How Should Property Investors Make Decisions Amid Heightened Uncertainty: Developing an Adaptive Behavioural Model Based on Expert Perspectives

Abstract

In a significant transition from classical theories of efficient markets and perfectly rational investors, the recent literature has increasingly acknowledged the importance of the human element and external market conditions in decision-making. However, the application of adaptive market frameworks in the property sector remains underexplored. This gap is particularly pronounced in the commercial property market, where structural inefficiencies, such as information asymmetry and illiquidity, amplify decision-making complexity. Given that investor rationality tends to diminish as uncertainty and complexity increase, this study explored how private commercial property investors adapt their strategies amid heightened uncertainty. The perspectives of seven experienced property experts were thematically analysed to highlight recurring patterns, which were then integrated into a conceptual mind map. The findings reveal that while economic fundamentals are the constant drivers of capital allocation decisions, investors process these signals through the lens of adaptive behaviour based on intuition, experience, risk perceptions, and herding. This relationship becomes more pronounced under conditions of heightened uncertainty, where investors seek to supplement available information with sentiment due to weaker signals and declining confidence in fundamentals. Sustainable investing and technology integration also emerged as core considerations, but interest among private investors is subdued due to ambiguous value propositions regarding the long-term economic benefits of a green premium. These findings offer practical insights into how external market conditions influence property investment decisions and provide a platform for operational models of investment decision-making that integrate adaptive behaviour.

1. Introduction

Property investment decisions are inherently complex, requiring the careful consideration of multiple interrelated factors, ranging from asset fundamentals and financing conditions to broader economic and regulatory shifts [1,2]. Although initial attempts to explain investor behaviour were predominantly made under the assumptions of complete rationality and market efficiency [3], more recent literature has highlighted their insufficiency due to the pervasive effects of human behaviour, cognitive biases, and market imperfections [4,5,6,7,8,9]. This complexity is amplified in the commercial property sector, where transactions are characterised by larger capital outlays, lower liquidity, greater heterogeneity of assets, and persistent market inefficiencies [10].

These inefficiencies restrict how swiftly investors can respond to changing market signals, thus increasing their reliance on imperfect information, intuitive judgement, and experience [4,11,12]. These limitations impact decision-making under relatively stable conditions, where risk can be modelled, but they exacerbate irrational decision-making during periods of heightened uncertainty in the aftermath of major external shocks, such as the COVID-19 pandemic or monetary policy shifts [5,12,13,14]. As noted by Gallimore and Gray [4], this environment creates fertile ground for heuristics, behavioural biases, and adaptive strategies to influence decisions as investors seek to augment imperfect information with their interpretation of future market movement signals. The most recent global market disruption, COVID-19, highlighted how external market signals can impact behaviour and performance. The COVID-19 shock resulted in declines of up to 32.9% in US GDP [15], and a 32% dip in transaction volumes across the Asia-Pacific region [16].

In this context, traditional models are insufficient because the underlying considerations that investors make to allocate capital change in response to external market signals [5,17,18]. In response to this heightened uncertainty and added complexity, investors may adopt a wait-and-see approach, exhibit more cautious attitudes, or leverage their intuition to account for increased perceptions of risk [5,6,19]. Because investors depict varying levels of rationality based on market conditions and information availability [20], the immediate aftermath of an external market disruption is characterised by suboptimal decision-making often based on intuition [1]. Notably, the decision-making of other market participants, such as property valuers, is also influenced by uncertainty and behavioural biases. Research in this domain highlights substantial psychological and contextual factors that shape valuation accuracy and reliability, including client pressure, heuristics, ethical concerns, and opportunistic behaviours [21]. Similarly, Mohammad et al. [22] identified six key behavioural uncertainties affecting valuation practice: heuristics and bias, ethical conduct, client influence, valuer experience and knowledge, market data availability and accuracy, and professional negligence. These insights reinforce that behavioural influences extend across multiple domains of property decision-making, providing a useful reference point for examining how similar dynamics shape investment strategies under heightened uncertainty.

Although decision-making in the commercial property sector is inherently complex due to the market’s structural inefficiencies, heightened uncertainty introduces an additional layer of complexity, often disrupting previously reliable signals and rendering standard decision-making approaches impractical [5,23,24]. A plethora of studies have documented how uncertainty significantly impacts asset returns, transaction volumes, and investment appetite [16,25,26]. This underscores the value of decision aids and frameworks in guiding judgement and reducing cognitive burden when investors must navigate heightened uncertainty. Yet, as Lausberg and Krieger [27] observed, the application of static decision models in property markets is impractical, given the sector’s dynamic, fragmented nature and the diversity of investor goals.

The extant literature has seen a gradual transition from the strict assumptions of perfectly rational investors and perfectly efficient markets to more flexible models that account for human behaviour and volatile market conditions. This shift in thinking is exemplified by the Adaptive Markets Hypothesis (AMH) proposed by Lo [28], which reinterprets the traditional Efficient Markets Hypothesis (EMH) through the lens of evolutionary theory and behavioural sciences. At its core, AMH integrates insights from cognitive neuroscience and decision-making research to evince that market efficiency is not static but evolves over time as investors adapt their behaviours to changing environments and external signals. Subsequent research has provided further empirical evidence in support of the theory that market conditions influence investment performance [29], and behaviour is a critical consideration when explaining decision-making because investors adapt to market signals [5,30,31]. The concept of adaptive behaviour itself is difficult to define without a single consensus across disciplines [32,33], and this lack of definitional clarity also complicates efforts to delineate what constitutes adaptive behaviour.

