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In this context, as a new office model that uses shared office space to reduce rental costs and improve space resource utilization, the co-working space (CWS) caters to many small and medium-sized enterprises with its low price, flexible lease period, and intense community atmosphere.
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At the same time, the development of the sharing economy and the knowledge-based economy has also significantly changed people’s lifestyles and work styles, leading to a continuous increase in the proportion of decentralized, mobile, and independent laborers. Its development has not effectively integrated the market’s idle resources, improving the overall utilization of resources, dramatically reducing transaction costs, and fostering new economic forms and consumption concepts, covering areas involving transportation, urban housing, tourism, leisure, and green energy. With the development of technologies such as the mobile internet, the internet of things, and big data, the sharing economy, as a new collaborative economy that maximizes value, has gradually replaced the old and closed capital model. We hope that the research can be used to provide a scientific basis for the rational planning and development guidance of CWSs. The cost of rent has the most negligible impact on site selection, and its weight is only 0.0195. The order of importance of other influencing factors is the convenience of life (0.3147), business atmosphere (0.1352), and traffic conditions (0.1171). Our conclusions are as follows: (1) CWSs in Hangzhou generally present a multi-center distribution pattern (2) based on the different degrees of dependence of the target customer groups on resources such as commerce, capital, and information, the factor that has the most significant impact on the site of CWSs is the regional innovation environment, and its weight is 0.3941. We then conducted an empirical study to reveal the influence mechanism behind different factors. From the perspectives of traffic accessibility, business atmosphere, innovation environment, living convenience, and rental cost, we innovatively constructed an indicator system of factors affecting site selection of CWSs. Taking Hangzhou as a case study, this paper uses big data analysis technologies including Python and ArcGIS to reveal the distribution characteristics of CWSs. This not only innovates the traditional office model, but also helps to realize the efficient utilization of office buildings and the sustainable development of office spaces. Co-working spaces (CWSs) have gradually become a new form of spatial economic activity in large cities in China.