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A comparison of approaches to exploit budget allocation data in cross-sectional maximum likelihood estimation of multi-attribute choice models

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  • González-Benito, Óscar
  • Santos-Requejo, Libia

Abstract

In this paper, four calibration approaches to exploit budget allocation data in maximum likelihood estimation of multi-attribute choice models are proposed. They differ on the implicit meaning of the dependent variable: (A) share of consumers according to the preferred alternative; (B) share of sales; (C) average share of consumer's budget; and (D) share of sales according to the preferred alternative. Differences between them can be conceived as depending on two circumstances: customer loyalty and customer selectivity. These are tested in the context of spatial consumer behavior, market response to hypermarket chains being represented as a function of their location strategies. Results show that different nuances on the definition of the dependent variable lead to slightly different relationships with the explanatory variables and to different predictive capabilities.

Suggested Citation

  • González-Benito, Óscar & Santos-Requejo, Libia, 2002. "A comparison of approaches to exploit budget allocation data in cross-sectional maximum likelihood estimation of multi-attribute choice models," Omega, Elsevier, vol. 30(5), pages 315-324, October.
    • Handle: RePEc:eee:jomega:v:30:y:2002:i:5:p:315-324
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    Cited by:

    1. Óscar González-Benito & César Bustos-Reyes & Pablo Muñoz-Gallego, 2007. "Isolating the geodemographic characterisation of retail format choice from the effects of spatial convenience," Marketing Letters, Springer, vol. 18(1), pages 45-59, June.
    2. Gonzalez-Benito, Oscar, 2005. "Spatial competitive interaction of retail store formats: modeling proposal and empirical results," Journal of Business Research, Elsevier, vol. 58(4), pages 457-466, April.

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