Impact Of Cognitive Biases Research Articles

Software architecture for implementing a personal budget manager with artificial intelligence

The rapid adoption of artificial intelligence (AI) in consumer markets has led to the need for extensive research into its impact on consumer behavior, particularly in how it exploits cognitive biases. This raises ethical questions and highlights the need to balance such influences with AI systems that help consumers, not manipulate them. The development and implementation of an intelligent financial management system, which not only automates financial processes, but also integrates AI-driven tools to support better financial decision-making, contributes to solving these problems. The work contains a description of the development of the architecture of an intelligent financial management system, which is aimed at solving problems related to financial illiteracy, the complexity of financial markets, and the impact of cognitive biases on financial decision-making. The system provides for the use of modern technologies of artificial intelligence and machine learning to automate financial processes and provide users with personalized recommendations. The development of a system based on microservice architecture requires the use of certain architectural patterns that ensure efficiency, reliability and scalability, so the work was based on a critical analysis of modern architectural paradigms, such as microservice architecture and Event-Driven Architecture. The implementation of AI supports ethical guidelines that prioritize transparency, fairness and consumer autonomy, i.e. ensure that the AI ​​system is free from bias, actions can be easily interpreted by users. The methodology of this research is based on an interdisciplinary approach that combines the analysis of architectural solutions, methods of machine learning and artificial intelligence with methods of ensuring the reliability and scalability of software systems.

The Impact of Cognitive Biases and Emotional Factors on Investor Behavior and Stock Market Anomalies

The Impact of Cognitive Biases and Emotional Factors on Investor Behavior and Stock Market Anomalies

Impact of Cognitive Biases on Investment Intentions: Exploring the Mediating Role of Self-Esteem among Indian Emerging Investors

Impact of Cognitive Biases on Investment Intentions: Exploring the Mediating Role of Self-Esteem among Indian Emerging Investors

The impact of cognitive biases, mental models, and mindsets on leadership and change in the health system.

Understanding how cognitive biases, mental models, and mindsets impact leadership in health systems is essential. This article supports the notion of cognitive biases as flawed thinking or cognitive traps which negatively influence leadership. Mental models that do not fit with current evidence limit our ability to comprehend and respond to system issues. Resulting mindsets affect cognition, behaviour, and decision-making. Metacognition is critical. The wicked problems in today's complex health system require leaders and everyone involved to elevate their personal, organizational, and disciplinary perspectives to a systems level. Three examples of mental models/mindsets are reviewed. They do not change simply because we wish or will them to. The first step is being aware of what they are and how they impact our thinking and decision-making. Some tips for managing these traps are offered as examples of how to challenge our leadership approach in the health system.

Cognitive Factors in Social Anxiety Disorder and Relevant Interventions

Understanding how social interactions and fear responses affect mental health requires research on cognitive aspects of social anxiety disorder (SAD). SAD could be a substantial factor in a person's emotional, interpersonal, and professional areas of life. By examining cognitive issues, researchers can develop more effective treatments by understanding the biases and thought patterns that can contribute to the emergence and duration of SAD. Previous research focused on cognitive functioning, self-esteem, attentional biases, and the impact of cognitive biases on social interactions. The information-processing model and the cognitive model of SAD, which emphasizes negative interpretations and high expectations of oneself, are the main theories. To improve therapeutic outcomes, studies primarily focused on people with social anxiety across a range of age groups. In looking at different studies done on interventions for SAD, it has been shown that individualized treatment plans had the greatest impact on diminishing SAD symptoms and treating individuals to overcome their anxiety.

Navigating the narrowing effect of public discourse for a healthier future.

This article explores the concerning phenomenon of the narrowing effect in public discourse, particularly in the context of healthcare and Medicare. It discusses the challenges posed by this narrowing effect, the impact of cognitive biases, and the ethical dilemmas faced by healthcare providers and organizations when patients take their concerns public. The article also emphasizes the importance of responsible leadership and offers navigation for overcoming the narrowing of public discourse.

