• Previous Article
    Pricing new and remanufactured products based on customer purchasing behavior
  • JIMO Home
  • This Issue
  • Next Article
    Equilibrium periodic dividend strategies with non-exponential discounting for spectrally positive Lévy processes
doi: 10.3934/jimo.2020116

Channel leadership and recycling channel in closed-loop supply chain: The case of recycling price by the recycling party

1. 

College of Information Science and Engineering, Northeastern University, Fundamental Teaching Department of Computer and Mathematics, Shenyang Normal University, Shenyang, Liaoning, 110034, China

2. 

Research Institute of Business Analytics and Supply Chain Management, College of Management, Shenzhen University, Shenzhen, 518060, China

3. 

College of Information Science and Engineering, State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, Liaoning, 110819, China

4. 

Department of Mathematics, The University of Hong Kong, Pokfulam, Hong Kong, China

5. 

College of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, 110819, China

* Corresponding author: Min Huang

Received  June 2019 Revised  March 2020 Published  June 2020

Due to the fast growing of the waste electrical and electronic equipment (WEEE), the business values of closed-loop supply chains (CLSCs) have been well recognized. In this paper, we investigate the performance of the CLSCs under different combinations of the recycling channel and the channel leadership when the recycling price is determined by the recycling party. Specially, we consider a CLSC consisting of two channel members, i.e., a manufacturer and a retailer. Each member acting as the channel leader has three different channels to collect the used products, and they are (ⅰ) the manufacturer (M-channel), (ⅱ) the retailer (R-channel) and (ⅲ) the third-party (T-channel). Given the recycling party determines the recycling price, mathematical models are developed to investigate the performance of the CLSC under different combinations of the channel leadership and the recycling channel. Through a comparison analysis, we find that M-channel is the most effective recycling channel. Moreover, once the M-channel be adopted, the retailer-led structure is as good as manufacture-led structure. We find that the recycling channel structure could be more important than the channel leadership in the CLSC. Finally, we illustrate that the CLSC can be coordinated by a two-part tariff contract.

Citation: Zhidan Wu, Xiaohu Qian, Min Huang, Wai-Ki Ching, Hanbin Kuang, Xingwei Wang. Channel leadership and recycling channel in closed-loop supply chain: The case of recycling price by the recycling party. Journal of Industrial & Management Optimization, doi: 10.3934/jimo.2020116
References:
[1]

E. Almehdawe and B. Matin, Vendor managed inventory with a capacitated manufacturer and multiple retailer: Retailer versus manufacturer leadership, Internat. J. Prod. Econ., 128 (2010), 292-302.  doi: 10.1016/j.ijpe.2010.07.029.  Google Scholar

[2]

A. AtasuV. D. R. Guide and L. N. Van Wassenhove, Product reuse economics in closed-loop supply chain research, Prod. Oper. Manag., 17 (2010), 483-496.  doi: 10.3401/poms.1080.0051.  Google Scholar

[3]

A. AtasuL. B. Toktay and L. N. Van Wassenhove, How collection cost structure drives a manufacturer's reverse channel choice, Prod. Oper. Manag., 22 (2013), 1089-1102.  doi: 10.1111/j.1937-5956.2012.01426.x.  Google Scholar

[4]

M. Bhattacharyya and S. S. Sana, A mathematical model on eco-friendly manufacturing system under probabilistic demand, RAIRO Oper. Res., 53 (2019), 1899-1913.  doi: 10.1051/ro/2018120.  Google Scholar

[5]

G. P. Cachon and A. G. Kök, Competing manufacturers in a retail supply chain: On contractual form and coordination, Manag. Sci., 56 (2010), 571-589.  doi: 10.1287/mnsc.1090.1122.  Google Scholar

[6]

J.-M. Chen and C.-I. Chang, The co-operative strategy of a closed-loop supply chain with remanufacturing, Transpor. Res. Part E, 48 (2012), 387-400.  doi: 10.1016/j.tre.2011.10.001.  Google Scholar

[7]

T.-M. ChoiY. Li and L. Xu, Channel leadership, performance and coordination in closed loop supply chains, Internat. J. Prod. Econ., 146 (2013), 371-380.  doi: 10.1016/j.ijpe.2013.08.002.  Google Scholar

[8]

C.-H. ChuangC. X. Wang and Y. Zhao, Closed-loop supply chain models for a high-tech product under alternative reverse channel and collection cost structures, Internat. J. Prod. Econ., 156 (2014), 108-123.  doi: 10.1016/j.ijpe.2014.05.008.  Google Scholar

[9]

P. De Giovanni and G. Zaccour, A two-period game of a closed-loop supply chain, European J. Oper. Res., 232 (2014), 22-40.  doi: 10.1016/j.ejor.2013.06.032.  Google Scholar

