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An improved mathematical programming formulation and application of multi-attribute choice behaviour

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  • Soumojit Kumar
  • Ashis Kumar Chatterjee

Abstract

Conjoint analysis and mathematical programming approaches have been used extensively for modelling multi-attribute choice behaviour. The mathematical programming approaches are more versatile in their ability to capture complex behaviour but have been limited to dealing with objective attributes. Conjoint analysis, though limited by the additive utility assumption, allows for both subjective and objective attributes. In this article, we modify the existing mathematical models to account for situations where the decision maker may base her decisions on only a subset of the attributes. A limitation of the earlier mathematical programming approaches has been the use of interval scale data. In the proposed model we remove this drawback using ordinal scaled data for objective attributes. The resulting MIP problem has been solved using the data provided by Green and Wind (1975) in the context of a conjoint analysis study. Finally, a case study to illustrate the utility of our model is presented.

Suggested Citation

  • Soumojit Kumar & Ashis Kumar Chatterjee, 2016. "An improved mathematical programming formulation and application of multi-attribute choice behaviour," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 25(1), pages 100-113.
    • Handle: RePEc:ids:ijores:v:25:y:2016:i:1:p:100-113
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