Skip to main content
Log in

A three-stage game model of plastic circular supply chain management in the context of cap-and-trade and plastic packaging regulations

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

Abstract

Circular supply chain management (CSCM) has become an emerging solution against plastic pollution and carbon emission associated with plastic production. This paper develops a three-stage game model to investigate decisions of three critical players in plastic CSCM, including a petrochemical company that produces virgin plastic and faces a cap-and-trade regulation, a multinational company (MNC) with a Scope 3’s emission reduction commitment that sells products in two markets with or without a plastic packaging regulation, and a plastic recycling company that collects and produces recycled plastic. Specifically, the petrochemical company first determines the optimal carbon reduction effort level. The plastic recycling company then determines the optimal price for recycled plastic. After observing the price of recycled plastic and the level of petrochemical company’s carbon reduction effort, the MNC finally determines the optimal proportion of recycled plastic to be used in product packaging. Our results show that the cap-and-trade regulation could encourage the petrochemical company to make greater effort to reduce carbon emission, but possibly lead to a reduction in the use of recycled plastic in packaging by the MNC. Higher plastic fines could incentivize the MNC to use more recycled plastic in the packaging, which is a disincentive for the petrochemical company to make carbon reduction effort. The MNC’s commitment to Scope 3’s carbon reduction contributes to an increased use of recycled plastics, but surprisingly, this results in more carbon emission from the petrochemical company. Interestingly, the total carbon emission of the plastics circular supply chain increases and then decreases as the Scope 3’s commitment by the MNC increases.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Notes

  1. There is much evidence that MNCs make decisions with the goal of reducing their Scope 3’s carbon emission. For example, The MNCs such as Apple and Unilever have committed to Scope 3’s carbon reduction as a goal and vision (Clancy, 2024; Johnson, 2023). Plambeck (2012) indicated that large firms have set internal and external (supplier-oriented) targets to reduce their greenhouse gas emission. Touboulic et al. (2018) found that companies must adopt a global supply chain perspective to profitably minimize overall "Scope 3" emission, encompassing emission by both suppliers and customers. Li et al. (2020) showed that enterprises have the potential to drive more ambitious action to reduce their Scope 3’s carbon emission and further achieve climate goals. Therefore, we consider λ as the coefficient of the Scope 3 carbon emission reduction’s commitment in the MNC’s objective function. The larger λ is, the greater the commitment of the MNC to Scope 3’s emission reduction. The parameter λ is greater than or equal to 0, which depends on the company's commitment level to Scope 3.

  2. The setting of parameters comes from practice. Specifically, based on data from The Association of Plastic Recyclers (2020), we set \(e_{{m_{0} }} = 2.23\) and \(e_{r} = 0.91\). According to the European recycled standard thermoplastic prices, we set the price of virgin and recycled plastic as \(p_{v} = 70\), \(p_{{r_{{}} }}^{{}} = 110\) (Platt, 2023). Furthermore, we set the minimum government-mandated proportion of recycled plastic in packaging \(\theta = 30\%\), which is similar as HM Revenue and Customs (2023). The parameter settings in the subsequent sections are the same as this.

References

  • Asif, M. S., Lau, H., Nakandala, D., Fan, Y., & Hurriyet, H. (2022). Case study research of green life cycle model for the evaluation and reduction of scope 3 emissions in food supply chains. Corporate Social Responsibility and Environmental Management, 29(4), 1050–1066.

    Article  Google Scholar 

  • Atasu, A., Toktay, L. B., & Van Wassenhove, L. N. (2013). How collection cost structure drives a manufacturer’s reverse channel choice. Production and Operations Management, 22(5), 1089–1102.

    Article  Google Scholar 

  • Berry, I. (2021). 10 countries tackling plastic pollution [EB/OL]. https://sustainabilitymag.com/top10/10-countries-tackling-plastic-pollution.

  • Chen, Z., & Tan, A. (2021). Exploring the circular supply chain to reduce plastic waste in Singapore. Logforum, 17(2), 271–286.

    Article  Google Scholar 

  • Civancik-Uslu, D., Puig, R., Voigt, S., Walter, D., & Fullana-i-Palmer, P. (2019). Improving the production chain with LCA and eco-design: Application to cosmetic packaging. Resources Conservation and Recycling, 151, 104475.

    Article  Google Scholar 

  • Clancy, H. (2024). Unilever takes tougher stance on supply-chain emissions [EB/OL]. https://www.greenbiz.com/article/unilever-takes-tougher-stance-supply-chain-emissions.

  • Coca-Cola. (2024). Eco-friendly packaging solutions for a World Without Waste [EB/OL]. https://www.coca-colacompany.com/sustainability/packaging-sustainability.

  • European Commission. (2023). EU rules on packaging and packaging waste, including design and waste management [EB/OL]. https://environment.ec.europa.eu/topics/waste-and-recycling/packaging-waste_en.

  • Exxonmobil. (2023). Proven technologies like carbon capture and storage are critical to help meet society’s lower-emission goals [EB/OL]. https://lowcarbon.exxonmobil.com/lower-carbon-technology/carbon-capture-and-storage?utm_source=google&utm_medium=cpc&utm_campaign=1ELC_GAD_TRAF_OT_Non-Brand_Carbon&utm_content=OT_Non-Brand_Carbon+Capture&utm_term=carbon+capture+technology+companies&gclid=Cj0KCQjw06-oBhC6ARIsAGuzdw382Xtvf9JDGOn8Zx3ol3R0U4WBEO6DOIbDnxBJlSaOqW_W_broSjkaAqmcEALw_wcB&gclsrc=aw.ds#Newagreement.

  • Farooque, M., Zhang, A., Liu, Y., & Hartley, J. L. (2022). Circular supply chain management: Performance outcomes and the role of eco-industrial parks in China. Transportation Research Part E: Logistics and Transportation Review, 157, 102596.

    Article  Google Scholar 

  • Ghosh, D., & Shah, J. (2012). A comparative analysis of greening policies across supply chain structures. International Journal of Production Economics, 135(2), 568–583.

    Article  Google Scholar 

  • Gock, A., Dale, E., Ou-Yang, L., Wheeler, S., & Faunce, T. (2018). Legal strategies to cure the plastic planet: Corporate marriage and public health regulation of single-use non-biodegradeable plastics. Journal of Law and Medicine, 26(2), 311–321.

