Adolescence is marked by increased risk-taking. Dual Systems Models explain this stage as an imbalance between the socioemotional reward and cognitive control systems. This study applies such models to explore neurocognitive aspects of contraceptive method (CM) use in adolescents. We analyzed trajectories of risk propensity, self-regu­lation, and consideration of future consequences (CFC), controlling for sex and socioeconomic status, in a sample of adolescents from Montevideo (Uruguay). A simple prospective longitudinal panel design was used with two time points, T1 (314 cases) and T2 (49 cases), separated by 20 months. Behavioral tasks (BART, Stoplight, Tower of London), the CFC scale, and questionnaires were used. A decrease in risk propensity and immediacy was observed, aligning with the inverted U-shaped development of the reward system. No changes were found in self-regulation or CFC-Future, consistent with models proposing a plateau in the development of the cognitive control system. Decreased risk propensity was associated with lower use of ineffective CM at last sexual intercourse. These findings highlight the importance of understanding neurocognitive development and its implications for adolescent sexual and reproductive health, particularly in Global South contexts.

This paper proposes a rigorous, enterprise-ready framework for leveraging Artificial Intelligence (AI) to strengthen strategic business decision-making in volatile, uncertain, complex, and ambiguous environments. The framework integrates five reinforcing layers: (1) problem framing and value hypotheses; (2) data readiness and governance; (3) model portfolio design; (4) human–AI teaming and controls; and (5) impact measurement and continuous learning. Strategic questions are decomposed into decision statements, testable hypotheses, and measurable value drivers, linking choices to outcomes with logic models and decision trees. Data readiness establishes standards for quality, lineage, privacy, and security, supported by metadata catalogs, access controls, and stewardship roles. Governance aligns with regulatory obligations and ethical principles to ensure trustworthy, auditable data use across the enterprise. The model portfolio blends predictive, prescriptive, causal, and generative techniques. Forecasting and uplift models quantify demand, risk, and customer propensity; optimization and simulation allocate resources under constraints; causal inference and experimentation estimate treatment effects for policy and pricing; generative AI accelerates knowledge discovery, scenario authoring, and decision briefings. An MLOps backbone orchestrates feature stores, automated pipelines, testing, deployment, and monitoring to sustain reliability, fairness, and performance. Human–AI teaming pairs algorithmic recommendations with expert judgment via decision playbooks, role clarity, and calibrated trust, enabling interrogation, sensitivity analysis, and override when required. Controls integrate model risk management with fairness, accountability, transparency, and ethics requirements, including pre-deployment testing, bias and drift monitoring, audit-ready documentation, and incident response procedures. Impact measurement connects decisions to financial and non-financial outcomes through causal evaluation, OKRs, and benefit tracking. Implementation proceeds through a pragmatic roadmap: prioritize high-leverage use cases (demand shaping, dynamic pricing, supply risk sensing, workforce planning, churn prevention), establish a federated center of excellence, and standardize reusable accelerators such as feature stores, prompt libraries, governance checklists, and value-tracking templates. The contribution is a cohesive blueprint uniting decision science, data engineering, and organizational change to de-risk AI at scale. By aligning architecture, processes, and incentives, the framework enables repeatable value creation, resilient choices under uncertainty, and measurable strategic impact. Results generalize across sectors and varying data maturities. Keywords: Strategic Decision-Making, Artificial Intelligence, Decision Intelligence, MLOPS, Data Governance, Causal Inference, Generative AI, Human–AI Teaming, Model Risk Management, Prescriptive Analytics.

New product development drives innovation, and the ability to effectively manage resources is critical during the process. Startup founders represent an authentic, unique subset of designers trying to bring innovative products to market. While prior work has identified distinct archetypes that emerge based on individual traits such as entrepreneurial self-efficacy, entrepreneurial bricolage, risk propensity, and psychological safety, little work has investigated how resource management behaviours differ across archetypes and affect firm performance. We leveraged data from 123 startup founders to study the relationship between individual traits, resource management behaviours, and firm performance. Data Envelopment Analysis was employed to determine how efficiently participants managed financial resources in The Incubator, a serious game that mimics the new product development process. Results revealed differences between archetypes in resource management. Secondary data collection leveraged available reports of annual reported revenue, resulting in data from 32 firms from the original sample. Note, as these were startups, not all had available revenue data. Results suggest that the amount of money participants spent in the game is positively correlated with firm performance and that firms led by participants with greater levels of individual traits exhibited greater firm performance, measured by annual reported revenue.

