Production Smoothing and the Bullwhip Effect

References

• Aviv Y (2007) On the benefits of collaborative forecasting partnerships between retailers and manufacturers. Management Sci. 53(5):777–794.Link, Google Scholar
• Balakrishnan A, Geunes J, Pangburn MS (2004) Coordinating supply chains by controlling upstream variability propagation. Manufacturing Service Oper. Management 6(2):163–183.Link, Google Scholar
• Berkowitz J, Kilian L (2000) Recent developments in bootstrapping time series. Econometric Rev. 19(1):1–48.Crossref, Google Scholar
• Blinder AS, Maccini LJ (1991) Taking stock: A critical assessment of recent research on inventories. J. Econom. Perspect. 5(1)73–96.Crossref, Google Scholar
• Bray RL, Mendelson H (2012) Information transmission and the bullwhip effect: An empirical investigation. Management Sci. 58(5):860–875.Link, Google Scholar
• Bresnahan TF, Ramey VA (1992) Output fluctuations at the plant level. Quart. J. Econom. 109(3):593–624.Crossref, Google Scholar
• Bureau of Labor Statistics (2013) Producer Price Index Industry Data. Government Printing Office, Washington, DC. Accessed January 31, 2015, http://download.bls.gov/pub/time.series/pc/pc.data.17.PrimaryMetal.Google Scholar
• Cachon GP, Olivares M (2010) Drivers of finished-goods inventory in the U.S. automobile industry. Management Sci. 56(1):202–216.Link, Google Scholar
• Cachon GP, Gallino S, Olivares M (2012a) Does inventory increase sales? The billboard and scarcity effects in U.S. automobile dealerships. Working paper, University of Pennsylvania, Philadelphia.Google Scholar
• Cachon GP, Gallino S, Olivares M (2012b) Severe weather and automobile assembly productivity. Columbia Business School Research Paper 12/37, Columbia University, New York.Google Scholar
• Cachon GP, Randall T, Schmidt GM (2007) In search of the bullwhip effect. Manufacturing Service Oper. Management 9(4):457–479.Link, Google Scholar
• Cameron AC, Trivedi PK (2005) Microeconometrics: Methods and Applications (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
• Chen L, Lee HL (2009) Information sharing and order variability control under a generalized demand model. Management Sci. 55(5):781–797.Link, Google Scholar
• Chen L, Lee HL (2012) Bullwhip effect measurement and its implications. Oper. Res. 60(4):771–784.Link, Google Scholar
• Consumer Confidence Survey (2014) Consumer Confidence Index. The Conference Board, New York. Accessed January 31, 2015, https://www.conference-board.org/data/consumerdata.cfm.Google Scholar
• Copeland A, Hall G (2011) The response of prices, sales, and output to temporary changes in demand. J. Appl. Econometrics 269(26):232–269.Crossref, Google Scholar
• Federal Highway Administration (2013) Historical monthly VMT report. Office of Highway Policy Information, Bureau of Public Roads, Washington, DC. Accessed January 31, 2015, http://www.fhwa.dot.gov/policyinformation/travel_monitoring/historicvmt.cfm.Google Scholar
• Gavirneni S, Kapuscinski R, Tayur S (1999) Value of information in capacitated supply chains. Management Sci. 45(1):16–24.Link, Google Scholar
• Gopal A, Goyal M, Netessine S, Reindorp M (2013) The impact of new product introduction on plant productivity in the North American automotive industry. Management Sci. 1909(25):1–20.Google Scholar
• Graves SC, Kletter DB, Hetzel WB (1998) A dynamic model for requirements planning with application to supply chain optimization. Oper. Res. 46(3):S35–S49.Link, Google Scholar
• Graves SC, Meal HC, Dasu S, Qui Y (1986) Two-stage production planning in a dynamic environment. Axsater S, Schneeweiss C, Silver E, eds. Multi-Stage Production Planning and Inventory Control (Springer, Berlin), 9–43.Crossref, Google Scholar
• Guajardo JA, Cohen MA, Netessine S (2012) Service competition and product quality in the U.S. automobile industry. Working paper, Wharton Faculty and Research, University of Pennsylvania, Philadelphia.Google Scholar
