Prospect Theory Research Articles

Risk assessment of poverty-returning based on hybrid q-rung orthopair fuzzy EDAS and prospect theory

PurposeAccurately identifying the risk of poverty-returning is a complex and critical challenge in current poverty alleviation efforts. However, there is currently no study on evaluation methods for the risk of poverty-returning. This study aims to establish a robust and systematic approach for an evaluation framework for the risk of poverty-returning.Design/methodology/approachBased on relevant assessment criteria, a maximum deviation method was established to identify the weights of the indicators. A complex evaluation methodology using prospect theory (PT), a q-rung orthopair fuzzy set (QrOFS) and evaluation relying on distance from average solution [EDAS] (QrOFS-PT-EDAS) was developed to evaluate the poverty-returning risks. Some policy recommendations to reduce the risk of poverty-returning have also been put forward.FindingsHis study identifies the risk factors of poverty relapse from nine aspects, including natural disasters, accidents and policy-driven poverty relapse. In addressing the evaluation challenge arising from uncertain decision-making, the QrOFS aligns more with people’s thinking habits and expression methods in complex environments. The proposed hybrid evaluation framework accurately measures the poverty-returning risk, which is beneficial for the formulation of policy recommendations.Originality/valueA scientific and comprehensive assessment system index for poverty-returning is constructed. A hybrid QrOFS-PT-EDAS framework is presented to make the evaluation results more scientific and objective. Several strategic recommendations for reducing the poverty-returning risk are presented. This study offers a novel framework for assessing poverty-returning issues that can be extended to many other areas.

How Does Loss Aversion Mediate the Relationship Between Personality Traits and Efficiency of Skills in Investment Decision- Making?

This study examines how loss aversion mediates the connection between personality factors and the effectiveness of investment decision-making skills among individual investors at the Colombo Stock Exchange. This research challenges the neoclassical paradigm that presumes investor rationality. Instead, it accords with behavioural finance, which emphasizes deviations from rationality in both beliefs and preferences. Using Prospect Theory as a framework, this study examines how the five major personality traits -conscientiousness, extraversion, agreeableness, neuroticism, and openness to experience influence investment decision-making. Analyzing data from 351 investors, a structured questionnaire and purposive sampling were used. The analysis was conducted using Structural Equation Modelling with SmartPLS4. The results demonstrate notable correlations: individuals with a higher level of openness to experience and agreeableness tend to have a positive impact on their investment decision-making, whereas extraversion, openness to experience, and conscientiousness are highly associated with loss aversion. Loss aversion plays a crucial role in connecting extraversion, conscientiousness, and openness to experience with investment decision-making. This study enhances the field of behavioural finance by providing a detailed understanding of how personality traits and loss aversion influence investing choices.

RELATIONSHIP BETWEEN ECONOMIC RISK AND FINANCIAL, PERFORMANCE OF COMMERCIAL BANKS IN KENYA

Financial institutions play a key role in spurring the growth of the economy. Commercial banks operate in a highly volatile environment which threatens their ability to achieve their desired goals. The purpose of this study was to establish the relationship between economic risk and the financial performance of commercial banks in Kenya. The study was anchored on agency and prospect theories. Longitudinal and cross-sectional research design was used. The study population was 42 commercial banks in Kenya. 32 purposively sampled commercial banks which had audited financial accounts for the years 2016 to 2021 were included in the study. Secondary panel data collected using an extraction tool validated by experts from banks and academia was analyzed using R statistical software version 4.3.2. Reliability of the data was ensured by using audited financial reports. Descriptive and inferential data analysis techniques were used. Inferential statistics used were linear mixed effects multiple regression allowing random effects to vary by banks. The study findings showed that economic risk significantly influence financial performance with high liquidity and credit risks associated with lower ROE (beta; -10.36; 95% Confidence Interval (CI): ( -18.45 to -2.27), p-value: 0.012) and (beta: -0.29; 95% CI (-0.46 to -0.13), p-value: 0.001.)The study concluded that there is a statistically significant relationship between economic risk and financial performance of commercial banks in Kenya. Based on the findings from this study, it is recommended that commercial banks may adopt a holistic approach to risk management by emphasizing economic risks. This study may significantly benefit the government, CBK and the commercial bank management in Kenya to inform policy framework as well as the academia and researchers as far as economic risk and financial performance of commercial banks is concerned.

