In the trap of certainty: the role of confirmation bias in criminal justice

Arguably, the relationship between the mass media and the criminal justice system is one of the more important, especially regrading the formation of criminal justice policies and general decision-making in the system.1 Criminal justice policy and decision making are both systematic and individual case level phenomena (Doppelt, 1990). That is, criminal justice policy is ultimately determined by both ad hoc decisions made by criminal justice personnel and offenders regarding individual crimes and cases and by system-wide decisions that affect entire classes of offenses and cases.2 In the area of media and criminal justice, two questions arise. The first, "What is the relationship between the media and criminal justice decision making?," has not been answered with any clarity and leads to a second question, "Despite a significant amount of research and interest, why isn't the relationship better understood?" This essay discusses underlying methodological problems that make deciphering the media and criminal justice relationship inherently difficult. Some of these problems are common issues found throughout the social sciences. However, they are exacerbated in the media-criminal justice area. Other problems are unique to the media-criminal justice relationship and arise due to the existence of unusual media relationships with criminal justice policy and decision-making.

We identify and present Brazil's most common behavioral and heuristic biases in judicial decision-making. Through bibliographic and specific cases, we notice the occurrence of the representativeness heuristic, availability heuristic, anchoring heuristic (anchoring effect), confirmation bias, and affect heuristic bias in Brazilian judicial decisions. We also present the current state of Brazilian legislation and its amendments that aim at impartiality in the production, the assessment of evidence, and the judge's conviction. Finally, we present the suggestions and initiatives that aim to mitigate biases and heuristics in judicial decision-making in Brazil, especially with awareness techniques, the replacement of judges by algorithms, and the review of judicial decisions by collegiate bodies.

Behavioral finance incorporates the field of psychology into finance and studies the behavior of individual which are guided by behavioral biases. The current study aims to examine the behavioral biases which can be seen in Nepalese stock investor and studies if the behavioral biases affect the financial decisions of investor or not. The study tested the following behavioral bias: Loss Aversion, Overconfidence, Optimism, Mental Accounting, Illusion of Control, Confirmation and Status Quo Bias. The data was collected from 136 respondents. The sample size was set as minimum of 120 on the basis of rule of thumb of Roscoe (1975). Likewise, four in-depth interviews were taken in order to collect response from institutional investor. The number of interviews for institutional investor was determined on the basis of Rao soft Sample Size Calculator. The study showed that Loss aversion, overconfidence and confirmation bias were correlated with financial decision making of the investor. The correlations were significant. But the regression analysis showed that there is influence of loss aversion, overconfidence and optimism bias in the financial decisions. Confirmation bias did not have significant relationship. Also, the behavioral bias as a whole affects the financial decisions. Likewise, the study also showed that status quo bias and mental accounting bias are prevailed in the institutional investor. These biases also influenced the individual investor financial decisions. As a whole the study shows that Nepalese investor are influenced by behavioral biases.

PURPOSE – Investment decisions are pivotal in shaping individuals' financial well-being and long- term wealth accumulation. However, these decisions are not always made rationally and objectively. Instead, they are often influenced by various psychological factors, including cognitive biases and sociocultural factors, such as gender. Understanding the interplay between gender dynamics and cognitive biases in investment decision-making is crucial for devising effective strategies to enhance financial literacy, promote gender equality, and optimize investment outcomes. Hence, the purpose of this research is to confirm the variables influencing cognitive behavioral biases such as overconfidence bias, confirmation bias, representativeness bias and anchoring bias of male and female investors in their investment decisions.RESEARCH DESIGN – In the current research study, a sample of 400 responses was gathered with the help of questionnaires and retail investors in India were the respondents for the study. Cronbach’s Alpha as used to check the reliability of the data gathered and Confirmatory Factor Analysis (CFA) was used to confirm the variables for the study.FINDINGS – This research paper delivers a second-order CFA model that displays adequate fit for both genders, with some variances in factor loadings, variances, and residuals. This proposes that while the overall structure is dependable, there are gender-specific gradations or shades.ORIGINALITY/VALUE – The study of behavioral bias in decision-making is a dynamic field, with each research study yielding varying results. There are numerous scales available for measuring behavioral biases. The items and dimensions of behavioral biases are well-defined, leading the study to employ Confirmatory Factor Analysis (CFA) to validate the variables influencing behavioral biases in the context of investment decisions among both men and women. The findings of this research are intended to lay the groundwork for further large-scale research.

Cognitive biases significantly influence decision-making in the business world, often leading to irrational choices that impact organizational success. This paper explores the role of cognitive biases in business decision-making and their implications for achieving business excellence. It categorizes key biases, such as confirmation bias, anchoring bias, and loss aversion, and examines their effects on leadership, strategy, and organizational behavior. Additionally, it discusses methods to mitigate these biases through evidence based decision-making and psychological interventions. Understanding and managing cognitive biases can enhance business performance, foster innovation, and drive sustainable success.

