Bundle Pricing, Reservation and Refund Policies in a Two-Level Supply Chain

Abstract

Refunding and bundling reservation are known as two popular methods to increase profit where in recent years have gained attention of researchers. One main application of refunding policy emerges for online product sale methods, where consumers can be refunded by returning goods which are not favorite according to their interest. Examining three scenarios including refunding, bundle reservation and refunding along with bundle reservation policies, we will investigate a model for each corresponding scenario. We try to compare two refund and bundle reservation pricing policies in a two-level supply chain including one manufacturer and one wholesaler, and we provide a combined model including two products. The demand is constant and also the population-related information about the division of the population into two types of consumers, strategic consumers (consumers who can predict the second stage discount) and myopic consumers (consumers who can not predict the second stage discount) are available. In addition, the percentage of consumers who refund the product due to regret, the inability to install the product or other reasons, is constant and is independent of the amount of refund. We show that the combined model is optimal and has a higher profit margin than any other policy alone.

Balancing Inventory Management: Genetic Algorithm Optimization for A Novel Dynamic Lot Sizing Model in Perishable Product Manufacturing

“…To perform crossover, a pair of parent chromosomes is randomly selected from the current population with a crossover probability, 𝑃 𝑐 . Several crossover operators exist in the literature, including single-point, twopoint, multi-point, and uniform crossover operators [30], [38]. This study implements a two-cut point crossover, which operates by randomly selecting two crossover points.…”

“…Additionally, considering return rates enables manufacturers to predict the likelihood of products being returned from the market owing to defects, rejections, or lack of sales [30]. Return rates can vary widely based on product type, ranging from 3-4% for dairy items and 8% or higher for delicate fresh produce [26].…”

Supply Chain Coordination of Product and Service Bundling Based on Network Externalities

“…In addition, different bundling methods have a significant impact on the overall profit of the supply chain. In the face of different bundling methods, the optimal decisions made by different enterprises are also different [25][26][27]. With the development of network technology, the research on bundling is extended to the direction of the IoT [28,29].…”