Search Results (687)

Background/Objectives: Risk taking, a crucial component of decision-making, is domain-specific. However, most literature has focused on financial risk-taking in relation to cognitive functioning. The current study investigated the association between risk-taking behaviors in five different domains and various cognitive abilities in cognitively normal older adults. Methods: Participants (mean age = 69.55 ± 7.35 years; mean education = 16.69 ± 2.19 years; 58.9% female) completed the Domain-Specific Risk-Taking Scale (DOSPERT), consisting of financial, health, ethical, recreational, and social risk-taking questions. Cognitive performance on associative memory, verbal memory, working memory, verbal fluency, processing speed, and executive function was examined. Linear regression models adjusted for age, gender, and education level were conducted. Results: Two out of five risk-taking domains were associated with various aspects of cognition. Conclusions: Financial risk-aversion was linked to better memory, while health and safety risk-taking was linked to faster processing speed. These findings have practical implications in the context of everyday decision making. Full article

This paper explores the application of the Value of Information, (VoI), based on the Claude Shannon/Ruslan Stratonovich framework within economic contexts. Unlike previous studies that examine circular settings and strategic interactions, we focus on a non-strategic linear setting. We employ standard economically motivated utility functions, including linear, quadratic, constant absolute risk aversion (CARA), and constant relative risk aversion (CRRA), across various priors of the stochastic environment, and analyse the resulting specific VoI forms. The curvature of these VoI functions play a decisive role in determining whether acquiring additional costly information enhances the efficiency of the decision making process. We also outline potential implications for broader decision-making frameworks. Full article

Automated Vehicles (AVs) are being developed with the aim to reduce the occurrence and severity of Road Traffic Crashes (RTCs). Studies suggest AVs may improve the safety of Vulnerable Road Users (VRUs), particularly on road crossings. However, exposure to novel technology over time may lead to behavioural adaptation. Thus, understanding VRUs’ behavioural intentions towards AVs is crucial for their safe integration into traffic. We investigate four external factors pedestrians consider when crossing a road in front of an AV. An online questionnaire with 281 participants assessed crossing intentions, focusing on road gradient, weather, pedestrian–AV distance, and AV type. Personality traits and self-reported behaviour were measured. Anderson’s experimental protocol revealed all factors significantly influenced crossing decisions. Using hierarchical clustering followed by K-means clustering, the participants were classified into three different profiles: risk-averse, resolute, and indecisive pedestrians. We provide evidence of a strong link between crossing decisions, reported behaviours and psychological facets while interacting with an AV at crossings. Pedestrian profiling allows targeting preventative measures for groups based on unique characteristics, maximising efficiency thereof. Furthermore, pedestrian profiling can inform AV’s driving style to support safer road interactions. This is salient for resolute pedestrians, who take more risks, which may lead to severe RTCs. Full article

This study investigates the influence of FOMO, loss aversion, and herd behavior on gold investment decisions in the Vietnamese market. Employing data collected from 727 investors and the Partial Least Squares Structural Equation Modeling (PLS-SEM) method, the analysis results confirm the pivotal role of FOMO, with both direct and indirect impacts on gold investment decisions. Notably, both loss aversion and herd behavior positively influence FOMO, thereby indirectly encouraging relatively hasty and inadequately considered investment decisions. The study also finds that FOMO has a negative relationship with anticipated regret but is positively correlated with subjective expected pleasure. Furthermore, as determined through Multi-Group Analysis (MGA), psychological messages featuring “self-decision” or “risk warning” demonstrate a significant moderating role, potentially reducing or enhancing the influence of FOMO on investment decisions. These findings contribute to enriching behavioral finance theory and provide an empirical basis for developing effective risk management policies and gold market regulation aimed at mitigating the negative impacts of FOMO. Full article