Several theoretical perspectives offer competing but complementary explanations for this adaptive process. Bounded rationality [34] highlights that investors aim for “good enough” rather than perfectly rational decisions, particularly when information is incomplete or ambiguous. Prospect theory, as proposed by Kahneman and Tversky [35], demonstrates investors’ risk-seeking behaviour in the face of potential losses. However, Barberis [36] noted a key weakness in the theory’s ability to account for the effects of external environmental factors on decision-making. Emergent norm theory [37] further explains how new standards arise when old routines collapse, while real options theory captures the tendency of investors to defer or stage decisions to preserve flexibility in uncertain contexts [38]. Notably, while some studies suggest that behavioural tendencies such as intuition or herding often lead to suboptimal outcomes [39,40], others argue they can provide adaptive shortcuts that enable faster and sometimes more effective decision-making under time pressure [4,5,12]. The challenge becomes even greater under conditions of heightened uncertainty, when market disruptions weaken established norms and amplify reliance on behavioural cues [41].

Despite these advancements in modelling human behaviour and decision-making, applications in property investment remain a unique challenge. In the commercial property space, evidence suggests that institutional investors dominate the market, have access to more information and expertise to navigate the added complexity [42]. However, the effect of these factors on private investors has been underexplored in the scholarly research, despite evidence that these investors are more prone to irrational decision-making amid increased complexity and heightened uncertainty [43]. This study addresses these gaps by drawing on the perspectives of experienced property professionals to explore how private commercial property investors in Australia navigate, interpret and adapt to heightened uncertainty following major market disruptions. Although the recent disruptions of COVID-19 and inflationary pressures have had global impacts, Australia provides a unique testing ground due to a series of aggressive monetary policy decisions by the Reserve Bank of Australia (RBA), which extended the period of heightened uncertainty [25,26,44,45].

The core objective of this study was to understand how and why investor behaviour shifts in response to uncertainty, and to identify practical decision-making strategies that investors leverage to navigate complex and rapidly changing conditions. By mapping the dynamic relationships between fundamentals, investor psychology, institutional context, and market uncertainty, the model offers a more realistic, flexible, and practitioner-informed framework of investment decision-making in the context of imperfect markets. In recognising the role of human judgement, imperfect information, and evolving investor behaviour, this study contributes to both academic literature and the practical domain by offering a conceptual model that represents the complex, fragmented, and uncertain nature of contemporary property markets.

2. Materials and Methods

2.1. Data Description

To explore how investors navigate heightened uncertainty, this study drew on semi-structured interviews with seven professionals operating across various segments in the Australian commercial property space. This qualitative interview-based approach facilitated deep, reflective insights into investor behaviour, particularly the cognitive processes, heuristics, and adaptive strategies that are difficult to measure with quantitative metrics [46,47]. Given the study’s aim to develop an adaptive behavioural model, this method was essential to uncover the contextual nuance and real-world complexity of decision-making during periods of market disruption.

The participants were selected using purposive sampling based on first-hand experience advising or making property investment decisions through recent periods of heightened uncertainty [47,48]. Although the perspectives of these respondents reflect secondary accounts of investment decisions, their interaction with a broad spectrum of investors provides a unique vantage point, which was ideal for the research aim of exploring how different investors adapt to external market movements. Specifically, the respondents held senior advisory roles during the recent market disruptions created by the COVID-19 pandemic, nationwide lockdowns, inflationary pressures, and the RBA’s monetary policy shifts in response to global economic instability. All interviewees held senior or strategic roles and specialised knowledge from different parts of the investment value chain—including finance, brokerage, consultancy, leasing, and advisory services. Their diverse yet complementary experiences provide a robust foundation for analysing behavioural patterns in uncertain conditions.

While the sample of seven expert participants is not representative of the entire population, the study was designed as an exploratory investigation to inform the design of a conceptual model to guide subsequent empirical research in an underexplored domain. This approach aligns with established practices in qualitative research, particularly within the property investment literature, where sample sizes of five to 10 participants have been deemed sufficient [41,49,50]. All interviews were conducted via the Zoom video conferencing platform and lasted approximately 45 min each. With participants’ consent, the conversations were audio-recorded and then transcribed for further analysis based on emerging themes. The professional profiles of the interviewees are summarised below in

Table 1. Profile of Property Experts (Validating Interviews).

Code	Role	Experience
PE1	Director (Property Investment Consultancy)	13 years
PE2	Managing Partner (Property Finance Advisory)	18 years
PE3	Director (Property Finance Brokerage)	16 years
PE4	Settlement Manager (Property Investment Consultancy)	3 years
PE5	Sales and Leasing Consultant (Property Agency and Advisory)	20 years
PE6	Director (Full-service Commercial Property Agency)	9 years
PE7	Sales and Leasing Consultant (Property Agency and Advisory)	23 years

Note: ‘Experience’ refers to the total number of years spent working in advisory and consulting roles in the commercial property sector.

