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作者

Jiangping Zhou;Yuling Yang;Hanxi Ma;Ying Li

来源

CITIES,Vol.97,Issue1,Article 102495

语言

英文

关键字

Familiar stranger;Big data era;Implications;Odds;Distribution;Beijing

作者单位

Department of Urban Planning and Design, Faculty of Architecture, The University of Hong Kong, Hong Kong SAR, China;Tsinghua Tongheng Urban Planning and Design Institute, Beijing, China;Department of Urban Planning and Design, Faculty of Architecture, The University of Hong Kong, Hong Kong SAR, China;Tsinghua Tongheng Urban Planning and Design Institute, Beijing, China

摘要

Traditionally, familiar strangers are defined as those we encounter and observe repeatedly in the city but never interact with. They are common to most urban dwellers. They also have various socioeconomic, sociopsychological and public-policy implications, which have only been sporadically mentioned and/or examined in existing studies across different disciplines. In this manuscript, we first summarize fragmental existing studies on familiar strangers that are defined in the traditional manner based on “small data” such as survey responses. Then we reconceptualize “familiar strangers” against the backdrop of the emergence and increased availability of big and open data. Such familiar strangers are called “familiar strangers in the big data era” (FSiBDE). After this, we have done the following: (a) synthesized and hypothesized factors influencing the distribution and quantity of the FSiBDE; (b) conducted an empirical study in the context of Beijing to embody and operationalize a special type of the FSiBDE among metro riders and to study its possible influencers. We find that across metro stations, it is spatial structure, population distribution, and transport network that significantly influence the count and odds of FSiBDE among millions of metro riders. In addition, the FSiBDE also can have important policy and planning implications for operating metro services and managing metro station.