Research on the Spatial Distribution and Influencing Factors of Digital Creative Industry—Take Shenzhen as an Example

In recent years, the digital creative industry has manifested a vigorous growth trend along with the continuous upgrading of the Internet and the leap of the national economy. This research identifies the spatial distribution characteristics of digital creative enterprises in Shenzhen, employs big d...

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Main Authors: Zhiyi Gan, Yan Zhang, Nengjun Chen, Ruipeng Li
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Proceedings
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Online Access:https://www.mdpi.com/2504-3900/110/1/26
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author Zhiyi Gan
Yan Zhang
Nengjun Chen
Ruipeng Li
author_facet Zhiyi Gan
Yan Zhang
Nengjun Chen
Ruipeng Li
author_sort Zhiyi Gan
collection DOAJ
description In recent years, the digital creative industry has manifested a vigorous growth trend along with the continuous upgrading of the Internet and the leap of the national economy. This research identifies the spatial distribution characteristics of digital creative enterprises in Shenzhen, employs big data of spatial information of various facilities such as transportation and commerce as the driving factor to construct a model, takes 1 km grid as the fundamental research unit, and explores the influence mechanism of enterprise location selection through methods like OLS and MGWR. The results are as follows: (1) The overall spatial distribution characteristics of digital creative industry are characterized by “widely distributed throughout the city, with a high concentration within the customs and a weak dispersion outside the customs”. (2) The factors of park foundation, production service, public service and life service exert a significant influence on the spatial distribution of digital creative industries in Shenzhen. Among them, the density of shopping facilities, staff, hotel and bus station exhibits a highly obvious spatial heterogeneity in terms of the influence on enterprise location. (3) The correlation of local scale factors is high and the influence range is precise, which frequently presents complex correlation outcomes in small scales such as streets or communities.
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spelling doaj-art-3bf9213cc36047f4b8fc27e4798a41632025-08-20T03:43:54ZengMDPI AGProceedings2504-39002024-12-0111012610.3390/proceedings2024110026Research on the Spatial Distribution and Influencing Factors of Digital Creative Industry—Take Shenzhen as an ExampleZhiyi Gan0Yan Zhang1Nengjun Chen2Ruipeng Li3School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, ChinaSchool of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, ChinaInstitute of Global Urban Civilization, Southern University of Science and Technology, Shenzhen 518055, ChinaSchool of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, ChinaIn recent years, the digital creative industry has manifested a vigorous growth trend along with the continuous upgrading of the Internet and the leap of the national economy. This research identifies the spatial distribution characteristics of digital creative enterprises in Shenzhen, employs big data of spatial information of various facilities such as transportation and commerce as the driving factor to construct a model, takes 1 km grid as the fundamental research unit, and explores the influence mechanism of enterprise location selection through methods like OLS and MGWR. The results are as follows: (1) The overall spatial distribution characteristics of digital creative industry are characterized by “widely distributed throughout the city, with a high concentration within the customs and a weak dispersion outside the customs”. (2) The factors of park foundation, production service, public service and life service exert a significant influence on the spatial distribution of digital creative industries in Shenzhen. Among them, the density of shopping facilities, staff, hotel and bus station exhibits a highly obvious spatial heterogeneity in terms of the influence on enterprise location. (3) The correlation of local scale factors is high and the influence range is precise, which frequently presents complex correlation outcomes in small scales such as streets or communities.https://www.mdpi.com/2504-3900/110/1/26digital creative industryspatial distribution patterninfluencing factorsgeographical weighted regressionShenzhen
spellingShingle Zhiyi Gan
Yan Zhang
Nengjun Chen
Ruipeng Li
Research on the Spatial Distribution and Influencing Factors of Digital Creative Industry—Take Shenzhen as an Example
Proceedings
digital creative industry
spatial distribution pattern
influencing factors
geographical weighted regression
Shenzhen
title Research on the Spatial Distribution and Influencing Factors of Digital Creative Industry—Take Shenzhen as an Example
title_full Research on the Spatial Distribution and Influencing Factors of Digital Creative Industry—Take Shenzhen as an Example
title_fullStr Research on the Spatial Distribution and Influencing Factors of Digital Creative Industry—Take Shenzhen as an Example
title_full_unstemmed Research on the Spatial Distribution and Influencing Factors of Digital Creative Industry—Take Shenzhen as an Example
title_short Research on the Spatial Distribution and Influencing Factors of Digital Creative Industry—Take Shenzhen as an Example
title_sort research on the spatial distribution and influencing factors of digital creative industry take shenzhen as an example
topic digital creative industry
spatial distribution pattern
influencing factors
geographical weighted regression
Shenzhen
url https://www.mdpi.com/2504-3900/110/1/26
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AT nengjunchen researchonthespatialdistributionandinfluencingfactorsofdigitalcreativeindustrytakeshenzhenasanexample
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