基于复杂市场网络绿色技术创新扩散的两阶段演化分析

doi:10.16381/j.cnki.issn1003-207x.2021.2026

摘要/Abstract

摘要：

为推动绿色技术创新、绿色产品的市场替代，缓解能源与环境压力，本研究构建了基于复杂市场网络的绿色技术创新扩散两阶段演化博弈模型，探索企业与消费者在市场机制与政策机制的协调互补下双方策略的调整过程，并分析得到有利于绿色技术创新扩散的较优稳定条件。经过仿真模拟实验可以发现：企业与消费者对市场导向更具敏感性，绿色产品的消费需求是企业主要的决策依据，而提升技术成熟度有利于推动绿色产品在消费者群体间的扩散。同时，具有相对竞争优势的支柱性主导企业会对绿色产品的市场需求更加关注，竞争性边缘企业则更加容易受到市场中选择绿色技术企业的比例影响。然而，绿色技术创新扩散产生的双重外部性容易导致市场失灵，这就需要政府部门利用经济政策调控，克服市场失灵带来的负外部性。因此，政府部门应该以提升绿色产品的消费需求为目的，通过刺激消费需求来激励更多企业采纳绿色生产技术。同时，亦可通过一系列规制手段激励企业不断完善绿色技术水平，以提升绿色产品的市场占有率。值得注意的是，政府的政策激励存在边际效用递减，应设置合理阈值区间。

关键词: 绿色技术创新扩散, 市场导向, 政策激励, 多层级网络, 两阶段演化博弈

Abstract:

To promote the market replacement of green innovative technology and green products， relieve the pressure of energy and environment. A two-stage evolutionary game model of green technology innovation diffusion is constructed based on complex market network， exploring the adjustment process of enterprises and consumers’ strategies under the coordination and complementarity of market mechanism and policy mechanism， and analyzing the optimal and stable conditions conducive to the diffusion of green technology innovation. Through simulation experiments， it could be found that enterprises and consumers are more sensitive to market orientation， consumer demand for green products is the main decision-making basis of enterprises and improving technology maturity is conducive to promoting the diffusion of green products among consumer groups. Meanwhile， the dominant enterprises with relative competitive advantages pay more attention to the market demand for green products， while the competitive marginal enterprises are more easily influenced by the proportion of green technology enterprises in the market. However， the double externalities caused by the diffusion of green technology innovation easily led to market failure， which requires the government to overcome the negative externalities caused by market failure through economic policy regulation. Hence， the government should take improving the consumption demand of green products as the priority to encourage more enterprises to choose green technology production. And promoting the market share by driving enterprises to improve the technology of green products. Meanwhile， it should also pay attention to the diminishing marginal utility of policy incentives.

Key words: diffusion of green technology innovation, market orientation, policy incentive, multi-level network, two-stage evolutionary game

中图分类号:

C93.1

陈恒,彭程,郭爽,杨志,祁凯. 基于复杂市场网络绿色技术创新扩散的两阶段演化分析[J]. 中国管理科学, 2024, 32(3): 135-144.

Heng Chen,Cheng Peng,Shuang Guo,Zhi Yang,kai Qi. Two-stage Evolution Analysis of Green Technology Innovation Diffusion Based on Complex Market Network[J]. Chinese Journal of Management Science, 2024, 32(3): 135-144.

