Capacity Management, Investment, and Hedging: Review and Recent Developments

Jan A. Van Mieghem*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

351 Scopus citations

Abstract

This paper reviews the literature on strategic capacity management concerned with determining the sizes, types, and timing of capacity investments and adjustments under uncertainty. Specific attention is given to recent developments to incorporate multiple decision makers, multiple capacity types, hedging, and risk aversion. Capacity is a measure of processing abilities and limitations and is represented as a vector of stocks of various processing resources, while investment is the change of capacity and includes expansion and contraction. After discussing general issues in capacity investment problems, the paper reviews models of capacity investment under uncertainty in three settings: The first reviews optimal capacity investment by single and multiple risk-neutral decision makers in a stationary environment where capacity remains constant. Allowing for multiple capacity types, the associated optimal capacity portfolio specifies the amounts and locations of safety capacity in a processing network. Its key feature is that it is unbalanced; i.e., regardless of how uncertainties are realized, one typically will never fully utilize all capacities. The second setting reviews the adjustment of capacity over time and the structure of optimal investment dynamics. The paper ends by reviewing how to incorporate risk aversion in capacity investment and contrasts hedging strategies involving financial versus operational means.

Original languageEnglish (US)
Pages (from-to)269-302
Number of pages34
JournalManufacturing and Service Operations Management
Volume5
Issue number4
DOIs
StatePublished - 2003

Keywords

  • Capacity
  • Expansion
  • Hedging
  • Investment
  • Mean-Variance
  • Planning
  • Real Options
  • Risk

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research

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