Behavioral Causes of the Bullwhip Effect and the Observed Value of Inventory Information

References

• Anderson E., Fine C., Tayur S., Ganeshan R., Magazine M. Business cycles and productivity in capital equipment supply chains. Quantitative Methods for Supply Chain Management (1998) (Kluwer Academic Publishers, Norwell, MA) . Chapter 13Google Scholar
• Anderson E., Morrice D. A simulation game for teaching service-oriented supply chain management: Does information sharing help managers with service capacity decisions? Production Oper. Management (2000) 9(1):40–55Crossref, Google Scholar
• Bourland K., Powell S., Pyke D. Exploiting timely demand information to reduce inventories. Eur. J. Oper. Res. (1996) 92:239–253Crossref, Google Scholar
• Cachon G. Managing supply chain variability with scheduled ordering policies. Management Sci. (1999) 45:843–856Link, Google Scholar
• Cachon G., Fisher M. Supply chain inventory management and the value of shared information. Management Sci. (2000) 46:1032–1048Link, Google Scholar
• Cachon G., Lariviere M. Capacity choice and allocation: Strategic behavior and supply chain performance. Management Sci. (1999) 45:1091–1108Link, Google Scholar
• Chen F. Echelon reorder points, installation reorder points, and the value of centralized demand information. Management Sci. (1998) 44:S221–S234Link, Google Scholar
• Chen F. Decentralized supply chains subject to information delays. Management Sci. (1999) 45:1016–1090Link, Google Scholar
• Chen F., Samroengraja R. The stationary beer game. Production Oper. Management (2000) 9:19–30Crossref, Google Scholar
• Chen F., Drezner Z., Ryan J. K., Simchi-Levi D., Tayur S., Ganeshan R., Magazine M. The bullwhip effect: Managerial insights on the impact of forecasting and information on variability in a supply chain. Quantitative Models for Supply Chain Management (1998) (Kluwer Academic Publishers, Norwell, MA) . Chapter 14Google Scholar
• Clark A. J., Scarf H. E. Optimal policies for a multi-echelon inventory problem. Management Sci. (1960) 6:475–490Link, Google Scholar
• Diehl E., Sterman J. D. Effects of feedback complexity in dynamic decision making. Organ. Behavior Human Decision Processes (1995) 62:198–215Crossref, Google Scholar
• Federgruen A., Zipkin P. Computational issues in an infinite horizon, multi-echelon inventory model. Oper. Res. (1984) 32:818–836Link, Google Scholar
• Forrester J. Industrial dynamics: A major breakthrough for decision makers. Harvard Bus. Rev. (1958) 36:37–66Google Scholar
• Gavirneni S., Kapuscinski R., Tayur S. Value of information in capacitated supply chains. Management Sci. (1999) 45:16–24Link, Google Scholar
• Graves S. C. A single-item inventory model for a nonstationary demand process. Manufacturing Service Oper. Management (1999) 1:50–61Link, Google Scholar
• Hogarth R.Judgment and Choice (1987) 2nd ed.(Wiley, New York) Google Scholar
• Hogarth R., Einhorn H. Order effects in belief updating: The belief-adjustment model. Cognitive Psych. (1992) 24:1–55Crossref, Google Scholar
• Kahneman D., Lovallo D. Timid choices and bold forecasts: A cognitive perspective on risk taking. Management Sci. (1993) 39:17–31Link, Google Scholar
• Kalidindi V. S. The web based beer distribution game: An application. (2001) . Unpublished Masters thesis, Department of Mechanical Engineering, University of Minnesota, Minneapolis, MNGoogle Scholar
• Kaminsky P., Simchi-Levi D., Lee H., Ng S. M. A new computerized beer distribution game: Teaching the value of integrated supply chain management. Global Supply Chain and Technology Management (1998) 1(The Production and Operations Management Society Series in Technology and Operations Management, Miami, FL) 216–225Google Scholar
• Lee H., Padmanabhan P., Whang S. Information distortion in supply chains. Sloan Management Rev. (1997a) 38:93–102Google Scholar
• Lee H., Padmanabhan P., Whang S. Information distortion in a supply chain: The bullwhip effect. Management Sci. (1997b) 43:546–558Link, Google Scholar
• Lee H., So K., Tang C. The value of information sharing in a two-level supply chain. Management Sci. (2000) 46:626–643Link, Google Scholar
• Paich M., Sterman J. D. Boom, bust, and failures to learn in experimental markets. Management Sci. (1993) 39:1439–1457Link, Google Scholar
• Scheck S. Net tools could save automakers $1 billion. Electronic News (1998) 14(September):104Google Scholar
• Schotter A., Weigelt K. Behavioral consequences of corporate incentives and long-term bonuses: An experimental study. Management Sci. (1992) 38:1280–1298Link, Google Scholar
• Schweitzer M., Cachon G. Decision biases and learning in the newsvendor problem: Experimental evidence. Management Sci. (2000) 46:404–420Link, Google Scholar
• Seigel S.Nonparametric Statistics for the Behavioral Sciences (1965) (Wiley, New York) Google Scholar
• Sengupta K., Abdel-Hamid T. Alternative conceptions of feedback in dynamic decision environments: An experimental investigation. Management Sci. (1993) 39:411–428Link, Google Scholar
• Sogomonian A., Tang C. A modeling framework for coordinating promotion and production decisions within a firm. Management Sci. (1993) 39:191–203Link, Google Scholar
• Steckel J., Gupta S., Banerji A. Supply chain decision making: Will shorter cycle times and shared point-of-sale information necessarily help? Management Sci. (2004) 52(4):458–464Link, Google Scholar
• Stein T. SAP targets apparel. Information Week (1998) . Online (May 4) http://www.informationweek.comGoogle Scholar
• Sterman J. D. Modeling managerial behavior: Misperceptions of feedback in a dynamic decision making experiment. Management Sci. (1989a) 35:321–339Link, Google Scholar
• Sterman J. D. Misperceptions of feedback in dynamic decision making. Organ. Behavior Human Decision Processes (1989b) 43:301–335Crossref, Google Scholar
• Sterman J. D. Deterministic chaos in an experimental economic system. J. Econom. Behavior Organ. (1989c) 12:1–28Crossref, Google Scholar
• Sterman J. D. Teaching takes off: Flight simulators for management education. OR/MS Today (1992) 19(5):40–44Google Scholar
• Sterman J. D. Learning in and about complex systems. System Dynam. Rev. (1994) 10:291–330Crossref, Google Scholar