Managing Short Life-Cycle Technology Products for Agere Systems

Published Online:https://doi.org/10.1287/inte.1050.0195

References

  • Armbruster Chris A. Case study: Optimizing the supply chain for horizontal business models. (2002) . Technical report, Agere Systems, Allentown, PAGoogle Scholar
  • Carbone Jim. Worldwide outsourcing rises. (2005) . Purchasing.com, February 3. Retrieved November 3, 2005 www.purchasing.com/article/CA501253.htmlGoogle Scholar
  • Fisher Marshall, Raman Ananth. Reducing the cost of demand uncertainty through accurate response to early sales. Oper. Res. (1996) 44(1):87–99LinkGoogle Scholar
  • Fuller Wayne A.Introduction to Statistical Time Series (1996) (John Wiley and Sons, New York) Google Scholar
  • Islam Towhidul, Meade Nigel. The diffusion of successive generations of a technology: A more general model. Tech. Forecasting and Soc. Change (1997) 56(1):49–60CrossrefGoogle Scholar
  • Jorgensen Barbara. Outsourcing continues positive growth trend. Electronic Bus. (2005) 31(2):34Google Scholar
  • Kumar Uma, Kumar Vinod. Technological innovation diffusion: The proliferation of substitution models and easing the user’s dilemma. IEEE Trans. Engrg. Management (1992) 39(2):158–168CrossrefGoogle Scholar
  • Kurawarwala Abbas A., Hirofumi Matsuo. Forecasting and inventory management of short life-cycle products. Oper. Res. (1996) 44(1):131–150LinkGoogle Scholar
  • Mahajan Vijay, Muller Eitan, Bass Frank M. New product diffusion models in marketing: A review and directions for research. J. Marketing (1990) 54(1):1–26CrossrefGoogle Scholar
  • Meixell Mary J., Wu S. David. Scenario analysis of demand in a technology market using leading indicators. IEEE Trans. Semiconductor Manufacturing (2001) 14(1):65–75CrossrefGoogle Scholar
  • Miller Leslie H. Table of percentage points of Kolmogorov statistics. Amer. Statist. Association J. (1956) 51(273):111–121CrossrefGoogle Scholar
  • Neftci Salih N. Lead-lag relations, exogeneity and prediction of economic time series. Econometrica (1979) 47(1):101–114CrossrefGoogle Scholar
  • Sharif Nawaz, Kabir Chowdhury. A generalized model for forecasting technological substitution. Tech. Forecasting and Soc. Change (1976) 8(4):353–364CrossrefGoogle Scholar
  • Sharma L., Basu A., Bhargava C. A new model of innovation diffusion. J. Sci. Indust. Res. (1993) 52:151–158Google Scholar
  • Silver Edward A., Pyke David F., Peterson Rein. Inventory Management and Production Planning and Scheduling (1998) (John Wiley and Sons, New York) Google Scholar
  • Skiadas Christos. Innovation diffusion models expressing asymmetry and/or positively or negatively influencing forces. Tech. Forecasting and Soc. Change (1986) 30(4):313–330CrossrefGoogle Scholar
  • Wells John M. Seasonality, leading indicators, and alternative business cycle theories. Appl. Econom. (1999) 31(5):531–538CrossrefGoogle Scholar
  • Wu S. David, Aytac Berrin, Berger Rosemary T., Armbruster Chris A. Predicting high-tech market demands using leading indicators. (2003) . Technical report, Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, PAGoogle 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.