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This real estate insight scrutinises the emerging role of Artificial Intelligence (AI), particularly Large Language Models (LLMs) like ChatGPT, in property valuation, advocating for establishing standardised reporting guidelines in AI-enabled property valuation.

Through a conceptual exploration, this piece examines the shift towards AI integration in property valuation and the critical role of Explainable Artificial Intelligence (XAI) in this transition. It discusses the CANGARU framework for developing inclusive and universally applicable reporting guidelines and the importance of human oversight in validating AI-enabled valuations.

Integrating LLMs into property valuation signifies potential efficiency gains and task automation but also introduces risks related to accuracy, bias, and ethical dilemmas. Standardised reporting guidelines are identified as essential for responsibly harnessing AI’s benefits.

The article underscores the need for the real estate industry to adopt transparent reporting practices, with valuers acting as expert interpreters of AI outputs. Emphasising error reporting in XAI not only aids in understanding AI-generated insights but also builds trust among stakeholders, ensuring AI’s ethical and effective application in property valuation.

This commentary contributes to the discourse on AI’s role in property valuation by focusing on the need for standard reporting guidelines that align with professional standards and legal frameworks. It advocates for a balanced approach to AI integration, where technological advancements complement traditional valuation expertise, ensuring accurate, fair, and transparent property valuations.

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.

This study aims to identify the pandemic’s impact on house rents by applying a rental gradient analysis to compare the pre-and post-COVID-19 periods in Auckland. The micro-level household census data from the Integrated Data Infrastructure of Statistics New Zealand is also applied to scrutinise this WFH trend as a robustness check.

Since the outbreak of COVID-19, work-from-home (WFH) and e-commerce have become much more common in many cities. Many news reports have contended that households are leaving city centres and moving into bigger and better houses in the suburbs or rural areas. This emerging trend has been redefining the traditional theory of residential location choices. Proximity to central business district (CBD) is no longer the most critical consideration in choosing one’s residence. WFH and e-commerce flatten the traditional bid rent curve from the city centre.

The authors examined micro-level housing rental listings in 242 suburbs of the Auckland Region from January 2013 to December 2021 (108 months) and found that the hedonic price gradient models suggest that there has been a trend of rental gradient flattening and that its extent was almost doubled in 2021. Rents are also found to be increasing more in lower-density suburbs.

The results imply that the pandemic has accelerated the trend of WFH and e-commerce. The authors further discuss whether the trend will be a transient phenomenon or a long-term shift.

Suppose an organisation is concerned about productivity and performance issues due to a companywide ability to WFH. In that case, some standard key performance indicators for management and employees could be implemented. Forward-thinking cities need to focus on attracting skilful workers by making WFH a possible solution, not by insisting on the primacy of antiquated nine-to-five office cultures.

WFH has traditionally encountered resistance, but more and more companies are adopting WFH policies in this post-COVID era. The early rental gradient and the micro-level household data analysis all confirm that the WFH trend is emerging and will likely be a long-term shift. Instead of resisting the change, organisations should improve their remote work policies and capabilities for this WFH trend.

So far, empirical studies of post-COVID urban restructuring have been limited. This study aims to empirically test such an urban metamorphosis by identifying the spatial and temporal impacts of COVID on house rental gradients in the Auckland Region, New Zealand. The authors apply rental gradient analysis to test this urban restructuring hypothesis because the method considers the spatial-temporal differences, i.e. a difference-in-differences between pre-and post-pandemic period against the distance measured from the city centre. The method can control for the spatial difference and the endogeneity involved.

Real estate is an asset that is traded in highly segmented, illiquid and informationally inefficient local markets. A short sale in real estate is almost infeasible and therefore impedes informed rational arbitrageurs to trade against mispricing. Thus, real estate returns are prone to sentiment-driven behaviours. Will the impacts on asset returns be identical for different types of sentiment?

This study argues that not all sentiment effects are created equal. Using the bounds test of the autoregressive distributed lag (ARDL) models, this paper examines how occupier sentiment versus investor sentiment contributes to the short-run and long-run dynamics of commercial real estate returns in Australia.

The empirical evidence suggests that investor sentiment and occupier sentiment influence return asymmetrically after macroeconomic conditions are controlled for.

