Journal of Information Systems Engineering and Management

Innovative AI Regional Economic Development Driven by Information System Innovation: Opportunities and Challenges—A Boosting Factor from Digitalization, Business Intelligence Analytics
Xin Song 1 * , Wenyuan Han 2
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1 Ph.D, School of Business, Economics and Management of the National Economy, Belarusian State University, Minsk, Belarus
2 Ph.D, Agronomy Faculty, Crop Production, Belarusian State Agriculture Academy, Gorki, Belarus
* Corresponding Author
Research Article

Journal of Information Systems Engineering and Management, 2023 - Volume 8 Issue 4, Article No: 23783
https://doi.org/10.55267/iadt.07.14035

Published Online: 27 Oct 2023

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How to cite this article
APA 6th edition
In-text citation: (Song & Han, 2023)
Reference: Song, X., & Han, W. (2023). Innovative AI Regional Economic Development Driven by Information System Innovation: Opportunities and Challenges—A Boosting Factor from Digitalization, Business Intelligence Analytics. Journal of Information Systems Engineering and Management, 8(4), 23783. https://doi.org/10.55267/iadt.07.14035
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Song X, Han W. Innovative AI Regional Economic Development Driven by Information System Innovation: Opportunities and Challenges—A Boosting Factor from Digitalization, Business Intelligence Analytics. J INFORM SYSTEMS ENG. 2023;8(4):23783. https://doi.org/10.55267/iadt.07.14035
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Song X, Han W. Innovative AI Regional Economic Development Driven by Information System Innovation: Opportunities and Challenges—A Boosting Factor from Digitalization, Business Intelligence Analytics. J INFORM SYSTEMS ENG. 2023;8(4), 23783. https://doi.org/10.55267/iadt.07.14035
Chicago
In-text citation: (Song and Han, 2023)
Reference: Song, Xin, and Wenyuan Han. "Innovative AI Regional Economic Development Driven by Information System Innovation: Opportunities and Challenges—A Boosting Factor from Digitalization, Business Intelligence Analytics". Journal of Information Systems Engineering and Management 2023 8 no. 4 (2023): 23783. https://doi.org/10.55267/iadt.07.14035
Harvard
In-text citation: (Song and Han, 2023)
Reference: Song, X., and Han, W. (2023). Innovative AI Regional Economic Development Driven by Information System Innovation: Opportunities and Challenges—A Boosting Factor from Digitalization, Business Intelligence Analytics. Journal of Information Systems Engineering and Management, 8(4), 23783. https://doi.org/10.55267/iadt.07.14035
MLA
In-text citation: (Song and Han, 2023)
Reference: Song, Xin et al. "Innovative AI Regional Economic Development Driven by Information System Innovation: Opportunities and Challenges—A Boosting Factor from Digitalization, Business Intelligence Analytics". Journal of Information Systems Engineering and Management, vol. 8, no. 4, 2023, 23783. https://doi.org/10.55267/iadt.07.14035
ABSTRACT
This investigation looks at the intricate relationships between business intelligence (BI) analytics, digitalization, cutting-edge artificial intelligence (AI), and information system innovation, as well as how they affect local economic growth. The study emphasizes the transformative potential of AI as a powerful accelerator for regional growth by stimulating innovation, enhancing efficiency, and expediting decision-making processes. It does this by applying map analysis and spatial econometric model regression to a dataset covering Chinese regions from 2010 to 2022. The study highlights the critical need for the development of sophisticated digitalization frameworks and information systems to adapt to the ever-evolving dynamics of regional economies and advocates for the collabourative efforts of researchers and local governments in tailoring AI-driven solutions that cater to the unique demands of individual localities. Although the research highlights the initial benefits provided by BI analytics, it also strongly emphasizes the need for ongoing innovation to maintain long-term success, encouraging academics to improve and streamline current BI analytics programmes. The paper also highlights the crucial importance of computing sustainability, effective administration of massive datasets, seamless human-AI collabouration, geographic computing, and the ethical considerations connected with AI adoption. The study emphasizes the value of utilizing AI's revolutionary potential while proactively tackling the issues it presents by offering a series of doable recommendations for policymakers, practitioners, and researchers. In the end, this study makes a significant contribution to the body of knowledge already available about the role of AI in regional economic development, providing priceless insights for those involved in directing the course of regional economies.
KEYWORDS
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