We study the causal effect of general education on returns to wealth ( k -returns) using a school reform that increased the length of compulsory schooling in Norway in the 1960s. OLS estimates reveal a strong, positive, and statistically significant correlation between education and returns to individual net worth. This effect disappears in IV regressions, implying that general education has no discernible causal effect on individual performance in capital markets, whose heterogeneity largely reflects individual ability and risk tolerance. In contrast, we find that education causes higher returns in the labor market ( l -returns). We consider a number of potential explanations for this important asymmetry.

• We use 2021 ECF data to analyze investor profiles in Spain. • Crypto investors are, on average, younger, male, and lower–income than stock market peers. • They show, on average, lower pension ownership and weaker retirement confidence. • Risk tolerance is higher among crypto investors, especially for younger adults. • Results support tailored financial education and differentiated regulation. This paper examines whether cryptocurrency investors differ from traditional stock market participants and identifies a third group that combines both asset types. Using data from the 2021 wave of the Survey of Financial Competencies conducted by the Bank of Spain, we analyze a nationally representative sample of Spanish households through logistic and multinomial regression models. Results show that crypto investors are more likely to be younger, male, and have lower income and educational attainment. They are also less likely to own pension products or feel confident about their retirement planning compared to stock market investors. In contrast, dual investors—those holding both crypto and traditional assets—exhibit higher financial literacy and greater risk tolerance, but do not differ significantly in income or education from stock investors. Our results reveal the existence of distinct investor profiles and highlight the need for tailored financial education and regulatory approaches that reflect the heterogeneity of market participants.

Mantle cell lymphoma (MCL) is a biologically and clinically heterogeneous B-cell malignancy with variable prognosis, ranging from indolent, asymptomatic forms to aggressive subtypes with early treatment failure. Contemporary management emphasizes risk-adapted strategies that integrate patient characteristics, clinical disease burden, and tumor biology. Prognostic tools such as the MCL International Prognostic Index (MIPI) and its biologically integrated variant (combined MIPI), alongside assessment of Ki-67 proliferation, TP53 status, and blastoid morphology, help guide treatment selection. In younger, fit patients, first-line therapy traditionally involves dose-intensified chemoimmunotherapy with high-dose cytarabine and autologous stem-cell transplantation (ASCT). The incorporation of Bruton tyrosine kinase inhibitors (BTKi), such as ibrutinib, into induction regimens has improved survival outcomes, with emerging evidence that may limit the use of ASCT to high-risk subsets. Maintenance therapy, particularly rituximab, remains crucial for durable disease control. In older or transplant-ineligible patients, bendamustine-rituximab remains a backbone therapy, with chemotherapy-free combinations incorporating BTKi, BCL2 inhibitors, and anti-CD20 antibodies offering effective, well-tolerated alternatives. High-risk patients, including those with TP53 mutations, may benefit from targeted triplet regimens or early cellular therapies. Relapsed/refractory MCL is increasingly managed with covalent and noncovalent BTKi, BCL2 inhibitors, and T-cell-redirecting therapies including chimeric antigen receptor T-cell therapy and bispecific antibodies. Ongoing trials are evaluating optimal sequencing and combination strategies to improve outcomes, particularly in high-risk and cBTKi-exposed patients. Overall, modern MCL management emphasizes individualized therapy based on biological risk, functional status, and treatment tolerability, with novel targeted and cellular approaches reshaping the frontline and relapsed treatment landscape.

