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The purpose of this study is to investigate the phenomenon of defensive biasing in work stress surveys, which occurs when employees trivialize potential stressors and strains due to fear of negative consequences from their supervisors or management. This study aims to better understand the factors that influence this behavior and to develop a scale to measure it.

The study used an online survey of 200 employees to investigate the factors influencing defensive biasing behavior. The researchers developed a scale for defensive biasing with the help of subject matter experts and derived possible factors from the literature. Participants were presented with a hypothetical scenario in which they imagined a work stress survey in their organization and were asked to answer related items. The data were analyzed using regression analysis.

The study found that defensive biasing behavior was significantly predicted by perceived anonymity and neuroticism. Participants who felt less anonymous and had higher levels of neuroticism were more likely to engage in defensive biasing. Job insecurity and trust in supervisors were not found to be significant predictors of defensive biasing.

This study contributes to the literature on work stress surveys by developing a scale for defensive biasing and investigating the factors that influence this behavior. The study highlights the importance of making the survey process more transparent to reduce defensive biasing and obtain trustworthy results.

This paper aims to provide an elucidative and explanatory overview of decision-making theory that human resource management and development (HR) researchers and practitioners can use to explore the impact of heuristics and biases on organizational decisions, particularly within HR contexts.

This paper draws upon three theoretical resources anchored in decision-making research: the theory of bounded rationality, the heuristics and biases program, and cognitive-experiential self-theory (CEST). A selective narrative review approach was adopted to identify, translate, and contextualize research findings that provide immense applicability, connection, and significance to the field and study of HR.

The authors extract key insights from the theoretical resources surveyed and illustrate the linkages between HR and decision-making research, presenting a theoretical framework to guide future research endeavors.

Decades of decision-making research have been distilled into a digestible and accessible framework that offers both theoretical and practical implications.

Heuristics are mental shortcuts that facilitate quick decisions by simplifying complexity and reducing effort needed to solve problems. Heuristic strategies can yield favorable outcomes, especially amid time and information constraints. However, heuristics can also introduce systematic judgment errors known as biases. Biases are pervasive within organizational settings and can lead to disastrous decisions. This paper provides HR scholars and professionals with a balanced, nuanced, and integrative framework to better understand heuristics and biases and explore their organizational impact. To that end, a forward-looking and direction-setting research agenda is presented.

The global prevalence of social media and its potential to cause polarization are highly debated and impactful. The previous literature often assumes that the ideological bias of any media outlet remains static and exogenous to the polarization process. By studying polarization as a whole from an ecosystem approach, the authors aim to identify policies and strategies that can help mitigate the adverse effects of polarization and promote healthier online discourse.

To investigate online polarization, the authors perform a systematic review and analysis of approximately 400 research articles to explore the connection between cognitive bias and polarization, examining both causal and correlational evidence. The authors extensively evaluate and integrate existing research related to the correlation between online polarization and crucial factors such as public engagement, selective exposure and political democracy. From doing so, the authors then develop a PolarSphere ecosystem that captures and illustrates the process of online polarization formation.

The authors' review uncovers a wide range of associations, including ideological cognition, bias, public participation, misinformation and miscommunication, political democracy, echo chambers and selective exposure, heterogeneity and trust. Although the impact of bias on social media polarization depends on specific environments and internal/external conditions, certain variables exhibit strong associations across multiple contexts. The authors use these observations as a basis from which to construct PolarSphere, an ecosystem of bias-based polarization on social media, to theorize the process of polarization formation.

Based on the PolarSphere ecosystem, the authors argue that it is crucial for governments and civil societies to maintain vigilance and invest in further research to gain a deep comprehension of how cognitive bias affects online polarization, which could lead to ways to eliminate polarization.

The authors evaluated the impact of an anti-bias training intervention for improving police behavior during interactions with community members and public perceptions of discrimination.

Fifty patrol officers from a diverse municipal agency were randomly selected to participate in an anti-bias intervention. Before and after the intervention, a random selection of Body Worn Camera (BWC) videos from the intervention group as well as from a control group of officers was coded using a validated tool for coding police “performance” during interactions with the public. Discrimination-based community member complaints were also collected before and after the intervention for treatment and control group officers.

The treatment group had a small but significant increase in performance scores compared to control group officers, F = 4.736, p = 0.009, R2ß < 0.01. They also had a small but significantly reduced number of discrimination-based complaints compared to control group officers, F = 3.042, p = 0.049, p2 = 0.015. These results suggest that anti-bias training could have an impact on officer behaviors during interactions with public and perceptions of discrimination.

Although these results are from a single municipal police department, this is the first study to suggest that anti-bias trainings may have a positive behavioral impact on police officers as well as the first to illustrate the potential for their impact on community members' perceptions of biased treatment by officers.

Employee Stock Options [ESOs] have been used widely as a component of employees' compensation. To maximise the incentive effect of these options it is very important to understand the exercise decision of the employees. This is an important financial decision that is dependent on both rational and psychological factors. This paper aims to study the mediating role of Herding Bias on Personality Traits and the employees' decision to exercise ESOs.

The data were collected through a self-structured questionnaire from 210 employees of Banks and NBFCs [Non-Banking Financial Companies] who have received and exercised the ESOs. SPSS MACRO version 25 was used to understand the mediational effect of Herding Bias on Personality Traits and Employees' decision to exercise their ESOs.

The results showed that Personality Traits affect the employees' decision to exercise their ESOs. The study also shows a partial negative mediating effect of Herding Bias on Personality Traits and employees' decision to exercise ESOs.

Limited study has been conducted on how the employees make their decision to exercise ESOs. Although extant studies have touched upon the importance of including behavioural biases in ascertaining the exercise decision of the employees, the predictors of the behavioural biases have not been studied under this context. To the best of the author's knowledge, this study is the first in itself to study the inter-linkage between Personality Traits, Herding Bias and employees' decision to exercise ESOs.