, where the participating experts are anonymised using identifiers: PE1–PE7.

The semi-structured interviews were guided by open-ended questions that addressed various aspects of investor behaviour under uncertainty, including reasons why uncertainty impacts decisions, risk perceptions, and adaptive strategies, as well as the emergence of sustainable investing and the integration of technology. In the latter part of each interview, participants also reviewed and provided feedback on a preliminary conceptual model. Their critiques helped to validate the initial framework, but also introduced new considerations, highlighting how investors often operate with limited information, evolving market signals, and diminishing confidence in previously accepted assumptions or rules of thumb. Appendix A presents the core prompts of the interview guide used in this study.

The interviews were conducted between April and June 2025, a period marked by easing economic pressures in response to cautious rate cuts by the RBA. This timing allowed participants to reflect retrospectively on how investor behaviour had shifted in response to earlier disruptions, including rising interest rates, inflationary pressures, and the COVID-19 pandemic. Accordingly, the study was positioned as an exploration of how investors adapt to heightened uncertainty in general, rather than attributing adaptive behaviour solely to the monetary policy decisions at the time of data collection.

2.2. Analysis Techniques

To explore the emerging norms of property investment decision-making in response to heightened uncertainty, this study operationalised a thematic analysis approach by identifying key themes, developing a coding system, categorising responses under the identified themes, and integrating those themes into a coherent structure for interpretation [46]. In addition to reducing researcher bias, this approach enables the organisation of complex qualitative data into meaningful patterns while retaining the nuanced insights provided by the experienced professionals [46,48].

All interviews were transcribed verbatim and analysed using the NVivo software (v.15), which supported the organisation, coding, and visualisation of emergent themes. Initial coding was grounded in the research objectives and concepts from the preliminary conceptual model developed during earlier phases of the study. Based on the existing literature in the domain of complex decision-making amid heightened uncertainty, these included the role of market fundamentals, investor risk perceptions, adaptive behaviour, cognitive biases, and investment allocation strategies [5,13,14,51].

The coding process was both inductive and iterative, as key concepts were identified directly from the interview data, and nodes were created to capture references that reflected meaningful ideas, responses, or behaviours [46].

Table 2. Codebook representing how property investors adapt to uncertainty.

Theme	Codes (Examples)	Illustrative Quotes
Economic fundamentals	Interest rates, Monetary policy	“The underlying economic fundamentals remain responsible for market movements, regardless of other market factors.” “As interest rates came down, we saw a huge [number] of people buying property.”
Property performance	Returns, Yields, Vacancy rates	“They can charge whatever rate they want, but an investor is buying for a return on investment.” “A lot of people were able to hold their commercial properties through the interest rate rises because they were they bought on really good yields.”
External market conditions	Uncertainty, Information	“A lot of people want to get in and buy; there’s a bit of fear of missing out before the rates go down.” “Initially, it (COVID-19) started with a lot of uncertainty [and] people not knowing what would happen to the market.”
Adaptive behaviour	Intuition, Sentiment, Experience, Herding	“The difference with experienced investors [is that] they know how to assess their worst-case scenario and the risk a little better than a novice.” “[Investors] try to intuitively pick interest rates, even though none of them have an economics degree.”
Investment decision		“There was definitely some sitting on hands for a time until people had an understanding as to what the future held.” “More sophisticated investors saw a good time to exit out of those lower, more susceptible to market movement properties.”

outlines the coding framework, including illustrative examples of how codes were developed into higher-order themes. The analysis involved a cross-case review of interview transcripts to identify both consistencies and disparities in participants’ perspectives on investors’ adaptive strategies to navigate uncertainty [52]. Frequently occurring words and patterns were identified and developed into preliminary codes, which were then refined to capture unique viewpoints. These codes were subsequently organised into broader categories, forming the coding framework that underpinned the design of the conceptual map of adaptive investor behaviour. This iterative review process enabled the researcher to validate and enrich the emerging themes, reducing subjectivity and enhancing the analytical rigour of the study.

Following the thematic coding and analysis, the core themes were mapped and synthesised into conceptual model. This model was developed to represent a comprehensive framework of commercial property investors’ decision-making considerations in response to market disruptions, heightened uncertainty, and added complexity in making near-irreversible capital allocation decisions. In response to these externalities, previous research has established long and pervasive effects on performance [16,24,25], which in turn influences behaviour and alters how investors allocate capital and make decisions [5,17,18].

The proposed mind map integrates the underlying fundamentals driving performance, the behavioural lens through which investors make sense of limited information and volatile conditions, as well as key external factors that impact decisions and performance. This adaptive model emerging from this analysis provides a practitioner-informed framework through which property investment behaviour amid uncertainty can be better understood. By integrating economic, behavioural and institutional dimensions, this framework offers a more realistic and responsive framework for navigating uncertainty in property markets in response to unexpected market disruptions.