This study examined the determinants of intentions to participate in digital asset investment among Thai mutual fund investors with medium-to-high risk tolerance by extending the Theory of Planned Behavior (TPB) to include financial literacy and trust. A quantitative survey was conducted with 360 respondents, and the proposed model was analyzed using structural equation modeling. The results indicate that attitudes toward behavior, subjective norms, and perceived behavioral control are positively associated with the intention to invest. Financial literacy and trust also demonstrate direct and indirect effects, with financial literacy emerging as the strongest overall predictor. In addition, perceived behavioral control and attitudes toward behavior serve as important mediating mechanisms linking cognitive and social factors to the intention to invest. The model explains 52% of the variance in investment intention, indicating moderate explanatory power. These findings suggest that intention to invest in digital assets among Thai mutual fund investors with medium-to-high risk tolerance is shaped by a combination of financial capability, social influence, perceived control, and evaluative judgment. However, these findings should be interpreted cautiously due to the purposive sampling approach and the fact that they are primarily applicable to financially experienced and relatively risk-tolerant investors rather than the broader Thai population.

Regionalization of acute care surgery (ACS) aims to improve outcomes by transferring complex cases from local hospitals to tertiary centers. Although improved outcomes have been demonstrated for select conditions, regionalization may impose social and financial burdens, and patient preferences in the ACS setting remain poorly characterized. We evaluated patient preferences and risk tolerance related to ACS regionalization in a multicenter cohort. We prospectively surveyed 602 adults with trauma or emergency general surgery (EGS) conditions at five trauma centers. Using a modified standard gamble utility assessment, patients indicated preferences for local care versus regional transfer under scenarios of equal perioperative risk and increasing hypothetical risks at their local hospital (absolute increases of 2%, 4%, 6%). Demographics and clinical variables were collected. Univariate analyses identified factors associated with local versus regional preference, and multivariable logistic regression determined independent predictors of site preference. Among 602 patients [67% EGS, 33% trauma, median age 50 (interquartile range: 24-61); 60% males], most preferred local care when complication or mortality risks were equivalent between hospitals (93% and 92%, respectively). As local risk increased, preference for local care declined; however, nearly half of patients preferred to remain at their local hospital despite a doubling of complication or mortality risk (4% vs. 2%). Preference for regional transfer at this inflection point was associated with higher household income, younger age, willingness to travel for specialty care, intensive care unit admission, and prior transfer. Trauma versus EGS diagnosis and mechanism did not predict site preference. Substantial variation in risk tolerance was observed across centers. ACS patients strongly prefer local care when outcomes are equivalent, and many are willing to forego interhospital transfer despite substantially increased risk. These findings highlight a discordance between patient preferences, risk tolerance, and regionalization practices, underscoring the need to incorporate patient perspectives into ACS transfer decision-making. (J Trauma Acute Care Surg. 2026;000: 000-000. Copyright © 2026 Wolters Kluwer Health, Inc. All rights reserved.). Prospective Observational Survey Study, Level III.

ABSTRACT Why do many individuals remain in climate-vulnerable areas despite escalating environmental hazards and, for some households, financially feasible relocation options? This study examines mobility decision-making among residents of two climate-risk-prone areas in Bangladesh. It develops a three-stage framework – appraisal & awareness, aspiration & intention, and action – to examine how cognitive and emotional considerations relate to im(mobility) preferences. The paper contributes to behavioural climate science by examining whether mechanisms usually studied in lower-stakes settings – selective information avoidance, sunk-cost sensitivity, time preferences, risk tolerance, and self-efficacy – are observable in consequential mobility decisions under climate risk. It also qualifies place-attachment accounts of immobility by asking whether attachment to place is linked not only to valued relationships and identities, but also to how people process uncomfortable risk information and evaluate prior investments. Study 1 (N = 247) used conflicting but factually correct satellite-based information: one video highlighted sea-level-rise risks such as erosion and migration pressure, while another highlighted geomorphic resilience such as land accretion and in-situ adaptation potential. Approximately 40% of respondents recommended ignoring one of the two evidence-based messages, consistent with selective information avoidance. In Study 2 (N = 385), about one-third referred to past investments in homes and land when evaluating relocation, consistent with sensitivity to sunk costs. Both tendencies appear more pronounced among individuals with strong emotional attachment to place. Across studies, stronger place attachment is associated with shorter time horizons and lower confidence in being able to adapt locally. Groups with different stay-or-move profiles also differ in willingness to take risks, including among households that appear able to afford relocation. The evidence is correlational, but it suggests that immobility cannot be understood through financial constraints, information deficits, or place attachment alone. Place-based ties may interact with behavioural frictions that shape risk appraisal, perceived feasibility, and the translation of intentions into action. Long-term adaptation support may therefore need to address not only resources and information, but also the cognitive and emotional processes through which people evaluate staying, moving, and adapting.

