Digital public services must control fraud, error, and consequential mistakes without excluding legitimate users. Existing reasonableness, proportionality, sludge audit, screening, and digital-burden approaches identify relevant principles but do not specify how incomplete evidence about one friction should change its operational status. This conceptual analysis develops behavioral risk–friction fit (BRFF), which treats justification as a time-indexed, revisable state. It separates design form into parallel claimed-mechanism and group-conditioned burden pathways, assessed through protection- and user-side outcomes before normative status. After a legal-authority precondition outside the trivalent structure, three behavioral criteria operate in a conditionally iterative procedure. Gate 1 tests incremental protection. Gate 2 screens lower-burden alternatives across primary and all material secondary protection outcomes using prespecified protection-loss margins (ε_k). G3(f) evaluates the current design, whereas G3(a|f) evaluates a protection-screened candidate. Candidate Found—Pending G3(a|f) is an intermediate routing state; completed behavioral assessments return Pass, Fail, or Unknown and map asymmetrically to four statuses and actions. Protection margins apply only to protection outcomes; access and rights floors remain non-compensable. Only controls with at least Grade C support may be used provisionally, with safeguards, evidence milestones, and constrained renewal. A worked SNAP application converts a measured access gain and unmeasured integrity effect into a testable action. Two hypothetical records demonstrate completed Justified and Sludge paths without treating illustrative values as evidence. BRFF contributes an auditable evidence-to-status transition framework with empirically testable behavioral inputs and revisable decision consequences.
IntroductionEmotions are widely recognized as influencing financial decision-making under uncertainty, yet it remains unclear whether pre-trading emotional predispositions are associated primarily with investment performance or with the way investors engage with the market. This study examines whether positive and negative pre-trading emotional predispositions are more closely associated with portfolio return or with trading style in a controlled stock market simulation.MethodsData were collected during a four-hour stock market simulation involving 133 second-year undergraduate students enrolled in a Bachelor's program in Management Sciences. Participants traded CAC 40 stocks under realistic market conditions, including transaction costs, without constraints on the number of trades or position size. The simulation incorporated a bonus-based incentive system, and participants received continuous feedback on their ranking throughout the session. Several composite scores were constructed to capture positive and negative pre-trading emotional tone, simulation-specific emotional expectations, and broader positive and negative emotional predispositions. Exploratory mediation-style analyses were conducted with portfolio return as the dependent variable and four behavioral indicators as potential descriptive channels: total number of transactions, average transaction volume, portfolio standard deviation, and average cash holdings relative to initial capital.ResultsNone of the composite emotional indices was significantly associated with portfolio return, and the mediation-style analyses did not reveal significant estimated indirect paths through the behavioral indicators. However, consistent differences emerged in trading style. Positive pre-trading emotional predispositions were associated with larger transaction sizes, greater portfolio variability, and lower cash holdings, whereas negative pre-trading emotional predispositions were associated with smaller positions, lower portfolio variability, and higher cash holdings.DiscussionThese findings suggest that pre-trading emotional predispositions are more closely associated with trading style than with final investment performance. They indicate that emotional predispositions are reflected more clearly in patterns of market engagement than in portfolio returns, highlighting the importance of considering behavioral processes when examining how emotions influence financial decision-making.
Kenya's informal sector remains excluded from formal trade due to fragmented regulation, complex standards, and the significant expansion of digital marketplaces. Drawing on market data, legislative review, and reputable literature, we identify regulatory gaps that impede compliance by informal Micro, Small, and Medium Enterprises (MSMEs), as well as significant behavioural obstacles, including elevated perceived compliance costs, information asymmetries, and limited trust. We propose a framework featuring informal MSME-specific, graduated standards, digital market surveillance, and platform-based seller verification, all aimed at fostering trust and reducing compliance friction. By addressing both behavioural and regulatory gaps, this approach seeks to enhance consumer protection, empower informal MSMEs, and promote inclusive growth in Kenya. Future research should evaluate the framework's effectiveness and scalability in Kenya and similar contexts across Africa and beyond.