The sectoral analysis further reveals that sector-specific sentiment plays a significant role in explaining commercial real estate returns. Furthermore, notable improvement is found in producing more accurate prediction in returns, given that measures of occupier and investor sentiment are appropriately specified in the forecast.

This study is novel in the sense that it acknowledges the impacts of occupiers' and investors' sentiment may be fundamentally different. The unique innovation and contribution of this study to behavioural finance literature are based on a new dataset from the Royal Institute of Chartered Surveyors which includes a survey-based measure of investor sentiment and occupier sentiment.

Achieving a balanced tenant mix is a long-standing discourse in the retailing and consumer marketing literature. From the perspective of marketing mix planning, the diversity of tenants is beneficial to the performance of shopping malls. This paper aims to use a revealed preference approach to study empirically the effect of retail tenant mix planning on the rents of shopping malls.

This study adopts a cross-disciplinary approach to develop the Island-Species-Area-Energy model to study the shopping mall marketing and management framework. The empirical data are obtained from the 129 major shopping malls in the UK.

The results confirm that the retail tenant mix is positively associated with mall size and shopping district purchasing power, implying a tenant mix equilibrium. Any deviations from the tenant mix equilibrium will impose a negative impact on total retail rents. Further, five factors, i.e. tenant mix equilibrium, building quality, locational convenience, leasing strategy and anchorage, are found to be contributing factors to retail rents.

The findings contribute to the current body of marketing knowledge from two perspectives: first, tenant mix effects on retail rents are empirically analysed based on the biogeography theory, which shows a tenant mix equilibrium for retail marketing planning. Second, a five-factor model on shopping mall marketing and management mix framework is developed and tested for the performance of shopping malls.

The repeat sales house price index (HPI) has been widely used to measure house price movements on the assumption that the quality of properties does not change over time. This study aims to develop a novel improvement-value adjusted repeat sales (IVARS) HPI to remedy the bias owing to the constant-quality assumption.

This study compares the performance of the IVARS model with the traditional hedonic price model and the repeat sales model by using half a million repeated sales pairs of housing transactions in the Auckland Region of New Zealand, and by a simulation approach.

The results demonstrate that using the information on improvement values from mass appraisal can significantly mitigate the time-varying attribute bias. Simulation analysis further reveals that if the improvement work done is not considered, the repeat sales HPI may be overestimated by 2.7% per annum. The more quality enhancement a property has, the more likely it is that the property will be resold.

This novel index may have the potential to enable the inclusion of home condition reporting in property value assessments prior to listing open market sales.

The novel IVARS index can help gauge house price movements with housing quality changes.

This paper aims to examine the effect of housing wealth on household consumption when there are resale and refinancing constraints that prevent housing assets from being cashed out.

Based on Household Expenditure Survey data in Hong Kong from 1999 to 2010, regression analysis is applied to compare the housing wealth effects of private and subsidized homeowners. Propensity score matching is adopted to ensure that the two groups of homeowners share similar household income. Further regression analysis is conducted to examine private homeowners’ consumption when their recourse mortgages are in negative equity.

Subsidized homeowners, who are not allowed to resell their units before sharing their capital gain with the government, experienced an insignificant housing wealth effect. While private homeowners experienced a significant housing wealth effect, the effect was weakened in the presence of a resale constraint induced by negative equity. The results remain robust after the application of more rigorous sample selection through propensity score matching.

The analyses are subject to two potential data limitations. One is a relatively small sample size. The other is that data on financial assets and mortgages are unavailable and have to be indirectly controlled through household characteristics. Nevertheless, our estimated marginal propensity to consume out of housing wealth is 0.03 of the annual household consumption for private homeowners, which is within the range of estimates reported in previous literature.

This study shows that the housing wealth effect enjoyed in the private sector does not necessarily apply to the subsidized sector where resale and refinancing constraints exist. This is not to suggest that the constraints be removed. Rather, policymakers should be aware of the tradeoff: while the constraints ensure that government subsidies are used to assist home ownership, not capital gain, they also bring about consumption inequality in a society, especially in a booming housing market.

Our findings extend the literature on the housing wealth effect, which has been exclusively focusing on private homeowners, to subsidized homeowners. This study also adds to the literature on housing welfare by highlighting that the resale constraints of subsidized housing can weaken the housing wealth effect.