To address the impact of the dynamic evolution of flood disaster chains and decision-makers’ (DMs’) risk preference heterogeneity on group decision-making, this study proposes a social network group decision-making method that integrates the evolutionary trend of the flood disaster chain with DMs’ risk preferences. First, a Bayesian network is constructed to quantify the disaster chain’s evolution, dynamically adjusting DMs’ evaluation values. Second, DMs’ risk preference types are identified based on the evaluation values, and a bounded confidence (BC) model, incorporating risk preferences, self-confidence and trust networks, is developed to promote consensus formation. Then, the optimal alternative is selected through weighted aggregation and used to update the Bayesian network dynamically during implementation. Finally, the effectiveness and superiority of the proposed method are verified using the flood disaster chain from the “7∙20” extreme rainfall disaster in Zhengzhou, Henan Province, China. The results show that risk-seeking DMs reduce BC values and resist consensus, whereas risk-averse DMs enlarge BC values and accelerate convergence. Moreover, worsening flood disaster chain trends drive DMs to update the optimal alternative. These findings show that the method captures both dynamic disaster evolution and behavioral heterogeneity, providing realistic and adaptive decision support in flood emergency scenarios. Full article

Today’s linear nutrient flows are rooted in a long history of agronomic and wastewater engineering strategies that have created cascading environmental, social, and economic side effects, signaling the need for more holistic and circular approaches. Our examination of the regulatory pathways that enable and constrain urine recycling—an underutilized approach to repurposing human waste as fertilizer—addresses a persistent research gap related to the mainstreaming of transformative technologies. Framed around policy process theories—Street Level Bureaucracy and Multiple Streams Theory—our methods include a review and mapping of 54 regulatory documents; action research where we reflect on our own efforts to expand urine recycling; and interviews with 16 practitioners and regulators in four states which, to our knowledge, are the only places in the US with efforts to scale up urine recycling in community settings. Given its circular nature, a key challenge we find is a lack of clarity around which sectors, or what scales of government, “own” the decision to allow the collection and use of urine as a fertilizer. Working around these challenges, we show how practitioners use many practical strategies to simplify the approval process and reduce the risk aversion regulators face when confronted with ambiguous rulemaking. Full article

The integration of renewable energy and power-to-gas (P2G) technology into park-level integrated energy systems (PIES) offers a sustainable pathway for low-carbon development. This paper presents a low-carbon economic dispatch model for PIES that incorporates uncertainties in renewable energy generation and load demand. A novel two-stage P2G, replacing traditional devices with electrolysers (EL), methane reactors (MR), and hydrogen fuel cells (HFC), enhances energy efficiency and facilitates the utilisation of captured carbon. Furthermore, adjustable thermoelectric ratios in combined heat and power (CHP) and HFC improve both economic and environmental performance. A ladder-type carbon trading and green certificate trading mechanism is introduced to effectively manage carbon emissions. To address the uncertainties in supply and demand, the study applies information gap decision theory (IGDT) and develops a robust risk-averse model. The results from various operating scenarios reveal the following key findings: (1) the integration of CCT with the two-stage P2G system increases renewable energy consumption and reduces carbon emissions by 5.8%; (2) adjustable thermoelectric ratios in CHP and HFC allow for flexible adjustment of output power in response to load requirements, thereby reducing costs while simultaneously lowering carbon emissions; (3) the incorporation of ladder-type carbon trading and green certificate trading reduces the total cost by 7.8%; (4) in the IGDT-based robust model, there is a positive correlation between total cost, uncertainty degree, and the cost deviation coefficient. The appropriate selection of the cost deviation coefficient is crucial for balancing system economics with the associated risk of uncertainty. Full article

