Developing several pricing models in green supply chain under risk by Game Theory Approach

Document Type : Research Paper

Authors

1 MSc. Student in Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran

2 Assistant Prof. in Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran

3 Assistant Prof. in Mathematics, Faculty of Science, Alzahra University, Tehran, Iran

Abstract

Green supply chain management is an environmental approach in supply chain management that aims to decrease ecological risks in products’ life cycle. Closed-loop supply chain by collecting and recycling the harmful production in nature attempts to achieve this goal. In this paper, due to different strategies in collecting products, several pricing models in two-echelon closed supply chain are presented. The interactions between the manufacturer and the retailer in pricing are investigated based on Stackelberg game and the optimal decisions of manufacturer and retailer are obtained in each model. Moreover, because of the dynamic nature of the supply chain in the real world, risk factor based on the mean-variance model is considered in the closed-loop. Finally, the presented models are analyzed using a numerical example and the best model is selected by comparing the profits. Moreover, sensitivity analyses are performed on collecting rate, recycling rate and the risk aversion. Results show that the coordinating model between the manufacturer and the retailer can be an appropriate substitution in high collecting rates and low risk aversion values.



 

Keywords

References

Abdoli, G. (2011). Game Theory and Applications, University of Tehran. Tehran. (In Persian)
 
Andiç, E., Yurt, Ö. & Baltacıoğlu, T. (2012). Green supply chains: Efforts and potential applications for the Turkish market. Resources, Conservation and Recycling, 58: 50-68.
 
Barari, S. A. (2012). A decision framework for the analysis of green supply chain contracts: An evolutionary game approach. Expert systems with applications, 39(3): 2965-2976.
 
Chung, S. L. A. M. C. (2008). Optimal policy for a closed-loop supply chain inventory system with remanufacturing. Mathematical and Computer Modelling, 48(5): 867-881.
 
Esmaeili, M. & Zeephongsekul, P. (2010). Seller-buyer models of supply chain management with an asymmetric information structure. International Journal of Production Economics, 123(1): 146-154.
 
Esmaeili , M., Abad, P. L. & Aryanezhad, M. B. (2009). Seller-buyer relationship when end demand is sensitive to price and promotion. Asia-Pacific Journal of Operational Research, 26(05): 605-621. (In Persian)
 
Esmaeili, M., Aryanezhad, M. B. & Zeephongsekul, P. (2009). A game theory approach in seller--buyer supply chain. European Journal of Operational Research, 195(2): 442-448.
 
Fatemi Ghomi, M. T. (2001). Production planing and invertory control, Amirkabir University of Technology. Tehran. (In Persian)
 
Haji, R., Maarefatdoost, M. M. & Ebrahimi, B. (2009). Finding the cost of inventory in make to order supply chain under vendor managed inventory program. Industrial Management, 1(3): (In Persian)
 
Huang, M., Song, M., Lee, L. H. & Ching, W. K. (2013). Analysis for strategy of closed-loop supply chain with dual recycling channel. International Journal of Production Economics, 144(2): 510-520.
 
Karray, S. (2011). Effectiveness of retail joint promotions under different channel structures. European Journal of Operational Research, 210(3): 745-751.
 
Majumder, P. & Groenevelt, H. (2001). Competition in Remanufacturing. Production and Operations Management, 10(2): 125-141.
 
Mirghafoori, H., Morovati Sharifabadi, A. & Assadian Ardakani, F. (2012). Evaluation of suppliers risk in supply chain using combining Fuzzy VIKOR and GRA techniques. Industrial Management, 4(2): 153-178. (In Persian)
 
Nagurney, A. & Yu, M. (2012). Sustainable fashion supply chain management under oligopolistic. International Journal of Production Economics, 135(2): 532-540.
 
Pishvaee, M. & Torabi, S. (2010). A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy Sets and Systems, 2668-2683. (In Persian)
 
Sadeghi Moghadam, M. R., Momeni, M. & Nalchigar, S. (2010). Material Flow Modeling in Supply Chain Management with Genetic Algorithm Approach. Industrial Management, 1(2), 71-88. (In Persian)
 
Savaskan, R. C. & Van Wassenhove, L. N. (2006). Reverse channel design: the case of competing retailers. Management Science, 52: 1-14.
 
Savaskan, R. C., Bhattacharya, S. & Van Wassenhove, L. N. (2004). Closed-loop supply chain models with product remanufacturing. Management science, 50(2): 239-252.
 
Xiang-yun, C. & Jian-jun, Z. (2008). Pricing and coordination analysis for a closed-loop supply chain based on game theory. Wireless Communications, Networking and Mobile Computing. WiCOM'08. 4th International Conference on (pp. 1-5). IEEE.
 
Xiao, T. & Yang, D. (2008). Price and service competition of supply chains with risk-averse retailers under demand uncertainty. International Journal of Production Economics, 187-200.
 
Xie, J. & Wei, J. C. (2009). Coordinating advertising and pricing in a manufacturer--retailer channel. European Journal of Operational Research, 197(2): 785-791.
 
Xu, G., Dan, B., Zhang, X. & Liu, C. (2014). Coordinating a dual-channel supply chain with risk-averse under a two-way revenue sharing contract. International Journal of Production Economics, 171-179.
 
Zhao, R., Neighbour, G., Han, J., McGuire, M. & Deutz, P. (2012). Using game theory to describe strategy selection for environmental risk and carbon emissions reduction in the green supply chain. Journal of Loss Prevention in the Process Industries, 25(6): 927-936.
Industrial Management Journal
Volume 6, Issue 4 - Serial Number 4
January 2015
Pages 767-789

Files

Share

How to cite

Statistics