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Although many papers purport the significant value attributable to supply chain performance from the use of Collaborative Planning, Forecasting and Replenishment (CPFR), the question of “what are the main constructs and efficient framework for successful implementation of CPFR?” remains largely unanswered. This question will be addressed by identifying and analysing the main constructs for successful implementation of CPFR. The purpose of this paper is to attempt first to seek answers to this question. Second, to review the scope and value of CPFR using a devised state-of-the-art taxonomy for the classification of selected bibliographical references and third, to develop a conceptual framework by identifying areas which need more research.

The method underlying this paper followed the steps of a systematic literature review process outlined by Soni and Kodali (2011). The review is based on a total of 93 papers published from 1998 to 2013 on CPFR.

Four main constructs for successful implementation of CPFR have been identified: CPFR enablers, CPFR barriers, trading partner selection and IA. The findings indicate that there is a need for better understanding of the amount and level of information sharing as an important function of CPFR implementation. The paper also illustrates a number of shortcomings in the current literature and provides suggestions to guide future research on implementing CPFR in different industries.

This paper is of interest to both academicians and practitioners as it helps to better understand the concept and role of CPFR in supply chain integration and its implementation results, enablers and inhibitors. The proposed framework in this paper can be used to give insight for future research and practice.

The paper offers a framework for the review of previous research on CPFR and identifies the most important shortcomings that need to be addressed in future research. In addition, this review is both greater in scope than previous reviews and is broader in its subject focus.

The purpose of this paper is to present an operations model for retail replenishment collaboration and identifies its expected benefits and limitations for the members of a grocery supply chain.

A case study is conducted on a development project between a grocery wholesaler and two grocery product suppliers. Data are collected through semi-structured interviews with key respondents from four different companies.

Despite advances in collaborative practices in grocery supply chains, retail store replenishment management faces challenges. In particular, demand exceptions management is a challenge in the grocery industry. A replenishment model called Collaborative Buyer-Managed Forecasting (CBMF) creates a proactive planning approach and a platform for close collaboration in the supply chain. The centralised forecasting transforms retailer sales data into a plan which serves the whole supply chain by creating one-order forecast. The CBMF model facilitates efficient demand management, improves demand responsiveness and promotes better availability of products in retail stores.

CBMF provides a replenishment planning model for the whole supply chain. It is tested to a limited extent in one supply chain.

The study provides managers with a better understanding of the benefits of centralised forecasting and closer replenishment collaboration, especially during periods of exceptional demand.

A new approach for managing demand in grocery supply chains with centralised forecasting is provided.

The purpose of this paper is to provide a systematic review of the literature on Collaborative Planning, Forecasting and Replenishment (CPFR). The review emphasises the descriptors of CPFR implementation and models, as well as the impact of CPFR and other supply chain collaboration (SCC) initiatives on supply chain (SC) performance.

The systematic review includes 50 full-text papers retrieved from four databases: Emerald, EBSCO, ScienceDirect and Wiley. Rigorous and verifiable keywords, review steps and selection criteria were applied to the database and inter-coders agreement was systematically checked.

There is no consensus regarding the breadth and scope of CPFR configurations. CPFR is context-dependent and varies according to the configuration of the SC. Trust, information-communication technology and the quality of information sharing are main enablers and inhibitors of implementation.

Practitioners will benefit from insights related to the choice of SCC configurations (e.g. number of partners, nature of products and spatial complexity), the importance of trust and empowerment for SCC and the need to outweigh carefully the costs and benefits of specific SCC before implementation.

CPFR, which is considered by many to be the most advanced and the most comprehensive SCC process and has a direct impact upon SC performance. Nonetheless, efforts to synthesise the overall state of the art in CPFR have been rather limited to date. As an effort to fill this gap, this paper provides a better understanding of the role of CPFR as a determinant of SC performance. As an effort to contribute to complete the cycle of theory building based on the literature review, seven propositions for CPFR research are put forward.

Automatic replenishment systems that restock inventory based on actual demand triggers rather than relying on long‐range forecasts and layers of safety stock have been implemented in a great number of firms in recent years. Now these same firms are taking supply chain cooperation to another level through involvement in collaborative planning/forecasting/replenishment (CPFR). The results of a recent survey assessing current levels of involvement in cross‐organizational collaboration among firms utilizing automatic inventory replenishment are presented. The results provide strong support for positive associations between high levels of CPFR and implementation of operating process change and information system capabilities. Results supported only a very weak association between CPFR and effectiveness in achieving operational performance goals.

The aim of this paper is to provide an overview of contemporary supply‐chain management systems.

The paper highlights the examples of state‐of‐the‐art practice in supply‐chain management, and speculates about where this movement is headed. Some of the collaborative supply chain management products generating the most interest will also be examined.

Collaborative planning, forecasting and replenishment (CPFR) is the most recent prolific management initiative that provides supply chain collaboration and visibility. By following CPFR, companies can dramatically improve supply chain effectiveness with demand planning, synchronized production scheduling, logistic planning, and new product design. CPFR will force suppliers to innovate, building on strong one‐to‐one relationships that will drive smarter ways of doing things. Most companies and industries can benefit from CPFR. However, companies that experience variation in demand, buy or sell a product on a periodic basis, and those that deal in highly differentiated or branded products will benefit the most.

