Temporal-spatial Patterns and Mechanisms of Illegal Street Vending from the Social Sensing Perspective: A Comparison between Law-enforcement-reported and Resident-complained Events

Abstract

Street vendors play a crucial role in the urban informal economy, particularly in rapidly urbanizing third-world nations. Their presence provides employment, alleviates social pressures, and complements formal commerce. However, regulatory loopholes related to safety and hygiene, along with potential hazards such as traffic congestion, create conflicts between urban governance entities and street vendors. The informal economy’s significance to urban landscapes makes integrating street vendors while minimizing conflicts a key issue in urban planning. Limited data has hindered effective solutions for disorder in urban informal spaces. This study addresses this gap by examining the temporal-spatial distribution and underlying mechanisms of unauthorized street vending in Beijing’s Fengtai District in 2022. Using records of street vending infractions from municipal enforcement agencies and complaints from residents via the “12345” platform, this research employs statistical methods and machine learning models to analyze disparities in the perception of street vending activities between urban managers and residents. The findings enhance theoretical understanding and offer a bottom-up approach for governance practices, contributing to more humane and sustainable urban planning and governance.