Circadian Variations and Risky Decision Making

Over the past decades, decision making under risk has garnered a great amount of attention both in the field of economics and psychology. Although state-dependent variabilities of risk taking are well-documented, little is known about the effects of a person’s preferred time of day, or chronotype, in risky decision making. Under circumstances of circadian mismatch (e.g., when an “early bird” makes decisions in the evening), research suggests that decision making may reflect a greater reliance on heuristics, such as using stereotypes in social judgments. However, the effects of circadian mismatch on heuristics in risky decision making are relatively unexplored. This paper looks into the effects of circadian mismatch on the reflection effect: a behavioral bias in financial decision making, wherein individuals are risk averse when facing potential gains, and risk seeking when facing potential losses. Participants will be randomly assigned to their circadian matched or circadian mismatched conditions and will play a series of financial gambling tasks with real monetary incentives. This study predicts that the reflection effect will be exacerbated in circadian mismatched individuals as compared to matched participants. Exploring such an effect could have real-world implications on decision making under risk by providing critical knowledge about the effects of time of day on our susceptibility to behavioral biases. It could therefore point to the existence of a more optimal time of day to engage in such critical decision making

From Bounded Rationality to Behavioral Economics

The paper provides an brief overview of the “state of the art” in the theory of rational decision making since the 1950’s, and focuses specially on the evolutionary justification of rationality. It is claimed that this justification, and more generally the economic methodology inherited from the Chicago school, becomes untenable once taking into account Kauffman’s Nk model, showing that if evolution it is based on trial-and-error search process, it leads generally to sub- optimal stable solutions: the ‘as if’ justification of perfect rationality proves therefore to be a fallacious metaphor. The normative interpretation of decision-making theory is therefore questioned, and the two challenging views against this approach , Simon’s bounded rationality and Allais’ criticism to expected utility theory are discussed. On this ground it is shown that the cognitive characteristics of choice processes are becoming more and more important for explanation of economic behavior and of deviations from rationality. In particular, according to Kahneman’s Nobel Lecture, it is suggested that the distinction between two types of cognitive processes – the effortful process of deliberate reasoning on the one hand, and the automatic process of unconscious intuition on the other – can provide a different map with which to explain a broad class of deviations from pure ‘olympian’ rationality. This view requires re-establishing and revising connections between psychology and economics: an on-going challenge against the normative approach to economic methodology.Bounded Rationality, Behavioral Economics, Evolution, As If

Understanding Construction Workers’ Risk Decisions Using Cognitive Continuum Theory

The goal of the research presented in this article was to construct a theory about the influence of decision cues on intuitive and deliberative decision-making in high-hazard construction environments. Drawing from Cognitive Continuum Theory, the article specifies a framework for understanding why and how construction workers make decisions that lead to taking or avoiding physical risks when they encounter daily hazards. A secondary aim of the research was to construct a set of hypotheses about how specific decision cues influence whether a worker is more likely to engage their intuitive impulses or to use careful deliberation when responding to a hazard. These hypotheses are described in this article, and the efficacy of the hypotheses was evaluated using cross-tabulations and nonparametric measures of association. While most of the associations between decision cues and decision mode (i.e., intuition or deliberation) identified in this data set were generally modest, none of the associations were statistically zero, thus indicating that further research is warranted based on theoretical grounds. A rigorous program of theory testing is the next logical step to the research, and the article thus concludes with numerous suggestions for extending the research and testing the proposed hypotheses

Relevant information, personality traits and anchoring effect

Although personality has been one of the most-studied factors in management and decision-making research, this stream of research has generated inconsistent support for the relationship between personality traits and individuals' susceptibility to heuristics, and therefore biased judgment. The aim of this study is to investigate how the provision of correct information and individual difference factors influence susceptibility to anchoring effect. To test this hypothesis, individual levels of the personality traits have been measured. Then, participants were provided with an anchoring task involving the Taj Mahal either providing them correct information before the experiment or not. Providing individuals with the correct information limited susceptibility to the irrelevant anchor; even if only 33% of those exactly recalled it when providing the estimate. High values in agreeableness and openness to experience were found to be related with reduced susceptibility to the anchor

Heuristics in Entrepreneurial Opportunity Evaluation: A Comparative Case Study of the Middle East and Germany

Heuristics are mental shortcuts applied, consciously, subconsciously or both, to save time and efforts at the expense of risking the accuracy of the outcome. Therefore, one might argue that it is just an accuracy-effort trade-off. Nonetheless, we ought to recognize the distinction between the circumstances of risk, where all choices, outcomes, and probabilities might be generally known, and the circumstances of uncertainty, where, at least some, are not. Traditional models like the Subjective Expected Utility (SEU) work best for decisions under risk but not under uncertainty, which portrays most situations people need to tackle. Uncertainty requires simple heuristics that are sufficient instead of perfect. In this dissertation, the notion of heuristics was researched through a comprehensive historical review that unfolded the heuristics-linked ideas of significant scholars. An explicit distinction between the deliberate and the automatic heuristics was stated with chronological categories of pre and post-introduction of the SEU theory; providing a new perspective and opening a discussion for future research to consider. Additionally, qualitative and quantitative studies were applied that produced an unsophisticated heuristic set that was used by entrepreneurs in the Middle East and Germany. Perhaps entrepreneurs, and people in general, do not always know or acknowledge their use of heuristics. But still, they use it extensively and may exchange heuristics among others. That may lead us to think that in a world where uncertainty prevails, the Homo heuristicus might become a real threat to the Homo economicus

Reasoning with heuristics

Which rules should guide our reasoning? Human reasoners often use reasoning shortcuts, called heuristics, which function well in some contexts but lack the universality of reasoning rules like deductive implication or inference to the best explanation. Does it follow that human reasoning is hopelessly irrational? I argue: no. Heuristic reasoning often represents human reasoners reaching a local rational maximum, reasoning more accurately than if they try to implement more “ideal” rules of reasoning. I argue this is a genuine rational achievement. Our ideal rational advisors would advise us to reason with heuristic rules, not more complicated ideal rules. I argue we do not need a radical new account of epistemic norms to make sense of the success of heuristic reasoning

Computational scientific discovery in psychology

Scientific discovery is a driving force for progress, involving creative problem-solving processes to further our understanding of the world. Historically, the process of scientific discovery has been intensive and time-consuming; however, advances in computational power and algorithms have provided an efficient route to make new discoveries. Complex tools using artificial intelligence (AI) can efficiently analyse data as well as generate new hypotheses and theories. Along with AI becoming increasingly prevalent in our daily lives and the services we access, its application to different scientific domains is becoming more widespread. For example, AI has been used for early detection of medical conditions, identifying treatments and vaccines (e.g., against COVID-19), and predicting protein structure. The application of AI in psychological science has started to become popular. AI can assist in new discoveries both as a tool that allows more freedom to scientists to generate new theories, and by making creative discoveries autonomously. Conversely, psychological concepts such as heuristics have refined and improved artificial systems. With such powerful systems, however, there are key ethical and practical issues to consider. This review addresses the current and future directions of computational scientific discovery generally and its applications in psychological science more specifically