Skip to main content

Advertisement

Log in

Evaluating the effects of environmental regulations on a closed-loop supply chain network: a variational inequality approach

  • Original Paper
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

Global climate change has encouraged international and regional adoption of pollution taxes and carbon emission reduction policies. Europe has taken the leadership in environmental regulations by introducing the European Union Emissions Trading System (EU-ETS) in 2005 and by promoting a set of policies destined to lower carbon emissions from energy, industrial, and transport sectors. These environmental policies have significantly affected the production choices of these European sectors. Considering this framework, the objective of this paper is to evaluate the effects of the application of environmental policies in a multitiered closed-loop supply chain network where raw material suppliers, manufacturers, consumers, and recovery centers operate. In particular, we assume that manufacturers are subject to the EU-ETS and a carbon tax is imposed on truck transport. In this way, the developed model captures carbon emission regulations, recycling, transportation and technological factors within a unified framework. In particular, it allows for evaluating the impacts of the considered environmental regulations on carbon emissions, product flows, and prices. The proposed model is optimized and solved by using the theory of variational inequalities. Our analysis shows that the combined application of the EU-ETS at the manufacturers’ tier and the carbon tax on truck transport implies additional costs for producers that reduce their good provisions. On the other side, this has a positive outcome for the environment since \(\hbox {CO}_2\) emissions reduce. Moreover, an increase of the efficiency level of the recycling process increments the availability of reusable raw material in the reverse supply chain. Finally, the distance between a couple of CLSC tiers plays a very important role. The lower is the distance covered by vehicles, the higher is the production of goods and the lower is the amount of \(\hbox {CO}_2\) emitted.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Notes

  1. See the Proposal for a Directive of the European Parliament and of the council amending Directive 2003/87/EC to enhance cost-effective emission reductions and low-carbon investments available at http://ec.europa.eu/clima/policies/ets/revision/documentation_en.htm.

  2. Aggiungere link.

  3. See http://ec.europa.eu/clima/policies/transport/index_en.htm.

  4. Note that this assumption can be easily adjusted when modeling sectors that still receive free allowances in the third EU-ETS phase. For more details, see http://ec.europa.eu/clima/policies/ets/index_en.htm.

  5. See https://www.politesi.polimi.it/bitstream/10589/26301/3/2011_10_CICCARELLO.pdf.

  6. See https://www.eex.com/en/.

References

  • Barbagallo, A., Daniele, P., Giuffrè, S., & Maugeri, A. (2014). Variational approach for a general financial equilibrium problem: The Deficit formula, the balance law and the liability formula a path to the economy recovery. European Journal of Operational Research, 237(1), 231–244.

    Article  Google Scholar 

  • Brandenburg, M., & Rebs, T. (2015). Sustainable supply chain management: A modeling perspective. Annals of Operations Research, 229(1), 213–252.

    Article  Google Scholar 

  • Daniele, P., Maugeri, A., & Oettli, W. (1999). Time-dependent traffic equilibria. Journal of Optimization Theory and Applications, 103, 543–555.

    Article  Google Scholar 

  • Dhanda, K. K., Nagurney, A., & Ramanujam, P. (1999). Environmental networks. A framework for economic decision-making and policy analysis. Cheltenham: Edward Elgar Publisher.

    Google Scholar 

  • European Commission Directorate General for Environment, McKinsey & Company, Ecofys. (2006). EU-ETS review. Report on international competitiveness. http://ec.europa.eu/clima/policies/ets/docs/report_int_competitiveness_20061222_en.pdf

  • Elhedhli, S., & Merrick, R. (2012). Green supply chain network design to reduce carbon emissions. Transportation Research Part D, 17, 370–379.

    Article  Google Scholar 

  • Facchinei, F., & Pang, J.-S. (2003). Finite-dimensional variational inequalities and complementarity problems. Berlin: Springer. (two volumes).

    Google Scholar 

  • Gao, N., & Ryan, S. M. (2014). Robust design of a closed-loop supply chain network for uncertain carbon regulations and random product flows. EURO Journal on Transportation and Logistics, 3(1), 5–34.

    Article  Google Scholar 

  • Govindan, K., Soleimanib, H., & Kannan, D. (2015). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European Journal of Operational Research, 240(3), 603–626.

    Article  Google Scholar 

  • Guide, V. D. R., & Van Wassenhove, L. N. (2009). The evolution of closed-loop supply chain research. Operation and Research, 57(1), 10–18.

  • Gupta, S., & Van Palsule-Desai, O. D. (2011). Sustainable supply chain management: Review and research opportunities. IIMB Management Review, 23(4), 234–245.

    Article  Google Scholar 

  • Hammond, D., & Beullens, P. (2007). Closed-loop supply chain network equilibrium under legislation. European Journal of Operational Research, 183, 895–908.

    Article  Google Scholar 

  • Kinderlehrer, D., & Stampacchia, G. (1980). An introduction to variational inequalities and their application. New York: Academic Press.

    Google Scholar 

  • Konnov, I. V. (1993). Combined relaxation methods for finding equilibrium points and solving related problems. Russian Mathematics (Iz. VUZ), 3, 44–51.

    Google Scholar 

  • Konnov, I. V. (2001). Combined relaxation methods for variational inequalities. Berlin: Springer.

    Book  Google Scholar 

  • Nagurney, A. (1999). Network economics: A variational inequality approach. Dordrecht: Kluwer.

    Book  Google Scholar 

  • Nagurney, A. (2003). Innovations in financial and economic networks. Cheltenham: Edward Elgar Publishing Inc.

    Google Scholar 

  • Nagurney, A., & Zhao, L. (1993). Variational inequalities and networks in the formulation and computation of market equilibria and disequilibria: The case of direct demand functions. Transportation Science, 27(1), 4–15.