[10]

V. D. R. Guide and L. N. Van Wassenhove, The evolution of closed-loop supply chain research, Oper. Res., 57 (2009), 10-18.   Google Scholar

[11]

G. Ertek and P. M. Griffin, Supplier-and buyer-driven channels in a two-stage supply chain, IIE Transactions, 34 (2002), 691-700.  doi: 10.1023/A:1014920510164.  Google Scholar

[12]

L. FengK. Govindan and C. Li, Strategic planning: Design and coordination for dual-recycling channel reverse supply chain considering consumer behavior, European J. Oper. Res., 260 (2017), 601-612.  doi: 10.1016/j.ejor.2016.12.050.  Google Scholar

[13]

H. Garg, Fuzzy inventory models for deteriorating items under different types of lead-time distributions, in Intelligent Techniques in Engineering Management, Intelligent Systems Reference Library, 87, Springer, Cham, 2015,247–274. doi: 10.1007/978-3-319-17906-3_11.  Google Scholar

[14]

V. D. R. GuideR. H. Teunter and L. N. Van Wassenhove, Matching demand and supply to maximize profits from remanufacturing, Manufac. Service Oper. Manag., 5 (2003), 303-316.  doi: 10.1287/msom.5.4.303.24883.  Google Scholar

[15]

X. HongZ. Wang and H. Zhang, Decision models of closed-loop supply chain with remanufacturing under hybrid dual-channel collection, Internat. J. Advanced Manufac. Tech., 68 (2013), 1851-1865.  doi: 10.1007/s00170-013-4982-1.  Google Scholar

[16]

M. HuangM. SongL. H. Lee and W. K. Ching, Analysis for strategy of closed-loop supply chain with dual recycling channel, Internat. J. Prod. Econ., 144 (2013), 510-520.  doi: 10.1016/j.ijpe.2013.04.002.  Google Scholar

[17]

A. P. Jeuland and S. M. Shugan, Managing channel profits, Marketing Science, 2 (1983), 239-272.  doi: 10.1287/mksc.2.3.239.  Google Scholar

[18]

I. KarakayaliH. Emir-Farinas and E. Akcal, An analysis of decentralized collection and processing of end-of-life products, J. Oper. Manag., 25 (2007), 1161-1183.  doi: 10.1016/j.jom.2007.01.017.  Google Scholar

[19]

Y. LiangS. Pokharel and G. H. Lim, Pricing used products for remanufacturing, European J. Oper. Res., 193 (2009), 390-395.  doi: 10.1016/j.ejor.2007.11.029.  Google Scholar

[20]

H. LiuM. LeiH. DengG. K. Leong and T. Huang, A dual channel, quality-based price competition model for the WEEE recycling market with government subsidy, Omega, 59 (2016), 290-302.  doi: 10.1016/j.omega.2015.07.002.  Google Scholar

[21]

P. Majumder and A. Srinivasan, Leadership and competition in network supply chains, Manag. Science, 54 (2008), 1189-1204.  doi: 10.1287/mnsc.1070.0752.  Google Scholar

[22]

T. W. McGuire and R. Staelin, An industry equilibrium analysis of downstream vertical integration, Marketing Science, 2 (1983), 161-190.  doi: 10.1287/mksc.2.2.161.  Google Scholar

[23]

P. R. Messinger and C. Narasimhan, Has power shifted in the grocery channel?, Marketing Science, 14 (1995), 189-223.   Google Scholar

[24]

S. Mitra, Revenue management for remanufactured products, Omega, 35 (2007), 553-562.  doi: 10.1016/j.omega.2005.10.003.  Google Scholar

[25]

S. K. MukhopadhyayD.-Q. Yao and X. Yue, Information sharing of value-adding retailer in a mixed channel hi-tech supply chain, J. Business Res., 61 (2008), 950-958.  doi: 10.1016/j.jbusres.2006.10.027.  Google Scholar

[26]

I. E. NielsenS. MajumderS. S. Sana and S. Saha, Comparative analysis of government incentives and game structures on single and two-period green supply chain, J. Cleaner Prod., 235 (2019), 1371-1398.  doi: 10.1016/j.jclepro.2019.06.168.  Google Scholar

[27]

A. ÖrsdemirE. Kemahlioğlu-Ziya and A. K. Parlaktürk, Competitive quality choice and remanufacturing, Prod. and Oper. Manag., 23 (2014), 48-64.  doi: 10.1111/poms.12040.  Google Scholar

[28]

S. SahaN. M. ModakS. Panda and S. S. Sana, Managing a retailer's dual-channel supply chain under price- and delivery time-sensitive demand, J. Modelling Manag., 13 (2018), 351-374.  doi: 10.1108/JM2-10-2016-0089.  Google Scholar

[29]