Our paper investigates how emotions and cognitive biases shape small investors’ decisions in a bearish market or are perceived as such. Using semi-structured interviews and a focus group, we analyze the behavior of eight management science students engaged in a three-day trading simulation with virtual portfolios. Our findings show that emotions are active forces influencing judgment. Fear, often escalating into anxiety, was pervasive in response to losses and uncertainty, while frustration and powerlessness frequently led to decision paralysis. Early successes sometimes generated happiness and pride but also resulted in overconfidence and excessive risk-taking. These emotional dynamics contributed to the emergence of cognitive biases such as loss aversion, anchoring, confirmation bias, overconfidence, familiarity bias and herd behavior. Emotions often acted as precursors to biases, which then translated into specific decisions—such as holding losing positions, impulsive “revenge” trades or persisting with unsuitable financial strategies. In some cases, strong emotions bypassed cognitive biases and directly drove behavior. Social comparison through portfolio rankings also moderated responses, offering both comfort and additional pressure. By applying a qualitative perspective—not commonly used in behavioral finance—our study highlights the dynamic chain of emotions → biases → decisions and the role of social context. While limited by sample size and the short simulation period, this research provides empirical insights into how psychological mechanisms shape investment behavior under stress, offering avenues for future quantitative studies. Full article

Hirshleifer’s difference-form contest technology is a useful tool in the study of a class of conflict, especially military combats. We aim to highlight an important feature that the Hirshleifer contest model distinctively has, namely passivity (bidding zero effort) may stand as an effective choice in conflict even when the contest is highly deterministic (i.e., with small noise). For that purpose, we establish two propositions on the contest with $n\ge 2$ risk-neutral contestants under small noise. The first proposition states that every contestant bids arbitrarily close to zero (if not bidding zero with positive probability at all) under sufficiently small noise. The second proposition, more strikingly, states that every contestant either bids arbitrarily close to the second-highest valuation (among all the contestants’ valuations), or simply remains passive with certainty under any sufficiently small noise. We further show that the first proposition holds for the contest between risk-averse individuals endowed with constant absolute risk aversion as well, and illustrate by an example how quickly polarization in bidding among contestants, as is predicted by the propositions, may emerge as the noise of the contest abates. These results help pave the way toward a complete characterization of the difference-form contest. Full article

To mitigate the risks posed by uncertainties in renewable energy output and Electric Vehicle (EV) travel patterns on the scheduling of Virtual Power Plants (VPPs), this paper proposes an optimal scheduling model for a VPP incorporating EVs based on Information Gap Decision Theory (IGDT). First, a Monte Carlo load forecasting model is established based on the behavioral characteristics of EV users, and a Sigmoid function is introduced to quantify the dynamic relationship between user response willingness and VPP incentive prices. Second, within the VPP framework, an economic optimal scheduling model considering multi-source collaboration is developed by integrating wind power, photovoltaics, gas turbines, energy storage systems, and EV clusters with Vehicle-to-Grid (V2G) capabilities. Subsequently, to address the uncertain parameters within the model, IGDT is employed to construct a bi-level decision-making mechanism that encompasses both risk-averse and opportunity-seeking strategies. Finally, a case study on a VPP is conducted to verify the correctness and effectiveness of the proposed model and algorithm. The results demonstrate that the proposed method can effectively achieve a 7.94% reduction in the VPP’s comprehensive dispatch cost under typical scenarios, exhibiting superiority in terms of both economy and stability. Full article

Alcohol-associated liver disease (ALD) is a major cause of liver-related mortality worldwide; however, only a subset of heavy drinkers develop progressive disease, suggesting a role for host genetics. In East Asian populations, functional polymorphisms in alcohol-metabolizing enzymes, such as alcohol dehydrogenase 1B (ADH1B) and aldehyde dehydrogenase 2 (ALDH2), are common and significantly affect acetaldehyde metabolism. ADH1B accelerates ethanol oxidation, whereas ALDH2 impairs acetaldehyde detoxification and increases oxidative stress, inflammation, and liver injury. Based on genotype combinations, individuals were stratified into five alcohol sensitivity groups with differing risks of cirrhosis and cancer. Although ALDH2 deficiency often suppresses alcohol intake via aversive reactions, paradoxically, continued drinking increases the risk of liver and gastrointestinal cancers. Genetic risk stratification may inform personalized prevention and precision of public health approaches. However, expansion of direct-to-consumer genetic testing has raised ethical and educational challenges. Understanding the interaction between alcohol metabolism and genetic variations is crucial for identifying high-risk individuals and guiding tailored interventions in East Asian populations. Full article