3. Results and Discussion

3.1. Underlying Reasons Why Uncertainty Impacts Property Investment Decisions

Investment decisions must inherently be made under conditions of uncertainty, as investors rarely possess perfect information about future market movements, asset performance, or broader economic shifts [2]. Asset performance, even when backed by extensive feasibility analysis and due diligence, is often influenced by external factors beyond the investor’s control [2,13,53,54]. However, the existing literature consistently shows that uncertainty becomes significantly heightened in the immediate aftermath of major market disruptions, such as the COVID-19 pandemic, geopolitical events and monetary policy interventions [16,24,25,26]. These shocks not only increase the unpredictability of returns but also challenge the reliability of previously established assumptions and investment strategies [5,18,55].

You still get one in ten enquiries that talk about a recession coming. But be mindful, people have always said that—they always say the bubble is going to burst. (PE1)

Despite the widespread notion that investors generally adopt a more cautious stance in response to uncertainty [12,18], Ahiadu et al. [17] reported a more nuanced reaction, highlighting significant differences in attitudes based on risk appetite and investment experience. Further, different classes of investors are also impacted in markedly different ways by heightened uncertainty. In particular, smaller and less sophisticated investors, such as private ‘mum and dad’ investors active in the commercial property space, tend to react more acutely to market disruptions than institutional investors, who typically operate with more structured strategies, diversified portfolios, and more expertise [42,43]. As PE5 noted, “Your mum and dad investors are the ones that (sic) are more active. And also, the climate of deals changes so much quicker with them. They feel [market movements] a lot quicker and there’s a lot more variables.” This highlights the susceptibility of private investors to external market signals, as they may be more emotionally reactive in response to short-term signals and media sentiment.

The difference with experienced investors [is that] they know how to assess their worst-case scenario and the risk a little better than a novice. A novice [will worry about] what happens if this property goes vacant for three years, whereas an experienced one [has been] through vacancies and knows it’s usually three to six months. They (experienced investors) can put a buffer in place and keep buying. (PE1)

The initial reaction to the added complexity introduced by heightened uncertainty is, unsurprisingly, caution. Many investors adopt a “wait-and-see” approach, choosing to delay investment decisions until markets stabilise or until more reliable information becomes available [1,56,57]. Specifically, when discussing notable changes in the immediate aftermath of the COVID-19 disruption, PE5 explained that: “Primarily, [investors] kept course with what they were doing, albeit there was definitely some sitting on hands for a time until people had an understanding as to what the future held. I don’t think anybody really knew what was going to happen when COVID first hit again”.

Contrary to some of the established rules of thumb, a sizeable proportion of investors also capitalise on emerging opportunities in an underperforming market, as highlighted by PE5: “The savvy investors, especially the ones that smelled a bit of blood in the water, some distress selling, they definitely entered the market. When everything falls, if you have [obtained] liquidity and funding, the opportunity rose to really make some good money in a short amount of time. There were some investors that did take it as an opportunity.” The core motivator for these aggressive investors, who disregard obvious market signals of underperformance and uncertainty, is rooted in cognitive biases rather than market fundamentals or expert knowledge. According to Gallimore and Gray [4], investors tend to supplement traditional fundamental analysis with sentiment-driven judgments to inform their strategies as market signals become ambiguous and decisions grow increasingly complex.

There are two aspects of it—optimism of picking out a bargain and [buying] at the bottom of the market. When interest rates were going up, they [would say], I’ll wait for them to come down, then I’ll jump in… [They] can have zero macro data to show [a trend] and still, human sentiment is going to change the outcome. It’s a weird human nature of trying to pick a bargain. (PE1)

3.2. Developing an Adaptive Model for Property Investment Decision-Making Amid Heightened Economic Uncertainty

In response to the increasingly volatile conditions characterising contemporary property markets, this study proposes a mind map to illustrate how investors navigate complex decision-making under uncertainty. This addresses a critical gap in the literature, where existing decision aids are underdeveloped for the property sector, largely due to its inherent heterogeneity, the illiquidity of assets, long decision cycles, and the prevalence of conservative decision-makers who are often hesitant to adopt rigid or overly technical tools [27]. Moreover, the intrinsic information asymmetry within the commercial property market poses significant challenges to the application of formal modelling or static decision aids in normal conditions, an imperfection that uncertainty exacerbates [10,58]. In this context, this study leveraged expert perspectives to conceptualise a more adaptive model of these complex relationships, presented in Figure 1.

This adaptive model of decision-making in uncertain conditions maps the key factors and interrelationships that underpin investment decisions in a constantly changing and uncertain environment. Hargitay and Yu [2] established uncertainty is a persistent feature of investment decisions, rather than an episodic anomaly. As such, any meaningful attempt to model investor decision-making must acknowledge uncertainty as a constant structural condition, rather than treating it as a temporary deviation from equilibrium, and this is doubly true due to the inherent inefficiencies of the property market [1,10,59].

