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Stein-Rule Combination Forecasting on RFID Based Supply Chain

Author

Listed:
  • WenJie Wang

    (Glorious Sun School of Business and Management, Donghua University, 1882 Yan An Xi Lu, Shanghai 200051, P. R. China)

  • Qi Xu

    (Glorious Sun School of Business and Management, Donghua University, 1882 Yan An Xi Lu, Shanghai 200051, P. R. China)

  • Dandan Fan

    (Glorious Sun School of Business and Management, Donghua University, 1882 Yan An Xi Lu, Shanghai 200051, P. R. China)

Abstract

Radio frequency identification technology has been applied in many fields, especially in logistics operations and supply chain management. Supply chain coordination among partners, which is the core part of supply chain management, can be more practical and effective through sharing real-time product data along the supply chain tracked by RFID technology. This paper focused on the study of the supply chain collaborative forecasting process by sharing RFID real-time data. The collaborative forecasting process among supply chain partners based on the sharing RFID product data is discussed for product demand decision in the paper at first. Then, a Stein-rule combination-forecasting model is proposed to integrate the forecasting knowledge and coordinate forecasting process between the retailers and manufactures shared the RFID data in the supply chain. Moreover, in order to enhance collaborative forecasting precision an error correction combination-forecasting model is discussed. Finally, the outcomes of mathematics simulation verify that the forecast combinations with Stein-rule estimation rules and error correction algorithms are effective to improve forecast precision and coordinate RFID-based supply chain.

Suggested Citation

  • WenJie Wang & Qi Xu & Dandan Fan, 2018. "Stein-Rule Combination Forecasting on RFID Based Supply Chain," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(02), pages 1-13, April.
    • Handle: RePEc:wsi:apjorx:v:35:y:2018:i:02:n:s0217595918400018
    DOI: 10.1142/S0217595918400018
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    References listed on IDEAS

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