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Property of Fluctuations of Sales Quantities by Product Category in Convenience Stores

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  • Gaku Fukunaga
  • Hideki Takayasu
  • Misako Takayasu

Abstract

The ability to ascertain the extent of product sale fluctuations for each store and locality is indispensable to inventory management. This study analyzed POS data from 158 convenience stores in Kawasaki City, Kanagawa Prefecture, Japan and found a power scaling law between the mean and standard deviation of product sales quantities for several product categories. For the statistical domains of low sales quantities, the power index was 1/2; for large sales quantities, the power index was 1, so called Taylor’s law holds. The value of sales quantities with changing power indixes differed according to product category. We derived a Poissonian compound distribution model taking into account fluctuations in customer numbers to show that the scaling law could be explained theoretically for most of items. We also examined why the scaling law did not hold in some exceptional cases.

Suggested Citation

  • Gaku Fukunaga & Hideki Takayasu & Misako Takayasu, 2016. "Property of Fluctuations of Sales Quantities by Product Category in Convenience Stores," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-19, June.
  • Handle: RePEc:plo:pone00:0157653
    DOI: 10.1371/journal.pone.0157653
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    References listed on IDEAS

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    5. Mizuno, Takayuki & Toriyama, Masahiro & Terano, Takao & Takayasu, Misako, 2008. "Pareto law of the expenditure of a person in convenience stores," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3931-3935.
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    Cited by:

    1. Gen Sakoda & Hideki Takayasu & Misako Takayasu, 2019. "Data Science Solutions for Retail Strategy to Reduce Waste Keeping High Profit," Sustainability, MDPI, vol. 11(13), pages 1-30, June.
    2. Kazuki Koyama & Mariko I. Ito & Takaaki Ohnishi, 2022. "Fluctuation in Grocery Sales by Brand: An Analysis Using Taylor’s Law," The Review of Socionetwork Strategies, Springer, vol. 16(2), pages 417-430, October.
    3. Gen Sakoda & Hideki Takayasu & Misako Takayasu, 2019. "Tracking Poisson Parameter for Non-Stationary Discontinuous Time Series with Taylor’s Abnormal Fluctuation Scaling," Stats, MDPI, vol. 2(1), pages 1-15, January.

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