Managing high-end ex-demonstration product returns

Some manufacturers demonstrate their products so that customers can gain experience before making a purchase. We present a novel application of a closed-loop supply chain where product returns from demonstrations of high-end IT equipment are substantial and the major delay in the system is due to the long demonstration time at the client sites. In addition, the product lifecycle is short and the value erodes rapidly over time, with steep drops in the resale revenue when new product generations are introduced. We present a finite lifecycle model that captures the key trade-offs in this environment, that is, either to reuse a collected ex-demo product for a next demonstration or to salvage its residual value in the secondary market and use a new product to satisfy the next demo request. We derive two cost/revenue signals that enable us to distinguish between fast and slow value erosion. We show that the fast/slow erosion decision is dynamic and depends on the rate of value erosion and the length of the demonstration time. We analyze the optimal demo pool strategies and show that in the case of fast erosion it may be better to postpone reuse activities until later in the lifecycle. We illustrate our model using empirical data from a large IT manufacturer and formulate several guidelines so as to better manage high value ex-demonstration product returns

Maximizing remanufacturing profit using product acquisition management

The profitability of remanufacturing depends on the quantity and quality of product returns and on the demand for remanufactured products. The quantity and quality of product returns can be influenced by varying quality dependent acquisition prices, i.e., by using product acquisition management. Demand can be influenced by varying the selling price. We develop a framework for determining the optimal prices and the corresponding profitability

A Reverse Logistics Network Model for Handling Returned Products

58827Due to the emergence of e-commerce and the proliferation of liberal return policies, product returns have become daily routines for many companies. Considering the significant impact of product returns on the company’s bottom line, a growing number of companies have attempted to streamline the reverse logistics process. Products are usually returned to initial collection points (ICPs) in small quantities and thus increase the unit shipping cost due to lack of freight discount opportunities. One way to address this issue is to aggregate the returned products into a larger shipment. However, such aggregation increases the holding time at the ICP, which in turn increases the inventory carrying costs. Considering this logistics dilemma, the main objectives of this research are to minimize the total cost by determining the optimal location and collection period of holding time of ICPs; determining the optimal location of a centralized return centre; transforming the nonlinear objective function of the proposed model formulation by Min et al. (2006a) into a linear form; and conducting a sensitivity analysis to the model solutions according to varying parameters such as shipping volume. Existing models and solution procedures are too complicated to solve real-world problems. Through a series of computational experiments, we discovered that the linearization model obtained the optimal solution at a fraction of the time used by the traditional nonlinear model and solution procedure, as well as the ability to handle up to 150 customers as compared to 30 in the conventional nonlinear model. As such, the proposed linear model is more suitable for actual industry applications than the existing models.S

Product recovery strategies

no abstract

Maximizing remanufacturing profit using product acquisition management

The profitability of remanufacturing depends on the quantity and quality of product returns and on the demand for remanufactured products. The quantity and quality of product returns can be influenced by varying quality dependent acquisition prices, i.e., by using product acquisition management. Demand can be influenced by varying the selling price. We develop a framework for determining the optimal prices and the corresponding profitability.remanufacturing;profitability;acquisition management