Skip to main content
Log in

Differential game theoretic analysis of the dynamic emission abatement in low-carbon supply chains

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

Abstract

This paper studies the impact of bilateral participation strategy on the dynamic emission-reducing behaviors and associated performance of low-carbon supply chains using differential game models. We first consider a dyadic supply chain comprising one supplier and one manufacturer in the base model and derive the equilibrium solutions of dynamic emission abatement in decentralized and centralized systems, respectively. In the decentralized supply chain, we consider both unilateral sharing and bilateral participation contracts and examine the feedback equilibrium strategies and trajectories of emission abatement of all parties. By comparison, we find that the bilateral contract leads to lower emission abatement and higher profits of all players and the system than that under unilateral sharing contract. Meanwhile, we show that the properly-designed bilateral participation contract can coordinate the decentralized dyadic supply chain. By extending the base model, we further figure out the equilibria and optimal trajectories for the dynamic cooperative emission abatement and the associated mechanism design in a supply chain with two competing suppliers and one manufacturer. Interestingly, we find that the bilateral participation contract can also coordinate the competing channels with competitive or complementary components at the upstream level. We uncover that the bilateral participation contract is effective in coordinating supply chains with dynamic cooperative emission abatement since it can overcome the disadvantage of uneven distribution of emission-reducing capability endowments among chain members. Finally, we also conduct computational and sensitivity analyses to illustrate the previous results. These findings provide potential implications for firms’ dynamic cooperation in emission abatement.

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

Similar content being viewed by others

References

  • AliResearch. (2016). 2016 Report on green consumers in China. Retrieved from https://www.sohu.com/a/108953836_263856.

  • Arshinder, K., Kanda, A., & Deshmukh, S. G. (2011). A review on supply chain coordination: Coordination mechanisms, managing uncertainty and research directions. Springer.

    Google Scholar 

  • Birkenberg, A., & Birner, R. (2018). The world's first carbon neutral coffee: Lessons on certification and innovation from a pioneer case in Costa Rica. Journal of Cleaner Production, 189, 485–501.

  • Brecard, D., Hlaimi, B., Lucas, S., Perraudeau, Y., & Salladarre, F. (2009). Determinants of demand for green products: An application to eco-label demand for fish in Europe. Ecological Economics, 69(1), 115–125.

    Article  Google Scholar 

  • Cachon, G. P. (2003). Supply chain coordination with contracts. Handbooks in Operations Research and Management Science, 11(11), 227–339.

    Article  Google Scholar 

  • Cachon, G. P., & Lariviere, M. A. (2005). Supply chain coordination with revenue- sharing contracts: Strengths and limitations. Management Science, 51(1), 30–44.

  • Cellini, R., & Lambertinib, L. (2002). A differential game approach to investment in product differentiation. Journal of Economic Dynamics & Control, 27(1), 51–62.

  • CBJ. (2010). Haier’s low carbon supply chain facing integration problems. China Business Journal (CBJ). Retrieved from https://tech.qq.com/a/20100418/000016.htm.

  • Choudhary, A., Suman, R., Dixit, V., Tiwari, M. K., Fernandes, K. J., & Chang, P.-C. (2015). An optimization model for a monopolistic firm serving an environmentally conscious market: Use of chemical reaction optimization algorithm. International Journal of Production Economics, 164, 409–420.

    Article  Google Scholar 

  • Corbett, C. J., & Klassen, R. D. (2006). Extending the horizons: Environmental excellence as key to improving operations. Manufacturing & Service Operations Management, 8(1), 5–22.

  • Du, S., Ma, F., Fu, Z., Zhu, L., & Zhang, J. (2015). Game-theoretic analysis for an emission-dependent supply chain in a “cap-and-trade” system. Annals of Operations Research, 228(1), 135–149.

    Article  Google Scholar 

  • Du, S., Zhu, L., Liang, L., & Ma, F. (2013). Emission-dependent supply chain and environment-policy-making in the “cap-and-trade” system. Energy Policy, 57, 61–67.

    Article  Google Scholar 

  • Erickson, G. M. (2011). A differential game model of the marketing-operations interface. European Journal of Operational Research, 211(2), 394–402.

    Article  Google Scholar 

  • Ghosh, D., & Shah, J. (2015). Supply chain analysis under green sensitive consumer demand and cost sharing contract. International Journal of Production Economics, 164, 319–329.

    Article  Google Scholar 

  • He, L., Zhao, D., & Liu, Y. (2011). Side-payment self-enforcing contract based supply chain dynamic game coordination. Systems Engineering—Theory & Practice, 31(10), 1864–1878.

    Google Scholar 

  • He, L., Zhao, D., & Xia, L. (2015). Game theoretic analysis of carbon emission abatement in fashion supply chains considering vertical incentives and channel structures. Sustainability, 7(4), 4280–4309.

    Article  Google Scholar 

  • He, X., Prasad, A., & Sethi, S. P. (2009). Cooperative advertising and pricing in a dynamic stochastic supply chain: Feedback stackelberg strategies. Production and Operations Management, 18(1), 78–94.

    Google Scholar 

  • He, Z., Xu, S., Shen, W., Long, R., & Chen, H. (2017). Impact of urbanization on energy related CO2 emission at different development levels: Regional difference in China based on panel estimation. Journal of Cleaner Production, 140, 1719–1730.

    Article  Google Scholar 

  • Ibanez, L., & Grolleau, G. (2008). Can ecolabeling schemes preserve the environment? Environmental & Resource Economics, 40(2), 233–249.

  • Itakura, N., Kinbara, Y., Fuwa, T., & Sakamoto, K. (1996). Discrimination of forearm’s motions by surface EMG signals using neural network. Applied Human Science: Journal of Physiological Anthropology, 15(6), 287–294.

    Article  Google Scholar 

  • JD. (2017). JD.com releases green consumption development report “green kinetic energy” to create a new open ecology. Retrieved from http://finance.ce.cn/gsxw/201710/13/t201710-13_26524031.shtml.

  • Ji, J., Zhang, Z., & Yang, L. (2017). Carbon emission reduction decisions in the retail-/dual-channel supply chain with consumers’ preference. Journal of Cleaner Production, 141, 852–867.

    Article  Google Scholar 

  • Jorgensen, S., & Zaccour, G. (2003). Channel coordination over time: Incentive equilibria and credibility. Journal of Economic Dynamics & Control, 27(5), 801–822.

  • Jorgensen, S., Martin-Herran, G., & Zaccour, G. (2010). Dynamic games in the economics and management of pollution. Environmental Modeling & Assessment, 15(6), 433–467.

    Article  Google Scholar 

  • Jørgensen, S., Pierre, S. S., & Zaccour, G. (2000). Dynamic cooperative advertising in a channel. Journal of Retailing, 76(1), 71–92.

    Article  Google Scholar 

  • Jørgensen, S., Taboubi, S., & Zaccour, G. (2003). Retail promotions with negative brand image effects: Is cooperation possible? European Journal of Operational Research, 150(2), 395–405.

    Article  Google Scholar 

  • Kumar, S., & Sethi, S. P. (2009). Dynamic pricing and advertising for web content providers. European Journal of Operational Research, 197(3), 924–944.

  • Leng, M., & Zhu, A. (2009). Side-payment contracts in two-person nonzero-sum supply chain games: Review, discussion and applications. European Journal of Operational Research, 196(2), 600–618.

    Article  Google Scholar 

  • Li, Q., Chen, X., & Huang, Y. (2019). The stability and complexity analysis of a low-carbon supply chain considering fairness concern behavior and sales service. International Journal of Environmental Research and Public Health, 16(15), 2711. https://doi.org/10.3390/ijerph16152711

    Article  Google Scholar 

  • Li, X., Du, J., & Long, H. (2019). Green development behavior and performance of industrial enterprises based on grounded theory study: Evidence from china. Sustainability, 11(15), 4132–4151.

  • Li, X., Du, J., & Long, H. (2020). Understanding the green development behavior and performance of industrial enterprises (GDBP-IE): Scale development and validation. International Journal of Environmental Research and Public Health, 17(5), 1716. https://doi.org/10.3390/ijerph17051716

    Article  Google Scholar 

  • Li, X., Du, J., & Long, H. (2020). Mechanism for green development behavior and performance of industrial enterprises (GDBP-IE) using partial least squares structural equation modeling (PLS-SEM). International Journal of Environmental Research and Public Health, 17(22), 8450. https://doi.org/10.3390/ijerph17228450

    Article  Google Scholar 

  • Linton, J. D., Klassen, R., & Jayaraman, V. (2007). Sustainable supply chains: An introduction. Journal of Operations Management, 25(6), 1075–1082.

    Article  Google Scholar 

  • Liu, H., Long, H., & Li, X. (2020). Identification of critical factors in construction and demolition waste recycling by the grey-DEMATEL approach: A Chinese perspective. Environmental Science and Pollution Research, 27(8), 8507–8525.

    Article  Google Scholar 

  • Liu, P. (2018). Pricing policies and coordination of low-carbon supply chain considering targeted advertisement and carbon emission reduction costs in the big data environment. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2018.10.328

    Article  Google Scholar 

  • Liu, Z., Anderson, T. D., & Cruz, J. M. (2012). Consumer environmental awareness and competition in two-stage supply chains. European Journal of Operational Research, 218(3), 602–613.

