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.
|Keywords||onderdelen, remanufacturing, revenue management, revenues, spare parts inventory|
|JEL||L1, Market Structure, Firm Strategy, and Market Performance (jel), M, Business Administration and Business Economics; Marketing; Accounting (jel), M11, Production Management (jel), Q59, Environmental Economics: Other (jel), R4, Transportation Systems (jel)|
|Publisher||Erasmus Research Institute of Management (ERIM)|
Ferguson, M, Fleischmann, M, & Souza, G.C. (2008). Applying Revenue Management to the Reverse Supply Chain (No. ERS-2008-052-LIS). ERIM report series research in management Erasmus Research Institute of Management. Erasmus Research Institute of Management (ERIM). Retrieved from http://hdl.handle.net/1765/13211