Prospect Theory Based Individual Irrationality Modelling and Behavior Inducement in Pandemic Control

Understanding and modeling individuals’behaviors during epidemics is crucial for effective epidemic control.However,existing research ignores the impact of users’irrationality on decision-making in the epidemic.Meanwhile,existing disease control methods often assume users’full compliance with measures like mandatory isolation,which does not align with the actual situation.To address these issues,this paper proposes a prospect theorybased framework to model users’decision-making process in epidemics and analyzes how irrationality affects individuals’behaviors and epidemic dynamics.According to the analysis results,irrationality tends to prompt conservative behaviors when the infection risk is low but encourages risk-seeking behaviors when the risk is high.Then,this paper proposes a behavior inducement algorithm to guide individuals’behaviors and control the spread of disease.Simulations and real user tests validate our analysis,and simulation results show that the proposed behavior inducement algorithm can effectively guide individuals’behavior.

The Evaluation of Alternative Risk Control Schemes Based on Cumulative Prospect Theory

Based on the analysis of the evaluation problems associated with the risk control scheme for major engineering projects,the evaluation method of the risk control scheme considering the irrational behavior of evaluation members in fuzzy random environment is proposed.Firstly,a maximum entropy model corresponding to any evaluation member is es-tablished by using triangular fuzzy random variables and grey correlation coefficient in order to obtain the weight of each risk factor of the member.Secondly,a nonlinear programming model is established according to the principle of minimiz-ing deviation to estimate the weight of different evaluation members on the evaluation of alternative risk control schemes.Lastly,the cumulative entropy model is used to calculate the weight of risk control schemes.Cumulative prospect theory obtains the comprehensive prospect utility value of each alternative to determine the optimal alternative.

Prospect Theory Based Hesitant Fuzzy Multi-Criteria Decision Making for Low Sulphur Fuel of Maritime Transportation

The environmental impact of maritime transport has now become a relevant issue in sustainable policy formulation and has attracted increasing interest from academia.For the sustainable development of maritime transport,International Maritime Organization stipulates that the sulfur content of ship emissions will reach 0.5 from 2020.With the approaching of the stipulated implementation date,shipowners need to adopt scientific methods to make decision on low sulfur fuel.In this study,we applied a prospect theory based hesitant fuzzy multi-criteria decision-making model to obtain the optimal decision of low Sulphur marine fuel.For this purpose,the hesitant fuzzy decision matrix is established to collect expert opinions,the maximizing deviation method is adopted to determine criteria weights.According to calculate the Euclidean distance from the reference points,we obtain the comprehensive prospect values of alternatives.Lastly,a case study is carried out to illustrate the significance and effectiveness of the proposed methodology.The innovation of this study is that it is the first-time adopting prospect theory and hesitate fuzzy sets to multi-criteria decision making for low Sulphur marine fuel,which provides an effective decision model for shipping companies under Low Sulphur regulations,and can also be extended to other industries.

Evaluation of the Effect of China’s Health Care Reform Based on Prospect Theory

Objective To evaluate the effect of health care reform policy in China comprehensively and provide suggestions for its further implementation.Methods Data on the effect of health care reform were obtained from“China Health Statistics Yearbook”and National Bureau of Statistics of China and the indicators were selected by corrected item total correlation(CITC)and Cronbach’sαreliability coefficient.Then,the selected indicators were calculated through the prospect theory model.Meanwhile,the gray relation analysis method was introduced to enlarge the differences between the advantages and disadvantages to make the comprehensive evaluation result more obvious.Results and Conclusion The implementation of China’s health care reform has a significant impact on China’s medical and health system.However,the effect of the policy will become less with the increase of the total amount.An effective management can ensure that the policy continues to play its role.

EXTENSION OF THE TOPSIS METHOD BASED ON PROSPECT THEORY AND TRAPEZOIDAL INTUITIONISTIC FUZZY NUMBERS FOR GROUP DECISION MAKING

Considering the decision maker＇s risk psychological factors and information ambiguity under uncertainty, a novel TOPSIS based on prospect theory （PT） and trapezoidal intuitionistic fuzzy numbers （YrIFNs） for group decision making is investigated, in which the criteria values and the criteria weights take the form of TrIFNs, and weights of decision makers are unknown. Firstly, distance measures for TrIFNs are used to induce value function under trapezoidal intuitionistic fuzzy environment. Secondly, the concepts of distance measures and trapezoidal intuitionistie fuzzy weighted averaging operator are employed to induce the weights of decision makers and thus the decision makers＇ options can be aggregated. Then the PT-based separation measures and relative closeness coefficient are defined and an algorithm for ranking alternatives under trapezoidal intuitionistic fuzzy environment is proposed. Finally, a numerical example further illustrates the practicality and effectiveness of the proposed TOPSIS method.