Cognitive biases significantly influence decision-making in the business world, often leading to irrational choices that impact organizational success. This paper explores the role of cognitive biases in business decision-making and their implications for achieving business excellence. It categorizes key biases, such as confirmation bias, anchoring bias, and loss aversion, and examines their effects on leadership, strategy, and organizational behavior. Additionally, it discusses methods to mitigate these biases through evidence-based decision-making and psychological interventions. Understanding and managing cognitive biases can enhance business performance, foster innovation, and drive sustainable success.

The desire to better understand design cognition has led to the application of literature from psychology to design research, e.g., in learning, analogical reasoning, and problem solving. Psychological research on cognitive heuristics and biases offers another relevant body of knowledge for application. Cognitive biases are inherent biases in human information processing, which can lead to suboptimal reasoning. Cognitive heuristics are unconscious rules utilized to enhance the efficiency of information processing and are possible antecedents of cognitive biases. This paper presents two studies that examined the role of confirmation bias, which is a tendency to seek and interpret evidence in order to confirm existing beliefs. The results of the first study, a protocol analysis involving novice designers engaged in a biomimetic design task, indicate that confirmation bias is present during concept generation and offer additional insights into the influence of confirmation bias in design. The results of the second study, a controlled experiment requiring participants to complete a concept evaluation task, suggest that decision matrices are effective tools to reduce confirmation bias during concept evaluation.

This study aims to analyze the influence of risk propensity on various cognitive biases in investment decision-making among investors in Indonesia. The research method uses a quantitative and exploratory approach with questionnaires distributed to 110 individual investors. The results of the study show that risk propensity has a significant positive influence on belief perseverance bias and information processing bias. Furthermore, the study found that risk propensity is also associated with several dimensions of cognitive bias, such as conservatism bias, confirmation bias, representativeness bias, and cognitive dissonance bias. However, the influence of risk propensity was not significant on illusion of control bias, self-attribution bias, and outcome bias. These findings provide important implications for investment management firms in identifying clients' risk profiles to help them overcome cognitive biases in investment decision-making.

PurposeEvery day, critical care providers in the prehospital setting respond to time sensitive and outcome-critical emergencies, often in unfamiliar environments with little or no prior knowledge about the patient. In these demanding situations, they must make multifactorial clinical decisions that may be critical for the patient’s life and future health. Errors in this complex decision-making have identified as a significant cause of patient harm and, consequently, there is increasing research focus upon clinical decision-making and risk mitigation in prehospital critical care. Cognitive biases have been identified as a common cause of these systematic errors in the hospital environment and these studies inspired the aim of this article to map current evidence and investigate, “What cognitive biases affects clinical decision-making in prehospital critical care”.Materials and methodsA scoping review was conducted following Joanna Briggs Institute`s framework, by searching OVID MEDLINE and PubMed, EMBASE, and Cochrane for articles, no restrictions were set for type of article. Articles describing cognitive biases and clinical decision-making in pre-, and in-hospital critical care were included. Additionally, a search in Google scholar was conducted using keywords identified in included articles.ResultsFive hundred unique articles were identified through the search, of which 16 articles examining cognitive biases and clinical decision making in critical care were included, with only two articles focussed exclusively on prehospital critical care. Twenty-eight unique cognitive biases were identified in these articles. The most identified cognitive biases were, anchoring bias, framing effect, availability bias, confirmation bias, overconfidence bias, premature closure, and omission bias. Twelve articles described contributing factors for cognitive biases and these were categorized into 3 main categories. The main categories identified were lack of unbiased feedback, social behaviour and beliefs, and time pressure. Eleven articles proposed mitigation factors, which were categorized into 3 categories, consisting of feedback and follow-up, organizational culture, and education and training.ConclusionsThis scoping review has identified several cognitive biases that affect clinical decision-making, as well as research gaps in both pre- and in-hospital critical care. Identified evidence suggest that both clinicians and organisations are affected by cognitive biases in clinical decision-making in critical care. Future research should aim to establish how these cognitive biases affect clinical decisions in prehospital critical care, and what measures may mitigate the consequent errors, may reduce patient harm, and improve outcomes.

With the gradual increase of social competition, the enterprise's financial investment management has become an important way to obtain economic benefits and achieve sustainable development. Based on the author's work practice, this paper first analyzes the enterprise investment decision makers' cognitive bias and irrational behavior, and then, it puts forward the financial innovation strategies of the enterprise investment decision: The enterprise investment decision maker must be familiar with the characteristics of various cognitive biases and irrational behaviors in the investment decision, be good at learning, understanding and accepting new investment idea of behavior finance, keep calm, self-discipline mentality, implement collective decision-making and scientific decision-making, establish an investment project termination mechanism.