Shared equity homeownership is a form of subsidised, resale-restricted housing through which lower-income households can sustain their affordability. This paper aims to distinguish two types of affordability within shared equity homeownership: “entry affordability” indicates how affordable subsidised housing is when a household first becomes a subsidised owner; while “exit affordability” means how affordable private housing is after a household has enjoyed subsidised homeownership for a period of time.

Using price-to-income ratios, this study compares the entry and exit affordability of shared equity homeownership programs in Australia, Mainland China, Hong Kong, Norway, the UK and the USA. Based on these international comparisons, this study generalises two distinct types of shared equity homeownership models, namely, the models of “share-to-buy” and “share forever”. A new model, “follow-as-you-go”, is further suggested to increase the elasticity of potential affordable housing supply by providing incentives for existing subsidised homeowners to move.

A key finding of this study is that while shared equity homeownership programs can improve entry affordability, homeowners’ exit affordability is weak when subsidised homeowners have to share their capital gain with the government. While many housing policy discussions around the world that support shared equity homeownership focus only on the improvement of entry affordability, these discussions usually ignore the importance of exit affordability. This study attempts to fill the void in the understanding of these two types of affordability.

Shared equity homeownership policy is not only about offering low-income households but also an affordable housing option. It is also about facilitating well-off subsidised homeowners to move up the housing ladder so that the affordable housing option can be freed up for others in need. In a word, it is not only entry affordability but also exit affordability that matters.

This study aims to investigate the three-way interaction effect of sanitary risk, aesthetic risk and psychological risk on consumers' purchase intention for second-hand clothing (SHC) based on perceived risk theory.

A survey method is used to collect data from consumers, and the final valid sample comprises 290 respondents. Partial least squares structural equation modelling (PLS-SEM) and PROCESS macro are used to analyse the data.

The results reveal that aesthetic risk moderates the negative influence of sanitary risk on purchase intention, such that the negative influence is stronger when aesthetic risk is high. In addition, the three-way interaction effect of sanitary risk, aesthetic risk and psychological risk on consumers' purchase intention for SHC is found to be significant. That is, the negative influence of sanitary risk on purchase intention is strongest when both aesthetic risk and psychological risk are high.

Previous studies have only examined the direct effect of perceived risk on consumers' purchase intention for SHC. This study contributes to perceived risk theory by examining the joint moderating effect of aesthetic risk and psychological risk on the relationship between sanitary risk and purchase intention in the context of SHC.

This study aims to investigate whether gamified elements affect the use behaviour of young people (between age 12 and 25 years) on consumption-related mobile applications.

A survey was conducted on 151 young people between the ages of 12 and 25 years.

The results showed that use behaviour on consumption mobile applications was affected by gamification. Behavioural intention to use was affected by the performance expectancy (PE) and effort expectancy (EE) of mobile application designs. Mobile applications characteristics do not affect behavioural intention to use mobile applications but through the mediator mobile application designs.

This study also proposes mechanisms that explain how mobile apps characteristics affect EE and PE through app designs. Use behaviour is affected by Gamification elements. Affective need and social need link up uses and gratification (U&G) theory and unified theory of acceptance and use of technology (UTAUT)in gamification context. This study confirms the affective need affecting behavioural intention (Thongsri et al., 2018). In this regard, the mechanism between the relationship of affective need and behavioural intention was showed. Affective need through both PE and EE influencing behavioural intention.

Corporations should consider adding gamified elements into consumption-related mobile apps to increasing usage behaviour. Lucky draws, quizzes and games could be built in for mobile apps. Mobile app designs and characteristics could improve user experience by allowing consumers to perform their search and buying processes easily. Mobile app designs will not directly influence “behavioral intention to use” but use behaviour.

Practitioners need to look at the problem from technological and customer perspectives. From technological viewpoint, both mobile apps characteristics and design are important in affecting user behaviour. From customer’s perspective, it would be helpful to add gaming elements to the mobile apps and induce emotion. One may also use visual image to create an immersive experience on the development of storyline. Prospective customers might focus on what is going on in the story and pay less attention on its own logic. Thus, simply lucky draw might not have a true effect since player have its own belief working. A suitable story element could have positive effect on mobile apps use behaviour.

This study is one of the first to examine the association between gamification and use behaviour on consumption-related mobile applications. A new framework was proposed by integrating UTAUT model and U&G theory.