Cold chain logistics is an important source of carbon emissions, yet high investment costs often weaken enterprises' motivation for low-carbon transformation. This study constructs an evolutionary game model involving the government, cold chain logistics enterprises (CCLEs), and new energy vehicle manufacturers (NEVMs) under policy intervention. Using parameter values derived from industry statistics, we employed numerical simulations to analyze the stability of stakeholders' strategies and the system's equilibrium points. The results revealed that stakeholders' decisions are mutually dependent, while carbon tax penalties and environmental external costs serve as key drivers of low-carbon innovation. In particular, government subsidies can effectively accelerate NEV adoption, but excessive reliance on subsidies without penalties may hinder long-term stability. These findings provide managerial insights for designing balanced subsidy–penalty mechanisms in the cold chain logistics sector.
Citation: Jiawen Zhang, Changhong Zou, Hailong Li. Tripartite evolutionary game analysis of cold chain logistics enterprises, NEV manufacturers, and government under dual-policy interventions[J]. Journal of Industrial and Management Optimization, 2026, 22(1): 528-553. doi: 10.3934/jimo.2026020
Cold chain logistics is an important source of carbon emissions, yet high investment costs often weaken enterprises' motivation for low-carbon transformation. This study constructs an evolutionary game model involving the government, cold chain logistics enterprises (CCLEs), and new energy vehicle manufacturers (NEVMs) under policy intervention. Using parameter values derived from industry statistics, we employed numerical simulations to analyze the stability of stakeholders' strategies and the system's equilibrium points. The results revealed that stakeholders' decisions are mutually dependent, while carbon tax penalties and environmental external costs serve as key drivers of low-carbon innovation. In particular, government subsidies can effectively accelerate NEV adoption, but excessive reliance on subsidies without penalties may hinder long-term stability. These findings provide managerial insights for designing balanced subsidy–penalty mechanisms in the cold chain logistics sector.
| [1] |
R. Wu, L. Zhu, M. Jiang, Research on the evolution game of low-carbon operations in cold chain logistics considering environmental regulations and green credit, Heliyon, 10 (2024), e30559. https://doi.org/10.1016/j.heliyon.2024.e30559 doi: 10.1016/j.heliyon.2024.e30559
|
| [2] |
J. Wu, Q. Li, G. Liu, R. Xie, Y. Zou, A. Scipioni, et al., Evaluating the impact of refrigerated transport trucks in China on climate change from the life cycle perspective, Environ. Impact Assess. Rev., 97 (2022), 106866. https://doi.org/10.1016/j.eiar.2021.106866 doi: 10.1016/j.eiar.2021.106866
|
| [3] |
Y. Xiong, L. Dai, Does green finance investment impact on sustainable development: Role of technological innovation and renewable energy, Renew. Energy, 214 (2023), 342–349. https://doi.org/10.1016/j.renene.2023.119184 doi: 10.1016/j.renene.2023.119184
|
| [4] |
A. Saif, S. Elhedhli, Cold supply chain design with environmental considerations: A simulation-optimization approach, Eur. J. Oper. Res., 251 (2016), 274–287. https://doi.org/10.1016/j.ejor.2015.11.029 doi: 10.1016/j.ejor.2015.11.029
|
| [5] |
S. Ji, D. Zhao, R. Luo, Evolutionary game analysis on local governments and manufacturers' behavioral strategies: Impact of phasing out subsidies for new energy vehicles, Energy, 189 (2019), 116064. https://doi.org/10.1016/j.energy.2019.116064 doi: 10.1016/j.energy.2019.116064
|
| [6] |
Q. Zhao, C. Tang, The impact of economic policy uncertainty on green technology innovation of new energy vehicle enterprises in China, Sustainability, 16 (2024), 4206. https://doi.org/10.3390/su16104206 doi: 10.3390/su16104206
|
| [7] |