    Article  Google Scholar 

  • Nagurney, A., & Siokos, S. (1998). Network modeling of international financial equilibria with hedging. Annals of Operations Research, 82, 139–160.

    Article  Google Scholar 

  • Nagurney, A., & Dhanda, K. K. (2000). Noncompliant oligopolistic firms and marketable pollution permits: Statics and dynamics. Annals of Operations Research, 95, 285–312.

    Article  Google Scholar 

  • Nagurney, A., Dong, J., & Zhang, D. (2002). A supply chain network equilibrium model. Transportation Research Part E, 38, 281–303.

    Article  Google Scholar 

  • Nagurney, A., & Toyasaki, F. (2005). Reverse supply chain management and electronic waste recycling: A multitiered network equilibrium framework for e-cycling. Transportation Research Part E, 41(1), 1–28.

    Article  Google Scholar 

  • Nagurney, A., Liu, Z., & Woolley, T. (2007). Sustainable supply chain and transportation networks. International Journal of Sustainable Transportation, 1(1), 29–51.

    Article  Google Scholar 

  • Nagurney, A., & Dong, L. (2015). A supply chain network game theory model with product differentiation, outsourcing of production and distribution, and quality and price competition. Annals of Operations Research, 226, 479–503.

    Article  Google Scholar 

  • Nagurney, A., Daniele, P., & Shukla, S. (2017). A supply chain network game theory model of cybersecurity investments with nonlinear budget constraints. Annals of Operations Research, 248(1), 405–427.

    Article  Google Scholar 

  • Paksoy, T., Ozceylan, E., & Weber, G. W. (2011). A multi objective model for optimization of a green supply chain network. Global Journal of Technology & Optimization, 2(2), 84–96.

    Google Scholar 

  • Qiang, Q. (2015). The closed-loop supply chain network with competition and design for remanufactureability. Journal of Cleaner Production, 105, 348–356.

    Article  Google Scholar 

  • Qiang, Q., Ke, K., Anderson, T., & Dong, J. (2013). The closed-loop supply chain network with competition, distribution channel investment, and uncertainties. Omega, 41(2), 186–194.

    Article  Google Scholar 

  • Rezaee, A., Dehghanian, F., Fahimnia, & Beamon, B., (2017). Green supply chain network design with stochastic demand and carbon price. Annals of Operations Research. doi:10.1007/s10479-015-1936-z6-z.

  • Reinaud, J. (2009). Trade, competitiveness and carbon leakage: challenges and opportunities. Energy, Environment and Development Programme Paper 9(1), 1–25.

  • Scrimali, L. (2004). Variational inequalities and optimal equilibrium distributions in transportation networks. Mathematical Inequalities and Applications, 7(3), 439–451.

    Article  Google Scholar 

  • Seuring, S. (2013). A review of modeling approaches for sustainable supply chain management. Decision Support Systems, 54(4), 1513–1520.

    Article  Google Scholar 

  • Sijm, J. P. M., Neuhoff, K., & Chen, Y. (2006). Cost pass thought and windfall profits in the power sector. Climate Policy, 5, 61–78.

    Google Scholar 

  • Sivrastava, S. K. (2007). Green supply-chain management: A state-of-the-art literature review. International Journal of Management Reviews, 9(1), 53–80.

    Article  Google Scholar 

  • Toyasaki, F., Daniele, P., & Wakolbinger, T. (2014). A variational inequality formulation of equilibrium models for end-of-life products with nonlinear constraints. European Journal of Operational Research, 236, 340–350.

    Article  Google Scholar 

  • Wakolbinger, T., Toyasaki, F., Nowak, T., & Nagurney, A. (2014). When and for whom would e-waste be a treasure trove? Insights from a network equilibrium model of e-waste flows. International Journal of Production Economics, 154, 263–273.

    Article  Google Scholar 

  • Wang, H.-F., & Hsu, H.-W. (2010). A closed-loop logistic model with a spanning-tree based genetic algorithm. Computers & Operations Research, 37, 376–389.

    Article  Google Scholar 

  • Wang, F., Lai, X., & Shi, N. (2011). A multi-objective optimization for green supply chain network design. Decision Support Systems, 51, 262–269.

    Article  Google Scholar 

  • Wang, G., & Gunasekaran, A. (2015). Modeling and analysis of sustainable supply chain dynamics. Annals of Operations Research, 51, 262–269.

    Google Scholar 

  • Wu, K., Nagurney, A., Liu, Z., & Stranlund, J. K. (2006). Modeling generator power plant portfolios and pollution taxes in electric power supply chain networks: A transportation network equilibrium transformation. Transportation Research Part D, 11, 171–190.

    Article  Google Scholar 

  • Yang, G., Wang, Z., & Li, X. (2009). The optimization of the closed-loop supply chain network. Transportation Research Part E, 45, 16–28.

    Article  Google Scholar 

Download references

Acknowledgements

In this work, Igor Konnov was supported by the RFBR Grant, Project No. 16-01-00109a. His results were obtained within the state assignment of the Ministry of Science and Education of Russia, project No. 1.460.2016/1.4. Elisabetta Allevi and Giorgia Oggioni are grateful to the UniBS H&W Project “Brescia 20-20-20” for the financial support. All the authors thank the editor and the two anonymous reviewers for their valuable comments, which helped them to improve the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to G. Oggioni.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Allevi, E., Gnudi, A., Konnov, I.V. et al. Evaluating the effects of environmental regulations on a closed-loop supply chain network: a variational inequality approach. Ann Oper Res 261, 1–43 (2018). https://doi.org/10.1007/s10479-017-2613-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-017-2613-1

Keywords

Navigation