A Note on“Prospect Theory and the Newsvendor Problem”

Based on the newsvendor setting,many behavioral models are proposed to predict the biases of decision makers in inventory management.Recently,Nagarajan and Shechter(Manag Sci 60:1057–1062,2014)claimed that prospect theory cannot explain the consistent empirical findings.However,it is noticed that their model is a special case of the general prospect theorymodel.In this note,we showthat the general prospect theory model may be powerful in predicting the preferences of decision makers in inventory management.

The Park-and-Ride Behavior in a Cumulative Prospect Theory-Based Model

As an effective travel demand management means,park-and-ride(P&R)mode is an important part of urban traffic.In a traffic corridor with P&R service,suppose that the travel time on highway is uncertain,a cumulative prospect theory(CPT)-based travel decision-making model is established with two travel modes of driving all the way and(P&R).With this setting,the effect of various factors such as the transit fare rate,the parking fee and the total travel demand on the CPT-based and expected utility theory(EUT)-based equilibrium results are compared.In addition,the sensitivity analysis focus on CPT-related parameters are also performed.The numerical results in our case show that the equilibrium flow on P&R mode is always underestimated in an EUT-based model,especially for a low total travel demand.Also,it is found that reducing the transit fare rate or parking fee for P&R station and raising the parking fee for CBD has the same effect on promoting more commuters transfer to P&R mode,whatever CPT-based or EUT-based model is employed.Furthermore,commuter’s reference dependence characteristic is also observed in a CPT-based model,and it is especially noticeable when the road uncertainty is large.

Prospect Theory and the Newsvendor Problem with Mental Accounting

The manner in which economic outcomes are coded in a value function is critical because it has substantial influence on the evaluation of risky choices.In this paper,we formulate multiple mental accounts in a nonlinear value function and propose a newsvendor problem with mental accounting to predict and explain pull-to-center phenomenon.We show that the distinctive predictions of the proposed model come from the value function with mental accounting.We identify the individual and combined effects of loss aversion,risk aversion,and risk seeking on shaping newsvendor ordering behavior.Our work demonstrates that prospect theory can explain the decision bias and ordering behavior observed in newsvendor experiments.We also provide some additional insights to explain the studies in the literature.

Oderly accumulation theory of shale system petroleum resource and its prospecting significance-A case study of Chang 7 Member of Yanchang Formation in Ordos Basin

1 Introduction Shale formations bear abundant mineral resource and*unconventional petroleum resource,and the unconventional petroleum resource that contain in the shale formation should be integrated and researched.

Three-Way Behavioral Decision Making With Hesitant Fuzzy Information Systems:Survey and Challenges

Three-way decision(T-WD)theory is about thinking,problem solving,and computing in threes.Behavioral decision making(BDM)focuses on effective,cognitive,and social processes employed by humans for choosing the optimal object,of which prospect theory and regret theory are two widely used tools.The hesitant fuzzy set(HFS)captures a series of uncertainties when it is difficult to specify precise fuzzy membership grades.Guided by the principles of three-way decisions as thinking in threes and integrating these three topics together,this paper reviews and examines advances in three-way behavioral decision making(TW-BDM)with hesitant fuzzy information systems(HFIS)from the perspective of the past,present,and future.First,we provide a brief historical account of the three topics and present basic formulations.Second,we summarize the latest development trends and examine a number of basic issues,such as one-sidedness of reference points and subjective randomness for result values,and then report the results of a comparative analysis of existing methods.Finally,we point out key challenges and future research directions.

A New Method of Portfolio Optimization Under Cumulative Prospect Theory

In this paper, the portfolio selection problem under Cumulative Prospect Theory （CPT） is investigated and a model of portfolio optimization is presented. This model is solved by coupling scenario generation techniques with a genetic algorithm. Moreover, an Adaptive Real-Coded Genetic Algorithm （ARCGA） is developed to find the optimal solution for the proposed model. Computational results show that the proposed method solves the portfolio selection model and that ARCGA is an effective and stable algorithm. We compare the portfolio choices of CPT investors based on various bootstrap techniques for scenario generation and empirically examine the effect of reference points on investment behavior.

