Dual Sourcing and Smoothing Under Nonstationary Demand Time Series: Reshoring with SpeedFactories

Robert N. Boute (), Stephen M. Disney (), Joren Gijsbrechts () and Jan A. Van Mieghem ()
Additional contact information
Robert N. Boute: Research Center for Operations Management, KU Leuven, 3000 Leuven, Belgium; Technology & Operations Management Area, Vlerick Business School, 3000 Leuven, Belgium
Stephen M. Disney: Centre for Simulation, Analytics and Modelling, University of Exeter Business School, Exeter, EX4 4PU, United Kingdom
Joren Gijsbrechts: Católica Lisbon School of Business & Economics, Lisbon, 1649-023, Portugal
Jan A. Van Mieghem: Kellogg School of Management, Northwestern University, Evanston, Illinois 60208

Management Science, 2022, vol. 68, issue 2, 1039-1057

Abstract: We investigate near-shoring a small part of the global production to local SpeedFactories that serve only the variable demand. The short lead time of the responsive SpeedFactory reduces the risk of making large volumes in advance, yet it does not involve a complete reshoring of demand. Using a break-even analysis, we investigate the lead time, demand, and cost characteristics that make dual sourcing with a SpeedFactory desirable compared with complete off-shoring. Our analysis uses a linear generalization of the celebrated order-up-to inventory policy to settings where capacity costs exist. The policy allows for order smoothing to reduce capacity costs and performs well relative to the (unknown) optimal policy. We highlight the significant impact of auto-correlated and nonstationary demand series, which are prevalent in practice yet challenging to analyze, on the economic benefit of reshoring. Methodologically, we adopt a linear policy and normally distributed demand and use Z –transforms to present exact analyses.

Keywords: inventory management; order smoothing; order-up-to policy; auto-regressive demand; integrated moving average demand; global outsourcing; dual sourcing; z -transform (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.2020.3951 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:68:y:2022:i:2:p:1039-1057

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().