Previous studies attempting to model these relationships have increasingly highlighted the role of behaviour in property investment decisions, though their approaches differ in scope and depth. Foundational behavioural finance studies in the extant literature illustrated how heuristics, judgement errors, and cognitive shortcuts shape property investment choices [4,60]. Bolomope et al. [41] also stressed the importance of considering institutional and contextual factors during market disruptions, noting that investment behaviour is influenced by belief, experience, and culture under a broader framework of a structured process.

3.2.1. The Constant Drivers: Economic and Property Fundamentals

While this study emphasises the growing relevance of adaptive behaviour and behavioural influences under conditions of uncertainty, economic and property market fundamentals remain the primary drivers of investment decisions [1,10,59,61,62]. This is well established in the literature, where fundamental factors such as interest rates, financing costs, capitalisation rates, rental yields, asset prices, vacancy rates, market demand and supply, and locational attributes have consistently been shown to influence both investment intentions and capital allocation [2,63]. Insights from the respondents of this study also highlighted the imperfect nature of markets and how investors respond to market disruptions through their interpretation of market signals.

The underlying fundamentals are not only central to profitability and risk assessments, but the interactions between them also determine broader portfolio strategy. As noted by PE7, changes in monetary policy directly affect the cost of capital, which in turn influences yield expectations and investment thresholds: “With the interest rates increasing, yes, we did see a change in the investor market. If anything, it actually took the investor out of the market”. In high-interest rate environments, investors typically demand higher returns to justify the cost of borrowing, often leading to price corrections or a re-pricing of risk across asset classes [24,26]. Similarly, metrics such as vacancy rates and rental growth forecasts shape perceptions of income stability and asset performance, especially in markets characterised by cyclical supply-demand dynamics. As one expert participant (PE5) explained, even amid market turbulence and sentiment-driven shifts, economic fundamentals continue to underpin pricing mechanisms and strategic decisions:

The underlying economic fundamentals are still responsible for market movements, regardless of what else is happening in the market. Cost of money definitely has an effect. Yields jumped up to allow for [higher] interest rates at the time. Instead of traditional assets which would have sold for 6% yields, they probably jumped to 7% yields to allow that wiggle room. (PE5)

3.2.2. Human Element: Investor Behaviour, Profile and Perceptions

Traditional efforts to debias investors are often ineffective in structurally inefficient markets because investors inevitably augment limited information with their intuition, experience and cognitive biases [4,11,28,64]. Rather than representing perfect investors with access to perfect information in a market, the proposed model instead emphasises investor heterogeneity and adaptability in response to a fluid economic climate, through the lens of behaviour [28,65]. The interaction between economic fundamentals, property performance metrics, adaptive behaviour, and broader market conditions provides a robust explanation of the real-world dynamics that shape investment decision-making under imperfect and uncertain conditions. Under such conditions, the human element emerges as a critical interpretive lens, allowing investors to make sense of complex environments by drawing on intuition, social cues, and prior experience [4,5,17].

Novice investors rarely use big data, and by that, I mean reports from Savills, CBRE, and Knight Frank, vacancy rates, and the economy. It’s always just clickbait headlines—interest rates, what inflation is doing, what unemployment is doing, what their friend told them at a barbecue and they kind of mash [all those opinions together]. [For instance], almost everyone says [they won’t invest] in office spaces because of work-from-home trends, but they have no idea what the actual vacancy rates are. (PE1)

The human element is also the source of nuance in how investors navigate uncertainty and increased complexity, most prominently driven by differences in risk tolerance, experience levels, investment goals, and access to information [11,12,17]. These behavioural patterns are not necessarily flaws [4], but an adaptive evolutionary response to make sense of complexity [28]. Practically, this strategic agility enables investors to remain responsive to changing market conditions, even when formal decision-making frameworks become less reliable [41,65,66]. From the perspective of AMH [28], such behaviour reflects the way investors evolve in response to changing environmental pressures, adjusting strategies based on feedback, emotion, and social learning rather than rigid rationality. By integrating these insights, the proposed model positions the human element at the core of property investment decision-making under uncertainty. Rather than viewing behavioural biases as distortions to be corrected, the model recognises them as functional responses to imperfect information and volatile conditions, which are ubiquitous features of commercial property markets [2,5,10].

Experienced investors perceive the market as much more profitable, whereas first-time investors perceive it as a negative and or second-guess themselves—is this a bad decision, or when is a recession going to happen? [For] someone who’s been in the market and got lots of properties, you’ve seen how much money you’ve made in the last five years, and you’re going, this is going to be OK long term, if I have that long-term approach. Novice investors have way more uncertainty in their decision-making approach. (PE1)

3.2.3. Volatile Externalities: Market Disruptions, Uncertainty, and Information Asymmetry

Volatile externalities such as market disruptions, uncertainty, and information asymmetry represent fundamental imperfections that shape, and often distort, the way decisions are made [18,34,67]. Market disruptions, such as the COVID-19 pandemic, demonstrate how rapidly changing external conditions can upend previously sound investment strategies and reshape consumer preferences. As PE1 alluded to, the performance of entire asset classes can be inhibited by an external disruption: “However, there was a bit of a struggle [with childcare centres]. Obviously, when COVID hit, because people were working from home and not sending their kids to childcare, [investors realised] it was not a great asset.” Such shifts are difficult to anticipate and often occur faster than investors can react, especially in a market where reliable, real-time data may be unavailable or difficult to interpret. In this context, investors are not simply making decisions based on fundamentals but also have to navigate information constraints and ambiguity.