Surgery is an indispensable component of a health system, yet financing its delivery faces significant financing challenges. This study seeks to address the research question: What is the financial contribution of philanthropy to the delivery of surgical care in low and middle-income countries (LMICs)? This study combines a qualitative and a quantitative component to examine the magnitude of philanthropic contributions in surgical care. The qualitative analysis is composed of a narrative review of peer-reviewed and gray literature that was conducted and synthesised through thematic analysis to identify patterns of philanthropic engagement. To quantify philanthropic contributions, a cross-sectional analysis was employed by using the Organization for Economic Cooperation and Development Creditor Reporting System, to identify philanthropic funding for surgical projects between 2014 and 2022. Four thematic domains were identified from the narrative review: (1) an overview of philanthropy, highlighting its role in filling critical funding gaps in financing health systems; (2) the modes of engagement in philanthropic giving, including partnerships with multilateral organisations, corporate social responsibility, domestic philanthropy, crowdfunding and remittances; (3) recipient channels such as non-profit, non-government organisations, faith-based organisations, non-profit private hospitals and academic institutions who more often contribute to surgical service delivery, research and capacity building; (4) facilitators include flexibility and risk tolerance, contrasted by barriers such as weak policy environments and donor dependency. Quantitatively, 10 philanthropic organisations collectively funded a total of $124.8 million to surgical care from 2014 to 2022. East Asia and the Pacific received the largest share totalling $38.02 million (30.5%). Pediatric surgery received the most amount of funding at $49.07 million (39.3%), with 95.3% contributed by the UBS Optimus Foundation. Global surgery remains chronically underfunded despite its substantial burden of disease. Amid shifting financial aid landscapes, renewed philanthropic investment in global surgery is urgent. Philanthropy often focuses resources where perceived need is greatest. Although modest in scale, it has the potential to seed and catalyse surgical systems, advancing the expansion of access to surgical care in LMICs.

High-dose methotrexate (HD-MTX)-induced nephrotoxicity remains a critical clinical challenge in primary central nervous system lymphoma (PCNSL) treatment, yet quantitative tools for individualized risk prediction are currently lacking. Here, a population pharmacokinetic/pharmacodynamic analysis was performed using 5,918 plasma concentration samples from 743 Chinese adult patients. Nonlinear mixed-effects modeling was employed to establish toxicodynamic structural models driven by MTX alone, 7-Hydroxy-MTX alone, or their combination. Although all models exhibited comparable predictive performance, the MTX linear model was selected as it offered the optimal balance between predictive performance and clinical feasibility. Covariate analysis identified hemoglobin as the most significant predictor, with higher levels correlating with reduced susceptibility to renal injury. To facilitate clinical translation, exposure-toxicity probability curves were constructed, enabling clinicians to identify dynamic concentration thresholds tailored to specific toxicity grades (Grade 1 vs. ≥2 nephrotoxicity) and individualized risk tolerance. Using a 10% risk probability for Grade ≥2 nephrotoxicity as the safety monitoring threshold, the corresponding MTX concentration thresholds at 24, 48, and 72 h were 9.71, 0.81, and 0.26 μmol/L, respectively. This quantitative framework serves as an exploratory tool to complement therapeutic drug monitoring, assisting in the early identification of MTX-induced renal injury among PCNSL patients with normal to mildly impaired renal function.

