Research Note—Do Electronic Linkages Reduce the Bullwhip Effect? An Empirical Analysis of the U.S. Manufacturing Supply Chains

Published Online:https://doi.org/10.1287/isre.1110.0394

References

  • Aeppel T. “Bullwhip” hits firms as growth snaps back. Wall Street Journal (2010) January 27):A1, A6Google Scholar
  • Allen D. S. Do inventories moderate fluctuations in output? Federal Reserve Bank St. Louis Rev. (1997) July–August):39–50Google Scholar
  • Anderson E., Fine C., Parker G. Upstream volatility in the supply chain: The machine tool industry as a case study. Production Oper. Management (2000) 9(3):239–261CrossrefGoogle Scholar
  • Bakos J. Y. Information links and electronic marketplaces: Implications of interorganizational information systems in vertical markets. J. Management Inform. Systems (1991) 8(2):31–52CrossrefGoogle Scholar
  • Bakos Y. J. Reducing buyer search costs: Implications for electronic marketplaces. Management Sci. (1997) 43(12):1676–1692LinkGoogle Scholar
  • Barua A., Kriebel C. H., Mukhopadhyay T. Information technologies and business value:—An analytic and empirical investigation. Inform. Systems Res. (1995) 6(1):3–23LinkGoogle Scholar
  • Barua A., Ravindran S., Whinston A. B. Efficient selection of suppliers over the Internet. J. Management Inform. Systems (1997) 13(4):117–137CrossrefGoogle Scholar
  • Barua A., Konana P., Whinston A. B., Yin F. An empirical investigation of net-enabled business value. MIS Quart. (2004) 28(4):585–620CrossrefGoogle Scholar
  • Blanchard O. The production and inventory behavior of the American automobile industry. J. Political Econom. (1983) 91(3):365–400CrossrefGoogle Scholar
  • Brynjolfsson E., Hitt L. Paradox lost? Firm-level evidence on the returns to information systems spending. Management Sci. (1996) 42(4):541–558LinkGoogle Scholar
  • Cachon G. P., Randall T., Schmidt G. M. In search of the bullwhip effect. Manufacturing Service Oper. Management (2007) 9(4):457–479LinkGoogle Scholar
  • Caplin A. S. The variability of aggregate demand with (S, s) inventory policies. Econometrica (1985) 53(6):1395–1409CrossrefGoogle Scholar
  • Cash J. I., Konsynski B. IS redraws competitive boundaries. Harvard Bus. Rev. (1985) 63(2):134–142Google 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):436–443LinkGoogle Scholar
  • Cheng J., Nault B. R. Industry level supplier-driven IT spillovers. Management Sci. (2007) 53(8):1199–1261LinkGoogle Scholar
  • Choudhury V., Hartzel K. S., Konsynski B. R. Uses and consequences of electronic markets: An empirical investigation in the aircraft parts industry. MIS Quart. (1998) 22(4):471–507CrossrefGoogle Scholar
  • Clemons E. K., Reddi S. P., Row M. C. The impact of information technology on the organization of economic activity: The move to the middle hypothesis. J. Management Inform. Systems (1993) 10(2):9–36CrossrefGoogle Scholar
  • Coase R. The nature of the firm. Economica (1937) 4(16):386–405CrossrefGoogle Scholar
  • Croson R., Donohue K. Behavioral causes of the bullwhip effect and the observed value of inventory information. Management Sci. (2006) 52(3):323–336LinkGoogle Scholar
  • Demsetz H. The cost of transacting. Quart. J. Econom. (1968) 82(1):33–53CrossrefGoogle Scholar
  • Dedrick J., Xu S. X., Zhu K. X. How does information technology shape supply-chain structure? Evidence on the number of suppliers. J. Management Inform. Systems (2008) 25(2):41–72CrossrefGoogle Scholar
  • Dong S., Xu S. X., Zhu K. X. Information technology in supply chains: The role of IT-enabled resources under competition. Inform. Systems Res. (2009) 20(1):18–32LinkGoogle Scholar
  • Ghali M. A. Seasonality, aggregation and the testing of the production smoothing hypothesis. Amer. Econom. Rev. (1987) 77(3):464–469Google Scholar
  • Gaur V., Fisher M. L., Raman A. An econometric analysis of inventory turnover performance in retail services. Management Sci. (2005) 51(2):181–194LinkGoogle Scholar
  • Greene W. H.Econometric Analysis (1997) (Prentice Hall, Upper Saddle River, NJ) Google Scholar
  • Grover V., Malhotra M. K. Transaction cost framework in operations and supply chain management research: Theory and measurement. J. Oper. Management (2003) 21(4):457–473CrossrefGoogle Scholar
  • Holt C. C., Modigliani F., Shelton J. P. The transmission of demand fluctuations through a distribution and production systems, the TV-set industry. Canad. J. Econom. (1968) 1(4):718–739CrossrefGoogle Scholar
  • Jonston H. R., Vitale M. R. Creating competitive advantage with interorganizational systems. MIS Quart. (1988) 12(2):153–165CrossrefGoogle Scholar
