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An integrated production and inventory model to dampen upstream demand variability in the supply chain

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  • Boute, Robert N.
  • Disney, Stephen M.
  • Lambrecht, Marc R.
  • Van Houdt, Benny

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  • Boute, Robert N. & Disney, Stephen M. & Lambrecht, Marc R. & Van Houdt, Benny, 2007. "An integrated production and inventory model to dampen upstream demand variability in the supply chain," European Journal of Operational Research, Elsevier, vol. 178(1), pages 121-142, April.
  • Handle: RePEc:eee:ejores:v:178:y:2007:i:1:p:121-142
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    References listed on IDEAS

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    1. Blanchard, Olivier J, 1983. "The Production and Inventory Behavior of the American Automobile Industry," Journal of Political Economy, University of Chicago Press, vol. 91(3), pages 365-400, June.
    2. Fair, Ray C., 1989. "The production-smoothing model is alive and well," Journal of Monetary Economics, Elsevier, vol. 24(3), pages 353-370, November.
    3. Jing-Sheng Song & David D. Yao, 2002. "Performance Analysis and Optimization of Assemble-to-Order Systems with Random Lead Times," Operations Research, INFORMS, vol. 50(5), pages 889-903, October.
    4. Miron, Jeffrey A & Zeldes, Stephen P, 1988. "Seasonality, Cost Shocks, and the Production Smoothing Models of Inventories," Econometrica, Econometric Society, vol. 56(4), pages 877-908, July.
    5. Alan S. Blinder, 1986. "Can the Production Smoothing Model of Inventory Behavior be Saved?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 101(3), pages 431-453.
    6. Donald S. Allen, 1997. "Do inventories moderate fluctuations in output?," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 39-50.
    7. Jing-Sheng Song & Paul H. Zipkin, 1996. "The Joint Effect of Leadtime Variance and Lot Size in a Parallel Processing Environment," Management Science, INFORMS, vol. 42(9), pages 1352-1363, September.
    8. Dejonckheere, J. & Disney, S. M. & Lambrecht, M. R. & Towill, D. R., 2003. "Measuring and avoiding the bullwhip effect: A control theoretic approach," European Journal of Operational Research, Elsevier, vol. 147(3), pages 567-590, June.
    9. Stephen C. Graves, 1999. "A Single-Item Inventory Model for a Nonstationary Demand Process," Manufacturing & Service Operations Management, INFORMS, vol. 1(1), pages 50-61.
    10. Warburton, Roger D. H., 2004. "An exact analytical solution to the production inventory control problem," International Journal of Production Economics, Elsevier, vol. 92(1), pages 81-96, November.
    11. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    12. West, Kenneth D, 1986. "A Variance Bounds Test of the Linear Quadratic Inventory Model," Journal of Political Economy, University of Chicago Press, vol. 94(2), pages 374-401, April.
    13. Yingdong Lu & Jing-Sheng Song & David D. Yao, 2003. "Order Fill Rate, Leadtime Variability, and Advance Demand Information in an Assemble-to-Order System," Operations Research, INFORMS, vol. 51(2), pages 292-308, April.
    14. Frank Chen & Zvi Drezner & Jennifer K. Ryan & David Simchi-Levi, 2000. "Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information," Management Science, INFORMS, vol. 46(3), pages 436-443, March.
    15. Krane, Spencer D & Braun, Stephen N, 1991. "Production Smoothing Evidence from Physical-Product Data," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 558-581, June.
    16. Arthur F. Veinott, Jr., 1966. "The Status of Mathematical Inventory Theory," Management Science, INFORMS, vol. 12(11), pages 745-777, July.
    17. Stephen C. Graves, 1999. "Addendum to "A Single-Item Inventory Model for a Nonstationary Demand Process"," Manufacturing & Service Operations Management, INFORMS, vol. 1(2), pages 174-174.
    18. Disney, S. M. & Towill, D. R., 2003. "On the bullwhip and inventory variance produced by an ordering policy," Omega, Elsevier, vol. 31(3), pages 157-167, June.
    19. Herbert J. Vassian, 1955. "Application of Discrete Variable Servo Theory to Inventory Control," Operations Research, INFORMS, vol. 3(3), pages 272-282, August.
    20. Anantaram Balakrishnan & Joseph Geunes & Michael S. Pangburn, 2004. "Coordinating Supply Chains by Controlling Upstream Variability Propagation," Manufacturing & Service Operations Management, INFORMS, vol. 6(2), pages 163-183, July.
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    Cited by:

