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Coordinating a supply chain with green innovation in a dynamic setting

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Abstract

This paper addresses the channel coordination problem in a green supply chain consisting of a manufacturer and a retailer, in which the manufacturer controls green innovation and wholes price, while the retailer controls sales price. Pricing and green innovation strategies in integrated and decentralized channels are computed and compared, and a two-part tariff contract is designed to coordinate the decentralized supply chain. A Nash bargaining model is further developed to distribute the extra-profit between channel members. A numerical example is conducted to explore the impacts of green effectiveness and operational inefficiency effect on optimal/equilibrium solutions and coordination. The main results show that the green innovation investment, energy efficiency level and channel profit of integrated channel are larger than those of decentralized one, but the relationship of sales prices under two channel structures depends on system parameters. Green effectiveness exerts a positive effect on optimal/equilibrium solutions. The coordinator’s coordination capability is improved by green effectiveness, but weakened by operational inefficiency effect.

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References

  • Aguilera-Caracuel J, Ortiz-de-Mandojana N (2013) Green innovation and financial performance an institutional approach. Organ Environ 26(4):365–385

    Article  Google Scholar 

  • Banerjee A, Solomon B (2003) Eco-labeling for energy efficiency and sustainability: a meta-evaluation of US programs. Energy Policy 31(2):109–123

    Article  Google Scholar 

  • Barari S, Agarwal G, Zhang W et al (2012) A decision framework for the analysis of green supply chain contracts: an evolutionary game approach. Expert Systems with Applications 39(3):2965–2976

    Article  Google Scholar 

  • Bemporad R, Baranowski M (2007) Conscious consumers are changing the rules of marketing. Are You Ready? Highlights from the BBMG Conscious Consumer Report

  • Bhaskaran S, Krishnan V (2009) Effort, revenue, and cost sharing mechanisms for collaborative new product development. Manag Sci 55(7):1152–1169

    Article  Google Scholar 

  • BP (2011) BP Statistical review of world energy 2011

  • Cachon G (2003) Supply chain coordination with contracts. Handb Oper Res Manag Sci 11:227–339

    Article  Google Scholar 

  • Cachon G, Lariviere M (2005) Supply chain coordination with revenue-sharing contracts: strengths and limitations. Manag Sci 51(1):30–44

    Article  Google Scholar 

  • Chitra K (2007) In search of the green consumers: a perceptual study. J Serv Res 7(1):173–191

    Google Scholar 

  • Choi T, Li Y, Xu L (2013) Channel leadership, performance and coordination in closed loop supply chains. Int J Prod Econ 146(1):371–380

    Article  Google Scholar 

  • Cronin J Jr, Smith J, Gleim M et al (2011) Green marketing strategies: an examination of stakeholders and the opportunities they present. J Acad Mark Sci 39(1):158–174

    Article  Google Scholar 

  • Cuerva M, Triguero-Cano A, Corcoles D (2014) Drivers of green and non-green innovation: empirical evidence in Low-Tech SMEs. J Clean Prod 68:104–113

    Article  Google Scholar 

  • De Giovanni P (2011) Quality improvement vs. advertising support: which strategy works better for a manufacturer? Euro J Oper Res 208(2):119–130

    Article  Google Scholar 

  • De Giovanni P, Zaccour G (2014) A two-period game of a closed-loop supply chain. Euro J Oper Res 232(1):22–40

    Article  Google Scholar 

  • Dixon R, McGowan E, Onysko G et al (2010) US energy conservation and efficiency policies: challenges and opportunities. Energy Policy 38(11):6398–6408

    Article  Google Scholar 

  • Drake D, Kleindorfer P, Van Wassenhove L (2012) Technology choice and capacity portfolios under emissions regulation (working paper)

  • EI Saadany A, Jaber M (2010) A production/remanufacturing inventory model with price and quality dependant return rate. Comput Ind Eng 58(3):352–362

