Developing a Pricing Model in a Retail and Chain Dual-Channel Supply Chain with Discounts and a Revenue-Sharing Contract

Document Type : Research/ Original/ Regular Article

Authors

1 Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran.

2 university alzahra

3 Department of Industrial Engineering, Faculty of Engineering, Alzahra University

Abstract

Most organizations use different channels to offer products and services in order to increase their market share and attract more customers. In a supply chain with more than one sales channel, product pricing is a critical issue in the decision-making process. Proper pricing can be very effective in reducing the conflict between channels and increasing the profitability of existing channels. In this paper, a pricing strategy between the dual retail and chain channels is presented to maximize profits by considering a discount in the chain channel and a revenue sharing contract between the manufacturer and the chain stores. The input parameters of the problem are adjusted using the Taguchi method and solved by the particle swarm metaheuristic algorithm in order to validate the model. Regarding the short solution time of the proposed algorithm, it has a good quality and efficiency in comparison to GAMS software. In addition, the gap of the objective value obtained by the proposed algorithm is less than 1% compared to the GAMS output. The results also show that the potential demand of the retail channel has a higher impact on the profit of the supply chain, in comparison to other parameters.

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References

  • E. Cressman, “Value-based pricing: A state-of-the-art review,” Handbook of business-to-business marketing, pp. 246–274, 2012.
  • M. Noble and T. S. Gruca, “Industrial pricing: Theory and managerial practice,” Marketing Science, vol. 18, no. 3, pp. 435-454, 1999.
  • Hinterhuber and S. M. liozu, “is it time to rethink your pricing strategy? ,” MIT Sloan Management Review, pp. 69-77, 2012.
  • R. Nasiri, H. Deymeh, B. Karimi, and E. Miandoabchi, “Incorporating sales and marketing considerations into a competitive multi-echelon distribution network design problem with pricing strategy in a stochastic environment,” Journal of Retailing and Consumer Services, vol. 62, Article ID 102646, 2021.
  • R. Nasiri, M. Kalantari, and B. Karimi, “Fast-moving consumer goods network design with pricing policy in an uncertain environment with correlated demands,” Computers & Industrial Engineering, vol.153, Article ID 106997, 2021.
  • C. Giri, A. Chakraborty, and T. Maiti, “Pricing and return product collection decisions in a closed-loop supply chain with dual-channel in both forward and reverse logistics,” Journal of manufacturing systems, vol. 42, pp. 104-123, 2017.
  • Yang, P. Hu, F. Zhao, and C. Hu, “Customer returns model in a dual-channel supply chain,” Journal of Modelling in Management, vol. 10,no. 3, pp. 360-379, 2015.
  • Batarfi, M. Y. Jaber, and S. M. Aljazzar, “A profit maximization for a reverse logistics dual-channel supply chain with a return policy,” Computers & Industrial Engineering, vol. 106, pp. 58-82, April 2017.
  • Zhao, X. Hou, Y. Guo, and J. Wei, “Pricing policies for complementary products in a dual-channel supply chain,” Applied mathematical modelling, vol. 49, pp. 437-451,2017.
  • Sha and S. Zheng, “Research on Pricing Strategy of Three-echelon Dual-channel Supply Chain under Market Equilibrium,” In Journal of Physics: Conference Series, 1910, Article ID 012049, 2021.
  • Zhang and C. Wang, “Dynamic pricing strategy and coordination in a dual-channel supply chain considering service value,” Applied Mathematical Modelling, vol. 54, pp. 722-742, 2018.
  • Ma, Z. Cheng and S. Xu, “A game theoretic approach for improving environmental and economic performance in a dual-channel green supply chain,” Sustainability, vol. 10, no. 6, 2018.
  • Liu, “Pricing and coordination strategies of dual-channel green supply chain considering products green degree and channel environment sustainability,” International Journal of Sustainable -Engineering,vol. 12, no. 6, pp.  404-414, 2018.
  • Wang and X. Sun, “Dynamic vs. static wholesale pricing strategies in a dual-channel green supply chain,” Complexity, vol. 2019, Article ID 8497070, 2019.
  • Cao, T. You, C. Liu, and J. Zhao, “Pricing and Channel Coordination in Online-to-Offline Supply Chain Considering Corporate Environmental Responsibility and Lateral Inventory Transshipment,” Mathematics, vol. 9, no. 20, 2021.
  • Hu, S. Feng, J. Liu, A. Yang, G. Wang, and H. Xu, “Return Mode Selection and Pricing Strategy for a Dual-Channel Retailer,” Discrete Dynamics in Nature and Society, 2020, Article ID 5261486, 2020.
  • Yang, Y. Si, J., Zhang, Liu, and A. Appolloni, “Coordination mechanism of dual-channel supply chains considering retailer innovation inputs,” Sustainability, vol. 13, no. 2, 2021.
  • Xu, B. Dan, X. Zhang, and C. Liu, “Coordinating a dual-channel supply chain with risk-averse under a two-way revenue sharing contract,” International Journal of Production Economics, vol. 147, pp. 171-179, 2014.
  • Qiu, L. Hou, Y. Sun, M. Sun, and Y. Sun, “Joint pricing, ordering and order fulfillment decisions for a dual-channel supply chain with demand uncertainties: A distribution-free approach,” Computers & Industrial Engineering, vol. 160, Article ID 107546, 2021.
  • Peymandoost, A. Nakhai, and R. Maihami, “Joint Inventory Control & Pricing for Deteriorating Items in a Two-Echelon Supply Chain,” Journal of Supply Chain Management, vol. 15, no. 40, pp. 66-56, 2013. (in Persian)
  • Biranvand and M. Nazari, “Identification Affecting Factors of Price Discount Threshold: Meta Synthesis,” Journal of Business Management, vol.12, no.1, pp. 44-63, 2020. (in Persian)
  • Seydanlou and N. Javadian, “Solve the green routing problem of developed heterogeneous vehicles using particle swarm optimization and keshtel algorithm,” 1st National Conference on Optimization and new Solution Methods, no.1, pp. 139-152, 2021. (In Persian)

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History

  • Receive Date: 05 March 2022
  • Revise Date: 18 May 2022
  • Accept Date: 28 May 2022
  • Publish Date: 22 May 2022

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