S. SahaN. M. ModakS. Panda and S. S. Sana, Promotional coordination mechanisms with demand dependent on price and sales efforts, J. Industrial Prod. Engrg., 36 (2019), 13-31.  doi: 10.1080/21681015.2019.1565451.  Google Scholar

[30]

S. S. SanaJ. Ferro-CorreaA. Quintero and R. Amaya, A system dynamics model of financial flow in supply chains: A case study, RAIRO Oper. Res., 52 (2018), 187-204.  doi: 10.1051/ro/2017025.  Google Scholar

[31]

R. C. SavaskanS. Bhattacharya and L. N. Van Wassenhove, Closed-loop supply chain models with product remanufacturing, Manag. Science, 50 (2004), 239-252.  doi: 10.1287/mnsc.1030.0186.  Google Scholar

[32]

R. C. Savaskan and L. N. Van Wassenhove, Reverse channel design: The case of competing retailers, Manag. Science, 52 (2006), 1-14.  doi: 10.1287/mnsc.1050.0454.  Google Scholar

[33]

J. ShiG. Zhang and J. Sha, Optimal production and pricing policy for a closed loop system, Resources Conservation Recycling, 55 (2011), 639-647.  doi: 10.1016/j.resconrec.2010.05.016.  Google Scholar

[34]

S. TiwariC. K. Jaggi and S. S. Sana, Integrated supply chain of supplier and retailer for stochastic demand, Math. Model. Anal., 23 (2018), 582-595.  doi: 10.3846/mma.2018.035.  Google Scholar

[35]

A. A. TaleizadehM. S. Moshtagh and I. Moon, Pricing, product quality, and collection optimization in a decentralized closed-loop supply chain with different channel structures: Game theoretical approach, J. Cleaner Prod., 189 (2018), 406-431.  doi: 10.1016/j.jclepro.2018.02.209.  Google Scholar

[36]

R. H. Teunter, Determining optimal disassembly and recovery strategies, Omega, 34 (2006), 533-537.  doi: 10.1016/j.omega.2005.01.014.  Google Scholar

[37]

M. ThierryM. Salomon and N. L. V. Wassenhove, Strategies issues in product recovery management, California Manag. Review, 37 (1995), 114-135.  doi: 10.2307/41165792.  Google Scholar

[38]

A. A. Tsay and N. Agrawal, Channel dynamics under price and service competition, Manufacturing and Service Oper. Manag., 2 (2000), 93-110.  doi: 10.1287/msom.2.4.372.12342.  Google Scholar

[39]

J. Vorasayan and S. M. Ryan, Optimal price and quantity of refurbished products, Prod. Oper. Manag., 15 (2006), 369-383.  doi: 10.1111/j.1937-5956.2006.tb00251.x.  Google Scholar

[40]

Z. WangB. ZhangJ. Yin and X. Zhang, Willingness and behavior towards e-waste recycling for residents in Beijing city, China, J. Cleaner Prod., 19 (2011), 977-984.  doi: 10.1016/j.jclepro.2010.09.016.  Google Scholar

[41]

W. WangY. ZhangK. ZhangT. Bai and J. Shang, Reward-penalty mechanism for closed-loop supply chains under responsibility-sharing and different power structures, Internat. J. Prod. Econ., 170 (2015), 178-190.  doi: 10.1016/j.ijpe.2015.09.003.  Google Scholar

[42]

D.-Q. Yao and J. J. Liu, Competitive pricing of mixed retail and e-tail distribution channels, OMEGA, 33 (2005), 235-247.  doi: 10.1016/j.omega.2004.04.007.  Google Scholar

show all references

References:
[1]

E. Almehdawe and B. Matin, Vendor managed inventory with a capacitated manufacturer and multiple retailer: Retailer versus manufacturer leadership, Internat. J. Prod. Econ., 128 (2010), 292-302.  doi: 10.1016/j.ijpe.2010.07.029.  Google Scholar

[2]

A. AtasuV. D. R. Guide and L. N. Van Wassenhove, Product reuse economics in closed-loop supply chain research, Prod. Oper. Manag., 17 (2010), 483-496.  doi: 10.3401/poms.1080.0051.  Google Scholar

[3]

A. AtasuL. B. Toktay and L. N. Van Wassenhove, How collection cost structure drives a manufacturer's reverse channel choice, Prod. Oper. Manag., 22 (2013), 1089-1102.  doi: 10.1111/j.1937-5956.2012.01426.x.  Google Scholar

[4]

M. Bhattacharyya and S. S. Sana, A mathematical model on eco-friendly manufacturing system under probabilistic demand, RAIRO Oper. Res., 53 (2019), 1899-1913.  doi: 10.1051/ro/2018120.  Google Scholar

[5]