    Article  Google Scholar 

  • Frondel M, Horbach J, Renning K (2008) What triggers environmental management and innovation? Empir Evid Ger Ecol Econ 66(1):153–160

    Google Scholar 

  • Gaspar R, Antunes D (2011) Energy efficiency and appliance purchases in Europe: consumer profiles and choice determinants. Energy Policy 39(11):7335–7346

    Article  Google Scholar 

  • Ghosh D, Shah J (2012) A comparative analysis of greening policies across supply chain structures. Int J Prod Econ 135(2):568–583

    Article  Google Scholar 

  • Ghosh D, Shah J (2015) Supply chain analysis under green sensitive consumer demand and cost sharing contract. Int J Prod Econ 164:319–329

    Article  Google Scholar 

  • He X, Krishnamoorthy A, Prasad A et al (2012) Co-op advertising in dynamic retail oligopolies. Decis Sci 43(1):73–106

    Article  Google Scholar 

  • Jeuland A, Shugan S (1983) Managing channel profits. Mark Sci 2(3):239–272

    Article  Google Scholar 

  • Karakayali I, Emir-Farinas H, Akcali E (2007) An analysis of decentralized collection and processing of end-of-life products. J Oper Manag 25(6):1161–1183

    Article  Google Scholar 

  • Karray S (2015) Cooperative promotions in the distribution channel. Omega 51:49–58

    Article  Google Scholar 

  • Khanna N, Zhou N, Fridley D et al (2013) Evaluation of China’s local enforcement of energy efficiency standards and labeling programs for appliances and equipment. Energy Policy 63:646–655

    Article  Google Scholar 

  • Krass D, Nedorezov T, Ovchinnikov A (2013) Environmental taxes and the choice of green technology. Prod Oper Manag 22(5):1035–1055

    Google Scholar 

  • Lambertini L (2014) Coordinating static and dynamic supply chains with advertising through two-part tariffs. Automatica 50(2):565–569

    Article  Google Scholar 

  • Li B, Zhu M, Jiang Y et al (2016) Pricing policies of a competitive dual-channel green supply chain. J Clean Prod 112:2029–2042

  • Lin H, Zeng S, Ma H et al (2014) Can political capital drive corporate green innovation? Lessons from China. J Clean Prod 64:63–72

    Article  Google Scholar 

  • Lin R, Tan K, Geng Y (2013) Market demand, green product innovation, and firm performance: evidence from Vietnam motorcycle industry. J Clean Prod 40:101–107

    Article  Google Scholar 

  • Liu Z, Anderson T, Cruz J (2012) Consumer environmental awareness and competition in two-stage supply chains. Euro J Oper Res 218(3):602–613

    Article  Google Scholar 

  • López M, Garcia A, Rodriguez L (2007) Sustainable development and corporate performance: a study based on the Dow Jones sustainability index. J Bus Eth 75(3):285–300

    Article  Google Scholar 

  • Martín-Herrán G, Taboubi S (2015) Price coordination in distribution channels: a dynamic perspective. Euro J Oper Res 240(2):401–414

    Article  Google Scholar 

  • Moorthy S (1987) Managing channel profits: comments. Mark Sci 6(4):375–379

    Article  Google Scholar 

  • Muthulingam S, Corbett C, Benartzi S et al (2013) Energy efficiency in small and medium-sized manufacturing firms: order effects and the adoption of process improvement recommendations. Manuf Serv Opera Manag 15(4):596–615

    Google Scholar 

  • Nash J Jr (1950) The bargaining problem. Econom J Econom Soc 18(2):155–162

    Google Scholar 

  • Patterson M (1996) What is energy efficiency? Concepts, indicators and methodological issues. Energy policy 24(5):377–390

    Article  Google Scholar 

  • Rennings K (2000) Redefining innovation-eco-innovation research and the contribution from ecological economics. Ecolo Econ 32(2):319–332

    Article  Google Scholar 

  • Sarkis J (2003) A strategic decision framework for green supply chain management. J Clean Prod 11(4):397–409