The impact of cognitive biases on the believability of fake news

ABSTRACT Modern technologies, especially social networks, contribute to the rapid evolution and spread of fake news. Although the creation of fake news is a serious issue, it is the believability of fake news and subsequent actions that produce negative outcomes that can be harmful to individuals and society. Prior research has focused primarily on the role of confirmation bias in explaining the believability of fake news, but other biases are likely. In this research, we use theories of truth and a taxonomy of 10 cognitive biases to conduct an exploratory, qualitative survey of social media users. Five cognitive biases (herd, framing, overconfidence, confirmation, and anchoring) emerge as the most influential. We then propose a Cognitive Bias Mitigation Model of methods that could reduce the believability of fake news. The mitigation methods are grouped according to three themes as they relate to the five biases.

Corporate capital allocation: a behavioral perspective and guidance for future research

PurposeThe purpose of this integrative review is to develop a holistic behavioral framework on capital allocation decisions.Design/methodology/approachThe article first structures, maps and synthesizes the prevalent cognitive biases that are present during capital allocation decisions. It then seeks to offer a robust understanding on how firms can mitigate the effects of cognitive biases.FindingsNot only do several cognitive biases interfere with a decision-makers ability to make adequate capital allocation decisions but firms already have a number of tools at their disposal to mitigate them.Research limitations/implicationsBesides identifying cognition- and repair-based implications to extend the literature, this article outlines key methodological challenges for future research conducted along the lines of capital allocation.Practical implicationsSince the paper structures cognitive limitations in one of the most important managerial decision-making processes and discusses what firms can do to counteract them, it is of high relevance for practitioners. Managers need to know what drives successful capital allocation and what not.Originality/valueThe article provides a rare integrative review on the impact of cognitive biases on capital allocation and addresses the need to build linkages to the ongoing conversation on how to design strategic decision processes.

The influence of cognitive bias on crisis decision-making: Experimental evidence on the comparison of bias effects between crisis decision-maker groups

A crisis requires the affected population, governments or non-profit organizations, as well as crisis experts, to make urgent and sometimes life-critical decisions. With the urgency and uncertainty they create, crises are particularly amenable to inducing cognitive biases that influence decision-making. However, there is limited empirical evidence regarding the impact of cognitive biases on estimation, judgment, and decision-making tasks in crises. Possible biases occurring in crises are: (1) to be influenced by how information is framed (i.e., framing effect), (2) to overly rely on information that confirms rather than opposes preliminary assumptions (i.e., confirmation bias), (3) to rely heavily on a skewed informational cue when making estimations (i.e., anchoring bias), and (4) to see the own decision-making as less biased than decision-making of others (i.e., bias blind spot). We investigate these four cognitive biases using three online survey experiments targeting crisis-affected people of the general public (n = 460, mTurk workers), governmental and non-profit workers (n = 50, mTurk workers), and crisis experts (n = 21, purposefully sampled). Our findings show that crisis experts are the least biased group but are still significantly affected by anchoring, framing, and bias blind spot. Crisis-affected people from the general public showed the strongest susceptibility to all four biases studied. The findings have implications for future research on crisis information systems (IS) design. As crisis response is increasingly facilitated through IS, we propose debiasing functions that account for biased user behavior in crises.

A framework for human-centered production planning and control in smart manufacturing

Smart manufacturing systems have to meet high performance expectations in form of customer individual products, short lead times, high due date reliability and resilience by the integration of new technologies and by intelligent process design. The planning and control of such smart manufacturing systems necessitates several instances of human decision-making. The latest research at the nexus of operations management and psychology reveals that human decision-making in such fast-paced, dynamic and complex environments is often biased, resulting in suboptimal operational performance. Human-centered design of planning and control processes can mitigate biased decisions, thus boosting performance in smart manufacturing systems. Current research is silent about the impact and mitigation of cognitive biases in operations management, though. We intend to close this research gap. We combine systematic reviews of literature on behavioral operations management and cognitive biases in operations management, particularly in production planning and control with an in-depth case study based on 12 expert interviews. We explore two decision-making models and combine them in a PPC framework. We create a framework for human-centered PPC in smart manufacturing systems, which includes the main impact factors, challenges and performance capabilities. Based on a detailed case study of a steel producer, we present a framework of human-centered PPC comprising five hypotheses on the impact of cognitive biases on human decision-making and on manufacturing performance.