G. P. Cachon and A. G. Kök, Competing manufacturers in a retail supply chain: On contractual form and coordination, Manag. Sci., 56 (2010), 571-589.  doi: 10.1287/mnsc.1090.1122.  Google Scholar

[6]

J.-M. Chen and C.-I. Chang, The co-operative strategy of a closed-loop supply chain with remanufacturing, Transpor. Res. Part E, 48 (2012), 387-400.  doi: 10.1016/j.tre.2011.10.001.  Google Scholar

[7]

T.-M. ChoiY. Li and L. Xu, Channel leadership, performance and coordination in closed loop supply chains, Internat. J. Prod. Econ., 146 (2013), 371-380.  doi: 10.1016/j.ijpe.2013.08.002.  Google Scholar

[8]

C.-H. ChuangC. X. Wang and Y. Zhao, Closed-loop supply chain models for a high-tech product under alternative reverse channel and collection cost structures, Internat. J. Prod. Econ., 156 (2014), 108-123.  doi: 10.1016/j.ijpe.2014.05.008.  Google Scholar

[9]

P. De Giovanni and G. Zaccour, A two-period game of a closed-loop supply chain, European J. Oper. Res., 232 (2014), 22-40.  doi: 10.1016/j.ejor.2013.06.032.  Google Scholar

[10]

V. D. R. Guide and L. N. Van Wassenhove, The evolution of closed-loop supply chain research, Oper. Res., 57 (2009), 10-18.   Google Scholar

[11]

G. Ertek and P. M. Griffin, Supplier-and buyer-driven channels in a two-stage supply chain, IIE Transactions, 34 (2002), 691-700.  doi: 10.1023/A:1014920510164.  Google Scholar

[12]

L. FengK. Govindan and C. Li, Strategic planning: Design and coordination for dual-recycling channel reverse supply chain considering consumer behavior, European J. Oper. Res., 260 (2017), 601-612.  doi: 10.1016/j.ejor.2016.12.050.  Google Scholar

[13]

H. Garg, Fuzzy inventory models for deteriorating items under different types of lead-time distributions, in Intelligent Techniques in Engineering Management, Intelligent Systems Reference Library, 87, Springer, Cham, 2015,247–274. doi: 10.1007/978-3-319-17906-3_11.  Google Scholar

[14]

V. D. R. GuideR. H. Teunter and L. N. Van Wassenhove, Matching demand and supply to maximize profits from remanufacturing, Manufac. Service Oper. Manag., 5 (2003), 303-316.  doi: 10.1287/msom.5.4.303.24883.  Google Scholar

[15]

X. HongZ. Wang and H. Zhang, Decision models of closed-loop supply chain with remanufacturing under hybrid dual-channel collection, Internat. J. Advanced Manufac. Tech., 68 (2013), 1851-1865.  doi: 10.1007/s00170-013-4982-1.  Google Scholar

[16]

M. HuangM. SongL. H. Lee and W. K. Ching, Analysis for strategy of closed-loop supply chain with dual recycling channel, Internat. J. Prod. Econ., 144 (2013), 510-520.  doi: 10.1016/j.ijpe.2013.04.002.  Google Scholar

[17]

A. P. Jeuland and S. M. Shugan, Managing channel profits, Marketing Science, 2 (1983), 239-272.  doi: 10.1287/mksc.2.3.239.  Google Scholar

[18]

I. KarakayaliH. Emir-Farinas and E. Akcal, An analysis of decentralized collection and processing of end-of-life products, J. Oper. Manag., 25 (2007), 1161-1183.  doi: 10.1016/j.jom.2007.01.017.  Google Scholar

[19]

Y. LiangS. Pokharel and G. H. Lim, Pricing used products for remanufacturing, European J. Oper. Res., 193 (2009), 390-395.  doi: 10.1016/j.ejor.2007.11.029.  Google Scholar

[20]

H. LiuM. LeiH. DengG. K. Leong and T. Huang, A dual channel, quality-based price competition model for the WEEE recycling market with government subsidy, Omega, 59 (2016), 290-302.  doi: 10.1016/j.omega.2015.07.002.  Google Scholar

[21]

P. Majumder and A. Srinivasan, Leadership and competition in network supply chains, Manag. Science, 54 (2008), 1189-1204.  doi: 10.1287/mnsc.1070.0752.  Google Scholar

[22]

T. W. McGuire and R. Staelin, An industry equilibrium analysis of downstream vertical integration, Marketing Science, 2 (1983), 161-190.  doi: 10.1287/mksc.2.2.161.  Google Scholar

[23]

P. R. Messinger and C. Narasimhan, Has power shifted in the grocery channel?, Marketing Science, 14 (1995), 189-223.   Google Scholar

[24]