    1. Cannella, S. & Ciancimino, E. & Ashayeri, J., 2010. "On the Significance of Demand and Inventory Smoothing Interventions in Supply Chain," Other publications TiSEM 03de2e58-4ef5-40a3-96e1-6, Tilburg University, School of Economics and Management.
    2. Dejian Yu & Zhaoping Yan, 2021. "Knowledge diffusion of supply chain bullwhip effect: main path analysis and science mapping analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8491-8515, October.
    3. Hum, Sin-Hoon & Parlar, Mahmut & Zhou, Yun, 2018. "Measurement and optimization of responsiveness in supply chain networks with queueing structures," European Journal of Operational Research, Elsevier, vol. 264(1), pages 106-118.
    4. Kumar, Kunal & Aouam, Tarik, 2019. "Extending the strategic safety stock placement model to consider tactical production smoothing," European Journal of Operational Research, Elsevier, vol. 279(2), pages 429-448.
    5. Kunnumkal, Sumit & Topaloglu, Huseyin, 2008. "Price discounts in exchange for reduced customer demand variability and applications to advance demand information acquisition," International Journal of Production Economics, Elsevier, vol. 111(2), pages 543-561, February.
    6. Herman de Kwaatsteniet, 2011. "Demand Variability in Supply Chains: The Influence of Global developments and Globalization on the Local Dutch Steel Industry," Working Papers 2011/32, Maastricht School of Management.
    7. Chaharsooghi, S. Kamal & Heydari, Jafar, 2010. "Supply chain coordination for the joint determination of order quantity and reorder point using credit option," European Journal of Operational Research, Elsevier, vol. 204(1), pages 86-95, July.
    8. Hoberg, Kai & Thonemann, Ulrich W., 2014. "Modeling and analyzing information delays in supply chains using transfer functions," International Journal of Production Economics, Elsevier, vol. 156(C), pages 132-145.
    9. Reiner, Gerald & Fichtinger, Johannes, 2009. "Demand forecasting for supply processes in consideration of pricing and market information," International Journal of Production Economics, Elsevier, vol. 118(1), pages 55-62, March.
    10. Cannella, S. & Ciancimino, E. & Ashayeri, J., 2010. "On the Significance of Demand and Inventory Smoothing Interventions in Supply Chain," Discussion Paper 2010-126, Tilburg University, Center for Economic Research.
    11. Ciancimino, Elena & Cannella, Salvatore & Bruccoleri, Manfredi & Framinan, Jose M., 2012. "On the Bullwhip Avoidance Phase: The Synchronised Supply Chain," European Journal of Operational Research, Elsevier, vol. 221(1), pages 49-63.
    12. Hoque, M.A., 2008. "Synchronization in the single-manufacturer multi-buyer integrated inventory supply chain," European Journal of Operational Research, Elsevier, vol. 188(3), pages 811-825, August.
    13. Noblesse, Ann M. & Boute, Robert N. & Lambrecht, Marc R. & Van Houdt, Benny, 2014. "Lot sizing and lead time decisions in production/inventory systems," International Journal of Production Economics, Elsevier, vol. 155(C), pages 351-360.
    14. Özelkan, Ertunga C. & Lim, Churlzu & Adnan, Ziaul Haq, 2018. "Conditions of reverse bullwhip effect in pricing under joint decision of replenishment and pricing," International Journal of Production Economics, Elsevier, vol. 200(C), pages 207-223.
    15. Hoque, M.A., 2011. "An optimal solution technique to the single-vendor multi-buyer integrated inventory supply chain by incorporating some realistic factors," European Journal of Operational Research, Elsevier, vol. 215(1), pages 80-88, November.
    16. Gu, Qiannong & Jitpaipoon, Thawatchai & Yang, Jie, 2017. "The impact of information integration on financial performance: A knowledge-based view," International Journal of Production Economics, Elsevier, vol. 191(C), pages 221-232.
    17. Ciancimino, Elena & Cannella, Salvatore & Canca Ortiz, José David & Framiñán Torres, José Manuel, 2009. "Análisis multinivel de cadenas de suministros: dos técnicas de resolución del efecto bullwhip // Supply Chain Multi-level Analysis: Two Bullwhip Dampening Approaches," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 8(1), pages 7-28, December.
    18. Yu, Dejian & Yan, Zhaoping, 2023. "Main path analysis considering citation structure and content: Case studies in different domains," Journal of Informetrics, Elsevier, vol. 17(1).
    19. Mervegül Kirci & Olov Isaksson & Ralf Seifert, 2022. "Managing Perishability in the Fruit and Vegetable Supply Chains," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    20. Wang, Xun & Disney, Stephen M., 2016. "The bullwhip effect: Progress, trends and directions," European Journal of Operational Research, Elsevier, vol. 250(3), pages 691-701.
    21. Noblesse, Ann M. & Boute, Robert N. & Lambrecht, Marc R. & Van Houdt, Benny, 2014. "Characterizing order processes of continuous review (s,S) and (r,nQ) policies," European Journal of Operational Research, Elsevier, vol. 236(2), pages 534-547.

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