图/表 8

图1

图2

图3

图4

图5

图6

图7

图8

参考文献 37

1	潘燕春，马晓晨. C&T和政府补贴下的绿色技术选择和产品定价研究［J］.中国管理科学，2024，32（2）：99-107.
	Pan Y C， Ma X C. Green technology selection and product pricing research under C&T and government subsidies［J］. Chinese Journal of Management Science，2024，32（2）：99-107.
2	Lin B， Jia Z. Economic， energy and environmental impact of coal-to-electricity policy in China： a dynamic recursive CGE study［J］. Science of The Total Environment， 2020， 698： 134241.
3	Pan L Y， Zhou K， Li W Q， et al. Subsidy policy discussion on the hydroelectric power substitution for scattered coal consumption： a case study of sichuan province［J］. Renewable and Sustainable Energy Review， 2019， 108： 539-549.
4	Zeng Y C， Dong P W， Shi Y Y， et al. Analyzing the co-evolution of green technology diffusion and consumers' pro-environmental attitudes： an agent-based model［J］. Journal of Cleaner Production， 2020， 256： 120384.
5	张宏伟．政策工具及其组合与海上风电技术创新和扩散：来自德国的考察［J］. 科技进步与对策， 2017， 34（14）： 119-125．
	Zhang H W. Policy instrument， policy instr-ument mix and offshore wind power technology innovation and diffusion： the conditions from Germany［J］. Science & Technology Progress and Policy， 2017， 34（14）： 119-125．
6	Shi Y Y， Wei Z X， Shahbaz M， et al. Exploring the dynamics of low-carbon technology diffusion among enterprises： an evolutionary game model on a two-level heterogeneous social network［J］. Energy Economics， 2021， 101： 105399.
7	Luo G， Liu Y， Zhang L， et al. Do governmental subsidies improve the financial performance of China’s new energy power generation enterprises？［J］. Energy， 227： 120432.
8	唐啸，胡鞍钢．创新绿色现代化：隧穿环境库兹涅兹曲线［J］. 中国人口·资源与环境， 2018， 28（5）： 1-7．
	Tang X， Hu A G. Achieve innovative and ecological modernization： tunneling through the environmental kuznets curve［J］． China Population， Resources and Environment， 2018， 28（5）： 1-7．
9	汪明月，李颖明.政府市场规制、产品消费选择和企业绿色技术创新［J］.管理工程学报，2021， 35（2）： 44-54.
	Wang M Y， Li Y M. Market regulation，product consumption choice and enterprise green technological innovation［J］. Journal of Industrial Engineering and Engineering Management， 2021， 35（2）： 44-54.
10	Chavez R， Yu W， Feng M， et al. The effect of customer-centric green supply chain management on operational performance and customer satisfaction［J］. Business Strategy Environment， 2016， 25（3）： 205-220.
11	Ozdemir O， Hobbs B F， Van H M， et al. Capacity vs energy subsidies for promoting renewable investment： benefits and costs for the EU power market［J］. Energy Policy， 2020， 137： 111166.
12	Mahmoudi R， Rasti-Barzoki M. Sustainable supply chains under government intervention with a real-world case study： an evolutionary game theoretic approach［J］. Computer Industry Engineering， 2018， 116： 130-143.
13	Gu H， Liu Z， Qing Q. Optimal electric vehicle production strategy under subsidy and battery recycling［J］. Energy Policy， 2017， 109： 579-589.
14	Zhao R， Zhou X， Han J， et al. For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation［J］. Technology Forecast and Social Change， 2016， 112： 262-274.
15	Wang L， Zheng J J. Research on low-carbon diffusion considering the game among enterprises in the complex network context［J］. Journal of Cleaner Production， 2019， 210： 1-11.
16	Zhuge C X， Wei B R， Dong C J， et al. Exploring the future electric vehicle market and its impacts with an agent-based spatial integrated framework： a case study of Beijing， China［J］. Journal of Cleaner Production， 2019， 221： 710-737.
17	Li J J， Jiao J L， Tang Y S. An evolutionary analysis on the effect of government policies on electric vehicle diffusion in complex network［J］. Energy Policy， 2019， 129： 1-12.
18	Encarnaç˜ao S， Santos F P， Santos F C， et al. Paths to the adoption of electric vehicles： an evolutionary game theoretical approach［J］. Transportation Research Part B： Methodological， 2018， 113： 24-33.
19	Li J J， Jiao J L， Tang Y S. Analysis of the impact of policies intervention on electric vehicles adoption considering information transmission—based on consumer network model［J］. Energy Policy， 2020， 144： 111560.
