The revenue and preservation-technology investment sharing contract in the fresh-product supply chain:A game-theoretic approach

Document Type : conference paper

Authors

School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract

This research considers a fresh-product supply chain consisting of a single-buyer, a single-supplier for deteriorating products where the market demand is dependent on the retail price, fresh rate, and remaining rate. Firstly, in a competitive model, the primary decision variables (i.e., the supplier's wholesale price and preservation-technology investment and also buyer's order quantity and retail price) are determined. Afterward, a centralized model is developed to optimize the whole system so that all the players of supply chain reach equilibrium. Then, a combined incentive mechanism based on revenue and preservation-technology investment sharingis designed to motivate the members to participate in the centralized model. Finally, the proposed models are accreditedwith the data set of a real-life case study. The results indicate that the designed contract is capable of coordinating the fresh-product supply chain under a wide variety of sharing rate. Moreover, the transactions in the centralized mode will have less Lost-of-Profit than the decentralized ones while it also has a higher whole channel's profit.

Keywords

Main Subjects


Affisco, J. F., Paknejad, M. J., & Nasri, F. (2002). Quality improvement and setup reduction in the joint economic lot size model. European Journal of Operational Research142(3), 497-508.
 
Ala-Harja, H., & Helo, P. (2015). Reprint of “Green supply chain decisions–Case-based performance analysis from the food industry”. Transportation Research Part E: Logistics and Transportation Review74, 11-21.
 
Amad, M. J. (2012). Agriculture, Poverty and Reform in Iran (RLE Iran D). Routledge.
 
Ameknassi, L., Aït-Kadi, D., & Rezg, N. (2016). Integration of logistics outsourcing decisions in a green supply chain design: a stochastic multi-objective multi-period multi-product programming model. International Journal of Production Economics182, 165-184.
 
Bisi, A., & Dada, M. (2007). Dynamic learning, pricing, and ordering by a censored newsvendor. Naval Research Logistics (NRL)54(4), 448-461.
 
Buisman, M. E., Haijema, R., & Bloemhof-Ruwaard, J. M. (2017). Discounting and dynamic shelf life to reduce fresh food waste at retailers. International Journal of Production Economics.
 
Cao, E., Zhou, X., & Lϋ, K. (2015). Coordinating a supply chain under demand and cost disruptions. International Journal of Production Research53(12), 3735-3752.
 
Cai, X., Chen, J., Xiao, Y., Xu, X., & Yu, G. (2013). Fresh-product supply chain management with logistics outsourcing. Omega41(4), 752-765.
 
     Cai, X., Chen, J., Xiao, Y., & Xu, X. (2010). Optimization and coordination of fresh product supply chains with freshness‐keeping effort. Production and Operations Management19(3), 261-278.
 
Chen, F. (2007). Auctioning supply contracts. Management Science53(10), 1562-1576.
 
Chen, R. R., Roundy, R. O., Zhang, R. Q., & Janakiraman, G. (2005). Efficient auction mechanisms for supply chain procurement. Management Science51(3), 467-482.
 
     Choi, C. Y., Takekawa, J. Y., Liu, Y., Wikelski, M., Heine, G., Prosser, D. J., ... & Xiao, X. (2016). Tracking domestic ducks: A novel approach for documenting poultry market chains in the context of avian influenza transmission. Journal of integrative agriculture15(7), 1584-1594.
 
Cook, R. (1990). Challenges and opportunities in the US fresh produce industry. Journal of Food Distribution Research21(1), 67-74.
 
Dye, C. Y., & Yang, C. T. (2016). Optimal dynamic pricing and preservation technology investment for deteriorating products with reference price effects. Omega62, 52-67.
 
Evans, D. (2012). Beyond the throwaway society: ordinary domestic practice and a sociological approach to household food waste. Sociology46(1), 41-56.
 
