From e-trash to e-treasure: how value can be created by the new e-business models for reverse logistics

Reverse logistics, that is, all operations related to the reuse of used products, excess inventory and packaging materials, gain increasing attention globally both for their promising financial potentials, the sustainable growth alternative they offer and the environmental positive impact they have. In this paper, we introduce reverse logistics and we explain how the adoption of e-commerce provides new possibilities to existing business models and what are the new e-business models in reverse logistics that have emerged. We compare these three new e-business models, namely, returns aggregators, specialty locators and integrated solution providers on a number of aspects and identify keys for their competitive advantage. Finally, we discuss conceptual and actual opportunities for these e-business models to thrive and advance and present some e-commerce tools that are being developed with the aim to address the distributed, dynamic and knowledge-intensive aspects of applications that contribute to the advancement of e-businesses in the field of reverse logistics.e-commerce;Reverse logistics;e-business models

Applying Revenue Management to the Reverse Supply Chain

We study the disposition decision for product returns in a closed-loop supply chain. Motivated by the asset recovery process at IBM, we consider two disposition alternatives. Returns may be either refurbished for reselling or dismantled for spare parts. Reselling a refurbished unit typically yields higher unit margins. However, demand is uncertain. A common policy in many firms is to rank disposition alternatives by unit margins. We show that a revenue management approach to the disposition decision which explicitly incorporates demand uncertainty can increase profits significantly. We discuss analogies between the disposition problem and the classical airline revenue management problem. We then develop single period and multi-period stochastic optimization models for the disposition problem. Analyzing these models, we show that the optimal allocation balances expected marginal profits across the disposition alternatives. A detailed numerical study reveals that a revenue management approach to the disposition problem significantly outperforms the current practice of focusing exclusively on high-margin options, and we identify conditions under which this improvement is the highest. We also show that the value recovered from the returned products critically depends on the coordination between forward and reverse supply chain decisions

Stock Management in Hospital Pharmacy using Chance-Constrained Model Predictive Control

One of the most important problems in the pharmacy department of a hospital is stock management. The clinical need for drugs must be satisfied with limited work labor while minimizing the use of economic resources. The complexity of the problem resides in the random nature of the drug demand and the multiple constraints that must be taken into account in every decision. In this article, chance-constrained model predictive control is proposed to deal with this problem. The flexibility of model predictive control allows taking into account explicitly the different objectives and constraints involved in the problem while the use of chance constraints provides a trade-off between conservativeness and efficiency. The solution proposed is assessed to study its implementation in two Spanish hospitals.Junta de Andalucía P12-TIC-240

Advancing Cost-Effective Readiness by Improving the Supply Chain Management of Sparse, Intermittently-Demanded Parts

Many firms generate revenue by successfully operating machines such as welding robots, rental cars, aircraft, hotel rooms, amusement park attractions, etc. It is critical that these revenue-generating machines be operational according to the firm s target or requirement; thus, assuring sustained revenue generation for the firm. Machines can and do fail, and in many cases, restoring the downed machine requires spare part(s), which are typically managed by the supply chain. The scope of this research is on the supply chain management of the very sparse, intermittently-demanded spare parts. These parts are especially difficult to manage because they have little to no lead time demand; thus, modeling via a Poisson process is not viable. The first area of our research develops two new frameworks to improve the supply chain manager s stock policy on these parts. The stock polices are tested via case studies on the A-10C attack aircraft and B1 bomber fleets. Results show the AF could save $10M/year on the A10 and improve support to the B1 without increasing inventory. The second area of our research develops a framework to integrate the supply chain processes that generate these service parts. With the integrated framework, we establish two new forward-looking metrics. We show examples how these forward-looking metrics can advance the supply chain manager s desire to know what proactive decisions to make to improve his/her supply chain for the good of the firm