    Article  Google Scholar 

  • Long, H., Liu, H., Li, X., & Chen, L. (2020). An evolutionary game theory study for construction and demolition waste recycling considering green development performance under the chinese government’s reward-penalty mechanism. International Journal of Environmental Research and Public Health, 17(17), 6303. https://doi.org/10.3390/ijerph17176303

    Article  Google Scholar 

  • Quinn, B. (2009). Walmarts sustainable supply chain. Pollution Engineering, 41(9), 24.

    Google Scholar 

  • Sethi, S. P. (1983). Deterministic and stochastic optimization of a dynamic advertising model. Optimal Control Applications & Methods, 4(2), 179–184.

    Article  Google Scholar 

  • Upham, P., Dendler, L., & Bleda, M. (2011). Carbon labelling of grocery products: public perceptions and potential emissions reductions. Journal of Cleaner Production, 19(4), 348–355.

    Article  Google Scholar 

  • Vanclay, J. K., Shortiss, J., Aulsebrook, S., Gillespie, A. M., Howell, B. C., Johanni, R., Maher, M. J., Mitchell, K. M., Stewart, M. D., & Yates, J. (2011). Customer response to carbon labelling of groceries. Journal of Consumer Policy, 34(1), 153–160.

    Article  Google Scholar 

  • Wang, Q., Zhao, D., & He, L. (2016). Contracting emission reduction for supply chains considering market low-carbon preference. Journal of Cleaner Production, 120, 72–84.

    Article  Google Scholar 

  • Wang, R., Gou, Q., Choi, T.-M., & Liang, L. (2018). Advertising strategies for mobile platforms with “Apps.” IEEE Transactions on Systems Man Cybernetics-Systems, 48(5), 767–778.

    Article  Google Scholar 

  • Wang, Y., Jiang, L., & Shen, Z. J. (2004). Channel performance under consignment contract with revenue sharing. Management Science, 50(1), 34–47.

    Article  Google Scholar 

  • Wang, Z., Hu, S., Zhang, B., & Wang, B. (2018). Optimizing cooperative carbon emission reduction among enterprises with non-equivalent relationships subject to carbon taxation. Journal of Cleaner Production, 172, 552–565.

    Article  Google Scholar 

  • Ward, H., Burger, M., Chang, Y.-J., Fuertmann, P., Neugebauer, S., Radebach, A., Sproesser, G., Pittner, A., Rethmeier, M., Uhlmann, E., & Steckel, J. C. (2017). Assessing carbon dioxide emission reduction potentials of improved manufacturing processes using multiregional input output frameworks. Journal of Cleaner Production, 163, 154–165.

    Article  Google Scholar 

  • White, J. C., Petry, W. H., & Wagner, W. R. (1996). United nations framework convention on climate change (1992). Educational Testing, 17(4), 8.

    Google Scholar 

  • Wu, D., & Yang, Y. (2020). The low-carbon supply chain coordination problem with consumers’ low-carbon preference. Sustainability, 12(9), 3591. https://doi.org/10.3390/su12093591

    Article  Google Scholar 

  • Xia, L., Guo, T., Qin, J., Yue, X., & Zhu, N. (2018). Carbon emission reduction and pricing policies of a supply chain considering reciprocal preferences in cap-and-trade system. Annals of Operations Research, 268(1–2), 149–175.

    Article  Google Scholar 

  • Yu, B., Wang, J., Lu, X., & Yang, H. (2020). Collaboration in a low-carbon supply chain with reference emission and cost learning effects: Cost sharing versus revenue sharing strategies. Journal of Cleaner Production. https://doi.org/10.1016/j.jcle-pro.2019.119460

    Article  Google Scholar 

  • Zhang, J. J., Nie, T. F., & Du, S. F. (2011). Optimal emission-dependent production policy with stochastic demand. International Journal of Society Systems Science, 3(1/2), 21–39.

    Article  Google Scholar 

  • Zhang, J., Xie, J., & Chen, B. (2013). Cooperative advertising with bilateral participation. Decision Sciences, 44(1), 193–203.

    Article  Google Scholar 

  • Zhang, L., Wang, J., & You, J. (2015). Consumer environmental awareness and channel coordination with two substitutable products. European Journal of Operational Research, 241(1), 63–73.

    Article  Google Scholar 

  • Zhao, D., Xu, C., & Wang, Q. (2014). Differential strategies of joint emission reductions and low-carbon promotion considering competing retailers. Control and Decision, 29(10), 1809–1815.

    Google Scholar 

  • Zhao, D., Yuan, B., & Xu, C. (2016). Dynamic coordination strategy of vertical cooperative on carbon emission reduction in supply chain under low-carbon era. Journal of Industrial Engineering & Engineering Management, 30(1), 147–154.

    Google Scholar 

  • Zhou, Y., & Ye, X. (2018). Differential game model of joint emission reduction strategies and contract design in a dual-channel supply chain. Journal of Cleaner Production, 190(20), 592–607.

Download references

Acknowledgements

The authors sincerely thank the editors and three anonymous reviewers for their time and effort devoted to handling this paper. Their constructive comments and suggestions have helpfully improved the study. This work is partially supported by National Natural Science Foundation of China (NSFC) Grants (Nos.91646118, 71501108, 71602142, 71701144) and The Science & Technology Pillar Key Program of Tianjin Key Research and Development Plan (20YFZCGX00640).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Baiyun Yuan or Kin Keung Lai.

Ethics declarations

The authors declare no conflict of interest.

Additional information

Publisher's Note

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

Appendix

Appendix

Proof of Propostion 1

Maximizing the right side of Eq. (9) produces

$$ Z_{S}^{C*} = \alpha V_{Tx} (x,y){/}\mu_{S} ; $$
(89)
$$ Z_{M}^{C*} = \delta V_{Ty} (x,y){/}\mu_{M} . $$
(90)

Substituting Eqs. (89) and (90) into Eq. (9), respectively gives

$$ \rho V_{T} (x,y) = (\gamma V_{Ty}^{{}} - \beta V_{Tx}^{{}} )x + [(U_{M} + U_{S} )\eta - V_{Ty}^{{}} \beta ]y + (U_{M} + U_{S} )D_{0} + \frac{{\alpha^{2} }}{{2\mu_{S} }}V_{Tx}^{2} + \frac{{\delta^{2} }}{{2\mu_{M} }}V_{Ty}^{2} . $$
(91)

Inferred from Eq. (91), the linear function of \(x\) and \(y\) is the solution of the HJB equation. Set

$$ V_{T} (x,y) = ax + by + c, $$
(92)

where \(a_{1}\), \(b_{1}\) and \(c_{1}\) are constants. From Eq. (92), we know that

$$ \left\{ \begin{gathered} V_{Tx}^{{}} (x,y) = a_{1} \hfill \\ V_{Ty}^{{}} (x,y) = b_{1} \hfill \\ \end{gathered} \right.. $$
(93)

Substitute Eqs. (93) and (94) into Eq. (92) respectively, then collate and compare the coefficients of the similar terms on the left and right sides, and we have

$$ \left\{ \begin{aligned} a_{1} & = (U_{M} + U_{S} )\eta \gamma {\text{/}}(\rho + \beta )^{2} \\ b_{1} & = (U_{M} + U_{S} )\eta {\text{/(}}\rho + \beta {\text{)}} \\ c_{1} & = \frac{{(U_{M} + U_{S} )D_{0} }}{\rho } + \frac{{\alpha ^{2} }}{{2\rho \mu _{S} }}[\frac{{(U_{M} + U_{S} )\eta \gamma }}{{(\rho + \beta )^{2} }}]^{2} + \frac{{\delta ^{2} }}{{2\rho \mu _{M} }}[\frac{{(U_{M} + U_{S} )\eta }}{{\rho + \beta }}]^{2} \\ \end{aligned} \right.. $$
(94)

Substituting Eq. (94) into Eqs. (89) and (90) respectively, the static feedback equilibrium strategy of emission reduction efforts of suppliers and manufacturer under centralized decision making is

$$ \left\{ \begin{gathered} Z_{S}^{C*} = (U_{M} + U_{S} )\alpha \eta \gamma {/[}\mu_{S} (\rho + \beta )^{2} {]} \hfill \\ Z_{M}^{C*} = (U_{M} + U_{S} )\delta \eta {/[}\mu_{M} (\rho + \beta ){]} \hfill \\ \end{gathered} \right.. $$
(95)

Thus, Proposition 1 can be proved.

Proof of Proposition 2

Substituting the optimal strategies \(Z_{S}^{C*} { = }\frac{{(U_{M} + U_{S} )\alpha \eta \gamma }}{{\mu_{S} (\rho + \beta )^{2} }}\) and \(Z_{M}^{C*} { = }\frac{{(U_{M} + U_{S} )\delta \eta }}{{\mu_{M} (\rho + \beta )}}\) into Eq. (2) in the case of centralized decision making of Proposition 1, we can solve the following differential equations

$$ \left\{ \begin{gathered} \dot{x}(t) = \alpha Z_{S} (t) - \beta x(t) \hfill \\ \dot{y}(t) = \gamma x(t) + \delta Z_{M} (t) - \beta y(t) \hfill \\ \end{gathered} \right.. $$
(96)

Eq. (103) is expressed in terms of vectors as follows.

$$ {\dot{\mathbf{x}}} = {\mathbf{AX}} + {\mathbf{b(t)}}. $$
(97)

Introduce vectors \({\mathbf{X}} = (x,y)^{T} {,}\) \({\mathbf{b(t)}} = (\alpha Z_{S} ,\delta Z_{M} )^{T}\) and matrix \({\mathbf{A = }}\left( {\begin{array}{*{20}c} { - \beta } & 0 \\ \gamma & { - \beta } \\ \end{array} } \right)\), where there are homogeneous system of differential equations.

$$ {\dot{\mathbf{x}}} = {\mathbf{AX}}. $$
(98)

Then the general solution of differential equations Eq. (97) consists of a special solution and the general solution of Eq. (98).

