地理科学进展 ›› 2018, Vol. 37 ›› Issue (9): 1277-1290.doi: 10.18306/dlkxjz.2018.09.010

• 研究论文 • 上一篇    下一篇

大城市通勤方式与职住失衡的相互关系

申犁帆1(), 张纯2,*(), 李赫3, 王烨4   

  1. 1. 武汉大学城市设计学院, 武汉 430072
    2. 北京交通大学建筑与艺术学院, 北京 100044
    3. 中国银行国际金融研究所, 北京 100818
    4. 广州市城市规划勘测设计研究院, 广州 510030
  • 收稿日期:2018-01-09 修回日期:2018-06-02 出版日期:2018-09-28 发布日期:2018-09-28
  • 通讯作者: 张纯 E-mail:495062785@foxmail.com;zhangc@bjtu.edu.cn
  • 作者简介:

    作者简介:申犁帆(1987-),男,北京人,博士研究生,研究方向为城市轨道交通与空间规划、城市可持续发展,E-mail: 495062785@foxmail.com

  • 基金资助:
    国家自然科学基金项目(51678029,51778039);中国城市轨道交通协会专项研究项目(A17M00080)

Interaction between commuting modes and job-housing imbalance in metropolis: An empirical study by Bayesian-tobit analysis in Beijing

Lifan SHEN1(), Chun ZHANG2,*(), He LI3, Ye WANG4   

  1. 1. School of Urban Design, Wuhan University, Wuhan 430072, China
    2. School of Architecture and Design, Beijing Jiaotong University, Beijing 100044, China
    3. International Finance Institute, Bank of China, Beijing 100818, China
    4. Guangzhou Planning & Design Survey Research Institute, Guangzhou 510030, China;
  • Received:2018-01-09 Revised:2018-06-02 Online:2018-09-28 Published:2018-09-28
  • Contact: Chun ZHANG E-mail:495062785@foxmail.com;zhangc@bjtu.edu.cn
  • Supported by:
    National Natural Science Foundation of China, No. 51678029, No. 51778039;Specific Research Project of China Urban Rail Transit Association, No. A17M00080

摘要:

随着城市的扩张,人们的就业—居住空间跨度不断扩大。通勤方式的多样化和通勤效率的提高会对就业者的职住状况产生影响。以通勤时间作为通勤成本能从就业者的角度辨析个体的职住失衡状况。本文基于贝叶斯-tobit的统计分析方法,结合北京市7个街道和地区的问卷调查数据,分析了慢行交通、机动车、轨道交通、地面公交等4种通勤方式与职住失衡的相互关系。同时,引入就业可达性和用地混合度作为调节变量,考察其对不同通勤方式与职住失衡之间原有关系的影响。研究发现:①慢行交通的通勤方式与职住失衡程度存在负相关性;②机动车、轨道交通和地面公交的通勤方式与职住失衡程度存在正相关性;③就业可达性和用地混合度会弱化慢行交通、轨道交通、地面公交通勤方式与职住失衡程度的原有关系,即在低就业可达性和用地混合度条件下,慢行交通通勤者的职住失衡度更低,而轨道交通和地面公交通勤者的职住失衡度更高;④就业可达性和用地混合度的差异对机动车通勤与职住失衡之间的关系没有影响。上述结果表明:低就业可达性和用地混合度能够缓解慢行交通通勤者的职住失衡程度;但对于轨道交通和地面公交的通勤者来说,低就业可达性和用地混合度会加剧其职住失衡的程度。此外,机动车通勤者不易受外部客观因素的影响而改变出行方式。

关键词: 通勤方式, 职住失衡, 就业可达性, 用地混合度, 贝叶斯-tobit, 北京

Abstract:

The spatial span of residents' job-housing places is increasingly expanded with urban sprawl. The diversity of commuting modes and improvement of commuting efficiency will affect commuters' previous job-housing imbalance. Commuting time as cost of commuting will contribute to better analyzing job-housing condition from commuters' perspective. Based on the statistical method of Bayesian-tobit and individual survey data of 7 sub-districts in Beijing, this study examined the interaction between four kinds of commuting modes (slow traffic, automobile, urban rail transit, and bus) and job-housing imbalance. Meanwhile, this study set employment accessibility and land use mix as moderator variables and explored their impacts on the relationship between varies commuting modes and job-housing imbalance. The study findings indicate that: (1) There is a negative relationship between commuting mode of slow traffic and job-housing imbalance. (2) By contrast, there is a positive dependency among automobile, urban rail transit, and bus and job-housing imbalance. (3) Employment accessibility and land use mix would weaken the original relationship among slow traffic, urban rail transit, and bus and job-housing imbalance. Specifically, under relatively low employment accessibility and land use mix conditions, the job-housing imbalance degree of slow traffic commuters is lower, while the job-housing imbalance degree of urban rail transit and bus commuters is higher. (4) Nevertheless, the relationship between commuting modes and job-housing imbalance will not be affected by employment accessibility and land use mix. These results suggest that (1) worse condition of employment accessibility and land use mixt can alleviate jobs-housing imbalance of commuters who use slow traffic. (2) However, lower value of employment accessibility and land use mix degree will aggravate job-housing imbalance of commuters. (3) In addition, the commuting behavior of automobile users will not be easily influenced by external factors.

Key words: commuting modes, job-housing imbalance, employment accessibility, land use mix, Bayesian-tobit, Beijing