A heuristic approach to product design
Management Science
Product positioning under price competition
Management Science
Heuristics for product-line design using conjoint analysis
Management Science
Genetic algorithms for product design
Management Science
An evolutionary algorithm approach to the share of choices problem in the product line design
Computers and Operations Research
Conjoint analysis for IPTV service
Expert Systems with Applications: An International Journal
Conjoint analysis for recruiting high quality students for college education
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A game theory-based model for product portfolio management in a competitive market
Expert Systems with Applications: An International Journal
A Conjoint-based approach to student evaluations of teaching performance
Expert Systems with Applications: An International Journal
How to go global with differentiated products
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
In today's highly competitive environment, where market oriented firms aim to maximize profits through customer satisfaction, there is an increasing need to design a product line, rather than a single product. The main goal of designing a profit maximizing product line is to target the 'right product' to the 'right customer'. Although conjoint analysis has turned out to be one of the most widely used techniques for product line design, it falls to explicitly consider retaliatory reactions from competitors. In this paper, we propose a new conjoint-based approach to competitive new product line design, employing the Nash equilibrium concept. The optimal product line design problem for each firm is formulated as a nonlinear integer programming problem. In the absence of a closed-form solution, to compute the Nash equilibrium and to determine the optimal product line, we propose a two-phase procedure: a sequential iterative procedure in the first phase, and backward induction in the second. To solve the optimization problem in each of the iterations of the sequential procedure, we used the branch-and-bound method. The proposed approach is illustrated under several scenarios of competition using previously published conjoint data.