To find the general solution of Eq. (98), the eigenvalue of A is obtained firstly as double root \(\lambda_{1} = \lambda_{2} = - \beta\). From the properties of the eigenvalue, one of the eigenvectors is \({\mathbf{v}} = (0,1)^{T}\). The corresponding linear independent solution can be solved as \({\mathbf{x}}_{{\mathbf{1}}} {\mathbf{(t)}} = \left( {_{1}^{0} } \right)e^{ - \beta t}\). Let another corresponding linear independent solution is \({\mathbf{x}}_{{\mathbf{2}}} {\mathbf{(t)}} = ({\mathbf{m}} + {\mathbf{n}}t)e^{ - \beta t}\). The conditions that \({\mathbf{x}}_{{\mathbf{2}}} {\mathbf{(t)}}\) is the solution of Eq. (97) are \({\mathbf{n + m}}l{\mathbf{ = Am}}\) and \({\mathbf{n}}l{\mathbf{ = An}}\), set \({\mathbf{n = v}}\), we can get \({\mathbf{m}} = (1{/}\gamma ,1)^{T}\). Here, the general solution of homogeneous system of differential equations Eq. (98) is

$$ {\mathbf{x(t)}} = C_{1} {\mathbf{x}}_{{\mathbf{1}}} {\mathbf{(t)}}{ + }C_{2} {\mathbf{x}}_{{\mathbf{2}}} {\mathbf{(t)}} = C_{1} \left( {_{1}^{0} } \right)e^{ - \beta t} + C_{2} \left[ {\left( \begin{gathered} 1{/}\gamma \hfill \\ 1 \hfill \\ \end{gathered} \right) + \left( {_{1}^{0} } \right)t} \right]e^{ - \beta t} . $$
(99)

Let the special solution of Eq. (97) be \(\tilde{x} = (f_{1} {; }f_{2} )\),where \(f_{1}\) and \(f_{2}\) are constants, and substitute them into Eq. (2), then we can get

$$ {\tilde{\mathbf{x}}} = \left( \begin{gathered} \, \alpha Z_{S} {/}\beta \hfill \\ \left( {\gamma \alpha Z_{S} {/}\beta + \delta Z_{M} } \right){/}\beta \hfill \\ \end{gathered} \right). $$
(100)

From Eqs. (99) and (100), the general solution of differential equations Eq. (97) is as follows:

$$ {\mathbf{x(t)}} = C_{1} \left( {_{1}^{0} } \right)e^{ - \beta t} + C_{2} \left[ {\left( \begin{gathered} 1{/}\gamma \hfill \\ 1 \hfill \\ \end{gathered} \right) + \left( {_{1}^{0} } \right)t} \right]e^{ - \beta t} + \left( {_{{{(}\gamma f_{1} + \delta Z_{M} {)/}\beta }}^{{ \, \alpha Z_{S} {/}\beta }} } \right). $$
(101)

When \(t = 0\), substituting the initial values \(x(0) = x_{0}\) and \(y(0) = y_{0}\) into Eq. (101) yields

$$ C_{1} = y_{0} - y_{{_{SS} }}^{C*} - (x_{0} - x_{{_{SS} }}^{C*} )\gamma ; $$
(102)
$$ C_{2} = (x_{0} - x_{ss}^{{C^{*} }} )\gamma ; $$
(103)

where \(x_{{_{SS} }}^{C*} = \alpha Z_{S} {/}\beta\) and \(y_{{_{SS} }}^{{\text{C*}}} = (\gamma x_{ss}^{C*} + \delta Z_{M} ){/}\beta\).

Substitute Eqs. (102) and (103) into Eq. (101), and we can get

$$ x^{C} (t) = (x{}_{0} - x_{{_{SS} }}^{C*} )e^{ - \beta t} + x_{{_{SS} }}^{C*} ; $$
(104)
$$ y^{C} (t) = (y{}_{0} - y_{{_{SS} }}^{C*} )e^{ - \beta t} + \gamma (x{}_{0} - x_{SS} )te^{ - \beta t} + y_{{_{SS} }}^{{\text{C*}}} . $$
(105)

Thus, Proposition 2 has been proved.

Proof of Proposition 3

Maximizing the right side of Eqs. (18) and Eq. (19) gives

$$ Z_{S}^{D*} = \alpha V_{Sx}^{{}} (x,y){/}\mu_{S} ; $$
(106)
$$ Z_{M}^{D*} = \delta V_{My}^{{}} (x,y){/}\mu_{M} . $$
(107)

Substitute Eqs. (106) and (107) into Eqs. (18) and (19), respectively, and collate it. Then we can get

$$ \begin{aligned} \rho V_{S}^{D*} (x,y) & = U_{S} (D_{0} + \eta y) - \mu_{S} [\alpha V_{Sx}^{{}} (x,y){/}\mu_{S} ]^{2} {/2} + V_{Sx}^{D*} (x,y)[\alpha^{2} V_{Sx}^{{}} (x,y){/}\mu_{S} - \beta x] \\ & \quad + V_{Sy}^{D*} (x,y)[\delta^{2} V_{My}^{{}} (x,y){/}\mu_{M} + \gamma x - \beta y] \\ \end{aligned} $$
(108)
$$ \begin{aligned} \rho V_{M}^{D*} (x,y) & = U_{M} (D_{0} + \eta y) - \mu_{M} [\delta V_{My}^{{}} (x,y){/}\mu_{M} ]^{2} {/2} + V_{Mx}^{D*} (x,y)[\alpha^{2} V_{Sx}^{{}} (x,y){/}\mu_{S} - \beta x] \\ & \quad + V_{My}^{D*} (x,y)[\gamma x + \delta^{2} V_{My}^{{}} (x,y){/}\mu_{M} - \beta y] \\ \end{aligned} $$
(109)

It is inferred from the Eqs. (108) and (109) that the linear function of x and y is the solution of the HJB equation. Set

$$ V_{S} = a_{2} x + b_{2} y + c_{2} $$
(110)
$$ V_{M} = a_{3} x + b_{3} y + c_{3} $$
(111)

Then \(V_{Sx} = a_{2}\), \(V_{Sy} = b_{2}\), \(V_{Mx} = a_{3}\), \(V_{My} = b_{3}\). Substituting Eqs. (110) and (111) into Eqs. (108) and (109) respectively produces

$$ \rho (a_{2} x + b_{2} y + c_{2} ) = U_{S} (D_{0} + \eta y) - \mu_{S} (\alpha a_{2} {/}\mu_{S} )^{2} {/2} + a_{2} (\alpha^{2} a_{2} {/}\mu_{S} - \beta x) + b_{2} (\gamma x + \delta^{2} b_{3} {/}\mu_{M} - \beta y); $$
(112)
$$ \rho (a_{3} x + b_{3} y + c_{3} ) = U_{M} (D_{0} + \eta y) - \mu_{M} (\delta b_{3} {/}\mu_{M} )^{2} {/2} + a_{3} (\alpha^{2} a_{2} {/}\mu_{S} - \beta x) + b_{3} (\gamma x + \delta^{2} b_{3} {/}\mu_{M} - \beta y). $$
(113)

Collating Eq. (112) and comparing its coefficients of the counterpart terms in both sides yields

$$ \left\{ \begin{aligned} a_{2} & = U_{S} \eta \gamma {\text{/}}(\rho + \beta )^{2} \\ b_{2} & = U_{S} \eta {\text{/(}}\rho + \beta {\text{)}} \\ c_{2} & = U_{S} D_{0} {\text{/}}\rho + \alpha ^{2} [U_{S} \eta \gamma {\text{/}}(\rho + \beta )^{2} ]^{2} {\text{/(}}2\rho \mu _{S} {\text{)}} + \delta ^{2} [U_{S} \eta {\text{/(}}\rho + \beta {\text{)}}]^{2} {\text{/(}}2\rho \mu _{M} {\text{)}} \\ \end{aligned} \right.. $$
(114)

Doing the same thing in Eq. (113) gives

$$ \left\{ \begin{aligned} a_{3} & = U_{M} \eta \gamma {\text{/}}(\rho + \beta )^{2} \\ b_{3} & = U_{M} \eta {\text{/(}}\rho + \beta {\text{)}} \\ c_{3} & = U_{M} D_{0} {\text{/}}\rho + \alpha ^{2} [U_{M} \eta \gamma {\text{/}}(\rho + \beta )^{2} ]^{2} {\text{/(}}2\rho \mu _{S} {\text{)}} + \delta ^{2} [U_{M} \eta {\text{/(}}\rho + \beta {\text{)}}]^{2} {\text{/(}}2\rho \mu _{M} {\text{)}} \\ \end{aligned} \right.. $$
(115)

Then substitute them into Eqs. (106) and (107), we can get

$$ \left\{ \begin{gathered} Z_{S}^{D*} { = }\alpha a_{2} {/}\mu_{S} { = }U_{S} \alpha \eta \gamma {/[}\mu_{S} (\rho + \beta )^{2} {]} \hfill \\ Z_{M}^{D*} { = }\delta b_{3} {/}\mu_{M} { = }U_{M} \delta \eta {/[}\mu_{M} (\rho + \beta ){]} \hfill \\ \end{gathered} \right.. $$
(116)

So, the Proposition 3 has been proved.