Leveraging Loss Aversion and Self-Efficacy: The Role of Water Pricing and Risk in Driving Individual Innovation for Sustainable Water Consumption

Water scarcity is a growing global challenge, requiring effective management strategies to ensure sustainable water use, particularly in regions like West Dorset, U.K., where rising prices and environmental pressures make sustainable consumption practices essential. This study develops and empirically tests an integrated theoretical framework combining Prospect Theory (PT) and Social Cognitive Theory (SCT) to examine the mechanisms driving household water conservation. Using structural equation modelling on data from 429 residents in West Dorset (response rate 78.3%), we investigated how water pricing (WP) and perceived water risk (PWR) influence sustainable water consumption through individual innovativeness (II) and community engagement (CE), with environmental regulations (ERs) as a moderator. The results revealed significant positive effects of WP and PWR on individual innovativeness, which, in turn, strongly predicted community engagement. The relationship between these factors and sustainable water consumption was significantly moderated by ERs. This study makes three key contributions: Firstly, it empirically validates an integrated PT-SCT framework in water conservation behavior. Secondly, it identifies the crucial mediating role of II in translating price and risk perceptions into community action; and lastly, it demonstrates how regulatory frameworks can enhance or inhibit conservation outcomes. These findings inform policy recommendations for tiered pricing structures, community-based conservation initiatives, and adaptive regulatory frameworks. This study provides a comprehensive model for understanding and promoting sustainable water consumption in water-stressed regions worldwide.

Gains–loss asymmetry of jobs, income, and risk‐taking behaviors

AbstractDespite extensive theorizing on the employment–crime link, little discussion has taken place on the mechanisms through which job gains and losses affect behavior. We draw on prospect theory and the loss aversion principle, which suggests people are more sensitive to losses than gains, to assess how individuals contend with transitions in employment and income. Using fixed‐effects and asymmetrical fixed‐effects models, we analyze 36 months of retrospective information for a sample of incarcerated males collected as part of the Second Nebraska Inmate Study. First, we assess whether job losses are more likely than job gains to generate financial stress and find support for the loss aversion principle. Second, we explore how people might compensate for changes in job and income status by engaging in risk‐taking behaviors (illegal earnings, gun carrying, and offending versatility). We find the positive relationship between job and income loss on the probability of reporting illegal earnings and crime versatility is stronger than the negative relationship between job and income gain and these behaviors. Financial stress, however, does not attenuate the relationship between losses and risk‐taking behaviors. We discuss the implications for theory and policy.

Probabilistic linguistic carpooling matching decision-making considering time satisfaction based on prospect theory

To improve the travel efficiency of carpooling demanders and reduce travel costs, a carpooling matching decision-making method is proposed that considers preference satisfaction and time satisfaction in a probabilistic linguistic environment. First, the multiattribute many-to-one carpooling matching problem in the probabilistic linguistic environment is described. To solve this problem, based on probabilistic linguistic term set (PLTS) evaluation matrices, attribute prospect values are calculated via prospect theory, and based on probabilistic linguistic preference relations (PLPRs) for attributes, group consistency attribute weights are calculated. Second, cumulative prospect values are calculated by aggregating attribute prospect values and attribute weights and then standardized to obtain the preference satisfactions of passengers and drivers. Third, based on the interval expected waiting time provided by passengers and the estimated arrival time provided by drivers, the time satisfaction of passengers is calculated considering time tendency coefficients. Then, the comprehensive satisfaction of passengers is calculated by aggregating preference satisfaction and time satisfaction via the geometric average method. Furthermore, based on the comprehensive satisfaction of passengers and the preference satisfaction of drivers, a many-to-one carpooling matching model is constructed and then solved to obtain an optimal many-to-one carpooling matching scheme. An example analysis shows the effectiveness, reliability and accuracy of the proposed method. The main innovations of this study are as follows: (1) A calculation method for the improved score of PLTSs considering hesitation is proposed. (2) Two algorithms for calculating unknown attribute weights are designed based on PLPRs. (3) A calculation method for time satisfaction considering time tendency coefficients is presented. (4) A model for probabilistic linguistic multiattribute many-to-one carpooling matching considering time satisfaction is built.