Rape myths, or false beliefs about rape and sexual assault, held by professionals in the American Criminal Justice System have contributed to reduced rates of sexual offense case reporting, biased investigative procedures, and the nonprosecution of offenders. Thus, Rape Myth Acceptance (RMA) has been considered by scholars to be a direct contributor to the under-sentencing or non-sentencing of perpetrators of sexual assault and rape. Prior research on RMA in the American Criminal Justice System has disproportionately focused on criminal justice students and law enforcement professionals. With the potential to influence victim reporting and rape case outcomes, an understanding of RMA held by actual decision-makers in all steps of the criminal-legal process is needed. This study extends prior research in this area by examining RMA among various criminal justice decision-makers, including police officers, prosecuting attorneys, and jurors, and comparing the RMA held by a sample of criminal justice decision-makers to that of a sample of the general public. Specifically, this study used data collected from a nationwide survey of criminal justice decision-makers (n = 228) and members of the general public (n = 865) to examine the presence and predictors of RMA. Findings reveal that, in the aggregate, while both samples held RMA scores indicative of nonacceptance of such attitudes, criminal justice decision-makers reported higher RMA than members of the general public, with younger males, more conservative-leaning respondents, and higher socioeconomically advantaged individuals holding the highest rates of RMA in both samples. Policy implications, limitations, and directions for future research based on these findings are discussed within.

Cognitive biases play a significant role in the decision-making process covering medical, financial, social, and personal choices. Our review indicated that the need for reliable measures to assess perception of cognitive biases. The current study aimed to develop a self-report measure to assess the perception of cognitive biases in decision-making and to test its initial psychometric properties. In the study, exploratory factor analysis was conducted with Sample 1, while confirmatory factor analysis confirmed a six-factor model in Sample 2, showing satisfactory reliability. The total sample consisted of 453 randomly selected Turkish adults, 302 of whom are women (66.67%), and 151 are men (33.33%), with ages ranging from 18 to 65 years (M = 33.25, SD = 9.50). Cronbach’s alpha coefficient was 0.88, indicating good internal consistency. The Perception of Cognitive Biases in Decision-Making Scale (PCBDM-S) scores were found to be negatively correlated with mindfulness scores. PCBDM-S consists of six dimensions: Framing and Anchoring bias, Overconfidence bias, Sunk-Cost bias, Status-Quo bias, Confirmatory bias, and Availability bias. The findings provide preliminary evidence of the psychometric properties of the PCBDM-S, suggesting that the scale holds promise for further validation as a tool to assess perception of cognitive biases in decision-making.

Cognitive biases have been intensely studied in security markets so far (Simon 1987). Flyvberg (2005) also found, that project management decisions in the construction of infrastructure suffer from cognitive biases. In the field of real estate development investment decisions no empirical analysis of these social-psychological effects like miscalibration (e.g. Zacharakis/Sheperd, 2001), over optimism (e.g. Heating, 2002) or escalating commitment (Staw/Ross 1987) are known so far. A lot of actual large scale projects like the new Berlin Brandenburg Airport or the new Hamburg Opera House Elbphilharmonie, which is one of the 10 most expensive single building project developments of the last years gives a lot of impressionistically evidence, that the cognition bias of project investment decision makers is one of the most important reasons for running out of time and costs.Therefore we develop a model of cognition biases in real estate development decision situations containing the most relevant biases and the key types of decision makers and situations. Real estate development decisions differ from security investments, because there are several parties who work together in one relatively long lasting project, while they can physically see the project and it's success grow.In a large-scale empirical survey among all types of real estate project decision makers (e.g. sector, hierarchy, personal experience) we analyze and compare the individual degrees of cognition biases with methods coming from the empirical social research. We measure cognition biases and their specific reasons. The results of several univariate and multivariate analyses show heavily cognition biases in real estate investment decisions, which vary intensely between different types of decision makers. Especially in real estate development decisions the degree of bias depends on the individual objective and subjective knowledge and the incentives of the decision maker. We also found evidence, that the degree of the bias in decision situations, which results in inefficiency, is not given, but can reduced by far. So we are able to derive some methodological implications for theory and practice in the field of efficient institutionalizing the project.