Proof of Proposition 4

Similar to the proof of Proposition 2, substituting optimal strategies \(Z_{S}^{D*} { = }U_{S} \alpha \eta \gamma {/[}\mu_{S} (\rho + \beta )^{2} {]}\) and \(Z_{M}^{D*} { = }U_{M} \delta \eta {/[}\mu_{M} (\rho + \beta ){]}\) into Eq. (2) respectively, in the case of decentralized decision making of Proposition 3, we can solve the following differential equations:

$$ \left\{ \begin{gathered} \dot{x}(t) = \alpha Z_{S} (t) - \beta x(t) \hfill \\ \dot{y}(t) = \gamma x(t) + \delta Z_{M} (t) - \beta y(t) \hfill \\ \end{gathered} \right.. $$
(117)

Then the optimal trajectory of Proposition 4 can be obtained.

Proof of Proposition 5

Maximizing the right side of Eqs. (34) and (35) shows us

$$ Z_{S}^{B*} = \alpha V_{Sx}^{{}} (x,y){/[}(1{ - }\omega )\mu_{S} {];} $$
(118)
$$ Z_{M}^{B*} = \delta V_{{M{\text{y}}}}^{{}} (x,y){/[}(1{ - }\psi )\mu_{M} {]}{\text{.}} $$
(119)

Substituting Eqs. (118) and (119) into Eqs. (34) and (35) respectively shows

$$ \begin{aligned} \rho V_{S}^{B*} (x,y) & = U_{S} (D_{0} + \eta y) - \frac{{\mu_{S} }}{2}(1 - \omega )\left[ {\frac{{\alpha V_{Sx}^{{}} (x,y)}}{{(1{ - }\omega )\mu_{S} }}} \right]^{2} - \frac{{\mu_{M} }}{2}\psi \left[ {\frac{{\delta V_{{M{\text{y}}}}^{{}} (x,y)}}{{(1{ - }\psi )\mu_{M} }}} \right]^{2} \\ & \quad + V_{Sx}^{B*} (x,y)\left[ {\alpha \frac{{\alpha V_{Sx}^{{}} (x,y)}}{{(1{ - }\omega )\mu_{S} }} - \beta x} \right] + V_{Sy}^{B*} (x,y)\left[ {\gamma x + \delta \frac{{\delta V_{{M{\text{y}}}}^{{}} (x,y)}}{{(1{ - }\psi )\mu_{M} }} - \beta y} \right]; \\ \end{aligned} $$
(120)
$$ \begin{aligned} \rho V_{M}^{B*} (x,y) & = U_{M} (D_{0} + \eta y) - \frac{{\mu_{M} }}{2}(1 - \psi )\left[ {\frac{{\delta V_{{M{\text{y}}}}^{{}} (x,y)}}{{(1{ - }\psi )\mu_{M} }}} \right]^{2} - \frac{{\mu_{S} }}{2}\omega \left[ {\frac{{\alpha V_{Sx}^{{}} (x,y)}}{{(1{ - }\omega )\mu_{S} }}} \right]^{2} \\ & \quad + V_{Mx}^{B*} (x,y)\left[ {\alpha \frac{{\alpha V_{Sx}^{{}} (x,y)}}{{(1{ - }\omega )\mu_{S} }} - \beta x} \right] + V_{My}^{B*} (x,y)\left[ {\gamma x + \delta \frac{{\delta V_{{M{\text{y}}}}^{{}} (x,y)}}{{(1{ - }\psi )\mu_{M} }} - \beta y} \right]. \\ \end{aligned} $$
(121)

It can be inferred from the Eqs. (120) and (121) that the linear function of x and y is the solution of the HJB equation. Set

$$ V_{S}^{B} = a_{4} x + b_{4} y + c_{4} ; $$
(122)
$$ V_{M}^{B} = a_{5} x + b_{5} y + c_{5} . $$
(123)

Then \(V_{Sx}^{B} = a_{4}\), \(V_{Sy}^{B} = b_{4}\), \(V_{Mx}^{B} = a_{5}\), and \(V_{My}^{B} = b_{5}\). Substituting Eqs. (122) and (123) into Eqs. (120) and (121), respectively, yields

$$ \begin{aligned} \rho (a_{4} x + b_{4} y + c_{4} ) & = U_{S} (D_{0} + \eta y) - \frac{{\mu_{S} }}{2}(1 - \omega )\left[ {\frac{{\alpha a_{4} }}{{(1{ - }\omega )\mu_{S} }}} \right]^{2} - \frac{{\mu_{M} }}{2}\psi \left[ {\frac{{\delta b_{5} }}{{(1{ - }\psi )\mu_{M} }}} \right]^{2} \\ & \quad + a_{4} \left( {\alpha \left[ {\frac{{\alpha a_{4} }}{{(1{ - }\omega )\mu_{S} }}} \right] - \beta x} \right) + b_{4} \left[ {\gamma x + \delta \frac{{\delta b_{5} }}{{(1{ - }\psi )\mu_{M} }} - \beta y} \right]; \\ \end{aligned} $$
(124)
$$ \begin{aligned} \rho (a_{5} x + b_{5} y + c_{5} ) & = U_{M} (D_{0} + \eta y) - \frac{{\mu_{M} }}{2}(1 - \psi )\left[ {\frac{{\delta b_{5} }}{{(1{ - }\psi )\mu_{M} }}} \right]^{2} - \frac{{\mu_{S} }}{2}\omega \left[ {\frac{{\alpha a_{4} }}{{(1{ - }\omega )\mu_{S} }}} \right]^{2} \\ & \quad + a_{5} \left( {\alpha \left[ {\frac{{\alpha a_{4} }}{{(1{ - }\omega )\mu_{S} }}} \right] - \beta x} \right) + b_{5} \left[ {\gamma x + \delta \frac{{\delta b_{5} }}{{(1{ - }\psi )\mu_{M} }} - \beta y} \right]. \\ \end{aligned} $$
(125)

Collate Eq. (124) and compare its coefficients of the similar terms on the left and right sides, and we can get

$$ \left\{ \begin{aligned} a_{4} & = U_{S} \eta \gamma {\text{/}}(\rho + \beta )^{2} \\ b_{4} & = U_{S} \eta {\text{/(}}\rho + \beta {\text{)}} \\ c_{4} & = \frac{{U_{S} D_{0} }}{\rho } + \frac{{\alpha ^{2} }}{{2\rho \mu _{S} (1 - \omega )}}\left[ {\frac{{U_{S} \eta \gamma }}{{(\rho + \beta )^{2} }}} \right]^{2} - \frac{{\psi \delta ^{2} }}{{2\rho \mu _{M} (1 - \psi )^{2} }}\left[ {\frac{{U_{S} \eta }}{{\rho + \beta }}} \right]^{2} + \frac{{U_{S} U_{M} \delta ^{2} }}{{\rho \mu _{M} (1 - \psi )}}\left[ {\frac{\eta }{{\rho + \beta }}} \right]^{2} \\ \end{aligned} \right.. $$
(126)

Collating Eq. (125) and compare its coefficients of the similar terms in the left and right sides gives

$$ \left\{ \begin{aligned} a_{5} & = U_{M} \eta \gamma {\text{/}}(\rho + \beta )^{2} \\ b_{5} & = U_{M} \eta {\text{/(}}\rho + \beta {\text{)}} \\ c_{5} & = \frac{{U_{M} D_{0} }}{\rho } + \frac{{\delta ^{2} }}{{2\rho \mu _{M} (1 - \psi )}}\left[ {\frac{{U_{M} \eta }}{{\rho + \beta }}} \right]^{2} - \frac{{\omega \alpha ^{2} }}{{2\rho \mu _{S} (1 - \omega )^{2} }}\left[ {\frac{{U_{S} \eta \gamma }}{{(\rho + \beta )^{2} }}} \right]^{2} + \frac{{U_{S} U_{M} \alpha ^{2} }}{{\rho \mu _{S} (1 - \omega )}}\left[ {\frac{{\eta \gamma }}{{(\rho + \beta )^{2} }}} \right]^{2} \\ \end{aligned} \right.. $$
(127)

Then substitute them into Eqs. (118) and (119), we can get

$$ Z_{S}^{B*} = U_{S} \alpha \eta \gamma {/[}\mu_{S} (1 - \omega )(\rho + \beta )^{2} {];} $$
(128)
$$ Z_{M}^{B*} = U_{M} \delta \eta {/[}\mu_{M} (1 - \psi )(\rho + \beta ){]}{\text{.}} $$
(129)

Coordinating the supply chain system can make the optimal emission reduction efforts of suppliers and manufacturer under bilateral decision making equal to those under centralized decision making, so \(Z_{S}^{C*} = Z_{S}^{B*}\), \(Z_{M}^{C*} = Z_{M}^{B*}\), i.e., \(\frac{{(U_{M} + U_{S} )\alpha \eta \gamma }}{{\mu_{S} (\rho + \beta )^{2} }} = \frac{{U_{S} \alpha \eta \gamma }}{{(1 - \omega )\mu_{S} (\rho + \beta )^{2} }}\), \(\frac{{(U_{M} + U_{S} )\delta \eta }}{{\mu_{M} (\rho + \beta )}} = \frac{{U_{M} \delta \eta }}{{(1 - \psi )\mu_{M} (\rho + \beta )}}\).

