Title: A two-period lot sizing and pricing model under multiplicative error demand

Authors: Prakash Abad

Addresses: DeGroote School of Business, McMaster University, Hamilton, Ontario L8S 4M4, Canada

Abstract: In this study, we present a two-period lot sizing and pricing model for a seasonal good, assuming that the random error in the demand function is multiplicative. The proposed model extends the classical price-setting newsvendor problem in which the selling price is held constant during the entire season. We divide the season into two periods and assume that the reseller can change the selling price mid-season. Using the service level approach, we develop a stochastic optimisation procedure for determining the lot size, period-1 price, and the rule for setting period-2 price tailored to the supply available at the beginning of period 2. We show that the two-period recourse price approach has a higher expected profit than the single-period method. The model is also applicable when a warehouse delivers a perishable good at a fixed interval, and the units lying on the shelf at any time have the same best-before date. A retailer may follow such an approach to ensure that the consumers see the items with the same best-before date at any time and do not have to search for an article with the farthest best-before date.

Keywords: stochastic optimisation; multiplicative error demand; seasonal good; lot sizing; pricing.

DOI: 10.1504/IJIR.2023.130388

International Journal of Inventory Research, 2023 Vol.6 No.2, pp.182 - 202

Received: 02 Aug 2021
Accepted: 03 Apr 2022

Published online: 18 Apr 2023 *

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