Abstract

Internet-based technologies have changed the way firms do business and manage their supply chains. They have influenced customers’ purchase patterns, thereby motivating manufacturers to introduce online channels alongside traditional ones. Such structures are known as dual-channels. Nowadays, an increasing number of manufacturers offer a return policy to attract more customers and to stay competitive. Furthermore, learning-based continuous improvements help firms cope with market changes and be competitive, flexible and efficient. This thesis presents three main models: The first model investigates the effect of adopting a dual-channel (comprised of a retail channel and an online channel) on the performance of a two-level (vendor-retailer) supply chain. The objective is to maximize the total profit of the system by finding the optimal markup margin and inventory decisions before and after adopting the dual-channel. The results show that adding an online channel would increase the profit of the system. However, it creates a conflict due to competition between the retail and online channels. The second model studies a supply chain system, which is comprised of production, refurbishing, collection, and waste disposal processes. A return policy in which customers can return the purchased item for a refund is also considered. The purpose is to examine the effect of different return policies on the behavior of the system before and after adopting the dual-channel strategy. In both strategies, the model analyzes the change in the profit, the pricing and inventory decisions. The findings demonstrate that the more generous the return policy is, the higher the demand, the selling prices and the overall profit. The third model investigates the effects of learning and forgetting in the vendor’s production processes. It also considers single- and dual-channel strategies. Each channel structure can adopt any of six inventory policies. Learning and forgetting effects are considered in all policies except one. The objective is to maximize the profit of the system by finding the joint optimal pricing and inventory decisions. The results suggests that learning, despite being impeded by forgetting, reduces inventory-related costs thereby allowing the chain to reduce the prices of its product(s), which increases demand and subsequently sales.

Full Text
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