    Article  Google Scholar 

  • Sayadi M, Makui A (2014) Feedback nash equilibrium for dynamic brand and channel advertising in dual channel supply chain. J Optim Theory Appl 161(3):1012–1021

    Article  Google Scholar 

  • Schiederig T, Tietze F, Herstatt C (2012) Green innovation in technology and innovation management-an exploratory literature review. R&D Manag 42(2):180–192

    Article  Google Scholar 

  • Shi X (2014) Setting effective mandatory energy efficiency standards and labelling regulations: a review of best practices in the Asia Pacific region. Appl Energy 133:135–143

    Article  Google Scholar 

  • Swami S, Shah J (2012) Channel coordination in green supply chain management. J Oper Res Soc 64(3):336–351

    Article  Google Scholar 

  • Testa F, Iraldo F (2010) Shadows and lights of GSCM (green supply chain management): determinants and effects of these practices based on a multinational study. J Clean Prod 18(10):953–962

    Article  Google Scholar 

  • Vachon S, Klassen R (2006) Extending green practices across the supply chain: the impact of upstream and downstream integration. Int J Oper Prod Manag 26(7):795–821

    Article  Google Scholar 

  • Vörös J (2006) The dynamics of price, quality and productivity improvement decisions. Euro J Oper Res 170(3):809–823

    Article  Google Scholar 

  • Xie J, Neyret A (2009) Co-op advertising and pricing models in manufacturer-retailer supply chains. Computers & Industrial Engineering 56(4):1375–1385

    Article  Google Scholar 

  • Xie J, Wei J (2009) Coordinating advertising and pricing in a manufacturer-retailer channel. Euro J Oper Res 197(2):785–791

    Article  Google Scholar 

  • Xie G, Yue W, Liu W et al (2012) Risk based selection of cleaner products in a green supply chain. Pac J Optim 8(3):473–484

    Google Scholar 

  • Xie G (2015) Modeling decision processes of a green supply chain with regulation on energy saving level. Comput Oper Res 54:266–273

    Article  Google Scholar 

  • Yao X, Liu Y, Yan X (2014) A quantile approach to assess the effectiveness of the subsidy policy for energy-efficient home appliances: evidence from Rizhao, China. Energy Policy 73:512–518

    Article  Google Scholar 

  • Young W, Hwang K, McDonalds S et al (2010) Sustainable consumption: green consumer behavior when purchasing products. Sustain Dev 18(1):20–31

    Google Scholar 

  • Zaccour G (2008) On the coordination of dynamic marketing channels and two-part tariffs. Automatica 44(5):1233–1239

    Article  Google Scholar 

  • Zhang C, Liu L (2013) Research on coordination mechanism in three-level green supply chain under non-cooperative game. Appl Math Model 37(5):3369–3379

    Article  Google Scholar 

  • Zhang L, Wang J, You J (2015) Consumer environmental awareness and channel coordination with two substitutable products. Euro J Oper Res 241(1):63–73

    Article  Google Scholar 

  • Zhou N, Fridley D, McNeil M et al (2011) Analysis of potential energy saving and \(\text{ CO }_2\) emission reduction of home appliances and commercial equipments in China. Energy Policy 39(8):4541–4550

    Article  Google Scholar 

  • Zhu Q, Sarkis J, Lai K (2007) Initiatives and outcomes of green supply chain management implementation by Chinese manufacturers. J Environ Manag 85(1):179–189

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by National Natural Foundation of China Nos. 61473204, 71371133, and Humanity and Social Science Youth Foundation of Ministry of Education of China No. 14YJCZH204.

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Correspondence to Jianxiong Zhang.

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Appendix

Appendix

For simplification, the time argument is omitted in the Appendices.

