Risk Attitudes Research Articles

The Importance of Being Consistent: Attribution of Mental States in Strategic Human-Robot Interactions.

This article investigates the attribution of mental state (AMS) to an anthropomorphic robot by humans in a strategic interaction. We conducted an experiment in which human subjects are paired with either a human or an anthropomorphic robot to play an iterated Prisoner's Dilemma game, and we tested whether AMS is dependent on the robot "consistency," that is, the correspondence between the robot's verbal reaction and its behavior after a nonoptimal social outcome of the game is obtained. We find that human partners are attributed a higher mental state level than robotic partners, regardless of the partner's consistency between words and actions. Conversely, the level of AMS assigned to the robot is significantly higher when the robot is consistent in its words and actions. This finding is robust to the inclusion of psychological factors such as risk attitude and trust, and it holds regardless of subjects' initial beliefs about the adaptability of the robot. Finally, we find that when the robot apologizes for its behavior and defects in the following stage, the epistemic component of the AMS significantly increases.

Does education promote risk-taking? Evidence from Vietnam

PurposeThis study examines the impact of schooling on risk perceptions and the moderation role of a non-cognitive skill, locus of control.Design/methodology/approachUsing information from the Thailand Vietnam Socio Economic Panel data set, the study employs Generalised Method of Moments (GMM) to address the potential endogeneity problem of the schooling variable.FindingsThe findings indicate that a higher level of willingness to take risks is correlated with additional schooling years. In other words, those with higher levels of education are more prone to take more risks. The result demonstrates that the association between education and risk attitudes is moderated by locus of control.Originality/valueThis study contributes to the growing literature on education in emerging countries by addressing the endogeneity problem of schooling variables using the GMM method. Moreover, this study examines the mediating role of personal non-cognitive skills, namely locus of control, in the relationship between education and risk attitudes.

Targeting farmers’ heterogeneity to enrich climate change adaptation policy design: findings from northern Italy

With its scientifically proven effects and widespread acceptance, climate change stands as one of the most pressing and intricate challenges for society and economies. Farmers are on the frontline of managing climate change. Therefore, how they perceive and respond to climate change shapes their risk assessment and structures future resilience and adaptive capacity. Employing a bottom-up approach, we conducted 460 surveys randomly among farmers throughout the Lombardy region in northern Italy. A triple-loop approach considering climate change awareness, perceived impacts, and adaptation measures and barriers was implemented to characterize the potential heterogeneity of farmer behaviour and explore whether risk attitudes and adaptation actions differ between farmer profiles. We then profiled farmers through a clustering analysis. Four groups emerged, highlighting farmers’ adaptation preferences and risk attitudes: (1) cropping-adapted and isolated farmers, (2) cooperation-adapted and insecure farmers, (3) risk insurance-adapted and confident farmers, and (4) climate services-adapted and aware farmers. Although the groups vary in terms of farmers’ characterization and farming activities (e.g. young and highly educated vs. old and highly experienced farmers, rainfed vs. irrigated farms), similar patterns were observed regarding climate change awareness and perceived impacts—however, the contrast increased in terms of adaptation measures and barriers. Gaining a more comprehensive understanding of the diverse ways in which farmers assess risks and adapt can promote the transferability of bottom-up findings and inform the co-design of tailored and flexible adaptation instruments, minimizing the risk of maladaptation or ineffective transformation in the face of climate change.

The Impact of Children’s Gender on Family Housing Assets

China's household asset investment shows the characteristics of real estate concentration, which reduces the short-term risk-resistant ability of households and restricts the consumption ability of residents. This paper puts forward the theoretical hypothesis that “families whose eldest son is a boy have stronger housing investment motives”. A probit model is constructed using data from CHFS2019 for empirical testing. The results find that households whose eldest son is a boy have a stronger propensity to invest in housing than households whose eldest son is a girl. The degree of local sex ratio imbalance and the risk attitude of the head of household also influence investment behavior.