A three-way decision with prospect-regret theory under Pythagorean fuzzy environments

As science and technology continue to advance at a rapid pace, people are facing increasingly complex data, and research on uncertain information technology has become a hot field. Compared to intuitionistic fuzzy sets, Pythagorean fuzzy sets are more tolerant and flexible in representing uncertain information. Therefore, this article mainly focuses on the study of three-way decisions based on Pythagorean fuzzy β covering. First, considering the disadvantages of other methods in comparing the magnitudes of Pythagorean fuzzy numbers, we propose the concept of the ideal positive degree in a Pythagorean fuzzy environment and determine a method for calculating conditional probabilities based on this newly defined ideal positive degree. Second, regret theory and prospect theory are combined to obtain a relative utility function. Then, based on the aforementioned conditional probabilities and relative utility function, a three-way multi-attribute decision-making method based on the Pythagorean fuzzy environment is established. Finally, the three-way multi-attribute decision-making method is utilized to solve the problem of selecting the optimal choice for rural revitalization industrial projects. Through experimental comparison and analysis, the effectiveness and reliability of this method are verified.

An investigation of firm size distributions involving the growth functions

Following the ideas of prospect theory, a class of growth functions is used to characterize deterministic variations of firm size, which portrays the asymmetric efforts of the firm to achieve the desired size. Considering the differences in the ability of different firm size to cope with uncertainties, the Boltzmann equation for the evolution of firm size is constructed. Utilizing a suitable scaling limit, the Fokker–Planck equation is acquired and its explicit steady-state solution is derived. Our results illustrate that different choices of parameters in the growth function lead to various statistical laws for firm size, such as the Amoroso distribution, the lognormal distribution and Zipf’s law. Under certain conditions, inequality for the distribution of firm size decreases as firm size increases. The numerical analyses are presented to illustrate our results.

Governance of responsible research and innovation: A social welfare, psychologically grounded multicriteria decision analysis approach

Our article deals with the governance of responsible research and innovation (RRI) and aims to set out a first psychologically grounded decision-theoretic method for the governance of RRI. We approach the governance of RRI as a multicriteria group decision analysis problem of delivering social welfare in an innovation ecosystem. Following such a methodological approach, we develop a psychologically grounded multicriteria group decision analysis method that integrates in its value function the main psychological effects captured in the value function of prospect theory as the main theory of individual decision-making under risk. The method first applies a psychologically motivated multicriteria decision analysis function that measures the welfare delivered to all stakeholders involved in a research and innovation consortium. The method then applies a social welfare function on the welfare measurements of stakeholders to propose a social welfare solution that emerges as an RRI-compliant solution for the consortium. The results are a first psychologically grounded multicriteria group decision analysis method and its first application to the governance of RRI. The implications of our results are theoretical but also practical, as our method contributes not only to the established field of multicriteria decision analysis by setting out new method but also to the field of RRI by delivering a psychologically grounded decision-theoretic general method for the governance of RRI.

ESG Performance and Innovation in Listed Manufacturing Companies — A Prospect Theory Perspective

ESG Performance and Innovation in Listed Manufacturing Companies — A Prospect Theory Perspective

A comprehensive multi-stage decision-making model for supplier selection and order allocation approach in the digital economy

The increasingly serious environmental issues and fierce competition caused by globalization have brought pressure on supply chain managers who seek to allocate multiple purchase demands comprehensively, highlighting the significance of supplier assessment considering sustainability and technique. Moreover, many multi-criteria decision-making (MCDM) methods fail to quantify the risk preference of decision-makers (DMs) when conducting the supplier assessment process. Indeed, a hybrid supplier selection and order allocation model that integrates such requirements is yet to be proposed. Thus, this work develops a comprehensive decision-making model that constructs a deep learning model to forecast the potential demand and addresses the sustainable supplier selection based on cumulative prospect theory (CPT) and multi-material order allocation problem simultaneously. The proposed order allocation model is solved by the second generation of adaptive geometry estimation based many-objective evolutionary algorithm, with the technique of order preference similarity to the ideal solution used to filter out the best Pareto solution for DMs as the reference. Through implementing an illustrative case study of a leading Chinese engineering machinery manufacturer followed by a sensitivity analysis, the relatively strong applicability and scalability of the proposed model and methods are demonstrated. The results show that introducing Weibull distribution to estimate the theoretical obsolescence rate of historically sold accessories can result in higher demand prediction accuracy for consumable mechanical accessories. Integrating CPT into the MCDM framework allows us to evaluate suppliers more comprehensively by capturing the effect of DMs’ risk preferences and gain or loss sensitivity.