The Impact of Cognitive Biases on Professionals' Decision-Making: A Review of Four Occupational Areas.

The author reviewed the research on the impact of cognitive biases on professionals’ decision-making in four occupational areas (management, finance, medicine, and law). Two main findings emerged. First, the literature reviewed shows that a dozen of cognitive biases has an impact on professionals’ decisions in these four areas, overconfidence being the most recurrent bias. Second, the level of evidence supporting the claim that cognitive biases impact professional decision-making differs across the areas covered. Research in finance relied primarily upon secondary data while research in medicine and law relied mainly upon primary data from vignette studies (both levels of evidence are found in management). Two research gaps are highlighted. The first one is a potential lack of ecological validity of the findings from vignette studies, which are numerous. The second is the neglect of individual differences in cognitive biases, which might lead to the false idea that all professionals are susceptible to biases, to the same extent. To address that issue, we suggest that reliable, specific measures of cognitive biases need to be improved or developed.

Impact of Cognitive Biases on Forecasting

Impact of Cognitive Biases on Forecasting

The Impact of Cognitive Bias on Students’ Programming Performance in an Introduction to Programming Course

The Impact of Cognitive Bias on Students’ Programming Performance in an Introduction to Programming Course

Which eye are you looking through? The impact of cognitive bias on process safety

AbstractBias surrounds us every day. Everything we look at has a lens of our experience coloring our perception, and everyone has their own lens. This impacts how we share and receive information. So why is this important for process safety? Cognitive biases cover a range of aspects, each of which can have an impact on process safety, from what we remember, to coping with too much information, to a lack of context and meaning or a need to act with great haste. There are many identified specific cognitive biases, not every one of them impacts on process safety, but many can and have. This paper will review several process safety type incidents that had cognitive bias as a factor and discuss ideas on how to manage the bias, so we do not fall into its trap.

How Human Decision-making Biases Influence Health Outcomes in Patient Care

Purpose: Medical treatments and medical decision making are mostly human based and therefore in risk of being influenced by cognitive biases. The potential impact could lead to bad medical outcome, unnecessary harm or even death. The aim of this comprehensive literature study is to analyse the evidence whether healthcare professionals are biased, which biases are most relevant in medicine and how these biases may be reduced.
 Approach/Findings: The results of the comprehensive literature based meta-analysis confirm on the one hand that several biases are relevant in the medical decision and treatment process. On the other hand, the study shows that the empirical evidence on the impact of cognitive biases on clinical outcome is scarce for most biases and that further research is necessary in this field.
 Value/Practical Implications: Nevertheless, it is important to determine the extent to which biases in healthcare professionals translate into negative clinical outcomes such as misdiagnosis, delayed diagnosis, or mistreatment. Only this way, the importance of incorporating debiasing strategies into the clinical setting, and which biases to focus on, can be properly assessed.
 Research Limitations/Future Research: Though recent literature puts great emphasis on cognitive debiasing strategies, there are still very few approaches that have proven to be efficient. Due to the increasing degree of specialization in medicine, the relevance of the different biases varies.
 Paper type: Theoretical.

The association between cognitive biases and the quality of strategic decision making: Evidence from Jordanian banks

Excellence in strategic decision making is the driving force behind successful strategy adoption and implementation. However, it is becoming more and more complex as businesses emerge in unpredictable environments and conditions. The main objective of this study is to investigate the impact of cognitive bias and its dimensions (the illusion of control, prior hypothesis bias, escalating commitment bias and representativeness, and availability bias) on strategic decision making. In terms of methodology, the study used a random sampling technique. The study applied a survey as a research tool distributed among 138 bankers (employees at the managerial level) in managerial and administrative positions. Further, descriptive analysis and regression analysis were used to analyze the data and test hypotheses. The results show a positive and significant effect of the illusion of control and representativeness. The results show that the illusion of control, prior hypothesis bias, escalating commitment bias and representativeness, and availability bias significantly impact the strategic decision-making in Jordanian banks. It is concluded that the null hypothesis will be accepted and, therefore, the alternative hypothesis will be rejected based on the significant levels for the primary and secondary hypotheses. The factors of the escalating commitment bias, the availability bias, and the reasoning by analogy were not significant. Finally, the study recommends developing more literature on integrating psychology and discrimination and applying the research to different industries and managerial levels.