    Google Scholar 

  • Gopalakrishnan, S., Granot, D., Granot, F., Sošić, G., & Cui, H. (2021). Incentives and emission responsibility allocation in supply chains. Management Science, 67(7), 4172–4190.

    Article  Google Scholar 

  • Govindan, K., Salehian, F., Kian, H., Hosseini, S. T., & Mina, H. (2023). A location-inventory-routing problem to design a circular closed-loop supply chain network with carbon tax policy for achieving circular economy: An augmented epsilon-constraint approach. International Journal of Production Economics, 257, 108771.

    Article  Google Scholar 

  • Griffin, P. W., Hammond, G. P., & Norman, J. B. (2018). Industrial energy use and carbon emissions reduction in the chemicals sector: A UK perspective. Applied Energy, 227, 587–602.

    Article  Google Scholar 

  • Harada, I. (2017). China to create world’s largest cap-and-trade program [EB/OL]. https://asia.nikkei.com/Economy/China-to-create-world-s-largest-cap-and-trade-program2.

  • He, H. (2012). Effects of environmental policy on consumption: Lessons from the Chinese plastic bag regulation. Environment and Development Economics, 17(4), 407–431.

    Article  Google Scholar 

  • He, P., Wang, Z., Shi, V., & Liao, Y. (2021). The direct and cross effects in a supply chain with consumers sensitive to both carbon emissions and delivery time. European Journal of Operational Research, 292(1), 172–183.

    Article  Google Scholar 

  • HM Revenue & Customs. (2023). Plastic packaging tax: Steps to take [EB/OL]. https://www.gov.uk/guidance/check-if-you-need-to-register-for-plastic-packaging-tax.

  • Huang, Y., Yi, Q., Kang, J.-X., Zhang, Y.-G., Li, W.-Y., Feng, J., & Xie, K.-C. (2019). Investigation and optimization analysis on deployment of China coal chemical industry under carbon emission constraints. Applied Energy, 254, 113684.

    Article  Google Scholar 

  • Johnson, L. (2023). Apple makes strides towards reaching 2030 carbon neutrality goal in Q4 [EB/OL]. https://www.esgdive.com/news/apple-2030-product-supply-chain-carbon-neutrality-progress-tim-cook-2023-q4/699002/.

  • Kabadurmus, O., Kazançoğlu, Y., Yüksel, D. & Pala, M. Ö. (2022). A circular food supply chain network model to reduce food waste. Annals of Operations Research (Forthcoming).

  • Karayılan, S., Yılmaz, Ö., Uysal, Ç., & Naneci, S. (2021). Prospective evaluation of circular economy practices within plastic packaging value chain through optimization of life cycle impacts and circularity. Resources, Conservation and Recycling, 173, 105691.

    Article  Google Scholar 

  • Lau, W. W. Y., Shiran, Y., Bailey, R. M., Cook, E., Stuchtey, M. R., Koskella, J., Velis, C. A., Godfrey, L., Boucher, J., Murphy, M. B., Thompson, R. C., Jankowska, E., Castillo, A. C., Pilditch, T. D., Dixon, B., Koerselman, L., Kosior, E., Favoino, E., Gutberlet, J., … Palardy, J. E. (2020). Evaluating scenarios toward zero plastic pollution. Science, 369(6510), 1455–1461.

    Article  Google Scholar 

  • Li, G., Wu, H., Sethi, S. P., & Zhang, X. (2021). Contracting green product supply chains considering marketing efforts in the circular economy era. International Journal of Production Economics, 234, 108041.

    Article  Google Scholar 

  • Li, M., Cao, G., Cui, L., Liu, X., & Dai, J. (2023). Examining how government subsidies influence firms’ circular supply chain management: The role of eco-innovation and top management team. International Journal of Production Economics, 261, 108893.

    Article  Google Scholar 

  • Li, M., Wiedmann, T., & Hadjikakou, M. (2020). Enabling full supply chain corporate responsibility: Scope 3 emissions targets for ambitious climate change mitigation. Environmental Science & Technology, 54(1), 400–411.

    Article  Google Scholar 

  • MacLeod, M., Arp, H. P. H., Tekman, M. B., & Jahnke, A. (2021). The global threat from plastic pollution. Science, 373(6550), 61–65.

    Article  Google Scholar 

  • Mahapatra, S. K., Schoenherr, T., & Jayaram, J. (2021). An assessment of factors contributing to firms’ carbon footprint reduction efforts. International Journal of Production Economics, 235, 108073.

    Article  Google Scholar 

  • Meier, O., Gruchmann, T., & Ivanov, D. (2023). Circular supply chain management with blockchain technology: A dynamic capabilities view. Transportation Research Part e: Logistics and Transportation Review, 176, 103177.

    Article  Google Scholar 

  • Meys, R., Katelhon, A., Bachmann, M., Winter, B., Zibunas, C., Suh, S., & Bardow, A. (2021). Achieving net-zero greenhouse gas emission plastics by a circular carbon economy. Science, 374(6563), 71–76.

    Article  Google Scholar 

  • Nagarajan, A. (2022). The governance of plastic in India: Towards a just transition for recycling in the unorganised sector. Local Environment, 27(10–11), 1394–1413.

    Article  Google Scholar 

  • Nasir, M. H. A., Genovese, A., Acquaye, A. A., Koh, S. C. L., & Yamoah, F. (2017). Comparing linear and circular supply chains: A case study from the construction industry. International Journal of Production Economics, 183, 443–457.

    Article  Google Scholar 

  • Park, H., Blanco, C. C., & Bendoly, E. (2022). Vessel sharing and its impact on maritime operations and carbon emissions. Production and Operations Management, 31(7), 2925–2942.

    Article  Google Scholar 

  • Plambeck, E. L. (2012). Reducing greenhouse gas emissions through operations and supply chain management. Energy Economics, 34, S64–S74.

    Article  Google Scholar 

  • Platt, D. (2023). Recyclers under pressure as downward price trend continues [EB/OL]. https://www.sustainableplastics.com/news/recyclers-under-pressure-downward-price-trend-continues.

