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Comparison Dimensions and Similarity: Addressing Individual Heterogeneity

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  • Jelnov, Pavel

    (Leibniz University of Hannover and Yezreel Valley College)

Abstract

How many comparison dimensions individuals consider when they are asked to judge how similar two different objects are? I address individual heterogeneity in the number of comparison dimensions with data from a laboratory experiment. I estimate the smallest number of dimensions such that objects may be represented in space where distance corresponds to similarity. I find that the mean smallest number of dimensions in real data is one standard deviation smaller than in randomly simulated data. Furthermore, I find that individuals who find the objects relatively similar to each other are also the ones who implicitly consider fewer dimensions.

Suggested Citation

  • Jelnov, Pavel, 2019. "Comparison Dimensions and Similarity: Addressing Individual Heterogeneity," IZA Discussion Papers 12355, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp12355
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    References listed on IDEAS

    as
    1. Louis Guttman, 1968. "A general nonmetric technique for finding the smallest coordinate space for a configuration of points," Psychometrika, Springer;The Psychometric Society, vol. 33(4), pages 469-506, December.
    2. Lefkoff-Hagius, Roxanne & Mason, Charlotte H, 1993. "Characteristic, Beneficial, and Image Attributes in Consumer Judgments of Similarity and Preference," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(1), pages 100-110, June.
    3. Lin, L. & Fong, D.K.H., 2019. "Bayesian multidimensional scaling procedure with variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 129(C), pages 1-13.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    multidimensional scaling; similarity; latent dimensions; dimensionality;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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