Analyzing the effect of inventory policies on the nonstationary performance with transfer functions

REFERENCES

• Anon . 2004 . Supply Chain Operations Reference Model, , Version 6.1 , Pittsburgh, PA : Supply-Chain Council .
   Google Scholar
• Box , G. E.P. , Jenkins , G. M. and Reinsel , G. C. 1994 . Time Series Analysis: Forecasting and Control, , 3rd edn. , Upper Saddle River, NJ : Prentice Hall .
   Google Scholar
• Burns , J. F. and Sivazlian , B. D. 1978 . Dynamic analysis of multi-echelon supply systems . Computers & Industrial Engineering , 2 : 181 – 193 .
   Web of Science ®Google Scholar
• Chen , F. , Ryan , J. K. and Simchi-Levi , D. 2000 . The impact of exponential smoothing forecasts on the bullwhip effect . Naval Research Logistics , 47 : 269 – 286 .
   Web of Science ®Google Scholar
• Chen , Y. F. , Drezner , Z. , Ryan , J. K. and Simchi-Levi , D. 2000 . Quantifying the bullwhip effect in a simple supply chain: the impact of forecasting, lead times and information . Management Science , 46 : 436 – 443 .
   Web of Science ®Google Scholar
• Chiu , H. N. and Huang , H. L. 2003 . A multi-echelon integrated JIT inventory model using the time buffer and emergency borrowing policies to deal with random delivery lead times . I nternational Journal of Production Research , 41 ( 13 ) : 2911 – 2931 .
   Web of Science ®Google Scholar
• De Bruyne , F. , Anderson , B. D.O. and Gevers , M. 1995 . Relating H 2- and H∞-norm for definite-dimensional systems . Systems & Control Letters , 24 : 173 – 181 .
   Web of Science ®Google Scholar
• Dejonckheere , J. , Disney , S. M. , Lambrecht , M. R. and Towill , D. R. 2003 . Measuring and avoiding the bullwhip effect: a control theoretic approach . European Journal of Operational Research , 147 : 567 – 590 .
   Web of Science ®Google Scholar
• Dejonckheere , J. , Disney , S. M. , Lambrecht , M. R. and Towill , D. R. 2004 . The impact of information enrichment on the bullwhip effect in supply chains: a control engineering perspective . European Journal of Operational Research , 153 : 727 – 750 .
   Web of Science ®Google Scholar
• Disney , S. M. , Farayn , I. , Lambrecht , M. R. , Towill , D. R. and Van de Velde , W. 2006 . Taming the bullwhip effect whilst watching customer service in a single echelon of a supply chain . European Journal of Operational Reserach , 173 : 151 – 172 .
   Web of Science ®Google Scholar
• Disney , S. M. and Grubbström , R. W. 2004 . Economic consequences of a production and inventory control policy . International Journal of Production Research , 42 ( 17 ) : 3419 – 3431 .
   Web of Science ®Google Scholar
• Disney , S. M. and Towill , D. R. 2003 . On the bullwhip and inventory variance produced by an ordering policy . Omega , 31 : 157 – 167 .
   Web of Science ®Google Scholar
• Duffy , M. 2004 . How Gillette cleaned up its supply chain . Supply Chain Management , 2004 ( 3 ) : 20 – 27 .
   Google Scholar
• Franklin , G. F. , Powell , J. D. and Workman , M. L. 1997 . Digital Control of Dynamic Systems. , 3rd edn. , Menlo Park, CA : Addison Wesley, Longman .
   Google Scholar
• Gilbert , K. 2005 . An ARIMA supply chain model . Management Science , 51 ( 2 ) : 305 – 310 .
   Web of Science ®Google Scholar
• Graves , S. A. 1999 . Single-item inventory model for a nonstationary demand process . Manufacturing & Service Operations Management , 1 ( 1 ) : 50 – 61 .
   Google Scholar
• Hoberg , K. , Bradley , J. R. and Thonemann , U. W. 2007 . Analyzing the effect of the inventory policy on order and inventory variability with linear control theory . European Journal of Operational Research , 176 ( 3 ) : 1620 – 1642 .
   Web of Science ®Google Scholar
• John , S. , Naim , M. M. and Towill , D. R. 1994 . Dynamic analysis of a WIP compensated decision support system . International Journal of Manufacturing System Design , 1 ( 4 ) : 283 – 297 .
   Google Scholar
• Jury , E. I. 1982 . Inners and Stability of Dynamic Systems, , 2nd edn. , Malabar : Krieger .
   Google Scholar
• Kapuscinski , R. , Zhang , R. Q. , Carbonneau , P. , Moore , R. and Reeves , B. 2004 . Inventory decisions in Dell's supply chain . InterFaces , 34 ( 3 ) : 191 – 204 .
   Web of Science ®Google Scholar
• Lee , H. L. 2004 . The Triple-A supply chain . Harvard Business Review , 82 ( 10 ) : 102 – 112 .
   PubMed Web of Science ®Google Scholar
• Lee , H. L. , Padmanabhan , V. and Whang , S. 1997 . Information distortion in a supply chain: the bullwhip effect . Management Science , 43 ( 4 ) : 546 – 558 .
   Web of Science ®Google Scholar
• Meyer , U. and Groover , M. P. 1972 . Multiechelon inventory systems using continuous systems analysis and simulation . AIIE Transactions , 4 ( 4 ) : 318 – 327 .
   Google Scholar
• Nahmias , S. 2005 . Production and Operations Analysis, , 5th edn. , New York, NY : McGraw-Hill .
   Google Scholar
• Nise , N. S. 2003 . Control Systems Engineering, , 4th edn. , New York, NY : Wiley .
   Google Scholar
• Segerstedt , A. 1995 . Cover-time planning, a method for calculation of material requirements . International Journal of Production Economics , 41 : 355 – 368 .
   Web of Science ®Google Scholar
• Simon , H. A. 1952 . On the application of servomechanism theory in a study of production control . Econometrica , 20 ( 2 ) : 247 – 268 .
   Web of Science ®Google Scholar
• Sterman , J. D. 1989 . Modeling managerial behavior: misconceptions of feedback in a dynamic decision making experiment . Management Science , 35 ( 3 ) : 321 – 339 .
   Web of Science ®Google Scholar
• Vassian , H. J. 1955 . Application of discrete variable servo theory to inventory control . Operations Research , 3 : 272 – 282 .
   Web of Science ®Google Scholar
• Zhang , X. 2004 . Evolution of ARMA demand in supply chains . Manufacturing & Service Operations Management , 6 ( 2 ) : 195 – 198 .
   Google Scholar
• Zipkin , P. H. 2000 . Foundations of Inventory Management , McGraw-Hill/Irwin .
   Google Scholar