jismart2023007: The Relationship between Spatial Aggregation of Occupational Diversity and Different Types of Occupational Burnout in Shenzhen City: Implications for Urban Planning

Abstract

Shenzhen, a leading coastal city and innovation hub in China, is characterized by its unique urban development. Simultaneously, the city's high-intensity work environment has given rise to various manifestations of occupational burnout among professionals from diverse sectors. This paper employs the K-means algorithm to discern and classify Point of Interest (POI) data extracted from workplaces across Shenzhen. The study amalgamates distinct zones, including economic special zones, high-tech industrial parks, industrial clusters, free trade zones, and government office districts, aiming to comprehensively investigate the spatial aggregation of diverse occupational categories within the urban fabric. Leveraging QGIS for the visual analysis of the collated data, it unveils the spatial distribution patterns and interrelationships among these areas. Furthermore, this research delves into the intricate correlation between urban planning-driven spatial layouts and occupational burnout. It concludes by offering recommendations for the creation of work environments tailored to spatial considerations, with the objective of fostering a positive and productive urban workforce.