• Hall GJ (2000) Non-convex costs and capital utilization: A study of production scheduling at automobile assembly plants. J. Monetary Econom. 45:681–716.Crossref, Google Scholar
• Hall G, Rust J (2000) An empirical model of inventory investment by durable commodity intermediaries. Carnegie-Rochester Conf. Ser. Public Policy 52:171–214.Crossref, Google Scholar
• Hardle W, Horowitz J, Kreiss J-P (2003) Bootstrap methods for time series. Internat. Statist. Rev. 71(2):435–459.Crossref, Google Scholar
• Hausman WH (1969) Sequential decision problems: A model to exploit existing forecasters. Management Sci. 16(2):93–111.Link, Google Scholar
• Heath DC, Jackson PL (1994) Modeling the evolution of demand forecasts ITH application to safety stock analysis in production/distribution systems. IIE Trans. 26(3):17–30.Crossref, Google Scholar
• Holt CC, Modigliani F, Muth JF, Simon HA (1960) Planning Production, Inventories, and Work Forces (Prentice-Hall, Englewood Cliffs, NJ).Google Scholar
• Kahn JA (1987) Inventories and the volatility of production. Amer. Econom. Rev. 77(4):667–679.Google Scholar
• Keane MP (2010) Structural vs. atheoretic approaches to econometrics. J. Econometrics 156(1):3–20.Crossref, Google Scholar
• Klein M (1961) On production smoothing. Management Sci. 7(3): 286–293.Link, Google Scholar
• Lee HL, Padmanabhan V, Whang S (1997) Information distortion in a supply chain: The bullwhip effect. Management Sci. 43(4): 546–558.Link, Google Scholar
• Lee HL, So KC, Tang CS (2000) The value of information sharing in a two-level supply chain. Management Sci. 46(5):626–643.Link, Google Scholar
• Lieberman MB, Demeester L, Rivas R (1995) Inventory reduction in the Japanese automotive sector, 1965–1991. Working paper, University of California, Los Angeles, Los Angeles.Google Scholar
• Lucas RE (1976) Econometric policy evaluation: A critique. Carnegie-Rochester Conf. Series Public Policy 1:19–46.Crossref, Google Scholar
• Moreno A, Terwiesch C (2011) Pricing and production flexibility: An empirical analysis of the U.S. automotive industry. Working paper, Northwestern University, Evanston, IL.Google Scholar
• Newey WK (1984) A method of moments interpretation of sequential estimators. Econom. Lett. 14(2–3):201–206.Crossref, Google Scholar
• Oh S, Özer Ö (2013) Mechanism design for capacity planning under dynamic evolutions of asymmetric demand forecasts. Management Sci. 59(4):987–1007.Link, Google Scholar
• Petersen KB, Pedersen MS (2008) The Matrix Cookbook (Technical University of Denmark, Kongens Lyngby, Denmark).Google Scholar
• Ramey VA, Vine DJ (2006) Declining volatility in the US automobile industry. Amer. Econom. Rev. 96(5):1876–1889.Crossref, Google Scholar
• Ramey VA, West KD (1999) Inventories. Taylor JB, Woodford, M, eds. Handbook of Macroeconomics, Vol. 1, Part B, Chap. 13 (Elsevier B.V., Amsterdam), 863–923.Crossref, Google Scholar
• Reiss PC, Wolak FA (2007) Structural econometric modeling: Rationales and examples from industrial organization. Heckman JJ, Leamer EE, eds. Handbook of Econometrics, Vol. 6, Part A (Elsevier B.V., Amsterdam), 4277–4415.Crossref, Google Scholar
• Shah R, Ball G, Netessine S (2013) Plant operations and product recalls in the automotive industry: An empirical investigation. INSEAD Working Paper 2013/116/TOM, INSEAD, Fontainebleau, France.Google Scholar
• Shan J, Yang S, Zhang J (2013) An empirical study of the bullwhip effect in China. Production Oper. Management 23(4):537–551.Crossref, Google Scholar
• U.S. Energy Information Administration (2014) Spot prices: Petroleum and other liquids. U.S. Department of Energy, Washington, DC. Accessed January 31, 2015, http://www.eia.gov/dnav/pet/pet_pri_spt_s1_d.htm.Google Scholar
• WardsAuto Group (2014) Wards Auto InfoBank. Penton Media, Chicago, IL. Accessed January 31, 2015, http://wardsauto.com/.Google Scholar