The comparison gives \(U_{M} + U_{S} = U_{S} {/(}1 - \omega {)}\) and \(U_{M} + U_{S} = U_{M} {/(}1 - \psi {)}\). Namely, \(\omega^{*} = U_{M} {/(}U_{M} + U_{S} {)}\), and \(\psi^{*} = U_{S} {/(}U_{M} + U_{S} {)}\). Thus, Proposition 5 can be proved.

Proof of Proposition 6

Maximizing the right side of Eq. (50) yields

$$ Z_{{S_{i} }}^{C*} = \alpha_{i} V_{{Tx_{i} }}^{{}} (x,y){/}\mu_{{S_{i} }} ; $$
(130)
$$ Z_{M}^{C*} = \delta V_{Ty}^{{}} (x,y){/}\mu_{M} . $$
(131)

Substituting Eqs. (130) and (131) into Eq. (50) derives

$$ \begin{aligned} \rho V_{T}^{C*} (x,y) & = \left( {U_{M} + \sum\nolimits_{i = 1}^{2} {v_{i} U_{{S_{i} }} } } \right)(D_{0} + \eta y) - \mu_{M} \left[ {\delta V_{Ty}^{{}} (x,y){/}\mu_{M} } \right]^{2} {/2} - \sum\nolimits_{i = 1}^{2} {\mu_{{S_{i} }} [\alpha_{i} V_{{Tx_{i} }}^{{}} (x,y){/}\mu_{{S_{i} }} ]^{2} {/2}} \\ & \quad + \sum\nolimits_{i = 1}^{2} {V_{Txi}^{C*} (x,y)\left[ {\alpha_{i}^{2} V_{{Tx_{i} }}^{{}} (x,y){/}\mu_{{S_{i} }} - \beta x_{i}^{{}} } \right]} + V_{Ty}^{C*} (x,y)\left[ {\sum\nolimits_{i = 1}^{2} {\gamma_{i} v_{i} x_{i} } + \delta^{2} V_{Ty}^{{}} (x,y){/}\mu_{M} - \beta {\text{y}}} \right]. \\ \end{aligned} $$
(132)

Inferred from the Eq. (132), the linear function of x and y is the solution of HJB equation. Let

$$ V_{T}^{C} = \sum\nolimits_{i = 1}^{2} {a_{6i} x} + b_{6} y + c_{6} . $$
(133)

Then \(V_{{Tx_{i} }}^{C} = a_{6i}\) and \(V_{Ty}^{C} = b_{6}\). Substituting Eq. (133) into Eq. (132) attains

$$ \begin{aligned} \rho (a_{6i} x + b_{6} y + c_{6} ) & = (b_{6} \gamma_{1} v_{1} - a_{61} \beta )x_{1} + (b_{6} \gamma_{2} v_{2} - a_{62} \beta )x_{2} + [(U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} )\eta - b_{6} \beta ]y \\ & \quad + (U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} )D_{0} - \mu_{M} (\delta b_{6} {/}\mu_{M} )^{2} {/2} - \mu_{{S_{1} }} (a_{61} \alpha_{1} {/}\mu_{{S_{1} }} )^{2} {/2} - \mu_{{S_{2} }} (a_{62} \alpha_{2} {/}\mu_{{S_{2} }} )^{2} {/2} \\ & \quad + a_{61} \alpha_{1} (a_{61} \alpha_{1} {/}\mu_{{S_{1} }} ) + a_{62} \alpha_{2} (a_{62} \alpha_{2} {/}\mu_{{S_{2} }} ) + b_{6} \delta^{2} b_{6} {/}\mu_{M} . \\ \end{aligned} $$
(134)

Comparing its coefficients of the similar terms of the left and right sides in Eq. (134) yields

$$ \left\{ \begin{aligned} a_{{61}} & = \left( {U_{M} + \sum\nolimits_{{j = 1}}^{2} {v_{i} U_{{S_{i} }} } } \right)\eta \gamma _{1} v_{1} {\text{/}}(\rho + \beta )^{2} \\ a_{{62}} & = \left( {U_{M} + \sum\nolimits_{{j = 1}}^{2} {v_{i} U_{{S_{i} }} } } \right)\eta \gamma _{2} v_{2} {\text{/}}(\rho + \beta )^{2} \\ b_{6} & = \left( {U_{M} + \sum\nolimits_{{j = 1}}^{2} {v_{i} U_{{S_{i} }} } } \right)\eta {\text{/(}}\rho + \beta {\text{)}} \\ c_{6} & = \frac{{\left( {U_{M} + \sum\nolimits_{{j = 1}}^{2} {v_{i} U_{{S_{i} }} } } \right)D_{0} }}{\rho } + \left[ {\sum\nolimits_{{j = 1}}^{2} {\frac{{\alpha _{i} ^{2} (\gamma _{i} v_{i} )^{2} }}{{\mu _{{S_{i} }} (\rho + \beta )^{2} }} + \frac{{\delta ^{2} }}{{\mu _{M} }}} } \right]\frac{{\left( {U_{M} + \sum\nolimits_{{j = 1}}^{2} {v_{i} U_{{S_{i} }} } } \right)^{2} \eta ^{2} }}{{2\rho (\rho + \beta )^{2} }} \\ \end{aligned} \right.. $$
(135)

Then substituting them into Eqs. (130) and (131), we have

$$ Z_{{S_{i} }}^{C*} = (U_{M} + \sum\nolimits_{j = 1}^{2} {v_{j} U_{{S_{j} }} } )\alpha_{i} \eta \gamma_{i} v_{i} {/[}\mu_{{S_{i} }} (\rho + \beta )^{2} {];} $$
(136)
$$ Z_{{S_{2} }}^{C*} = \left( {U_{M} + \sum\nolimits_{j = 1}^{2} {v_{j} U_{{S_{j} }} } } \right)\alpha_{2} \eta \gamma_{2} v_{2} {/[}\mu_{{S_{2} }} (\rho + \beta )^{2} {];} $$
(137)
$$ Z_{M}^{C*} = \left( {U_{M} + \sum\nolimits_{j = 1}^{2} {v_{j} U_{{S_{j} }} } } \right)\eta \delta {/[}\mu_{M} (\rho + \beta ){]}{\text{.}} $$
(138)

Thus, Proposition 6 can be proved.

Proof of Proposition 7

Plugging optimal strategies \(Z_{{S_{i} }}^{C*} = (U_{M} + \sum\nolimits_{i = 1}^{2} {v_{i} U_{{S_{i} }} } )\alpha_{i} \eta \gamma_{i} v_{i} {/[}\mu_{{S_{i} }} (\rho + \beta )^{2} {]}\) and \(Z_{M}^{C*} = (U_{M} + \sum\nolimits_{j = 1}^{2} {v_{j} U_{{S_{j} }} } )\eta \delta {/[}\mu_{M} (\rho + \beta ){]}\) into Eq. (2) respectively, in the case of centralized decision making of Proposition 6, we can solve the following differential equations

$$ \left\{ \begin{gathered} \dot{x}(t) = \alpha Z_{S} (t) - \beta x(t) \hfill \\ \dot{y}(t) = \gamma x(t) + \delta Z_{M} (t) - \beta y(t) \hfill \\ \end{gathered} \right.. $$
(139)

Then the optimal trajectory of Proposition 7 can be obtained.

Proof of Proposition 8

Maximizing the right side of Eqs. (62) and (63) gives

$$ Z_{{S_{i} }}^{D*} { = }\alpha_{i} V_{{S_{i} x_{i} }}^{{}} (x,y){/}\mu_{{S_{i} }} ; $$
(140)
$$ Z_{M}^{D*} = \delta V_{My}^{{}} (x,y){/}\mu_{M} . $$
(141)

Substituting Eqs. (140) and (141) into Eqs. (62) and (63), respectively, we have

$$ \begin{aligned} \rho V_{{S_{i} }}^{D*} (x,y) & = v_{i} U_{{S_{i} }} (D_{0} + \eta y) - \mu_{{S_{i} }} [\alpha_{i} V_{{S_{i} x_{i} }}^{{}} (x,y){/}\mu_{{S_{i} }} ]^{2} {/2} + \sum\nolimits_{j = 1}^{2} {V_{{S_{i} x_{j} }}^{D} (\alpha_{j} \alpha_{i} V_{{S_{i} x_{i} }}^{{}} (x,y){/}\mu_{{S_{i} }} - \beta x_{j} )} \\ & \quad + V_{{S_{i} y}}^{D} (\sum\nolimits_{j = 1}^{2} {v_{j} x_{j} \gamma_{j} } + \delta^{2} V_{My}^{{}} (x,y){/}\mu_{M} - \beta y); \\ \end{aligned} $$
(142)
$$ \begin{aligned} \rho V_{M}^{D*} (x,y) & = U_{M} (D_{0} + \eta y) - \mu_{M} [\delta V_{My}^{{}} (x,y){/}\mu_{M} ]^{2} {/2} + \sum\nolimits_{i = 1}^{2} {V_{{Mx_{i} }}^{D} (\alpha_{i}^{2} V_{{S_{i} x_{i} }}^{{}} (x,y){/}\mu_{{S_{i} }} - \beta x_{i} )} \\ & \quad + V_{My}^{D} \left( {\sum\nolimits_{j = 1}^{2} {v_{j} x_{j} \gamma_{j} } + \delta^{2} V_{My}^{{}} (x,y){/}\mu_{M} - \beta y} \right). \\ \end{aligned} $$
(143)

Inferred from Eqs. (142) and (143), the linear function of x and y is the solution for HJB equation.

$$ V_{{S_{i} }}^{D} = \sum\nolimits_{j = 1}^{2} {a_{7ji} x_{j} } + b_{7i} y + c_{7i} ; $$
(144)
$$ V_{M}^{D} = \sum\nolimits_{i = 1}^{2} {a_{8i} x_{i} } + b_{8} y + c_{8} . $$
(145)

Then \(V_{{S_{i} }}^{D} = a_{7ji}\) (\(j \ne i\)), \(V_{{S_{i} y}}^{D} = b_{7i}\), \(V_{{S_{i} x_{i} }}^{D} = a_{7ii}\), \(V_{{Mx_{i} }}^{D} = a_{8i}\), and \(V_{My}^{D} = b_{8}\).

