Research synthesis in collaborative planning forecast and replenishment
Abstract
Purpose
The purpose of this research synthesis is to gather and integrate findings on Collaborative Planning Forecast and Replenishment (CPFR) as a business process and as a management practice; and to assemble quantitative evidence of its impact on supply chain (SC) performance.
Design/methodology/approach
The researchers independently conducted a systematic review of 629 abstracts and 47 full-text papers. Original keywords were applied to four key electronic databases for operations management and information systems. Rigorous and verifiable selection criteria governed inter-coders reliability, review of steps and exclusion of papers. Resource and dependency-based view of the firm, contingency research and maturity models informed the analysis.
Findings
There is not a single “blueprint” for CPFR. Competing models emphasize the need for “trust and confidence” and reliable data systems. The type of products, scope, spatial diversity and number of partners in the network are important contextual variables. Firm resources that are unique and advantages from multiple and reciprocal dependencies are powerful levers. There is no consensus on maturity model and on required investment in data and communication systems.
Practical implications
Practical implications are implementation related: cost-benefit analysis and simulations should precede full-scale collaboration. There is a consensus on starting CPFR small and expanding gradually.
Originality/value
This synthesis applies a rigorous review method and attempts to assemble the dispersed literature in one study, utilizing explanatory operations management and information systems theories.
Keywords
Acknowledgements
The authors gratefully acknowledge MCT/CNPq (Research Project No. 307996/2011-5), CAPES/DFG (BRAGECRIM Research Project No. 010/09) and CAPES/DAAD (PROBRAL).
Citation
Márcio Tavares Thomé, A., Luis Hollmann, R. and Scavarda do Carmo, L.F.R.R. (2014), "Research synthesis in collaborative planning forecast and replenishment", Industrial Management & Data Systems, Vol. 114 No. 6, pp. 949-965. https://doi.org/10.1108/IMDS-03-2014-0085
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited