421 / 2019-02-27 15:58:56

The Inter-generational Effects of Job-housing Relationship Optimization based on Excess Commuting: A Case Study of Beijing and Shanghai

job-housing relationship,excess commuting,age,mobile phone grid data,Beijing,Shanghai

全体主题 > Big data in Urban Planning and Management

1. Introduction
Job-housing relationship has long been an important issue in urban planning which is mostly evaluated through commuting. In this topic, excess commuting is a well-accepted concept to measure commuting efficiency, which refers to the disparity between the actual commuting and the theoretically optimal commuting under a given urban structure(Ma and Banister, 2006).
However, studies on excess commuting are still scarce in China. The international literatures on excess commuting in the perspective of age are even scarcer. The mismatch between spatial structure of population age and urban functional structure, like aging in city center, has been witnessed in large cities in China(周婕, 2014), causing “wasteful commuting”. The purpose of this study is to explore better inter-generational job-housing relationships for the two largest cities of China, Beijing and Shanghai.

2. Data and Methodology
Data:
Mobile phone grid data is used in this study. It is basically derived from the cellular signaling data of China Unicom and geo-labeled using a point grid of 500-meters spacing. The data recorded the subscribers’ spatial-temporal information in September 2017, from which their residences and frequent travel destinations (FTD) were inferred. Over one million subscribers for each city were extracted from the data as samples based on the criterion that they should show up over 28 days (namely local residents). Using the subscribers’ age information, we divided the samples into three age groups: the youth (age of 19-39), the middle age (age of 40-59) and the elderly (age over 60).
Methodology:
The Euclidean distance between a subscriber’s residence and FTD is used as the commuting distance, a core indicator of the person’s job-housing relationship. Kernel Density Estimation is applied to characterize the spatial distributions. Excess commuting is estimated by recursively simulating any two subscribers exchanging their residences on condition that both of their commuting distances are shorter until no improvement is possible. This individual-based approach avoids the MAUP problem in the conventional linear programming approaches based on aggregate OD data (Niedzielski et al., 2013; White, 1988), and uses a significantly larger sample with actual individual behavior (Hu and Wang, 2015).

3. Results
Present job-housing relationship:
Age-specific commuting distance distributions of the two cites show similar features (figure1): with aging of the people, the median distances decline in general, with the peak at the 30-39 group.
As for the spatial distributions (figure 2 & figure 3), the residences are more dispersed than the FTDs. Most of the elderly live in the central cities, while the young people live in the widest areas.
Optimization of the job-housing relationship:
The excess commuting is 64% for Beijing and 69% for Shanghai with 93% and 96% of the sample subscribers exchanged their residences. Accordingly, the young people move to the central cities, and the middle age and the elderly move out (figure 4).

4. Conclusion
Beijing and Shanghai exhibit many commons in the inter-generational job-housing relationships.
(1) The current relationships become better with the age increasing.
(2) The benefits of optimizing the job-housing relationships are considerable. Most of the population will be involved with significantly decreased commuting distances and more balanced age distributions in space. Young people will be the biggest beneficiaries.

Reference:
Hu Y, Wang F, 2015, "Decomposing excess commuting: A Monte Carlo simulation approach" Journal of Transport Geography 44 43-52
Ma K R, Banister D, 2006, "Excess commuting: a critical review" TRANSPORT REVIEWS 26 749-767
Niedzielski M A, Horner M W, Xiao N, 2013, "Analyzing scale independence in jobs-housing and commute efficiency metrics" Transportation Research Part A 58 129-143
White M J, 1988, "Urban commuting journeys are not "wasteful"" JOURNAL OF POLITICAL ECONOMY 96 1097-1110
Zhou J, 2014, "Spatial distribution characteristics and evolution trends of urban elderly population" City Planning Review 38 18-25