AGRICULTURAL-FOOD SUPPLY CHAIN DESIGN WITH THE CPFR APPROACH: AN APPLICATION

Year 2022, Volume: 9 Issue: 2, 63 - 78, 30.06.2022

Atiye Tumenbatur Mehmet Tanyas Emre Cakmak

https://doi.org/10.17261/Pressacademia.2022.1554

Abstract

Purpose- Agri-food supply chain is an important supply chain for our country in terms of both cost and food safety. In this context, the selection
of suppliers, manufacturers and logistics companies that make up the chain and the relations between them are extremely important, and the
quality of the companies that make up the chain must be high in order to create effective and efficient supply chains. In this study, the author
aimed to conduct a research on the creation of an integrated supply chain with a collaborative approach. The framework of the study is limited
to the producers, suppliers and logistics enterprises, which are the main actors in the agriculture-food value chain.
Methodology- The author proposes an integrated methodology for collaborative work in the agri-food supply chain. Within the framework of the
methodology created within the framework of the CPFR method, the chains that enable the stakeholders included in the system to deliver the
product to the demand points at the most affordable cost were determined by the linear programming model. In the second stage, meeting the
demands created with random numbers was simulated. Finally, the suitability of the model was tested with the data of a company.
Findings- The findings show that the product moves less if the stakeholders in the chain are correctly matched within the framework of the
collaborative approach. In addition, it has been seen that the needs of both demand points are met thanks to the correct match. In addition, a
positive effect has been achieved in the use of the stakeholders' capacities.
Conclusion- This article is one of the first studies that looks at the agri-food supply chain in an integrated way and evaluates the processes within
the framework of a collaborative approach. The study also contributes to improvement in the sector in terms of including the stakeholders involved
in the collaborative process into the system according to the criteria determined.

Keywords

OR in agriculture, agri-food, agri-food supply chain, holistic design, CPFR

References

• Ahumada, O., ve Villalobos, J. (2009). Application of planning models in the agri-food supply chain: a review. European Journal of Operational Research, 1-20.
• Ahumada, O., & Villalobos, J. (2011). Operational model for planning the harvest and distribution of perishable agricultural products. International Journal of Production Economics, 677-687
• Aramyan, L., Vander Vorst, A. O. and Kooten, O. (2007). Performance measurement in agri-food supply chains: a case study. Supply Chain Management: An International (12/4): 304-315.
• Behzadi, G., O'sullivan, M. J., Olsen, T. L., & Zhang, A. (2017). Agribusiness supply chain risk management: a review of quantitative decision models. Omega, 1-22.
• Chen, J., & Y. Haihong. (2013). Performance simulation and optimization agricultural supply chains. 2013 International Conference on Information Science and Cloud Computing.
• Chen, W., Li, J., & Jin, X. (2016). The replenishment policy of agri-products with stochastic demand in integrated agricultural supply chains. Expert System with Applications, 55-66.
• Fang Du, X., & Leung, S. C. (2009). Procurement of agricultural products using the CPFR approach. Supply Chain Management: An International Journal, 253-258.
• Ferreira, J., Batalha, M., & Domingos, J. (2016). Integrated planning model for citrus agribusiness system dynamics. Computers and Electronics in Agriculture, 1-11.
• Folinas, D., Aidonis, D., Triantafillou, D., and Malindretos, G. (2013). Exploring the greening of the food supply chain with lean thinking techniques. 6th international conference on information and communication technologies in agriculture, 416-424.
• Gigler, J., Hendrix, E., Heesen, R., Hazelkamp, V., & Meerdink, G. (2002). On optimizations of agri chains by dynamic programming. European Journal of Operational Research 139, 613-625.
• Lamsal, K., Jones, P., & Thomas, B. (2016). harvest logistics in agricultural systems with multiple, independent producers and no on-farm storage. Computers & Industrial Engieneering 91, s. 129-138.
• Saaty, T. L. 1977. A Scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology.
• Sanjaya, S., & Perdana, T. (2015). Logistics system model development on supply chain management of tomato commodities for structured market. Procedia Manufacturing, 4, 513-520.
• Tsolakis, K., Keremydas, A., Toka, K., Aidonis, A., & Iakavou, T. (2014). Agrifood supply chain management: a compressive hierarchical decisionmaking framework and critical taxonomy. Biosystem Engineering, 47-64.
• Zhong, B., Yang, F., & Chen, Y. (2015). Information empowers vegetable supply chain: a study of information needs and sharing among farmers and vendors. Computers and Electronics in Agriculture, 81-90