Investment behaviour has emerged as a critical area of study in modern financial research, especially in developing economies like India where financial inclusion is rapidly expanding. This paper examines the relationship between income level and investment behaviour among individual investors. It explores how income influences investment preferences, risk tolerance, and decision-making patterns. The study is based on primary data collected through structured questionnaires from 100 respondents. Analytical tools such as percentage analysis and chi-square tests are used to evaluate the relationship between income and investment choices. The findings reveal that income level significantly affects investment allocation, diversification strategies, and risk appetite. Higher-income individuals tend to invest in market-linked instruments, while lower- income groups prefer safer options. The study highlights the importance of financial literacy and structured financial planning in improving investment decisions. It also suggests that policy interventions and awareness programs can help individuals make more informed financial choices. Keywords: Investment Behaviour, Income Level, Risk Tolerance, Financial Literacy, Behavioural Finance, India

Financial fraud represents one of the most critical operational risks faced by financial institutions, resulting in significant financial losses and destabilizing markets. While machine learning models are effective at prediction, their evaluation is often based on statistical performance metrics that do not directly translate into financial impact. This research develops an evaluation framework that integrates the costs of early fraud detection with predictive effectiveness and economic criteria for decision-making. Several supervised learning models (XGBoost, neural networks, Random Forest, decision trees, and logistic regression) were trained and tested on an imbalanced dataset of credit card transactions. To assess the potential benefit of these models for financial institutions, the savings rate and expected loss were employed alongside conventional metrics such as F1 score, AUC-PR, AUC-ROC, recall, and accuracy. The results show that economic outcomes are highly sensitive even among models with similar predictive performance. The ensemble methods, in particular, achieved the optimal balance between fraud detection capabilities and loss reduction, while models optimized solely for accuracy resulted in higher operating costs due to false positives or undetected fraud. The results indicate that the choice of fraud detection models should not be based solely on predictive accuracy, but also on cost asymmetry and risk tolerance. The proposed framework provides practical guidance to financial institutions seeking to align operational risk management and regulatory requirements with machine learning implementation, enabling risk-informed decision-making.

Introduction This study aimed to conceptualize how individual clinical supervisors make prospective entrustment decisions when considering trainee and supervisor factors. We sought to explore how supervisors operationalized different modes of trust (presumptive, initial, and grounded) when navigating the complexities of entrustment decision-making. Methods Between July and August 2024, experienced pharmacist supervisors across Australia participated in focus group interviews exploring how they make entrustment decisions and enact modes of trust when supervising trainees. The interview guide, informed by prior entrustment literature, explored prospective entrustment decision-making through the lens of individual supervisors. Thematic analysis was conducted using Braun and Clarke’s reflexive approach to identify themes and to interpret how supervisors’ decision-making processes aligned with different modes of trust. Results Seven focus group interviews involving 28 supervisors were conducted. Three key themes were evident: (1) Trainee trustworthiness is primarily defined by the ability of the trainee to recognize their limitations, demonstrate self-awareness, and show insight; (2) Supervisors’ entrustment decision-making is informed by their trust propensity, risk tolerance, and professional experiences and standards; and (3) The nature of the supervisor-trainee relationship shapes the act of entrustment. Supervisors emphasized the importance of direct observation and evidence accumulation in informing conscious, analytical entrustment decisions, even when prior entrustment decisions had been made by other supervisors. Discussion Entrustment decisions made by individual supervisors are grounded by accumulated evidence and establishing familiarity with the trainee. Supervisor characteristics and the supervisor-trainee relationship further influence how prospective entrustment decisions are made. Rather than relying on initial trust processes, supervisors described developing grounded trust through direct observation of the trainee and accumulation of multisource evidence to inform conscious, analytical entrustment decisions. This study offers an empirically grounded conceptual framework that deepens our understanding of how trust is enacted and developed in real-world entrustment decision-making.

