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Machine Learning-driven Analysis of Determinants Influencing Cooperative Development in Ho Chi Minh City under Digital Transformation.

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Název: Machine Learning-driven Analysis of Determinants Influencing Cooperative Development in Ho Chi Minh City under Digital Transformation.
Autoři: Tong, Quoc Bao, Nguyen, Minh Tuan, Le, Anh Tuan, Nguyen, Thuy-Van, Vu, Thuy-Vi, Pham, Minh-Tuan
Zdroj: International Journal on Advanced Science, Engineering & Information Technology; 2025, Vol. 15 Issue 4, p1213-1220, 8p
Témata: DIGITAL transformation, ECONOMIC development, MACHINE learning, CITIES & towns, SUSTAINABLE development, POLICY analysis, PREDICTION models, SHARING economy
Geografický termín: HO Chi Minh City (Vietnam), VIETNAM
Abstrakt: Developing the collective economy with the core of cooperatives is one of the four critical economic sectors in the market economy in Vietnam. The cooperative economic model operates effectively, contributing to sustainable economic development, building new rural areas, creating jobs, eliminating hunger, reducing poverty, and ensuring social security. This study employs advanced methods to identify and quantify the key factors influencing cooperative economic growth in Ho Chi Minh City, as the city undergoes digital transformation and initiatives aimed at making urban areas more sustainable. This study conducted a structured survey with 350 cooperative managers and members. Thereafter, a hybrid analytical framework that combined reliability assessment (Cronbach's Alpha), dimensionality reduction through Exploratory Factor Analysis (EFA), and predictive modelling through multivariate linear regression to process the data was employed. Regularization and model diagnostics were used to make the model stronger and less multicollinear. The adjusted R² value of the optimized regression model (0.676) showed that five meaningful factor clusters had a significant impact on cooperative performance: Policy and Institutional Environment (β = 0.428), Management Capacity – Resources – Technology (β = 0.356), Member Participation (β = 0.306), Market Dynamics (β = 0.274), and Value Chain Integration (β = 0.226). The results show how functional data-driven modelling can be for making specific policy suggestions and actions. The study concludes with practical tactics that use predictive insights to speed up cooperative growth in Ho Chi Minh City's changing digital economy. [ABSTRACT FROM AUTHOR]
Copyright of International Journal on Advanced Science, Engineering & Information Technology is the property of INSIGHT - Indonesian Society for Knowledge & Human Development and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Machine Learning-driven Analysis of Determinants Influencing Cooperative Development in Ho Chi Minh City under Digital Transformation.
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  Data: <searchLink fieldCode="AR" term="%22Tong%2C+Quoc+Bao%22">Tong, Quoc Bao</searchLink><br /><searchLink fieldCode="AR" term="%22Nguyen%2C+Minh+Tuan%22">Nguyen, Minh Tuan</searchLink><br /><searchLink fieldCode="AR" term="%22Le%2C+Anh+Tuan%22">Le, Anh Tuan</searchLink><br /><searchLink fieldCode="AR" term="%22Nguyen%2C+Thuy-Van%22">Nguyen, Thuy-Van</searchLink><br /><searchLink fieldCode="AR" term="%22Vu%2C+Thuy-Vi%22">Vu, Thuy-Vi</searchLink><br /><searchLink fieldCode="AR" term="%22Pham%2C+Minh-Tuan%22">Pham, Minh-Tuan</searchLink>
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  Data: International Journal on Advanced Science, Engineering & Information Technology; 2025, Vol. 15 Issue 4, p1213-1220, 8p
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  Data: <searchLink fieldCode="DE" term="%22DIGITAL+transformation%22">DIGITAL transformation</searchLink><br /><searchLink fieldCode="DE" term="%22ECONOMIC+development%22">ECONOMIC development</searchLink><br /><searchLink fieldCode="DE" term="%22MACHINE+learning%22">MACHINE learning</searchLink><br /><searchLink fieldCode="DE" term="%22CITIES+%26+towns%22">CITIES & towns</searchLink><br /><searchLink fieldCode="DE" term="%22SUSTAINABLE+development%22">SUSTAINABLE development</searchLink><br /><searchLink fieldCode="DE" term="%22POLICY+analysis%22">POLICY analysis</searchLink><br /><searchLink fieldCode="DE" term="%22PREDICTION+models%22">PREDICTION models</searchLink><br /><searchLink fieldCode="DE" term="%22SHARING+economy%22">SHARING economy</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22HO+Chi+Minh+City+%28Vietnam%29%22">HO Chi Minh City (Vietnam)</searchLink><br /><searchLink fieldCode="DE" term="%22VIETNAM%22">VIETNAM</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Developing the collective economy with the core of cooperatives is one of the four critical economic sectors in the market economy in Vietnam. The cooperative economic model operates effectively, contributing to sustainable economic development, building new rural areas, creating jobs, eliminating hunger, reducing poverty, and ensuring social security. This study employs advanced methods to identify and quantify the key factors influencing cooperative economic growth in Ho Chi Minh City, as the city undergoes digital transformation and initiatives aimed at making urban areas more sustainable. This study conducted a structured survey with 350 cooperative managers and members. Thereafter, a hybrid analytical framework that combined reliability assessment (Cronbach's Alpha), dimensionality reduction through Exploratory Factor Analysis (EFA), and predictive modelling through multivariate linear regression to process the data was employed. Regularization and model diagnostics were used to make the model stronger and less multicollinear. The adjusted R² value of the optimized regression model (0.676) showed that five meaningful factor clusters had a significant impact on cooperative performance: Policy and Institutional Environment (β = 0.428), Management Capacity – Resources – Technology (β = 0.356), Member Participation (β = 0.306), Market Dynamics (β = 0.274), and Value Chain Integration (β = 0.226). The results show how functional data-driven modelling can be for making specific policy suggestions and actions. The study concludes with practical tactics that use predictive insights to speed up cooperative growth in Ho Chi Minh City's changing digital economy. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal on Advanced Science, Engineering & Information Technology is the property of INSIGHT - Indonesian Society for Knowledge & Human Development and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 8
        StartPage: 1213
    Subjects:
      – SubjectFull: HO Chi Minh City (Vietnam)
        Type: general
      – SubjectFull: VIETNAM
        Type: general
      – SubjectFull: DIGITAL transformation
        Type: general
      – SubjectFull: ECONOMIC development
        Type: general
      – SubjectFull: MACHINE learning
        Type: general
      – SubjectFull: CITIES & towns
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      – SubjectFull: SUSTAINABLE development
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      – SubjectFull: POLICY analysis
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      – SubjectFull: PREDICTION models
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      – SubjectFull: SHARING economy
        Type: general
    Titles:
      – TitleFull: Machine Learning-driven Analysis of Determinants Influencing Cooperative Development in Ho Chi Minh City under Digital Transformation.
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            NameFull: Nguyen, Thuy-Van
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            – D: 01
              M: 07
              Text: 2025
              Type: published
              Y: 2025
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