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The price-setting newsvendor with Poisson demand

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  • Schulte, Benedikt
  • Sachs, Anna-Lena

Abstract

The price-setting newsvendor (PSN) model has received considerable attention since it was first introduced by Whitin (1955). However, the existing publications that study this model consistently assume the existence of a continuous density function of demand. In this paper, we study the PSN model with Poisson demand — that is, a discrete demand distribution without density function. The Poisson PSN has an important property, it combines price-dependency of variance and coefficient of variation of the (standard) additive and multiplicative models: demand variance decreases and the coefficient of variation increases in the selling price. We develop an analytical solution approach that covers a broad class of demand models, including linear and logit demand, explain how to apply our approach to more general demand functions via piece-wise linear approximation, and develop analytical and numerical insights. We characterize the behavior of the optimal price and we analyze the performance gap of different price-setting heuristics. Among other insights, we observe some instances in which a significant share of profits would be lost if the discrete nature of demand were not modeled explicitly. To help companies overcome this risk, we present an easily applicable decision rule with which to determine when to use simple heuristics and when to solve the associated discrete optimization problem.

Suggested Citation

  • Schulte, Benedikt & Sachs, Anna-Lena, 2020. "The price-setting newsvendor with Poisson demand," European Journal of Operational Research, Elsevier, vol. 283(1), pages 125-137.
  • Handle: RePEc:eee:ejores:v:283:y:2020:i:1:p:125-137
    DOI: 10.1016/j.ejor.2019.10.039
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    1. Nicholas C. Petruzzi & Maqbool Dada, 1999. "Pricing and the Newsvendor Problem: A Review with Extensions," Operations Research, INFORMS, vol. 47(2), pages 183-194, April.
    2. Pangburn, Michael S. & Stavrulaki, Euthemia, 2008. "Capacity and price setting for dispersed, time-sensitive customer segments," European Journal of Operational Research, Elsevier, vol. 184(3), pages 1100-1121, February.
    3. Edwin S. Mills, 1959. "Uncertainty and Price Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 73(1), pages 116-130.
    4. Junhong Chu & Pradeep Chintagunta & Javier Cebollada, 2008. "Research Note—A Comparison of Within-Household Price Sensitivity Across Online and Offline Channels," Marketing Science, INFORMS, vol. 27(2), pages 283-299, 03-04.
    5. E. Zabel, 1970. "Monopoly and Uncertainty," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 37(2), pages 205-219.
    6. Michael Salinger & Miguel Ampudia, 2011. "Simple Economics of the Price-Setting Newsvendor Problem," Management Science, INFORMS, vol. 57(11), pages 1996-1998, November.
    7. Gal Raz & Evan L. Porteus, 2006. "A Fractiles Perspective to the Joint Price/Quantity Newsvendor Model," Management Science, INFORMS, vol. 52(11), pages 1764-1777, November.
    8. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    9. Omar Besbes & Assaf Zeevi, 2015. "On the (Surprising) Sufficiency of Linear Models for Dynamic Pricing with Demand Learning," Management Science, INFORMS, vol. 61(4), pages 723-739, April.
    10. Arthur J. Nevins, 1966. "Some Effects of Uncertainty: Simulation of a Model of Price," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 80(1), pages 73-87.
    11. Teunter, Ruud H. & Klein Haneveld, Willem K., 2008. "Dynamic inventory rationing strategies for inventory systems with two demand classes, Poisson demand and backordering," European Journal of Operational Research, Elsevier, vol. 190(1), pages 156-178, October.
    12. David J. Braden & Marshall Freimer, 1991. "Informational Dynamics of Censored Observations," Management Science, INFORMS, vol. 37(11), pages 1390-1404, November.
    13. Gabriel R. Bitran & Susana V. Mondschein, 1997. "Periodic Pricing of Seasonal Products in Retailing," Management Science, INFORMS, vol. 43(1), pages 64-79, January.
    14. Zabel, Edward, 1972. "Multiperiod monopoly under uncertainty," Journal of Economic Theory, Elsevier, vol. 5(3), pages 524-536, December.
    15. T. M. Whitin, 1955. "Inventory Control and Price Theory," Management Science, INFORMS, vol. 2(1), pages 61-68, October.
    16. Gunnar T. Thowsen, 1975. "A dynamic, nonstationary inventory problem for a price/quantity setting firm," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 22(3), pages 461-476, September.
    17. Rubio-Herrero, Javier & Baykal-Gürsoy, Melike, 2018. "On the unimodality of the price-setting newsvendor problem with additive demand under risk considerations," European Journal of Operational Research, Elsevier, vol. 265(3), pages 962-974.
    18. Ayşe Kocabıyıkoğlu & Ioana Popescu, 2011. "An Elasticity Approach to the Newsvendor with Price-Sensitive Demand," Operations Research, INFORMS, vol. 59(2), pages 301-312, April.
    19. Samii, Amir-Behzad & Pibernik, Richard & Yadav, Prashant & Vereecke, Ann, 2012. "Reservation and allocation policies for influenza vaccines," European Journal of Operational Research, Elsevier, vol. 222(3), pages 495-507.
    20. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
    21. Delignette-Muller, Marie Laure & Dutang, Christophe, 2015. "fitdistrplus: An R Package for Fitting Distributions," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i04).
    22. Shengqi Ye & Goker Aydin & Shanshan Hu, 2015. "Sponsored Search Marketing: Dynamic Pricing and Advertising for an Online Retailer," Management Science, INFORMS, vol. 61(6), pages 1255-1274, June.
    23. Marie Laure Delignette-Muller & Christophe Dutang, 2015. "fitdistrplus : An R Package for Fitting Distributions," Post-Print hal-01616147, HAL.
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    5. Yuan, Jun & Shi, Xunpeng & He, Junliang, 2024. "LNG market liberalization and LNG transportation: Evaluation based on fleet size and composition model," Applied Energy, Elsevier, vol. 358(C).

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