Does household electrification alleviate energy poverty? Empirical evidence from China

In the context of carbon neutrality goals, mitigating energy poverty presents a certain level of complexity. This study employs Prospect Theory to analyze the impact of household electrification on energy poverty. It tests the non-linear relationship between household electrification and energy poverty using Oprobit models, Robin Hood algorithm and Regression Discontinuity Design. Besides, the mediating effect of energy efficiency and employment rate, and the moderating effect of family cohabitation are verified. The results show that there is an inverted U-shaped relationship between household electrification and energy poverty. Furthermore, urban households and those using old furniture experience a stronger increase in energy poverty in the early stages of electrification, while households in areas with long heating degree days experience an increase in energy poverty in the later stages of electrification. Household electrification impacts on energy poverty through energy efficiency and alleviates energy poverty by promote employment rate. Additionally, the higher the degree of family cohabitation, the more it can alleviate the exacerbating effect of household electrification on energy poverty.

A prospect theory-driven three-way decision framework: Integrating prior probability tolerance and dominance relations in fuzzy incomplete information systems

This study proposes a novel method that integrates Prospect Theory (PT) with a Three-Way Decision (TWD) framework to enhance decision quality in Fuzzy Incomplete Information Systems (FIIS). The method first applies prior probability tolerance dominance relations to manage and evaluate binary relationships among decision options, laying the groundwork for subsequent calculations. Based on this foundation, PT is used to construct objective weight and value functions, effectively reducing uncertainties due to subjective factors in the decision-making process. Unlike traditional methods, this PT-based TWD approach can address incomplete data while fully considering decision-makers’ psychological preferences under risk, enabling more precise and scientific decision support. Extensive experimental studies and comparative analyses demonstrate that this method outperforms existing approaches in terms of stability, effectiveness, and superiority, highlighting its potential for applications in fields with high data diversity and uncertainty, such as healthcare.

A Comprehensive Risk Based IT Governance Framework for SaaS Adoption in Capital Market

ABSTRACT Software as-a-service (SaaS) adoption is essential in regulated industry such as capital market to bring in scalability, required to deal with the fluctuations in trading volumes, and agility, required to stay responsive to changing market conditions. In this context, the study examines the factors that the capital market organization look for in adopting SaaS. Based on the perceived risk theory and prospect theory, we propose a perceived risk based IT governance framework in SaaS adoption decision in capital market. Following a case study-based research methodology, we examined the factors that influence the risk perception of the decision makers about SaaS-based solution in a capital market industry. We found that the decision to opt for SaaS adoption in organization depends on (i) the top management’s consideration for risk preference, problem framing, decision domain, and data security, and (ii) organizational processes in practice such as IT governance archetype and risk management processes. Based on this, we generate a risk score for a capital market firm to weigh potential benefits and risks in adopting SaaS. In this study, we assume that the top management provides guidance toward firm’s risk appetite which is then compared to the generated risk score to decide for SaaS adoption. This study contributes to the technology adoption literature by emphasizing the role of individual risk preferences and problem framing in influencing technology adoption decisions particularly for technologies that pose certain risks. Finally, the study contributes by bringing forth the role of an IT governance framework in assessing SaaS-related risks.