Japan's rapidly aging society and pension-related deficits highlight the importance of household financial asset formation. Despite policies such as the Nippon Individual Savings Account, Japanese households still allocate over half their portfolios to deposits. While financial literacy has been linked to retirement planning and investment participation, existing research is largely correlational. This study uses individual-level data from the 2022 Financial Literacy Survey. We apply the Fast Causal Inference algorithm, which accommodates latent confounders, to examine causal relationships between financial literacy and financial activities, specifically investment participation and retirement planning. Our findings indicate that increasing financial literacy may not directly boost engagement in financial investments or retirement planning in Japan, which underscores the necessity for alternative strategies to motivate financial activities among Japanese households. This research offers valuable insights for policymakers focused on improving financial wellbeing by advancing the use of causal discovery algorithms in understanding financial behaviors.
Behavioral economics has transformed public policy by identifying how cognitive limitations and biases systematically distort individual decisions. Yet the field's dominant tools, nudges that target cognitive heuristics and choice architecture, leave a powerful behavioral mechanism largely unaddressed: affect (good-bad feelings). In the domains where behavioral public policy is most urgently needed, from climate change to effective charitable giving to long-term health investment, the primary failure is not cognitive but affective. People endorse high-impact options in the abstract but feel emotionally drawn toward low-impact alternatives. We introduce Affective Paternalism (AP) as a theoretical framework that positions affect as a policy resource rather than a bias to correct. AP's operative tool is the cudge: a liberty-preserving intervention that works by redesigning the emotional texture of choices rather than their cognitive structure. The CARE taxonomy (Create, Attenuate, Reinforce, Eliminate) provides a systematic framework for designing such interventions. Using scope insensitivity and impact neglect as the central case study, we show how CARE interventions can redirect emotional engagement from low-impact to high-impact behaviors without reducing individual welfare or constraining autonomy. We argue that in domains where felt reward is decoupled from actual impact, affective interventions offer a welfare-superior approach to behavior change: they achieve large societal gains at negligible affective cost to individuals. We further show that AP satisfies the criterion of asymmetric paternalism, creating large benefits for those whose decisions are affectively miscalibrated while imposing little or no cost on those whose felt responses are already well-aligned with welfare. We derive testable predictions and identify a research agenda for affect-informed behavioral public policy.
We trust strangers every day. Deciding to trust another depends on the social and legal environments that influence calculative trust as well as unconsciously processed neural signals. Unenforceable communication (“cheap talk”) has been shown to increase cooperative behaviors, but why it does this is not well-understood. Herein we test whether physiologic synchrony during pre-decision communication explains why one would trust a stranger when the money at risk is meaningful. Working-age adults discussed how to share $480 before making sequential decisions in private. The social interaction was structured so that the first decision-maker had to sacrifice money s/he controlled by sending it to the second decision-maker in order to grow the money at stake. Electrodermal activity was captured during communication and two measures of synchrony, intersubject correlation and dynamic time warping, were evaluated for their predictive accuracy. We found that the dynamic time warping measure of synchrony predicted trust with a stranger with 60% accuracy, a 15% improvement over the accuracy using intersubject correlation. Our findings demonstrate that dynamic time warping is a more effective measure of physiologic synchrony, leading to new insights into the mechanisms through which communication influences the decision to trust a stranger.
