Evolution of ARMA demand in supply chains

Manufacturing and Service Operations Management

Volumn 6, Issue 2, 2004, Pages 195-198

  Zhang, Xiaolong ^a  

^a FAIRLEIGH DICKINSON UNIVERSITY   (United States)

Author keywords

Demand propagation; Supply chain; Time series forecasting

Indexed keywords

DEMAND PROPAGATION; INFORMATION SHARING; SUPPLY CHAINS; TIME SERIES FORECASTING;

ALGORITHMS; DECISION MAKING; INFORMATION ANALYSIS; INVENTORY CONTROL; PUBLIC POLICY; TECHNOLOGICAL FORECASTING; TIME SERIES ANALYSIS;

PRODUCTION CONTROL;

EID: 22544477501     PISSN: 15234614     EISSN: 15265498     Source Type: Journal    
DOI: 10.1287/msom.1040.0042     Document Type: Article

References (18)

1. Aviv, Y. 2001. The effect of collaborative forecasting on supply chain performance. Management Sci. 47 1226-1343.
2. Aviv, Y. 2002. Gaining benefits from joint forecasting and replenishment processes: The case of auto-correlated demand. Manufacturing Service Oper. Management 4 55-74.
3. Aviv, Y. 2003. A time-series framework for supply-chain inventory management. Oper. Res. 51(2) 210-227.
4. Box, G. E. P., G. M. Jenkins, G. C. Reinsel. 1994. Time Series Analysis: Forecasting and Control, 3rd ed. Prentice Hall, Upper Saddle River, NJ.
5. Cachon, G., M. Fisher. 2000. Supply chain inventory management and the value of shared information. Management Sci. 46 1032-1048.
6. Chen, F., Z. Drezner, J. K. Ryan, D. Simchi-Levi. 2000a. Quantifying the bullwhip effect in a simple supply chain. Management Sci. 46(3) 436-43.
7. Chen, F., Z. Drezner, J. K. Ryan, D. Simchi-Levi. 2000b. The impact of exponential smoothing forecasts on the bullwhip effect. Naval Res. Logist. 47 269-286.
8. De Jong, P., J. Penzer. 2000. The ARIMA model in state space form. Research report, Department of Statistics, London School of Economics, London, U.K.
9. Gilbert, K. 2002. An ARMA supply chain model. Working paper, Management Science Program, University of Tennessee, Knoxville, TN.
10. Graves, S. C. 1999. A single-item inventory model for a non-stationary demand process. Manufacturing Services Oper. Management 1(1) 50-61.
11. Hamilton, J. D. 1994. Time Series Analysis. Princeton University Press, Princeton, NJ.
12. Johnson, G. D., H. E. Thompson. 1975. Optimality of myopic inventory policies for certain dependent demand processes. Management Sci. 21(11) 1303-1307.
13. Lee, H. L., P. Padmanabhan, S. Whang. 1997. Information distortion in a supply chain: The bullwhip effect. Management Sci. 43 546-558.
14. Lee, H. L., K. C. So, C. S. Tang. 2000. The value of information sharing in a two-level supply chain. Management Sci. 46 626-643.
15. Li, G. S., S. Wang, G. Yu, H. Yan. 2003. The relationship between the demand process and the order process under a time-series framework. Working paper, Beijing University of Aeronautics and Astronautics, Beijing, China.
16. Raghunathan, S. 2001. Information sharing in a supply chain: A note on its value when demand is non-stationary. Management Sci. 47 605-610.
17. Seifert, D., J. McLaughlin, J. Andraski. 2003. CPFR: How to Create Supply Chain Advantage. AMACOM, New York.
18. Zipkin, P. 2000. Foundations of Inventory Management. McGraw-Hill, New York.