Spatial mismatch for distinct socioeconomic groups in Xiamen, China

IF 1.6 4区 工程技术 Q4 TRANSPORTATION
Yongling Li, S. Geertman, Yanliu Lin, P. Hooimeijer, W. Xu, Jie Huang
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引用次数: 3

Abstract

Studies have found that spatial mismatch is a universal phenomenon, although both their substantive and methodological focus can differ substantially. In China, there is a growing body of literature on spatial mismatch, but few studies have measured the degree of spatial mismatch between local and migrant workers in different occupations. To fill this gap, this research investigates the spatial mismatch for different socioeconomic groups in Xiamen according to their “hukou” status and occupation. As one of the country’s first four special economic zones, Xiamen achieved housing marketization earlier than most other Chinese cities, attracting a large amount of capital and migrants, and shaping different spatial patterns of local workers and migrant workers. The findings show that blue-collar, pink-collar, and white-collar workers, who are further categorized as either locals or migrants, experience varying degrees of job accessibility and spatial mismatch. In addition, even though migrant workers experience less spatial mismatch, they still have disadvantages in terms of commuting time due to their travel mode. The results presented in this paper are helpful for understanding the spatial mismatch for various social groups and facilitating sustainable mobility and social equity.
厦门不同社会经济群体的空间错配
研究发现,空间不匹配是一种普遍现象,尽管它们的实质性和方法论重点可能有很大不同。在中国,关于空间不匹配的文献越来越多,但很少有研究衡量不同职业的本地工人和农民工之间的空间不匹配程度。为了填补这一空白,本研究根据厦门不同社会经济群体的“户口”地位和职业,调查了他们的空间错配。作为中国首批四大经济特区之一,厦门比中国其他大多数城市更早实现了住房市场化,吸引了大量资本和移民,形成了当地工人和移民工人不同的空间格局。研究结果显示,蓝领、粉领和白领,进一步被归类为本地人或移民,经历了不同程度的工作可及性和空间不匹配。此外,尽管农民工经历的空间不匹配较少,但由于他们的出行方式,他们在通勤时间方面仍然存在劣势。本文的研究结果有助于理解不同社会群体的空间错配,促进可持续流动和社会公平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.40
自引率
5.30%
发文量
34
审稿时长
30 weeks
期刊介绍: The Journal of Transport and Land Usepublishes original interdisciplinary papers on the interaction of transport and land use. Domains include: engineering, planning, modeling, behavior, economics, geography, regional science, sociology, architecture and design, network science, and complex systems. Papers reporting innovative methodologies, original data, and new empirical findings are especially encouraged.
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