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基于显示性偏好数据的航运承运人应对全球限硫令的选择偏好研究

白茜文 侯尧 杨冬

白茜文, 侯尧, 杨冬. 基于显示性偏好数据的航运承运人应对全球限硫令的选择偏好研究[J]. 交通运输工程学报, 2022, 22(1): 240-249. doi: 10.19818/j.cnki.1671-1637.2022.01.020
引用本文: 白茜文, 侯尧, 杨冬. 基于显示性偏好数据的航运承运人应对全球限硫令的选择偏好研究[J]. 交通运输工程学报, 2022, 22(1): 240-249. doi: 10.19818/j.cnki.1671-1637.2022.01.020
BAI Xi-wen, HOU Yao, YANG Dong. A study on shipowners' selection preferences in response to global sulfur restrictions based on revealed preference data[J]. Journal of Traffic and Transportation Engineering, 2022, 22(1): 240-249. doi: 10.19818/j.cnki.1671-1637.2022.01.020
Citation: BAI Xi-wen, HOU Yao, YANG Dong. A study on shipowners' selection preferences in response to global sulfur restrictions based on revealed preference data[J]. Journal of Traffic and Transportation Engineering, 2022, 22(1): 240-249. doi: 10.19818/j.cnki.1671-1637.2022.01.020

基于显示性偏好数据的航运承运人应对全球限硫令的选择偏好研究

doi: 10.19818/j.cnki.1671-1637.2022.01.020
基金项目: 

国家自然科学基金项目 72001123

国家自然科学基金项目 71971185

广东省基础与应用基础研究基金项目 2021A1515010699

详细信息
    作者简介:

    白茜文(1991-),女,山东济南人,清华大学助理教授,工学博士,从事航运经济与航运大数据研究

    通讯作者:

    杨冬(1980-),男,贵州贵阳人,香港理工大学助理教授,工学博士

  • 中图分类号: U6-9

A study on shipowners' selection preferences in response to global sulfur restrictions based on revealed preference data

Funds: 

National Natural Science Foundation of China 72001123

National Natural Science Foundation of China 71971185

Basic and Applied Basic Research Foundation of Guangdong Province 2021A1515010699

More Information
  • 摘要: 建立了一个基于显示性偏好数据的航运承运人减排方案决策建模框架,从实证角度研究了承运人的实际减硫方案选择机制;基于AIS数据和其他相关数据库,采用数据挖掘方法与计量经济模型,综合考虑船舶特征、承运人特征和外部市场情况等方面共11个因素,克服了已有文献关注经济因素、忽视非经济因素的局限,系统分析了限硫令下承运人的应对措施选择。研究结果表明:11个因素均有助于解释承运人的能源选择,但其影响程度各不相同;各因素的修正效应量排序依次为距离新规实行的年限(3.957)、载重吨位(2.270)、船龄(1.711)、公司规模(1.579)、每吨燃料价差(1.456)、运价指数(1.442)、环保意识指数(1.353)、航速(1.243)、航程(1.172)、排放控制区航行占比(1.127)、贸易路线固定程度(1.108);对于承运人的能源方案选择,距离新规实行的年限和载重吨位对承运人决策产生了非常重要的影响,修正效应量均大于2.0;船龄、公司规模、每吨燃料价差、运价指数和环保意识指数5个因素对于决策的影响程度适中,修正效应量为1.3~1.8;其余4个与承运人运营模式相关因素虽然对于决策有一定影响,但影响程度较小,其修正效应量均小于1.3。

     

  • 表  1  描述性统计

    Table  1.   Descriptive statistics

    因素 均值 标准差
    使用低硫燃料 安装脱硫塔 使用低硫燃料 安装脱硫塔
    船龄/年 11.205 8.475 6.607 4.013
    载重吨位/百万吨 0.076 0.132 0.061 0.073
    航速/kn 11.307 11.917 2.317 2.625
    航程/103km 2.374 2.935 1.487 1.538
    ECA中航行占比/% 0.098 0.130 0.262 0.291
    贸易路线固定程度 0.732 0.739 0.145 0.140
    公司规模 0.416 0.694 0.493 0.461
    环保意识指数 60.504 64.874 12.523 13.220
    每吨燃料价差/美元 211.158 207.380 32.845 25.401
    运价指数 1.327 1.179 0.395 0.397
    距离新规实行的年限 1.137 0.749 0.526 0.312
    下载: 导出CSV

    表  2  模型估计结果

    Table  2.   Model estimation results

    因素 模型1 模型2
    船龄/年 -0.094 3***
    (0.009 3)
    -0.097 7***
    (0.004 0)
    载重吨位/百万吨 8.30***
    (0.45)
    11.38***
    (0.31)
    航速/kn 0.046 5**
    (0.018 0)
    0.087 5***
    (0.008 6)
    航程/103 km 0.067 6**
    (0.028 3)
    0.103 5***
    (0.013 9)
    ECA中航行占比/% 0.311**
    (0.135)
    0.432***
    (0.067)
    贸易路线固定程度 0.441
    (0.277)
    0.716***
    (0.133)
    公司规模 0.882***
    (0.086)
    0.919***
    (0.038)
    环保意识指数 0.025 9***
    (0.003 1)
    0.023 1***
    (0.001 4)
    每吨燃料价差/美元 0.017 5***
    (0.001 8)
    0.012 9***
    (0.000 7)
    运价指数 -0.715***
    (0.095)
    -0.911***
    (0.046)
    距离新规实行的年限 -2.817***
    (0.124)
    -2.907***
    (0.054)
    常数项 -9.047***
    (0.532)
    -2.951***
    (0.232)
    观测数 216 331 20 000
    麦克法登可决系数 0.160 4 0.356 7
    预测正确率/% 99.68 78.88
    预测错误率/% 0.32 21.12
    总增益/% 0.00 28.68
    百分比增益/% 0.00 80.07
    AUC值 0.500 0.789
    下载: 导出CSV

    表  3  模型2中各因素的效应量与修正效应量

    Table  3.   Effect sizes and modified effect sizes of factors in model 2

    因素 标准差 效应量 修正效应量
    船龄/年 5.497 0.585 1.711
    载重吨位/百万吨 0.072 2.270 2.270
    航速/kn 2.489 1.243 1.243
    航程/103 km 1.532 1.172 1.172
    ECA中航行占比/% 0.277 1.127 1.127
    贸易路线固定程度 0.143 1.108 1.108
    公司规模 0.497 1.579 1.579
    环保意识指数 13.087 1.353 1.353
    每吨燃料价差/美元 29.252 1.456 1.456
    运价指数 0.402 0.694 1.442
    距离新规实行的年限 0.473 0.253 3.957
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-07-16
  • 刊出日期:  2022-02-25

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