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Referring to “behavioural finance” and “normative model” theories, this study explores the relative significance of behavioural heuristic biases in the investment decisions of real estate investment trusts (REITs) when compared with the conventional normative decision factors, with an ultimate aim to identify the significant behavioural factors that should be avoided to ensure rational asset acquisitions and market efficiency.

A triangulation approach was adopted. Qualitative multiple case studies were conducted, with four cases selected from Australian and New Zealand REITs across the industry, to identify what normative and behavioural finance factors are involved in investment decisions. This formed the basis for the subsequent expert review survey to explore how significant the behavioural factors were manifested in the judgement when compared with the normative factors.

Three out of four theoretical behavioural factors manifested themselves in the investment decisions: investor sentiment, anchoring factors and overconfidence. The overall impact of these three behavioural factors was that they were as significant as normative factors in investment decisions. The heuristic availability of information was found to have no significant effect on experienced REIT fund managers.

The findings were based on four multiple cases and an expert review survey of six frontline fund managers, which form a baseline upon which further research can be conducted to widen the scope of research to cover all REITs in Australasia so that the results can become more robust to benefit the entire market in the region.

As behavioural factors are significant in the decision-making process, REIT fund managers should raise awareness to avoid the significant behavioural factors identified, in particular investor sentiment, which was found to be the most significant one.

This study confirms the relative significance of behavioural factors in property investment decisions within the context of Australasian REITs and alerts fund managers to the ways they should follow to ensure rational investments and market efficiency. It also extends the scale of existing studies to cover not only Australia but also New Zealand for the benefit of the entire Australasian market.

Healthcare property has become an important alternate property sector in recent years for many international institutional investors. The purpose of this paper is to assess the risk-adjusted performance, portfolio diversification benefits and performance dynamics of French healthcare property in a French property portfolio and mixed-asset portfolio over 1999–2020. French healthcare property is seen to have different performance dynamics to the traditional French property sectors of office, retail and industrial property. Drivers and risk factors for the ongoing development of the direct healthcare property sector in France are also identified, as well as the strategic property investment implications for institutional investors.

Using annual total returns, the risk-adjusted performance, portfolio diversification benefits and performance dynamics of French direct healthcare property over 1999–2020 are assessed. Asset allocation diagrams are used to assess the role of direct healthcare property in a French property portfolio and in a French mixed-asset portfolio. The role of specific drivers for French healthcare property performance is also assessed. Robustness checks are also done to assess the potential impact of COVID-19 on the performance of French healthcare property.

French healthcare property is shown to have different performance dynamics to the traditional French property sectors of office, retail and industrial property. French direct healthcare property delivered strong risk-adjusted returns compared to French stocks, listed healthcare and listed property over 1999–2020, only exceeded by direct property. Portfolio diversification benefits in the fuller mixed-asset portfolio context were also evident, but to a much lesser extent in a narrower property portfolio context. Importantly, this sees French direct healthcare property as strongly contributing to the French property and mixed-asset portfolios across the entire portfolio risk spectrum and validating the property industry perspective of healthcare property being low risk and providing diversification benefits in a mixed-asset portfolio. However, this was to some degree to the loss or substitution of traditional direct property exposure via this replacement effect. French direct healthcare property and listed healthcare are clearly shown to be different channels in delivering different aspects of French healthcare performance to investors. Drivers of French healthcare property performance are also shown to be both economic and healthcare-specific factors. The performance of French healthcare property is also shown to be different to that seen for healthcare property in the UK and Australia. During COVID-19, French healthcare property was able to show more resilience than French office and retail property.

Healthcare property is an alternate property sector that has become increasingly important in recent years. The results highlight the important role of direct healthcare property in a French property portfolio and in a French mixed-asset portfolio, with French healthcare property having different investment dynamics to the other traditional French property sectors. The strong risk-adjusted performance of French direct healthcare property compared to French stocks, listed healthcare and listed property sees French direct healthcare property contributing to the mixed-asset portfolio across the entire portfolio risk spectrum. French healthcare property’s resilience during COVID-19 was also an attractive investment feature. This is particularly important, as many institutional investors now see healthcare property as an important property sector in their overall portfolio; particularly with the ageing population dynamics in most countries and the need for effective social infrastructure. The importance of French direct healthcare property sees direct healthcare property exposure accessible to investors as an important alternate real estate sector for their portfolios going forward via both non-listed healthcare property funds and the further future establishment of more healthcare REITs to accommodate both large and small institutional investors respectively. The resilience of French healthcare property during COVID-19 is also an attractive feature for future-proofing an investor’s portfolio.

This paper is the first published empirical research analysis of the risk-adjusted performance, diversification benefits and performance dynamics of French direct healthcare property, and the role of direct healthcare property in a French property portfolio and in a French mixed-asset portfolio. This research enables empirically validated, more informed and practical property investment decision-making regarding the strategic role of French direct healthcare property in a portfolio; particularly where the strategic role of direct healthcare property in France is seen to be different to that in the UK and Australia via portfolio replacement effects. Clear evidence is also seen of the drivers of French healthcare property performance being strongly influenced by healthcare-specific factors, as well as economic factors.

There is strong excitement during Ponzi schemes and financial bubble periods. This emotion causes investors to turn to “unknown and new investment instruments”. This study, the factors that made “unknown and new investment instruments” preferable to “known and experienced investment instruments” were investigated.

It was taken into account unconscious like phantasy, emotional like emotional intelligence, both affective and cognitive like financial literacy and subjective beliefs like trust and overconfidence. In addition, risk preferences were measured with four different risk variables. In this context, data were collected by online survey method between November 2020 and May 2021 with convenience sampling. First, the data were collected from 832 participants in the pilot study. Additional data were also collected using convenience sampling and online surveys, and a total of 1,692 participants were obtained. Data were analyzed using Statistical Package for the Social Sciences (SPSS) 25 and AMOS 24.