PurposeIn an era marked by heightened market volatility and growing investor responsibility, understanding the psychological determinants of sound investment behaviour has become increasingly important. This study examines how emotional intelligence (EI) shapes investment performance (IP), with overconfidence bias (OB) and self-regulation (SR) acting as mediators and financial literacy (FL) serving as a moderator.DesignA quantitative, cross-sectional research design was employed. A structured questionnaire was administered to 448 active investors in India, predominantly working professionals aged 30–60 years who actively managed their own investment portfolios. Participants were selected through purposive sampling. The proposed conceptual model was tested using confirmatory factor analysis and structural equation modelling (SEM) in AMOS 26. Common method bias was assessed using Harman's single-factor test (which showed that a single factor accounted for 45.86% of the variance), and convergent and discriminant validity were established (CR > 0.87; AVE > 0.57).FindingsThe structural model demonstrated a satisfactory fit (CFI = 0.970; RMSEA = 0.055). EI exerted a significant positive association with IP (β = 0.465, p < 0.001) and a strong negative association with OB (β = −0.871, p < 0.001), while OB negatively influenced IP (β = −0.194, p < 0.01). Both OB and SR significantly mediated the the relationship between EI and IP, and FL significantly moderated this relationship (β = 0.128, p < 0.001), strengthening it under conditions of high financial literacy.Practical implicationsThe findings suggest that integrating EI training into financial literacy programmes can enhance investor decision-making, improve advisory effectiveness, and improve long-term portfolio outcomes.OriginalityThe study contributes a unified, theory-driven model that simultaneously tests dual mediation and moderation pathways within the behavioural finance literature.
Round, just-below (e.g., 9.99), and precise (e.g., 9.87) prices are widespread in consumer markets, yet evidence on their psychological effects remains inconclusive, at times even contradictory, and heavily concentrated on the contrast between just-below and round prices. Recent work further shows that these price endings differ systematically in their prevalence across countries, underscoring the need to understand the consumer-level mechanisms that may make them effective in the first place. Across two preregistered, high-powered experiments (total N = 729), we therefore examined how round, just-below, and precise prices shape purchase intentions, price image, quality image, and price recall. Across studies, precise prices produced the most favorable price image and were most likely to be underestimated in recall, followed by just-below prices and then round prices. By contrast, price endings did not reliably affect quality image or purchase intentions. Exploratory mediation analyses suggest that the relative advantage of precise prices operates through price image rather than quality image or recall-based underestimation. These findings identify behavioral foundations of price-ending effects at the level of individual consumer judgment and complement recent macro-level evidence on cross-cultural differences in the prevalence of round, just-below, and precise prices.
Out-of-pocket health care spending is an inefficient and inequitable financing mechanism, as it reduces household well-being and can push families into poverty. This study estimates the impoverishment associated with out-of-pocket health care expenditures in Peru between 2010 and 2021 and identifies the factors associated with such impoverishment. Using microdata from the National Household Survey and a multivariate logit model, the study assesses the probability of falling into poverty related to such direct spending. The results show that 2,7% of non-poor households became impoverished during the period analyzed, a percentage that increased to 4,5% during the COVID-19 pandemic. This pattern was more pronounced in rural areas, especially in the highlands and the rainforest. Regarding associated factors, it was found that years of education, per capita income, health insurance coverage, and visits to health facilities are significantly associated with a lower probability of falling into poverty due to out-of-pocket expenditures. In contrast, the presence of chronic diseases, disability, a higher economic dependency ratio, pregnancy, the presence of young children, unmet basic needs, lack of sanitation services, and the use of solid fuels for cooking are associated with a higher probability of this risk. Health insurance coverage, while essential, remains insufficient if it is not accompanied by substantive improvements in the social determinants of health.
Using a randomized field experiment, we provide evidence on how university students respond to interventions designed to encourage downloading and engaging with a mental health smartphone application (hereafter referred to as “app”). Our intervention targeted all students, both mentally healthy and unwell, and our sample was broadly representative (n = 1,812; women = 60%, men = 30%, non-binary/undisclosed = 10%). Paying students a small amount to download and engage with the app increased downloads by 7 percentage points, from a baseline take-up rate of 14%. Payments also increased the number of activities completed, but engagement across all groups remained extremely low. Inviting students to an exclusive social media group moderated by student ambassadors had no effect on take-up or engagement, although this may be due to the relatively low number of students who joined the group. Overall, our results suggest that university students are resistant to using this mental health app and respond weakly to these incentives, despite the high prevalence of mental health issues in this population. We supplement our quantitative analysis with information from open-text survey questions and interviews to provide some insights into this reluctance. Perceived lack of need, time constraints, and skepticism about the app's benefits emerge as potential barriers to app engagement.