Dupuytren's disease is a chronic fibroproliferative disorder characterized by progressive thickening and contracture of the palmar fascia, leading to nodules, cord formation, and varying degrees of digital flexion deformity. Although the disease most commonly affects the longitudinal fibers of the palmar aponeurosis, it can also involve distal transverse fibers, natatory ligaments, and digital fascial extensions, including Grayson's and Cleland's ligaments. Its clinical presentation is highly heterogeneous, ranging from slowly evolving, stable nodules to rapidly progressive forms associated with aggressive phenotypes such as Garrod's knuckles or spiral cords that may compromise neurovascular structures. Current evidence suggests a multifactorial etiology involving genetic predisposition, aberrant Wnt/β-catenin signaling, biomechanical stimulation, and metabolic factors such as diabetes. While open surgery (limited fasciectomy) has long been considered the gold standard for advanced contractures, its associated morbidity has prompted increasing interest in minimally invasive or adjunctive non-surgical treatments. Collagenase Clostridium histolyticum (CCH) injections have demonstrated rapid functional recovery and acceptable safety, although recurrence rates remain higher than those of open surgery. Percutaneous needle aponeurotomy offers a simple, low-cost outpatient alternative with excellent short-term correction but significant long-term recurrence, particularly in PIP joints. Radiotherapy has been proposed for early nodular disease and may stabilize progression in selected patients, yet current evidence is methodologically weak and insufficient to support routine use. Pharmacologic approaches-including antifibrotic agents, tyrosine kinase inhibitors, intralesional corticosteroids, and emerging biologics such as anti-TNF therapies-remain experimental, with limited clinical validation to date. Rehabilitation, including supervised exercises and nighttime orthoses, is frequently used following minimally invasive interventions, although high-quality evidence supporting their long-term efficacy is lacking. Overall, non-surgical therapies expand the spectrum of management options for patients with Dupuytren's disease, particularly those presenting with early-stage nodular disease or mild-to-moderate contractures who seek less invasive alternatives to open surgery. However, these treatments vary considerably in durability, recurrence rates, and level of supporting evidence. Consequently, therapeutic decisions must be individualized, taking into account disease stage, anatomical involvement, patient expectations, risk tolerance, and clinician expertise. Continued research is needed to refine patient selection criteria, optimize treatment combinations, and evaluate emerging molecular therapies targeting the disease's underlying pathobiology.

