Optimization Method For Product Line With Considering Risk Preference Behaviors Of Customers

Nowadays,with fierce market competition,many enterprises began to use product line to design products and production for the strategic objectives of reducing production cost,shorten manufacturing cycle and occupying a greater market share.With the increasing attention to customer demand,managers of enterprises began to consider purchasing risk preference of different customers in the process of product line design optimization.In the existing papers related to product line design optimization,expected utility theory and conjoint analysis method are generally used to model customer choice behavior.Customers are assumed completely rational by most experts.However,they do not consider the impact of many uncertainties including the asymmetry of customer information in product attributes and purchase process towards product line design.Prospect theory,as one of the main approaches which can represent personal irrational decision-making process under risk circumstances,is widely used in the fields of transportation,finance and so on.Due to a certain degree of similarity between product line design optimization problem and traffic net travelling problem,prospect theory can be used to measure the risk of customer purchase.In this thesis,the risk of purchasing decision-making and different behavior preference of customers has been considered.By taking typical case of high-tech products as an example,the main research achievements include the following three aspects:(1)A product utility measurement method based on prospect theory with considering risk preference behavior of customers has been proposed.This method improves the limitation of customer risk decision-making process in traditional product line design optimization theory,and explains the rationality and feasibility through actual case at the same time.As no quantitative model has been proposed in previous studies,the proposed method is an innovation point of this research.(2)The product line design optimization models which consider customers' risk preference behavior are established and solving algorithms are developed.By using the product utility measurement method which considering risk preference behavior of customers in the modeling process of customer choice behavior,the mathematical models of product line design optimization problem with the objective functions of maximum the number of customers and maximum total profit of the enterprise are established respectively.Genetic algorithm and scatter search algorithm have been designed to solve these models.(3)Scenarios based on product line cases are designed and numerical experiments of parameters are performed.In this thesis,seven possible product line case scenarios have been presented and applied in the experimental analysis.It is proved that the proposed measurement method is more reasonable than the expected utility theory in the analysis of customer behavior.Large numbers of simulation experiments of heuristic algorithms and model parameters show that the solving algorithms are effective.The customers are classified from the perspective of risk preference,and some valuable management implications are obtained.