Multi-Borrowing Practices and Loan Repayment of Micro and Small Enterprises in Trade Sector in Meru County, Kenya

In Kenya, the increase in multi-borrowing and its effects on loan repayment is a growing concern for microfinance institutions. The general purpose of this research was to establish the effect of multi-borrowing on loan repayment among MSEs in Meru County. Specifically, the study aimed to determine how the number of loans borrowed, interest payable, and the financial literacy of borrowers influenced loan repayment within Meru County Microfinance. The research was anchored on information asymmetry, prospect theory, moral hazard, and adverse selection theories. The study targeted 6,000 MSE owners who were members of Meru County Microfinance, from which a sample of 200 borrowers was selected. A descriptive research design was employed to assess how multiple borrowings affected loan repayment. Cluster and random sampling methods were used to identify respondents across the seven branches of Meru County Microfinance. Primary data was collected using questionnaires, and analyzed by use of descriptive, correlational, and regression analysis techniques. Inferential analysis was conducted at a 0.05 significance threshold, utilizing the Statistical Package for Social Sciences (SPSS) version 28 for data analysis. Ethical standards were strictly observed throughout the study. The study revealed that the number of loans borrowed had a significant impact on loan repayment among MSEs in Meru County. Effective management of borrowing was crucial for better repayment outcomes. Interest payable was identified as a critical factor affecting loan repayment; enterprises with well-managed credit risk practices, including the adjustment of interest rates and repayment schedules, exhibited better repayment performance. Furthermore, the level of financial literacy positively influenced loan repayment, with higher financial literacy levels leading to improved loan management and repayment behaviors. The study concluded that the number of loans borrowed significantly affected loan repayment, although its impact was less direct compared to other factors. Interest payable had the most substantial effect on loan repayment, with effective credit risk management correlating strongly with better repayment outcomes. Additionally, a higher level of financial literacy was found to significantly enhance loan repayment. Based on the findings, it is recommended that micro and small enterprises regularly review and manage their borrowing policies to improve loan repayment. Financial institutions should implement clear policies on irrecoverable loan provisions and adopt robust credit management practices to ensure better loan repayment. Moreover, enhancing financial literacy among borrowers is crucial for improving loan repayment, and thus, targeted financial education programs should be developed. Policymakers should also evaluate and update regulatory frameworks to support effective loan management and repayment practices within microfinance institutions.

Suitability matching evaluation of the low-carbon regional integrated energy system based on the “resource-demand” balance

The integrated energy system (IES) stands out due to its advantages of multi-energy complementarity, green and efficiency. This paper aims to provide a practical model for suitable region site selection of low-carbon regional IES based on the “resource-demand” balance. A “resource-demand” suitability matching analysis indicator system is established. By using prospect theory and variable precision rough set theory, the decision-making preferences and the cognitive fuzziness influence of expert scoring were corrected respectively, and reasonable subjective weights were obtained. Then, the objective weights are obtained using the entropy method, and the optimal combined weights are obtained through the game theory weighting method. Finally, this paper establishes a “resource-demand” suitability matching model consisting of three sub models: similarity matching degree, numerical matching degree, and suitability matching degree. An empirical study is conducted on 16 regions in Beijing, and the results show that the numerical matching degree of “resource-demand” gradually decrease from the central urban regions to the surrounding regions. The similarity matching degree in most regions reaches the highest range (0.776,1.00). There are 4 regions with a suitability matching rating of perfect, 7 regions with a rating of great, 1 region with a rating of good, and 4 regions with a rating of poor. The suitability matching model established in this paper can guide energy project decision-makers to select regions with greater potential for the development of IES. In addition, adjusting the similarity matching coefficient and numerical matching coefficient can meet the diversified needs of decision-makers for the similarity matching degree and numerical matching degree of the “resource-demand” balance, providing support for energy project planning decisions.

Application and Development of Behavioural Economics in Consumer Decision Making

Behavioural economics, as an interdisciplinary field integrating psychology and economics, offers new perspectives for understanding consumer decision-making. This paper provides an overview of the core theories of behavioural economics, its applications in consumer decision making, and its developments and challenges in market practice and policy making. First, behavioural economics challenges traditional economic assumptions about rational decision-making by revealing core concepts such as limited rationality, prospect theory and behavioural biases, providing a deeper understanding of consumer behaviour. Second, the paper explores the effectiveness of behavioural economics in practical applications, such as improving firms' market performance and policy implementation by optimising marketing strategies, utilising personalised recommendations and developing behavioural intervention policies. However, behavioural economics still faces challenges in terms of theoretical universality, cross-cultural applicability and dynamic adaptation. Future research directions include theoretical integration, cross-cultural validation, adaptation to technological developments, optimisation of policy practices and intersection studies with psychology. The review in this paper aims to provide reference for academic research and practical application, to promote the further development of behavioural economics, and to provide theoretical support for policy making and market strategies.

