The effect of information sharing on supply chain stability and the bullwhip effect.

*(English)*Zbl 1121.90366Summary: This paper analyzes the bullwhip effect in multi-stage supply chains operated with linear and time-invariant inventory management policies and shared supply chain information. Such information includes past order sequences and inventory records at all supplier stages. The paper characterizes the stream of orders placed at any stage of the chain when the customer demand process is known and ergodic, and gives an exact formula for the variance of the orders placed. The paper also derives robust analytical conditions, based only on inventory management policies, to predict the presence of the bullwhip effect and bound its magnitude. These results hold independently of the customer demand. The general framework proposed in this paper allows for any inventory replenishment policies, any ways of sharing and utilizing information, and any customer demand processes. It is also shown as a special case that sharing customer demand information across the chain significantly reduces, but does not completely eliminate, the bullwhip effect.

##### MSC:

90B50 | Management decision making, including multiple objectives |

90B05 | Inventory, storage, reservoirs |

##### Keywords:

supply chain management; stability; the bullwhip effect; information sharing; frequency domain analysis##### Software:

DYNAMO
PDF
BibTeX
XML
Cite

\textit{Y. Ouyang}, Eur. J. Oper. Res. 182, No. 3, 1107--1121 (2007; Zbl 1121.90366)

Full Text:
DOI

##### References:

[1] | Aviv, Y., The effect of collaborative forecasting on supply chain performance, Management science, 47, 10, 1326-1343, (2001) · Zbl 1232.90009 |

[2] | Aviv, Y., Gaining benefits from joint forecasting and replenishment processes: the case of auto-correlated demand, Manufacturing and service operations management, 4, 1, 55-74, (2002) |

[3] | Baganha, M.P.; Cohen, M.A., The stabilizing effect of inventory in supply chains, Operations research, 46, 3, 572-583, (1998) |

[4] | Blinder, A.S., Can the production smoothing model of inventory behavior be saved?, Quarterly journal of economics, 101, 431-454, (1986) |

[5] | Boyd, S.; Desoer, C.A., Subharmonic functions and performance bounds on linear time-invariant feedback systems, IMA journal of mathematical control and information, 2, 153-170, (1985) |

[6] | Cachon, G.P.; Fisher, M., Supply chain inventory management and the value of shared information, Management science, 46, 8, 1032-1048, (2000) · Zbl 1232.90028 |

[7] | Chen, F.; Drezner, Z.; Ryan, J.; Simchi-Levi, D., Quantifying the bullwhip effect in a simple supply chain: the impact of forecasting, lead times, and information, Management science, 46, 3, 436-443, (2000) · Zbl 1231.90019 |

[8] | Chen, F.; Ryan, J.; Simchi-Levi, D., The impact of exponential smoothing forecasts on the bullwhip effect, Naval research logistics, 47, 4, 271-286, (2000) · Zbl 0968.90006 |

[9] | Chen, F.R., Echelon reorder points, installation reorder points, and the value of centralized demand information, Management science, 44, 12, 221-234, (1998) · Zbl 1103.90303 |

[10] | Cooke, J.A., The \(30 billion promise, Traffic management, 32, December, 57-59, (1993\) |

[11] | C.F. Daganzo, A theory of supply chains, Institute of Transportation Studies Research Report, UCB-ITS-RR-2001-7, University of California, Berkeley, CA, 2001. |

[12] | Daganzo, C.F., A theory of supply chains, (2003), Springer Heidelberg, Germany · Zbl 1030.90003 |

[13] | Daganzo, C.F., On the stability of supply chains, Operations research, 52, 6, 909-921, (2004) · Zbl 1165.90346 |

[14] | Denardo, E.V.; Tang, C.S., Control of a stochastic production system with estimated parameters, Management science, 43, 1296-1307, (1997) · Zbl 1043.90509 |

[15] | Forrester, J., Industrial dynamics, a major breakthrough for decision makers, Harvard business review, 36, 37-66, (1958) |