Financial Access and Financial Risk Attitudes towards Improving Microenterprise Performance

Microenterprise sector plays a pivotal role in driving economic growth in developing nations. This research aims to devise a financial literacy strategy that augments the performance of microenterprise customers of Indonesia's Shariah Microbank in DKI Jakarta. Improving the performance of micro businesses is not only the responsibility of Bank Syariah Indonesia but also the responsibility of many parties, namely the role of the government through the establishment of KNEKS and KDEKS which aim to increase sharia financial literacy and need to be supported by associations both the Sharia Economic Society (MES) and universities who are concerned with increasing sharia financial literacy which leads to improving the performance of micro businesses. This is achieved by investigating the determinants of microenterprise performance, focusing on the financial literacy of the customers availing microfinance services from the said bank. This study adopts a quantitative approach and employs Structural Equation Modeling (SEM) to analyze data, with financial access as mediating variables. The results are further evaluated through Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis—a robust research technique for identifying obstacles and refining effective strategies. The study comprises a sample of 500 microenterprise operators who are clients of the Shariah Microbank in DKI Jakarta. The analysis reveals the following insights: (1) Financial literacy exhibits a positive and moderate influence on the microenterprise performance of Shariah Microbank customers in DKI Jakarta. (2) Financial access demonstrates a positive and moderate impact on microenterprise performance. (3) Financial literacy exhibits a positive and moderate effect on financial access. (4) financial literacy has a positive and moderate effect on financial risk attitudes, (5) financial risk attitudes have positive an insignificant effect on micro business performance, (6) financial literacy through financial access as a mediating variable has a positive and moderate effect on micro business performance, (7) financial literacy through financial risk attitudes variables have positive an insignificant affect the performance of micro business enterprises. This encompasses strategic programs including: (1) Financial proficiency through collaborative Shariah microfinance training within the Islamic Ecosystem and expansion and optimization of the BSI Microentrepreneur Center; (2) Financial attitude and behavior enhancement via workshops on Shariah microfinancial planning and mentorship by BSI personnel for microenterprise operators; (3) Financial access enhancement through intensified digitalization of Shariah microfinancial services and integration of bundled products and services (e.g., incorporating licensing and halal standardization).

Accounting for BEV Users’ Risk Attitudes and Charging Inertia in En Route Charging Choice Behavior

This paper innovatively explores BEV (battery electric vehicle) users’ risk attitudes and charging inertia, examining their effects on en route charging and charging route choice behavior. An attitudinal survey was conducted to explore the two latent variables of risk attitudes and charging inertia in relation to socioeconomic and travel-related characteristics. ICLV (Integrated choice and latent variable) models are adopted to estimate the latent variables and the charging choice behavior simultaneously. Specifically, uncertainty in energy consumption is first considered in the ICLV model, which is represented by the available range (AR) uncertainty. Multinomial logit (MNL) models directly incorporating socioeconomic attributes are employed as a reference for comparison with ICLV models. Results illustrate that risk attitudes and charging inertia both play significant roles in modeling en route charging choice behavior. Risk-averse users and users having charging inertia value AR uncertainty more. Battery range, charging frequency, and income emerge as the most crucial factors influencing users’ intention to charge en route. The results show significant heterogeneity of BEV users in attitudes and charging choice behavior, underscoring the importance of accounting for the heterogeneity in en route charging demand estimation and deployment optimization of public charging stations, particularly for medium-to long-distance trips.

Risk attitudes of tax practitioners and firm influence

PurposeThe purpose of this paper is to garner a deeper understanding of the site of influence of aspects of risk management for tax practitioners.Design/methodology/approachThe research design is twofold. Phase one consisted of a wide-scale international survey with 1,061 tax experts across 59 jurisdictions. In phase two, the authors followed up with 68 semi-structured interviews with tax practitioners working in 11 different countries.FindingsThe findings recognise the importance of the firm as a significant “site of influence” for tax practitioners in shaping their risk appetite in their tax work. The firm eclipses other influences of risk such as professional body oversight, public interest and demographic markers such as gender and career stage. The authors show that firm is significant, irrespective of size of firm.Practical implicationsThis work has practical implications as the findings highlight the importance of oversight of professional service firms by both the professional accountancy bodies and revenue authorities. The findings may have impact on the ethical training and guidance for trainee accountants in terms of an increased awareness on the employing firm as a site of influence for tax practitioners.Originality/valueThis research is important as it adds to the significant body of work on firm socialisation and highlights the important role that the firm holds in moderating (or exacerbating) the risk appetite of tax practitioners, which has significant implications in terms of pushing the boundaries of tax aggressive behaviours. The work aims to recognise the important role that tax practitioners can have in moderating aggressive tax practice, and, thus, reducing tax inequalities and shaping a better world of “Reduced Inequalities” (SDG10).

