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Collaborative forecasting in the food supply chain: A conceptual framework

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  • Eksoz, Can
  • Mansouri, S. Afshin
  • Bourlakis, Michael

Abstract

This paper develops a conceptual framework for factors involved in collaborative forecasting in food supply chains. Although the existing literature has analyzed many theoretical perspectives in relation to collaborative forecasting in the food supply chain, there is a scarcity of research examining how manufacturers and retailers conduct long-term and accurate collaborative forecasting for seasonal, perishable, promotional, and newly launched products. In the proposed framework, we focus on the collaborative forecasts of manufacturers and retailers. Through a systematic review of the literature, we have identified trends, gaps and areas for future research involving partners׳ integration, information sharing and forecasting process in the supply chain. The review reveals that partners׳ integration is a key requirement for collaborative forecasting while type and quality of information shared are critical for forecasts. Moreover, forecasting strategies of manufacturers and retailers play a pivotal role for consensus forecasts while the role of forecast horizon and frequency should not be neglected. Finally, the impact of forecasters is critical in addition to group forecasting techniques applied to generate consensus forecasts in collaborative forecasting. Ten propositions are developed for empirical testing. The proposed framework may serve as a guide for practitioners when initiating and conducting long-term collaborative forecasting partnerships. The research is limited to examining the manufacturer–retailer dyadic collaboration, and focuses on specific food product categories.

Suggested Citation

  • Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael, 2014. "Collaborative forecasting in the food supply chain: A conceptual framework," International Journal of Production Economics, Elsevier, vol. 158(C), pages 120-135.
  • Handle: RePEc:eee:proeco:v:158:y:2014:i:c:p:120-135
    DOI: 10.1016/j.ijpe.2014.07.031
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    2. Gunasekaran, Angappa & Irani, Zahir & Choy, King-Lun & Filippi, Lionel & Papadopoulos, Thanos, 2015. "Performance measures and metrics in outsourcing decisions: A review for research and applications," International Journal of Production Economics, Elsevier, vol. 161(C), pages 153-166.
    3. Fildes, Robert & Goodwin, Paul & Onkal, Dilek, 2015. "Information use in supply chain forecasting," MPRA Paper 66034, University Library of Munich, Germany.
    4. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.

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