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The Price-Setting Newsvendor with Poisson Demand

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The Price-Setting Newsvendor with Poisson Demand. / Schulte, Benedikt; Sachs, Anna-Lena.

In: European Journal of Operational Research, Vol. 283, No. 1, 16.05.2020, p. 125-137.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Schulte, B & Sachs, A-L 2020, 'The Price-Setting Newsvendor with Poisson Demand', European Journal of Operational Research, vol. 283, no. 1, pp. 125-137. https://doi.org/10.1016/j.ejor.2019.10.039

APA

Schulte, B., & Sachs, A-L. (2020). The Price-Setting Newsvendor with Poisson Demand. European Journal of Operational Research, 283(1), 125-137. https://doi.org/10.1016/j.ejor.2019.10.039

Vancouver

Schulte B, Sachs A-L. The Price-Setting Newsvendor with Poisson Demand. European Journal of Operational Research. 2020 May 16;283(1):125-137. Epub 2019 Nov 7. doi: 10.1016/j.ejor.2019.10.039

Author

Schulte, Benedikt ; Sachs, Anna-Lena. / The Price-Setting Newsvendor with Poisson Demand. In: European Journal of Operational Research. 2020 ; Vol. 283, No. 1. pp. 125-137.

Bibtex

@article{535f8fd6e5d043278312ca89e126d6ff,
title = "The Price-Setting Newsvendor with Poisson Demand",
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.",
keywords = "Inventory, Newsvendor model, Pricing, Poisson demand",
author = "Benedikt Schulte and Anna-Lena Sachs",
year = "2020",
month = may,
day = "16",
doi = "10.1016/j.ejor.2019.10.039",
language = "English",
volume = "283",
pages = "125--137",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier Science B.V.",
number = "1",

}

RIS

TY - JOUR

T1 - The Price-Setting Newsvendor with Poisson Demand

AU - Schulte, Benedikt

AU - Sachs, Anna-Lena

PY - 2020/5/16

Y1 - 2020/5/16

N2 - 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.

AB - 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.

KW - Inventory

KW - Newsvendor model

KW - Pricing

KW - Poisson demand

U2 - 10.1016/j.ejor.2019.10.039

DO - 10.1016/j.ejor.2019.10.039

M3 - Journal article

VL - 283

SP - 125

EP - 137

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 1

ER -