office property rents.

The method adopted in this study differs from that of previous studies on this topic. Firstly, based on the survey of the viewpoints of experts, Relative Importance Index (RII) analysis was used to identify rent determinants and to rank and ensure their relevance and validity in the Sri Lankan context. Secondly, sampling of data related to 115 office properties collected from property tenants and landlords located within the central built-up area of Colombo City was conducted using a multi-methods approach to carry out an objective hedonic analysis of office rents.

This research utilizes RII and hedonic models to provide insights into determinants and relationships. Both analyses confirm that the three top drivers of commercial office rent are distance from the major town center, availability of parking space and the condition of the property. In addition to these three factors, hedonic models reveal that the age of the property and the availability of a conference hall also play a relevant role in explaining office rents. Given the disparities in the findings of the two methods, further examination was able to confirm that factors such as distance from the major town center, parking availability, age of the property, presence of a conference hall, building condition, floor size, business type and type of building are likely to influence commercial office rent. These findings reflect elements such as the quality, newness and better facilities of different office properties.

This systematic study and analysis of office rent for the guidance of real estate investors can support sound investment decisions, potentially leading to more financially sound property development, reduced public debt levels and improved public-private financing. Further, the research findings offer valuable insights to real estate investors, developers and planners regarding location decisions for office development quality enhancements in future office developments.

This research provides fresh insights into the local scale office market, an area where limited evidence currently exists. Further, the methodology adopted provides evidence that hedonic analysis, supported by a multi-method approach, can mitigate the subjective judgments made by professionals.

This article seeks to offer an answer. It explores the criteria on which commercial property market participants can develop strategies in hugely challenging circumstances. For this purpose, a survey-based approach was developed with work conducted with property-market professional in the United Kingdom (UK), France, Germany and Sweden to produce a criteria-based tool supporting adaption to changing market circumstances.

The data have been analyzed using statistical analysis. The data's statistical analysis included Cronbach's alpha's application to evaluate the respondents' replies' reliability. A entral tendency test was used to identify the means of relevance of the criteria. The Mann–Whitney U test was used to determine potential material differences between the UK and other countries with Bonferroni corrections applied to minimize type-I errors.

Thirty characteristics have been identified that impact the dynamics of the commercial property market. Their relevance to the commercial property market was determined using a survey. The literature analysis showed that the researchers paid more attention to quantitative criteria and their comparison. The survey showed that the relevance of criteria to the commercial property market dynamics is unequal. However, the survey results showed that it is most important to pay attention to emotional criteria to adapt to uncertainty changing conditions. The problem of the environment has been on the agenda for the last four decades. Therefore, the fact that the results of the study showed that the environmental criteria are the least significant is unexpected.

The study involved economically developed countries of Europe. Extending the study's geographical scope would be valuable in revealing whether the same differences exist in other geographical areas (such as Australia or the USA).

The practical implication of the analysis may be to facilitate the decision-making process of either selecting a country for commercial property investment or selecting the most sensitive and relevant criteria for the decision-making.

Criteria for commercial property market performance which promote successful property investment have been developed. Moreover, the criteria affecting the commercial property market have been weighted by their relevance to the market and their sequence of relevance has been established. And finally, the developed criteria have been placed into five groups that could serve as a foundation for a macro-level assessment of commercial property market dynamics.