The purpose of this paper is to show that conjoint measurement has proved to be an effective tool for identifying customer preferences. However, in order to market products and services successfully information about the variable costs for the various attributes and their respective levels needs to be considered. A platform approach could reduce these costs and generate very effective preference drivers.
This paper proposes and elaborates a model, which examines a joint implementation of conjoint measurement and the platform concept. The model is empirically tested on data gathered on a stratified random sample of customers through the application of valid and reliable measures. The model is tested using a conjoint and regression design.
The results in this paper show the usefulness of a joint implementation of conjoint measurement and the platform concept. Variable costs can be reduced considerably and preferences can be adequately identified. In combining market information (preference data) with cost data profitability is increased.
This paper specifically is to address the following four questions: What are the most important attributes and levels for customers? What are the variable costs for those attributes and levels? Could an implementation of the platform concept reduce those costs significantly? Are there any efficient preference drivers?
Riesenbeck, H., Herrmann, A., Heitman, M. and Algesheimer, R. (2006), "An approach to profit‐maximizing product design on the basis of the platform concept", International Journal of Quality & Reliability Management, Vol. 23 No. 7, pp. 788-806. https://doi.org/10.1108/02656710610679815
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