The FUTURE study (International Standard Randomised Controlled Trial Number ISRCTN63268739) has reignited debate on the utility of urodynamics, this time in women presenting with refractory overactive bladder (OAB) symptoms [1]. The study concluded that incorporating urodynamics into the diagnostic work-up does not enhance clinical outcomes. This conclusion has sparked significant criticism and controversy within the urological community, underscoring the need for critical evaluation of the pathophysiology and management of OAB in women, clinical utility of urodynamics, and the generalisability of the FUTURE study's findings [2, 3]. Over the past three decades, OAB treatment options have expanded dramatically, culminating in a strict stepwise management algorithm. However, this approach has not proved to be patient centred. Many patients find the process protracted and demotivating. Moreover, the prevailing philosophy of transitioning from least invasive to most invasive treatments may be flawed. Concerns about the long-term cognitive effects of anticholinergics raise questions about their safety compared to more invasive options, such as intradetrusor injections of botulinum toxin A or sacral neuromodulation, and the alternative pharmacotherapy, beta-3 agonists, has notably poor adherence rates. Recent updates to the AUA/Society of Urodynamics, Female Pelvic Medicine and Urogenital Reconstruction (SUFU) guidelines (https://www.auanet.org/guidelines-and-quality/guidelines/idiopathic-overactive-bladder) recommend moving away from step therapy in favour of shared decision-making and personalised treatment. Implicit in this shift toward patient-centred care in OAB management is the expectation that both clinicians and patients are equipped with adequate information to choose a treatment that maximises the likelihood of success while minimising the risk of complications. Urodynamics has long been recognised as the ‘gold standard’ for objectively diagnosing lower urinary tract (LUT) dysfunction. Furthermore, women with similar OAB symptoms can exhibit vastly different underlying dysfunctions, highlighting the necessity of urodynamics for guiding treatment decisions. One study identified BOO in 19% of women with OAB [4], for whom empirical treatments like anticholinergics or botulinum toxin would have adverse effects. Detrusor overactivity (DO) is commonly presumed to be the cause of OAB symptoms, and some argue that its presence is predictable. However, standard urodynamics demonstrates DO in only about 40–60% of patients with OAB [5]. This may be because the DO is latent (in which case ambulatory urodynamics is indicated) or DO is not the primary cause of the OAB symptoms. Again, this insight is key in determining the likely benefit of treatment options. Urodynamic parameters have not only been demonstrated to predict outcomes but also to guide choice of second-line interventions by matching their primary mechanism of action to the specific LUT dysfunction demonstrated. An under-recognised but invaluable role of urodynamic testing is its ability to support shared decision-making. By increasing diagnostic certainty and revealing underlying LUT physiology, urodynamics empowers clinicians to explain clearly why specific treatments may or may not be effective and to estimate the likelihood of benefit or adverse effects. Integrating this physiological evidence with patient preferences, symptom burden, and risk tolerance enables more informed, transparent, pragmatic and personalised treatment decisions. The FUTURE study [1] has prompted essential discussions about the role of urodynamics in the management of female OAB. The value of urodynamics in characterising LUT function to allow tailored management is undeniable. As the provision of urodynamics is often limited, the motivation to prioritise which patients would benefit the most from the test is understandable. However, limited access or funding should not be reasons to downplay its overt clinical utility, which translates into five meaningful benefits for healthcare practice and the lives of our patients (Fig. 1). As the field of urology continues to evolve, it is crucial to challenge the perception that randomised controlled trials, which assess the value of a diagnostic test with the outcomes of an intervention at a population level, represent the apex of evidence, particularly in the context of heterogeneous syndromes like OAB. A nuanced understanding of each patient's unique presentation will ultimately lead to more effective and personalised treatment strategies and fully informed shared decision-making. No conflicts exist.

This study examines the relationship between financial literacy and the investment behavior of retail investors. Retail participation in financial markets has increased significantly in recent years, yet many investors continue to make decisions without adequate financial knowledge. The paper explores how financial awareness, risk perception, and access to information influence investment choices. Secondary research suggests that financially literate investors are more likely to diversify portfolios, evaluate risk carefully, and pursue long-term wealth creation. The study concludes that improving financial literacy can enhance market participation and promote more rational investment behavior among retail investors. Keywords Financial literacy, retail investors, investment behavior, risk tolerance, portfolio diversification, behavioral finance.

The deployment of grid-forming microgrids has attracted growing attention as a pathway toward improving energy system resilience and supporting low-carbon transitions in decentralized power systems. However, the relative influence of distinct stakeholder groups on microgrid development performance remains inadequately understood in the extant literature. Grounded in stakeholder theory and informed by behavioral economics, this study develops and empirically tests a stakeholder-based framework that examines the effects of government support, investor participation, user acceptance, and utility participation on microgrid development performance. Survey data were collected from 200 stakeholders engaged in microgrid-related activities and analyzed using consistent Partial Least Squares Structural Equation Modeling (PLS-SEM). The structural model accounts for a substantial proportion of the variance in microgrid development performance (R2 = 0.647). The quantitative results indicate that all four stakeholder constructs exert statistically significant positive effects on microgrid development performance. Investor participation emerges as the strongest driver (β = 0.399, p < 0.001), followed by user acceptance (β = 0.190, p < 0.001), government support (β = 0.175, p = 0.015), and utility participation (β = 0.170, p = 0.003). Interpreted through a behavioral economics lens, these findings demonstrate that development performance is governed primarily by behavioral and perceptual factors, namely capital confidence, risk tolerance, and demand-side acceptance, rather than by technical preparedness alone. Conventional assumptions of linear adoption driven by technical superiority are therefore insufficient to account for observed development outcomes in complex, decentralized energy systems. This study advances a stakeholder-centered and behaviorally grounded understanding of grid-forming microgrid development and offers empirical guidance for designing governance frameworks that align regulatory structures with market and user behavioral dynamics.

