TY - JOUR
T1 - Pricing policy in green supply chain design
T2 - the impact of consumer environmental awareness and green subsidies
AU - Shoaeinaeini, Maryam
AU - Govindan, Kannan
AU - Rahmani, Donya
N1 - Funding Information:
A considerable growth in public environmental awareness has made the governments and lawmakers to become more vigilant toward remanufacturing policies in CLSC networks (Recycling Laws and Regulations ; Waste Electrical and Electronic Equipment ; Ji et al. ; Yeow and Loo ). In this regard, the government has posed some incentive policies to encourage qualified manufacturers to implement remanufacturing and recycling their products, e.g., the WEEE Directive in the EU (Directive ), and "Administrative Measures on Collection and Use of Waste Electrical and Electronic Products Processing Funds" in China in 2012 (Zhang et al. ). In Australia, Australian and Victorian Governments under the federal Recycle Victoria Infrastructure Fund (RVIF) provided $28 M funding grants to address infrastructure gaps for the processing and remanufacture of glass, paper, cardboard and plastics to increase the capacity for recycling and improve the quality of available materials (Recent Government Recycling And Waste Management Initiatives ). Among the supportive government policies, the fund policy can promote more the recycling and remanufacturing mode (Zhang et al. ).
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2022/9
Y1 - 2022/9
N2 - This paper presents a mixed-integer non-linear programming model to design a green closed-loop supply chain comprising hybrid plants, hybrid collection centers, customer zones, secondary markets, and disposal centers. To ensure a smooth reverse flow, our model determines a return rate for each customer zone with respect to the consumers’ environmental awareness and the optimal acquisition price offered for returned products. Considering the environmental awareness levels and optimal green levels, specific cost and price functions for green products are proposed. Further, government subsidy as a financial incentive for manufacturers is considered to make the model more realistic and challenging. The effectiveness of the proposed model is analyzed by an illustrative example generated based on an Iranian straw factory. Beneficial managerial insights are obtained by conducting several sensitivity analyses. Further, the illustrative example and several generated examples in all scales are assessed by Sine Cosine Crow Search Algorithm using an efficient solution representation based on the priority-based encoding. As there is no benchmark available in the related literature to validate the results of Sine Cosine Crow Search Algorithm and to evaluate its performance, Particle Swarm Optimization and Genetic Algorithm are utilized to solve the examples. Finally, the obtained results of different metaheuristic algorithms and the exact solution are compared in terms of the CPU time and the objective function value.
AB - This paper presents a mixed-integer non-linear programming model to design a green closed-loop supply chain comprising hybrid plants, hybrid collection centers, customer zones, secondary markets, and disposal centers. To ensure a smooth reverse flow, our model determines a return rate for each customer zone with respect to the consumers’ environmental awareness and the optimal acquisition price offered for returned products. Considering the environmental awareness levels and optimal green levels, specific cost and price functions for green products are proposed. Further, government subsidy as a financial incentive for manufacturers is considered to make the model more realistic and challenging. The effectiveness of the proposed model is analyzed by an illustrative example generated based on an Iranian straw factory. Beneficial managerial insights are obtained by conducting several sensitivity analyses. Further, the illustrative example and several generated examples in all scales are assessed by Sine Cosine Crow Search Algorithm using an efficient solution representation based on the priority-based encoding. As there is no benchmark available in the related literature to validate the results of Sine Cosine Crow Search Algorithm and to evaluate its performance, Particle Swarm Optimization and Genetic Algorithm are utilized to solve the examples. Finally, the obtained results of different metaheuristic algorithms and the exact solution are compared in terms of the CPU time and the objective function value.
KW - Acquisition price
KW - Consumer environmental awareness
KW - Government subsidy
KW - Green supply chain
KW - Return rate
U2 - 10.1007/s12351-021-00680-z
DO - 10.1007/s12351-021-00680-z
M3 - Journal article
AN - SCOPUS:85118869435
SN - 1109-2858
VL - 22
SP - 3989
EP - 4028
JO - Operational Research
JF - Operational Research
IS - 4
ER -