Decision models of emission reduction considering CSR under reward-penalty policy

激励 利润(经济学) 企业社会责任 偏爱 社会福利 福利 业务 经济盈余 惩罚(心理学) 微观经济学 经济 公共经济学 产业组织 营销 市场经济 公共关系 社会心理学 法学 政治学 心理学
作者
Yang Wang,Chen Xiu-ling,Xideng Zhou
出处
期刊:PLOS ONE [Public Library of Science]
卷期号:18 (7): e0285895-e0285895
标识
DOI:10.1371/journal.pone.0285895
摘要

For the two emission reduction technologies of clean process (CT Mode) and end-of-pipe pollution control technology (ET Mode), this paper constructs production and low-carbon R&D decision-making models considering consumers’ green preference, and discusses the impact of social responsibility on firm’s decision-making, profit and social welfare. Then, the difference of optimal decision, profit and social welfare is analyzed when the firm adopt two emission reduction technologies with or without reward-penalty policy. The main conclusions of this paper are as follows: (1) Whether using clean process technology or end-of-pipe pollution control technology, consumers’ green preference behavior can increase corporate profit. When consumers’ green preference is small, consumers’ green preference is negatively correlated with social welfare. When consumers’ green preference is large, consumers’ green preference is positively correlated with social welfare. (2) Corporate social responsibility is conducive to improving the level of social welfare, not conducive to the increase of corporate profits. (3) When the reward and punishment intensity is small, the reward-penalty policy cannot effectively motivate the firm to assume social responsibility. Only when the reward and punishment reaches a certain level, the mechanism can have an incentive effect on the firm, and the government can actively implement the mechanism. (4) When the market scale is small, the adoption of end-of-pipe pollution control technology is more beneficial to the firm; When the market scale is large, it is beneficial for the firm to adopt clean technology. (5) If the efficiency of end-of-pipe pollution control and emission reduction is much higher than that of clean process, the firm should choose end-of-pipe pollution control technology, otherwise choose clean process.

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
jinjin发布了新的文献求助20
刚刚
1秒前
1秒前
syy080837发布了新的文献求助10
1秒前
aaa发布了新的文献求助20
2秒前
沉静傲霜发布了新的文献求助10
2秒前
健康的不愁完成签到 ,获得积分20
3秒前
zmin发布了新的文献求助10
3秒前
4秒前
4秒前
4秒前
vincent完成签到,获得积分10
4秒前
秦长春发布了新的文献求助10
5秒前
量子星尘发布了新的文献求助10
5秒前
无花果应助激动的曼雁采纳,获得10
5秒前
SSScoups完成签到,获得积分10
6秒前
在水一方应助emmaguo713采纳,获得10
6秒前
平淡的白云完成签到,获得积分10
6秒前
斯文败类应助晞嘻采纳,获得10
6秒前
明亮寒安完成签到,获得积分10
7秒前
7秒前
弥漫的橘发布了新的文献求助20
7秒前
8秒前
Sega完成签到,获得积分10
8秒前
廊桥遗梦发布了新的文献求助10
8秒前
sss完成签到 ,获得积分10
9秒前
英俊的铭应助小华采纳,获得10
9秒前
anubisi发布了新的文献求助30
10秒前
10秒前
流萤发布了新的文献求助10
10秒前
GCY发布了新的文献求助20
10秒前
田彬杰发布了新的文献求助10
11秒前
11秒前
11秒前
杜思淇完成签到,获得积分10
11秒前
kk发布了新的文献求助10
13秒前
Omni发布了新的文献求助10
13秒前
13秒前
Xman完成签到,获得积分10
14秒前
14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
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Exploring Nostalgia 500
Natural Product Extraction: Principles and Applications 500
Exosomes Pipeline Insight, 2025 500
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 500
Advanced Memory Technology: Functional Materials and Devices 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5667969
求助须知:如何正确求助?哪些是违规求助? 4888527
关于积分的说明 15122487
捐赠科研通 4826782
什么是DOI,文献DOI怎么找? 2584295
邀请新用户注册赠送积分活动 1538188
关于科研通互助平台的介绍 1496482