Information Transmission and the Bullwhip Effect: An Empirical Investigation

References

• Aeppel T. Bullwhip hits firms as growth snaps back. Wall Street Journal (2010) January 27). http://online.wsj.com/article/SB10001424052748704509704575019392199662672.html?mod=WSJ-hps-LEFTWhatsNewsGoogle Scholar
• Aviv Y. A time-series framework for supply-chain inventory management. Oper. Res. (2003) 51(2):210–227Link, Google Scholar
• Aviv Y. On the benefits of collaborative forecasting partnerships between retailers and manufacturers. Management Sci. (2007) 53(5):777–794Link, Google Scholar
• Balakrishnan A., Geunes J., Pangburn M. S. Coordinating supply chains by controlling upstream variability propagation. Manufacturing Service Oper. Management (2004) 6(2):163–183Link, Google Scholar
• Basu S., Fernald J. G., Oulton N., Srinivasan S. The case of the missing productivity growth, or does information technology explain why productivity accelerated in the United States but not in the United Kingdom? NBER Macroeconomics Annual (2004) (2003) 9–63Crossref, Google Scholar
• Cachon G. P., Lariviere M. A. Capacity choice and allocation: Strategic behavior and supply chain performance. Management Sci. (1999) 45(8):1091–1108Link, Google Scholar
• Cachon G. P., Randall T., Schmidt G. M. Search of the bullwhip effect. Manufacturing Service Oper. Management (2007) 9(4):457–479Link, Google Scholar
• Cameron A. C., Trivedi P. K.Microeconometrics: Methods and Applications (2005) (Cambridge University Press, New York) Crossref, Google Scholar
• Cameron A. C., Gelbach J. B., Miller D. L. Robust inference with multiway clustering. J. Bus. Econom. Statist. (2011) 29(2):238–249Crossref, Google Scholar
• Chen F., Drezner Z., Ryan J. K., Simchi-Levi D. Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Management Sci. (2000) 46(3):436–443Link, Google Scholar
• Chen H., Frank M. Z., Wu O. Q. What actually happened to the inventories of American companies between 1981 and 2000? Management Sci. (2005) 51(7):1015–1031Link, Google Scholar
• Chen L., Lee H. L. Information sharing and order variability control under a generalized demand model. Management Sci. (2009) 55(5):781–797Link, Google Scholar
• Chen L., Lee H. L. Bullwhip effect measurement and its implications. (2010) . Working paper, Fuqua School of Business, Duke University, Durham, NCGoogle Scholar
• Cohen M. A., Ho T. H., Ren Z. J., Terwiesch C. Measuring imputed cost in the semiconductor equipment supply chain. Management Sci. (2003) 49(12):1653–1670Link, Google Scholar
• Croson R., Donohue K. Impact of POS data sharing on supply chain management: An experimental study. Production Oper. Management (2003) 12(1):1–11Crossref, Google Scholar
• Croson R., Donohue K. Behavioral causes of the bullwhip effect and the observed value of inventory information. Management Sci. (2006) 52(3):323–336Link, Google Scholar
• Davidson R., MacKinnon J. G.Econometric Theory and Methods (2004) 21(Oxford University Press, New York) Google Scholar
• Davis S. J., Kahn J. A. Interpreting the great moderation: Changes in the volatility of economic activity at the macro and micro levels. J. Econom. Perspect. (2008) 22(4):155–180Crossref, Google Scholar
• Dong Y., Dresnera M., Yao O. An empirical analysis of the value of managing information asymmetry in vendor managed inventory. (2011) . Working paper, Robert H. Smith School of Business, University of Maryland, College ParkGoogle Scholar
• Ernst R., Pyke D. F. Optimal base stocks policies and truck capacity in a two-echelon system. Naval Res. Logist. (1993) 40(7):879–903Crossref, Google Scholar
• Fransoo J. C., Wouters M. J. F. Measuring the bullwhip effect in the supply chain. Supply Chain Management: An Internat. J. (2000) 5(2):78–89Crossref, Google Scholar
• Gaur V., Fisher M. L., Raman A. An econometric analysis of inventory turnover performance in retail services. Management Sci. (2005) 51(2):181–194Link, Google Scholar
• Gavirneni S., Kapuscinski R., Tayur S. Value of information in capacitated supply chains. Management Sci. (1999) 45(1):16–24Link, Google Scholar
