Selective Newsvendor Problem with Dependent Leadtime and Joint Marketing Decisions

TL;DR

This paper introduces new models for a selective newsvendor problem considering dependent lead times and joint marketing decisions, providing an efficient algorithm and insights for supply chain management in various industries.

Contribution

It develops two novel models addressing dependent lead times and joint marketing, along with an efficient solution algorithm for optimal decision-making in supply chains.

Findings

Optimal order quantity matches demand when demand is below the upper limit.

Market increases lead to shortages, prompting sourcing from local suppliers.

Model effectively explains behaviors and guides decision-making in supply networks.

Abstract

In this paper, we investigate a joint decision-making pattern for a two-stage supply chain network, including a supplier, a company, and its customers. We investigate two types of demand patterns, associated with dependent lead time and service level considerations. We define two novel models, including all-or-nothing selective newsvendor problem (AON-SNP) and selective news Vendor Problem with Dependent Lead Time and Price Related Demands (DLSNP). The proposed models are applicable to numerous areas such as the fashion, furniture, and electronic industries. We develop an efficient solution algorithm, referred to as R-search, to identify an optimal solution for the DL-selectivity problem. We examine various responses of the system through parameter sensitivity analysis. Our model proves that if the total demand is lower than the upper limit of the order quantity, the best strategy for Q is to match that demand. If the market increases, more demand comes in, leading to a shortage, and forcing the company to find other local suppliers to fill the additional demand. The results demonstrate that our model well explains various behavior for all involved parties in the network, and provide guidance on intelligent decision making for the company.