An improved mathematical programming formulation and application of multi-attribute choice behaviour
Soumojit Kumar and
Ashis Kumar Chatterjee
International Journal of Operational Research, 2016, vol. 25, issue 1, 100-113
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.
Keywords: multi-attribute choice behaviour; mixed integer programming; mathematical modelling; ordinal scaled data. (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=73253 (text/html)
Access to full text is restricted to subscribers.
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:ids:ijores:v:25:y:2016:i:1:p:100-113
Access Statistics for this article
More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().