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Endogenous Differentiation of Consumer Preferences Under Quality Uncertainty in a SPA Network

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Algorithms and Models for the Web Graph (WAW 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10519))

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Abstract

We study a duopoly market on which there is uncertainty of a product quality. Consumers adaptively learn about quality of products when they buy them (direct learning) or from other consumers with whom they are interacting in a social network modelled as a SPA graph (indirect learning). We show that quality uncertainty present in such a market leads to endogenous segmentation of consumers’ preferences towards suppliers. Additionally, we show that in this setting, even if both companies have the same expected quality, the company with lower variance of quality will gain higher market share.

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Notes

  1. 1.

    We omit it in the text as it is large but easy to derive.

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Author information

Authors and Affiliations

  1. Decision Support and Analysis Unit, Warsaw School of Economics, Warsaw, Poland

    Bogumił Kamiński & Tomasz Olczak

  2. Department of Mathematics, Ryerson University, Toronto, ON, M5B 2K3, Canada

    Paweł Prałat

Authors
  1. Bogumił Kamiński
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  2. Tomasz Olczak
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  3. Paweł Prałat
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Corresponding author

Correspondence to Paweł Prałat .

Editor information

Editors and Affiliations

  1. Ryerson University, Toronto, Ontario, Canada

    Anthony Bonato

  2. Mathematics, UC San Diego, La Jolla, California, USA

    Fan Chung Graham

  3. Mathematics, Ryerson University, Toronto, Ontario, Canada

    Paweł Prałat

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Kamiński, B., Olczak, T., Prałat, P. (2017). Endogenous Differentiation of Consumer Preferences Under Quality Uncertainty in a SPA Network. In: Bonato, A., Chung Graham, F., Prałat, P. (eds) Algorithms and Models for the Web Graph. WAW 2017. Lecture Notes in Computer Science(), vol 10519. Springer, Cham. https://doi.org/10.1007/978-3-319-67810-8_4

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  • DOI: https://doi.org/10.1007/978-3-319-67810-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67809-2

  • Online ISBN: 978-3-319-67810-8

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