  • Qian, D., Dargusch, P., & Hill, G. (2022). Carbon management behind the ambitious pledge of net zero carbon emission—a case study of PepsiCo. Sustainability, 14(4), 2171.

    Article  Google Scholar 

  • Qin, J., Han, Y., Wei, G., & Xia, L. (2019). The value of advance payment financing to carbon emission reduction and production in a supply chain with game theory analysis. International Journal of Production Research, 58(1), 200–219.

    Article  Google Scholar 

  • Roebroek, C. T. J., Duveiller, G., Seneviratne, S. I., Davin, E. L., & Cescatti, A. (2023). Releasing global forests from human management: How much more carbon could be stored? Science, 380(6646), 749–753.

    Article  Google Scholar 

  • Rowe, P., Eksioglu, B., & Eksioglu, S. (2015). Recycling procurement strategies with variable yield suppliers. Annals of Operations Research, 249(1–2), 215–234.

    Google Scholar 

  • Sardon, H., & Dove, A. P. (2018). Plastics recycling with a difference. Science, 360(6387), 380–381.

    Article  Google Scholar 

  • Savaskan, R. C., Bhattacharya, S., & Van Wassenhove, L. N. (2004). Closed-loop supply chain models with product remanufacturing. Management Science, 50(2), 239–252.

    Article  Google Scholar 

  • Song, S., Lian, J., Skowronski, K. & Yan, T. (2023). Customer base environmental disclosure and supplier greenhouse gas emissions: A signaling theory perspective. Journal of Operations Management (Forthcoming).

  • Steensgaard, I. M., Syberg, K., Rist, S., Hartmann, N. B., Boldrin, A., & Hansen, S. F. (2017). From macro- to microplastics-analysis of EU regulation along the life cycle of plastic bags. Environmental Pollution, 224, 289–299.

    Article  Google Scholar 

  • Stegmann, P., Daioglou, V., Londo, M., van Vuuren, D. P., & Junginger, M. (2022). Plastic futures and their CO2 emissions. Nature, 612, 272–276.

    Article  Google Scholar 

  • Stumpf, L., Schöggl, J.-P., & Baumgartner, R. J. (2023). Circular plastics packaging-prioritizing resources and capabilities along the supply chain. Technological Forecasting and Social Change, 188, 122261.

    Article  Google Scholar 

  • Syberg, K., Nielsen, M. B., Westergaard Clausen, L. P., van Calster, G., van Wezel, A., Rochman, C., Koelmans, A. A., Cronin, R., Pahl, S., & Hansen, S. F. (2021). Regulation of plastic from a circular economy perspective. Current Opinion in Green and Sustainable Chemistry, 29, 100462.

    Article  Google Scholar 

  • Tax News Update. (2023). Clarifications and further guidance provided for Spain’s plastic packaging tax which came into force on 1 January 2023 [EB/OL]. https://taxnews.ey.com/news/2023-0100-clarifications-and-further-guidance-provided-for-spains-plastic-packaging-tax-which-came-into-force-on-1-january-2023?uAlertID=Sd%2FG8rua1oj6%2Fl58EZ2AiA%3D%3D.

  • Taylor, R. L. C. (2019). Bag leakage: The effect of disposable carryout bag regulations on unregulated bags. Journal of Environmental Economics and Management, 93, 254–271.

    Article  Google Scholar 

  • The Association of Plastic Recyclers. (2020). Virgin vs. Recycled plastic life cycle assessment energy profile and life cycle assessment environmental burdens [EB/OL]. https://plasticsrecycling.org/images/library/APR-Recycled-vs-Virgin-May2020.pdf.

  • Touboulic, A., Matthews, L., & Marques, L. (2018). On the road to carbon reduction in a food supply network: A complex adaptive systems perspective. Supply Chain Management-an International Journal, 23(4), 313–335.

    Google Scholar 

  • Unilever. (2023). Partnering with suppliers to deliver net zero [EB/OL]. https://www.unilever.com/planet-and-society/climate-action/partnering-with-suppliers-to-deliver-net-zero/.

  • Walmart. (2017). Walmart launches project gigaton to reduce emissions in company’s supply chain [EB/OL]. https://corporate.walmart.com/newsroom/2017/04/19/walmart-launches-project-gigaton-to-reduce-emissions-in-companys-supply-chain.

  • Wang, C., Wang, L., Wang, W., Xiong, Y., & Du, C. (2023). Does carbon emission trading policy promote the corporate technological innovation? Empirical evidence from China’s high-carbon industries. Journal of Cleaner Production, 411, 137286.

    Article  Google Scholar 

  • Wang, M., Zhao, L., & Herty, M. (2019). Joint replenishment and carbon trading in fresh food supply chains. European Journal of Operational Research, 277(2), 561–573.

    Article  Google Scholar 

  • Wang, Y., Xu, X., & Zhu, Q. (2021). Carbon emission reduction decisions of supply chain members under cap-and-trade regulations: A differential game analysis. Computers & Industrial Engineering, 162, 107711.

    Article  Google Scholar 

  • Warzywoda, N., Dargusch, P., & Hill, G. (2022). How meaningful are modest carbon emissions reductions targets? The case of Sumitomo electrical group’s short-term targets towards longer-term net zero. Sustainability, 14(7), 4287.

    Article  Google Scholar 

  • Yang, L., Hu, Y., & Huang, L. (2020). Collecting mode selection in a remanufacturing supply chain under cap-and-trade regulation. European Journal of Operational Research, 287(2), 480–496.

    Article  Google Scholar 

  • Zhang, C., Chen, Y.-X., & Tian, Y.-X. (2023). Collection and recycling decisions for electric vehicle end-of-life power batteries in the context of carbon emissions reduction. Computers & Industrial Engineering, 175, 108869.

    Article  Google Scholar 

  • Zhou, H., Tan, Y., Guan, X. & Wu, P. (2023). Extended Vidale-Wolfe model on joint emission reduction and low-carbon advertising strategy design in a secondary supply chain. Annals of Operations Research (Forthcoming).

Download references

Acknowledgements

This work was supported by the projects of National Natural Science Foundation of China (72221001, 72192830/7219283, 72088101).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Qinghua Zhu.

