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Collaborative planning, forecasting, and replenishment & firm performance: An empirical evaluation

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  • Hill, Craig A.
  • Zhang, G. Peter
  • Miller, Keith E.

Abstract

The Collaborative Planning, Forecasting, and Replenishment (CPFR) initiative is an increasingly popular paradigm that helps the supply chain better coordinate activities to serve customers with improved demand forecasting and production scheduling. CPFR provides a framework that covers a broad range of issues including demand forecasting, inventory management, production and replenishment planning, and order fulfillment. This research provides empirical evidence of the effect of CPFR adoption on a firm's financial and operational performance as compared to similar firms who have not indicated that they were implementing CPFR. Using the event study method and a COMPUSTAT database, we find significant improvements in several performance measures for firms that have adopted CPFR.

Suggested Citation

  • Hill, Craig A. & Zhang, G. Peter & Miller, Keith E., 2018. "Collaborative planning, forecasting, and replenishment & firm performance: An empirical evaluation," International Journal of Production Economics, Elsevier, vol. 196(C), pages 12-23.
    • Handle: RePEc:eee:proeco:v:196:y:2018:i:c:p:12-23
    DOI: 10.1016/j.ijpe.2017.11.012
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    References listed on IDEAS

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    Cited by:

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    3. Patel, Pankaj C. & Ojha, Divesh & Naskar, Shankar, 2022. "The effect of firm efficiency on firm performance: Evidence from the Domestic Production Activities Deduction Act," International Journal of Production Economics, Elsevier, vol. 253(C).
    4. Chang-Tang Chiang & Tun-Chih Kou & Tian-Lih Koo, 2021. "A Systematic Literature Review of the IT-Based Supply Chain Management System: Towards a Sustainable Supply Chain Management Model," Sustainability, MDPI, vol. 13(5), pages 1-18, February.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Shoukohyar, Sajjad & Seddigh, Mohammad Reza, 2020. "Uncovering the dark and bright sides of implementing collaborative forecasting throughout sustainable supply chains: An exploratory approach," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    7. Satyendra Kumar Sharma & Praveen Ranjan Srivastava & Ajay Kumar & Anil Jindal & Shivam Gupta, 2023. "Supply chain vulnerability assessment for manufacturing industry," Annals of Operations Research, Springer, vol. 326(2), pages 653-683, July.
    8. Stolze, Hannah J. & Brusco, Michael J. & Smith, Jeffery S., 2021. "Exploring the social mechanisms for variation reduction for direct store delivery (DSD) and vendor managed inventory performance: An integrated network governance and coordination theory perspective," International Journal of Production Economics, Elsevier, vol. 234(C).

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