Decision Analysis and Coordination in Green Supply Chains with Stochastic Demand

Reference

K. Wu, B. De Schutter, J. Rezaei, and L. Tavasszy, "Decision analysis and coordination in green supply chains with stochastic demand," International Journal of Systems Science: Operations & Logistics, vol. 10, no. 1, p. 2208277, 2023.

Abstract

Consumer goods supply chains are intensifying their efforts to develop and offer green products, in order to seize new business opportunities and improve profitability. A specific type of green products concerns marginal and development cost-intensive green products (MDIGPs), like electric vehicles. As greening these products affects both marginal and development costs, their design presents special challenges, especially within the context of uncertain demand. This paper formulates the joint product pricing-ordering-greening decision problem in the supply chains of MDIGPs and examines the impact of demand uncertainty. A sequential game-theoretic framework is developed, providing analytical expressions of the optimal solutions for the stochastic model. A bargaining game on the wholesale price between supply chain members is proposed to coordinate decisions. We compare the optimal decisions numerically in the stochastic and deterministic cases and find that, although demand uncertainty creates inefficiency in the green supply chain, it might positively impact product greenness and prices. Given the impact of the unit-variable greening costs of MDIGPs, we are able to identify cases where - contrary to common belief - demand uncertainty does not always lead firms to reduce greenness or increase prices.

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BibTeX

@article{WuDeS:23-004,
   author  = {Wu, Kailan and De Schutter, Bart and Rezaei, Jafar and Tavasszy,
              L{\'{o}}r{\'{a}}nt},
   title   = {Decision Analysis and Coordination in Green Supply Chains with
              Stochastic Demand},
   journal = {International Journal of Systems Science: Operations \&
              Logistics},
   volume  = {10},
   number  = {1},
   pages   = {2208277},
   year    = {2023}
   }

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