Information Sharing in Supply Chains: An Empirical and Theoretical Valuation

References

• Aviv Y (2001) The effect of collaborative forecasting on supply chain performance. Management Sci. 47(10):1326–1343.Link, Google Scholar
• Aviv Y (2003) A time-series framework for supply chain inventory management. Oper. Res. 51(2):210–227.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
• Bray RL, Mendelson H (2012) Information transmission and the bullwhip effect: An empirical investigation. Management Sci. 58(5):860–875.Link, Google Scholar
• Brockwell PJ, Davis RA (2002) Introduction to Time Series and Forecasting (Springer, New York).Crossref, Google Scholar
• Cachon GP, Fisher M (2000) Supply chain inventory management and the value of shared information. Management Sci. 46(8):1032–1048.Link, 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
• Caplin AS (1985) The variability of aggregate demand with (s, S) inventory policies. Econometrica 53(6):1395–1409.Crossref, Google Scholar
• Chen F, Ryan JK, Simchi-Levi D (2000a) The impact of exponential smoothing forecasts on the bullwhip effect. Naval Res. Logist. 47(4):269–286.Crossref, Google Scholar
• Chen F, Drezner Z, Ryan JK, Simchi-Levi D (2000b) Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Management Sci. 46(3):436–443.Link, 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
• Cohen MA, Ho TH, Ren ZJ, Terwiesch C (2003) Measuring imputed cost in the semiconductor equipment supply chain. Management Sci. 49(12):1653–1670.Link, Google Scholar
• Dong Y, Dresner M, Yao Y (2014) Beyond information sharing: An empirical analysis of vendor-managed inventory. Production Oper. Management 23(5):817–828.Crossref, Google Scholar
• Gaur V, Giloni A, Seshadri S (2005) Information sharing in a supply chain under ARMA demand. Management Sci. 51(6):961–969.Link, Google Scholar
• Gilbert K (2005) An ARIMA supply chain model. Management Sci. 51(2):305–310.Link, Google Scholar
• Giloni A, Hurvich C, Seshadri S (2014) Forecasting and information sharing in supply chains under ARMA demand. IIE Trans. 46(1):35–54.Crossref, Google Scholar
• Graves SC (1999) A single-item inventory model for a nonstationary demand process. Manufacturing Service Oper. Management 1(1):50–61.Link, 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
• Hamilton JD (1994) Time Series Analysis (Princeton University Press, Princeton, NJ).Crossref, Google Scholar
• Heath DC, Jackson PL (1994) Modelling the evolution of demand forecasts with application to safety stock analysis in production/distribution systems. IIE Trans 26(3):17–30.Crossref, Google Scholar
• Irvine FO (1981) Retail inventory investment and the cost of capital. Amer. Econom. Rev. 71(4):633–648.Google Scholar
• Kesavan S, Gaur V, Raman A (2010) Do inventory and gross margin data improve sales forecasts for U.S. public retailers? Management Sci. 56(9):1519–1533.Link, Google Scholar
• Ledesma G (2004) Waste not, want not. Material Handling & Logistics (April 1), http://mhlnews.com/global-supply-chain/waste-not-want-not.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
• Miyaoka J, Hausman W (2004) How a base stock policy using “stale” forecasts provides supply chain benefits. Manufacturing Service Oper. Management 6(2):149–162.Link, Google Scholar
• Osadchiy N, Gaur V, Seshadri S (2013) Sales forecasting with financial indicators and experts’ input. Production Oper. Management 22(5):1056–1076.Crossref, Google Scholar
• Plosser CI, Schwert GW (1997) Estimation of a non-invertible moving average process: The case of overdifferencing. J. Econometrics (6):199–244.Google Scholar
• Retail Info Systems News (2013) Costco improves CRX supplier data technology platform. (April 22), http://risnews.edgl.com/retail-news/Costco-Improves-CRX-Supplier-Data-Technology-Platform86002.Google Scholar
• Rust J (1994) Structural estimation of Markov decision processes. Engle RF, McFadden DL, eds. Handbook of Econometrics, Vol. 4 (North-Holland, Amsterdam), 3081–3143.Google Scholar
• Schweitzer ME, Cachon GP (2000) Decision bias in the newsvendor problem with a known demand distribution: Experimental evidence. Management Sci. 46(3):404–420.Link, Google Scholar
• Terwiesch C, Ren ZJ, Ho TH, Cohen MA (2005) An empirical analysis of forecast sharing in the semiconductor equipment supply chain. Management Sci. 51(2):208–220.Link, Google Scholar
• Van Donselaar KH, Gaur V, Van Woensel T, Broekmeulen RACM, Fransoo JC (2010) Ordering behavior in retail stores and implications for automated replenishment. Management Sci. 56(5):766–784.Link, Google Scholar
• Wold H (1938) A Study in the Analysis of Stationary Time Series (Almqvist and Wiksell, Uppsala, Sweden).Google Scholar