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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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    1. Allan D. Shocker & V. Srinivasan, 1974. "A Consumer-Based Methodology for the Identification of New Product Ideas," Management Science, INFORMS, vol. 20(6), pages 921-937, February.
    2. D. Sudharshan & Jerrold H. May & Allan D. Shocker, 1987. "A Simulation Comparison of Methods for New Product Location," Marketing Science, INFORMS, vol. 6(2), pages 182-201.
    3. Glen L. Urban, 1975. "Perceptor: A Model for Product Positioning," Management Science, INFORMS, vol. 21(8), pages 858-871, April.
    4. Green, Paul E. & Krieger, Abba M., 1989. "Recent contributions to optimal product positioning and buyer segmentation," European Journal of Operational Research, Elsevier, vol. 41(2), pages 127-141, July.
    5. Hicks, C., 2004. "A genetic algorithm tool for designing manufacturing facilities in the capital goods industry," International Journal of Production Economics, Elsevier, vol. 90(2), pages 199-211, July.
    6. Bezalel Gavish & Dan Horsky & Kizhanatham Srikanth, 1983. "An Approach to the Optimal Positioning of a New Product," Management Science, INFORMS, vol. 29(11), pages 1277-1297, November.
    7. Bachem, A. & Simon, H., 1981. "A product positioning model with costs and prices," European Journal of Operational Research, Elsevier, vol. 7(4), pages 362-370, August.
    8. Albers, Sonke, 1979. "An extended algorithm for optimal product positioning," European Journal of Operational Research, Elsevier, vol. 3(3), pages 222-231, May.
    9. Baier, Daniel & Gaul, Wolfgang, 1998. "Optimal product positioning based on paired comparison data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 365-392, November.
    10. P. V. (Sundar) Balakrishnan & Varghese S. Jacob, 1996. "Genetic Algorithms for Product Design," Management Science, INFORMS, vol. 42(8), pages 1105-1117, August.
    11. Richard D. McBride & Fred S. Zufryden, 1988. "An Integer Programming Approach to the Optimal Product Line Selection Problem," Marketing Science, INFORMS, vol. 7(2), pages 126-140.
    12. Chou, Jui-Sheng & Tai, Yian & Chang, Lian-Ji, 2010. "Predicting the development cost of TFT-LCD manufacturing equipment with artificial intelligence models," International Journal of Production Economics, Elsevier, vol. 128(1), pages 339-350, November.
    13. Gruca, Thomas S. & Klemz, Bruce R., 2003. "Optimal new product positioning: A genetic algorithm approach," European Journal of Operational Research, Elsevier, vol. 146(3), pages 621-633, May.
    14. Rajeev Kohli & R. Sukumar, 1990. "Heuristics for Product-Line Design Using Conjoint Analysis," Management Science, INFORMS, vol. 36(12), pages 1464-1478, December.
    15. Karipidis, Philippos I., 2011. "Market evaluations of dimensions of design quality," International Journal of Production Economics, Elsevier, vol. 129(2), pages 292-301, February.
    16. Gregory Dobson & Shlomo Kalish, 1993. "Heuristics for Pricing and Positioning a Product-Line Using Conjoint and Cost Data," Management Science, INFORMS, vol. 39(2), pages 160-175, February.
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