Substituting Eqs. (144) and (145) into Eqs. (142) and (143), respectively, we have

$$ \begin{aligned} \rho (a_{711} x_{1} + a_{721} x_{2} + b_{71} y + c_{71} ) & = (b_{71} \gamma_{1} v_{1} - a_{711} \beta )x_{1} + (b_{71} \gamma_{2} v_{2} - a_{721} \beta )x_{2} + (v_{1} U_{{S_{1} }} \eta - b_{71} \beta )y \\ & \quad + v_{1} U_{{S_{1} }} D_{0} - \frac{{\mu_{{S_{1} }} }}{2}\left( {\frac{{a_{711} \alpha_{1} }}{{\mu_{{S_{1} }} }}} \right)^{2} + a_{711} \alpha_{1} \left( {\frac{{a_{711} \alpha_{1} }}{{\mu_{{S_{1} }} }}} \right) + a_{721} \alpha_{2} \left( {\frac{{a_{722} \alpha_{2} }}{{\mu_{{S_{2} }} }}} \right) + b_{71} \delta \frac{{\delta b_{8} }}{{\mu_{M} }}; \\ \end{aligned} $$
(146)
$$ \begin{aligned} \rho (a_{712} x_{1} + a_{722} x_{2} + b_{72} y + c_{72} ) & = (b_{72} \gamma_{1} v_{1} - a_{712} \beta )x_{1} + (b_{72} \gamma_{2} v_{2} - a_{722} \beta )x_{2} + (v_{2} U_{{S_{2} }} \eta - b_{72} \beta )y \\ & \quad + v_{2} U_{{S_{2} }} D_{0} - \frac{{\mu_{{S_{2} }} }}{2}\left( {\frac{{a_{722} \alpha_{2} }}{{\mu_{{S_{2} }} }}} \right)^{2} + a_{712} \alpha_{1} \left( {\frac{{a_{711} \alpha_{1} }}{{\mu_{{S_{1} }} }}} \right) + a_{722} \alpha_{2} \left( {\frac{{a_{722} \alpha_{2} }}{{\mu_{{S_{2} }} }}} \right) + b_{72} \delta \frac{{\delta b_{8} }}{{\mu_{M} }}; \\ \end{aligned} $$
(147)
$$ \begin{aligned} \rho (a_{81} x_{1} + a_{82} x_{2} + b_{8} y + c_{8} ) & = (b_{8} \gamma_{1} v_{1} - a_{81} \beta )x_{1} + (b_{8} \gamma_{2} v_{2} - a_{82} \beta )x_{2} + (U_{M} \eta - b_{8} \beta )y \\ & \quad + U_{M} D_{0} - \frac{{\mu_{M} }}{2}\left( {\frac{{b_{8} \delta }}{{\mu_{M} }}} \right)^{2} + a_{81} \alpha_{1} \left( {\frac{{a_{711} \alpha_{1} }}{{\mu_{{S_{1} }} }}} \right) + a_{82} \alpha_{2} \left( {\frac{{a_{722} \alpha_{2} }}{{\mu_{{S_{2} }} }}} \right) + b_{8} \delta \frac{{\delta b_{8} }}{{\mu_{M} }}. \\ \end{aligned} $$
(148)

From Eq. (146), comparing its coefficients of the similar terms on the left and right sides shows us

$$ \left\{ \begin{aligned} a_{{711}} & = v_{1} U_{{S_{1} }} \eta \gamma _{1} v_{1} {\text{/}}(\rho + \beta )^{2} \\ a_{{721}} & = v_{1} U_{{S_{1} }} \eta \gamma _{2} v_{2} /(\rho + \beta )^{2} \\ b_{{71}} & = v_{1} U_{{S_{1} }} \eta {\text{/(}}\rho + \beta {\text{)}} \\ c_{{71}} & = \frac{{v_{1} U_{{S_{1} }} D_{0} }}{\rho } + \frac{{\alpha _{1} ^{2} }}{{2\rho \mu _{{S_{1} }} }}\left[ {\frac{{v_{1} U_{{S_{1} }} \eta \gamma _{1} v_{1} }}{{(\rho + \beta )^{2} }}} \right]^{2} + \frac{{\alpha _{2} ^{2} v_{1} \gamma _{1} \gamma _{2} v_{2} }}{{\rho \mu _{{S_{2} }} }}\left[ {\frac{{v_{1} U_{{S_{1} }} \eta }}{{(\rho + \beta )^{2} }}} \right]^{2} + \frac{{U_{{M_{1} }} v_{1} U_{{S_{1} }} }}{{\rho \mu _{M} }}\left[ {\frac{{\delta \eta }}{{\rho + \beta }}} \right]^{2} \\ \end{aligned} \right.. $$
(149)

Collating Eq. (147) and comparing its coefficients of the similar terms on the left and right sides gives

$$ \left\{ \begin{aligned} a_{{712}} & = v_{2} U_{{S_{2} }} \eta \gamma _{1} v_{1} {\text{/}}(\rho + \beta )^{2} \\ a_{{722}} & = v_{2} U_{{S_{2} }} \eta \gamma _{2} v_{2} {\text{/}}(\rho + \beta )^{2} \\ b_{{72}} & = v_{2} U_{{S_{2} }} \eta {\text{/(}}\rho + \beta {\text{)}} \\ c_{{72}} & = \frac{{v_{2} U_{{S_{2} }} D_{0} }}{\rho } + \frac{{v_{1} U_{{S_{1} }} v_{2} U_{{S_{2} }} \alpha _{1} ^{2} }}{{2\rho \mu _{{S_{1} }} }}\left[ {\frac{{\eta \gamma _{1} v_{1} }}{{(\rho + \beta )^{2} }}} \right]^{2} + \frac{{\alpha _{2} ^{2} }}{{2\rho \mu _{{S_{2} }} }}\left[ {\frac{{v_{2} U_{{S_{2} }} \eta \gamma _{2} v_{2} }}{{(\rho + \beta )^{2} }}} \right]^{2} + \frac{{U_{M} v_{2} U_{{S_{2} }} }}{{\rho \mu _{M} }}\left[ {\frac{{\delta \eta }}{{\rho + \beta }}} \right]^{2} \\ \end{aligned} \right.. $$
(150)

Comparing the coefficients of terms on the left and right sides in Eq. (148) shows us

$$ \left\{ \begin{aligned} a_{{81}} & = U_{M} \eta \gamma _{1} v_{1} {\text{/}}(\rho + \beta )^{2} \\ a_{{82}} & = U_{M} \eta \gamma _{2} v_{2} {\text{/}}(\rho + \beta )^{2} \\ b_{8} & = U_{M} \eta {\text{/(}}\rho + \beta {\text{)}} \\ c_{8} & = \frac{{U_{M} D_{0} }}{\rho } + \frac{{v_{1} U_{{S_{1} }} U_{M} \alpha _{1} ^{2} }}{{\rho \mu _{{S_{1} }} }}\left[ {\frac{{\eta \gamma _{1} v_{1} }}{{(\rho + \beta )^{2} }}} \right]^{2} + \frac{{v_{2} U_{{S_{2} }} U_{M} \alpha _{2} ^{2} }}{{\rho \mu _{{S_{2} }} }}\left[ {\frac{{\eta \gamma _{2} v_{2} }}{{(\rho + \beta )^{2} }}} \right]^{2} + \frac{{\delta ^{2} }}{{2\rho \mu _{M} }}\left[ {\frac{{U_{M} \eta }}{{\rho + \beta }}} \right]^{2} \\ \end{aligned} \right.. $$
(151)

Then substitute them into Eqs. (140) and (141), we can get

$$ Z_{{S_{1} }}^{D*} { = }U_{{S_{1} }} \alpha_{1} \eta \gamma_{1} v_{1}^{2} {/[}\mu_{{S_{1} }} (\rho + \beta )^{2} {];} $$
(152)
$$ Z_{{S_{2} }}^{D*} { = }U_{{S_{2} }} \alpha_{2} \eta \gamma_{2} v_{2}^{2} {/}[\mu_{{S_{2} }} (\rho + \beta )^{2} ]; $$
(153)
$$ Z_{M}^{D*} { = }U_{M} \delta \eta {/[}\mu_{M} (\rho + \beta ){]}{\text{.}} $$
(154)

Thus, Proposition 8 can be proved.

