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

  • Bogumił Kamiński
  • Tomasz Olczak
  • Paweł Prałat
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10519)

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.

References

  1. Aiello, W., Bonato, A., Cooper, C., Janssen, J., Prałat, P.: A spatial web graph model with local influence regions. Internet Math. 5, 175–196 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  2. Akerlof, G.A.: The market for “lemons”: quality uncertainty and the market mechanism. Q. J. Econ. 84(3), 488–500 (1970)CrossRefGoogle Scholar
  3. Cooper, C., Frieze, A., Prałat, P.: Some typical properties of the spatial preferred attachment model. Internet Math. 10, 27–47 (2014)MathSciNetzbMATHGoogle Scholar
  4. Evans, G.W., Honkapohja, S.: Learning and Expectations in Macroeconomics. Princeton University Press (2001)Google Scholar
  5. Frydman, R., Phelps, E.S. (eds.): The Way Forward for Macroeconomics. Princeton University Press (2013)Google Scholar
  6. Izquierdo, S.S., Izquierdo, L.R.: The impact of quality uncertainty without asymmetric information on market efficiency. J. Bus. Res. 60(8), 858–867 (2007)CrossRefGoogle Scholar
  7. Janssen, J., Hurshman, M., Kalyaniwalla, N.: Model selection for social networks using graphlets. Internet Math. 8(4), 338–363 (2013a)MathSciNetCrossRefGoogle Scholar
  8. Janssen, J., Prałat, P., Wilson, R.: Geometric graph properties of the spatial preferred attachment model. Adv. Appl. Math. 50, 243–267 (2013b)MathSciNetCrossRefzbMATHGoogle Scholar
  9. Janssen, J., Prałat, P., Wilson, R.: Non-uniform distribution of nodes in the spatial preferential attachment model. Internet Math. 12(1–2), 121–144 (2016)MathSciNetCrossRefGoogle Scholar
  10. Linderman, K., Schroeder, R.G., Zaheer, S., Choo, A.S.: Six sigma: a goal-theoretic perspective. J. Oper. Manage. 21(2), 193–203 (2003)CrossRefGoogle Scholar
  11. Lucas, R.E.: Expectations and the neutrality of money. J. Econ. Theory 4(2), 103–124 (1972)MathSciNetCrossRefGoogle Scholar
  12. Muth, J.F.: Optimal properties of exponentially weighted forecasts. J. Am. Statist. Assoc. 55(290), 299–306 (1960)CrossRefzbMATHGoogle Scholar
  13. Muth, J.F.: Rational expectations and the theory of price movements. Econometrica J. Econ. Soc. 315–335 (1961)Google Scholar
  14. Nerlove, M.: Adaptive expectations and cobweb phenomena. Q. J. Econ. 72(2), 227–240 (1958)MathSciNetCrossRefGoogle Scholar
  15. Ostroumova Prokhorenkova, L., Prałat, P., Raigorodskii, A.: Modularity of complex networks models. In: Bonato, A., Graham, F.C., Prałat, P. (eds.) WAW 2016. LNCS, vol. 10088, pp. 115–126. Springer, Cham (2016). doi: 10.1007/978-3-319-49787-7_10 CrossRefGoogle Scholar
  16. Sargent, T.J.: Rational expectations, the real rate of interest, and the natural rate of unemployment. Brookings Papers Econ. Activity 2, 429–480 (1973)CrossRefGoogle Scholar
  17. Schroeder, R.G., Linderman, K., Liedtke, C., Choo, A.S.: Six sigma: definition and underlying theory. J. Oper. Manage. 26(4), 536–554 (2008)CrossRefGoogle Scholar
  18. Wormald, N.: The Differential Equation Method for Random Graph Processes and Greedy Algorithms. Lectures on Approximation and Randomized Algorithms, pp. 73–155 (1999)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Bogumił Kamiński
    • 1
  • Tomasz Olczak
    • 1
  • Paweł Prałat
    • 2
  1. 1.Decision Support and Analysis UnitWarsaw School of EconomicsWarsawPoland
  2. 2.Department of MathematicsRyerson UniversityTorontoCanada

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