S. Mitra, Revenue management for remanufactured products, Omega, 35 (2007), 553-562.  doi: 10.1016/j.omega.2005.10.003.  Google Scholar

[25]

S. K. MukhopadhyayD.-Q. Yao and X. Yue, Information sharing of value-adding retailer in a mixed channel hi-tech supply chain, J. Business Res., 61 (2008), 950-958.  doi: 10.1016/j.jbusres.2006.10.027.  Google Scholar

[26]

I. E. NielsenS. MajumderS. S. Sana and S. Saha, Comparative analysis of government incentives and game structures on single and two-period green supply chain, J. Cleaner Prod., 235 (2019), 1371-1398.  doi: 10.1016/j.jclepro.2019.06.168.  Google Scholar

[27]

A. ÖrsdemirE. Kemahlioğlu-Ziya and A. K. Parlaktürk, Competitive quality choice and remanufacturing, Prod. and Oper. Manag., 23 (2014), 48-64.  doi: 10.1111/poms.12040.  Google Scholar

[28]

S. SahaN. M. ModakS. Panda and S. S. Sana, Managing a retailer's dual-channel supply chain under price- and delivery time-sensitive demand, J. Modelling Manag., 13 (2018), 351-374.  doi: 10.1108/JM2-10-2016-0089.  Google Scholar

[29]

S. SahaN. M. ModakS. Panda and S. S. Sana, Promotional coordination mechanisms with demand dependent on price and sales efforts, J. Industrial Prod. Engrg., 36 (2019), 13-31.  doi: 10.1080/21681015.2019.1565451.  Google Scholar

[30]

S. S. SanaJ. Ferro-CorreaA. Quintero and R. Amaya, A system dynamics model of financial flow in supply chains: A case study, RAIRO Oper. Res., 52 (2018), 187-204.  doi: 10.1051/ro/2017025.  Google Scholar

[31]

R. C. SavaskanS. Bhattacharya and L. N. Van Wassenhove, Closed-loop supply chain models with product remanufacturing, Manag. Science, 50 (2004), 239-252.  doi: 10.1287/mnsc.1030.0186.  Google Scholar

[32]

R. C. Savaskan and L. N. Van Wassenhove, Reverse channel design: The case of competing retailers, Manag. Science, 52 (2006), 1-14.  doi: 10.1287/mnsc.1050.0454.  Google Scholar

[33]

J. ShiG. Zhang and J. Sha, Optimal production and pricing policy for a closed loop system, Resources Conservation Recycling, 55 (2011), 639-647.  doi: 10.1016/j.resconrec.2010.05.016.  Google Scholar

[34]

S. TiwariC. K. Jaggi and S. S. Sana, Integrated supply chain of supplier and retailer for stochastic demand, Math. Model. Anal., 23 (2018), 582-595.  doi: 10.3846/mma.2018.035.  Google Scholar

[35]

A. A. TaleizadehM. S. Moshtagh and I. Moon, Pricing, product quality, and collection optimization in a decentralized closed-loop supply chain with different channel structures: Game theoretical approach, J. Cleaner Prod., 189 (2018), 406-431.  doi: 10.1016/j.jclepro.2018.02.209.  Google Scholar

[36]

R. H. Teunter, Determining optimal disassembly and recovery strategies, Omega, 34 (2006), 533-537.  doi: 10.1016/j.omega.2005.01.014.  Google Scholar

[37]

M. ThierryM. Salomon and N. L. V. Wassenhove, Strategies issues in product recovery management, California Manag. Review, 37 (1995), 114-135.  doi: 10.2307/41165792.  Google Scholar

[38]

A. A. Tsay and N. Agrawal, Channel dynamics under price and service competition, Manufacturing and Service Oper. Manag., 2 (2000), 93-110.  doi: 10.1287/msom.2.4.372.12342.  Google Scholar

[39]

J. Vorasayan and S. M. Ryan, Optimal price and quantity of refurbished products, Prod. Oper. Manag., 15 (2006), 369-383.  doi: 10.1111/j.1937-5956.2006.tb00251.x.  Google Scholar

[40]

Z. WangB. ZhangJ. Yin and X. Zhang, Willingness and behavior towards e-waste recycling for residents in Beijing city, China, J. Cleaner Prod., 19 (2011), 977-984.  doi: 10.1016/j.jclepro.2010.09.016.  Google Scholar

[41]

W. WangY. ZhangK. ZhangT. Bai and J. Shang, Reward-penalty mechanism for closed-loop supply chains under responsibility-sharing and different power structures, Internat. J. Prod. Econ., 170 (2015), 178-190.  doi: 10.1016/j.ijpe.2015.09.003.  Google Scholar

[42]

D.-Q. Yao and J. J. Liu, Competitive pricing of mixed retail and e-tail distribution channels, OMEGA, 33 (2005), 235-247.  doi: 10.1016/j.omega.2004.04.007.  Google Scholar

