Behavoral Decision Making Theory And Its Applications In Portfolio And Probabilistic Selling

With the rapid development of Internet technology and the arrival of big-data era,a large number of online shopping platforms emerge online.However,all kinds of user needs are becoming more diverse and refined.Exploring users’ behaviors and their psychological char-acteristics has become a hot topic in management science.According to the users’ behavior preferences and psychological characteristics as well as combining with some kinds of novel selling strategies by dual-channel selling platform,constructing the behavior decision-making optimization model which meets different kinds of needs of users is of great importance in theory and practice.Firstly,some behavioral decision-making optimization models are well s-tudied by employing prospect theory,time discounting theory and regret theory to describe the main psychological and behavioral characteristics of users as well as combining with tradition-al decision-making optimization methods and techniques.Then,using game theory method,a dual-channel consumer-oriented selling model based on users’behaviors is constructed.These optimization models provide a new way of thinking and solution for the optimization decision in complex,dynamic and incomplete information of big-data environment.The main contents of this paper are presented as follows:(1)Based on cumulative prospect theory,the multistage time discounting portfolio op-timization model,the psychological account portfolio optimization model and the commuter departure-time model are constructed respectively.Firstly,a multistage portfolio selection model considering time discounting is constructed according to the investors’ time discounting preferences and their psychological behaviors.The optimal solution of the model is given by using pure analysis,and the responding related properties of the optimal solution are given,and the reasonable interpretations are given by describing the investor’s time discount preference model with discounting functions.Secondly,considering investors’ psychological accounts and actual preferences,a portfolio optimization model is constructed based on mental accounts,the original model is transformed into multiple sub-linear programming problems,and some illus-trative examples are given.Finally,owing to the reference point dependence of commuters on the choice of departure time,a commuter departure time model is constructed and its optimal solutions and properties are obtained by pure analysis method.(2)Based on traditional optimization method,the dual-channel online discount selling model considering consumer loss preference and the differentiated-quality products probabilis-tic selling model based on consumers’ preference are constructed respectively.Firstly,we study the decision-making process of selling products via physical and online store selling under the supplier providing online discounts price.Secondly,we study dual-channel selling model and dual-channel probabilistic selling model.We analyze their sensitivity analysis of the optimal prices and revenue of the two selling models and the effects of the parameters to optimal prices.Finally,we compare the difference of the optimal revenue of the models and give the numerical results.(3)Based on loss regret theory and dynamic evolution game theory,probabilistic selling model with consideration of consumers’loss regret theory and the dynamic evolution model of probabilistic selling are constructed respectively.Firstly,we explore consumers’ anticipat-ed loss and its role in a competitive market consisted of a vertical random product and its transparent rival.We start with the benchmark case in which consumers have loss neutrality.We then explore the case in which consumers can anticipate the potential-post purchase loss.Furthermore,even when consumers are extremely averse to selection loss,the random prod-uct should still be provided because of the benefits from the "reverse quality discrimination".Moreover,numerical application results and some parameters sensitivity analysis are given.Finally,the dynamic game evolution process of probabilistic selling model in duopoly selling differentiated-quality products market by using probabilistic and traditional selling strategy are studied.(4)Based on game theory and traditional optimization methods,Pay-what-you-want pric-ing model with consumers fairness and two-stage selling model considering Name-your-own-price channel are studied respectively.On the one hand,the fairness of consumers is incorporat-ed into pay-what-you-want model,and a dynamic game model satisfying resource constraints is established.The conditions for the existence of equilibrium solutions under the conditions of fairness and constraints are given.The equilibrium solution of the mixed strategy of the model is further derived.Then,an illustrative example and sensitivity analysis of relevant pa-rameters are given.On the other hand,a two-stage pricing selling model is constructed under the monopoly supplier providing entity channel and name-your-own-price channel.The opti-mal pricing,optimal revenue and inventory conditions of suppliers are obtained by theoretical analysis.Traditional research methods and different behavioral decision-making theories are used to describe the users’ main psychological characteristics and behaviors from different perspectives and sides.It is a further development and extension of model theories.They are not only of great importance in theory and practice,but also provide new means for users to make practical decisions.