[16] | Forrester, J., Industrial dynamics, (1961), MIT Press Cambridge MA |

[17] | Gaur, V.; Giloni, A.; Seshadri, S., Information sharing in a supply chain under ARMA demand, Management science, 51, 6, 961-969, (2005) · Zbl 1232.90049 |

[18] | Gavirneni, S.; Kapuscinski, R.; Tayur, S., Value of information in capacitated supply chains, Management science, 45, 1, 16-24, (1999) · Zbl 1231.90088 |

[19] | Goodwin, J.; Franklin, S., The beer distribution game: using simulation to teach systems thinking, Journal of management development, 13, 8, 7-15, (1994) |

[20] | L. Gong, H. Matsuo, Stabilizing work-in-process and smoothing production in a production system with random yield, Working Paper, Graduate School of Business, University of Texas, Austin 1990. |

[21] | Graves, S., A tactical planning model for a job shop, Operations research, 34, 522-533, (1986) · Zbl 0609.90061 |

[22] | Graves, S., A single item inventory model for a nonstationary demand process, Manufacturing and service operations management, 1, 50-61, (1999) |

[23] | Holt, C.C.; Modigliani, F.; Muth, J.; Simon, H.A., Planning production, inventories and work force, (1960), Prentice Hall Englewood Cliffs, NY |

[24] | Kahn, J., Inventories and the volatility of production, American economic review, 77, 667-679, (1987) |

[25] | Kaminsky, P.; Simchi-Levi, D., The computerized beer game: teaching the value of integrated supply chain management, () |

[26] | Lee, H.L.; Padmanabhan, V.; Whang, S., The bullwhip effect in supply chains, Sloan management review, 38, 3, 93-102, (1997), Spring |

[27] | Lee, H.L.; Padmanabhan, V.; Whang, S., Information distortion in a supply chain: the bullwhip effect, Management science, 43, 4, 546-558, (1997) · Zbl 0888.90047 |

[28] | Lee, H.L.; So, K.C.; Tang, C.S., The value of information sharing in a two level supply chain, Management science, 46, 5, 628-643, (2000) · Zbl 1231.90044 |

[29] | Magee, J.F., Guides to inventory control, Harvard business review, Part II, March-April, 106-116, (1956) |

[30] | Magee, J.F.; Boodman, D., Production planning and inventory control, (1967), McGraw-Hill NY |

[31] | Naish, H.F., Production smoothing in the linear quadratic inventory model, Economic journal, 104, 425, 864-875, (1994) |

[32] | Y. Ouyang, System-level stability and optimality of decentralized supply chains, Ph.D. Dissertation, University of California, Berkeley, 2005. |

[33] | Ouyang, Y.; Daganzo, C.F., Characterization of the bullwhip effect in linear, time-invariant supply chains: some formulae and tests, Management science, 52, 10, 1544-1556, (2006) · Zbl 1232.90082 |

[34] | Y. Ouyang, C.F. Daganzo, Robust tests for the bullwhip effect in supply chains with stochastic dynamics, European Journal of Operational Research, in press, doi:10.1016/j.ejor.2006.10.046. · Zbl 1137.90334 |

[35] | Ouyang, Y.; Lago, A.; Daganzo, C.F., Taming the bullwhip effect: from traffic to supply chains, () |

[36] | Ramey, V.A., Nonconvex costs and the behavior of inventories, Journal of political economy, 99, 306-334, (1991) |

[37] | Simchi-Levi, D.; Zhao, Y., The value of information sharing in a two-stage supply chain with production capacity constraint, Navy research logistics, 50, 888-916, (2003) · Zbl 1055.90030 |

[38] | Sterman, J., Modelling managerial behaviour: misperceptions of feedback in a dynamic decision making experiment, Management science, 35, 3, 321-339, (1989) |

[39] | Tang, C.S., The impact of uncertainty on a production line, Management science, 36, 12, 1518-1531, (1990) · Zbl 0719.90038 |

This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.