Ethics declarations

Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix

Proof of Lemma 1

In the scenario of the MNC violates the Market 1’s government-mandated proportion of recycled plastic (\(0 \le r_{{}}^{{}} < \theta\)), the profit maximization function is:

$$ \begin{gathered} \mathop {\max \Pi_{M}^{{}} }\limits_{(r)} = p_{{m_{1} }} \cdot D_{{m_{1} }} + p_{{m_{2} }} \cdot D_{{m_{2} }} - p_{r} (D_{{m_{1} }} + D_{{m_{2} }} )r - p_{v} (D_{{m_{1} }} + D_{{m_{2} }} )(1 - r) - kr^{2} \hfill \\ \, - \lambda \{ (D_{{m_{1} }} + D_{{m_{2} }} )[(e_{{m_{0} }} - e)(1 - r) + e_{r} r]\} - FD_{{m_{1} }} (\theta - r) \hfill \\ \end{gathered} $$

We solve the MNC’s optimization problem as follows. The first and second order derivative of \(\Pi_{M}^{{}}\) in relation to \(r\) are: \(\frac{{\partial \Pi_{M}^{{}} }}{\partial r} = (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{{}} - e_{r} } \right) + p_{v} - p_{r}^{{}} ] + FD_{{m_{1} }} - 2kr\), \(\frac{{\partial^{2} \Pi_{M}^{{}} }}{{\partial r^{2} }} = - 2k < 0\), which indicates the MNC’s profit is concave for \(r\). Let \(\frac{{\partial \Pi_{M}^{{}} }}{\partial r} = 0\), we have:

\(r_{{}}^{*} = r_{f}^{*} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{f}^{*} - e_{r} } \right) + p_{v} - p_{{r_{f} }}^{*} ] + FD_{{m_{1} }} }}{2k}\), where we have the prerequisite: \(0 \le r_{{}}^{{}} < \theta\), namely \(0 \le (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) + p_{v} - p_{r}^{*} ] + FD_{{m_{1} }} < 2k\theta\) must hold.

Proof of Lemma 2

In the scenario of the MNC complies with the Market 1’s government-mandated proportion of recycled plastic (\(\theta \le r_{{}}^{{}} \le 1\)), the profit maximization function is:

$$ \begin{gathered} \mathop {\max \Pi_{M}^{{}} }\limits_{(r)} = p_{{m_{1} }} \cdot D_{{m_{1} }} + p_{{m_{2} }} \cdot D_{{m_{2} }} - p_{r} (D_{{m_{1} }} + D_{{m_{2} }} )r - p_{v} (D_{{m_{1} }} + D_{{m_{2} }} )(1 - r) - kr^{2} \hfill \\ \, - \lambda \{ (D_{{m_{1} }} + D_{{m_{2} }} )[(e_{{m_{0} }} - e)(1 - r) + e_{r} r]\} \hfill \\ \end{gathered} $$

We solve the MNC’s optimization problem as follows. The first and second order derivative of \(\Pi_{M}^{{}}\) in relation to \(r\) are: \(\frac{{\partial \Pi_{M}^{{}} }}{\partial r} = (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{{}} - e_{r} } \right) + p_{v} - p_{r}^{{}} ] - 2kr\), \(\frac{{\partial^{2} \Pi_{M}^{{}} }}{{\partial r^{2} }} = - 2k < 0\), which indicates the MNC’s profit is concave for \(r\). Let \(\frac{{\partial \Pi_{M}^{{}} }}{\partial r} = 0\), we have:

\(r_{{}}^{*} = r_{g}^{*} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{f}^{*} - e_{r} } \right) + p_{v} - p_{{r_{f} }}^{*} ]}}{2k}\), where we have the prerequisite: \(\theta < r_{{}}^{{}} < 1\), it is obviously that:

  • if \(0 < (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) + p_{v} - p_{r}^{*} ] < 2k\theta\), then \(r_{{}}^{*} = r_{g}^{*} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{f}^{*} - e_{r} } \right) + p_{v} - p_{{r_{f} }}^{*} ]}}{2k}\);

  • if \(2k\theta - FD_{{m_{1} }} < (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) + p_{v} - p_{r}^{*} ] < 2k\theta\), then \(r_{{}}^{*} = r_{\theta }^{*} = \theta\);

  • if \((D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) + p_{v} - p_{r}^{*} ] \ge 2k\), then \(r_{{}}^{*} = r_{1}^{*} = 1\).

Proof of Lemma 3

When the MNC violates the proportion of recycled plastic in packaging (\(0 \le r_{{}}^{*} < \theta\)), according to the Lemma 1, we have already obtain the MNC’s proportion of recycled plastic \(r_{{}}^{*} = r_{f}^{*} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{f}^{*} - e_{r} } \right) + p_{v} - p_{{r_{f} }}^{*} ] + FD_{{m_{1} }} }}{2k}\).

Substituting \(r_{f}^{*}\) into the plastic recycling company’s profit function \(\Pi_{R}^{{}}\). The second order derivative of \(\Pi_{R}^{{}}\) in relation to \(p_{r}\) is: \(\frac{{\partial^{2} \Pi_{R}^{{}} }}{{\partial p_{r}^{2} }} = - \frac{{\eta (D_{{m_{1} }} + D_{{m_{2} }} )^{2} }}{{2k^{2} }} < 0\), which indicates the plastic recycling company’s profit is concave for \(p_{r}\). Let \(\frac{{\partial \Pi_{R}^{{}} }}{{\partial p_{r} }} = 0\), we have:

$$\begin{aligned} p_{{r_{f} }}^{*} (r_{{}}^{*} = r_{f}^{*} ) &= \frac{{[p_{v} + \lambda {\mkern 1mu} \left( {e_{m} - e_{f}^{*} - e_{r} } \right)](k + \eta )}}{2k + \eta } + \frac{{FD_{{m_{1} }} (k + \eta )}}{{(2k + \eta )(D_{{m_{1} }} + D_{{m_{2} }} )}}\\ & = p_{v} + \lambda {\mkern 1mu} \left( {e_{{m_{0} }} - e_{f}^{*} - e_{r} } \right) - \frac{{k[p_{v} + \lambda {\mkern 1mu} \left( {e_{{m_{0} }} - e_{f}^{*} - e_{r} } \right)]}}{2k + \eta } + \frac{{FD_{{m_{1} }} (k + \eta )}}{{(2k + \eta )(D_{{m_{1} }} + D_{{m_{2} }} )}}\end{aligned} $$

Substituting \(r_{f}^{*}\) and \(p_{{r_{f} }}^{*}\) into the petrochemical company’s profit function \(\Pi_{P}^{{}}\). The second order derivative of \(\Pi_{P}^{{}}\) in relation to \(e\) is: \(\frac{{\partial^{2} \Pi_{P}^{{}} }}{{\partial e^{2} }} = \frac{{\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} }}{{{\mkern 1mu} 2k + \eta }}{\mkern 1mu} - 2\gamma\).