Practitioners can gain first‐hand knowledge of the CPFR model, technology and factors influencing adoption. Practitioners can also find examples of state‐of‐the‐art practice in supply‐chain management, and study some of the collaborative supply chain management products generating the most interest.

The paper is valuable to practitioners interested in implementing CPFR in their organizations.

Most collaborative SCM research has focused on the ideal situation of a manufacturer engaging with all its downstream partners. In view of extensive entry costs, lack of trust or simply non‐suitability of electronic data processing systems this, however, provides only limited support to actual problems of many companies. The paper seeks to investigate various common supply chain performance measures to show what impact increasing adoption of collaborative replenishment between manufacturer and several major customers has on each market participant.

The study uses discrete event simulation to evaluate various adjustments within the distribution frameworks of two food‐manufacturers and their major customers.

The analysis suggests that manufacturer and customers can substantially benefit from even a partial increase in demand visibility. This nevertheless can be costly since favouring some customers due to sharing a collaborative replenishment system, while others often seem to experience heavier delivery delays and declining service‐level.

The research focused on the delivery framework of the two involved manufacturers and the chosen products. Hence, research findings may differ and need to be modified before drawing conclusions for different products, companies or industries.

The analysis aims to help practitioners to identify possible opportunities and threats within an expanding collaborative SC replenishment system.

Investigating heterogeneous delivery frameworks within an emerging collaboration system has not been addressed much within prior SCM research. It aims to help mainly small‐ or medium‐sized enterprises to reveal possible advantages and drawbacks within the process of emerging with a varying number of customers from a traditional predetermined reorder‐point into a collaborative VMI/CPFR system.

Supply chain integration (or synchronisation) is to a large extent still only a promise, despite many considerable efforts by organisations and their customers and suppliers. Lack of visibility of true consumer demand and collaborative relationships based upon joint decision making remain significant barriers to the goal of supply chain integration. Collaborative planning, forecasting and replenishment (CPFR) is a strategy which promises to overcome these barriers, and seeks through joint planning, joint decision making and the development of a clearer understanding of the dynamics of the supply chain replenishment process to deliver some of the promised benefits of actual supply chain integration. Despite the existence of a detailed and comprehensive process model, and promising initial results there has not been widespread adoption of CPFR, justifying the need to revisit the process model and to further explore the inhibitors and enablers. Based upon a review of the existing literature and a comprehensive survey of participants in existing CPFR implementations, this paper identifies the critical inhibitors and makes some proposals as to how these inhibitors may be overcome.

To propose and test an augmented collaborative planning, forecasting, and replenishment (A‐CPFR) model in a retailer‐supplier context with a view to improving forecasting accuracy and then reducing the “bullwhip effect” in the supply chain.

After a literature review, the paper presents a real case in which the present authors provided assistance. The description of the case includes: case company background; an “as‐is” model analysis; a “to‐be” (CPFR) model analysis; and a description of the results and potential benefits. The paper then proposes an A‐CPFR model for the case and performs a simulation of the new model for comparison with the existing CPFR model.

The results show that the mean absolute deviation of forecasting and the inventory variance are both better in the proposed model than in the existing CPFR model. The proposed model can thus improve the accuracy of sales forecasting, reduce inventory levels, and reduce the “bullwhip effect”.

In addition to information provided by the retailer, a logistics supplier should also obtain competitors' promotional information from the market as another factor for forecasting – thus enabling timely responses to demand fluctuations.

The proposed model is an original and useful development on the existing CPFR model. It could become a reference model for the retail industry in implementing CPFR in the future.

The challenge faced by supplier companies in the grocery supply chain for implementing collaborative planning, forecasting and replenishment (CPFR) is how to get the retailer to forecast, especially when it has not been necessary before. In this paper a solution that would allow collaboration on a wide scale is presented. The forecasting approach is called “rank and share” and uses input from the retailer’s existing planning process – the category management process. The benefit of using category management as the basis is that the retailer can scale up collaboration with a large number of suppliers without increasing planning resources. For the supplier the benefit is point of sales forecasts at the time of the assortment decision. To support this collaborative forecasting process there is a need for more robust replenishment solutions, new measures to illustrate benefits, and for a distributed planning architecture and software. Potential solutions for these are also discussed in the paper.

Despite the importance of collaborative planning, forecasting, and replenishment (CPFR), its influence on supply chain innovation capability (SCIC) and supply chain performance (SCP) has not been sufficiently examined. The purpose of this paper is to examine the antecedence of SCP through CPFR and SCIC.

Through cluster and stratified random sampling, 286 responses from top managers of 1,574 Nigerian manufacturing companies were analyzed. Data analysis was performed using structural equation modeling with AMOS graphics.

The results show that SCIC has a full mediating effect on the relationship between CPFR and SCP. Specifically, CPFR has a significant relationship with both SCP and SCIC, and SCIC also relates significantly to SCP.

This study offers implications for manufacturers in developing countries in general, and in Nigeria in particular, by providing a guideline on how to improve SCP through CPFR.

The paper contributes to the limited studies on CPFR and SCP by extending this line of study into the realm of innovation capability and innovation. It integrates the social exchange theory and the dynamic capabilities theory to examine the collaborative processes of CPFR in the supply chain context. This study stressed the importance of boundary theoretical spanning by extending CPFR and SCP into the domain of innovation capability.