1.1 Proof of Proposition 1

Let \(V^I\) denote the value function of the integrated channel. Taking the energy efficiency level evolution into account, the Hamilton-Jacobi-Bellman (HJB) equation for the whole supply chain is

$$\begin{aligned} \rho V^I(G)=\max \limits _{p, u}\{(p-c_0-c_1x)(\alpha -\beta p+\gamma x)-\frac{h}{2}u^2+\frac{\partial V^I}{\partial x}(\theta u-\delta x)\}. \end{aligned}$$

Maximization of the right-hand side of the HJB equation with respect to p and u yields

$$\begin{aligned} p= & {} \frac{\alpha +\beta c_0+(\gamma +\beta c_1) x}{2\beta },\end{aligned}$$
(30)
$$\begin{aligned} u= & {} \frac{\theta }{h}\frac{\partial V^I}{\partial x}. \end{aligned}$$
(31)

Inserting (30) and (31) on the right-hand side of the HJB equation provides

$$\begin{aligned} \rho V^I=\frac{(\alpha -\beta c_0+(\gamma -\beta c_1) x)^2}{4\beta }+\frac{\theta ^2}{2h}\left( \frac{\partial V^I}{\partial x}\right) ^2-\frac{\partial V^I}{\partial x}\delta x. \end{aligned}$$
(32)

Guided by the model’s linear-quadratic structure, we conjecture that the integrated channel value function is quadratic and given by

$$\begin{aligned} V^{I}(x)=\frac{I_{1}}{2}x^{2}+I_{2}x+I_{3}, \end{aligned}$$
(33)

and follows from (33) that

$$\begin{aligned} \frac{\partial V^I}{\partial x}=I_1x+I_2. \end{aligned}$$
(34)

Substituting (33) and (34) into (32) yields

$$\begin{aligned} \frac{\rho }{2}I_1x^2+\rho I_2x+\rho I_3= & {} \left( \frac{(\gamma -\beta c_1)^2}{4\beta }+\frac{\theta ^2}{2h}I_1^2-\rho I_1\right) x^2+\left( \frac{(\alpha -\beta c_0)(\gamma -\beta c_1)}{2\beta }\right. \nonumber \\&\quad \left. +\frac{\theta ^2}{h}I_1I_2-\delta I_2\right) x+\frac{(\alpha -\beta c_0)^2}{4\beta }+\frac{\theta ^2}{2h}I_2^2. \end{aligned}$$
(35)

Equating the coefficients of \(x^2, x\) on both sides of (35), we get the expressions of \(I_1, I_2\) shown in Proposition 1. Similarly, \(I_3\) is obtained as

$$\begin{aligned} I_{3}=\frac{(\alpha -\beta c_0)^2\left( (\rho \beta h+\eta _1)^2+2\beta h\theta ^2(\gamma -\beta c_1)^2\right) }{4\beta \rho (\rho \beta h+\eta _1)^2}. \end{aligned}$$
(36)

Accordingly, the channel profit is given by

$$\begin{aligned} J^{I}=\frac{I_{1}}{2}x_0^{2}+I_{2}x_0+I_{3}. \end{aligned}$$
(37)

Inserting (35) into (1) produces a differential equation for the optimal energy efficiency level. Integrating the differential equation one obtains the trajectory in (10), where the steady-state energy efficiency level \(x^{I}_{\infty }\) is globally stable if and only if \(R_1>0\), i.e.,

$$\begin{aligned} 2\beta \delta h(\delta +\rho )-\theta ^2(\gamma -\beta c_1)^2>0. \end{aligned}$$
(38)

1.2 Proof of Corollary 2

Note from Proposition 2 that the monotonicity of sales price depends on the relationship of \(x_0\) and \(x^I_\infty \), of which \(R_1>0\). Specifically, when \(x_0>x^I_\infty \), the sales price is monotonically decreasing with time, namely, skimming pricing; when \(x_0<x^I_\infty \), the sales price monotonically increases with time, namely, penetration pricing.

Since \(0<c_1<\frac{\gamma }{\beta }\) which is assumed to reflect operational inefficiency effect and to ensure a positive \(x^I_\infty \), we have \(0<x^I_\infty <\frac{\gamma \theta ^2(\alpha -\beta c_0)}{2\beta h\delta (\delta +\rho )-\theta ^2\gamma ^2}\).