Optimization of Group Multiattribute Decision-Making Model in Commercial Space Investment

A group multiattribute decision-making model was proposed by implementing prospect theory,multi-attribute decision-making,group decision-making and entropy methods for the optimization in commercial space investment.First,the decision-making function was decided using prospect theory by the preference of each expert to reach the comprehensive prospect value based on different investment options;second,expert decision weights were reached according to entropy method;third,the expert group decision-making information was congregated according to the group decision-making congregation algorithm to reach the most optimized investment option;finally,an example was given to demonstrate the feasibility and effectiveness of the method.This model com-prehensively takes the advantages of many methods to congregate experts'experiences and avoid the subjective influences,thus providing a scientific decision-making approach for the commercial space investment.

Prediction and assessment of demand response potential with coupon incentives in highly renewable power systems

Demand Response(DR)provides both operational and financial benefits to a variety of stakeholders in the power system.For example,in the deregulated market operated by the Electric Reliability Council of Texas(ERCOT),load serving entities(LSEs)usually purchase electricity from the wholesale market(either in day-ahead or real-time market)and sign fixed retail price contracts with their end-consumers.Therefore,incentivizing end-consumers’load shift from peak to off-peak hours could benefit the LSE in terms of reducing its purchase of electricity under high prices from the real-time market.As the first-of-its-kind implementation of Coupon Incentive-based Demand Response(CIDR),the EnergyCoupon project provides end-consumers with dynamic time-of-use DR event announcements,individualized load reduction targets with EnergyCoupons as the incentive for meeting these targets,as well as periodic lotteries using these coupons as lottery tickets for winning dollar-value gifts.A number of methodologies are developed for this special type of DR program including price/baseline prediction,individualized target setting and a lottery mechanism.This paper summarizes the methodologies,design,critical findings,as well as the potential generalization of such an experiment.Comparison of the EnergyCoupon with a conventional Time-of-Use(TOU)price-based DR program is also conducted.Experimental results in the year 2017 show that by combining dynamic coupon offers with periodic lotteries,the effective cost for demand response providers in EnergyCoupon can be substantially reduced,while achieving a similar level of demand reduction as conventional DR programs.

Behavioral Portfolio Selection with Loss Control

In this paper we formulate a continuous-time behavioral （4 la cumulative prospect theory） portfolio selection model where the losses are constrained by a pre-specified upper bound. Economically the model is motivated by the previously proved fact that the losses Occurring in a bad state of the world can be catastrophic for an unconstrained model. Mathematically solving the model boils down to solving a concave Choquet minimization problem with an additional upper bound. We derive the optimal solution explicitly for such a loss control model. The optimal terminal wealth profile is in general characterized by three pieces： the agent has gains in the good states of the world, gets a moderate, endogenously constant loss in the intermediate states, and suffers the maximal loss （which is the given bound for losses） in the bad states. Examples are given to illustrate the general results.

Existence of Arrow-Debreu Equilibrium with S-shaped Utility Function

This paper characterizes the optimal solution of subjective expected utility with S-shaped utility function, by using the prospect theory （PT）. We also prove the existence of Arrow-Debreu equilibrium.

Thinking of peace when rich:The effect of industry growth on corporate risk-taking

We investigate the unique role and mechanisms of industry growth in firms’risk-taking policies.We find that industry growth is negatively associated with corporate risk-taking,consistent with the prospect theory that a high-growth industry gives firms a superior external environment,which may cause them to refrain from corporate risk-taking as in the saying“thinking of peace when rich.”This correlation is stronger for product market leaders,industries encouraged by industry policies and industries that receive more government support.Firms reduce risk-taking through various corporate policies,including long-term,high-value investments,operational efficiency and cash holdings in response to high industry growth.Overall,our results are consistent with industry growth negatively affecting corporate risk-taking.

FUZZY ORDER EQUIVALENT CLASS WITH UNCERTAINTY

It is a new research topic to create a rational judgment matrix using the cognition theory because of the construction of judgment matrix in AHP involving the decision-maker's cognitive activities. Owing to the presence of uncertain information in the decision procedure, the improper use of the uncertain information will doubtless cause weight changes. In this paper, we add a feedforward process prior to constructing the judgment matrix so that the decision maker can use both the certain and uncertain information to get the initial uncertain rough judgment matrix, and then convert it into a fuzzy matrix. Consequently, it will be better for decision maker to obtain the rough set of order equivalent classes through the decision graph. According to the qualitative analysis, the decision maker can easily construct the final judgment matrix instructed by the rough set created earlier.