Thus, to ensure the petrochemical company’s profit function is concave, we need the condition \(2{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) \ge \lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2}\). Then, let \(\frac{{\partial \Pi_{P}^{{}} }}{\partial e} = 0\), we have

$$ e_{{}}^{*} = e_{f}^{*} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} \{ 4{\mkern 1mu} k{\mkern 1mu} p_{c} - (D_{{m_{1} }} + D_{{m_{2} }} )[\lambda p_{c} (\,2e_{{m_{0} }} - e_{r} ) + p_{v} (p_{c} - \lambda ) + \lambda c] + 2\eta p_{c} \} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }} - \frac{{FD_{{m_{1} }} (D_{{m_{1} }} + D_{{m_{2} }} )p_{c} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }} $$

Substituting \(e_{f}^{*}\) into \(p_{{r_{f} }}^{*}\), we could obtain the optimal recycled plastic price \(p_{{}}^{*}\). Then, substituting \(e_{f}^{*}\) and \(p_{{r_{f} }}^{*}\) into \(r_{{}}^{*}\), we could obtain the optimal proportion of recycled plastic.

Proof of Lemma 4–6

When the MNC complies with the proportion of recycled plastic in packaging (\(\theta \le r_{{}}^{*} \le 1\)), according to the Lemma 2, we have already obtain the MNC’s proportion of recycled plastic: when \(2k\theta - FD_{{m_{1} }} < (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) + p_{v} - p_{r}^{*} ] < 2k\theta\), \(r_{{}}^{*} = r_{\theta }^{*} = \theta\); when \(2k\theta < (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) + p_{v} - p_{r}^{*} ] < 2k\),\(r_{{}}^{*} = r_{g}^{*} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{g}^{*} - e_{r} } \right) + p_{v} - p_{{r_{g} }}^{*} ]}}{2k}\); when \((D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) + p_{v} - p_{r}^{*} ] \ge 2k\), \(r_{{}}^{*} = r_{1}^{*} = 1\).

  1. (1)

    \(\theta < r_{{}}^{*} < 1\)

    Substituting \(r_{g}^{*}\) into the plastic recycling company’s profit function \(\Pi_{R}^{{}}\). The second order derivative of \(\Pi_{R}^{{}}\) in relation to \(p_{r}\) is: \(\frac{{\partial^{2} \Pi_{R}^{{}} }}{{\partial p_{r}^{2} }} = - \frac{{\eta (D_{{m_{1} }} + D_{{m_{2} }} )^{2} }}{{2k^{2} }} < 0\), which indicates the plastic recycling company’s profit is concave for \(p_{r}\). Let \(\frac{{\partial \Pi_{R}^{{}} }}{{\partial p_{r} }} = 0\), we have:

    $$ p_{{r_{g} }}^{*} (r_{{}}^{*} = r_{g}^{*} ) = \frac{{[p_{p} + \lambda {\mkern 1mu} \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right)](k + \eta )}}{2k + \eta } = p_{p} + \lambda {\mkern 1mu} \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) - \frac{{k[p_{p} + \lambda {\mkern 1mu} \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right)]}}{2k + \eta } $$

    Then, substituting \(r_{g}^{*}\) and \(p_{{r_{g} }}^{*}\) into the petrochemical company’s profit function \(\Pi_{P}^{{}}\). The second order derivative of \(\Pi_{P}^{{}}\) in relation to \(e\) is: \(\frac{{\partial^{2} \Pi_{P}^{{}} }}{{\partial e^{2} }} = \frac{{\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} }}{{{\mkern 1mu} 2k + \eta }}{\mkern 1mu} - 2\gamma\).

    Similar to the proof of Lemma 3, to ensure the petrochemical company’s profit function is concave, we also need the condition \(2{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) \ge \lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2}\). Then, let \(\frac{{\partial \Pi_{P}^{{}} }}{\partial e} = 0\), we have

    $$ e_{{}}^{*} = e_{g}^{*} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} \{ 4{\mkern 1mu} k{\mkern 1mu} p_{c} - (D_{{m_{1} }} + D_{{m_{2} }} )[\lambda p_{c} (\,2e_{{m_{0} }} - e_{r} ) + p_{v} (p_{c} - \lambda ) + \lambda c] + 2\eta p_{c} \} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }}. $$

    Substituting \(e_{g}^{*}\) into \(p_{{r_{g} }}^{*}\), we could obtain the optimal recycled plastic price \(p_{{}}^{*}\). Then, substituting \(e_{g}^{*}\) and \(p_{{r_{g} }}^{*}\) into \(r_{{}}^{*}\), we could obtain the optimal proportion of recycled plastic.

  2. (2)

    \( r^{*} = r_{\theta }^{*} = \theta \)

    Substituting \( r_{f}^{*} \) into the plastic recycling company’s profit function \(\Pi_{R}^{{}}\), the first order derivative of \(\Pi_{R}^{{}}\) in relation to \(p_{r}\) is \(\frac{{\partial \Pi_{R}^{{}} }}{{\partial p_{r} }} = \theta (D_{{m_{1} }} + D_{{m_{2} }} ) \ge 0\). Since we have \(2k\theta - FD_{{m_{1} }} < (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) + p_{v} - p_{r}^{*} ] < 2k\theta\), that means \(p_{v} + \lambda {\mkern 1mu} \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) - \frac{2k\theta }{{D_{{m_{1} }} + D_{{m_{2} }} }} \le p_{{r_{{}} }}^{*} \le p_{v} + \lambda {\mkern 1mu} \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) - \frac{2k\theta }{{D_{{m_{1} }} + D_{{m_{2} }} }} + \frac{{FD_{{m_{1} }} }}{{D_{{m_{1} }} + D_{{m_{2} }} }}\). Hence, the optimal recycled plastic price of the plastic recycling company is \(p_{{r_{\theta } }}^{*} = p_{v} + \lambda {\mkern 1mu} \left( {e_{{m_{0} }} - e_{\theta }^{*} - e_{r} } \right) - \frac{2k\theta }{{D_{{m_{1} }} + D_{{m_{2} }} }} + \frac{{FD_{{m_{1} }} }}{{D_{{m_{1} }} + D_{{m_{2} }} }}\).