Figure 1.  The manufacturer's tradeoff between the channel leadership and the recycling channel
Figure 2.  The retailer's tradeoff between the channel leadership and the recycling channel
Table 1.  Notations
Symbol Description
Parameters
$c_{m}$ Unit producing cost from original materials
$c_{0}$ Unit producing cost from returns
$\delta$ Unit saving cost by recovery, $\delta=c_{m}-c_{0}$
$A$ The size of the market
$\alpha$ Sensitivity of the consumers for the retail price, $\alpha>0$
$k$ The basic recovery quantity, which represents the level of
environmental awareness of consumers
$h$ Sensitivity of the customers for the recycling price, $h>0$
Decision variables
$p$ The unit retail price
$w$ The unit wholesale price
$b$ The unit recycling price in centralized decision system
$b_{j}$ The unit recycling price of the recycling party $j$, subscript
$j=t, r, m$ denotes the recycling by the third-party, the
retailer and the manufacturer, respectively
$b_{mj}$ The unit transfer price, $j=r, t$, denotes R-channel and
T-channel, respectively
Derived function
$D(p)$ The demand of the products
$R(b_{j})$ The amount of the recycling products
$\pi_{m}$ The profits of the manufacturer
$\pi_{r}$ The profits of the retailer
$\pi_{t}$ The profits of the third-party
$\Pi$ The profits of the system
Symbol Description
Parameters
$c_{m}$ Unit producing cost from original materials
$c_{0}$ Unit producing cost from returns
$\delta$ Unit saving cost by recovery, $\delta=c_{m}-c_{0}$
$A$ The size of the market
$\alpha$ Sensitivity of the consumers for the retail price, $\alpha>0$
$k$ The basic recovery quantity, which represents the level of
environmental awareness of consumers
$h$ Sensitivity of the customers for the recycling price, $h>0$
Decision variables
$p$ The unit retail price
$w$ The unit wholesale price
$b$ The unit recycling price in centralized decision system
$b_{j}$ The unit recycling price of the recycling party $j$, subscript
$j=t, r, m$ denotes the recycling by the third-party, the
retailer and the manufacturer, respectively
$b_{mj}$ The unit transfer price, $j=r, t$, denotes R-channel and
T-channel, respectively
Derived function
$D(p)$ The demand of the products
$R(b_{j})$ The amount of the recycling products
$\pi_{m}$ The profits of the manufacturer
$\pi_{r}$ The profits of the retailer
$\pi_{t}$ The profits of the third-party
$\Pi$ The profits of the system
Table 2.  Main results of the M-led models
Model MM Model MR Model MT
$p^*$ $p^{MM*}=\frac{3A+\alpha c_m}{4\alpha}$ $p^{MR*}=\frac{3A+\alpha c_m}{4\alpha}$ $p^{MT*}=\frac{3A+\alpha c_m}{4\alpha}$
$b^*_i$ $b^{MM*}_m=\frac{h\delta -k}{2h}$ $b^{MR*}_r=\frac{h\delta -3k}{4h}$ $b^{MT*}_t=\frac{h\delta -3k}{4h}$
$w^*$ $w^{MM*}=\frac{A+\alpha c_m}{2\alpha}$ $w^{MR*}=\frac{A+\alpha c_m}{2\alpha}$ $w^{MT*}=\frac{A+\alpha c_m}{2\alpha}$
$b^*_{mj}$ N/A $b^{MR*}_{mr}=\frac{h\delta -k}{2h}$ $b^{MT*}_{mt}=\frac{h\delta -k}{2h}$