Self-driving vehicle (SDV) safety and reliability are becoming critical design parameters as SDVs increase their market share. This paper examines public preferences for key SDV safety features (system reliability, sensor resilience, failure behavior, and driver alert methods) using a choice-based conjoint survey of 403 U.S. respondents. A novel integration of conjoint analysis with Least Absolute Shrinkage and Selection Operator (LASSO) regression and generalized linear mixed-effects models (GLMMs) was applied to identify the most influential features and their demographic or behavioral predictors. Results show that multimodal driver alerts (i.e., audio + visual) were the most influential factor, accounting for nearly two-thirds of decision weight. System reliability (i.e., low human intervention rates) and sensor resilience (i.e., low tolerance for failures) were secondary, while failure behavior had minimal influence. Subgroup analyses revealed modest variations by willingness to pay for SDVs, income, race/ethnicity, marital status, education, driving frequency, and risk propensity, though the importance of alerts and reliability remained consistent across groups. This combined conjoint-LASSO-GLMM framework enhances the precision of preference estimation and offers actionable guidance for SDV manufacturers seeking to align safety feature design with consumer expectations.

This study investigates how personality traits, age, risk propensity, and structural factors influence the long-term financial success of solopreneurs, defined as solo-founded ventures typically characterized by the absence of a dedicated workforce during the early years of operation. Using data from 4,470 solo-founded ventures in the German Institute for Employment Research/Centre for European Economic Research start-up panel, we model sustained profitability over the first 7 years as a binary outcome and test seven hypotheses grounded in trait, decision-making, and resource-based theories. The regression results show that two psychological traits - Openness and Conscientiousness - significantly increase the likelihood of long-term profitability (odds ratio OR = 1.616; OR = 1.279). Preference for low-risk projects (OR = 1.607) and being age ≤ 50 years (OR = 2.126) further enhance success odds. Conversely, general risk attitude, gender, sector affiliation, and research and development involvement show no significant effects. The results challenge assumptions about sectoral or innovation-based advantages and emphasize the significance of psychological variables in solopreneurship. This study contributes to a multidimensional understanding of entrepreneurial success and supports the development of evidence-based support strategies tailored to individual trait-context combinations.

IntroductionPrevious studies have investigated the relationship between childhood experiences of harshness and unpredictability and risky adult behaviors from a life-history theory perspective. However, findings have been inconsistent, suggesting that the relationship between early environments and current behavior is complex and may be influenced by moderating variables. This study examined whether childhood harshness (resource scarcity) and unpredictability (proximal environmental instability) were positively related to risk propensity, considering reproductive strategy-related trade-offs (i.e., the age of first sexual intercourse and the age of menarche) and current environmental factors (i.e., being in a committed relationship, perceived family support, and poverty rate of the participant's municipality) as potential moderators.MethodsWe sampled 368 individuals in two settings: college classrooms and a controlled laboratory environment.ResultsOverall, we did not find a clear relationship between perceived childhood environment and risk-taking. Contrary to expectations, we found a positive relationship between perceived childhood harshness and risk propensity in women who delayed their first sexual intercourse. Exploratory analyses by data collection setting revealed that harsh and unpredictable childhood environments may impact risk propensity differently, though no coherent pattern emerged.DiscussionThis study underscores the importance of context dependence and the need to consider additional variables that may moderate the relationship between childhood experiences and risk-taking behaviors.

Purpose This study explores the factors influencing informal investment intention among future investors, particularly MBA students in India. It aims to identify key psychological, social and cognitive traits that affect investment behavior, contributing to a better understanding of informal investment dynamics in emerging economies. Design/methodology/approach The study adopted a survey approach, utilizing an expert-validated questionnaire. Data were collected from 388 students across multiple institutions. Structural equation modeling (SEM) and artificial neural networks (ANN) were used to analyze the relationships between traits like self-efficacy, subjective norms, risk propensity and entrepreneurial alertness. Findings Self-efficacy, subjective norms and entrepreneurial alertness were found to significantly influence informal investment intention. Mediation analysis revealed partial mediation by entrepreneurial alertness, while ANN results ranked self-efficacy as the most important predictor. Regulatory focus showed no significant effect. Research limitations/implications The study is limited to a student sample in India, which may not fully represent the broader population of potential informal investors. Future research could explore diverse demographic groups and longitudinal data to validate and extend these findings. Practical implications The findings suggest that enhancing self-efficacy and fostering positive subjective norms could encourage informal investment. Policymakers and educational institutions can use these insights to design targeted programs promoting entrepreneurial behavior and financial inclusion. Originality/value This study offers unprecedented insights into informal investment behavior by integrating cognitive and personality traits with behavioral intentions, providing a comprehensive framework for understanding the factors that influence informal investment in emerging markets.

