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A methodology for optimal product positioning with engineering constraints consideration

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  • Kwong, C.K.
  • Luo, X.G.
  • Tang, J.F.

Abstract

Due to the complex mapping relationship between product attributes and engineering characteristics, as well as the correlations between engineering characteristics and the engineering constraints on a product, a new product following a probabilistic rule of multidimensional scaling may not be in an optimal position in product engineering space. In this paper, a new methodology for optimal product positioning by considering engineering constraints is proposed. In the proposed methodology, perceptual mapping and house of quality are introduced to link the consumer perceptual space, and product engineering space. The degree of overall customer satisfaction is considered in the rule of consumer choice probability. Based on this, an optimal product positioning model can be established. Genetic algorithms are introduced to solve the problem of the optimization model due to its non-linear characteristics. By applying genetic algorithms, the optimal value settings of a new product's engineering characteristics can be obtained. An example of optimal positioning and determination of value settings of engineering characteristics of packing machines is used to illustrate the proposed methodology.

Suggested Citation

  • Kwong, C.K. & Luo, X.G. & Tang, J.F., 2011. "A methodology for optimal product positioning with engineering constraints consideration," International Journal of Production Economics, Elsevier, vol. 132(1), pages 93-100, July.
    • Handle: RePEc:eee:proeco:v:132:y:2011:i:1:p:93-100
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    References listed on IDEAS

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    1. Chih-Hsuan Wang, 2016. "Integrating correspondence analysis with Grey relational model to implement a user-driven STP product strategy for smart glasses," Journal of Intelligent Manufacturing, Springer, vol. 27(5), pages 1007-1016, October.

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