    Then, substituting \(r_{\theta }^{*}\) and \(p_{{r_{\theta } }}^{*}\) into the petrochemical company’s profit function \(\Pi_{P}^{{}}\). The second order derivative of \(\Pi_{P}^{{}}\) in relation to \(e\) is: \(\frac{{\partial^{2} \Pi_{P}^{{}} }}{{\partial e^{2} }} = - 2\gamma\), which indicates the petrochemical company’s profit is concave for \(e\). Let \(\frac{{\partial \Pi_{P}^{{}} }}{\partial e} = 0\), we have: \(e_{\theta }^{*} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} )(1 - \theta )p_{c} }}{2\gamma }\).

    Substituting \(e_{\theta }^{*}\) into \(p_{{r_{\theta } }}^{*}\), we could obtain the optimal recycled plastic price \(p_{{}}^{*}\). Then, substituting \(e_{\theta }^{*}\) and \(p_{{r_{\theta } }}^{*}\) into \(r_{{}}^{*}\), we could obtain the optimal proportion of recycled plastic.

  3. (3)

    \( r^{*} = r_{1}^{*} = 1 \)

    Substituting \(r_{1}^{*} = 1\) into the plastic recycling company’s profit function \(\Pi_{R}^{{}}\), the first order derivative of \(\Pi_{R}^{{}}\) in relation to \(p_{r}\) is \(\frac{{\partial \Pi_{R}^{{}} }}{{\partial p_{r} }} = (D_{{m_{1} }} + D_{{m_{2} }} ) \ge 0\). Since we have \((D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) + p_{v} - p_{r}^{*} ] \ge 2k\), that means \(p_{{r_{{}} }}^{*} \le p_{v} + \lambda {\mkern 1mu} \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) - \frac{2k}{{D_{{m_{1} }} + D_{{m_{2} }} }}\). Hence, the optimal recycled plastic price of the plastic recycling company is \(p_{{r_{1} }}^{*} = p_{v} + \lambda {\mkern 1mu} \left( {e_{{m_{0} }} - e_{1}^{*} - e_{r} } \right) - \frac{2k}{{D_{{m_{1} }} + D_{{m_{2} }} }}\).

    Then, substituting \(r_{1}^{*}\) and \(p_{{r_{1} }}^{*}\) into the petrochemical company’s profit function \(\Pi_{P}^{{}}\). The second order derivative of \(\Pi_{P}^{{}}\) in relation to \(e\) is: \(\frac{{\partial^{2} \Pi_{P}^{{}} }}{{\partial e^{2} }} = - 2\gamma\), which indicates the petrochemical company’s profit is concave for \(e\). Let \(\frac{{\partial \Pi_{P}^{{}} }}{\partial e} = 0\), we have: \(e_{1}^{*} = 0\).

    Substituting \(e_{1}^{*}\) into \(p_{{r_{1} }}^{*}\), we could obtain the optimal recycled plastic price \(p_{{}}^{*}\). Then, substituting \(e_{1}^{*}\) and \(p_{{r_{1} }}^{*}\) into \(r_{{}}^{*}\), we could obtain the optimal proportion of recycled plastic.

Proof of Proposition 1

The proof of Proposition 1 could be obtained by the above Lemma 1–6.

Proof of Proposition 2

Since we have proved that when \(0 \le (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right) + p_{v} - p_{r}^{*} ] + FD_{{m_{1} }} \ge 2k\theta\), the MNC will comply with government regulations on the proportion of recycled plastic. That means when the government unit fines \(F \ge \frac{{2k\theta - (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{f}^{*} - e_{r} } \right) + p_{v} - p_{{r_{f} }}^{*} ]}}{{D_{{m_{1} }} }}\), the MNC will not violates the regulation.

Let this threshold \(\frac{{2k\theta - (D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} [\lambda \left( {e_{{m_{0} }} - e_{f}^{*} - e_{r} } \right) + p_{v} - p_{{r_{f} }}^{*} ]}}{{D_{{m_{1} }} }} = R\). Taking the derivative of this threshold \(T\) with respect to consumer demand in Market 1 \(D_{{m_{1} }}^{{}}\), government-mandated minimum proportion of recycled plastic \(\theta\) and commitment coefficient from Scope3 carbon reduction \(\lambda\) respectively, we have \(\frac{\partial R}{{\partial D_{{m_{1} }}^{{}} }} = - \frac{{2k\theta - D_{{m_{2} }} [\lambda \left( {e_{{m_{0} }} - e_{f}^{*} - e_{r} } \right) + p_{v} - p_{{r_{f} }}^{*} ]}}{{D_{{m_{1} }}^{2} }} \le 0\), \(\frac{\partial R}{{\partial \theta }} = \frac{2k}{{D_{{m_{1} }} }} \ge 0\), \(\frac{\partial R}{{\partial \lambda }} = - \frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} \left( {e_{{m_{0} }} - e_{{}}^{*} - e_{r} } \right)}}{{D_{{m_{1} }} }} \le 0\).

Proof of Proposition 3

Since \(e_{f}^{*} = e_{g}^{*} + \frac{{FD_{{m_{1} }} (D_{{m_{1} }} + D_{{m_{2} }} )p_{c} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }}\), and \(\frac{{FD_{{m_{1} }} (D_{{m_{1} }} + D_{{m_{2} }} )p_{c} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }} \ge 0\), we have \(e_{g}^{*} \le e_{f}^{*}\). We have obtained that \(e_{1}^{*} = 0\), hence, \(e_{1}^{*} \le e_{g}^{*} \le e_{f}^{*}\) must hold.

