Inventory Pooling to Deliver Differentiated Service

Aydin Alptekinoglu (), Arunava Banerjee (), Anand Paul () and Nikhil Jain ()
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Aydin Alptekinoglu: Cox School of Business, Southern Methodist University, Dallas, Texas 75275
Arunava Banerjee: Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida 32611
Anand Paul: Warrington College of Business Administration, University of Florida, Gainesville, Florida 32611
Nikhil Jain: Servigistics India, Gurgaon, Haryana 122001, India

Manufacturing & Service Operations Management, 2013, vol. 15, issue 1, 33-44

Abstract: Inventory pooling is at the root of many celebrated ideas in operations management. Postponement, component commonality, and resource flexibility are some examples. Motivated by our experience in the aftermarket services industry, we propose a model of inventory pooling to meet differentiated service levels for multiple customers. Our central research question is the following: What are the minimum inventory level and optimal allocation policy when a pool of inventory is used in a single period to satisfy individual service levels for multiple customers? We measure service by the probability of fulfilling a customer's entire demand immediately from stock. We characterize the optimal solution in several allocation policy classes; provide some structural results, formulas, and bounds; and also make detailed interpolicy comparisons. We show that the pooling benefit is always strictly positive, even when there are an arbitrary number of customers with perfectly positively correlated demands.

Keywords: inventory pooling; type 1 service level; inventory allocation policy; aftermarket services; spare parts; pooling benefit; demand correlation (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:15:y:2013:i:1:p:33-44

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