This article presents a pragmatic framework for time-sensitive analysis of behavioral RCTs using sequence methods and Markov modeling. The focus is not methodological novelty but translation: we map common policy questions to appropriate temporal tools, provide a reporting checklist for transparency, and show how estimates become implementable rules for booster timing, triage, and exit. We position sequence analysis alongside multi-state hazards, HMMs, SMART/MRT, and g-methods, and we introduce an openly documented R package, sequenceRCT, that operationalises the end-to-end workflow with uncertainty quantification and reproducible outputs. A simulated illustration demonstrates interpretation and decision use, with ablations and a counterfactual booster vignette. We extend the framework to personalized interventions–where state-specific individual treatment effects are difficult to detect–and to reinforcement learning, where sequence-derived state spaces, empirical kernels, and off-policy evaluation support safe policy learning. We conclude with a staged validation agenda on existing datasets.
Hospitality and consumer environments are undoubtedly multisensory, yet auditory stimuli remain underutilized as intentional components of choice architecture. This mini-review synthesizes evidence from psychology, neuroscience, and behavioral economics examining how soundscapes—particularly micro-auditory cues such as door clicks and elevator tones—are undervalued in their functions as behavioral nudges that influence guest perception and decision-making within bounded rationality frameworks. Current evidence demonstrates that auditory stimuli activate affective priming, processing fluency, and associative memory mechanisms that systematically bias consumer judgments of value and satisfaction, yet research predominantly examines macro-level interventions while micro-auditory cues and biometric methods remain underexplored. Smart technologies now enable adaptive, personalized sonic ecosystems that could respond dynamically to guest and consumer states, presenting opportunities for experience-enhancing nudges and ethical risks regarding manipulation and consumer autonomy. This review identifies critical research gaps and proposes future directions emphasizing micro-level interventions, biometric methods, and ethical frameworks for auditory choice architecture in hospitality environments.
Human cooperation persists among strangers in large, well-mixed populations despite theoretical predictions of difficulties, leaving a fundamental evolutionary puzzle. While upstream (pay-it-forward: helping others because you were helped) and downstream (rewarding-reputation: helping those with good reputations) indirect reciprocity have been independently considered as solutions, their joint dynamics in multiplayer contexts remain unexplored. We study public goods games without self-return (often called "others-only" PGGs) with benefit b and cost c and analyze evolutionary dynamics for three strategies: unconditional cooperation (ALLC), unconditional defection (ALLD), and an integrated reciprocity strategy combining unconditional forwarding with reputation-based discrimination. We show that integrating upstream and downstream reciprocity can yield a globally asymptotically stable mixed equilibrium of ALLD and integrated reciprocators when b/c > 2 in the absence of complexity costs. We analytically derive a critical threshold for complexity costs. If cognitive demands exceed this threshold, the stable equilibrium disappears via a saddle-node bifurcation. Otherwise, within the stable regime, complexity costs counterintuitively stabilize the equilibrium by preventing not only ALLC but also alternative conditional strategies from invading. Rather than requiring uniformity, our model reveals one pathway to stable cooperation through strategic diversity. ALLD serves as "evolutionary shields" preventing system collapse while integrated reciprocators flexibly combine open and discriminative responses. This framework demonstrates how pay-it-forward broadcasting and reputation systems can jointly maintain social polymorphism including cooperation despite cognitive limitations and group size challenges, offering a potential evolutionary foundation for behavioral diversity in human societies.