As such, if \(x_0>\frac{\gamma \theta ^2(\alpha -\beta c_0)}{2\beta h\delta (\delta +\rho )-\theta ^2\gamma ^2}\), meaning that \(x_0>x^I_\infty \), a skimming pricing strategy is adopted.

However, if \(x_0<\frac{\gamma \theta ^2(\alpha -\beta c_0)}{2\beta h\delta (\delta +\rho )-\theta ^2\gamma ^2}\), there exists \(\widetilde{c}_1\) which satisfies that \(x_0=\frac{\theta ^2(\gamma -\beta \widetilde{c}_1)(\alpha -\beta c_0)}{2\beta h\delta (\delta +\rho )-\theta ^2(\gamma -\beta \widetilde{c}_1)^2}\). When \(0<c_1<\widetilde{c}_1\), one has \(x_0>x^I_\infty \), which implies a skimming pricing strategy; when \(\widetilde{c}_1<c_1<\frac{\gamma }{\beta }\), it is found that \(x_0<x^I_\infty \), implying a penetration pricing.

1.3 Proof of Proposition 3

To obtain a Stackelberg equilibrium, we first determine the retailer’s pricing strategy p as a function of the manufacturer’s decisions w and u. Let \(V_R^D, V_M^D\) denote the value functions for the retailer and the manufacturer. The retailer’s HJB equation can be specified as

$$\begin{aligned} \rho V_R^D=\max \limits _{p}\{(p-w)(\alpha -\beta p+\gamma x)+\frac{\partial V_R^D}{\partial x}(\theta u-\delta x)\}. \end{aligned}$$
(39)

The maximization with respect to p yields the retailer’s reaction function:

$$\begin{aligned} p=\frac{\alpha +\beta w+\gamma x}{2b}. \end{aligned}$$
(40)

Anticipating the retailer’s response in (40), the manufacturer’s HJB equation is given by

$$\begin{aligned} \rho V_M^D=\max \limits _{w, u}\{(w-c_0-c_1x)(\alpha -\beta p+\gamma x)-\frac{h}{2}u^2+\frac{\partial V_M^D}{\partial x}(\theta u-\delta x)\}. \end{aligned}$$
(41)

Performing the maximization on the right-hand side with respect to w and u yields

$$\begin{aligned} w=\frac{\alpha +\beta c_0+(\gamma +\beta c_1) x}{2\beta }, u=\frac{\theta }{h}\frac{\partial V_M^D}{\partial x}. \end{aligned}$$
(42)

Substituting the expression of w above into (40) produces

$$\begin{aligned} p=\frac{3\alpha +\beta c_0+(3\gamma +\beta c_1) x}{4\beta }. \end{aligned}$$
(43)

Substitute (42) and (43) into HJB equations (39) and (41), and assume the following quadratic value functions:

$$\begin{aligned} V^{D}_{M}= & {} \frac{A_{1}}{2}x^{2}+A_{2}x+A_{3},\nonumber \\ V^{D}_{R}= & {} \frac{B_{1}}{2}x^{2}+B_{2}x+B_{3}. \end{aligned}$$
(44)

Following the same procedure as that in the proof of Proposition 1, the six Riccati equations that characterize the coefficients of the value functions \(A_i, B_i, i=1, 2, 3\) are determined by identification. The coefficients \(A_1, A_2\) are given in Proposition 3, and other coefficients are presented as follows.

