Pricing strategy in a dual-channel and remanufacturing supply chain system

Authored by Chengzhi Jiang, Feng Xu, Zhaohan Sheng

Date Published: 2010

DOI: 10.1080/00207720903576506

Sponsors: Chinese National Natural Science Foundation

Platforms: Java

Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

This article addresses the pricing strategy problems in a supply chain system where the manufacturer sells original products and remanufactured products via indirect retailer channels and direct Internet channels. Due to the complexity of that system, agent technologies that provide a new way for analysing complex systems are used for modelling. Meanwhile, in order to reduce the computational load of searching procedure for optimal prices and profits, a learning search algorithm is designed and implemented within the multi-agent supply chain model. The simulation results show that the proposed model can find out optimal prices of original products and remanufactured products in both channels, which lead to optimal profits of the manufacturer and the retailer. It is also found that the optimal profits are increased by introducing direct channel and remanufacturing. Furthermore, the effect of customer preference, direct channel cost and remanufactured unit cost on optimal prices and profits are examined.

Tags

Agent-based modelling Pricing dual-channel learning agent remanufacturing supply chain system