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Note--Commonality Strategies: Value Drivers and Equivalence with Flexible Capacity and Inventory Substitution

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  • Jan A. Van Mieghem

    (Kellogg School of Management, Northwestern University, Evanston, Illinois 60208)

Abstract

Commonality strategies assemble different products from at least one common component and one other product-specific component. The distinguishing feature of commonality, i.e., the presence of dedicated components to be assembled with a common component, is shown to be mathematically inconsequential in the sense that the unified commonality problem for two products can be reduced to an equivalent substitution flexibility problem without those dedicated components. This significant simplification provides the first general, closed-form condition for commonality adoption and identifies its value drivers. Commonality is optimal even for perfectly correlated demands if products have sufficiently different margins. This introduces the "revenue-maximization option" of commonality as a second benefit that is independent of the traditional risk-pooling benefit. "Pure commonality" strategies are never optimal unless complexity costs are introduced. Dual sourcing, externalities, and operational hedging features of commonality are discussed.

Suggested Citation

  • Jan A. Van Mieghem, 2004. "Note--Commonality Strategies: Value Drivers and Equivalence with Flexible Capacity and Inventory Substitution," Management Science, INFORMS, vol. 50(3), pages 419-424, March.
  • Handle: RePEc:inm:ormnsc:v:50:y:2004:i:3:p:419-424
    DOI: 10.1287/mnsc.1030.0197
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    References listed on IDEAS

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    Cited by:

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    4. Jiri Chod & David Pyke & Nils Rudi, 2010. "The Value of Flexibility in Make-to-Order Systems: The Effect of Demand Correlation," Operations Research, INFORMS, vol. 58(4-part-1), pages 834-848, August.
    5. Ebru K. Bish & Qiong Wang, 2004. "Optimal Investment Strategies for Flexible Resources, Considering Pricing and Correlated Demands," Operations Research, INFORMS, vol. 52(6), pages 954-964, December.
    6. Kostas Bimpikis & Mihalis G. Markakis, 2016. "Inventory Pooling Under Heavy-Tailed Demand," Management Science, INFORMS, vol. 62(6), pages 1800-1813, June.
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    8. Brian Tomlin & Yimin Wang, 2008. "Pricing and Operational Recourse in Coproduction Systems," Management Science, INFORMS, vol. 54(3), pages 522-537, March.
    9. Atan, Zümbül & Ahmadi, Taher & Stegehuis, Clara & Kok, Ton de & Adan, Ivo, 2017. "Assemble-to-order systems: A review," European Journal of Operational Research, Elsevier, vol. 261(3), pages 866-879.
    10. Transchel, Sandra, 2017. "Inventory management under price-based and stockout-based substitution," European Journal of Operational Research, Elsevier, vol. 262(3), pages 996-1008.
    11. Fernando Bernstein & Gregory A. DeCroix & Yulan Wang, 2011. "The Impact of Demand Aggregation Through Delayed Component Allocation in an Assemble-to-Order System," Management Science, INFORMS, vol. 57(6), pages 1154-1171, June.
    12. Manu Goyal & Serguei Netessine, 2011. "Volume Flexibility, Product Flexibility, or Both: The Role of Demand Correlation and Product Substitution," Manufacturing & Service Operations Management, INFORMS, vol. 13(2), pages 180-193, March.
    13. Francas, David & Löhndorf, Nils & Minner, Stefan, 2011. "Machine and labor flexibility in manufacturing networks," International Journal of Production Economics, Elsevier, vol. 131(1), pages 165-174, May.
    14. Hekimoğlu, Mustafa & Scheller-Wolf, Alan, 2023. "Dual sourcing models with stock-out dependent substitution," European Journal of Operational Research, Elsevier, vol. 311(2), pages 472-485.
    15. Lingxiu Dong & Panos Kouvelis & Ping Su, 2010. "Global Facility Network Design with Transshipment and Responsive Pricing," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 278-298, February.
    16. Aydin Alptekinoglu & Arunava Banerjee & Anand Paul & Nikhil Jain, 2013. "Inventory Pooling to Deliver Differentiated Service," Manufacturing & Service Operations Management, INFORMS, vol. 15(1), pages 33-44, September.
    17. Hsieh, Chung-Chi & Wu, Cheng-Han, 2009. "Coordinated decisions for substitutable products in a common retailer supply chain," European Journal of Operational Research, Elsevier, vol. 196(1), pages 273-288, July.
    18. Jing-Sheng Song & Yao Zhao, 2009. "The Value of Component Commonality in a Dynamic Inventory System with Lead Times," Manufacturing & Service Operations Management, INFORMS, vol. 11(3), pages 493-508, March.
    19. Achal Bassamboo & Ramandeep S. Randhawa & Jan A. Van Mieghem, 2010. "Optimal Flexibility Configurations in Newsvendor Networks: Going Beyond Chaining and Pairing," Management Science, INFORMS, vol. 56(8), pages 1285-1303, August.
    20. Jan A. Van Mieghem, 2007. "Risk Mitigation in Newsvendor Networks: Resource Diversification, Flexibility, Sharing, and Hedging," Management Science, INFORMS, vol. 53(8), pages 1269-1288, August.
    21. Fernando Bernstein & Gregory A. DeCroix & Yulan Wang, 2007. "Incentives and Commonality in a Decentralized Multiproduct Assembly System," Operations Research, INFORMS, vol. 55(4), pages 630-646, August.
    22. Amit Eynan & Meir J. Rosenblatt, 2007. "The impact of component commonality on composite assembly policies," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(6), pages 615-622, September.
    23. Santiago Gallino & Antonio Moreno & Ioannis Stamatopoulos, 2017. "Channel Integration, Sales Dispersion, and Inventory Management," Management Science, INFORMS, vol. 63(9), pages 2813-2831, September.
    24. Yangyang Peng & Xiaolin Xu & Xue Liang & Weili Xue, 2020. "Mismatch risk allocation in a coproduct supply chain," Annals of Operations Research, Springer, vol. 291(1), pages 707-730, August.
    25. Kranenburg, A.A. & Van Houtum, G.J., 2007. "Effect of commonality on spare parts provisioning costs for capital goods," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 221-227, July.

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