Pricing Decisions for an Omnichannel Retailing Under Service Level Considerations - Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems Access content directly
Conference Papers Year : 2021

Pricing Decisions for an Omnichannel Retailing Under Service Level Considerations

Abstract

An increasing number of retailers are presently moving to omnichannel configurations and embracing modern innovations to integrate the physical store and the online store to provide customers a comprehensive shopping experience. We develop a classical newsvendor model where a retailer buys items from a supplier and distributes them through two market segments, online vs. offline. We seek optimal prices for the product in the two channels under the newsvendor model with a single period, price-based stochastic demand, and cycle service level-based order quantity to maximize the retailer’s profit. Motivated by market share models often used in marketing, we focus on a demand model involving multiplicative uncertainty and interaction between the two sales channels. The pricing problem arising is not to be well behaved because it is difficult to verify the joint concavity in prices of the objective function’s deterministic version. However, we find that the objective function is still reasonably well behaved within the sense that there is a unique solution for our optimal problem. We observe such a situation through the visualization graphs in bounded conditions for prices and find the approximate optimal point.
Fichier principal
Vignette du fichier
520759_1_En_20_Chapter.pdf (553.03 Ko) Télécharger le fichier
Origin : Explicit agreement for this submission
licence : CC BY - Attribution

Dates and versions

hal-03573606 , version 1 (14-02-2022)

Licence

Attribution

Identifiers

Cite

Minh Tam Tran, Yacine Rekik, Khaled Hadj-Hamou. Pricing Decisions for an Omnichannel Retailing Under Service Level Considerations. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.175-185, ⟨10.1007/978-3-030-85906-0_20⟩. ⟨hal-03573606⟩
50 View
5 Download

Altmetric

Share

Gmail Facebook X LinkedIn More