$$\begin{aligned} A_{3}= & {} \frac{(\alpha -\beta c_0)^2\left( (\rho \beta h+\eta _2)^2+\beta h\theta ^2(\gamma -\beta c_1)^2\right) }{8\beta \rho (\rho \beta h+\eta _2)^2},\nonumber \\ B_{1}= & {} \frac{h(\gamma -\beta c_1)^2}{8\eta _2},\nonumber \\ B_{2}= & {} \frac{h(\alpha -\beta c_0)(\gamma -\beta c_1)(\theta ^ 2\beta h(\gamma -\beta c_1)^2 +2\eta _2(\rho \beta h+\eta _2))}{8\eta _2(\rho \beta h+\eta _2)^2},\nonumber \\ B_{3}= & {} \frac{(\alpha -\beta c_0)^2(\eta _2(\rho \beta h+\eta _2)((\rho \beta h+\eta )^2+2\beta h\theta ^2(\gamma -\beta c_1)^2)+h^2\theta ^4\beta ^2(\gamma -\beta c_1)^4)}{16\rho \beta \eta _2(\rho \beta h+\eta _2)^3}.\nonumber \\ \end{aligned}$$
(45)

Then, the equilibrium profits of the manufacturer, the retailer and the whole channel are

$$\begin{aligned}&J^{D}_{M}=\frac{A_{1}}{2}x_0^{2}+A_{2}x_0+A_{3},\nonumber \\&J^{D}_{R}=\frac{B_{1}}{2}x_0^{2}+B_{2}x_0+B_{3},\nonumber \\&J^{D}=\frac{1}{2}(A_1+B_1)x_0^{2}+(A_{2}+B_{2})x_0+A_{3}+B_{3}. \end{aligned}$$
(46)

Similarly, the optimal time path of the energy efficiency level can be written as in (17), where the steady state \(x^{D}_{\infty }\) is globally stable if and only if \(R_2>0\), i.e.,

$$\begin{aligned} 4\beta \delta h(\delta +\rho )-\theta ^2(\gamma -\beta c_1)^2>0. \end{aligned}$$
(47)

1.4 Proof of Proposition 5

Let \(V_R^C, V^C\) denote the value functions for the retailer and the manufacturer, respectively. The retailer’s HJB equation can be specified as

$$\begin{aligned} \rho V_R^C=\max \limits _{p}\{(p-c_0-c_1x)(\alpha -\beta p+\gamma x)-k+\frac{\partial V_R^C}{\partial x}(\theta u-\delta x)\}. \end{aligned}$$
(48)

The equilibrium sales price is given below by maximizing the right-hand side of (48) with respect to p, i.e.,

$$\begin{aligned} p^C=\frac{\alpha +\beta c_0+(\gamma +\beta c_1)x}{2\beta }. \end{aligned}$$
(49)

The manufacturer’s optimization problem is given by

$$\begin{aligned} \max \limits _{u}\int _0^\infty e^{-\rho t}\left( (p-c_0-c_1x)(\alpha -\beta p+\gamma x)-\frac{h}{2}u^{2}\right) \mathrm{d}t, \end{aligned}$$
(50)

subject to the dynamic evolution of energy efficiency level (1).

The corresponding HJB equation is

$$\begin{aligned} \rho V^C=\max \limits _{u}\{(p-c_0-c_1x)(\alpha -\beta p+\gamma x)-\frac{h}{2}u^2+\frac{\partial V^C}{\partial x}(\theta u-\delta x)\}. \end{aligned}$$
(51)

Substituting (49) into (51), then maximizing the right-hand side with respect to u yields

$$\begin{aligned} u^C=\frac{\theta }{h}\frac{\partial V^C_M}{\partial x}. \end{aligned}$$
(52)

Conjecture the following value functions:

$$\begin{aligned} V^C_R(x)= & {} \frac{N_1}{2}x^{2}+N_{2}x+N_{3},\end{aligned}$$
(53)
$$\begin{aligned} V^C(x)= & {} \frac{C_{1}}{2}x^{2}+C_{2}x+C_{3}. \end{aligned}$$
(54)