Modelling the role of multiple risk attitudes in implementing adaptation measures to reduce drought and flood losses

Human activities have increasingly affected hydrological processes in many river basins worldwide leading to changes in the severity of droughts and floods. A number of modelling studies have used system dynamic models to represent the complex dynamics generated by the interplays between the social and physical systems. Yet, attitudes towards drought and flood risk leading to the implementation of individual and collective adaptation measures are not included in current system dynamics modelling approaches. To address this gap, we developed a system dynamic model to represent the dynamics between human societies, decision-making processes, adaptation measures, and hydrological extremes. The model accounts for a society characterized by the co-existence of four types of risk attitudes and management responses: risk-neglecting, risk-controlling, risk-downplaying, and risk-monitoring. Our findings show that the presence of a prevalent social group with a certain risk attitude has a strong influence on the awareness, preparedness, and consequent losses of the other social groups. On the other hand, the homogenous presence of social groups with diverse risk attitudes leads to higher drought and flood losses due to the unsustainable water use of risk-neglecting and risk-downplaying groups. Finally, our results highlight that societies characterized by high homogeneity in risk-attitudes tend to implement less collective measures, opting instead for individual measures by specific social groups. This emphasizes the importance of accounting for different social groups when modelling human-water dynamics to promote an integrated risk management and design more sustainable and resilient future adaptation pathways.

Motivating factors of farmers’ adaptation behaviors to climate change in China: A meta-analysis

Adapting to climate change is critical to building sustainable and resilient agricultural systems. Understanding farmers' perceptions of climate change has become the key to the effective implementation of climate change adaptation policies. This research draws multidisciplinary attention to how farmers participate in decision-making on adaptation behaviors and provides useful insights for realizing synergies between environmental change and agricultural production. In this work, we conducted a meta-analysis of 63 quantitative studies on Chinese farmers' adaptation to climate change to assess the relationship between motivational factors and adaptation behavior. Our analysis highlights that farmers' perceptions of precipitation changes are often inaccurate; however, other psychological factors, such as perception, experience, and risk attitude, significantly positively impact their adaptation behavior. In addition, different climate regions are the main source of high heterogeneity in inter-study comparisons of climate change perception, and the effect of climate regions may therefore constitute a moderating factor that weakens the positive relationship between climate change perception and adaptive behavior. Furthermore, this study highlights the need to intervene at the household level to enhance farmers' adaptability to climate change, which includes providing support through income diversification, early warning information services, training, assistance, credit, subsidies, and other resources. In the future, research on how perception, experience, and risk interact to affect adaptive behavior should be strengthened.

Simulation-based hybrid genetic algorithms for the stochastic multi-mode resource-constrained project scheduling problem with minimized financial risk

Projects face uncertainties during implementation, and these uncertainties often lead to risk factors that disrupt successful project execution and cause a loss of profit. The stochastic project scheduling technique has been an effective avenue for reducing the risks in project management. Nevertheless, previous studies often neglected resource limits for minimizing the financial risks of projects in stochastic project scheduling problems. This study aims to optimize the conditional net present value at risk (CNPVaR), which measures a project’s expected loss of net present value (NPV) in a stochastic multi-mode resource-constrained project scheduling problem (SMRCPSP). Accordingly, considering the stochastic activity duration and cash flow, we construct a scenario-based optimization model for the SMRCPSP, where the solution (strategy) of the SMRCPSP is represented by a policy that includes an activity list and execution mode list; a scheduling policy is then employed to map the start times of activities at each decision time based on the solution. Three simulation-based hybrid genetic algorithms embedded with different iteration alternatives according to activity-based (AB) or resource-based (RB) scheduling policies are used. Furthermore, computational experiments are conducted to evaluate the proposed procedures through 480 instances. With respect to the CNPVaR, expected NPV, and algorithm stability metrics, the results of the experiments demonstrate that the genetic algorithm (GA) with local search based on the RB scheduling policy performed best compared with two other hybrids of the GA, the existing vibration damping optimization (VDO) method and a pure GA for large-sized projects. However, the VDO outperforms the other approaches according to the AB scheduling policy for small-scale projects. Additionally, a case study is conducted; the findings demonstrate that the risk attitude (confidence level) of project managers and the discount factor have impacts on the CNPVaR and expected NPV, but the CNPVaR is insensitive to the number of simulations.

Portfolio optimization with mental accounts under uncertain random environment and butterfly optimization algorithm with adaptive strategies

In complex security markets, uncertainty and randomness may coexist. The investors hold different risk attitudes towards different investment objectives in reality. In order to reflect this phenomenon, this paper applies mental accounts to portfolio optimization in an uncertain random environment. Firstly, considering the influence of transaction costs and diversification degree, this paper establishes an uncertain random mean-absolute semi-deviation-entropy bi-objective optimization model. Then the bi-objective model is converted to two single-objective models through three steps. Secondly, the equivalent forms of the models are deduced when the return rates of random risky securities are assumed to be normal random variables and the return rates of uncertain risky securities are assumed to be linear and zigzag uncertain variables. Furthermore, we propose an improved butterfly optimization algorithm (IBOA) to solve the two single-objective models. Finally, numerical simulations are presented to analyze the practicability and effectiveness of the models with different mental accounts and the IBOA algorithm. The results indicate that the IBOA algorithm is effective and putting money into more mental accounts may gain higher returns.

