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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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    as
    1. Novy-Marx, Robert, 2013. "The other side of value: The gross profitability premium," Journal of Financial Economics, Elsevier, vol. 108(1), pages 1-28.
    2. Parsa, Payam & Rossetti, Manuel D. & Zhang, Shengfan & Pohl, Edward A., 2017. "Quantifying the benefits of continuous replenishment program for partner evaluation," International Journal of Production Economics, Elsevier, vol. 187(C), pages 229-245.
    3. Mark J. Cotteleer, 2006. "An Empirical Study of Operational Performance Parity Following Enterprise System Deployment," Production and Operations Management, Production and Operations Management Society, vol. 15(1), pages 74-87, March.
    4. C. Ranganathan & Carol V. Brown, 2006. "ERP Investments and the Market Value of Firms: Toward an Understanding of Influential ERP Project Variables," Information Systems Research, INFORMS, vol. 17(2), pages 145-161, June.
    5. Yossi Aviv, 2002. "Gaining Benefits from Joint Forecasting and Replenishment Processes: The Case of Auto-Correlated Demand," Manufacturing & Service Operations Management, INFORMS, vol. 4(1), pages 55-74, December.
    6. Charles J. Corbett & María J. Montes-Sancho & David A. Kirsch, 2005. "The Financial Impact of ISO 9000 Certification in the United States: An Empirical Analysis," Management Science, INFORMS, vol. 51(7), pages 1046-1059, July.
    7. Dong, Yan & Xu, Kefeng, 2002. "A supply chain model of vendor managed inventory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 38(2), pages 75-95, April.
    8. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    9. Anantaram Balakrishnan & Joseph Geunes & Michael S. Pangburn, 2004. "Coordinating Supply Chains by Controlling Upstream Variability Propagation," Manufacturing & Service Operations Management, INFORMS, vol. 6(2), pages 163-183, July.
    10. Ramanathan, Usha & Gunasekaran, Angappa, 2014. "Supply chain collaboration: Impact of success in long-term partnerships," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 252-259.
    11. Kamalapur, Raj & Lyth, David & Houshyar, Azim, 2013. "Benefits Of Cpfr And Vmi Collaboration Strategies: A Simulation Study," Journal of Operations and Supply Chain Management (JOSCM), Fundação Getulio Vargas, Escola de Administração de Empresas de São Paulo (FGV EAESP), vol. 6(2), December.
    12. Sari, Kazim, 2008. "On the benefits of CPFR and VMI: A comparative simulation study," International Journal of Production Economics, Elsevier, vol. 113(2), pages 575-586, June.
    13. Gonul Kochan, Cigdem & Nowicki, David R. & Sauser, Brian & Randall, Wesley S., 2018. "Impact of cloud-based information sharing on hospital supply chain performance: A system dynamics framework," International Journal of Production Economics, Elsevier, vol. 195(C), pages 168-185.
    14. Disney, S. M. & Naim, M. M. & Potter, A., 2004. "Assessing the impact of e-business on supply chain dynamics," International Journal of Production Economics, Elsevier, vol. 89(2), pages 109-118, May.
    15. Gérard P. Cachon & Marshall Fisher, 2000. "Supply Chain Inventory Management and the Value of Shared Information," Management Science, INFORMS, vol. 46(8), pages 1032-1048, August.
    16. Jin Kyung Kwak & Srinagesh Gavirneni, 2015. "Impact of information errors on supply chain performance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(2), pages 288-298, February.
    17. Daugherty, Patricia J. & Richey, R. Glenn & Roath, Anthony S. & Min, Soonhong & Chen, Haozhe & Arndt, Aaron D. & Genchev, Stefan E., 2006. "Is collaboration paying off for firms?," Business Horizons, Elsevier, vol. 49(1), pages 61-70.
    18. Yossi Aviv, 2001. "The Effect of Collaborative Forecasting on Supply Chain Performance," Management Science, INFORMS, vol. 47(10), pages 1326-1343, October.
    19. Yossi Aviv, 2007. "On the Benefits of Collaborative Forecasting Partnerships Between Retailers and Manufacturers," Management Science, INFORMS, vol. 53(5), pages 777-794, May.
    20. Cannella, Salvatore & Framinan, Jose M. & Bruccoleri, Manfredi & Barbosa-Póvoa, Ana Paula & Relvas, Susana, 2015. "The effect of Inventory Record Inaccuracy in Information Exchange Supply Chains," European Journal of Operational Research, Elsevier, vol. 243(1), pages 120-129.
    21. Kevin B. Hendricks & Vinod R. Singhal, 1997. "Does Implementing an Effective TQM Program Actually Improve Operating Performance? Empirical Evidence from Firms That Have Won Quality Awards," Management Science, INFORMS, vol. 43(9), pages 1258-1274, September.
    22. Cannella, Salvatore & Dominguez, Roberto & Framinan, Jose M., 2017. "Inventory record inaccuracy – The impact of structural complexity and lead time variability," Omega, Elsevier, vol. 68(C), pages 123-138.
    23. Holweg, Matthias & Disney, Stephen & Holmström, Jan & Småros, Johanna, 2005. "Supply Chain Collaboration:: Making Sense of the Strategy Continuum," European Management Journal, Elsevier, vol. 23(2), pages 170-181, April.
    24. Gu, Qiannong & Jitpaipoon, Thawatchai & Yang, Jie, 2017. "The impact of information integration on financial performance: A knowledge-based view," International Journal of Production Economics, Elsevier, vol. 191(C), pages 221-232.
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    3. 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.
    4. 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.
    5. 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).
    6. Omoruyi Osayuwamen, 2018. "Competitiveness Through the Integration of Logistics Activities in SMEs," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, vol. 63(3), pages 15-32, December.
    7. 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).
    8. 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.

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