A methodology for optimal product positioning with engineering constraints consideration

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

International Journal of Production Economics, 2011, vol. 132, issue 1, 93-100

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.

Keywords: Product; positioning; Customer; satisfaction; Optimization; Genetic; algorithms (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0925-5273(11)00135-6
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:132:y:2011:i:1:p:93-100

Access Statistics for this article

International Journal of Production Economics is currently edited by Stefan Minner

More articles in International Journal of Production Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().