In the wake of the Affordable Care Act's coverage expansions and the COVID-19 pandemic's urgent demand for remote services, telehealth has become a critical gateway to healthcare for underserved and access-challenged populations across the United States. While telehealth offers the potential to reduce barriers related to distance, transportation, and provider shortages, persistent disparities in broadband access, digital literacy, and socioeconomic status continue to shape utilization patterns. Utilizing data from the 2024 Financial Inclusion Survey, this study applies a dual modeling strategy. Single-stage Probit, OLS, and Ologit models are used to analyze telehealth utilization and satisfaction. To address nonrandom selection into telehealth, a Heckman two-stage model–incorporating a cubic polynomial for perceived network adequacy and comprehensive controls including an urban/suburban geographic indicator–is implemented. Telehealth utilization in this nationally representative cross-sectional sample is unevenly distributed, with higher rates observed in urban and suburban communities. The analysis shows that perceived network adequacy has a nonlinear association with telehealth use: moderate adequacy increases utilization, while very high adequacy may reduce it. Administrative convenience and affordability are associated with higher satisfaction in single-stage models; however, these effects are attenuated after correcting for selection bias (Inverse Mills Ratio, β = −0.778, p < 0.05). Unobserved factors influencing telehealth adoption also bias satisfaction estimates, highlighting the necessity of correcting for selection effects. The cubic modeling approach effectively captures nonlinear associations between access and satisfaction. Accurate assessment of telehealth's impact requires robust adjustment for selection bias. These findings have significant policy implications for improving network adequacy, digital access, and operational efficiency to ensure equitable telehealth adoption and satisfaction, particularly for underserved and non-urban communities.
The concept of “Ecohesion” offers a novel perspective on sustainable transitions by emphasizing social cohesion as a central element. Drawing inspiration from Herbert Gintis's combination of macro social dynamics and micro behavioral evidence, this framework integrates his theories on the interplay between social norms, endogenous preferences, and institutional dynamics. By identifying four fundamental social conditions—access to basic goods and services, decent jobs, time affluence, and social capital—Ecohesion provides an analytical lens to assess the sustainability and political feasibility of transition policies.
Communication is crucial to resolving conflicts such as social dilemmas. Previous literature concurs that communication among all group members increases cooperation. However, gathering all the members is often difficult. Hence, the effect of communication among some group members needs to be examined. The current study addressed this notion in a public goods experiment framework measuring the social value orientation of individuals. We conducted a six-person public goods game 20 times with members fixed. Between the 10th and 11th periods, we implemented different communication tactics: communication among all members, communication among three members selected randomly, or no communication (control). We observed that communication among some members increased the cooperation rate compared to no communication; however, the effect was weaker when compared with communication among all the members. Furthermore, partial communication increased the cooperation rate of prosocial individuals regardless of whether to join the communication process themselves. Proself individuals, on the contrary, cooperated as long as they communicated. Non-communicating members did not decrease their perception of goal-sharing and reciprocity compared to communicating members. These observations affirm that communication among some members is beneficial, even if assembling all the members is not always feasible.
This paper aims to assess the impact of cultural heritage on Greek economic development. An input-output model approach is used to estimate a set of multipliers that measure the direct, indirect and induced (broader) macroeconomic impact of income, output, value added and employment of cultural heritage on economic growth. The multipliers of product, gross value added, income and employment are calculated, based on which the importance of the cultural heritage sector for the Greek economy is identified. Three different impact scenarios were applied to this analysis. The main finding of the study is the importance of the cultural heritage sector in conjunction with its interconnection with the tourism sector. The study provides a policy analysis framework for targeted structural economic interventions that can be implemented to improve the operational efficiency of the cultural sector in Greece.
We test for gender effects in the “vote with your wallet” game, a multi- person version of the prisoner's dilemma that models responsible consump- tion decisions. We find that women cooperate significantly more (have more responsible consumption decisions) than men in the baseline version of the game. This baseline excludes three additional elements tested in companion treatments: i) a legality frame, where the ethical product is labeled as being certified for compliance with anticorruption standards; ii) an ex-post redistribution scheme, where those who buy the less ethical product compensate those who choose the more responsible option; and iii) a conformity treatment, where participants are informed of prior players' choices to simulate social influence. Without these added interventions, women still show significantly greater cooperation, revealing a baseline preference for prosocial behavior in this strategic consumption setting.
