全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

政府调控下的节能电器消费者购买行为决策研究
Research on Consumer Purchasing Behavior Decision of Energy Saving Electrical Appliances under Government Regulation

DOI: 10.12677/ecl.2024.132288, PP. 2349-2363

Keywords: 能源效率,居民住宅反弹效应,消费者行为,能源政策,演化博弈,节能减排
Energy Efficiency
, Residential Rebound Effect, Consumer Behavior, Energy Policy, Evolutionary Game, Energy Conservation and Emission Reduction

Full-Text   Cite this paper   Add to My Lib

Abstract:

节能消费是实施节能产品供应链的引擎,节能产品生产企业是节能产品供应链的主要实施者。运用演化博弈理论,构建了政府规制下节能产品生产与消费双方行为选择过程的演化博弈模型。通过分析,得到了双方在不同情况下的稳定策略。考虑能效成本下降可能引起能源需求的额外增加,本文也将同时对能源反弹与消费行为融入研究问题之中。研究结果显示,在政府逐步降低节能产品补贴的过程中,有效降低能源效率反弹效应对促进市场向正向状态转变具有显著作用。对于企业在政府政策激励下过度生产节能产品而造成的市场中节能产品供大于求的非良性状态有一定的改善作用。
Energy saving consumption is the engine of energy saving product supply chain, and energy saving product production enterprises are the main implementors of energy saving product supply chain. Based on the evolutionary game theory, an evolutionary game model of the behavior selection process of both production and consumption of energy-saving products under government regulation is constructed. Through the analysis, the stability strategies of both sides in different situations are obtained. Considering that the reduction of energy efficiency costs may lead to an additional increase in energy demand, this paper will also integrate energy rebound and consumption behavior into the research question. The results show that in the process of gradually reducing subsidies for energy-saving products, effectively reducing the rebound effect of energy efficiency has a significant effect on promoting the market to change to a positive state. It has a certain effect on improving the non-benign state of oversupply of energy-saving products in the market caused by over-production of energy-saving products under the incentive of government policies.

References

[1]  Liu, J., Sun, X., Lu, B., Zhang, Y. and Sun, R. (2016) The Life Cycle Rebound Effect of Air-Conditioner Consumption in China. Applied Energy, 184, 1026-1032.
https://doi.org/10.1016/j.apenergy.2015.11.100
[2]  Jenkins, J., Nordhaus, T. and Shellenberger, M. (2011) Energy Emergence: Rebound and Backfire as Emergent Phenomena. Breakthrough Institute, Oakland.
[3]  Jeremy, H. (2000) Environmental Supply Chain Dynamics. Journal of Cleaner Production, 8, 455-471.
https://doi.org/10.1016/S0959-6526(00)00013-5
[4]  Doonan, J., Lanoie, P. and Laplante, B. (2005) Determinants of Environmental Performance in the Canadian Pulp and Paper Industry: An Assessment from Inside the Industry. Ecological Economics, 55, 73-84.
https://doi.org/10.1016/j.ecolecon.2004.10.017
[5]  Carter, C.R. and Easton, P.L. (2011) Evolution and Future Journal of Distribution & Logistics Management. Sustainable Supply Chain Management, 4, 46-62.
https://doi.org/10.1108/09600031111101420
[6]  Anton, W.R.Q., Deltas, G. and Khanna, M. (2004) Incentives for Environmental Self-Regulation and Implications for Environmental Performance. Journal of Environmental Economics and Management, 48, 632-654.
https://doi.org/10.1016/j.jeem.2003.06.003
[7]  鞠芳辉, 谢子远, 宝贡敏. 企业社会责任的实现——基于消费者选择的分析[J]. 中国工业经济, 2005(9): 91-98.
[8]  张露, 帅传敏, 刘洋. 消费者绿色消费行为的心理归因及干预策略分析——基于计划行为理论与情境实验数据的实证研究[J]. 中国地质大学学报(社会科学版), 2013(5): 49-55, 139.
[9]  李友东, 赵道致, 夏良杰. 低碳供应链环境下政府和核心企业的演化博弈模型[J]. 统计与决策, 2013(20): 38-41.
[10]  李媛, 赵道致. 低碳供应链中政府监管企业减排的演化博弈模型[J]. 天津大学学报(社会科学版), 2013(3): 193-197.
[11]  何丽红, 王秀. 低碳供应链中政府与核心企业进化博弈模型[J]. 中国人口·资源与环境, 2014(S1): 27-30.
[12]  Zhu, Q.H. and Dou, Y.J. (2007) Evolutionary Game Model between Governments and Core Enterprises in Greening Supply Chains. Systems Engineering-Theory and Practice, 27, 85-89.
https://doi.org/10.1016/S1874-8651(08)60075-7
[13]  Barari, S., Agarwal, G., Zhang, W.J.C., et al. (2012) A Decision Framework for the Analysis of Green Supply Chain Contracts: An Evolutionary Game Approach. Expert Systems with Applications, 39, 2965-2976.
https://doi.org/10.1016/j.eswa.2011.08.158
[14]  付秋芳, 忻莉燕, 马士华. 惩罚机制下供应链企业碳减排投入的演化博弈[J]. 管理科学学报, 2016(4): 56-70.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133