C. Liu, Y. Liu, D. Zhang, C. Xie, The capital market responses to new energy vehicle (NEV) subsidies: An event study on China, Energy Econ., 105 (2022), 105677. https://doi.org/10.1016/j.eneco.2021.105677 doi: 10.1016/j.eneco.2021.105677
|
| [8] |
T. Zhang, S. Li, Y. Li, W. Wang, Evaluation of technology innovation efficiency for the listed NEV enterprises in China, Econ. Anal. Policy, 80 (2023), 1445–1458. https://doi.org/10.1016/j.eap.2023.09.004 doi: 10.1016/j.eap.2023.09.004
|
| [9] |
K. Yuan, C. Wang, G. Wu, Range Coopetition: NEV Automakers' Strategies Under Dual Credit Policy Influences, J. Knowl. Econ., 16 (2025), 5056–5092. https://doi.org/10.1007/s13132-025-02420-6 doi: 10.1007/s13132-025-02420-6
|
| [10] | J. W. Weibull, Evolutionary Game Theory, MIT Press, Cambridge, MA, 1992. |
| [11] |
K. Kang, B. Q. Tan, Carbon emission reduction investment in sustainable supply chains under cap-and-trade regulation: An evolutionary game-theoretical perspective, Expert Syst. Appl., 227 (2023), 120335. https://doi.org/10.1016/j.eswa.2023.120335 doi: 10.1016/j.eswa.2023.120335
|
| [12] |
S. Zhang, N. Chen, X. Song, J. Yang, Optimizing decision-making of regional cold chain logistics system in view of low-carbon economy, Transp. Res. Part A: Policy Pract., 130 (2019), 844–857. https://doi.org/10.1016/j.tra.2019.07.004 doi: 10.1016/j.tra.2019.07.004
|
| [13] |
G. Qin, F. Tao, L. Li, A vehicle routing optimization problem for cold chain logistics considering customer satisfaction and carbon emissions, Int. J. Environ. Res. Public Health, 16 (2019), 576. https://doi.org/10.3390/ijerph16040576 doi: 10.3390/ijerph16040576
|
| [14] |
Z. Liu, Y.-Q. Huang, W.-L. Shang, Y.-J. Zhao, Z.-L. Yang, Z. Zhao, Precooling energy and carbon emission reduction technology investment model in a fresh food cold chain based on a differential game, Appl. Energy, 326 (2022), 119945. https://doi.org/10.1016/j.apenergy.2022.119945 doi: 10.1016/j.apenergy.2022.119945
|
| [15] |
X. Wei, W. Chen, M. Li, Y. Wang, Do environmental regulations promote low-carbon diffusion among different scales of enterprise? A complex network-based evolutionary game approach, Carbon Manag., 12 (2021), 681–692. https://doi.org/10.1080/17583004.2021.1998594 doi: 10.1080/17583004.2021.1998594
|
| [16] |
N. Cadavid-Giraldo, M. C. Velez-Gallego, A. Restrepo-Boland, Carbon emissions reduction and financial effects of a cap and tax system on an operating supply chain in the cement sector, J. Clean. Prod., 275 (2020), 122583. https://doi.org/10.1016/j.jclepro.2020.122583 doi: 10.1016/j.jclepro.2020.122583
|
| [17] |
L. P. Widianingsih, Can Renewable Energy, Carbon Taxes, and Economic Growth Mitigate Countries' Carbon Emissions? Int. J. Energy Econ. Policy, 15 (2024), 103–109. https://doi.org/10.32479/ijeep.17566 doi: 10.32479/ijeep.17566
|
| [18] |
J. Planelles, M.-E. Sanin, Carbon taxation in a global production network, Eur. Econ. Rev., 172 (2025), 104938. https://doi.org/10.1016/j.euroecorev.2024.104938 doi: 10.1016/j.euroecorev.2024.104938
|
| [19] |
Z. Cheng, L. Li, J. Liu, The emissions reduction effect and technical progress effect of environmental regulation policy tools, J. Clean. Prod., 149 (2017), 191–205. https://doi.org/10.1016/j.jclepro.2017.02.035 doi: 10.1016/j.jclepro.2017.02.035
|
| [20] |
S. Abbasi, H. A. Choukolaei, A systematic review of green supply chain network design literature focusing on carbon policy, Decis. Anal. J., 6 (2023), 100–189. https://doi.org/10.1016/j.dajour.2023.100189 doi: 10.1016/j.dajour.2023.100189
|
| [21] |
S. Elhedhli, R. Merrick, Green supply chain network design to reduce carbon emissions, Transp. Res. Part D: Transp. Environ., 17 (2012), 370–379. https://doi.org/10.1016/j.trd.2012.02.003 doi: 10.1016/j.trd.2012.02.003
|
| [22] |
T.-C. Kuo, M.-L. Tseng, H.-M. Chen, P.-S. Chen, P.-C. Chang, Design and analysis of supply chain networks with low carbon emissions, Comput. Econ., 52 (2018), 1353–1374. https://doi.org/10.1007/s10614-017-9767-4 doi: 10.1007/s10614-017-9767-4
|
| [23] |
