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Commercial property development builds floor space in anticipation of potential, but unknown, future demand, making it particularly prone to risk and uncertainty. The research explores the degree to which property developer decision-making is objective and rational and the degree to which it relies on behavioural instincts and intuition. Decision-making theory, including heuristics, is considered and its prevalence in the field of commercial property development is examined.

A “dual-processing” decision-making model, comprising intuitive System 1 and objective System 2 processing, is proposed and tested. Inductive research using template analysis of interviews, with “high status” commercial property developers, explored whether the model offers an accurate representation of developers' behaviour and effective lens through which to examine decisions made under conditions of risk and uncertainty.

Participants believed they adopted objective and rational approaches to complex commercial property development decisions. Analysis of interviews reveals that System 1 heuristics and intuition play significant roles in decision-making behaviour, leading to potential bias and systematic error. The research concludes that the dual-processing model provides a useful lens through which to better understand the decision-making approach adopted by commercial property developers.

The research represents the rare application of behavioural theory to the realm of commercial property development and provides new and original insight as to how important investment decisions are made under conditions of risk and uncertainty, with implications for professional practice.

To: evaluate Prospect Theory and Cumulative Prospect Theory as functional models of decision making and risk within various contexts; compare and analyze risk models and decision‐making models; evaluate models of stock risk developed by Robert Engle and related models; establish whether the models are related and have the same foundations; relate risk, decision making and options theory; and develop the foundations for a new model of decision making and risk named “belief systems”.

Critiques existing academic work in different contexts. Analyzes the shortcomings of various measures of risk, and group decision making, which was not addressed in developing Prospect Theory and Cumulative Prospect Theory. Develops the characteristics of a mew model for decision making and risk named “belief systems”, and then differentiates it from belief networks.

Decision making is a multi‐factor, multi‐dimensional process that often requires the processing of information, and thus, it is inaccurate to impose rigid models in decision making; the existing metrics for quantifying risk are inadequate; Prospect Theory and Cumulative Prospect Theory were developed using questionable methods and data, and are impractical; the analysis of probabilistic insurance and most of the theories and “effects” developed by Kahneman and Tversky's articles are invalid and impractical; Prospect Theory, Cumulative Prospect Theory, Expected Utility Theory, and market‐risk models are conceptually the same and do not account for many facets of risk and decision making; risk and decision making are better quantified and modeled using a mix of situation‐specific dynamic, quantitative and qualitative factors; belief systems can better account for the multi‐dimensional characteristics of risk and decision making.

Areas for further research include: development of dynamic market‐risk models that incorporate asset‐market psychology, liquidity, market size, frequency of trading, knowledge differences among market participants, and trading rules in each market; and further development of concepts in belief systems.

Decision making and risk assessment are multi‐criteria processes that typically require some processing of information, and thus cannot be defined accurately by rigid quantitative models; Prospect Theory and Cumulative Prospect Theory are abstract, rigid, and are not practical models for decision making; and existing market‐risk models are inaccurate, and thus the international financial system may be compromised.

The issues discussed are relevant to government regulators, central banks, judges, risk managers, executives, derivatives regulators, stock exchange regulators, legislators, psychologists, boards of directors, finance professionals, management science/operations research professionals, health‐care‐informatics professionals, scientists, engineers, and people in any situation that requires decision making and risk assessment.

This case study aims to explore the perceptions and attitudes towards risk within a UK local authority and the subsequent effects on decision-making. Through a qualitative analysis of both primary and secondary data, this study advances current understanding of the complex relationships between risk and decision-making. The study concludes by suggesting how local governments may better provide value to constituents.

This research follows a single case study approach. Data were collected through both a focused online survey and semi-structured interviews. Respondents were selected through purposive sampling in order to capture direct insights and understanding of the concepts under consideration. The study focuses on a single local authority within the UK.

Building on extant literature, this case study highlights both the individual and organisational considerations towards risk perception. Following the analysis of collected data, the study highlights the influence of risk aversion and public involvement within decision-making.

By aiming to improve and advance understanding of risk and decision-making in a local authority setting, the relevance of this research may be wider than internal organisational structures. The study provides recommendations for further research towards facilitating the inclusion of the citizen within decision-making processes.

The purpose of this paper is to focus on the risk decision making of entrepreneurial team, deconstruct the intermediate process mechanism of cognitive adaptability in promoting risk decision making and reveal the role of opportunity identification and entrepreneurial efficacy in the decision-making process, which clarifies how cognitive adaptability affects decision-making speed and effect.

This study establishes a relationship model among entrepreneurial team’s cognitive adaptability, opportunity identification, entrepreneurial efficacy and risk decision making, and selects 316 entrepreneurial teams to empirically study the relationship among core variables using Bootstrap analysis and Johnson–Neyman technology.

