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Forecasting the forecastability quotient for inventory management

Author

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  • Hill, Arthur V.
  • Zhang, Weiyong
  • Burch, Gerald F.

Abstract

This research develops and empirically tests a model for estimating the economic advantage of using a time phased order point system (TPOP) with time series forecasting rather than a simple reorder point system in an independent demand inventory management context. We define the forecastability quotient (Q) to support this economic analysis. We implement TPOP in our empirical analysis via double exponential smoothing with a damped trend, and implement ROP through a simple moving average.

Suggested Citation

  • Hill, Arthur V. & Zhang, Weiyong & Burch, Gerald F., 2015. "Forecasting the forecastability quotient for inventory management," International Journal of Forecasting, Elsevier, vol. 31(3), pages 651-663.
  • Handle: RePEc:eee:intfor:v:31:y:2015:i:3:p:651-663
    DOI: 10.1016/j.ijforecast.2014.10.006
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    References listed on IDEAS

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    Cited by:

    1. Gardner, Everette Shaw & Acar, Yavuz, 2016. "The forecastability quotient reconsidered," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1208-1211.
    2. Joanna Bruzda, 2020. "Multistep quantile forecasts for supply chain and logistics operations: bootstrapping, the GARCH model and quantile regression based approaches," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 309-336, March.
    3. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.

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