Influence of eHealth literacy on acceptance of healthcare services with risks in China: chain-mediating effect of general risk propensity and self-efficacy.

Psychometric validation of the risk propensity scale among Chinese young people

Unlike previous research that examines solely the direct effects of personality traits on investment behaviour, this study introduces a mechanism to investigate how individual investors’ personality traits, combined with their overconfidence and risk propensity, jointly influence investment behaviour. The data were collected from 392 individual investors registered with the Pakistan Stock Exchange through a survey. The purposive sampling technique was used to select individual investors. Structural equation modelling was employed for data analysis using SmartPLS 3.0 software. The findings showed that conscientiousness and extraversion are the strongest predictors of investors’ overconfidence, followed by openness to experience. Neuroticism was neither supported nor found to be significant regarding investors’ overconfidence. Furthermore, investors’ overconfidence has a positive influence on their risk propensity, which, in turn, exhibits a positive association with their investment behaviour. This study is one of the earliest attempts to apply the sequential mediation approach to investigate how overconfidence and risk propensity influence investment behaviour.

The features of socially responsible business are considered, taking into account the implementation of the national project “Family”. The analysis is based on an axiological approach, which allowed us to reveal the features of the positive responsibility of business entities. Compliance and social entrepreneurship are analyzed as examples of the manifestation of an entrepreneur’s social responsibility. Constitutional principles of justice and equality play a key role in the formation of effective mechanisms for interaction between business and society. The axiological paradigm involves a detailed study of the inherent qualities and values of entrepreneurship, among which independence, a propensity for risk and a sense of responsibility stand out. The use of the systemic and institutional research method has made it possible to comprehensively assess the impact of entrepreneurial activity on the legal, economic and social spheres of society. A special place is occupied by the analysis of the interrelationships between the interests of economic entities and public needs, emphasizing their close dependence on each other

IntroductionThe role of employability in employees' unethical decision-making remains unclear. Drawing on goal shielding theory, this research investigates how internal and external employability differentially influence unethical pro-organizational behavior (UPB). We propose that these relationships are mediated by bottom-line mentality (BLM) and moderated by employees' risk propensity.MethodsWe conducted two multi-wave survey studies in China. Study 1 (N = 273) provided an initial test of the direct and curvilinear relationships. Study 2 (N = 316) tested the full mediated moderation model, with data on employability and risk propensity collected at Time 1, BLM at Time 2, and UPB at Time 3.ResultsThe findings revealed distinct pathways for the two dimensions of employability. Internal employability was negatively associated with UPB, an indirect effect mediated by a reduction in BLM. This negative indirect relationship was significantly stronger for employees with low risk propensity. Conversely, we found an indirect, inverted U-shaped relationship between external employability and UPB via BLM, such that moderate external employability was associated with the highest levels of BLM and UPB. This non-linear effect was not moderated by risk propensity.DiscussionThese findings offer a new theoretical lens for understanding the motivational mechanisms behind UPB, highlighting how internal job security can reduce unethical conduct while moderate external opportunities may paradoxically increase it. The results provide practical implications for organizations on managing employee career development to prevent unethical behavior.

How we deal with stress and certain traits of our personality can be influenced not only by psycho-social factors, but also by biological factors, including genetics. Research studies suggest that the long allele of the DRD4 gene (DRD4-7R) is associated with novelty seeking and risk taking—features potentially important for healthcare workers. The aim of this study was to assess the DRD4-7R polymorphism and its impact on propensity for risk taking and ways of coping with stress in medical professionals This preliminary study involved 82 volunteers from among active healthcare professionals, including 33 medical doctors (MDs). All participants were asked to fill out psychological questionnaires for assessment of their stress-coping strategies (Mini-COPE) and risk-taking propensity (IVE). A swab of the inside of the cheek was taken from the study participants to determine the polymorphism within the gene for the dopamine D4 receptor gene (DRD4). In our study, medical doctors (MDs) tend to have the DRD4-7R allele more often than other medical professionals. Our study also indicates that DRD4-R7 allele carriers are significantly less likely to use stimulants and other substances to help themselves with stress coping and less likely to expect emotional support. The DRD4 gene polymorphism may be important for the development of specific personality traits and ways of coping with stress. However, further research with larger numbers of participants is needed.