Proof of Proposition 9

Similar to the proof of Proposition 2, substituting the optimal strategies \(Z_{{S_{i} }}^{D*} { = }U_{{S_{i} }} \alpha_{i} \eta \gamma_{i} v_{i}^{2} {/[}\mu_{{S_{i} }} (\rho + \beta )^{2} {]}\) and \(Z_{M}^{D*} { = }U_{M} \delta \eta {/[}\mu_{M} (\rho + \beta ){]}\) into Eq. (2) in the case of decentralized decision making of Proposition 8, we can solve the following differential equations

$$ \left\{ \begin{gathered} \dot{x}(t) = \alpha Z_{S} (t) - \beta x(t) \hfill \\ \dot{y}(t) = \gamma x(t) + \delta Z_{M} (t) - \beta y(t) \hfill \\ \end{gathered} \right.. $$
(155)

Then the optimal trajectory of Proposition 9 can be obtained.

Proof of Proposition 10

Maximizing the right side of Eqs. (77) and (78) gives

$$ Z_{{S_{i} }}^{B*} { = }\alpha_{i} V_{{S_{i} x_{i} }}^{{}} (x,y){/[}\mu_{{S_{i} }} (1 - \omega_{i} ){];} $$
(156)
$$ Z_{M}^{B*} = {{\delta V_{My}^{{}} (x,y)} \mathord{\left/ {\vphantom {{\delta V_{My}^{{}} (x,y)} {\left[ {\mu_{M} \left( {1 - \sum\nolimits_{i = 1}^{2} {\psi_{i} } } \right)} \right]}}} \right. \kern-\nulldelimiterspace} {\left[ {\mu_{M} \left( {1 - \sum\nolimits_{i = 1}^{2} {\psi_{i} } } \right)} \right]}}{.} $$
(157)

Substituting Eqs. (156) and (157) into Eqs. (77) and (78) respectively attains

$$ \begin{aligned} \rho V_{{S_{i} }}^{B*} (x,y) & = U_{{S_{i} }} v_{i} (D_{0} + \eta y) - \frac{{\mu_{{S_{i} }} }}{2}(1 - \omega_{i} )\left[ {\frac{{\alpha_{i} V_{{S_{i} x_{i} }}^{{}} (x,y)}}{{\mu_{{S_{i} }} (1 - \omega_{i} )}}} \right]^{2} - \frac{{\mu_{M} }}{2}\psi_{i} \left[ {\frac{{\delta V_{{M_{1} y}}^{{}} (x,y)}}{{\mu_{M} (1 - \sum\nolimits_{j = 1}^{2} {\psi_{j} } )}}} \right]^{2} \\ & \quad + \sum\limits_{j = 1}^{2} {V_{{S_{i} x_{j} }}^{B*} \left[ {\alpha_{j} \frac{{\alpha_{i} V_{{S_{i} x_{i} }}^{{}} (x,y)}}{{\mu_{{S_{i} }} (1 - \omega_{i} )}} - \beta x_{j} } \right]} + V_{{S_{i} y}}^{B*} \left[ {\sum\limits_{j = 1}^{2} {\gamma_{j} x_{j} v_{j} } + \frac{{\delta^{2} V_{My}^{{}} (x,y)}}{{\mu_{M} (1 - \sum\nolimits_{j = 1}^{2} {\psi_{j} } )}} - \beta y} \right]; \\ \end{aligned} $$
(158)
$$ \begin{aligned} \rho V_{M}^{B*} (x,y) & = U_{{M_{1} }} (D_{0} + \eta y) - \frac{{\mu_{M} }}{2}(1 - \sum\nolimits_{j = 1}^{2} {\psi_{j} } )\left[ {\frac{{\delta V_{My}^{{}} (x,y)}}{{\mu_{M} (1 - \sum\nolimits_{j = 1}^{2} {\psi_{j} } )}}} \right]^{2} - \sum\limits_{i = 1}^{2} {\frac{{\mu_{{S_{i} }} }}{2}\omega_{i} \left[ {\frac{{\alpha_{i} V_{{S_{i} x_{i} }}^{{}} (x,y)}}{{\mu_{{S_{i} }} (1 - \omega_{i} )}}} \right]}^{2} \\ & \quad + \sum\nolimits_{j = 1}^{2} {V_{{Mx_{i} }}^{B*} \left( {\frac{{\alpha_{i}^{2} V_{{S_{i} x_{i} }}^{{}} (x,y)}}{{\mu_{{S_{i} }} (1 - \omega_{i} )}} - \beta x_{i} } \right)} + V_{My}^{B*} \left[ {\sum\limits_{i = 1}^{2} {\gamma_{i} x_{i} v_{i} } + \frac{{\delta^{2} V_{My}^{{}} (x,y)}}{{\mu_{M} (1 - \sum\nolimits_{j = 1}^{2} {\psi_{j} } )}} - \beta y} \right]. \\ \end{aligned} $$
(159)

From Eqs. (158) and (159), The HJB equation has the linear function of \(x\) and \(y\) as the solution. Set

$$ V_{{S_{i} }}^{B} = \sum\nolimits_{j = 1}^{2} {a_{9ji} x_{j} } + b_{9i} y + c_{9i} ; $$
(160)
$$ V_{M}^{B} = \sum\nolimits_{i = 1}^{2} {a_{10i} x_{i} } + b_{10} y + c_{10} . $$
(161)

Then \(V_{{S_{i} x_{i} }}^{B} = a_{9ii}\), \(V_{{S_{i} x_{j} }}^{B} = a_{9ji}\) Eq. (\(j \ne i\)); \(V_{{S_{i} y}}^{B} = b_{9i}\), \(V_{{M_{1} x_{i} }}^{B} = a_{10i}\), \(V_{{M_{1} y}}^{B} = b_{10}\).

Plugging Eqs. (160) and (161) into Eqs. (158) and (159) respectively gives

$$ \begin{aligned} \rho (a_{911} x_{1} + a_{921} x_{2} + b_{91} y + c_{91} ) & = (b_{91} \gamma_{1} v_{1} - a_{911} \beta )x_{1} + (b_{91} \gamma_{2} v_{2} - a_{921} \beta )x_{2} + (v_{1} U_{{S_{1} }} \eta - b_{91} \beta )y \\ & \quad + v_{1} U_{{S_{1} }} D_{0} - \frac{{\mu_{{S_{1} }} }}{2}(1 - \omega_{1} )\left[ {\frac{{a_{911} \alpha_{1} }}{{\mu_{{S_{1} }} (1 - \omega_{1} )}}} \right]^{2} + a_{911} \alpha_{1} \left[ {\frac{{a_{911} \alpha_{1} }}{{\mu_{{S_{1} }} (1 - \omega_{1} )}}} \right] \\ & \quad + a_{921} \alpha_{2} \left[ {\frac{{a_{922} \alpha_{2} }}{{\mu_{{S_{2} }} (1 - \omega_{2} )}}} \right] + b_{91} \delta \frac{{\delta b_{10} }}{{\mu_{M} (1 - \psi_{1} - \psi_{2} )}} - \frac{{\mu_{M} }}{2}\psi_{1} \left[ {\frac{{\delta b_{10} }}{{\mu_{M} (1 - \psi_{1} - \psi_{2} )}}} \right]^{2} ; \\ \end{aligned} $$
(162)
$$ \begin{aligned} \rho (a_{912} x_{1} + a_{922} x_{2} + b_{92} y + c_{92} ) & = (b_{92} \gamma_{1} v_{1} - a_{912} \beta )x_{1} + (b_{92} \gamma_{2} v_{2} - a_{922} \beta )x_{2} + (v_{2} U_{{S_{2} }} \eta - b_{92} \beta )y \\ & \quad + v_{2} U_{{S_{2} }} D_{0} - \frac{{\mu_{{S_{2} }} }}{2}(1 - \omega_{2} )\left[ {\frac{{a_{922} \alpha_{2} }}{{\mu_{{S_{2} }} (1 - \omega_{2} )}}} \right]^{2} + a_{912} \alpha_{1} \left[ {\frac{{a_{911} \alpha_{1} }}{{\mu_{{S_{1} }} (1 - \omega_{1} )}}} \right] \\ & \quad + a_{922} \alpha_{2} \left[ {\frac{{a_{922} \alpha_{2} }}{{\mu_{{S_{2} }} (1 - \omega_{2} )}}} \right] + b_{92} \delta \frac{{\delta b_{10} }}{{\mu_{M} (1 - \psi_{1} - \psi_{2} )}} - \frac{{\mu_{M} }}{2}\psi_{2} \left[ {\frac{{\delta b_{10} }}{{\mu_{M} (1 - \psi_{1} - \psi_{2} )}}} \right]^{2} ; \\ \end{aligned} $$
(163)
$$ \begin{aligned} \rho (a_{101} x_{1} + a_{102} x_{2} + b_{10} y + c_{10} ) & = (b_{10} \gamma_{1} v_{1} - a_{101} \beta )x_{1} + (b_{10} \gamma_{2} v_{2} - a_{102} \beta )x_{2} + (U_{M} \eta - b_{10} \beta )y \\ & \quad + U_{M} D_{0} - \frac{{\mu_{M} }}{2}(1 - \psi_{1} - \psi_{2} )\left[ {\frac{{b_{10} \delta }}{{\mu_{M} (1 - \psi_{1} - \psi_{2} )}}} \right]^{2} - \frac{{\mu_{{S_{1} }} }}{2}\omega_{1} \left[ {\frac{{a_{911} \alpha_{1} }}{{\mu_{{S_{1} }} (1 - \omega_{1} )}}} \right]^{2} - \frac{{\mu_{{S_{2} }} }}{2}\omega_{2} \left[ {\frac{{a_{922} \alpha_{2} }}{{\mu_{{S_{2} }} (1 - \omega_{2} )}}} \right]^{2} \\ & \quad + a_{101} \alpha_{1} \left[ {\frac{{a_{911} \alpha_{1} }}{{\mu_{{S_{1} }} (1 - \omega_{1} )}}} \right] + a_{102} \alpha_{2} \left[ {\frac{{a_{922} \alpha_{2} }}{{\mu_{{S_{2} }} (1 - \omega_{1} )}}} \right] + b_{10} \delta \frac{{\delta b_{10} }}{{\mu_{M} (1 - \psi_{1} - \psi_{2} )}}. \\ \end{aligned} $$
(164)