The awareness of growth and what a commercial property sold for is actually a bit less, so there’s more readily available information for residential. [Investors] know exactly what properties sold for. For commercial properties, you basically can’t get that information. It’s always almost blank. (PE1)

Moreover, information asymmetry also complicates decision-making, particularly in the commercial property sector, where access to market intelligence, valuation data, and off-market activity is often uneven [68,69,70]. Larger, institutional investors may benefit from proprietary datasets and industry networks, but smaller private investors typically rely on publicly available data, media reports, or anecdotal insights [71]. This divergence in access to information not only reinforces structural inefficiencies in the property market but also creates space for behavioural biases to exert greater influence, as investors fill knowledge gaps with intuition, heuristics, or herd behaviour. The role of the media in shaping investor sentiment is particularly critical to these private investors, as oversimplification of complex market trends can amplify uncertainty and influence perception, contributing to decision-making that is emotionally driven rather than evidence-based [72,73,74].

Industrial [attracted more investors] because it got so much media [coverage] about how well it was performing, especially with the really tight vacancy rates, A lot of people [who saw] it as a bit of a dirty asset at the time jumped on because everyone started talking about it, started doing a little bit more research and then realized that industrial has been around for 100 years, it’s not going anywhere, especially with e-commerce. (PE5)

A lot of people want to get in and buy, there’s a bit of fear of missing out before the rates go down… A lot of people now think it’s a good time to buy before the rates go down because if they wait until the rates go down, there will be a rush of everyone going in. (PE3)

3.3. Implementing the Model to Improve Decision-Making Amid Heightened Uncertainty

3.3.1. Expert Perspectives on Navigating Uncertainty Through Adaptive Decision-Making

A critical foundation for improving decision-making amid uncertainty is recognising that investors are heterogeneous and all are susceptible to behavioural influences. Differences in risk appetite, experience, and cognitive capacity mean that investors respond to uncertainty in diverse ways, with some adopting cautious attitudes, while others seek out emerging opportunities [5,12,17].

[Investors] try to intuitively pick interest rates, even though none of them have an economics degree. A client will [say], we’ll probably see two or three interest rate cuts this year—and you’re like, how do you know? They’ve obviously heard it from somewhere. So, that’s a blend of investor behaviour and intuition, where they [are sure] something is going to happen without any metric or data. (PE1)

If you’re getting a lot of marketing, then you’re getting swayed by people [and] certain decisions. [Even experienced investors are susceptible] because of the herd. It’s the people that aren’t sophisticated, buying in places which changes the data metrics. And then, people who are sophisticated understand that, and then they may invest in there to take advantage of those data metrics. (PE2)

Access to more information and a better understanding of market movements are essential for enhancing decision-making in uncertain environments [58,70], as explicated by PE2: “[Due to] the substantial increase of buyers’ advocates, marketing and forums, there’s a lot more property awareness now through property professionals than ever before. That is definitely a difference maker. There’s a substantial amount more of property knowledge out there from professionals, from Facebook forums, from groups, and also from property professionals with a whole bunch of marketing”. This improved access to information can improve decision-making, but also presents potential challenges by overloading investors and further complicating an already intricate process [75,76].

There’s way more education in the commercial space now—books in stores and four or five podcast series that didn’t exist [before]. It’s more mainstream now. Commercial wasn’t even spoken about [by private investors] five years ago. The experience and education have changed the behaviour… It removes [unfounded] fear and risks—they had no knowledge five years ago, but now they’re slightly [more] understanding… Knowledge is power. People feel more empowered with a certain amount of education… People default to negative when they don’t know something. (PE1)

Beyond individual behaviour, macroeconomic policy interventions play a pivotal role in shaping market sentiment and liquidity, with direct consequences for commercial property investment [5,26,77]. PE6 highlighted the significant impact of fiscal and monetary responses during the COVID-19 crisis, where government stimulus and interest rate reductions helped stabilise investor confidence and reignited transaction activity: “With the recent rate drops and market commentary of rates going down, we’ve already seen a spike in confidence and investor appetite. Yes, [buyers are responding to the Reserve Bank’s monetary policy decisions]”. Additionally, these insights illustrate how strategic policy decisions can directly shape investor behaviour amid heightened uncertainty, when confidence is often tied less to market fundamentals than to the signals conveyed by central banks and fiscal authorities [1,5,78].