Children are not fully able to associate severity and injury probability with cognitive, emotional, and social factors. This study focused on physical risk-taking by exploring the associations between risk propensity and physical balance during the developmental age. Specifically, sixteen girls aged 58 to 108 months (≈ 5 to 9 years), of whom 43.75% normal-weighted and all were active in rhythmic gymnastics, were subjected to a combination of physical tests (i.e., static and dynamic) and questionnaires to evaluate balance, sensation seeking, and risk propensity, respectively. Our results showed that the better the static balance, the higher the sensation seeking and risk propensity, while age had a negligible effect on these associations. Our study suggested that balance affects propensity towards risky behaviors in children.

To identify risk factors for cement leakage (CL) in spinal fusion surgery using cement-augmented fenestrated pedicle screw (CAFPS). As a secondary objective, clinical outcomes were compared between CAFPS and conventional pedicle screw (CPS) in patients with osteoporosis. We included 67 patients (272 screws) who underwent spinal fusion surgery with CAFPS and 104 patients with CPS. In the CAFPS group, cement volume, leakage rate, and distance from the cement fenestration hole in the CAFPS to the vertebral wall were evaluated. Clinical outcomes including blood loss, operative time, number of fusion intervertebral segments, local kyphosis, screw loosening, pullout, pedicle fractures, adjacent vertebral fracture (AVF), proximal/distal junctional kyphosis (PJK/DJK), and reoperation were compared between groups. The primary outcome was identifying risk factors for CL. After propensity score matching (PSM) adjusted for age, sex, body mass index (BMI), surgical procedures, and the use of osteoanabolic agents, the secondary outcome was comparing clinical outcomes between the CAFPS and CPS groups. CL occurred in 61.2% of patients and in 23.5% of screws. A shorter distance from the cement fenestration hole in CAFPS to the vertebral wall was a predictor for CL (odds ratio [OR] 0.75, 95% confidence interval [CI]: 0.64-0.88, P < 0.001). The CAFPS group had significantly lower operative time, fused segments, loss of kyphotic correction, screw loosening, and pullout rates. Medial positioning of CAFPS may reduce CL. CAFPS use in osteoporotic spinal fusion may enhance stability, resulting in a less invasive surgery.

Acceptance of Risk and Confidence Assessing Avalanche Terrain and Conditions: A Large Cross-Sectional Study.

Entrustment in Action: Factors that Contribute to Entrustment Decision-Making Through the Lens of the Supervisor and the Intern.

Adolescence is a critical period characterized by an increased propensity for risk taking behaviors, including socially accepted addictive behaviors such as alcohol consumption, smoking, excessive Internet use, gambling, and video games. Although these behaviors are often perceived as normal or transient, they can have a significant impact on cognitive, emotional, and social development. Addictive behaviors among adolescents are a major public health concern with significant implications for their development and well-being. Socially accepted addictions, such as alcohol, tobacco, and excessive technology use, are often underestimated in terms of their negative impact. This article examines the factors that contribute to the initiation and maintenance of these addictive behaviors, including individual, family, and social influences. Long-term consequences, such as deterioration in physical and mental health, academic decline, and social dysfunction, are also examined. This paper aims to highlight the impact of substance use on personality structure and dynamics, analyzing the correlation between substance use and the risks associated with addictive behavior. To rigorously substantiate the results obtained from this study, a systematic literature review methodology was adopted, involving the critical evaluation of 58 relevant scientific articles published between 2017 and 2022. The synthesized results highlight the need to develop effective prevention and intervention measures based on education, active parental involvement, and community support.

Why do females display lower financial risk propensity than males? Evidence from structural MRI and resting-state fMRI

We live in an era marked by Black Swan events, making a clear conceptualization of risk essential for advancing public administration (PA) research. This study applies Aristotle’s rhetorical framework to analyze 302 articles from 40 PA journals, clarifying how risk is defined and suggesting future research directions. From the logos perspective, risk is framed objectively—primarily as the probability of adverse events—supporting studies on risk measurement and decision-making. The pathos perspective highlights the subjective dimension, emphasizing cognitive risk, risk culture, and perceptions of risk. The ethos perspective focuses on how risk is managed, defining it through unfavorable outcomes and pointing to new research avenues such as risk propensity and communication. By distinguishing these rhetorical lenses, this study not only reveals the multidimensional nature of risk in PA but also lays a foundation for more integrated and theoretically grounded risk research.