$\pi^*_m$ $\pi^{MM*}_m=\frac{P_f}{2}+P_r$ $\pi^{MR*}_m=\frac{P_f+P_r}{2}$ $\pi^{MT*}_m=\frac{P_f}{2}+\frac{P_r}{2}$
$\pi^*_r$ $\pi^{MM*}_r=\frac{P_f}{4}$ $\pi^{MR*}_r=\frac{P_f+P_r}{4}$ $\pi^{MT*}_r=\frac{P_f}{4}$
$\pi^*_t$ N/A N/A $\pi^{MT*}_t=\frac{P_r}{4}$
$\Pi^*$ $\Pi^{MM*}=\frac{3P_f}{4}+P_r$ $\Pi^{MR*}=\frac{3(P_f+P_r)}{4}$ $\Pi^{MT*}=\frac{3(P_f+P_r)}{4}$
Model MM Model MR Model MT
$p^*$ $p^{MM*}=\frac{3A+\alpha c_m}{4\alpha}$ $p^{MR*}=\frac{3A+\alpha c_m}{4\alpha}$ $p^{MT*}=\frac{3A+\alpha c_m}{4\alpha}$
$b^*_i$ $b^{MM*}_m=\frac{h\delta -k}{2h}$ $b^{MR*}_r=\frac{h\delta -3k}{4h}$ $b^{MT*}_t=\frac{h\delta -3k}{4h}$
$w^*$ $w^{MM*}=\frac{A+\alpha c_m}{2\alpha}$ $w^{MR*}=\frac{A+\alpha c_m}{2\alpha}$ $w^{MT*}=\frac{A+\alpha c_m}{2\alpha}$
$b^*_{mj}$ N/A $b^{MR*}_{mr}=\frac{h\delta -k}{2h}$ $b^{MT*}_{mt}=\frac{h\delta -k}{2h}$
$\pi^*_m$ $\pi^{MM*}_m=\frac{P_f}{2}+P_r$ $\pi^{MR*}_m=\frac{P_f+P_r}{2}$ $\pi^{MT*}_m=\frac{P_f}{2}+\frac{P_r}{2}$
$\pi^*_r$ $\pi^{MM*}_r=\frac{P_f}{4}$ $\pi^{MR*}_r=\frac{P_f+P_r}{4}$ $\pi^{MT*}_r=\frac{P_f}{4}$
$\pi^*_t$ N/A N/A $\pi^{MT*}_t=\frac{P_r}{4}$
$\Pi^*$ $\Pi^{MM*}=\frac{3P_f}{4}+P_r$ $\Pi^{MR*}=\frac{3(P_f+P_r)}{4}$ $\Pi^{MT*}=\frac{3(P_f+P_r)}{4}$
Table 3.  Main results of the R-led models
Model RM Model RR Model RT
$p^*$ $p^{RM*}=\frac{3A+\alpha c_m}{4\alpha}$ $p^{RR*}=\frac{3A+\alpha c_m}{4\alpha}$ $p^{RT*}=\frac{3A+\alpha c_m}{4\alpha}$
$b^*_i$ $b^{RM*}_m=\frac{h\delta -k}{2h}$ $b^{RR*}_r=\frac{h\delta -3k}{4h}$ $b^{RT*}_t=\frac{h\delta -3k}{4h}$
$w^*$ $w^{RM*}=\frac{A+3\alpha c_m}{4\alpha}$ $w^{RR*}=\frac{A+3\alpha c_m}{4\alpha}$ $w^{RT*}=\frac{A+3\alpha c_m}{4\alpha}$
$b^*_{mj}$ N/A $b^{RR*}_{mr}=\frac{3h\delta -k}{4h}$ $b^{RT*}_{mt}=\frac{h\delta -k}{2h}$
$\pi^*_m$ $\pi^{RM*}_m=\frac{P_f}{4}+P_r$ $\pi^{RR*}_m=\frac{P_f+P_r}{4}$ $\pi^{RT*}_m=\frac{P_f}{4}+\frac{P_r}{2}$
$\pi^*_r$ $\pi^{RM*}_r=\frac{P_f}{2}$ $\pi^{RR*}_r=\frac{P_f+P_r}{2}$ $\pi^{RT*}_r=\frac{P_f}{2}$
$\pi^*_t$ N/A N/A $\pi^{RT*}_t=\frac{P_r}{4}$
$\Pi^*$ $\Pi^{RM*}=\frac{3P_f}{4}+P_r$ $\Pi^{RR*}=\frac{3(P_f+P_r)}{4}$ $\Pi^{RT*}=\frac{3(P_f+P_r)}{4}$
Model RM Model RR Model RT
$p^*$ $p^{RM*}=\frac{3A+\alpha c_m}{4\alpha}$ $p^{RR*}=\frac{3A+\alpha c_m}{4\alpha}$ $p^{RT*}=\frac{3A+\alpha c_m}{4\alpha}$
$b^*_i$ $b^{RM*}_m=\frac{h\delta -k}{2h}$ $b^{RR*}_r=\frac{h\delta -3k}{4h}$ $b^{RT*}_t=\frac{h\delta -3k}{4h}$
$w^*$ $w^{RM*}=\frac{A+3\alpha c_m}{4\alpha}$ $w^{RR*}=\frac{A+3\alpha c_m}{4\alpha}$ $w^{RT*}=\frac{A+3\alpha c_m}{4\alpha}$
$b^*_{mj}$ N/A $b^{RR*}_{mr}=\frac{3h\delta -k}{4h}$ $b^{RT*}_{mt}=\frac{h\delta -k}{2h}$
$\pi^*_m$ $\pi^{RM*}_m=\frac{P_f}{4}+P_r$ $\pi^{RR*}_m=\frac{P_f+P_r}{4}$ $\pi^{RT*}_m=\frac{P_f}{4}+\frac{P_r}{2}$
$\pi^*_r$ $\pi^{RM*}_r=\frac{P_f}{2}$ $\pi^{RR*}_r=\frac{P_f+P_r}{2}$ $\pi^{RT*}_r=\frac{P_f}{2}$
$\pi^*_t$ N/A N/A $\pi^{RT*}_t=\frac{P_r}{4}$
$\Pi^*$ $\Pi^{RM*}=\frac{3P_f}{4}+P_r$ $\Pi^{RR*}=\frac{3(P_f+P_r)}{4}$ $\Pi^{RT*}=\frac{3(P_f+P_r)}{4}$
[1]

