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Decoding the Multidimensional Structuring of Urban Poles of Growth of Nighttime Economics—An Inter-Discipline Study in Lanzhou City, China, Based on Geomodeling and Big Data

Author

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  • Wenbo Hu

    (School of Communication and Information Engineering, Institute of Smart City, Shanghai University, Shanghai 200444, China)

  • Huiyu Wu

    (School of Sociology and Ethnology, University of Chinese Academy of Social Sciences, Beijing 100102, China)

  • Wanggen Wan

    (School of Communication and Information Engineering, Institute of Smart City, Shanghai University, Shanghai 200444, China)

Abstract

The nighttime economy, or NTE—the combination of nocturnal specialties and the extension of the diurnal economy into the night—has been implemented as an effective boosting instrument set to “revitalize the urban space”. The instrument, applied in regions around world, develops new socioeconomic dynamics and poles of growth within cities. Although some cases emphasize the functional success of NTE practices, disequilibrium between urban elements—social groups, communities, and the cultures in which they live—are ongoing. The present article argues that urban nights must be considered within a broader reflection on the question of sustainability because a closer integration between brands, cultural elements, employment, and capital in different scales is demonstrated at night. Based on growth pole theory, this study combines data mining, spatial modeling, and other complementary approaches, and successfully (1) identifies the growth poles of the NTE in Lanzhou City, a postindustrial city transitioning towards a nighttime economy that forms dotted and non-uniform nocturnal zones through its geography and demography; (2) characterizes their socioeconomic organization, and (3) analyzes various causes and manifestations of the disequilibrium.

Suggested Citation

  • Wenbo Hu & Huiyu Wu & Wanggen Wan, 2022. "Decoding the Multidimensional Structuring of Urban Poles of Growth of Nighttime Economics—An Inter-Discipline Study in Lanzhou City, China, Based on Geomodeling and Big Data," Sustainability, MDPI, vol. 15(1), pages 1-16, December.
  • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:245-:d:1013131
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    References listed on IDEAS

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