It takes two to tango: Spousal risk preferences and CEO risk-taking behavior

Using hand-collected data on the cultural origins of S&P 500 CEOs and their spouses, we examine whether differences in risk attitudes within marriages influence corporate risk-taking behavior. We find that CEOs with more risk averse spouses adopt relatively safer corporate policies. The effect is stronger if the CEO comes from a more collectivist culture, has been married more recently, or shares more responsibilities with their spouse. Together, these findings suggest that the cultural composition of CEO household and spousal risk preference affect corporate risk-taking behavior.

320. A Preliminary Investigation of Risk and Ambiguity Attitudes in Adult Patients With Bulimia Nervosa

320. A Preliminary Investigation of Risk and Ambiguity Attitudes in Adult Patients With Bulimia Nervosa

Selection of an economics-energy-environment scheduling strategy for a community virtual power plant considering decision-makers’ risk attitudes based on improved information gap decision theory

To address the impact of decision-makers' risk attitudes (DMRA) and uncertainties on dispatch strategy in community integrated energy systems, a multi-objective dispatch model of a community virtual power plant (CVPP) is proposed. Firstly, a novel CVPP model that considers DMRA and a multi-objective satisfaction model of economics-energy-environment are built. Secondly, the information gap decision theory (IGDT) model is improved by considering uncertainties of renewable energy, loads, and DMRA. Thirdly, the VIKOR method is improved by using the weights from multiple objective functions derived by combining the entropy weight and full consistency method. And the conservative and risky strategy selection methods in the VIKOR method are used to select the optimal strategy from the obtained multi-objective Pareto solution set that satisfies decision-makers with risk preferences. Thus, the impact of DMRA on optimal strategy selection is fully described. Finally, the proposed model's effectiveness is validated using a multi-scenario example of a residential area. The results indicate that: 1) The novel CVPP provides realistic scheduling strategies based on the DMRA. 2) After implementing demand response, the resident cost and net carbon emissions are reduced by 9 % and 91 %, respectively. Energy supplier profit and renewable energy utilization rate are increased. The constructed IGDT model also improves multiple objectives. 3) The improved IGDT model's uncertainty and deviation factors allow for diverse scheduling strategies. Simultaneously, the improved VIKOR method provides a new method for decision-makers to select strategies. The model is a guide for selecting scheduling strategies and a way of encouraging the usage of renewable energy.

Determinants of Smallholder Farmers' Awareness of Crop Insurance in Kedah, Malaysia

Agriculture is a major source of income for humans and has become an agro-food commodity. However, this industry is vulnerable to a wide range of dangers, including climate change, natural disasters, illnesses, and pests. Crop insurance is not a new concept in advanced economies since it has been recognized as an efficient instrument for mitigating agricultural risks and encouraging farmers to employ modern technology and innovation. This research investigates the determinants of smallholder farmers' awareness of crop insurance in the agricultural landscape of Kedah, Malaysia. Therefore, this study examines the relationship between knowledge, risk attitude and farm size on the farmers' awareness of crop insurance. The study, based on a sample of 100 farmers, utilizes a non-probability sampling technique to collect data through structured questionnaires. The research employs reliability analysis, correlation analysis, and regression analysis to evaluate the raw data and uncover the factors influencing farmers' awareness of crop insurance. The study conclusion shows a strong correlation between farmers' knowledge levels and farm size as important indicators of crop insurance awareness. The analysis emphasizes how crucial it is to increase farmers' understanding through focused educational programs and customized awareness campaigns that take farm size dynamics into account. Policymakers and agricultural extension services can enable smallholder farmers to make well-informed decisions about using crop insurance as a strategy to manage agricultural risks and guarantee financial stability by making information and resources easily accessible.

Consumer behavior toward virtual wine experiences as a technology-based sustainable transformation

IntroductionThis study examines the behavior of wine consumers toward virtual wine experiences (VWEs), which are innovative and resilient solutions adopted by actors in the wine and wine tourism sectors during the recent pandemic, with an inherent potential for sustainability. While the phenomenon is still evolving due to the digitalization megatrend and the marketing potential of VWEs for wineries, the literature on this topic is still limited.MethodsWe apply an extended Theory of Planned Behavior (TPB), relying on a large and representative sample of Italian wine consumers to analyze the effect of personal wine involvement, risk attitude, and future wine tourism intention in addition to attitude, subjective norms, and perceived behavioral control.ResultsThe results confirm that attitude, subjective norms, perceived behavioral control, wine involvement, and future wine tourism intention positively influence intentions, while risk aversion negatively affects behavior.DiscussionThis first application of the TPB to technology-based wine experiences. It provides key insights for researchers, practitioners (such as wineries and wine tourism stakeholders), and policymakers for the development of VWEs.