C. Das, S. Jharkharia, Low carbon supply chain: A state-of-the-art literature review, J. Manuf. Technol. Manag., 29 (2018), 398–428. https://doi.org/10.1108/JMTM-06-2017-0126 doi: 10.1108/JMTM-06-2017-0126
|
| [24] |
X. Guo, W. Zhang, B. Liu, Low-carbon routing for cold-chain logistics considering the time-dependent effects of traffic congestion, Transp. Res. Part D: Transp. Environ., 113 (2022), 103502. https://doi.org/10.1016/j.trd.2022.103502 doi: 10.1016/j.trd.2022.103502
|
| [25] |
L. Shen, X. Xu, F. Shao, H. Shao, Y. Ge, A multi-objective optimization model for medical waste recycling network design under uncertainties, Transp. Res. Part E: Logist. Transp. Rev., 184 (2024), 103492. https://doi.org/10.1016/j.tre.2024.103492 doi: 10.1016/j.tre.2024.103492
|
| [26] |
X. Xu, F. Li, T. Wu, X. Huang, X. Guan, T. Zheng, et al., Location-routing optimization problem of pharmaceutical cold chain logistics with oil-electric mixed fleets under uncertainties, Comput. Ind. Eng., 201 (2025), 110932. https://doi.org/10.1016/j.cie.2025.110932 doi: 10.1016/j.cie.2025.110932
|
| [27] |
Q. Bai, M. Jin, X. Xu, Effects of carbon emission reduction on supply chain coordination with vendor-managed deteriorating product inventory, Int. J. Prod. Econ., 208 (2019), 83–99. https://doi.org/10.1016/j.ijpe.2018.11.008 doi: 10.1016/j.ijpe.2018.11.008
|
| [28] |
H.-O. Günther, M. Kannegiesser, N. Autenrieb, The role of electric vehicles for supply chain sustainability in the automotive industry, J. Clean. Prod., 90 (2015), 220–233. https://doi.org/10.1016/j.jclepro.2014.11.069 doi: 10.1016/j.jclepro.2014.11.069
|
| [29] |
J.-H. Zhao, D.-L. Zeng, T.-W. Zhou, Z.-C. Zhu, Data mining of urban new energy vehicles in an intelligent government subsidy environment using closed-loop supply chain pricing model, Comput. Syst. Sci. Eng., 35 (2020), 151–172. https://doi.org/10.32604/csse.2020.011244 doi: 10.32604/csse.2020.011244
|
| [30] |
X. Xia, P. Li, Z. Xia, R. Wu, Y. Cheng, Life cycle carbon footprint of electric vehicles in different countries: A review, Sep. Purif. Technol., 301 (2022), 122063. https://doi.org/10.1016/j.seppur.2022.122063 doi: 10.1016/j.seppur.2022.122063
|
| [31] |
A. Zahoor, Y. Yu, H. Zhang, B. Nihed, S. Afrane, S. Peng, et al., Can the new energy vehicles (NEVs) and power battery industry help China to meet the carbon neutrality goal before 2060? J. Environ. Manag., 336 (2023), 117663. https://doi.org/10.1016/j.jenvman.2023.117663 doi: 10.1016/j.jenvman.2023.117663
|
| [32] |
L. Shao, S. Jin, Resilience assessment of the lithium supply chain in China under impact of new energy vehicles and supply interruption, J. Clean. Prod., 252 (2020), 119624. https://doi.org/10.1016/j.jclepro.2019.119624 doi: 10.1016/j.jclepro.2019.119624
|
| [33] |
J. Li, Y. Ku, Y. Yu, C. Liu, Y. Zhou, Optimizing production of new energy vehicles with across-chain cooperation under China's dual credit policy, Energy, 194 (2020), 116832. https://doi.org/10.1016/j.energy.2019.116832 doi: 10.1016/j.energy.2019.116832
|
| [34] |
J. Cai, L. Jia, M. Ping, Supply chain competition model with a NEV-sharing platform: Financing and risk attitude concerns, Comput. Ind. Eng., 172 (2022), 108554. https://doi.org/10.1016/j.cie.2022.108554 doi: 10.1016/j.cie.2022.108554
|
| [35] |
Y. Xue, C. Zhu, Y. Lu, Research on the influence mechanism of new energy vehicle promotion policy, Sustainability, 17 (2025), 3699. https://doi.org/10.3390/su17083699 doi: 10.3390/su17083699
|
| [36] |
S. Franzò, A. Nasca, The environmental impact of electric vehicles: A novel life cycle-based evaluation framework and its applications to multi-country scenarios, J. Clean. Prod., 315 (2021), 128005. https://doi.org/10.1016/j.jclepro.2021.128005 doi: 10.1016/j.jclepro.2021.128005
|
| [37] |
C.-W. Su, X. Yuan, R. Tao, M. Umar, Can new energy vehicles help to achieve carbon neutrality targets? J. Environ. Manag., 297 (2021), 113348. https://doi.org/10.1016/j.jenvman.2021.113348 doi: 10.1016/j.jenvman.2021.113348
|
| [38] |
