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An ARIMA Supply Chain Model

Citations

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Cited by:

  1. M M Ali & J E Boylan, 2011. "Feasibility principles for Downstream Demand Inference in supply chains," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 474-482, March.
  2. Gérard P. Cachon & Taylor Randall & Glen M. Schmidt, 2007. "In Search of the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 457-479, April.
  3. Isaksson, Olov H.D. & Seifert, Ralf W., 2016. "Quantifying the bullwhip effect using two-echelon data: A cross-industry empirical investigation," International Journal of Production Economics, Elsevier, vol. 171(P3), pages 311-320.
  4. Wang, Zhaodong & Wang, Xin & Ouyang, Yanfeng, 2015. "Bounded growth of the bullwhip effect under a class of nonlinear ordering policies," European Journal of Operational Research, Elsevier, vol. 247(1), pages 72-82.
  5. Li Chen & Hau L. Lee, 2009. "Information Sharing and Order Variability Control Under a Generalized Demand Model," Management Science, INFORMS, vol. 55(5), pages 781-797, May.
  6. Rupesh Kumar Pati, 2014. "Modelling Bullwhip Effect in a Closed Loop Supply Chain with ARMA Demand," IIM Kozhikode Society & Management Review, , vol. 3(2), pages 149-164, July.
  7. Lai, Richard, 2005. "Bullwhip in a Spanish Shop," MPRA Paper 4758, University Library of Munich, Germany.
  8. Ma, Yungao & Wang, Nengmin & He, Zhengwen & Lu, Jizhou & Liang, Huigang, 2015. "Analysis of the bullwhip effect in two parallel supply chains with interacting price-sensitive demands," European Journal of Operational Research, Elsevier, vol. 243(3), pages 815-825.
  9. Yelland, Phillip M., 2010. "Bayesian forecasting of parts demand," International Journal of Forecasting, Elsevier, vol. 26(2), pages 374-396, April.
  10. Babai, Zied & Boylan, John E. & Kolassa, Stephan & Nikolopoulos, Konstantinos, 2016. "Supply chain forecasting: Theory, practice, their gap and the futureAuthor-Name: Syntetos, Aris A," European Journal of Operational Research, Elsevier, vol. 252(1), pages 1-26.
  11. Hosoda, Takamichi & Disney, Stephen M., 2009. "Impact of market demand mis-specification on a two-level supply chain," International Journal of Production Economics, Elsevier, vol. 121(2), pages 739-751, October.
  12. Xuhan Tian & Junmin (Jim) Shi & Xiangtong Qi, 2022. "Stochastic Sequential Allocations for Creative Crowdsourcing," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 697-714, February.
  13. Ruomeng Cui & Gad Allon & Achal Bassamboo & Jan A. Van Mieghem, 2015. "Information Sharing in Supply Chains: An Empirical and Theoretical Valuation," Management Science, INFORMS, vol. 61(11), pages 2803-2824, November.
  14. Fernando Rojas & Peter Wanke & Víctor Leiva & Mauricio Huerta & Carlos Martin-Barreiro, 2022. "Modeling Inventory Cost Savings and Supply Chain Success Factors: A Hybrid Robust Compromise Multi-Criteria Approach," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
  15. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  16. Yanfeng Ouyang & Carlos Daganzo, 2006. "Characterization of the Bullwhip Effect in Linear, Time-Invariant Supply Chains: Some Formulae and Tests," Management Science, INFORMS, vol. 52(10), pages 1544-1556, October.
  17. Agrawal, Sunil & Sengupta, Raghu Nandan & Shanker, Kripa, 2009. "Impact of information sharing and lead time on bullwhip effect and on-hand inventory," European Journal of Operational Research, Elsevier, vol. 192(2), pages 576-593, January.
  18. Zhu, Siying & Jia, Shuai & Sun, Qinghe & Meng, Qiang, 2023. "An empirical study of China–Singapore International Land–Sea Trade Corridor: Analysis from supply and demand sides," Transport Policy, Elsevier, vol. 135(C), pages 1-10.
  19. Fernando Rojas & Víctor Leiva & Peter Wanke & Camilo Lillo & Jimena Pascual, 2019. "Modeling lot-size with time-dependent demand based on stochastic programming and case study of drug supply in Chile," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-24, March.
  20. Chiang, Chung-Yean & Lin, Winston T. & Suresh, Nallan C., 2016. "An empirically-simulated investigation of the impact of demand forecasting on the bullwhip effect: Evidence from U.S. auto industry," International Journal of Production Economics, Elsevier, vol. 177(C), pages 53-65.
  21. Zhang, Xiaolong & Burke, Gerard J., 2011. "Analysis of compound bullwhip effect causes," European Journal of Operational Research, Elsevier, vol. 210(3), pages 514-526, May.
  22. Gaalman, Gerard & Disney, Stephen M., 2009. "On bullwhip in a family of order-up-to policies with ARMA(2,2) demand and arbitrary lead-times," International Journal of Production Economics, Elsevier, vol. 121(2), pages 454-463, October.
  23. Sodhi, ManMohan S. & Tang, Christopher S., 2011. "The incremental bullwhip effect of operational deviations in an arborescent supply chain with requirements planning," European Journal of Operational Research, Elsevier, vol. 215(2), pages 374-382, December.
  24. Babai, M.Z. & Boylan, J.E. & Syntetos, A.A. & Ali, M.M., 2016. "Reduction of the value of information sharing as demand becomes strongly auto-correlated," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 130-135.
