Characterization of the Bullwhip Effect in Linear, Time-Invariant Supply Chains: Some Formulae and Tests

Published Online:https://doi.org/10.1287/mnsc.1060.0573

References

  • Aviv Y. A time-series framework for supply chain inventory management. Oper. Res. (2003) 51(2):210–227LinkGoogle Scholar
  • Baganha M. P., Cohen M. A. The stabilizing effect of inventory in supply chains. Oper. Res. (1998) 46(3):572–583Google Scholar
  • Blinder A. S. Can the production smoothing model of inventory behavior be saved? Quart. J. Econom. (1986) 101:431–454CrossrefGoogle Scholar
  • Boyd S., Desoer C. A. Subharmonic functions and performance bounds on linear time-invariant feedback systems. IMA J. Math. Control Inform. (1985) 2:153–170CrossrefGoogle Scholar
  • Chen J. Logarithmic integrals, interpolation bounds, and performance limitations in MIMO feedback systems. IEEE Trans. Automatic Control (2000) 45(6):1098–1115CrossrefGoogle Scholar
  • Chen F., Ryan J., Simchi-Levi D. The impact of exponential smoothing forecasts on the bullwhip effect. Naval Res. Logist. (2000a) 47(4):271–286CrossrefGoogle Scholar
  • 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 Sci. (2000b) 46(3):436–443LinkGoogle Scholar
  • Cooke J. A. The $30 billion promise. Traffic Management (1993) 32(Dec.):57–59Google Scholar
  • Daganzo C. F. A theory of supply chains. (2001) . Institute of Transportation Studies Research Report, UCB-ITS-RR-2001-7, University of California, Berkeley, CAGoogle Scholar
  • Daganzo C. F.A Theory of Supply Chains (2003) (Springer, Heidelberg, Germany) CrossrefGoogle Scholar
  • Daganzo C. F. On the stability of supply chains. Oper. Res. (2004) 52(6):909–921LinkGoogle Scholar
  • Dejonckheere J., Disney S. M., Lambrecht M. R., Towill D. R. Measuring and avoiding the bullwhip effect: A control theoretic approach. Eur. J. Oper. Res. (2003) 147:567–590CrossrefGoogle Scholar
  • Dejonckheere J., Disney S. M., Lambrecht M. R., Towill D. R. The impact of information enrichment on the bullwhip effect in supply chains: A control engineering perspective. Eur. J. Oper. Res. (2004) 153(3):727–750CrossrefGoogle Scholar
  • Forrester J. Industrial dynamics, a major breakthrough for decision makers. Harvard Bus. Rev. (1958) 36(July–Aug):37–66Google Scholar
  • Forrester J.Industrial Dynamics (1961) (MIT Press, Cambridge, MA) Google Scholar
  • Gaur V., Giloni A., Seshadri S. Information sharing in a supply chain under ARMA demand. Management Sci. (2005) 51(6):961–969LinkGoogle Scholar
  • Gavirneni S., Kapuscinski R., Tayur S. Value of information in capacitated supply chains. Management Sci. (1999) 45(1):16–24LinkGoogle Scholar
  • Gilbert K. An ARIMA supply chain model. Management Sci. (2005) 51(2):305–310LinkGoogle Scholar
  • Goodwin J., Franklin S. The beer distribution game: Using simulation to teach systems thinking. J. Management Development (1994) 13(8):7–15CrossrefGoogle Scholar
  • Graves S. A single item inventory model for a nonstationary demand process. Manufacturing Service Oper. Management (1999) 1:50–61LinkGoogle Scholar
  • Hariharan R., Zipkin P. Customer-order information, leadtimes and inventories. Management Sci. (1995) 41(10):1599–1607LinkGoogle Scholar
  • Holt C. C., Modigliani F., Muth J., Simon H. A.Planning Production, Inventories and Work Force (1960) (Prentice Hall, Englewood Cliffs, NJ) Google Scholar
  • Kahn J. Inventories and the volatility of production. Amer. Econom. Rev. (1987) 77:667–679Google Scholar
  • Kaminsky P., Simchi-Levi D., Lee Hau, Ng Shu Ming. The computerized beer game: Teaching the value of integrated supply chain management. Supply Chain and Technology Management (1998) 1:216–225Google Scholar
  • Lee H. L., Padmanabhan V., Whang S. The bullwhip effect in supply chains. Sloan Management Rev. (1997a) 38(3):93–102Google Scholar
  • Lee H. L., Padmanabhan V., Whang S. Information distortion in a supply chain: The bullwhip effect. Management Sci. (1997b) 43(4):546–558LinkGoogle Scholar
  • Lee H. L., So K. C., Tang C. S. The value of information sharing in a two level supply chain. Management Sci. (2000) 46(5):628–643LinkGoogle Scholar
  • Magee J. F. Guides to inventory control (Part II). Harvard Bus. Rev. (1956) March–April):106–116Google Scholar
  • Magee J. F., Boodman D.Production Planning and Inventory Control (1967) 2nd ed.(McGraw-Hill, New York) Google Scholar
  • Naish H. F. Production smoothing in the linear quadratic inventory model. Econom. J. (1994) 104(425):864–875Google Scholar
  • Ouyang Y., Daganzo C. F. Counteracting the bullwhip effect with decentralized negotiations and advance demand information. Physica A (2006) 363(1):14–23CrossrefGoogle Scholar
  • Ramey V. A. Nonconvex costs and the behavior of inventories. J. Political Econom. (1991) 99:306–334CrossrefGoogle Scholar
  • Seiler P. J. Coordinated control of unmanned aerial vehicles. (2001) . PhD dissertation, University of California, Berkeley, CAGoogle Scholar
  • So K. C., Zheng X. Impact of supplier's lead time and forecast demand updating on retailer's order quantity variability in a two-level supply chain. Internat. J. Production Econom. (2003) 86:169–179CrossrefGoogle Scholar
  • Sterman J. Modelling managerial behavior: Misperceptions of feedback in a dynamic decision making experiment. Management Sci. (1989) 35(3):321–339LinkGoogle Scholar
  • Zhang X. Evolution of ARMA demand in supply chains. Manufacturing Service Oper. Management (2004) 6:195–198LinkGoogle Scholar
  • Zipkin P. H.Foundations of Inventory Management (2000) (McGraw-Hill/Irwin, New York) Google Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.