Business models often transform due to adaptation in response to external changes. However, relatively little is known about what causes these types of adaptations. We suggest that threat-rigidity as well as prospect theory have the potential to explain what causes business model adaptation in response to gains and losses. Firm leaders’ inclination to adapt their business model is sensitive to risk that is perceived as a gain or a loss in the macro-economic environment. We apply threat-rigidity and prospect theories to examine the relationship between risk perception and business model adaptation. We also investigate if emotion has explanatory value for how managers adapt to business models. We test our hypotheses in a field experiment involving 95 Scandinavian managers. Here, we relate managers’ inclinations to adapt to different business models under different risk scenarios. The results reveal that, in general, managers are more risk seeking in gain scenarios than in loss scenarios. This finding is in line with the threat-rigidity theory. In addition, emotional style is found to relate more to risk aversion than to risk seeking in the domain of potential gain. We argue that emotional style has explanatory value for how managers adapt to business models, because emotions are key influencers on risk perception. Full article

Synergizing soil quality improvement and greening for increased yields are essential to ensuring grain security and developing sustainable agriculture, which has become a key issue in agricultural cultivation. This study considers a contract farming supply chain composed of a risk-averse farmer and a risk-neutral firm making green and efficient technology (GET) investments, which refers to the use of technology monitoring to achieve fertilizer reduction and yield increases with yield uncertainty. Based on the CvaR (Conditional value at Risk) criterion, the Stackelberg game method is applied to construct a two-level supply chain model and analyze different cooperation mechanisms. The results show that when the wholesale price is moderate, both sides will choose the cooperative mechanism of cost sharing to invest in technology; the uncertainty of yield and the degree of risk aversion have a negative impact on the agricultural inputs and GET investment, and when yield fluctuates greatly, the farmer invests in GET to make higher utility but lowers profits for the firm and supply chain. This study provides a theoretical basis for GET investment decisions in agricultural supply chains under yield uncertainty and has important practical value for promoting sustainable agricultural development and optimizing supply chain cooperation mechanisms. Full article

This study models a three-level supply chain (farmer–retailer–government) incorporating farmer risk aversion. Under land capacity and fiscal budget constraints, it analyzes two subsidy strategies: area-based subsidies to farmers (SF) and volume-based subsidies to retailers (SR). Key findings include that when farmer land capacity exceeds a critical threshold and the fiscal budget is constrained, SF yields superior performance to SR. Conversely, with sufficient budgets, SR outperforms SF under high land capacity. Under moderate land capacity and unlimited budgets, both strategies exhibit equivalent effects. When land capacity falls below a critical threshold, government subsidies become unnecessary. The SF strategy demonstrates greater resilience against output uncertainty compared to SR. Under constrained budgets, SF is preferable; SR becomes more advantageous with abundant budgets. Critically, increasing risk aversion significantly reduces social welfare under both SF and SR strategies. This indicates neither subsidy mechanism effectively mitigates the adverse effects of farmer risk aversion. Full article

The present article analyzes the value that investors assign to financial products that contribute to Sustainable Development Goal 11 (SDG 11): “Sustainable Cities and Communities” by comparing investor preferences in Spain and Mexico through a choice experiment. Spain and Mexico were selected due to their contrasting levels of economic development, sustainability awareness, and regulatory maturity, offering a meaningful basis for a cross-country comparison. Preferences for investment funds that promote SDG 11 are examined by evaluating key attributes such as financial institution type, expected return, risk level, and explicit contribution to SDG 11. The results, estimated using a mixed logit model applied to a choice experiment with 568 respondents, evaluating attributes such as institution type, return, risk, and contribution to SDG 11, reveal strong risk aversion and a differentiated willingness to pay for sustainable attributes, particularly among Spanish investors. Relevant differences between the two countries emerge, suggesting the need for tailored strategies to foster sustainable investment, especially in Mexico, where sustainability is less valued in investment decisions. The policy implications include the need for investment approaches and communication strategies that are adapted to national contexts. This article concludes with recommendations for designing financial products that better align with the values and expectations of responsible investors, particularly regarding sustainable cities and communities. Full article