Synergies and trade‐offs across sustainable development goals: A novel method incorporating indirect interactions analysis

可持续发展 公司治理 包裹体(矿物) 计算机科学 环境经济学 管理科学 风险分析(工程) 业务 经济 政治学 心理学 财务 社会心理学 法学
作者
Huijuan Xiao,Yue Liu,Jingzheng Ren
出处
期刊:Sustainable Development [Wiley]
卷期号:31 (2): 1135-1148 被引量:39
标识
DOI:10.1002/sd.2446
摘要

Abstract The sustainable development goals (SDGs) are presented as significantly interacted. Yet most studies only investigated the direct interactions of SDG targets, and indirect interactions, that is, the interlinkages transmitted through one or more mediums, should also be considered to obtain more accurate interaction estimation and more scientific policy decisions. We first made a methodological contribution by proposing a plus‐minus decision‐making trial and evaluation laboratory model, which can consider not only the direct synergies and trade‐offs but the indirect ones. Then, based on this proposed method, we navigated the complicated network across the SDGs considering both direct and indirect interactions, find out the key interactive ones with a visually directed graph, obtain the weights of each SDG, and define the best governance structures to capitalize on synergies and minimize trade‐offs. Results show that, when incorporating indirect interactions, the share of synergy effect of SDGs dominates the total influence, taking up to 98.33%, suggesting that the achievement of the 2030 Agenda can be facilitated through interactions. Although all SDGs should be equally addressed by 2030 suggested by the United Nations, equal importance across 17 SDGs does not mean we have to make the same efforts in achieving each SDG, and SDG 4 and SDG 13 are the top priority to tap into these interaction potentials. Our interdisciplinary analysis across economic growth, social inclusion, and environmental protection provides a science‐driven reference for all UN member states to facilitate achieving the SDGs by maximizing the synergies and minimizing the trade‐offs.
最长约 10秒,即可获得该文献文件

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
chen01hang应助我不是BOB采纳,获得50
1秒前
李健应助彬彬发文章采纳,获得10
1秒前
Honahlee完成签到,获得积分10
1秒前
马明旋发布了新的文献求助20
2秒前
2秒前
3秒前
852应助strongfrog采纳,获得10
3秒前
科研通AI6应助清秀送终采纳,获得10
4秒前
4秒前
4秒前
4秒前
CipherSage应助TearMarks采纳,获得10
4秒前
silin完成签到,获得积分10
4秒前
小豆包完成签到,获得积分20
5秒前
xttju2014发布了新的文献求助10
5秒前
5秒前
super完成签到,获得积分20
6秒前
6秒前
Ak完成签到,获得积分0
6秒前
田小班发布了新的文献求助10
7秒前
Irene发布了新的文献求助10
7秒前
认真日记本完成签到 ,获得积分10
7秒前
www发布了新的文献求助10
7秒前
8秒前
桐桐应助哈哈哈哈哈哈采纳,获得10
8秒前
李小莉0419发布了新的文献求助10
8秒前
Ava应助MC采纳,获得10
9秒前
baobaot发布了新的文献求助30
9秒前
9秒前
承乐应助小豆包采纳,获得10
9秒前
英姑应助小豆包采纳,获得10
9秒前
秋寒完成签到,获得积分10
10秒前
量子星尘发布了新的文献求助10
10秒前
斯文败类应助mikiisme采纳,获得10
11秒前
algain完成签到,获得积分10
11秒前
Wizzzzzzzy发布了新的文献求助10
11秒前
necos发布了新的文献求助10
14秒前
14秒前
15秒前
fmx完成签到,获得积分10
15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
Basic And Clinical Science Course 2025-2026 3000
Encyclopedia of Agriculture and Food Systems Third Edition 2000
人脑智能与人工智能 1000
花の香りの秘密―遺伝子情報から機能性まで 800
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
Pharmacology for Chemists: Drug Discovery in Context 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 5608407
求助须知:如何正确求助?哪些是违规求助? 4693040
关于积分的说明 14876313
捐赠科研通 4717445
什么是DOI,文献DOI怎么找? 2544206
邀请新用户注册赠送积分活动 1509230
关于科研通互助平台的介绍 1472836