By means of the procedure of the proof for Proposition 1, we have

$$\begin{aligned} C_1= & {} I_1, C_2=I_2, C_3=I_3,\nonumber \\ N_1= & {} \frac{h(\gamma -\beta c_1)^2}{2\eta _1}, \end{aligned}$$
(55)
$$\begin{aligned} N_2= & {} \frac{h(\alpha -\beta c_0)(\gamma -\beta c_1)(\theta ^2\beta h(\gamma -\beta c_1)^2 +\eta _1(\rho \beta h+\eta _1))}{\eta _1(\rho \beta h+\eta _1)^2}, \end{aligned}$$
(56)
$$\begin{aligned} N_3(k)= & {} \frac{\theta ^2(\alpha -\beta c_0)(\gamma -\beta c_1)}{\rho (\rho \beta h+\eta _1)}N_2+\frac{(\alpha -\beta c_0)^{2}}{4\beta \rho }-\frac{k}{\rho }. \end{aligned}$$
(57)

Consequently, \(u^C=u^I, x^C=x^I, p^C=p^I\). These equilibrium strategies are identical with the integrated solutions.

Similarly, the profits of the manufacturer and retailer, \(J^C_M\), \(J^C_R\), are given by the value functions in (24) and (25), where

$$\begin{aligned} M_1= & {} -\frac{(\beta h(2\delta +\rho )-\eta _1)^2}{4\theta ^2\beta \eta _1}, \end{aligned}$$
(58)
$$\begin{aligned} M_2= & {} \frac{h(\eta _1^2-\beta ^2h^2(2\delta +\rho )^2)(\alpha -\beta c_0)(\gamma -\beta c_1)}{2\eta _1(\rho \beta h+\eta _1)^2}, \end{aligned}$$
(59)
$$\begin{aligned} M_3(k)= & {} \frac{k}{\rho }+\frac{\theta ^2(\alpha -\beta c_0)(\gamma -\beta c_1)}{\rho (\rho \beta h+\eta _1)}M_2-\frac{h\theta ^2(\alpha -\beta c_0)^2(\gamma -\beta c_1)^2}{2\rho (\rho \beta h+\eta _1)^2}. \end{aligned}$$
(60)

1.5 Proof of Proposition 6

According to (26), we have

$$\begin{aligned} \frac{M_1}{2}x_0^2+M_2x_0+M_3(k)-\frac{A_1}{2}x_0^2-A_2x_0-A_3>0, \end{aligned}$$

i.e.,

$$\begin{aligned} \frac{k}{\rho }&>-\left( \frac{M_1}{2}x_0^2+M_2x_0+\frac{\theta ^2(\alpha -\beta c_0)(\gamma -\beta c_1)}{\rho (\rho \beta h+\eta _1)}M_2-\frac{h\theta ^2(\alpha -\beta c_0)^2(\gamma -\beta c_1)^2}{2\rho (\rho \beta h+\eta _1)^2}\right) \nonumber \\&\quad +\frac{A_1}{2}x_0^2+A_2x_0+A_3=J_M^{D}-J_{M}^C(0).\nonumber \end{aligned}$$

Thus, k satisfies \(k>\rho (J_M^{D}-J_{M}^C(0))\).

Similarly, according to (27), we have \(k<\rho (J_R^C(0)-J_R^{D})\).

Let \(k_1=\rho (J_M^{D}-J_{M}^C(0)), k_2=\rho (J_R^C(0)-J_R^{D})\). It’s easy to verify that \(J_{M}^C(0)<0, J_M^{D}>0\), so \(k_1>0\). Also,

$$\begin{aligned} k_2-k_1&=J_{M}^C(0)+J_R^C(0)-J_M^{D}-J_R^D\nonumber \\&=J^{I}-J^{D}\nonumber \\&>0.\nonumber \end{aligned}$$

Consequently, k should satisfy \(\rho (J_M^{D}-J_{M}^C(0))<k<\rho (J_R^C(0)-J_R^{D})\).

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Zhang, Q., Zhang, J. & Tang, W. Coordinating a supply chain with green innovation in a dynamic setting. 4OR-Q J Oper Res 15, 133–162 (2017). https://doi.org/10.1007/s10288-016-0327-x

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