Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
School of Civil Engineering, University of Sydney, Sydney, NSW 2006, Australia.
Proc Natl Acad Sci U S A. 2018 Dec 11;115(50):12710-12715. doi: 10.1073/pnas.1815928115. Epub 2018 Nov 19.
Residential locations, the jobs-housing relationship, and commuting patterns are key elements to understand urban spatial structure and how city dwellers live. Their successive interaction is important for various fields including urban planning, transport, intraurban migration studies, and social science. However, understanding of the long-term trajectories of workplace and home location, and the resulting commuting patterns, is still limited due to lack of year-to-year data tracking individual behavior. With a 7-y transit smartcard dataset, this paper traces individual trajectories of residences and workplaces. Based on in-metro travel times before and after job and/or home moves, we find that 45 min is an inflection point where the behavioral preference changes. Commuters whose travel time exceeds the point prefer to shorten commutes via moves, while others with shorter commutes tend to increase travel time for better jobs and/or residences. Moreover, we capture four mobility groups: home mover, job hopper, job-and-residence switcher, and stayer. This paper studies how these groups trade off travel time and housing expenditure with their job and housing patterns. Stayers with high job and housing stability tend to be home (apartment unit) owners subject to middle- to high-income groups. Home movers work at places similar to stayers, while they may upgrade from tenancy to ownership. Switchers increase commute time as well as housing expenditure via job and home moves, as they pay for better residences and work farther from home. Job hoppers mainly reside in the suburbs, suffer from long commutes, change jobs frequently, and are likely to be low-income migrants.
居住地点、职住关系和通勤模式是理解城市空间结构和城市居民生活方式的关键要素。它们的连续互动对于城市规划、交通、城市内迁移研究和社会科学等各个领域都很重要。然而，由于缺乏逐年跟踪个人行为的数据，对工作场所和家庭位置的长期轨迹以及由此产生的通勤模式的理解仍然有限。本文利用 7 年的过境智能卡数据集，追踪个人的居住和工作地点轨迹。基于工作和/或家庭变动前后的市内旅行时间，我们发现 45 分钟是行为偏好变化的转折点。通勤时间超过该点的通勤者更愿意通过搬迁来缩短通勤时间，而其他通勤时间较短的人则更愿意增加通勤时间，以获得更好的工作和/或住所。此外，我们还捕捉到了四个流动群体：家庭搬迁者、工作变动者、工作和住所转换者和留守者。本文研究了这些群体如何在工作和住房模式方面权衡通勤时间和住房支出。留守者的工作和住房稳定性较高，往往是中高收入群体的自有住房业主。家庭搬迁者在与留守者类似的地方工作，而他们可能会从租赁转为拥有。转换者通过工作和家庭的搬迁增加通勤时间和住房支出，因为他们要支付更好的住所，并离家更远。工作变动者主要居住在郊区，通勤时间长，工作频繁变动，而且可能是低收入移民。