  • Kahn J. A. Why is production more volatile than sales? Theory and evidence on the stockout-avoidance motive for inventory-holding. Quart. J. Econom. (1992) 107(2):481–510CrossrefGoogle Scholar
  • Kennedy P.A Guide to Econometrics (2003) 5th ed.(MIT Press, Cambridge, MA) Google Scholar
  • Krane S. D., Braun S. N. Production smoothing evidence from physical-product data. J. Political Econom. (1991) 99(3):558–581CrossrefGoogle 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):546–559LinkGoogle Scholar
  • Lee H. G., Clark T., Tam K. Y. Research report: Can EDI benefit adopters? Inform. Systems Res. (1999) 10(2):186–195LinkGoogle Scholar
  • Lee H. L., Padmanabhan V., Whang S. Comments on “Information distortion in a supply chain: The bullwhip effect”. Management Sci. (2004) 50(12 Supplement):1887–1893LinkGoogle Scholar
  • Lucking-Reiley D., Spulber D. F. Business-to-business electronic commerce. J. Econom. Perspect. (2001) 15(1):55–68CrossrefGoogle Scholar
  • Malone T. W., Yates J., Benjamin R. I. Electronic markets and electronic hierarchies. Comm. ACM (1987) 30(6):484–497CrossrefGoogle Scholar
  • Miron J. A., Zeldes S. P. Seasonality, cost shocks, and the production smoothing model of inventories. Econometrica (1988) 56(4):877–908CrossrefGoogle Scholar
  • Mithas S., Jones J. L. Do auction parameters affect buyer surplus in e-auctions for procurement? Production Oper. Management (2007) 16(4):455–470CrossrefGoogle Scholar
  • Mithas S., Jones J. L., Mitchell W. Buyer intention to use Internet-enabled reverse auctions? The role of asset specificity, product specialization, and non-contractibility. MIS Quart. (2008) 32(4):705–724CrossrefGoogle Scholar
  • Mukhopadhyay T., Kekre S. Strategic and operational benefits of electronic integration in B2B procurement. Management Sci. (2002) 48(10):1301–1313LinkGoogle Scholar
  • Mukhopadhyay T., Kekre S., Kalathur S. Business value of information technology: A study of electronic data interchange. MIS Quart. (1995) 19(2):137–156CrossrefGoogle Scholar
  • Rumyantsev S., Netessine S. What can be learned from classical inventory models? A cross-industry exploratory investigation. Manufacturing Service Oper. Management (2007) 9(4):409–429LinkGoogle Scholar
  • Saeed K. A., Malhotra M. K., Grover V. Examining the impact of interorganizational systems on process efficiency and sourcing leverage in buyer-supplier dyads. Decision Sci. (2005) 36(3):365–396CrossrefGoogle Scholar
  • Shah R., Shin H. Relationships among information technology, inventory, and profitability: An investigation of level invariance using sector level data. J. Oper. Management (2006) 25(4):768–784CrossrefGoogle Scholar
  • Srinivasan K., Kekre S., Mukhopadhyay T. Impact of electronic data interchange technology on JIT shipments. Management Sci. (1994) 40(10):1291–1304LinkGoogle Scholar
  • Tatsiopoulos I. P., Ponis S. T., Hadzillias E. A., Panayiotou N. A. Realization of the virtual enterprise paradigm in the clothing industry through e-business technology. Production Oper. Management (2002) 11(2):413–423Google 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):208–220LinkGoogle Scholar
  • Williamson O. E.Markets and Hierarchies: Analysis and Antitrust Implications (1975) (Free Press, New York) Google Scholar
  • Williamson O. E. Transaction-cost economics: The governance of contractual relations. J. Law Econom. (1979) 22(2):233–261CrossrefGoogle Scholar
  • Wooldridge J. M.Econometric Analysis of Cross Section and Panel Data (2002) (MIT Press, Cambridge, MA) Google Scholar
  • Yao Y., Dresner M., Palmer J. Private network EDI vs. the Internet electronic markets: A direct comparison of fulfillment performance. Management Sci. (2009) 55(5):843–852LinkGoogle Scholar
  • Zhou Z., Zhu K. X. The effects of information transparency on suppliers, manufacturers and consumers in online markets. Marketing Sci. (2010) 29(6):1125–1137LinkGoogle Scholar
  • Zhu K. Information transparency of business-to-business electronic markets: A game-theoretic analysis. Management Sci. (2004a) 50(5):670–685LinkGoogle Scholar
  • Zhu K. The complementarity of IT infrastructure and ecommerce capability: A resource-based assessment of business value. J. Management Inform. Systems (2004b) 21(1):167–202CrossrefGoogle Scholar
  • Zhu K., Kraemer K. L. E-commerce metrics for net-enhanced organizations: Assessing the value of e-commerce to firm performance in the manufacturing sector. Inform. Systems Res. (2002) 13(3):275–295LinkGoogle Scholar
  • Zhu K., Kraemer K. L., Gurbaxani V., Xu S. Migration to open-standard interorganizational systems: Network effects, switching costs, and path dependency. MIS Quart. (2006) 30(3):515–539CrossrefGoogle 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.