已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Analysis of regional differences and evolution features for waterway transport efficiency in the Yangtze River Economic Belt considering undesired outputs

长江 环境科学 水资源管理 水文学(农业) 环境资源管理 地理 地质学 中国 岩土工程 考古
作者
Jun Zhu,Ying Zhao,Qiang Yang,Jun Jiang
出处
期刊:Ocean & Coastal Management [Elsevier BV]
卷期号:253: 107122-107122
标识
DOI:10.1016/j.ocecoaman.2024.107122
摘要

Waterway transport plays an increasingly important role in pursuing the sustainable development of the transportation industry and promoting regional economic development. Understanding the regional differences and evolution features of waterway transport efficiency (WTE) is a requisite for formulating waterway transport development policies. However, many studies of transport efficiency mainly focus on road, railway, and air transportation. Few studies have conducted an in-depth analysis of the WTE in the Yangtze River Economic Belt (YREB) from the perspective of considering undesired output. Adopting the Super slack-based measure (Super-SBM) model, Dagum Gini coefficient, and kernel density estimation as an analysis tool, this study explored the WTE's region disparities and dynamic evolution features based on the data from 2011 to 2020 in YREB. The analysis results represent that: (1) there represented a fluctuating and slowly upward trend of waterway transport efficiency during the study period. (2) The midstream region has the highest waterway transport efficiency, followed by the upstream region, and last is the downstream region. (3) The regional disparities in waterway transport efficiency exist in YREB, and the primary source of these differences is the inter-regional difference. And (4) the polarization phenomenon and agglomeration characteristics of waterway transport efficiency in YREB are gradually weakened and decreased, respectively. In the end, this article summarized the implications of this study to improve the waterway transport efficiency and service capabilities in YREB.

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
EurekaOvo发布了新的文献求助10
刚刚
Texas完成签到,获得积分10
3秒前
4秒前
大模型应助chen1314采纳,获得10
4秒前
zkkz完成签到,获得积分10
6秒前
MZY完成签到,获得积分20
7秒前
欣喜的人龙完成签到 ,获得积分10
8秒前
前进的光发布了新的文献求助10
9秒前
10秒前
13秒前
Makula完成签到,获得积分10
13秒前
qzp完成签到 ,获得积分10
14秒前
葡萄成熟时完成签到,获得积分10
14秒前
爱笑的鹿完成签到 ,获得积分10
15秒前
bkagyin应助zhang采纳,获得10
16秒前
17秒前
Accepted完成签到 ,获得积分10
18秒前
18秒前
背后艳完成签到 ,获得积分10
20秒前
铁臂阿童木完成签到,获得积分10
20秒前
chen1314发布了新的文献求助10
22秒前
jiyuan发布了新的文献求助10
22秒前
CodeCraft应助科研通管家采纳,获得10
24秒前
在水一方应助科研通管家采纳,获得10
24秒前
传奇3应助科研通管家采纳,获得80
24秒前
24秒前
24秒前
依桉完成签到 ,获得积分10
24秒前
嘻嘻哈哈发布了新的文献求助40
24秒前
木可完成签到,获得积分10
25秒前
26秒前
zhang完成签到,获得积分10
27秒前
31秒前
zhang发布了新的文献求助10
31秒前
32秒前
小二郎应助jiyuan采纳,获得10
32秒前
Makula发布了新的文献求助10
34秒前
35秒前
C2发布了新的文献求助10
37秒前
研友_VZG7GZ应助zoelir采纳,获得10
38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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1500
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Rheumatoid arthritis drugs market analysis North America, Europe, Asia, Rest of world (ROW)-US, UK, Germany, France, China-size and Forecast 2024-2028 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6366564
求助须知:如何正确求助?哪些是违规求助? 8180435
关于积分的说明 17245947
捐赠科研通 5421379
什么是DOI,文献DOI怎么找? 2868442
邀请新用户注册赠送积分活动 1845529
关于科研通互助平台的介绍 1693032