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The technological disruption from artificial intelligence (AI) within the economy requires intelligent property professionals for tomorrow. This paper proposes that the direction of interaction between AI and tomorrow's property professional, the property graduate, should be AI-empowered rather than AI-directed.

The paper reflects on the growing influence of AI in property combined with literature on technological adoption in the workplace. It proposes a way forward in navigating future decision-making.

An AI-empowered paradigm promotes the importance of industry-specific knowledge to determine factual information in decision-making. In contrast, an AI-directed paradigm leads to over-dominance of the user on pre-specified knowledge available through AI tools that could lead to AI-directed output that carries significant risk for the property industry.

Navigating the future requires a paradigm that moves from a computational focus driven predominantly by technological tools to one where tomorrow's professionals have a cognitive focus that leads to AI-enabled property graduates that can apply the correct tools in the right circumstances.

This paper reflects on the increasing role that technology and AI have within the property profession and brings to light the importance of learning through experience and the transparent use of AI tools in property.

This study systematically reviewed existing literature on the impact of economic uncertainty on property performance to highlight focus areas and spur future research amid unprecedented global uncertainty levels. Conceptually, uncertainty levels and environmental dynamism are related to investors' risk judgement and decision-making.

Peer-reviewed journal articles published from 2007 to 2022 were assembled and arranged through the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. The initial search produced 2,028 results from the Web of Science and Scopus databases, which were rigorously purified for a final dataset of 70 articles. These records were subsequently assessed through content analysis, bibliographic modelling, topic modelling and thematic analysis. Recurring themes were visualised using the VOSviewer software.

The existing literature suggests that economic uncertainty negatively impacts investment volumes, returns and performance. Research has also increased since 2018, with a strong emphasis on the housing sector and developed property markets. Commercial property and emerging markets account for only 10 and 8% of previous research, respectively.

These findings highlight the negative impact of economic uncertainties on property performance and investment volumes, which necessitate careful risk assessment. Given the high susceptibility of emerging and commercial property markets to uncertainty, these markets warrant further research amid ongoing uncertainty concerns across the globe.

Given current unprecedented levels of global uncertainty, the effects of economic uncertainty have received renewed interest. This study synthesised the current understanding of how different property markets respond to increased uncertainty and outlined future research directions to enhance understanding. Themes and relationships were also integrated into a conceptual map summarising the reported effects of economic uncertainty on housing, commercial property, investment and behaviour in the property market.

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 paper identifies the need to expand the range of research methodologies considered suitable for high-calibre property research publications in the top property journals, particularly concerning the critical “bigger” property research issues going forward. This is important for early career researchers (ECRs), as the ECRs develop the suitability of the research methodologies used by the ECRs in expanding the ECRs' property research agendas.

This research is based on a thorough understanding and extensive experience of the range of property research methodologies available today to publish in the top property journals. This depth of understanding is supported by extensive discussions with leading property industry professionals, as well as reviewing the property research, track record of several leading property researchers from the UK.

A broader range of research methodologies is needed in property research today to fully capture the challenges of the critical property research questions going forward. These methodologies need to go well beyond the finance paradigm that has dominated property research in recent years.

Many of the key property research questions going forward need to be addressed by a range of methodologies for richer and deeper insights into resolving these property issues. This particularly relates to the important research issues for the property industry which require a “bigger picture” analysis of these issues, with the research presented in a manner which is accessible and relevant to property industry professionals.

This paper addresses the need to expand the research methodologies used in property research today. This is a key issue for property researchers going forward, as many of the important property research questions cannot be addressed from just within the traditional finance paradigm.

This research investigated Australian property valuers' identification and consideration of physical climate change risks in valuation practice.

Thirty Australian valuer members of the Australian Property Institute from a variety of specialisations were interviewed. The semi-structured interviews explored climate change risks and the extent of risk investigation and consideration in valuation practice. The analysis utilised the Moser and Luers (2008) climate risk preparedness framework as a lens to evaluate current valuation practice in Australia.

The analysis reflects that while physical risks are easily identified and engaged with by valuers, correspondingly, there is a lack of understanding of and engagement with, climate change risks. This supports the need for better information sources and guidance to inform valuers of climate change risks and the development of specific mechanisms for the consideration of such risks to be included in valuation processes, practices and reports.

The research was limited by its sample size and qualitative approach. Therefore, the research is not a representative opinion of the Australian profession; however, the analysis provides the perspective of a range of valuers from across Australia with different valuation specialisations.

This research has established that valuers have the potential to be prepared to address climate change in their professional capacity, as described by Moser and Luers (2008). However, they are constrained by information communication, access and detail and subsequent market awareness of information on climate change risk exposure on properties. There is a need for further support, guidance, information and tools, as well as awareness-raising, to enable valuers to accurately identify and reflect all risks affecting a property in the process of valuation.

This research provides the first investigation into the consideration of climate change in valuation practice. Property stakeholders—owners, investors, financiers and occupiers—are escalating their climate change risk analysis and reporting for property portfolios and organisations. This research suggests that valuers also need to be aware of the changing dynamics of market reporting and decision-making related to climate change risks to ensure appropriate reflection in valuation practice.

With access to the large-scale search data from Rightmove plc, the paper firstly indicated the possibility of using user-generated data from online property portals to predict housing market activities and secondly embraced a GIS approach to explore what people search for housing and what they chose and investigated the issue of mismatch between search patterns and revealed patterns. Based on the analysis, the paper contributes a visual GIS-based approach which may help planners and designers to make more informed decisions related to new housing supply, particularly where to build, what to build and how many to build.