Let \(e_{\theta }^{*} - e_{f}^{*} \ge 0\), we have \((1 - \theta ) \ge \frac{{\gamma \{ 2p_{c} (2k + \eta ) - (D_{{m_{1} }} + D_{{m_{2} }} )[\lambda p_{c} (\,2e_{{m_{0} }} - e_{r} ) + p_{v} (p_{c} - \lambda ) + \lambda c]\} }}{{2{\mkern 1mu} \gamma p_{c} {\mkern 1mu} (2k + \eta ) - \lambda p_{c}^{2} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }}\). Let \(e_{\theta }^{*} - e_{g}^{*} \ge 0\) and \(e_{\theta }^{*} - e_{f}^{*} \le 0\), we have \(\frac{{\gamma \{ 2p_{c} (2k + \eta ) - (D_{{m_{1} }} + D_{{m_{2} }} )[\lambda p_{c} (\,2e_{{m_{0} }} - e_{r} ) + p_{v} (p_{c} - \lambda ) + \lambda c]\} - FD_{{m_{1} }} p_{c} \gamma }}{{2{\mkern 1mu} \gamma p_{c} {\mkern 1mu} (2k + \eta ) - \lambda p_{c}^{2} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }} \le (1 - \theta ) \le \frac{{\gamma \{ 2p_{c} (2k + \eta ) - (D_{{m_{1} }} + D_{{m_{2} }} )[\lambda p_{c} (\,2e_{{m_{0} }} - e_{r} ) + p_{v} (p_{c} - \lambda ) + \lambda c]\} }}{{2{\mkern 1mu} \gamma p_{c} {\mkern 1mu} (2k + \eta ) - \lambda p_{c}^{2} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }}\). Let \(e_{g}^{*} - e_{\theta }^{*} \ge 0\), we have \((1 - \theta ) \le \frac{{\gamma \{ 2p_{c} (2k + \eta ) - (D_{{m_{1} }} + D_{{m_{2} }} )[\lambda p_{c} (\,2e_{{m_{0} }} - e_{r} ) + p_{v} (p_{c} - \lambda ) + \lambda c]\} - FD_{{m_{1} }} p_{c} \gamma }}{{2{\mkern 1mu} \gamma p_{c} {\mkern 1mu} (2k + \eta ) - \lambda p_{c}^{2} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }}\).

Proof of Proposition 4

Taking the derivative of the optimal recycled plastic proportion \(r_{f}^{*}\) and \(r_{g}^{*}\) with respect to the MNC’s Scope 3 commitment coefficient \(\lambda\), we have:

$$ \frac{{\partial r_{f}^{*} }}{\partial \lambda } = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} )\left( {e_{{m_{0} }} - \frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} \{ 4{\mkern 1mu} k{\mkern 1mu} p_{c} - (D_{{m_{1} }} + D_{{m_{2} }} )[\lambda p_{c} (\,2e_{{m_{0} }} - e_{r} ) + p_{v} (p_{c} - \lambda ) + \lambda c] + 2\eta p_{c} \} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }} + \frac{{FD_{{m_{1} }} (D_{{m_{1} }} + D_{{m_{2} }} )p_{c} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }} - e_{r} } \right)}}{2k} $$

Since \(\frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} \{ 4{\mkern 1mu} k{\mkern 1mu} p_{c} - (D_{{m_{1} }} + D_{{m_{2} }} )[\lambda p_{c} (\,2e_{{m_{0} }} - e_{r} ) + p_{v} (p_{c} - \lambda ) + \lambda c] + 2\eta p_{c} \} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }} - \frac{{FD_{{m_{1} }} (D_{{m_{1} }} + D_{{m_{2} }} )p_{c} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }} = e_{f}^{*}\), and \(e_{{m_{0} }} - e_{f}^{*} - e_{r} \ge 0\), hence \(\frac{{\partial r_{f}^{*} }}{\partial \lambda } \ge 0\).

$$ \frac{{\partial r_{g}^{*} }}{\partial \lambda } = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} )\left( {e_{{m_{0} }} - \frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} \{ 4{\mkern 1mu} k{\mkern 1mu} p_{c} - (D_{{m_{1} }} + D_{{m_{2} }} )[\lambda p_{c} (\,2e_{{m_{0} }} - e_{r} ) + p_{v} (p_{c} - \lambda ) + \lambda c] + 2\eta p_{c} \} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }} - e_{r} } \right)}}{2k} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} )\left( {e_{{m_{0} }} - e_{g}^{*} - e_{r} } \right)}}{2k} \ge 0 $$

Since \(\frac{{(D_{{m_{1} }} + D_{{m_{2} }} ){\mkern 1mu} \{ 4{\mkern 1mu} k{\mkern 1mu} p_{c} - (D_{{m_{1} }} + D_{{m_{2} }} )[\lambda p_{c} (\,2e_{{m_{0} }} - e_{r} ) + p_{v} (p_{c} - \lambda ) + \lambda c] + 2\eta p_{c} \} }}{{4{\mkern 1mu} \gamma {\mkern 1mu} (2k + \eta ) - 2\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} {\mkern 1mu} }} = e_{g}^{*}\), and \(e_{{m_{0} }} - e_{g}^{*} - e_{r} \ge 0\), hence \(\frac{{\partial r_{g}^{*} }}{\partial \lambda } \ge 0\).

