Configuration Equilibrium Model of Product Variant Design Driven by Customer Requirements

Abstract

In view of the dynamic change of customer requirements (CRs) during the process of product use, in this paper we propose a Bayesian Nash equilibrium configuration model for product variant design driven by CRs. By analyzing CRs, the complete variant requirements of the products can be obtained. Combined with modularization and parameterization variant design methods, a parametric variant instance is proposed. Since cost and delivery time are affected by the product variant design, firms and customers are established as two decision-making bodies, and Bayesian Nash theory is introduced to the product configuration. The theory takes the product cost and customer satisfaction as the payoff function of the game, and based on the threshold value search of the customer satisfaction it determines the strategy set of the two parties. The Nash equilibrium solution equation is established and solved by a simulated annealing algorithm. The optimal product configuration scheme satisfying the interests of both sides of the game is obtained. Finally, the automatic guided vehicle (AGV) is taken as an example to illustrate the effectiveness and practicability of the method.

Product Portfolio Management in Competitive Environments

“…In Liu et al (2017), the competitive interactions of firms to design product line has been formulated with the Stackelberg model and for an industrial case of cell phones and the analysis of finding an equilibrium of this model has been implemented. Moreover, the competition environment between two firms from the viewpoint of the product cost and customer satisfaction has been modeled by a Bayesian game Yang et al (2019).…”

A Pro-Environmental Method of Sample Size Determination to Predict the Quality Level of Products Considering Current Customers’ Expectations

“…In previous research [29], the DBC method has been used, which allows for customers to participate in the process of product design, resulting in modification and adjustment of the product to the customers' requirements. Therefore, in the context of processing and determination of products' quality level, the main methods used have been Kansei (KE) [24,[30][31][32], Quality Function Deployment (QFD) [33][34][35][36], Kano [16,34,37,38], and the Bayesian Network (Naive Bayesian Classifier) [39][40][41][42][43]. These methods were also integrated [31,32,34,38,44].…”

“…In turn, the above-mentioned Bayesian network (i.e., the so-called Naive Bayesian Classifier), is a probabilistic classifier based on independent, conditional assumptions. Examples in the literature, e.g., [39][40][41][42][43], apply the Bayesian network to adjust the level of product quality to meet customers' requirements. Forecasting or prediction of products' quality level has been analyzed in which authors applied a hidden Markov chain model [16,33,36].…”

A Self-Adaptive Extra-Gradient Methods for a Family of Pseudomonotone Equilibrium Programming with Application in Different Classes of Variational Inequality Problems

“…The equilibrium problem (EP) has many mathematical problems as a particular case, for example, the fixed point problems, complementarity problems, the variational inequality problems (V IP), the minimization problems, Nash equilibrium of noncooperative games, saddle point problems and problem of vector minimization (see [1][2][3][4]). The unique formulation of an equilibrium problem was specifically defined in 1992 by Muu and Oettli [5] and further developed by Blum and Oettli [1].…”