Collating Eq. (162) and compare its coefficients of the similar terms on both sides yields

$$ \left\{ \begin{aligned} a_{911} & = v_{1} U_{{S_{1} }} \eta \gamma_{1} v_{1} {/}(\rho + \beta )^{2} \\ a_{921} & = v_{1} U_{{S_{1} }} \eta \gamma_{2} v_{2} {/}(\rho + \beta )^{2} \\ b_{91} & = v_{1} U_{{S_{1} }} \eta {/(}\rho + \beta {)} \\ c_{91} & = \frac{{v_{1} U_{{S_{1} }} D_{0} }}{\rho } + \frac{{\alpha_{1}^{2} }}{{2\rho \mu_{{S_{1} }} (1 - \omega_{1} )}}\left[ {\frac{{v_{1} U_{{S_{1} }} \eta \gamma_{1} v_{1} }}{{(\rho + \beta )^{2} }}} \right]^{2} + \frac{{\alpha_{2}^{2} v_{1} U_{{S_{1} }} v_{2} U_{{S_{2} }} }}{{\rho \mu_{{S_{2} }} (1 - \omega_{2} )}}\left[ {\frac{{\eta \gamma_{2} v_{2} }}{{(\rho + \beta )^{2} }}} \right]^{2} \\ & \quad + \frac{{v_{1} U_{{S_{1} }} U_{M} \delta^{2} }}{{\rho \mu_{M} (1 - \psi_{1} - \psi_{2} )}}\left[ {\frac{\eta }{\rho + \beta }} \right]^{2} + \frac{{\psi_{1} \delta^{2} }}{{2\rho \mu_{M} }}\left[ {\frac{{U_{M} \eta }}{{(1 - \psi_{1} - \psi_{2} )(\rho + \beta )}}} \right]^{2} \\ \end{aligned} \right.. $$
(165)

Collating Eq. (163) and comparing its coefficients of the terms on the left and right sides gives

$$ \left\{ \begin{aligned} a_{912} & = v_{2} U_{{S_{2} }} \eta \gamma_{1} v_{1} {/}(\rho + \beta )^{2} \\ a_{922} & = v_{2} U_{{S_{2} }} \eta \gamma_{2} v_{2} {/}(\rho + \beta )^{2} \\ b_{92} & = v_{2} U_{{S_{2} }} \eta {/(}\rho + \beta {)} \\ c_{92} & = \frac{{v_{2} U_{{S_{2} }} D_{0} }}{\rho } + \frac{{\alpha_{2}^{2} }}{{2\rho \mu_{{S_{2} }} (1 - \omega_{2} )}}\left[ {\frac{{v_{2} U_{{S_{2} }} \eta \gamma_{2} v_{2} }}{{(\rho + \beta )^{2} }}} \right]^{2} + \frac{{\alpha_{1}^{2} v_{1} U_{{S_{1} }} v_{2} U_{{S_{2} }} }}{{\rho \mu_{{S_{1} }} (1 - \omega_{1} )}}\left[ {\frac{{\eta \gamma_{1} v_{1} }}{{(\rho + \beta )^{2} }}} \right]^{2} \\ & \quad + \frac{{v_{2} U_{{S_{2} }} U_{M} \delta^{2} }}{{\rho \mu_{M} (1 - \psi_{1} - \psi_{2} )}}\left[ {\frac{\eta }{\rho + \beta }} \right]^{2} + \frac{{\psi_{2} \delta^{2} }}{{2\rho \mu_{M} }}\left[ {\frac{{U_{M} \eta }}{{(1 - \psi_{1} - \psi_{2} )(\rho + \beta )}}} \right]^{2} \\ \end{aligned} \right.. $$
(166)

Comparing its coefficients of the similar terms on both sides in Eq. (164) produces

$$ \left\{ \begin{aligned} a_{101} & = U_{M} \eta \gamma_{1} v_{1} {/}(\rho + \beta )^{2} \\ a_{102} & = U_{M} \eta \gamma_{2} v_{2} {/}(\rho + \beta )^{2} \\ b_{10} & = U_{M} \eta {/(}\rho + \beta {)} \\ c_{10} & = \frac{{U_{M} D_{0} }}{\rho } - \frac{{\omega_{1} \alpha_{1}^{2} }}{{2\rho \mu_{{S_{1} }} (1 - \omega_{1} )}}\left[ {\frac{{v_{1} U_{{S_{1} }} \eta \gamma_{1} v_{1} }}{{(\rho + \beta )^{2} }}} \right]^{2} - \frac{{\omega_{2} \alpha_{2}^{2} }}{{2\rho \mu_{{S_{2} }} (1 - \omega_{2} )^{2} }}\left[ {\frac{{v_{2} U_{{S_{2} }} \eta \gamma_{2} v_{2} }}{{(\rho + \beta )^{2} }}} \right]^{2} \\ & \quad + \frac{{\delta^{2} }}{{2\rho \mu_{M} (1 - \psi_{1} - \psi_{2} )}}\left[ {\frac{{U_{{M_{1} }} \eta }}{\rho + \beta }} \right]^{2} + \frac{{v_{1} U_{{S_{1} }} U_{M} \alpha_{1}^{2} }}{{\rho \mu_{{S_{1} }} (1 - \omega_{1} )}}\left[ {\frac{{\eta \gamma_{1} v_{1} }}{{(\rho + \beta )^{2} }}} \right]^{2} + \frac{{v_{2} U_{{S_{2} }} U_{M} \alpha_{2}^{2} }}{{\rho \mu_{{S_{2} }} (1 - \omega_{2} )^{2} }}\left[ {\frac{{\eta \gamma_{2} v_{2} }}{{(\rho + \beta )^{2} }}} \right]^{2} \\ \end{aligned} \right.. $$
(167)

Coordinating the supply chain system can make the optimal emission reduction efforts of suppliers and manufacturer under bilateral contract equal to those under centralized case, so \(Z_{{S_{1} }}^{C*} = Z_{{S_{1} }}^{B*}\),\(Z_{{S_{2} }}^{C*} = Z_{{S_{2} }}^{B*}\),\(Z_{M}^{C*} = Z_{M}^{B*}\). Namely, \(\frac{{(U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} )\alpha_{1} \eta \gamma_{1} v_{1} }}{{\mu_{{S_{1} }} (\rho + \beta )^{2} }} =\)\(\frac{{v_{1} U_{{S_{1} }} \alpha_{1} \eta \gamma_{1} v_{1} }}{{(1 - \omega_{1} )\mu_{{S_{2} }} (\rho + \beta )^{2} }}\), \(\frac{{(U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} )\alpha_{2} \eta \gamma_{2} v_{2} }}{{\mu_{{S_{2} }} (\rho + \beta )^{2} }} = \frac{{v_{2} U_{{S_{2} }} \alpha_{2} \eta \gamma_{2} v_{2} }}{{(1 - \omega_{2} )\mu_{{S_{2} }} (\rho + \beta )^{2} }}{,}\)\(\frac{{(U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} )\delta \eta }}{{\mu_{{M_{1} }} (\rho + \beta )}}\)\(= \frac{{U_{M} \delta \eta }}{{(1 - \psi_{1} - \psi_{2} )\mu_{M} (\rho + \beta )}}{.}\) By comparison, we have \(U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} = v_{1} U_{{S_{1} }} {/(}1 - \omega_{1} {)}\), \(U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} = v_{2} U_{{S_{2} }} {/(}1 - \omega_{2} {),}\) \(U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} = U_{M} {/(}1 - \psi_{1} - \psi_{2} {)}\). So we get \(\omega_{1}^{*} = \frac{{U_{M} + v_{2} U_{{S_{2} }} }}{{U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} }}\), \(\omega_{2}^{*} = \frac{{U_{M} + v_{1} U_{{S_{1} }} }}{{U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} }}\), \(\psi_{1}^{*} + \psi_{2}^{*} = \frac{{v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} }}{{U_{M} + v_{1} U_{{S_{1} }} + v_{2} U_{{S_{2} }} }}\). Thus, Proposition 10 can be proved.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

He, L., Yuan, B., Bian, J. et al. Differential game theoretic analysis of the dynamic emission abatement in low-carbon supply chains. Ann Oper Res 324, 355–393 (2023). https://doi.org/10.1007/s10479-021-04134-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-021-04134-9

Keywords

Navigation