Benrong Zheng, Xianpei Hong. Effects of take-back legislation on pricing and coordination in a closed-loop supply chain. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021035

[2]

Reza Lotfi, Yahia Zare Mehrjerdi, Mir Saman Pishvaee, Ahmad Sadeghieh, Gerhard-Wilhelm Weber. A robust optimization model for sustainable and resilient closed-loop supply chain network design considering conditional value at risk. Numerical Algebra, Control & Optimization, 2021, 11 (2) : 221-253. doi: 10.3934/naco.2020023

[3]

Jinsen Guo, Yongwu Zhou, Baixun Li. The optimal pricing and service strategies of a dual-channel retailer under free riding. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021056

[4]

Kai Kang, Taotao Lu, Jing Zhang. Financing strategy selection and coordination considering risk aversion in a capital-constrained supply chain. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021042

[5]

Jun Tu, Zijiao Sun, Min Huang. Supply chain coordination considering e-tailer's promotion effort and logistics provider's service effort. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021062

[6]

Qiang Lin, Yang Xiao, Jingju Zheng. Selecting the supply chain financing mode under price-sensitive demand: Confirmed warehouse financing vs. trade credit. Journal of Industrial & Management Optimization, 2021, 17 (4) : 2031-2049. doi: 10.3934/jimo.2020057

[7]

Juliang Zhang, Jian Chen. Information sharing in a make-to-stock supply chain. Journal of Industrial & Management Optimization, 2014, 10 (4) : 1169-1189. doi: 10.3934/jimo.2014.10.1169

[8]

Guiyang Zhu. Optimal pricing and ordering policy for defective items under temporary price reduction with inspection errors and price sensitive demand. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021060

[9]

Qing Liu, Bingo Wing-Kuen Ling, Qingyun Dai, Qing Miao, Caixia Liu. Optimal maximally decimated M-channel mirrored paraunitary linear phase FIR filter bank design via norm relaxed sequential quadratic programming. Journal of Industrial & Management Optimization, 2021, 17 (4) : 1993-2011. doi: 10.3934/jimo.2020055

[10]

Min Li, Jiahua Zhang, Yifan Xu, Wei Wang. Effects of disruption risk on a supply chain with a risk-averse retailer. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021024

[11]

Haodong Chen, Hongchun Sun, Yiju Wang. A complementarity model and algorithm for direct multi-commodity flow supply chain network equilibrium problem. Journal of Industrial & Management Optimization, 2021, 17 (4) : 2217-2242. doi: 10.3934/jimo.2020066

[12]

Zhisong Chen, Shong-Iee Ivan Su. Assembly system with omnichannel coordination. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021047

[13]

Mikhail Dokuchaev, Guanglu Zhou, Song Wang. A modification of Galerkin's method for option pricing. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021077

[14]

Chong Wang, Xu Chen. Fresh produce price-setting newsvendor with bidirectional option contracts. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021052

[15]

Ajay Jasra, Kody J. H. Law, Yaxian Xu. Markov chain simulation for multilevel Monte Carlo. Foundations of Data Science, 2021, 3 (1) : 27-47. doi: 10.3934/fods.2021004

[16]

Kai Li, Tao Zhou, Bohai Liu. Pricing new and remanufactured products based on customer purchasing behavior. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021043

[17]

Gaurav Nagpal, Udayan Chanda, Nitant Upasani. Inventory replenishment policies for two successive generations price-sensitive technology products. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021036

[18]

Anastasiia Panchuk, Frank Westerhoff. Speculative behavior and chaotic asset price dynamics: On the emergence of a bandcount accretion bifurcation structure. Discrete & Continuous Dynamical Systems - B, 2021  doi: 10.3934/dcdsb.2021117

[19]

Kehan Si, Zhenda Xu, Ka Fai Cedric Yiu, Xun Li. Open-loop solvability for mean-field stochastic linear quadratic optimal control problems of Markov regime-switching system. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021074

[20]

Liqin Qian, Xiwang Cao. Character sums over a non-chain ring and their applications. Advances in Mathematics of Communications, 2021  doi: 10.3934/amc.2020134

2019 Impact Factor: 1.366

Article outline

Figures and Tables

[Back to Top]