Nested bilevel genetic algorithms for game-theoretic optimization of product line design considering competition

Author(s):  
Xiaojie Liu ◽  
Gang Du ◽  
Roger J. Jiao ◽  
Yi Xia
2014 ◽  
Vol 48 (9/10) ◽  
pp. 1870-1891 ◽  
Author(s):  
Hwan Chung ◽  
Eunkyu Lee

Purpose – The purpose of this study is to analyze the problem of optimal product line design in marketing channels. Design/methodology/approach – This paper develops a game theoretic model, in which a firm markets a line of a limited number of products at different quality levels to serve a market composed of multiple consumer segments. The consumer segments are modeled as clusters of somewhat heterogeneous consumers as typically observed in the real world. These model characteristics allow us to consider a broader set of targeting strategies such as sub-segmentation and partial cannibalization which have not been considered previously. By considering both a vertically integrated channel and a decentralized channel, we investigate how channel structure influences optimal product line design. We analyze the model mathematically with supplemental numerical analyses. Findings – Our analysis shows that “quality distortion” in product line design is not limited to the low-end product, as previously reported, but can happen to the high-end product. The direction of these quality distortions may be downward or upward, leading to either increased or decreased differentiation between the two products. Furthermore, channel decentralization makes it more likely for the firm to strategically choose upward partial cannibalization or sub-segmentation. Consequently, contrary to previous studies, we demonstrate that there exist conditions under which channel decentralization leads to higher product quality. Originality/value – Our model reflects a more realistic market environment and a firm’s practical constraints than previous studies, which typically assume perfect homogeneity within each segment and/or the feasibility of offering an infinite number of products. This extension produces interesting new results and insights that provide more practical implications for a firm’s optimal product line design strategy.


2003 ◽  
Vol 45 (2) ◽  
pp. 1-13 ◽  
Author(s):  
Winfried Steiner ◽  
Harald Hruschka

Recently, Balakrishnan and Jacob (1996) have proposed the use of Genetic Algorithms (GA) to solve the problem of identifying an optimal single new product using conjoint data. Here we extend and evaluate the GA approach with regard to the more general problem of product line design. We consider profit contribution as a firm's economic criterion to evaluate product design decisions and illustrate how the genetic operators work to find the product line with maximum profit contribution. In a Monte Carlo simulation, we assess the performance of the GA methodology in comparison to Green and Krieger's (1985) greedy heuristic.


Author(s):  
Michail Pantourakis ◽  
Stelios Tsafarakis ◽  
Konstantinos Zervoudakis ◽  
Efthymios Altsitsiadis ◽  
Andreas Andronikidis ◽  
...  

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