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Drivers of fulfillment performance in mission critical logistics systems: An empirical analysis

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  • Johnson, Andrew
  • Carnovale, Steven
  • Song, Ju Myung
  • Zhao, Yao

Abstract

Logistics systems that involve truncated timelines, where failure to meet such a timeline results in a substantial loss to business, have been coined ‘mission critical logistics’ systems, and their management is quite different from their ‘traditional’ counterparts. Yet, much of the research in this space has operated under the assumption that the methods, approaches, and tactics are equally applicable to both mission critical, and traditional logistics systems. Is this necessarily so? Most literature addresses functional issues such as inventory or process management but does not provide an understanding of the drivers of fulfillment performance in mission critical systems. This is a critical gap in the literature. Partnering with the Defense Logistics Agency (DLA) and the United States Navy, we studied a mission critical logistics system in order to understand the drivers of these logistics systems and their performance. We utilize a unique dataset consisting of inventory fulfillment and ordering, as well as part criticality and location. Overall the results indicate that inventory management is a much more dynamic process in mission critical logistics systems, whereby flexibility is crucial, and designation of part categories and essentiality can be the determining factor for whether or not the mission fails.

Suggested Citation

  • Johnson, Andrew & Carnovale, Steven & Song, Ju Myung & Zhao, Yao, 2021. "Drivers of fulfillment performance in mission critical logistics systems: An empirical analysis," International Journal of Production Economics, Elsevier, vol. 237(C).
    • Handle: RePEc:eee:proeco:v:237:y:2021:i:c:s0925527321001146
    DOI: 10.1016/j.ijpe.2021.108138
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    as
    1. Harvey M. Wagner, 2002. "And Then There Were None," Operations Research, INFORMS, vol. 50(1), pages 217-226, February.
    2. Kumar, Kunal & Aouam, Tarik, 2018. "Integrated lot sizing and safety stock placement in a network of production facilities," International Journal of Production Economics, Elsevier, vol. 195(C), pages 74-95.
    3. Snyder, Ralph, 2002. "Forecasting sales of slow and fast moving inventories," European Journal of Operational Research, Elsevier, vol. 140(3), pages 684-699, August.
    4. Anil Kukreja & Charles P. Schmidt & David M. Miller, 2001. "Stocking Decisions for Low-Usage Items in a Multilocation Inventory System," Management Science, INFORMS, vol. 47(10), pages 1371-1383, October.
    5. David Simchi-Levi & Yao Zhao, 2012. "Performance Evaluation of Stochastic Multi-Echelon Inventory Systems: A Survey," Advances in Operations Research, Hindawi, vol. 2012, pages 1-34, December.
    6. A A Syntetos & J E Boylan & J D Croston, 2005. "On the categorization of demand patterns," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(5), pages 495-503, May.
    7. George Tagaras & Morris A. Cohen, 1992. "Pooling in Two-Location Inventory Systems with Non-Negligible Replenishment Lead Times," Management Science, INFORMS, vol. 38(8), pages 1067-1083, August.
    8. Zahraei, Seyed Mehdi & Teo, Chee-Chong, 2018. "Optimizing a recover-and-assemble remanufacturing system with production smoothing," International Journal of Production Economics, Elsevier, vol. 197(C), pages 330-341.
    9. Vinayak Deshpande & Morris A. Cohen & Karen Donohue, 2003. "An Empirical Study of Service Differentiation for Weapon System Service Parts," Operations Research, INFORMS, vol. 51(4), pages 518-530, August.
    10. Freedman, David A., 2006. "On The So-Called "Huber-Sandwich Estimator" and "Robust Standard Errors"," The American Statistician, American Statistical Association, vol. 60, pages 299-302, November.
    11. Xu, Jiuping & Li, Bin & Wu, Desheng, 2009. "Rough data envelopment analysis and its application to supply chain performance evaluation," International Journal of Production Economics, Elsevier, vol. 122(2), pages 628-638, December.
    12. Lima-Junior, Francisco Rodrigues & Carpinetti, Luiz Cesar Ribeiro, 2019. "Predicting supply chain performance based on SCOR® metrics and multilayer perceptron neural networks," International Journal of Production Economics, Elsevier, vol. 212(C), pages 19-38.
    13. Garvey, Myles D. & Carnovale, Steven, 2020. "The rippled newsvendor: A new inventory framework for modeling supply chain risk severity in the presence of risk propagation," International Journal of Production Economics, Elsevier, vol. 228(C).
    14. John Pencavel, 2014. "The Changing Size Distribution of U.S. Trade Unions and its Description by Pareto's Distribution," ILR Review, Cornell University, ILR School, vol. 67(1), pages 138-170, January.
    15. Van Horenbeek, Adriaan & Buré, Jasmine & Cattrysse, Dirk & Pintelon, Liliane & Vansteenwegen, Pieter, 2013. "Joint maintenance and inventory optimization systems: A review," International Journal of Production Economics, Elsevier, vol. 143(2), pages 499-508.
    16. Dissanayake, C. Kalpani & Cross, Jennifer A., 2018. "Systematic mechanism for identifying the relative impact of supply chain performance areas on the overall supply chain performance using SCOR model and SEM," International Journal of Production Economics, Elsevier, vol. 201(C), pages 102-115.
    17. Grace Hua, N. & Willems, Sean P., 2016. "Analytical insights into two-stage serial line supply chain safety stock," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 107-112.
    18. Kennedy, W. J. & Wayne Patterson, J. & Fredendall, Lawrence D., 2002. "An overview of recent literature on spare parts inventories," International Journal of Production Economics, Elsevier, vol. 76(2), pages 201-215, March.
    19. Kranenburg, A.A. & van Houtum, G.J., 2009. "A new partial pooling structure for spare parts networks," European Journal of Operational Research, Elsevier, vol. 199(3), pages 908-921, December.
    20. Wang, Wenbin & Syntetos, Aris A., 2011. "Spare parts demand: Linking forecasting to equipment maintenance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1194-1209.
    21. Teunter, Ruud H. & Syntetos, Aris A. & Zied Babai, M., 2011. "Intermittent demand: Linking forecasting to inventory obsolescence," European Journal of Operational Research, Elsevier, vol. 214(3), pages 606-615, November.
    22. Acar, Yavuz & Atadeniz, Sukran Nilvana, 2015. "Comparison of integrated and local planning approaches for the supply network of a globally-dispersed enterprise," International Journal of Production Economics, Elsevier, vol. 167(C), pages 204-219.
    23. Hald, Kim Sundtoft & Mouritsen, Jan, 2018. "The evolution of performance measurement systems in a supply chain: A longitudinal case study on the role of interorganisational factors," International Journal of Production Economics, Elsevier, vol. 205(C), pages 256-271.
    24. Morris Cohen & Pasumarti V. Kamesam & Paul Kleindorfer & Hau Lee & Armen Tekerian, 1990. "Optimizer: IBM's Multi-Echelon Inventory System for Managing Service Logistics," Interfaces, INFORMS, vol. 20(1), pages 65-82, February.
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