Digitalization era: Investigating the spatial interplay between cyber human activity and economy with a hierarchical framework

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The development of Information and Communication Technology has shifted human activity from offline to online, and promoted digital economy. These changes challenge traditional methodologies relying on physical human activity as a micro-level reflection of the macro-level economy. To address this, a hierarchical framework is proposed to characterize cyber human activity, incorporating activity diversity, size, and preference. Then, Ordinary Least Squares and Geographically Weighted Regression models are used to examine the spatial interplay between cyber human activity and township-level economy. K-Medoids clustering is further applied to coefficients in cyber GWR model to reveal mechanisms influencing local economies. Taking diverse geospatial data in Jilin Province, China as an example, the result indicates that the significant extreme values of cyber human activity have divided Jilin Province into four subregions, closely aligning with local economic segmentation. Moreover, the local economy can be better reflected by cyber human activity rather than physical ones, especially in highly digitized regions. Furthermore, the regions with similar influence mechanisms cluster geographically. These clusters are categorized into three types, namely, dynamics, robust, and balanced, representing different mechanisms influencing the local economy. Practical and theoretical implications are discussed, including using cyber human activity in assessing the economy and implementing adaptable economic policies at township level.