Purpose The purpose of this study is to address a critical gap in enterprise resource planning (ERP) implementation process for small and medium-sized enterprises (SMEs) by acknowledging and countering cognitive biases through a cognitive bias awareness matrix model. Cognitive biases such as temporal discounting and optimism bias often skew decision-making, leading SMEs to prioritize short-term benefits over long-term sustainability or underestimate the challenges involved in ERP implementation. These biases can result in costly missteps, underutilizing ERP systems and project failure. This study enhances decision-making processes in ERP adoption by introducing a matrix that allows SMEs to self-assess their level of awareness and proactivity when addressing cognitive biases in decision-making. Design/methodology/approach The design and methodology of this research involves a structured approach using the problem-intervention-comparison-outcome-context (PICOC) framework to systematically explore the influence of cognitive biases on ERP decision-making in SMEs. The study integrates a comprehensive literature review, empirical data analysis and case studies to develop the Cognitive Bias Awareness Matrix. This matrix enables SMEs to self-assess their susceptibility to biases like temporal discounting and optimism bias, promoting proactive strategies for more informed ERP decision-making. The approach is designed to enhance SMEs’ awareness and management of cognitive biases, aiming to improve ERP implementation success rates and operational efficiency. Findings The findings underscore the profound impact of cognitive biases and information asymmetry on ERP system selection and implementation in SMEs. Temporal discounting often leads decision-makers to favor immediate cost-saving solutions, potentially resulting in higher long-term expenses due to the lack of scalability. Optimism bias tends to cause underestimating risks and overestimating benefits, leading to insufficient planning and resource allocation. Furthermore, information asymmetry between ERP vendors and SME decision-makers exacerbates these biases, steering choices toward options that may not fully align with the SME’s long-term interests. Research limitations/implications The study’s primary limitation is its concentrated focus on temporal discounting and optimism bias, potentially overlooking other cognitive biases that could impact ERP decision-making in SMEs. The PICOC framework, while structuring the research effectively, may restrict the exploration of broader organizational and technological factors influencing ERP success. Future research should expand the range of cognitive biases and explore additional variables within the ERP implementation process. Incorporating a broader array of behavioral economic principles and conducting longitudinal studies could provide a more comprehensive understanding of the challenges and dynamics in ERP adoption and utilization in SMEs. Practical implications The practical implications of this study are significant for SMEs implementing ERP systems. By adopting the Cognitive Bias Awareness Matrix, SMEs can identify and mitigate cognitive biases like temporal discounting and optimism bias, leading to more rational and effective decision-making. This tool enables SMEs to shift focus from short-term gains to long-term strategic benefits, improving ERP system selection, implementation and utilization. Regular use of the matrix can help prevent costly implementation errors and enhance operational efficiency. Additionally, training programs designed around the matrix can equip SME personnel with the skills to recognize and address biases, fostering a culture of informed decision-making. Social implications The study underscores significant social implications by enhancing decision-making within SMEs through cognitive bias awareness. By mitigating biases like temporal discounting and optimism bias, SMEs can make more socially responsible decisions, aligning their business practices with long-term sustainability and ethical standards. This shift improves operational outcomes and promotes a culture of accountability and transparency. The widespread adoption of the Cognitive Bias Awareness Matrix can lead to a more ethical business environment, where decisions are made with a deeper understanding of their long-term impacts on employees, customers and the broader community, fostering trust and sustainability in the business ecosystem. Originality/value This research introduces the original concept of the Cognitive Bias Awareness Matrix, a novel tool designed specifically for SMEs to evaluate and mitigate cognitive biases in ERP decision-making. This matrix fills a critical gap in the existing literature by providing a structured, actionable framework that effectively empowers SMEs to recognize and address biases such as temporal discounting and optimism bias. Its practical application promises to enhance decision-making processes and increase the success rates of ERP implementations. This contribution is valuable to behavioral economics and information systems, offering a unique approach to integrating cognitive insights into business technology strategies.

The study covers how cognitive biases are involved in financial choosing and considers their possible effect on auditing and risk management in large organisations. When organisations face highly dynamic and important situations, anchoring, overconfidence, confirmation bias, herd behaviour, framing effects and the availability heuristic make it difficult for decisions to be made wisely. Bias in companies can change the way they handle financial matters such as budgeting, making forecasts and investing, creating problems that auditors and risk managers must handle. Prospect theory, behavioural finance, agency theory and internal control frameworks are used in this review to blend and expand ideas that explain how biases appear in finance, audit and risk management. They show that negative thinking patterns are shared throughout an organisation and can cause conflicts between departments. For example, being too confident about financial estimates can make audit scepticism less effective if people have confirmation bias. On the other hand, well-organised approaches such as clear decision-making, learning new ways of behaving and using AI systems can help solve bias at various places. The review further points out that boards and audit committees help detect and prevent biassed choices and create a culture that encourages people to challenge them. Apart from suggesting actions for businesses, the review points out there are few studies and little publicly available data on how cognitive biases play out in organisations and on testing strategies to overcome them. Working on these deficiencies would be important for further academic work. All in all, the study supports the idea that tackling cognitive biases benefits decision-making, the organisation’s abilities to withstand stress and stakeholder trust in major companies.