This paper examines the relationship between behavioral biases, and demand decisions for life insurance products in Uganda.

Data were collected from 351 life insurance policyholders in Uganda. The authors used a cross-sectional survey by applying a structured questionnaire. Descriptive analysis was conducted and hypothesized relationships between the constructs were evaluated through the use of structural equation modeling.

Results indicate that, behavioral biases are significant predictors of life insurance demand among Ugandan policyholders. Also, the two behavioral bias variables (heuristic bias and prospect bias) are significant predictors of demand decisions for life insurance products.

These results are helpful for both insurers and regulators. For insurers, it is now evident that demand decisions for life insurance products are not fully rational. It is imperative for insurers to simplify life insurance product information (heuristics), integrate product education and widen dissemination of product information (prospect bias) to allow policyholders to come up with optimal demand decisions. While for insurance policymakers, the study provides an understanding of behavioral biases. With such insights, policymakers can identify exploitative and deceptive information that target policyholders to better guide life insurance documentation and product designs.

This study is the first to offer insights into behavioral biases' influence on demand decisions for life insurance products in a developing country like Uganda. By integrating prospects and expected utility theory, this study examines rationality and irrationality in demand decisions for life insurance products.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0201

The study assesses impact of individual cultural values on investment choices (aggressive or conservative), of 450 investors with behavioural biases and risk propensity in serial as mediators in the relationship.

The study used serial mediation analysis using Hayes model 6 for creating six models.

Findings of the study indicated that individualism traits are inclined to aggressive investment choices due to presence of overconfidence biases. Uncertainty avoidance and longtermism traits of investors resulted in aggressive investment choices due to presence of herd mentality bias. The moderating impact of past investing experiences was found significant.

The study indicates the importance of cultural values and past investing experiences of investors that may develop biases to assess investment choices and decisions of investors.

The purpose of this study is to explore and understand, how strong financial literacy influences the cognitive biases of students in Germany while investing. Second, it also evaluates the most influential cognitive biases that students encounter when undertaking their investment decisions within this environment.

A quantitative approach is used to assess the relationship between financial literacy and students’ investment-related cognitive biases by using the frameworks proposed by Clercq (2019) and Pompian (2012).

The results advocate that the students’ financial literacy positively impacts their cognitive biases within the investment process. It additionally revealed the most significant biases regarding students’ investment decision-making and proposed the possible reasons behind their behavioral distortions.

The study provides a detailed review of the behavioral tendencies of the younger generation while investing and creates recommendations for prospective researchers.

This research lies at the junction of the behavioral finance field, suggesting that it assists in developing a theoretical framework of cognitive biases within students’ financial decisions. Furthermore, it serves as an addition to the financial management subject course that would provide valuable insights about, first and foremost, financial literacy and subsequently, the theory behind the investment process.

This paper aims to identify the impacts of sociodemographic covariates on behavioural biases (BB) scores; the psychometric evidence of the BB measurement instruments; and the main BB that influences the decision-making of individual investors.

Papers were retrieved through search using keywords in ten databases. This systematic review is based on 69 peer-reviewed papers, most of which were published between 2017 and 2021. The relevance of the included papers was assessed through the analysis of statistical/psychometric methods used, and content analysis of the BB literature and its sociodemographic correlations.

Overconfidence is higher in men and not related to age. There was no consensus regarding the relationship between BB and other sociodemographic variables. Most measuring instruments are ad hoc, showing ≤ 4 types of psychometric evidence and assessing ≤ 9 BB. Therefore, the findings demonstrate that there is no gold standard instrument for measuring investors’ BB. Furthermore, 37 BB were cited as influencers of individual investors’ decision-making and overconfidence, herding, anchoring, representativeness and loss aversion were the most prevalent.

Considering that very few systematic reviews have been published in the behavioural finance area, this paper highlights the current state-of-the-art and identifies significant gaps in the literature that can be explored by further research.

To the best of the authors’ knowledge, this is the first systematic review that analyses the psychometric properties of instruments used for individual investors BB assessment.

This paper describes how financial professionals' behavioral biases influence their financial forecast and decision-making process. Most of the earlier studies are focused on well-developed financial markets, and little is researched about financial professionals, such as institutional investors, portfolio managers, investment advisors, financial analysts, etc., in emerging markets.

An expert-validated questionnaire measure four prominent behavioral biases and Indian financial professionals' rational decision-making process. The final sample consists of 274 valid responses using the purposive sampling technique. IBM SPSS and AMOS structural equation modeling (SEM) software are used to build measurement and structural models, multivariate analysis including regression, factor analysis, etc.

The results provide empirical insights into the relationship between behavioral biases and the decision-making process. The results suggest that the structural path model closely fits the sample data. The presence of behavioral biases indicates that financial professionals' forecasting and decision-making is not always rational but bounded rational or irrational due to these factors. Furthermore, these biases (except overconfidence bias) have a markedly significant and positive relationship with irrational decision-making.

It is critical to eradicate these psychological errors, but awareness and attentiveness toward behavioral biases may help financial professionals to make informed decisions. Investors can improve their portfolio decisions and investments by recognizing their judgment errors and focusing on specific investment strategies to mitigate the impact of these biases. It is necessary to incorporate behavioral insights while developing training techniques for financial professionals. Rules of thumb, visual tools, financial coaching and implementing social-cultural elements in training programs enable financial professionals to develop simple, engaging, appealing and customized approaches for their clients.

This novel study is the first of this kind of research that examines the relationship between financial professionals' behavioral biases and rational decision-making process. This study significantly and remarkably provides insights into irrationality in financial professionals' decision-making.