Publication: Pricing Strategy versus Heterogeneous Shopping Behavior under Market Price Dispersion
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2016
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Hindawi Publishing Corporation
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We consider the ubiquitous problem of a seller competing in a market of a product with dispersed prices and having limited information about both his competitors’ prices and the shopping behavior of his potential customers. Given the distribution of market prices, the distribution of consumers’ shopping behavior, and the seller’s cost as inputs, we find the computational solution for the pricing strategy that maximizes his expected profits. We analyze the seller’s solution with respect to different exogenous perturbations of parametric and functional inputs. For that purpose, we produce synthetic price data using the family of Generalized Error Distributions that includes normal and quasiuniform distributions as particular cases, and we also generate consumers’ shopping data from different behavioral assumptions. Our analysis shows that, beyond price mean and dispersion, the shape of the price distribution plays a significant role in the seller’s pricing solution. We focus on the seller’s response to an increasing diversity in consumers’ shopping behavior. We show that increasing heterogeneity in the shopping distribution typically lowers seller’s prices and expected profits.
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[1] J. Bertrand, “Review of Cournot,” Journal des Savants, vol. 67, pp. 499–508, 1838.
[2] M. R. Baye, J. Morgan, and P. Scholten, “Information, search, and price dispersion,” in Handbook on Economics and Information Systems, vol. 1, 2006.
[3] G. Kaplan and G. Menzio, “The morphology of price dispersion,” International Economic Review, vol. 56, no. 4, pp. 1165–1206, 2015.
[4] G. J. Stigler, “The Economics of Information,” Journal of Political Economy, vol. 69, no. 3, pp. 213–225, 1961.
[5] K. Burdett and K. L. Judd, “Equilibrium price dispersion,” Econometrica, vol. 51, no. 4, pp. 955–969, 1983.
[6] F. Alvarez, J.-M. Rey, and R. G. Sanchis, “Choice overload, satisficing behavior, and price distribution in a time allocation model,” Abstract and Applied Analysis, vol. 2014, Article ID 569054, 9 pages, 2014.
[7] B. Scheibehenne, R. Greifeneder, and P. M. Todd, “Can there ever be too many options? A meta-analytic review of choice overload,” Journal of Consumer Research, vol. 37, no. 3, pp. 409–425, 2010.
[8] R. G. Sanchis, J.-M. Rey, and F.Alvarez, “Numerical analysis of a time allocation model accounting for choice overload,” International Journal of Computer Mathematics, vol. 91, no. 2, pp. 315–326, 2014.
[9] B. Schwartz, “Self-determination: the tyranny of freedom,” American Psychologist, vol. 55, no. 1, pp. 79–88, 2000.
[10] S. S. Iyengar and M. R. Lepper, “When choice is demotivating: can one desire too much of a good thing?” Journal of Personality and Social Psychology, vol. 79, no. 6, pp. 995–1006, 2000.
[11] B. Schwartz, A. Ward, J. Monterosso, S. Lyubomirsky, K. White, and D. R. Lehman, “Maximizing versus satisficing: happiness is a matter of choice,” Journal of Personality and Social Psychology, vol. 83, no. 5, pp. 1178–1197, 2002.
[12] R Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, 2014, http://www.R-project.org/.
[13] C. Forbes, M. Evans, N. Hastings, and B. Peacock, Statistical Distributions, John Wiley & Sons, New York, NY, USA, 2011.
[14] R. M. Gray, Entropy and Information Theory, Springer, New York, NY, USA, 1990.