Z. Wu, Q. He, J. Li, G. Bi, M. F. Antwi-Afari, Public attitudes and sentiments towards new energy vehicles in China: A text mining approach, Renew. Sustain. Energy Rev., 178 (2023), 113242. https://doi.org/10.1016/j.rser.2023.113242 doi: 10.1016/j.rser.2023.113242
|
| [39] |
C. Xu, F. Liu, Y. Zhou, R. Dou, X. Feng, B. Shen, Manufacturers' emission reduction investment strategy under carbon cap-and-trade policy and uncertain low-carbon preferences, Ind. Manag. Data Syst., 123 (2023), 2522–2550. https://doi.org/10.1108/IMDS-02-2023-0087 doi: 10.1108/IMDS-02-2023-0087
|
| [40] |
D. Friedman, Evolutionary games in economics, Econometrica, 59 (1991), 637–666. https://doi.org/10.2307/2938181 doi: 10.2307/2938181
|
| [41] |
Y. Zu, L. Chen, Y. Fan, Research on low-carbon strategies in supply chain with environmental regulations based on differential game, J. Clean. Prod., 177 (2018), 527–546. https://doi.org/10.1016/j.jclepro.2017.12.255 doi: 10.1016/j.jclepro.2017.12.255
|
| [42] |
Z.-H. Zhang, D. Ling, Q.-X. Yang, Y.-C. Feng, J. Xiu, Central environmental protection inspection and carbon emission reduction: A tripartite evolutionary game model from the perspective of carbon neutrality, Pet. Sci., 21 (2024), 2139–2153. https://doi.org/10.1016/j.petsci.2024.04.022 doi: 10.1016/j.petsci.2024.04.022
|
| [43] |
Y. Gao, M. Zhang, M. A. Nasir, Y. Hao, J. Wu, L. Zhang, ESG greenwashing behaviour in the electric vehicle supply chain: Insights from evolutionary game theory, Int. J. Prod. Econ., 19 (2015), 109798. https://doi.org/10.1016/j.ijpe.2025.109798 doi: 10.1016/j.ijpe.2025.109798
|
| [44] |
S. Ebrahimi, S.-M. Hosseini-Motlagh, M. Nematollahi, L.E. Cárdenas-Barrón, Coordinating double-level sustainability effort in a sustainable supply chain under cap-and-trade regulation, Expert Syst. Appl., 207 (2022), 117872. https://doi.org/10.1016/j.eswa.2022.117872 doi: 10.1016/j.eswa.2022.117872
|
| [45] |
Y. Wang, H. Luo, X. Zhang, Y. Li, S. Yang, Q. Lu, et al., Research on evolutionary game of low-carbon logistics in two-level supply chain under carbon tax policy, Sustain. Futures, 8 (2024), 100387. https://doi.org/10.1016/j.sftr.2024.100387 doi: 10.1016/j.sftr.2024.100387
|
| [46] |
C. Zhao, X. Ma, K. Wang, The electric vehicle promotion in the cold-chain logistics under two-sided support policy: An evolutionary game perspective, Transp. Policy, 121 (2022), 14–34. https://doi.org/10.1016/j.tranpol.2022.03.008 doi: 10.1016/j.tranpol.2022.03.008
|
| [47] |
D. Liao, B. Tan, An evolutionary game analysis of new energy vehicles promotion considering carbon tax in post-subsidy era, Energy, 264 (2023), 126156. https://doi.org/10.1016/j.energy.2022.126156 doi: 10.1016/j.energy.2022.126156
|
| [48] |
L. Zhang, Y. Ding, Y.-H. Kuo, L. Zhang, Cold chain routing for product freshness and low carbon emissions: A target-oriented robust optimization approach, SSRN J., 199 (2024), 104138. https://doi.org/10.2139/ssrn.4802417 doi: 10.2139/ssrn.4802417
|
| [49] |
A. Mishra, T. Kundu, R. Kapoor, M. Goh, Blockchain adoption in cross-border cold supply chains: Cost, Efficiency and Trust, Transp. Res. Part E: Logist. Transp. Rev., 201 (2025), 104236. https://doi.org/10.1016/j.tre.2025.104236 doi: 10.1016/j.tre.2025.104236
|
| [50] | L. Lv, T. Liu, C. Chen, Research on the Impact of Development of the New Energy Vehicle Industry on the Tax Revenue of Automotive Products in China and Trend Forecast, 2024 5th Int. Conf. Clean Energy Electr. Power Eng. (ICCEPE), IEEE, 2024,189–194. |
| [51] | OECD, The Economic Consequences of Outdoor Air Pollution, OECD Publ., Paris, 2016. https://doi.org/10.1787/9789264257474-en |
| [52] |
F. Wang, C. Gao, W. Zhang, D. Huang, Industrial structure optimization and low-carbon transformation of Chinese industry based on the forcing mechanism of CO2 emission peak target, Sustainability, 13 (2021), 4417. https://doi.org/10.3390/su13084417 doi: 10.3390/su13084417
|
| [53] | C. Deuskar, S. Murray, J. S. L. Molano, I. A. Khan, A. Maria, Banking on Cities, 2025. Available from: https://www.worldbank.org/en/topic/urbandevelopment/publication/banking-on-cities. |