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Managing Broader Product Lines through Delayed Differentiation Using Vanilla Boxes

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Author Info

  • Jayashankar M. Swaminathan

    (Walter A. Haas School of Business, University of California, Berkeley, California 94720)

  • Sridhar R. Tayur

    (GSIA, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

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    Abstract

    In an attempt to reduce cost while maintaining good customer service, some of the leading manufacturers in the computer industry are delaying product differentiation (by exploiting component commonality) while managing broader product lines. In an environment where demands are stochastic, it seems a good strategy to store inventory in the form of semi-finished products (vanilla boxes) that can serve more than one final product. However, finding the optimal configurations and inventory levels of the vanilla boxes could be a challenging task. In this paper, we model the above problem as a two-stage integer program with recourse. By utilizing structural decomposition of the problem and (sub)gradient derivative methods, we provide an effective solution procedure. A special case, a variant, and several extensions are also discussed. In our computational section, we utilize our model to study several new research issues. We provide insights on the effect of demand variance, correlation, and capacity limitations on the optimal configuration and inventory levels of vanilla boxes and the performance of a vanilla assembly process. In addition, we compare the performance of the vanilla assembly process to make-to-stock and assemble-to-order processes and provide managerial insights on the conditions under which one might be better than the others. Finally, we discuss the characteristics of an IBM product line (which motivated this work) and the effectiveness of a heuristic tailored for that application.

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    File URL: http://dx.doi.org/10.1287/mnsc.44.12.S161
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 44 (1998)
    Issue (Month): 12-Part-2 (December)
    Pages: S161-S172

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    Handle: RePEc:inm:ormnsc:v:44:y:1998:i:12-part-2:p:s161-s172

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    Related research

    Keywords: Stochastic Multi-Product Assembly Systems; Product Variety; Component Commonality; Demand Correlation; Inventory Management; Stochastic Integer Programs;

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    Citations

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    Cited by:
    1. Xiao, Yongbo & Chen, Jian & Lee, Chung-Yee, 2010. "Optimal decisions for assemble-to-order systems with uncertain assembly capacity," International Journal of Production Economics, Elsevier, vol. 123(1), pages 155-165, January.
    2. Tibben-Lembke, Ronald S. & Bassok, Yehuda, 2005. "An inventory model for delayed customization: A hybrid approach," European Journal of Operational Research, Elsevier, vol. 165(3), pages 748-764, September.
    3. Wong, Hartanto & Potter, Andrew & Naim, Mohamed, 2011. "Evaluation of postponement in the soluble coffee supply chain: A case study," International Journal of Production Economics, Elsevier, vol. 131(1), pages 355-364, May.
    4. Almehdawe, Eman & Jewkes, Elizabeth, 2013. "Performance analysis and optimization of hybrid manufacturing systems under a batch ordering policy," International Journal of Production Economics, Elsevier, vol. 144(1), pages 200-208.
    5. Brabazon, Philip G. & MacCarthy, Bart, 2006. "Fundamental behaviour of virtual-build-to-order systems," International Journal of Production Economics, Elsevier, vol. 104(2), pages 514-524, December.
    6. Tang, Dong, 2011. "Managing finished-goods inventory under capacitated delayed differentiation," Omega, Elsevier, vol. 39(5), pages 481-492, October.
    7. Vliegen, I.M.H. & Kleingeld, P.A.M. & van Houtum, G.J., 2010. "Separate tools or tool kits: An exploratory study of engineers' preferences," International Journal of Production Economics, Elsevier, vol. 125(1), pages 173-184, May.
    8. Droge, Cornelia & Vickery, Shawnee K. & Jacobs, Mark A., 2012. "Does supply chain integration mediate the relationships between product/process strategy and service performance? An empirical study," International Journal of Production Economics, Elsevier, vol. 137(2), pages 250-262.
    9. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    10. Reimann, Marc, 2012. "Accurate response by postponement," European Journal of Operational Research, Elsevier, vol. 220(3), pages 619-628.
    11. Hai Che & Chakravarthi Narasimhan & V. Padmanabhan, 2010. "Leveraging uncertainty through backorder," Quantitative Marketing and Economics, Springer, vol. 8(3), pages 365-392, September.
    12. Agard, Bruno & Penz, Bernard, 2009. "A simulated annealing method based on a clustering approach to determine bills of materials for a large product family," International Journal of Production Economics, Elsevier, vol. 117(2), pages 389-401, February.
    13. Langenberg, Kerstin U. & Seifert, Ralf W. & Tancrez, Jean-S├ębastien, 2012. "Aligning supply chain portfolios with product portfolios," International Journal of Production Economics, Elsevier, vol. 135(1), pages 500-513.

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