Cognitive adaptability though has no direct impact on risk decision-making speed, whereas it directly affects risk decision-making effect; opportunity identification has a full mediating effect between cognitive adaptability and decision-making speed, and a partial mediating effect between cognitive adaptability and decision-making effect; entrepreneurial efficacy plays a moderating role between opportunity identification and decision-making speed, and a same role between opportunity identification and decision-making effect.

First, in setting the research model, the study does not take other moderators into consideration, which might be improved. Second, the study ignores the origin and formation of entrepreneurial team’s cognitive adaptability, the predisposing factors of which might be discussed in the future research.

The practical implication of this paper is to guide the entrepreneurial team to turn their focus on the impact of highly implicit cognitive adaptability on decision making, which might be divided into two aspects: the first is to enhance the cognitive adaptability of the entrepreneurial team, cultivate team members’ self-examination awareness and self-monitoring habits. The second is to strengthen team’s psychological capital and value the cultivation of entrepreneurial efficacy.

This paper breaks through the team process and structure perspectives, explores the driving mechanism of entrepreneurial team risk decision making from team cognition perspective, and deconstructs the logical framework of cognitive adaptability’s influence on risk decision making. This paper applies Johnson–Neyman technology to quantify the mediating effect entrepreneurial efficacy exerts on cognitive adaptability and decision-making speed, as well as on cognitive adaptability and decision-making effect.

To: evaluate Prospect Theory and Cumulative Prospect Theory as functional models of decision making and risk within various contexts; compare and analyze risk models and decision‐making models; evaluate models of stock risk developed by Robert Engle and related models; establish whether the models are related and have the same foundations; relate risk, decision making and options theory; and develop the foundations for a new model of decision making and risk named “belief systems”.

Critiques existing academic work in different contexts. Analyzes the shortcomings of various measures of risk, and group decision making, which was not addressed in developing Prospect Theory and Cumulative Prospect Theory. Develops the characteristics of a mew model for decision making and risk named “belief systems”, and then differentiates it from belief networks.

Decision making is a multi‐factor, multi‐dimensional process that often requires the processing of information, and thus, it is inaccurate to impose rigid models in decision making; the existing metrics for quantifying risk are inadequate; Prospect Theory and Cumulative Prospect Theory were developed using questionable methods and data, and are impractical; the analysis of probabilistic insurance and most of the theories and “effects” developed by Kahneman and Tversky's articles are invalid and impractical; Prospect Theory, Cumulative Prospect Theory, Expected Utility Theory, and market‐risk models are conceptually the same and do not account for many facets of risk and decision making; risk and decision making are better quantified and modeled using a mix of situation‐specific dynamic, quantitative and qualitative factors; belief systems can better account for the multi‐dimensional characteristics of risk and decision making.

Areas for further research include: development of dynamic market‐risk models that incorporate asset‐market psychology, liquidity, market size, frequency of trading, knowledge differences among market participants, and trading rules in each market; and further development of concepts in belief systems.

Decision making and risk assessment are multi‐criteria processes that typically require some processing of information, and thus cannot be defined accurately by rigid quantitative models; Prospect Theory and Cumulative Prospect Theory are abstract, rigid, and are not practical models for decision making; and existing market‐risk models are inaccurate, and thus the international financial system may be compromised.

The issues discussed are relevant to government regulators, central banks, judges, risk managers, executives, derivatives regulators, stock exchange regulators, legislators, psychologists, boards of directors, finance professionals, management science/operations research professionals, health‐care‐informatics professionals, scientists, engineers, and people in any situation that requires decision making and risk assessment.

Drawing on the literature on public service motivation, the authors investigate the relationship between public service motivation and defensive decision-making. Further, the authors explore risk propensity and risk perception as potential antecedents of defensive decision-making.

Based on survey data from 144 German public financial managers of municipalities and federal agencies, the authors find no significant direct relationship between public service motivation and defensive decision-making.

However, the authors can show that risk propensity fully mediates the relationship between public service motivation and defensive decision-making. The findings also indicate that beyond the public service motivation and individual risk propensity of public financial managers, their risk perception does influence their decision making.

The study makes three contributions to the literature. First, the authors contribute to the relatively small amount of research on the risk-taking behaviour of public managers by explaining the indirect impact of PSM on their risk-taking behaviour. Second, this paper furthers the understanding of the influence of risk perception and risk propensity on decision-making and enhances the models of Sitkin and Pablo (1992) and Sitkin and Weingart (1995). Third, the paper also contributes to the call for more international research on German public administrations.

Making the right bid/no-bid decision is critical to the success and development of construction contracting enterprises. Decision makers’ personal characteristics, such as risk perception and propensity, have great impact on bid/no-bid decisions, which is the major concern of this research. The purpose of this paper is to explore the relationship among decision makers’ risk perception, risk propensity, and their bid/no-bid decision making of construction projects, as well as the factors influencing the risk perception and propensity.

