Publication: The construction of urban cultural and creative industries using deep learning and information management
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Issued Date
2024-07-15
Resource Type
ISSN
24058440
Scopus ID
2-s2.0-85197494472
Journal Title
Heliyon
Volume
10
Issue
13
Rights Holder(s)
SCOPUS
Bibliographic Citation
Heliyon Vol.10 No.13 (2024)
Suggested Citation
Zhao Z., Garcia-Campayo J., Liang J., Pu R., Perez H.M., Xue X., Borao L., Li H., Masanda A.B., Chen J., Portugal L.M., Aganan J.B. The construction of urban cultural and creative industries using deep learning and information management. Heliyon Vol.10 No.13 (2024). doi:10.1016/j.heliyon.2024.e33787 Retrieved from: https://hdl.handle.net/20.500.14740/20255
Author's Affiliation
Lyceum of the Philippines University Batangas
University of Chinese Academy of Social Sciences
Sichuan University of Media and Communications
National University, Philippines
University of Santo Tomas, Manila
Yonsei University
Universidad de Zaragoza
Fudan University
The Catholic University of Korea
Srinakharinwirot University
University of San Miguel
The International Institute of Computing and Societal Education University
Xiamen Institute of Technology
Professional Regulation Commission
University of Chinese Academy of Social Sciences
Sichuan University of Media and Communications
National University, Philippines
University of Santo Tomas, Manila
Yonsei University
Universidad de Zaragoza
Fudan University
The Catholic University of Korea
Srinakharinwirot University
University of San Miguel
The International Institute of Computing and Societal Education University
Xiamen Institute of Technology
Professional Regulation Commission
Corresponding Author(s)
Other Contributor(s)
Abstract
The ongoing transition within the Chinese economy assumes a pivotal role in shaping the landscape of the cultural and creative industries (CCI). Renowned for its environmentally sustainable attributes, coupled with high productivity, CCI has garnered considerable attention across diverse societal strata. This study endeavors to delineate the determinants influencing the developmental trajectory of CCI, with a focal point on City A as the primary subject of investigation, juxtaposed against Cities G, D, B, H, and X for comparative analysis, leveraging developmental data from the year 2021. Initially, the study elucidates the conceptual framework underpinning CCI and its intrinsic significance in facilitating urban metamorphosis. Subsequently, the positive impact of CCI through deep learning and information management technology is emphasized, and a cultural and creative recommendation model based on LSTM algorithm is constructed. Through performance evaluation, the recommendation accuracy for cultural and creative projects reaches 94.74 %. A robust developmental assessment model for CCI is then constructed via meticulous factor analysis of pertinent influencers. Employing factor analysis techniques, the study identifies two primary determinants exerting sway over CCI development: sustainable profitability factors and cultural influence factors. Noteworthy among the factors influencing CCI development within City A are fixed asset investment, cultural industry financing, the proliferation of university-based research institutions, and per capita cultural expenditure by residents. Of these, fixed asset investment, cultural industry financing, and the density of university research institutions prominently impinge upon sustainable profitability, with a discernible impact weight of 0.738 in the evaluative framework of CCI development, thus significantly shaping its trajectory. Moreover, consumer psychological factors, particularly market consumption patterns, are observed to exert a discernible influence on CCI evolution. This study augurs fresh insights into the realm of CCI development, infusing it with renewed vigor and vitality. Moreover, it underscores the inherent interdependence and positive correlation among the various research factors, offering novel perspectives and methodologies germane to the advancement of urban CCI.