Taking the derivative of the optimal recycled plastic proportion \(r_{f}^{*}\) and \(r_{g}^{*}\) with respect to the carbon trading price \(p_{c}\), we have:

\(\frac{{\partial r_{g}^{*} }}{{\partial p_{c} }} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} )^{5} {\mkern 1mu} \lambda^{3} (c - p_{v} ) + 2\gamma \lambda {\mkern 1mu} (2k + \eta )\left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} [\left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)(2e_{{m_{0} }} \lambda - e_{r} \lambda + p_{v} ) - 2{\mkern 1mu} (2k + \eta )]}}{{4{\mkern 1mu} {\mkern 1mu} (2k + \eta )[\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} - 2\gamma {\mkern 1mu} (2k + \eta )]^{2} {\mkern 1mu} }}\),

\(\frac{{\partial r_{f}^{*} }}{{\partial p_{c} }} = \frac{{(D_{{m_{1} }} + D_{{m_{2} }} )^{5} {\mkern 1mu} \lambda^{3} (c - p_{v} ) + 2\gamma \lambda {\mkern 1mu} (2k + \eta )\left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} [\left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)(2e_{{m_{0} }} \lambda - e_{r} \lambda + p_{v} ) - 2{\mkern 1mu} (2k + \eta )]}}{{4{\mkern 1mu} {\mkern 1mu} (2k + \eta )[\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} - 2\gamma {\mkern 1mu} (2k + \eta )]^{2} {\mkern 1mu} }} + \frac{{FD_{{m_{1} }} \gamma \lambda (D_{{m_{1} }} + D_{{m_{2} }} )^{2} }}{{2[\lambda p_{c} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} - 2\gamma {\mkern 1mu} (2k + \eta )]^{2} {\mkern 1mu} }}\). Let \(\frac{{\partial r_{g}^{*} }}{{\partial p_{c} }} \ge 0\), we have \(\lambda \ge \frac{{\gamma (2e_{{m_{0} }} - e_{r} ){\mkern 1mu} (2k + \eta ) + \sqrt {K_{1} + \gamma {\mkern 1mu} (2k + \eta )\{ - 8kp_{v} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right) - 2c\left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)[p_{v} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right) - 2{\mkern 1mu} (2k + \eta )]\} } }}{{\left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} (p_{v} - c){\mkern 1mu} }}\). Let \(\frac{{\partial r_{f}^{*} }}{{\partial p_{c} }} \ge 0\), we have:

\(\lambda \ge \frac{{\gamma (2e_{{m_{0} }} - e_{r} ){\mkern 1mu} (2k + \eta ) + \sqrt {K_{1} + \gamma {\mkern 1mu} (2k + \eta )\{ 2p_{v} {\mkern 1mu} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)(FD_{{m_{1} }} - 4k) - 2c\left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)[p_{v} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right) - 2{\mkern 1mu} (2k + \eta ) + FD_{{m_{1} }} ]\} } }}{{\left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} (p_{v} - c){\mkern 1mu} }}\),where \(K_{1} = \gamma {\mkern 1mu} (2k + \eta )\{ 2\gamma k( - 2e_{{m_{0} }} + e_{r} )^{2} + 2{\mkern 1mu} p_{v}^{2} \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)^{2} + \gamma \eta ( - 2e_{{m_{0} }} + e_{r} )^{2} - 4p_{v} \eta \left( {D_{{m_{1} }} + D_{{m_{2} }} } \right)\}\).

Proof of Proposition 5

Given the optimal petrochemical company’s carbon reduction effort level \(e_{{}}^{*}\), the recycled plastic price under different scenarios is as follows:

\(p_{{r_{f} }}^{*} = p_{v} + \lambda {\mkern 1mu} \left( {e_{m} - e_{{}}^{*} - e_{r} } \right) - \frac{{k[p_{v} + \lambda {\mkern 1mu} \left( {e_{m} - e_{{}}^{*} - e_{r} } \right)]}}{2k + \eta } + \frac{{FD_{{m_{1} }} (k + \eta )}}{{(2k + \eta )(D_{{m_{1} }} + D_{{m_{2} }} )}}\), \(p_{{r_{\theta } }}^{*} = p_{v} + \lambda {\mkern 1mu} \left( {e_{m} - e_{{}}^{*} - e_{r} } \right) - \frac{2k\theta }{{D_{{m_{1} }} + D_{{m_{2} }} }} + \frac{{FD_{{m_{1} }} }}{{D_{{m_{1} }} + D_{{m_{2} }} }}\),

\(p_{{r_{g} }}^{*} = p_{v} + \lambda {\mkern 1mu} \left( {e_{m} - e_{{}}^{*} - e_{r} } \right) - \frac{{k[p_{v} + \lambda {\mkern 1mu} \left( {e_{m} - e_{g}^{*} - e_{r} } \right)]}}{2k + \eta }\), \(p_{{r_{1} }}^{*} = p_{v} + \lambda {\mkern 1mu} \left( {e_{m} - e_{{}}^{*} - e_{r} } \right) - \frac{2k}{{D_{{m_{1} }} + D_{{m_{2} }} }}\). If \(p_{v} \le p_{r}^{*}\), then the price inversion between virgin and recycled plastics occurs.

Thus, let \(p_{{r_{f} }}^{*} - p_{v} \ge 0\), \(p_{{r_{\theta } }}^{*} - p_{v} \ge 0\),\(p_{{r_{g} }}^{*} - p_{v} \ge 0\) and \(p_{{r_{1} }}^{*} - p_{v} \ge 0\) respectively, we have \(\lambda {\mkern 1mu} \left( {e_{m} - e_{{}}^{*} - e_{r} } \right) + \frac{{FD_{{m_{1} }} (k + \eta )}}{{(2k + \eta )(D_{{m_{1} }} + D_{{m_{2} }} )}} \ge \frac{{k[p_{v} + \lambda {\mkern 1mu} \left( {e_{m} - e_{{}}^{*} - e_{r} } \right)]}}{2k + \eta }\), \(\lambda {\mkern 1mu} \left( {e_{m} - e_{{}}^{*} - e_{r} } \right) + \frac{{FD_{{m_{1} }} }}{{D_{{m_{1} }} + D_{{m_{2} }} }} \ge \frac{2k\theta }{{D_{{m_{1} }} + D_{{m_{2} }} }}\), \(\lambda {\mkern 1mu} \left( {e_{m} - e_{{}}^{*} - e_{r} } \right) \ge \frac{{k[p_{v} + \lambda {\mkern 1mu} \left( {e_{m} - e_{g}^{*} - e_{r} } \right)]}}{2k + \eta }\), \(\lambda {\mkern 1mu} \left( {e_{m} - e_{{}}^{*} - e_{r} } \right) \ge \frac{2k}{{D_{{m_{1} }} + D_{{m_{2} }} }}\).

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y., Zhu, Q. A three-stage game model of plastic circular supply chain management in the context of cap-and-trade and plastic packaging regulations. Ann Oper Res (2024). https://doi.org/10.1007/s10479-024-06013-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10479-024-06013-5

Keywords

Navigation