Fouayzi, H., Caswell, J. A., & Hooker, N. H. (2006). Motivations of fresh-cut produce firms to implement quality management systems. Review of agricultural economics28(1), 132-146.
 
Govindan, K., Popiuc, M. N., & Diabat, A. (2013). Overview of coordination contracts within forward and reverse supply chains. Journal of Cleaner Production47, 319-334.
 
Govindasamy, R., & Thornsbury, S. (1999). Theme Overview: Fresh Produce Marketing: Critical Trends and Issues.
 
Gustavsson, J., Cederberg, C., Sonesson, U., Otterdijk, R. V., & Meybeck, A. Global food losses and food waste [recurso electrónico]: extent, causes and prevention.
 
Hsu, P. H., Wee, H. M., & Teng, H. M. (2010). Preservation technology investment for deteriorating inventory. International Journal of Production Economics124(2), 388-394.
 
Jin, W., & Luo, J. (2017). Optimal inventory and insurance decisions for a supply chain financing system with downside risk control. Applied Stochastic Models in Business and Industry33(1), 63-80.
 
Khojaste Nejad, A. (2011). Studying the difficulties of flower and plants producers in Iran and giving solutions.
 
Lee, H. H. (2008). The investment model in preventive maintenance in multi-level production systems. International Journal of Production Economics112(2), 816-828.
 
Li, J. C., Zhou, Y. W., & Huang, W. (2017). Production and procurement strategies for seasonal product supply chain under yield uncertainty with commitment-option contracts. International journal of production economics183, 208-222.
 
LI, G. Q., XU, S. W., LI, Z. M., SUN, Y. G., & DONG, X. X. (2012). Using quantile regression approach to analyze price movements of agricultural products in china. Journal of Integrative Agriculture11(4), 674-683.
 
Monier, V., Mudgal, S., Escalon, V., O’Connor, C., Gibon, T., Anderson, G., ... & Morton, G. (2010). Preparatory study on food waste across EU 27. European Commission, Directorate-General for the Environment.
 
Nahmias, S. (1977). On ordering perishable inventory when both demand and lifetime are random. Management Science24(1), 82-90.
 
Nakandala, D., Lau, H., & Zhao, L. (2017). Development of a hybrid fresh food supply chain risk assessment model. International Journal of Production Research55(14), 4180-4195.
 
Papargyropoulou, E., Lozano, R., Steinberger, J. K., Wright, N., & bin Ujang, Z. (2014). The food waste hierarchy as a framework for the management of food surplus and food waste. Journal of Cleaner Production76, 106-115.
 
Petruzzi, N. C., & Dada, M. (1999). Pricing and the newsvendor problem: A review with extensions. Operations research47(2), 183-194.
 
Pishvaee, M. S., Farahani, R. Z., & Dullaert, W. (2010). A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Computers & operations research37(6), 1100-1112.
 
Riasi, A. (2015). Barriers to international supply chain management in Iranian flower industry. Management Science Letters5(4), 363-368.
 
Saha, S., Nielsen, I., & Moon, I. (2017). Optimal retailer investments in green operations and preservation technology for deteriorating items. Journal of Cleaner Production140, 1514-1527.
 
Sana, S. S. (2012). A collaborating inventory model in a supply chain. Economic Modelling29(5), 2016-2023.
 
S Shukla, M., & Jharkharia, S. (2013). Agri-fresh produce supply chain management: a state-of-the-art literature review. International Journal of Operations & Production Management33(2), 114-158.
 
Su, J., Wu, J., & Liu, C. (2014). Research on coordination of fresh produce supply chain in big market sales environment. The Scientific World Journal2014.
 
XIAO, Y. B., Jian, C. H. E. N., & XU, X. L. (2008). Fresh product supply chain coordination under CIF business model with long distance transportation. Systems Engineering-Theory & Practice28(2), 19-34.
 
Yu, J., & Zhang, S. (2011). Optimal trade policy in tariff games with inside money. Economic Modelling28(4), 1604-1614.