20	Strazzabosco A， Conrad S A， Lant P A， et al. Expert opinion on influential factors driving renewable energy adoption in the water industry［J］. Renewable Energy， 2020， 162： 754-765.
21	王璐，马庆庆，杨劼，等.基于复杂网络演化博弈的绿色消费者对新能源汽车扩散的影响研究［J］.中国管理科学， 2022， 30（4）： 74-85.
	Wang l， Ma Q Q， Yang J， et al. Research on the influence of green consumers on the diffusion of new energy vehicles based on complex network evolutionary game［J］. Chinese Journal of Management Science， 2022， 30（4）： 74-85.
22	胡玉真，张耸，等.民航干扰管理—旅客意愿视角［M］. 北京：科学出版社，2022.
	Hu Y Z， Zhang S， et al. Interference management in civil aviation： passenger willingness perspective［M］.Beijing： Science Press， 2022.
23	Zhang H， Li P， Zheng H， et al. Impact of carbon tax on enterprise operation and production strategy for low-carbon products in a co-opetition supply chain［J］. Journal of Cleaner Production， 2021， 287： 125058.
24	Zhou Y. The role of green customers under competition： a mixed blessing？［J］. Journal of Cleaner Production， 2018， 170： 857866.
25	Fan R G， Dong L L， Yang W， et al. Study on the optimal supervision strategy of government low-carbon subsidy and the corresponding efficiency and stability in the small-world network context［J］. Journal of Cleaner Production， 2017， 168： 536-550.
26	Chen F， Wu B， Lou W. An evolutionary analysis on the effect of government policies on green R & D of photovoltaic industry diffusion in complex network［J］. Energy Policy， 2021， 152： 112217.
27	Sreekumar R. Bhaskaran V K. Effort， revenue， and cost sharing mechanisms for collaborative new product development［J］. Management Science， 2009， 55（7）：1152-1169.
28	曾炳昕，丁庆国，朱磊.碳市场中市场势力对减排技术采用的影响［J］.中国管理科学， 2022， 30（2）： 38-47.
	Zeng B X， Ding G Q， Zhu L. The effect of market power in carbon market on emission abatement technology adoption［J］. Chinese Journal of Management Science， 2022， 30（2）： 38-47.
29	Li F Y， Cao X， Ou R. A network-based evolutionary analysis of the diffusion of cleaner energy substitution in enterprises： the roles of PEST factors［J］. Energy Policy， 2021， 156： 112385.
30	Meng Q C， Wang Y T， Zhang Z， et al. Supply chain green innovation subsidy strategy considering consumer heterogeneity［J］. Journal of Cleaner Production， 2021， 281： 125199.
31	Coria J. Taxes， permits， and the diffusion of a new technology［J］. Resource and Energy Economics， 2009， 31（4）： 249-271.
32	Chen L Q， Gao M. Novel information interaction rule for municipal household waste classification behavior based on an evolving scale-free network［J］. Resources Conservation and Recycling， 2021， 168： 105445.
33	孙耀吾，卫英平. 高技术企业联盟知识扩散研究——基于小世界网络的视角［J］.管理科学学报， 2011， 14（12）： 17-26.
	Sun Y W， Wei Y P. Study on knowledge diffusion of high-tech enterprise alliance from the small-world network perspective［J］. Journal of Management Sciences in China， 2011， 14（12）： 17-26.
34	李柏洲，曾经纬，王丹，等. 基于知识行为的企业绿色创新系统协同演化研究［J］. 管理工程学报， 2020， 34（5）： 42-52.
	Li B Z， Zeng J W， Wang D， et al. Research on co-evolution of enterprise green innovation system based on knowledge behavior［J］. Journal of Industrial Engineering/Engineering Management， 2020， 34（5）： 42-52.
35	Tian Y H， Govindan K， Zhu Q H. A system dynamics model based on evolutionary game theory for green supply chain management diffusion among Chinese manufacturers［J］. Journal of Cleaner Production， 2014， 80： 96-105.
36	Zhong M， Liu Q， Zeng A， et al. An effects analysis of China’s metal mineral resource tax reform： a heterogeneous dynamic multi-regional CGE appraisal［J］. Resources Policy， 2018， 58： 303–313.
37	Fan R G， Dong L L. The dynamic analysis and simulation of government subsidy strategies in low-carbon diffusion considering the behavior of heterogeneous agents［J］. Energy Policy， 2018， 117： 252-262.

[1]	黄定轩, 李树良, 吴永娇, 卢锐. 同时考虑博弈支付与有限市场容量的绿色建筑与传统建筑共生研究[J]. 中国管理科学, 2021, 29(8): 94-105.
[2]	顾琴轩, 胡冬青, 许彦妮. 市场导向对组织创造力的非线性作用机理——组织二元结构文化与创业导向的影响研究[J]. 中国管理科学, 2021, 29(4): 237-248.