Behavioral Intentions in Sports Tourism: Meta-Analysis and Structural Equation Modeling

This paper addresses fragmentation in sports tourism research, specifically concerning factors influencing behavioral intentions, focusing on key psychological and situational variables. Through a meta-analysis of 18 studies comprising 14,495 observations, drawn from an initial screening of 967 articles listed in the Scopus database, this study investigates the effects of perceived behavioral control, subjective norms, nostalgia, satisfaction, percieved benefit, and percieved risk, on behavioral intentions among general sport tourists. Two distinct theoretical frameworks were examined to uncover the core drivers of intentions. In the first framework, the analysis revealed that perceived behavioral control (effect size = .58), subjective norms (effect size = .50), and nostalgia (effect size = .43) have a stronger influence on behavioral intentions than attitude or image. This finding suggests that the participatory and socially embedded nature of sport tourism amplifies the impact of practical and social factors. Nostalgia emerged as a particularly strong emotional motivator, as it fosters attachment to past sport experiences and enhances future engagement. Among the components of the Theory of Planned Behavior, perceived behavioral control highlights the significance of practical considerations, such as ease of access and affordability, in shaping tourists’ intentions. The second framework underscored satisfaction as the most influential predictor of behavioral intentions (effect size = .77), consistent with Expectancy-Disconfirmation Theory, where experiences that meet or exceed expectations lead to future engagement. Perceived benefit (effect size = 0.50) also played a significant role, indicating that anticipated rewards, such as enjoyment and social connections, positively affect decision-making. In contrast, perceived risk (effect size = -0.25) showed a negative effect on behavioral intentions, in line with Prospect Theory, which emphasizes how potential losses deter engagement, particularly in unfamiliar or high-risk settings. These findings have practical implications for sport tourism management. Enhancing nostalgia, facilitating easy access, and fostering social connections can significantly boost behavioral intentions. Additionally, strategies that prioritize high-quality experiences to maximize satisfaction, while emphasizing perceived benefits and minimizing perceived risks through transparent safety measures, can further encourage positive engagement. Future research should explore specific conditions, such as familiar destinations, group dynamics, and satisfaction-driven contexts, that might enhance the influence of these key factors.

Dynamics inventory decisions in perishable supply chain considering sudden change in demand and risk attitude

To elucidate the impact of decision-makers’ risk preferences on the perishable-goods supply chain system during demand fluctuations, this study utilizes prospect theory and system dynamics to develop a simulation model that incorporates decision-makers’ risk attitudes. By solving this model with different parameter settings, the Lyapunov exponent is obtained to determine the system’s stability domain under different scenarios. Retailer losses are evaluated using spoilage conversion rates and fresh product stockouts, shedding light on the relationship between system stability and retailer losses. The research aims to explore the optimal ordering strategy under demand fluctuations. The findings indicate that inappropriate inventory strategies, coupled with decision-makers’ risk attitudes, can lead to system oscillations and substantial losses. Conversely, an appropriate inventory strategy coupled with moderate risk aversion can help mitigate retailer losses.

Risk Perception: Measurement and Aggregation

Abstract In a model inspired by neuroscience, we study choice between lotteries as a process of encoding and decoding noisy perceptual signals. The implications of this process for behavior depend on the decision-maker’s understanding of risk. When the aggregation of perceptual signals is coarse, encoding and decoding generate behavioral risk attitudes even for vanishing perceptual noise. We show that the optimal encoding of lottery rewards is S-shaped and that low-probability events are optimally oversampled. Taken together, the model can explain adaptive risk attitudes and probability weighting, as in prospect theory. Furthermore, it predicts that risk attitudes are influenced by the anticipation of risk, time pressure, experience, salience, and availability heuristics.