Emission Reduction Decisions in Blockchain-Enabled Low-Carbon Supply Chains under Different Power Structures

块链 还原(数学) 供应链 碳纤维 功率(物理) 业务 计算机科学 计算机安全 数学 物理 算法 营销 几何学 量子力学 复合数
作者
M.M. Jiang,Liping Qin,Wenjin Zuo,Qiang Hu
出处
期刊:Mathematics [MDPI AG]
卷期号:12 (5): 704-704 被引量:1
标识
DOI:10.3390/math12050704
摘要

With the global climate problem becoming increasingly severe, governments have adopted policies to encourage enterprises to invest in low-carbon technologies. However, the opacity of the carbon emission reduction process leads to incomplete consumer trust in low-carbon products as well as higher supply chain transaction costs. Based on this, this paper constructs Stackelberg game models with and without blockchain under different power structures and compares the impact of these models on low-carbon emission reduction decisions. The results show that: (1) blockchain does not necessarily improve enterprise profits and can only help enterprises maintain optimal profits within a certain range when the carbon emission cost is low; (2) when consumers’ environmental awareness is high, the blockchain can incentivize manufacturers to enhance carbon emission reduction, and it has an obvious promotional effect on retailers’ profits; and (3) the profit gap between enterprises in the supply chain is larger under different power structures, and the implementation of blockchain can coordinate profit distribution and narrow the gap between enterprises. Compared with the manufacturer-dominated model, the emission reduction in products is maximized under the retailer-dominated model. Our study provides theoretical support for the government to regulate greenhouse gas emissions as well as for the optimization of enterprises’ decision-making supported by blockchain.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
且听风呤发布了新的文献求助10
刚刚
1秒前
xLi发布了新的文献求助20
2秒前
可燃斌发布了新的文献求助10
2秒前
消逝发布了新的文献求助10
3秒前
4秒前
科研通AI6.1应助Cam采纳,获得10
4秒前
Wl0115完成签到,获得积分10
5秒前
在水一方应助优雅的魂幽采纳,获得10
5秒前
自然天真完成签到,获得积分10
6秒前
6秒前
7秒前
Wl0115发布了新的文献求助10
7秒前
niuma发布了新的文献求助30
8秒前
zzz18发布了新的文献求助10
8秒前
李健的小迷弟应助小兔叽采纳,获得10
8秒前
CipherSage应助嘻嘻采纳,获得20
9秒前
烟花应助勤恳的元绿采纳,获得10
9秒前
疯狂的小松鼠完成签到,获得积分10
10秒前
12秒前
12秒前
12秒前
Lucas应助自然天真采纳,获得10
12秒前
14秒前
14秒前
shi完成签到,获得积分10
14秒前
q6157发布了新的文献求助10
15秒前
希望天下0贩的0应助XIEMIN采纳,获得10
15秒前
orixero应助duoduo采纳,获得10
15秒前
16秒前
大模型应助虚拟的画板采纳,获得10
17秒前
18秒前
18秒前
18秒前
孤独幻枫发布了新的文献求助10
18秒前
善学以致用应助东方天奇采纳,获得10
19秒前
19秒前
留胡子的裘完成签到 ,获得积分10
20秒前
20秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 3000
Digital Twins of Advanced Materials Processing 2000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6041258
求助须知:如何正确求助?哪些是违规求助? 7780313
关于积分的说明 16233688
捐赠科研通 5187272
什么是DOI,文献DOI怎么找? 2775741
邀请新用户注册赠送积分活动 1758854
关于科研通互助平台的介绍 1642332