In modern countries with more complicated financial markets, financial literacy has grown into a crucial element of responsible financial decision-making. Customers are frequently introduced to a variety of financial instruments, such as digital investing platforms, retirement plans, mutual funds, insurance products, and equities markets. Despite the growing availability of such instruments, inadequate financial knowledge often limits the capacity of individuals to make wise investing choices. Academic professionals represent a unique group within the workforce due to their high educational qualifications and relatively stable income levels; however, financial competency is not always correlated with academic discipline expertise. This study investigates the association between academic experts employed by higher education institutions in Uttarakhand, India, and financial literacy and investment decision dynamics.Using primary data collected from structured questionnaires given to faculty members in specific districts, a quantitative research approach was chosen. The survey assesses respondents' perceptions of risk, investment behavior, financial literacy, and diversification of portfolios.Using statistical methods like "regression modeling," "correlation analysis," and "descriptive statistics," the effect of financial literacy on investment decision-making was examined. The findings shows that long-term risk tolerance, financial planning, and investment behavior are significantly impacted by financial literacy among academics. While people who have lower financial literacy levels typically rely on conventional saving choices like fixed deposits and savings accounts, those with higher financial literacy levels show increased interaction with diversified investment instruments like mutual funds, stocks, and retirement funds. In order to increase financial awareness and strengthen individual financial management, the study emphasizes the significance of focused financial literacy activities within academic institutions. By concentrating on a comparatively understudied demographic group within the Indian financial literacy landscape, the study adds to the body of literature.

Purpose The study addresses two key questions: (1) How do customers' risk tolerance and relationship age moderate the effect of customer engagement on customer co-creation? (2) How does customer engagement in the co-creation process influence the success of new products? Design/methodology/approach This study develops a framework that links customer engagement, co-creation, customers' risk tolerance, relationship age, and new product success. Data were collected from customers involved in the co-creation process. Structural equation modeling (SEM) was employed to test the study’s hypotheses. Findings The findings reveal that customer engagement has a significant positive impact on customer co-creation, suggesting that engaged customers are more likely to contribute actively to the development of new products. This relationship is further strengthened when customers demonstrate higher risk tolerance and when their relationship with the firm is longer. Moreover, the results show that customer co-creation significantly enhances new product success, underscoring the value of involving customers in innovation processes to improve performance outcomes. These insights offer important implications for managing customer relationships and designing effective co-creation initiatives. Originality/value This study contributes to the literature by exploring the moderating role of customers' risk tolerance and relationship age on the link between customer engagement and co-creation. It also highlights the significant impact of customer co-creation on the success of new products, providing valuable insights for companies looking to enhance product development through customer involvement.

Understanding how farmers’ risk attitudes drive their borrowing behavior and agricultural production decisions is of significant importance for promoting rural financial innovation and sustainable agricultural development. Based on experimental and survey data from 447 agricultural operators in China (Sichuan, Chongqing, and Guizhou provinces), this study employs the “Bomb Risk Elicitation Task” to objectively quantify risk attitudes, innovatively utilizing a 3D-tensor-based neural network as a methodological cross-validation tool. To account for unobservable sample selection bias, we employ joint estimation models to systematically evaluate the impact of risk tolerance across the complete credit decision chain. The findings reveal a baseline of profound risk aversion among farmers. However, individuals with higher risk tolerance exhibit significantly stronger borrowing intentions and secure larger loan amounts. Marginal effects analysis demonstrates structural demographic heterogeneity: this risk-driven borrowing is highly pronounced among younger farmers and smaller households, whereas older and larger households exhibit attenuated responsiveness to risk attitudes. Furthermore, conditional on borrowing, higher risk tolerance drives a significant preference for formal credit channels and productive agricultural investments, ultimately leading to improved post-loan income levels. In contrast, farmers with lower risk tolerance show a preference for conservative management strategies and greater reliance on informal lending channels.