Impact of Cognitive Biases on Progressive Visualization.

Progressive visualization is fast becoming a technique in the visualization community to help users interact with large amounts of data. With progressive visualization, users can examine intermediate results of complex or long running computations, without waiting for the computation to complete. While this has shown to be beneficial to users, recent research has identified potential risks. For example, users may misjudge the uncertainty in the intermediate results and draw incorrect conclusions or see patterns that are not present in the final results. In this article, we conduct a comprehensive set of studies to quantify the advantages and limitations of progressive visualization. Based on a recent report by Micallef et al., we examine four types of cognitive biases that can occur with progressive visualization: uncertainty bias, illusion bias, control bias, and anchoring bias. The results of the studies suggest a cautious but promising use of progressive visualization - while there can be significant savings in task completion time, accuracy can be negatively affected in certain conditions. These findings confirm earlier reports of the benefits and drawbacks of progressive visualization and that continued research into mitigating the effects of cognitive biases is necessary.

The Impact of Cognitive Biases on User Decision Making in Human-Computer Interaction: A Review of the Literature

The Impact of Cognitive Biases on User Decision Making in Human-Computer Interaction: A Review of the Literature

Cognitive biases and decision-making strategies in times of change: a systematic literature review

PurposeIn a work environment marked by unprecedented complexity, volatility and ambiguity, managers must accomplish their objectives while navigating many challenges. This paper aims to investigate potential interrelations among environmental transformations, cognitive biases and strategic decisions. In particular, the purpose of the study is to crystallize the state of art on the impact of cognitive biases on strategic decisions, in the context of environmental transformations.Design/methodology/approachThe authors have conducted a systematic literature review to identify existing relevant work on this topic and to detect potential avenues for future research.FindingsThe findings highlight how decision-making is influenced and enabled by internal (e.g. perception) and external factors (e.g. digitalization). Specifically, the strategic role of cognitive biases appears to be crucial when investigating the related impact on strategic decisions in times of environmental transformation.Practical implicationsImplications are drawn for scholars and practitioners interested in evaluating the role of specific decision-making determinants for the formation and implementation of strategic decisions. In this sense, we stress that decision-makers need to manage their cognitive biases and select the right information out of a wide data set in order to adapt to environmental transformations.Originality/valueBy systematizing the literature review, potential interrelations among environmental transformations, cognitive biases and strategic decisions are identified. Furthermore, the primary phases that drive the decision-making process are proposed (analysis, decision, onboarding and control).

Enhancing banks’ strategic decision-making: Building on behavioural strategy — Application to Pillar 2 regulation

Market and regulatory pressure on bank boards and the current unpredictable environment have put more emphasis on enhancing strategic decision-making processes by systematically integrating risk analysis. This strategic risk management issue is at the heart of the Pillar 2 regulation. In line with its stated objectives, through one comprehensive Pillar 2 package, the board formally approves the bank’s strategy and financial projections, namely the impact of all strategic management actions, over a relevant time horizon and under business-as-usual and stress situations. This paper presents a practical approach to expand the value of costly Pillar 2 achievements by refining their mandatory approval process. The approach builds on insights from behavioural strategy, an evolving research discipline concerned with the impact of cognitive biases and social behaviour on decision-making. Behavioural strategy provides a better understanding of the biases to which the approval process of the bank’s strategy and business model embedded in the Pillar 2 package is particularly prone. Sixteen biases common to allocation processes and forward-looking planning are defined. To counteract these biases, limited safeguard questions are articulated and a proposal is made to embed these questions into a formal policy governing the approval process of the Pillar 2 assessments. An additional suggested summary of the key assumptions and outcomes of these assessments - covering (a) integrated performance and risk maps and (b) forward-looking stress tests identifying key vulnerabilities- provides the board with an integrated perspective on the riskiness of the business strategy and management decisions.