地理学报 ›› 2020, Vol. 75 ›› Issue (10): 2192-2205.doi: 10.11821/dlxb202010011

• 城市与区域发展 • 上一篇    下一篇

上海职住优化效应的代际差异

朱玮1(), 梁雪媚1, 桂朝2, 冯永恒2, 闫嘉2   

  1. 1.同济大学建筑与城市规划学院,上海 200092
    2.智慧足迹数据科技有限公司,北京 100031
  • 收稿日期:2019-01-21 修回日期:2020-02-28 出版日期:2020-10-25 发布日期:2020-12-25
  • 作者简介:朱玮(1978-), 男, 上海人, 博士, 副教授, 博士生导师, 研究方向为城乡规划方法与技术。E-mail: weizhu@tongji.edu.cn
  • 基金资助:
    国家自然科学基金项目(41771168)

The inter-generational differences in the effects of job-housing optimization in Shanghai

ZHU Wei1(), LIANG Xuemei1, GUI Zhao2, FENG Yongheng2, YAN Jia2   

  1. 1. College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
    2. Smart Steps Digital Technology Co. Ltd., Beijing 100031, China
  • Received:2019-01-21 Revised:2020-02-28 Published:2020-10-25 Online:2020-12-25
  • Supported by:
    National Natural Science Foundation of China(41771168)

摘要:

城市的职住关系一直为研究者广泛关注。过剩通勤概念以实际通勤与理论最短通勤的差距反映城市职住关系与通勤状态,是衡量通勤效率和优化潜力的常用指标。国内的过剩通勤研究数量有限,且鲜有从年龄视角考察。本文利用2017年9月上海市手机网格数据,分析不同年龄段居民的职住与通勤状态,采用模拟个人换居的方法测度过剩通勤,并探讨职住关系优化效应的代际差异。结果表明:上海居民的职住关系存在明显的代际差异,青年人是劣势群体,老年人是优势群体,中年人介于其间;上海全市过剩通勤率为69%,职住关系优化的潜力和效应巨大,可使得通勤距离显著减少,代际分异缓和,青年人的获得感最大,城市年龄空间结构更加均衡。提出上海的空间规划和政策应以理想的城市年龄空间结构为目标,以提高人的居住和就业空间的流动性、青年化城市中心、中老年化城市外围为途径。

关键词: 职住关系, 过剩通勤, 年龄, 手机网格数据, 上海

Abstract:

Job-housing relationship in city has always been a concern of scholars. Excess commuting is a well-accepted concept for evaluating commuting efficiency and potential of optimizing it. By calculating difference between observed commute and theoretical minimum commute, excess commuting can measure to what extent the commute of a city is wasted. Studies on excess commuting are rather scarce in China, especially in perspective of different age groups. Using the mobile phone grid data in September 2017 in Shanghai, this paper analyzes the residential locations, job locations, and commuting distances of three age groups, namely, the young, the middle and the old. To calculate their excess commuting, a modified algorithm is devised, simulating individuals exchanging their residences based on the principle of Pareto Optimality, so that no one has to sacrifice their status quo. The new method also uses large-scale individual data instead of small-scale aggregate origin-destination data adopted in the traditional linear programming method. The job-housing relationships under the optimal commuting are estimated and compared between age groups. The results show that: (1) There is an evident inter-generational differentiation in the job-housing relationships. The young people are the disadvantaged group with the longest commute distances and the farthest residence locations from the city center; the elderly are the dominant group with the shortest commute distances and the closest residence locations from the city center; the middle-aged are in-between. (2) The excess commuting rate in Shanghai is 69%, indicating a large potential in optimizing the job-housing relationships. (3) The benefits of the optimization are immense: the average commuting distance declines, the inter-generational differentiation moderates, and the spatial structure of population age becomes more balanced. (4) The young group will benefit most from this process. It is suggested that the spatial planning and policy making of Shanghai should set a target for an ideal spatial structure of the urban population age, so as to increase the fluidity of the job and housing spaces, youthen the city center, and make the perimeter areas more livable for the middle-age and old people.

Key words: job-housing relationship, excess commuting, age, mobile phone grid data, Shanghai