Initially, it (COVID-19) started with a lot of uncertainty [and] people not knowing what would happen to the market. But as soon as the government brought in the Jobkeeper platform and a substantial amount of other stimulus to small business entities, what that did along with a substantial amount of interest rate cuts, was significantly increased liquidity in the market. With increased liquidity, meaning more cash that people had available to them together with lower interest rates, the ability to borrow money, we saw a substantial increase in property transactions. (PE2)

Expert insights into investor decision-making during the historically uncertain period following the COVID-19 pandemic reinforce the proposition that the most effective investors demonstrate adaptive agility—a capacity to respond flexibly and strategically to the structural imperfections and volatility characteristic of the commercial property market [1,5,66]. Rather than reacting to heightened uncertainty and short-term signals in the aftermath of market disruptions, these investors adopt a strategically long-term orientation, grounding their decisions in core market fundamentals while remaining flexible in the face of disruption [5]. Their ability to recalibrate strategies in response to shifting conditions, such as rebalancing portfolios or reallocating capital toward more resilient asset classes, reflects a dynamic approach to risk assessment and opportunity recognition. This resilient adaptability is further underscored by the ability to evolve through experience, which is best represented by Lo’s [28] seminal work on the AMH and decision-making with incomplete information in imperfect markets.

Regardless of what’s going on [in the economy], [successful investors] will buy in the market that they are in—if it’s on the market, they will pay market price, if it’s a cool market, they will pick up a bargain… [Those] who cross-check every number don’t end up buying lots of properties, whereas the blasé investor [usually does] better than the person who over-analysed and only bought one property… It should be a mix between adequate due diligence using the numbers and perception in the industry. (PE1)

So, the best investors that I’ve seen do very well and adapt to [uncertainty] were the ones that did capitalise on a lot of the lower socioeconomic properties that they bought and did very well. And they then moved that money into more performing long-term assets on a little bit lower leverages because they were using the profit after tax to act as a deposit of their new properties. So, the more sophisticated investors saw a good time to exit those lower, more susceptible to market movement properties. And then put that money into more longer-term [properties which are] less susceptible to market economy movements. (PE2)

These distinct relationships may not be universally applicable across all investor types in the commercial property sector, particularly for larger, institutional investors who often have access to deeper market intelligence, diversified portfolios, and more sophisticated risk management strategies. However, they represent critical points of value for private and less-resourced investors, who typically face greater exposure to uncertainty, limited access to high-quality information, and a higher degree of irreversibility in their capital allocation decisions. For these investors, a deeper understanding of how behavioural tendencies interact with fundamental indicators and volatile market conditions can significantly improve strategic decision-making. Embedding these insights within a flexible and adaptive framework is essential for more context-aware responses, thereby mitigating the risks of overreaction, misjudged timing, or missed opportunities. Ultimately, recognising and responding to these complex dynamics is essential for supporting more resilient and effective investment outcomes in uncertain market environments.

3.3.2. Emerging Considerations: Sustainable Investment and Technology Integration

In today’s rapidly evolving investment landscape, sustainability and technology integration have become increasingly important considerations for property investors. Driven by shifting regulatory expectations, growing awareness of climate-related risks, and the long-term performance benefits associated with green and innovative assets, there is a strong case for embedding these priorities into investment strategies [79,80,81]. Jackson and Orr [82] also reported significant barriers to adoption, linked to tenant interest and the business case for sustainable solutions due to a green premium. Consequently, uptake remains uneven across the investor spectrum. Institutional investors, often guided by Environmental, Social, and Governance (ESG) mandates and long-term financial risks [80], are more inclined to integrate sustainability and technology as core investment criteria. As noted by PE5: “I think your institutional investors, yes. I think super funds, yes. So, from a larger scale, you don’t see any institutions or super funds buying fuel stations, for instance, it doesn’t fit their [corporate image].”

In contrast, many private investors remain focused on short-term performance and are slower to adopt these emerging priorities, reflecting a gap between broader market imperatives and individual decision-making behaviours. Myers et al. [83] highlighted the vicious cycle of blame between different stakeholders as a key barrier, with investors expressing some interest in adoption but limited by an apparent lack of demand. PE1 suggested an uptick in conversations about sustainable investments, although few are willing to pay a premium:

The conversation is coming up, but people aren’t willing to put their money where their mouth is—it still comes down to greed and numbers. You get a lot of people asking about solar panels—how do you pay for it, and what returns will it give? It’s never “I want to put solar panels to help the environment”. I’ve not once had that conversation. Every single time, [the focus] is what return on investment and government subsidies they can get. It’s never like I’m just feeling charitable, I want to help out the human race… But it is getting talked about more. I think it’s coming, but the driver is going to be legislation and incentives. (PE1)

I would say no, I can’t say I’ve ever had a client ask anything about that. I would say most [investors] are money-driven. If you presented two similar properties and one was eco-friendly and one was not, I don’t think they would [necessarily] choose the green option, definitely not something I ever get asked. (PE4)

This misalignment presents a practical challenge: although the long-term advantages of sustainable investment are increasingly clear, adoption at the private level lags due to perceived cost burdens, unclear value signals, and shorter investment horizons. Consequently, bridging this gap may require clearer financial rationales, tailored education, and policy mechanisms that translate sustainability into quantifiable returns for non-institutional investors. Similarly, private investors have shown reluctance to adopt emerging technologies, often due to unclear value propositions or a perception that the upfront costs outweigh tangible benefits [84,85,86]. Without clear evidence of immediate returns, many view technologies such as Artificial Intelligence (AI), Internet of Things (IoT), or blockchain as optional rather than essential, leading to slower integration compared to institutional counterparts.