The paper used the 2013 housing search data from Rightmove and the 2013 price data from Land Registry with transactions made after the search period and embraced a GIS approach to explore the potential housing demand patterns and the mismatch between searches and sales. In the analysis, the paper employed the K-means approach to group prices into five levels and used GIS software to draw maps based on these price levels. The paper also employed a simple analysis of linear regression based on the coefficient of determination to investigate the relationship between online property views and values of house sales.

The result indicated the strong relationship between online property views and the values of house sales, implying the possibility of using search data from online property portals to predict housing market activities. It then explore the spatial housing demand patterns based on searches and showed a mismatch between the spatial patterns of housing search and actual moves across submarkets. The findings may not be very surprising but the main objective of the paper is to open up a potentially useful methodological approach which could be extended in future research.

It is important to identify search patterns from people who search with the intention to buy houses and from people who search with no intention to purchase properties. Rightmove data do not adequately represent housing search activity, and therefore more attention should be paid to this issue. The analysis of housing search helps us have a better understanding of households' preferences to better estimate housing demand and develop search-based prediction models. It also helps us identify spatial and structural submarkets and examine the mismatches between current housing stock and housing demand in submarkets.

The GIS approach in this paper may help planners and designers better allocate land resources for new housing supply based on households' spatial and structural preferences by identifying high and low demand areas with high searches relative to low housing stocks. Furthermore, the analysis of housing search patterns helps identify areas with latent demand, and when combined with the analysis of transaction patterns, it is possible to realise the areas with a lack of housing supply relative to excess demand or a lack of latent demand relative to the housing stock.

The paper proves the usefulness of a GIS approach to investigate households' preferences and aspirations through search data from online property portals. The contribution of the paper is the visual GIS-based approach, and based on this approach the paper fills the international knowledge gap in exploring effective approaches to analysing user-generated search data and market outcome data in combination.

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.

The main purpose of this paper is to explore whether the nature of innovation is accumulative or radical and to what extent past year accumulation of technology stock can predict future innovation. More importantly, the authors are concerned with whether a change of policy regime or a variance in the quality of technology will moderate the nature of innovation.

The authors examined a dataset of 3.6 million Chinese patents during 1985–2015 and constructed more than 5 million citation pairs across 8 sections and 128 classes to track knowledge spillover across technology fields. The authors used this citation dataset to calculate the technology innovation network. The authors constructed a measure of upstream invention, interacting the pre-existing technology innovation network with historical patent growth in each technology field, and estimated measure's impact on future innovation since 2005. The authors also constructed three sets of metrics – technology dependence, centrality and scientific value – to identify innovation quality and a policy dummy to consider the impact of policy on innovation.

Innovation growth is built upon past year accumulation and technology spillover. Innovation grows faster for technologies that are more central and grows more slowly for more valuable technologies. A pro-innovation and pro-intellectual property right (IPR) policy plays a positive and significant role in driving technical progress. The authors also found that for technologies that have faster access to new information or larger power to control knowledge flow, the upstream and downstream innovation linkage is stronger. However, this linkage is weaker for technologies that are more novel or general. On most occasions, the nature of innovation was less responsive to policy shock.

This paper contributes to the debate on the nature of innovation by determining whether upstream innovation has strong predictive power on future innovation. The authors develop the assumption used in the technology spillover literature by considering a time-variant, directional and asymmetric matrix to model technology diffusion. For the first time, the authors answer how the nature of innovation will vary depending on the technology network configurations and policy environment. In addition to contributing to the academic debate, the authors' study has important implications for economic growth and industrial or innovation management policies.

Considering the changing dimensions of client influence in the emerging sub-market in Nigeria, different from previous general insinuations, this article examines the new strategies adopted by clients to influence estate surveyors and valuers (ESVs), factors that predispose ESVs to client influence and the effects of clients' influence on valuation outcomes and real estate markets in emerging sub-market, using Ibadan market as the study area.

The paper is situated within a client influence assessment framework, modified to reflect contextual incidents. Contextualization was made possible with the involvement of both practitioners and academic researchers. Validated copies of the questionnaire were administered to the registered practicing ESVs in an intact group during their monthly state (provincial) meeting and through direct delivery at their firms. Data collected were analyzed using descriptive and inferential statistics.

Contrary to the previous studies, the authors found no significant relationship between ESV professional qualifications, the firm's staff strength and the frequency of clients' influence in valuation assignments. Hiding important information and clauses, begging, lobbying, and seeking undue favor and promises for future jobs or appointments are the influencing strategies clients employ to pressure valuer. The topmost factors are emerging sub-market and economic-induced factors, lack of due process, and adequate transparency on the parts of firms and Valuers. It was established that the new dimension of client influence leads to the mortgage valuation accuracy dilemma, discredit of professional confidence, default and financial distress, and generating mistrust in the property market.

The implication is the new dimension of client influence, different from the previous studies, thus calling for professional and policy attention. As real estate investment and transactions transcend globally, understanding the local sub-market condition is imperative.

The novelty of the paper is the exposition on the dimensions of client influence within the economy and the implication for the professional body regulatory policy.

Property management companies in residential properties are increasingly using ICT and specific property management software applications to conduct daily property management tasks. However, the benefits of using specific software applications and how it can add value to property management companies are largely unexplored. The present study examines the impact of property management mobile applications usage features on strata property residents' satisfaction in Kuala Lumpur.

A total of 205 residents from 3 strata residential buildings in Kuala Lumpur using property management applications were surveyed. The study employed structural equation modelling using SPSS Amos software.

The findings suggest that visitor management and security management via software applications positively influence the residents' satisfaction. However, facility management via software application was found to be negatively affecting residents' satisfaction.

The study highlighted the benefit of property managers adopting property management software to achieve increased residents' satisfaction in strata residential properties.