• Gow I. D., Ormazabal G., Taylor D. Correcting for cross-sectional and time-series dependence in accounting research. Accounting Rev. (2010) 85(2):483–512Crossref, Google Scholar
• Granger C. W. J., Newbold P. Spurious regressions in econometrics. J. Econometrics (1974) 2(2):111–120Crossref, Google Scholar
• Graves S. C. A single-item inventory model for a nonstationary demand process. Manufacturing Service Oper. Management (1999) 1(1):50–61Link, Google Scholar
• Graves S. C., Kletter D. B., Hetzel W. B. A dynamic model for requirements planning with application to supply chain optimization. Oper. Res. (1998) 46(3-Supplement-3):S35–S49Link, Google Scholar
• Hahn J. Bootstrapping quantile regression estimators. Econometric Theory (1995) 11(1):105–121Crossref, Google Scholar
• Hall P., Horowitz J. L., Jing B. Y. On blocking rules for the bootstrap with dependent data. Biometrika (1995) 82(3):561–574Crossref, Google Scholar
• Hammond J. H. (1994) . Barilla SpA (A). HBS Case 9-694-046, Harvard Business School, BostonGoogle Scholar
• Hausman W. H. Sequential decision problems: A model to exploit existing forecasters. Management Sci. (1969) 16(2):93–111Link, Google Scholar
• Hausman W. H., Peterson R. Multiproduct production scheduling for style goods with limited capacity, forecast revisions, and terminal delivery. Management Sci. (1972) 18(7):370–383Link, Google Scholar
• Jorgenson D. W. Information technology and the U.S. economy. Amer. Econom. Rev. (2001) 91(1):1–32Crossref, Google Scholar
• Jorgenson D. W., Ho M. S., Stiroh K. J. Lessons for Europe from the U.S. growth resurgence. CESifo Econom. Stud. (2003) 49(1):27–47Crossref, Google Scholar
• Kahn J. A. Inventories and the volatility of production. Amer. Econom. Rev. (1987) 77(4):667–679Google Scholar
• Kahn J. A., Mcconnell M. M., Gabriel P.-Q. On the causes of the increased stability of the U. S. economy. Federal Reserve Bank of New York Econom. Policy Rev. (2002) 1(May):183–202Google Scholar
• Katz J. Creating high-value supply chains. Indust. Week (2011) February 16). http://www.industryweek.com/articles/creating_high-value_supply_chains_23884.aspx?SectionID=2Google Scholar
• Krishnan J., Kleindorfer P. R., Heching A. Demand distortions and capacity allocation policies. (2007) . Working paper, International Monetary Fund, Washington, DC. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1021950Crossref, Google Scholar
• Lai R. K. Bullwhip in a Spanish shop. (2005) . Harvard NOM Research Paper 06-06, Harvard Business School, BostonGoogle Scholar
• Lee H. L. The triple-A supply chain. Harvard Business Review (2004) 82(10):102–113Google Scholar
• Lee H. L., Padmanabhan V., Whang S. Information distortion in a supply chain: The bullwhip effect. Management Sci. (1997) 43(4):546–558Link, Google 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):626–643Link, Google Scholar
• Lütkepohl H.New Introduction to Multiple Time Series Analysis (2005) (Springer, Berlin) Crossref, Google Scholar
• Newey W. K. A method of moments interpretation of sequential estimators. Econom. Lett. (1984) 14(2–3):201–206Crossref, Google Scholar
• Petersen M. A. Estimating standard errors in finance panel data sets: Comparing approaches. Rev. Financial Stud. (2009) 22(1):435–480Crossref, Google Scholar
• Porteus E L.Foundations of Stochastic Inventory Theory (2002) (Stanford Business Books, Stanford, CA) Crossref, Google Scholar
• Songini M. L. Caterpillar moves to revamp supply-chain operations via the Web. Computer World (2000) October 11). http://www.computerworld.com/s/article/print/52290/Caterpillar_moves_to_revamp_supply_chain_operations_via_the_WebGoogle Scholar
• Sterman J. D. Modeling managerial behavior: Misperceptions of feedback in a dynamic decision-making experiment. Management Sci. (1989) 35(3):321–339Link, Google Scholar
• Terwiesch C., Ren Z. J., Ho T. H., Cohen M. A. An empirical analysis of forecast sharing in the semiconductor equipment supply chain. Management Sci. (2005) 51(2):208–220Link, Google Scholar
• Wong C. Y., El-Beheiry M. M., Johansen J., Hvolby H. H. The implications of information sharing on bullwhip effects in a toy supply chain. Internat. J. Risk Assessment Management (2007) 7(1):4–18Crossref, Google Scholar