In total, four hypotheses were proposed based on an extensive literature review. Experimental questionnaires were distributed to employees working in Chinese construction contracting enterprises with knowledge of construction bidding, and 134 valid questionnaires were obtained. Multivariate statistical analysis through SPSS 19.0 was used to analyze the acquired data.

Data analysis shows that in the context of international construction contracting: risk perception has a negative influence on bid/no-bid decision making; while risk propensity produces a positive influence and the probability and magnitude of potential gain or loss both have significant impacts on risk perception, and the probability plays a more important role.

This research studied the bid/no-bid decision making of construction projects from the new perspectives of risk perception and risk propensity of the decision makers.

The paper proposes an innovative systemic method helping decision-makers to control servitization transition process, through decision process risk diagnosis.

The proposed method is based on the modeling of decision processes and risk identification and analysis. This method was based on an action-research approach, in close relationship with two companies (SMEs). The paper develops the feasibility experiment at Automelec company.

The method was successfully implemented and delivered concrete diagnosis results.

The generalization of the applicability of the method needs to be tested on several different cases.

The first practical implication is related to the efficiency of the method to help decision-makers in a servitization context to limit uncertainty and get a global view of the weaknesses of their decision-making process, it raises their awareness about servitization transition for their companies. Furthermore, the method also helps to explain the strategy of a servitization transition. It enhances the level of maturity of the decision process of the company, and can be used as a training/learning tool for managers.

The results brought by the research contribute to give the decision-making boards for organization living a servitization transition and especially SMEs a better control over the servitization decision process and related risks, which will increase the economic stability of the company and its vision over long, medium and short horizons. This will bring positive impact on the overall economic and social environment and networks of the servitized SME, and enhance the confidence of coworkers, subcontractors and clients.

The first originality of the paper is related to the new way of considering risk, not only as an analysis criterion but as the central driver in steering a strategic transition for the company, such as servitization. The second originality of the study is about assessing risk occurrence over a decision-making process through decision reliability and decision confidence.

This article aims to ascertain the extent to which probabilistic decision making can enable managers to make crucial decisions in a world of uncertainty associated with globalization. Existing evidence suggests that probabilistic decision making can be deployed for risk management purposes if two conditions are satisfied: the decision maker must be aware of a complete list of possible future events; and the decision maker must be able to revise his/her expectations in the light of new information about such events. This article demonstrates that the satisfaction of these conditions requires a sound understanding of the sources of risks, quantifying those risks, and assessing the probability associated with each. To ensure that these conditions are satisfied, a risk management strategy must aim to maximize the amount of information that will be available at the time of taking the decision rather than wait to learn from outcomes. Outcomes‐based justification of decisions may no longer be an effective decision‐making strategy because the stakes involved, i.e. the risks and opportunities associated with globalization, are too high. An information‐driven, proactive decision‐making strategy requires higher levels of information pooling and exchange within companies.

Purpose: Risk is a multifaceted concept, and its identification requires complex approaches that are often misunderstood. The consequence is that decisions are based on limited perception rather than the full value and meaning of what risk is, as a result, the way it is being tackled is incorrect. The individuals are often limited in their perceptions and ideas and do not embrace the full multifaceted nature of risk. Regulators and individuals want to follow norms and checklists or overuse models, simulations, and templates, thereby reducing responsibility for decision-making. At the same time, the wider use of technology and rules reduces the critical thinking of individuals. We advance the automation process by building robots that follow protocols and forget about the part of risk assessment that cannot be programed. Therefore, with this study, the objective of this study was to discover how people define risk, the influencing factors of risk perception and how they behave toward this perception. The authors also determine how the perception differed with age, gender, marital status, education level and region. The novelty of the research is related to individual risk perception during COVID-19, as this is a new and unknown phenomenon. Methodology: The research is based on the analysis of the self-administered purposely designed questionnaires we distributed across different social media platforms between February and June 2020 in Europe and in some cases was carried out as a interview over communication platforms such as “Skype,” “Zoom” and “Microsoft Teams.” The questionnaire was divided into four parts: Section 1 was designed to collect demographic information from the participants; Section 2 included risk definition statements obtained from literature and a preliminary discussion with peers; Section 3 included risk behavior statements; and Section 4 included statements on risk perception experiences. A five-point Likert Scale was provided, and participants were required to answer along a scale of “1” for “Strongly Agree” to “5” for “Strongly Disagree.” Participants also had the option to elaborate further and provide additional comments in an open-ended box provided at the end of the section. 466 valid responses were received. Thematic analysis was carried out to analyze the interviews and the open-ended questions, while the questionnaire responses were analyzed using various quantitative methods on IBM SPSS (version 23). Findings: The results of the analysis indicate that individuals evaluate the risk before making a decision and view risk as both a loss and opportunity. The study identifies nine factors influencing risk perception. Nevertheless, it must be emphasized that we can continue to develop models and rules, but as long as the risk is not understood, we will never achieve anything.