As a result of the analyses made, the variables that lead investors to choose “unknown and new investment instruments” were determined as risky investment intention, phantasy, risk taking/risk avoidance, confidence, risk tolerance and subjective financial literacy. Trust and risk perception have a very weak effect on preferences. However, no effect of emotional intelligence and objective financial literacy was detected. In addition, a moderately positive and significant relationship was found between objective and subjective financial literacy. Subjective financial literacy was found to have a strong and significant relationship with emotional intelligence, confidence, trust, risky investment intention and phantasy.

This study investigates the factors underlying individuals' investment preferences from a broad perspective. We think that this study is unique in this structure and wide variables. We believe that the findings obtained in this manner are unique to both academics and practitioners. We also believe that the findings of the study will make an important contribution to understanding participation behavior in various Ponzi schemes and financial bubbles.

Stock markets are considered as the largest and most important units for the development and growth of the economy. The present study attempts to provide a comprehensive view of factors influencing investment decision making process of stock market investors. A multi group analysis of gender is also carried out on the proposed model.

The data of 402 valid responses are collected through structured questionnaires from individual investors of North India. SPSS 23 is used to do the descriptive analysis and AMOS 22 is used to establish the validity of the constructs and for hypotheses testing. For performing multi group analysis, several invariance tests have also been conducted to check the robustness of the model.

The results reveal that all the factors such as firm image, accounting information, neutral information, advocate recommendation and personal financial needs significantly influence investment decision making concluding image of the firm being the most influential factor and advocate recommendation being the least influential factor for investment decisions. No significant differences between males and females were found.

The current study suffers from the limitation of restricted geographical area of North India. Moreover, there is also a scope to incorporate more demographic factors for predicting investment decisions.

This study incorporates a range of factors which covers all the aspects of investment decision making. This study also highlights the notion of signaling theory, thus contributing to the limited literature in Indian context.

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

The purpose of this paper is to study the relationship between board attributes and national culture on firms’ investment decisions.

The study used data from listed firms from seven Sub-Saharan Africa countries. Descriptive analysis was performed to provide the background statistics of the variables examined. This was followed by regression analysis, which constitutes the main data analysis.

The multiple regression analysis results indicate a negative relationship between uncertainty avoidance (UAI) and corporate investment decisions. The study also found that there is a negative relationship between the interaction between UAI and the number of independent board members and corporate investment decisions.

This study is one of the few to measure the influence of governance variables and national culture on corporate investment decisions in Sub-Sahara Africa.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

Robotic process automation (RPA) has recently emerged as a technology focusing on the automation of repetitive, frequent, voluminous and rule-based tasks. Despite a few practical examples that document successful RPA deployments in organizations, evidence of its economic benefits has been mostly anecdotal. The purpose of this paper is to present a step-by-step method to RPA investment appraisal and a business case demonstrating how the steps can be applied to practice.

The methodology relies on design science research (DSR). The step-by-step method is a design artefact that builds on the mapping of processes and modelling of the associated costs. Due to the longitudinal nature of capital investments, modelling uses discounted cashflow and present value methods. Empirical grounding characteristic to DSR is achieved by field testing the artefact.

The step-by-step method is comprised of a preparatory step, three modelling steps and a concluding step. The modelling consists of compounding the interest rate, discounting the investment costs and establishing measures for comparison. These steps were applied to seven business processes to be automated by the case company, Estate Blend. The decision to deploy RPA was found to be trivial, not only based on the initial case data, but also based on multiple sensitivity analyses that showed how resistant RPA investments are to changing circumstances.

By following the provided step-by-step method, executives and managers can quantify the costs and benefits of RPA. The developed method enables any organization to directly compare investment alternatives against each other and against the probable status quo where many tasks in organizations are still carried out manually with little to no automation.

The paper addresses a growing new domain in the field of business process management by capitalizing on DSR and modelling-based approaches to RPA investment appraisal.

This study aims to explore and clarify the mechanism by which recognition-based heuristic biases influence the investment decision-making and performance of individual investors, with the mediating role of fundamental and technical anomalies.

The deductive approach was used, as the research is based on behavioral finance's theoretical framework. A questionnaire and cross-sectional design were employed for data collection from the sample of 323 individual investors trading on the Pakistan Stock Exchange (PSX). Hypotheses were tested through the structural equation modeling (SEM) technique.

The article provides further insights into the relationship between recognition-based heuristic-driven biases and investment management activities. The results suggest that recognition-based heuristic-driven biases have a markedly positive influence on investment decision-making and negatively influence the investment performance of individual investors. The results also suggest that fundamental and technical anomalies mediate the relationships between the recognition-based heuristic-driven biases on the one hand and investment management activities on the other.

The results of the study suggested that investment management activities that rely on recognition-based heuristics would not result in better returns to investors. The article encourages investors to base decisions on investors' financial capability and experience levels and to avoid relying on recognition-based heuristics when making decisions related to investment management activities. The results provides awareness and understanding of recognition-based heuristic-driven biases in investment management activities, which could be very useful for decision-makers and professionals in financial institutions, such as portfolio managers and traders in commercial banks, investment banks and mutual funds. This paper helps investors to select better investment tools and avoid repeating the expensive errors that occur due to recognition-based heuristic-driven biases.

The current study is the first to focus on links recognition-based heuristic-driven biases, fundamental and technical anomalies, investment decision-making and performance of individual investors. This article enhanced the understanding of the role that recognition-based heuristic-driven biases plays in investment management. More importantly, the study went some way toward enhancing understanding of behavioral aspects and the aspects' influence on investment decision-making and performance in an emerging market.