Combining Savage and Laplace: a new approach to ambiguity

AbstractThis paper presents a new representation of preference orderings for the study of ambiguity-related decision-making. The central feature is a preference-based decomposition of subjective probabilities that provides information about inherent ambiguity. The probability decomposition is combined with a utility function reflecting the decision-maker’s attitude toward ambiguity. The proposed theory generalizes Savage’s SEU and allows for a straightforward measurement of ambiguity and ambiguity aversion while keeping concepts for measuring risk and risk attitudes unaffected. For the measurement of ambiguity, concepts of probability theory can be used since decision acts can be interpreted as two-dimensional probability distributions. The proposed measure of ambiguity aversion exploits the properties of the utility function in the same way as the Arrow/Pratt measure of risk aversion.

Examining the impact of green technological specialization and the integration of AI technologies on green innovation performance: evidence from China.

China's commitment to achieving carbon neutrality by 2060 has sparked scholars' interest in examining the environmental ramifications of green technologies in the digital era. While plenty of them provide eco-efficiency policy such as increasing R&D investment or stimulating green exports, little attention has been paid to the firm-level technological management and recombination strategies such as differentiation/specialization of green portfolios along with AI integration, which can significantly impact the pace of net-zero transitions. To address these gaps, this study investigates the moderating effect of technological specialization on levels of AI integration into green technologies estimated by green-AI technological distance and enterprises' innovation performance in Chinese contemporary contexts. Regression results of fixed-effect model in Chinese patent data (2011-2020) indicate that enterprises' green innovation performance is significantly improved as AI integrates more into the green technologies due to the legitimacy and the inability to appropriate more green values. Interestingly, specialized green-technological enterprises demonstrate superior performance in integrating distant AI technologies. This occurrence could potentially be driven by the governments' incentives and the organization's risk attitudes, shaping green innovation outcomes. Hence, the study underscores the importance of considering both the AI integration and green specialization in shaping innovation outcomes amidst green transitions.

Multi-item order quantity optimization through stochastic goal programing

AbstractManaging multi-item economic order quantity (MIEOQ) problems within an uncertain business environment is a critical challenge. Decision-makers, with a comprehensive understanding of organizational goals and risk tolerances, play a pivotal role in this context. However, existing solutions often inadequately consider decision-maker preferences in MIEOQ problem-solving. The literature suggests that integrating the concept of satisfaction function with stochastic goal programming (SGP) can address this issue. However, the existing SGP approaches struggle with the challenge of effective goal setting. Additionally, employing distinct satisfaction functions for each uncertain goal can complicate threshold setting, diminishing their effectiveness. To tackle these challenges, we introduce a straightforward, yet effective approach called aspiration-free goal programming (AFGP) and integrate it with a unified satisfaction function. AFGP operates by minimizing expected values of deviation variables, eliminating the challenging task of goal setting under uncertainty. A unified satisfaction function is a singular metric applied uniformly across multiple goals, offering a consistent framework for evaluating performance across diverse objectives. This integration forms a preference-sensitive framework that not only captures nuanced trade-offs between conflicting objectives but also enhances decision quality and stakeholder satisfaction. By emphasizing the importance of decision-maker’s preferences and addressing identified issues, our research introduces a practical and effective approach for achieving balanced solutions in uncertain MIEOQ environments.

Get active now or later? The association between physical activity and risk and time preferences

Despite the well-established link between physical activity and positive health outcomes, much of the world’s population remains inactive. Many people don’t invest in health behaviours, such as physical activity, in the present, despite the long-term benefits of this. The aim of this study was to assess the relationship between physical activity levels and risk and time preferences in university students. A maximum likelihood model was used to jointly estimate risk and time preferences (elicited in an incentivised choice experiment), and to examine the relationship between these preferences and self-reported physical activity. Physically inactive people discounted the future significantly more than physically active people did. Physically active people made slightly more risky choices in our risk attitude task, although this directional relationship was not statistically significant. The link between time preferences and physical activity suggests that further research on behavioural strategies such as commitment devices, nudging or temptation bundling may be helpful in increasing physical activity for individuals who discount the future in favour of more immediate benefits.