  25. Gaalman, Gerard & Disney, Stephen M. & Wang, Xun, 2022. "When bullwhip increases in the lead time: An eigenvalue analysis of ARMA demand," International Journal of Production Economics, Elsevier, vol. 250(C).
  26. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
  27. Avci, Mualla Gonca & Selim, Hasan, 2018. "A multi-objective simulation-based optimization approach for inventory replenishment problem with premium freights in convergent supply chains," Omega, Elsevier, vol. 80(C), pages 153-165.
  28. Pournader, Mehrdokht & Ghaderi, Hadi & Hassanzadegan, Amir & Fahimnia, Behnam, 2021. "Artificial intelligence applications in supply chain management," International Journal of Production Economics, Elsevier, vol. 241(C).
  29. Omar, Haytham & Klibi, Walid & Babai, M. Zied & Ducq, Yves, 2023. "Basket data-driven approach for omnichannel demand forecasting," International Journal of Production Economics, Elsevier, vol. 257(C).
  30. Gaalman, Gerard & Disney, Stephen M., 2006. "State space investigation of the bullwhip problem with ARMA(1,1) demand processes," International Journal of Production Economics, Elsevier, vol. 104(2), pages 327-339, December.
  31. Mila Nambiar & David Simchi‐Levi & He Wang, 2021. "Dynamic Inventory Allocation with Demand Learning for Seasonal Goods," Production and Operations Management, Production and Operations Management Society, vol. 30(3), pages 750-765, March.
  32. Fernando Rojas, 2017. "A methodology for stochastic inventory modelling with ARMA triangular distribution for new products," Cogent Business & Management, Taylor & Francis Journals, vol. 4(1), pages 1270706-127, January.
  33. 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.
  34. Li Chen & Wei Luo & Kevin Shang, 2017. "Measuring the Bullwhip Effect: Discrepancy and Alignment Between Information and Material Flows," Manufacturing & Service Operations Management, INFORMS, vol. 19(1), pages 36-51, February.
  35. Springer, Mark & Kim, Ilhyung, 2010. "Managing the order pipeline to reduce supply chain volatility," European Journal of Operational Research, Elsevier, vol. 203(2), pages 380-392, June.
  36. Tliche, Y. & Taghipour, A. & Canel-Depitre, B., 2019. "Downstream Demand Inference in decentralized supply chains," European Journal of Operational Research, Elsevier, vol. 274(1), pages 65-77.
  37. Ali, Mohammad M. & Boylan, John E. & Syntetos, Aris A., 2012. "Forecast errors and inventory performance under forecast information sharing," International Journal of Forecasting, Elsevier, vol. 28(4), pages 830-841.
  38. Nagaraja, Chaitra H. & McElroy, Tucker, 2018. "The multivariate bullwhip effect," European Journal of Operational Research, Elsevier, vol. 267(1), pages 96-106.
  39. Ouyang, Yanfeng & Li, Xiaopeng, 2010. "The bullwhip effect in supply chain networks," European Journal of Operational Research, Elsevier, vol. 201(3), pages 799-810, March.
  40. Zhang, Xiaolong, 2007. "Inventory control under temporal demand heteroscedasticity," European Journal of Operational Research, Elsevier, vol. 182(1), pages 127-144, October.
  41. Nagaraja, C.H. & Thavaneswaran, A. & Appadoo, S.S., 2015. "Measuring the bullwhip effect for supply chains with seasonal demand components," European Journal of Operational Research, Elsevier, vol. 242(2), pages 445-454.
  42. QU, Zhan & RAFF, Horst, 2023. "Two-part tariffs, inventory stockpiling, and the bullwhip effect," European Journal of Operational Research, Elsevier, vol. 308(1), pages 201-214.
  43. Tliche, Youssef & Taghipour, Atour & Canel-Depitre, Béatrice, 2020. "An improved forecasting approach to reduce inventory levels in decentralized supply chains," European Journal of Operational Research, Elsevier, vol. 287(2), pages 511-527.
  44. Ali, Mohammad M. & Babai, Mohamed Zied & Boylan, John E. & Syntetos, A.A., 2017. "Supply chain forecasting when information is not shared," European Journal of Operational Research, Elsevier, vol. 260(3), pages 984-994.
  45. Ouyang, Yanfeng & Daganzo, Carlos, 2008. "Robust tests for the bullwhip effect in supply chains with stochastic dynamics," European Journal of Operational Research, Elsevier, vol. 185(1), pages 340-353, February.
  46. Layth C. Alwan & Christian H. Weiß, 2017. "INAR implementation of newsvendor model for serially dependent demand counts," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1085-1099, February.
  47. Zhan Qu & Horst Raff, 2021. "Vertical Contracts in a Supply Chain and the Bullwhip Effect," Management Science, INFORMS, vol. 67(6), pages 3744-3756, June.
  48. Xiaoxin Zhu & Guanghai Zhang & Baiqing Sun, 2019. "A comprehensive literature review of the demand forecasting methods of emergency resources from the perspective of artificial intelligence," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 97(1), pages 65-82, May.
  49. Junhai Ma & Jing Zhang & Liqing Zhu, 2018. "Study of the Bullwhip Effect under Various Forecasting Methods in Electronics Supply Chain with Dual Retailers considering Market Share," Complexity, Hindawi, vol. 2018, pages 1-19, January.
  50. Babai, M.Z. & Ali, M.M. & Boylan, J.E. & Syntetos, A.A., 2013. "Forecasting and inventory performance in a two-stage supply chain with ARIMA(0,1,1) demand: Theory and empirical analysis," International Journal of Production Economics, Elsevier, vol. 143(2), pages 463-471.
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