This study investigates the impact of investor awareness and behavioural factors on saving and investment decisions among young professionals residing in a Tier-III city in India. Rapid economic growth, increasing financial product availability, and the expanding middle-class population in smaller urban centers have rendered the study of investment behaviour critically relevant. Despite growing financial inclusion initiatives, empirical evidence on how awareness and psychological biases jointly influence investment decisions at the micro-urban level remains sparse. The present research adopts a descriptive and analytical research design with a quantitative approach, employing a structured Likert-scale questionnaire administered to a purposive sample of 200 young professionals. Data are analysed using SPSS through percentage analysis, Pearson correlation, multiple linear regression, independent samples t-test, and one-way ANOVA. Findings reveal that investor awareness positively and significantly affects both investment choice patterns and investment size. Demographic variables—particularly gender and income—exercise a dominant influence on investor behaviour, while psychological factors such as risk tolerance, overconfidence, and herding behaviour significantly predict investment outcomes. The study contributes to the behavioural finance literature by offering Tier-III city-specific empirical evidence, with practical implications for financial educators, policymakers, and investment advisors. Keywords: Investor Awareness, Behavioural Finance, Investment Decisions, Psychological Biases, Tier-III City, Young Professionals, Herding Behaviour, Risk Tolerance.

The research focuses on methods and software tools for decision support for the organization of distributed production of unmanned aerial vehicles (UAVs) based on digital twin and multi-agent systems technologies. The purpose of the work is to provide a critical review of existing approaches to the organization of distributed production of UAVs, as complex technical objects, and to substantiate an approach to building a multi-agent decision support system for the synthesis of a rational production structure based on digital twins of participants in production cooperation. The tasks include: classifying unmanned aerial vehicles according to the main features that determine their production specifics; analysing modern scientific publications in the field of distributed production informatization, multi-agent systems, digital twins and intelligent decision support; identifying the limitations of existing solutions; and proposing an approach to the organization of distributed production of UAVs using digital twins in the form of intelligent agents. The applied methods are based on system and classification analysis, generalization of modern scientific approaches to the organization of production, decision-making theory, the concept of multi-agent systems, digital twin technologies, production logistics and artificial intelligence. The following results were obtained: UAVs were classified by mass, purpose and level of autonomy, which made it possible to determine the specifics of their production and life cycle management. An analysis of scientific publications was performed, which showed the active development of areas related to the use of multi-agent systems, digital twins and artificial intelligence to address complex tasks in UAV life cycle management. It was established, in particular, that the works of recent years consider the issues of cooperative UAV production, the use of deep learning algorithms for decision-making in dynamic environments and the integration of digital twins into relevant production systems. At the same time, a number of limitations on the implementation of existing solutions were identified: insufficient formalization of business processes between production participants, weak integration of digital twins into production logistics, and the lack of self-organization mechanisms. An approach to solving the problem of effective organization of distributed UAV production is proposed. The architecture of a multi-agent decision support system for distributed UAV production is developed, which includes modules for coordination, self-organization, and the evaluation of the effectiveness of production configuration options, considering the initial risk tolerance indicator. Conclusions. The scientific novelty of the results obtained is as follows: an approach to solving the problem of effective organization of distributed UAV production is proposed, which, unlike existing ones, is based on the representation of production participants as digital twins in the form of intelligent agents, this enables the generation of multiple options and the subsequent selection of the most rational configuration for organizing distributed UAV production in terms of business process efficiency and the reduction of production risks. The research results create a basis for further integration of multi-agent technologies into real-world manufacturing platforms and the expansion of their application to other types of complex machinery.