Not in the lower-level space. I know a lot of the big players when they’re buying the big warehouse, it has to be AI-integrated. But the club sub-15 million aren’t thinking about it because the [properties] they are buying still is concrete tilt up panels on a roller door. They’re not buying anything significant enough to warrant changing their decision. [The institutional investors], they’re all looking at it knowing there’s going to be some restrictions put in by the government. (PE1)

4. Conclusions

Recent literature has highlighted the limitations of normative models attempting to explain property investment decision-making, given the structural inefficiencies of the asset class, the complexity of decision-making processes, and the persistent effects of uncertainty. In what is a significant departure from classical notions of EMH, the role of the human element in decision-making is now a prominent consideration when attempting to understand how investors make decisions amid volatile economic conditions. The AMH extends the classic theories of efficient markets, perfect access to information, and fully rational investors to reflect a more realistic framework of decision-making that recognises how investors adapt to volatile market conditions through evolutionary psychology. Despite further findings in support of adaptive markets and behaviour, especially in financial markets, there is still a notable gap in the literature on the decision-making considerations of commercial property investors. This gap is even more critical for private commercial property investors, who are known to be less rational than institutional investors when navigating the complex landscape of heightened uncertainty and information asymmetry in the aftermath of unexpected market disruptions.

This study addresses these gaps and contributes to the growing literature on the applications of AMH by exploring the decision-making strategies of private commercial property investors in Australia amid heightened uncertainty created by the COVID-19 pandemic, inflationary pressures, and a series of monetary policy shocks due to a series of cash rate hikes by the RBA. The perspectives of seven experienced property experts in various phases of the investment lifecycle, including acquisition, financing, advisory, and asset management, provided a well-rounded perspective on decision-making under uncertainty. Subsequently, a thematic analysis approach was operationalised to identify key themes, assign codes, classify responses into themes, and integrate themes. The emerging themes were discussed based on underlying reasons why uncertainty impacts decision-making, the intricate relationship between fundamentals and the external macroeconomic environment, persistent market inefficiencies, as well as investors’ adaptive strategies. A comprehensive mind map representing this relationship provides a more adaptive model of property investment decision-making based on market fundamentals, in a constantly uncertain environment that investors navigate through the lens of adaptive behaviour.

The findings of this study reinforce that property investment decision-making is rarely a linear process, given the pervasive effects of uncertainty about future market movements and structural inefficiencies. Instead, investors engage in a dynamic process of evaluating market signals and adapting their strategies in real-time based on perceived risks, opportunities, and informational clarity. Depending on the strength and direction of these signals, investors tend to pursue one of three pathways: capital allocation when conditions appear favourable, strategic delay when signals are ambiguous, conflicting or overwhelming, or market exit when perceived risks outweigh potential returns. Economic and property market fundamentals remain the primary drivers of investment decisions, which investors leverage to assess risk and opportunities in the market. However, rather than fully basing decisions on these statistics, investors process these signals through the lens of adaptive behaviour, guided by their intuition, experience, risk appetite, or other investors’ actions (herding). Unsurprisingly, these cognitive shortcuts are more prominent amid heightened uncertainty and among less sophisticated investors.

Practically, these findings align with the theoretical principles of real options theory, which emphasises the value of flexibility and the strategic use of timing in irreversible investment decisions. In volatile and imperfect markets, the ability to wait, rather than commit capital prematurely, is an adaptive strategy that commercial property investors exercise to retain value or avoid potential losses. Recognising the diverse decision paths investors may take under uncertainty also calls for more adaptive decision frameworks that support investor agility rather than enforcing rigid rules. This recurring theme was a particularly strong point of difference for investors during the COVID-19 pandemic, where strategic allocation of capital from the historically resilient office asset class to industrial assets yielded returns for more agile investors.

While this study provides valuable insights into how private commercial property investors navigate uncertainty through adaptive decision-making, some limitations could spur future research in this domain. Primarily, the proposed model is a conceptual mapping of how investors adapt to external market conditions amid conditions of uncertainty, which serves as a foundation for future empirical testing to develop operational frameworks. The absence of post hoc member checking also limits the extent to which the findings can be verified directly with participants; future studies would benefit from incorporating formal validation of themes through follow-up engagement. Additionally, the findings are based on a relatively small sample of expert perspectives, which, although diverse in terms of roles and experience, may not fully capture the breadth of adaptive strategies across the wider investor population. Future research could build on these findings by focusing on direct investor accounts of decision-making amid market disruptions, or by observing decision processes and outcomes as they unfold in real time. This study’s focus on private investors also excludes institutional investors, who dominate the commercial property space and are less susceptible to short-term disruptions. Further empirical testing, particularly through longitudinal or simulation-based studies, could evaluate how these pathways evolve over time or under different market shocks. The different composition of each property market and the varied policy responses to market disruptions suggest that these relationships could be unique to each market. In particular, the role of behaviour may be more prominent in less mature markets than Australia. Finally, future research could also explore opportunities to improve investment decision-making in the commercial property space as artificial intelligence becomes a more integral feature of these models.