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Examining the Importance of AI-Based Criteria in the Development of the Digital Economy: A Multi-Criteria Decision-Making Approach

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Examining the Importance of AI-Based Criteria in the Development of the Digital Economy: A Multi-Criteria Decision-Making Approach

Entezami, Mahmoudreza, Basirat, Sepideh, Moghaddami, Behzad, Bazmandeh, Danial and Charkhian, Dorsa (2025) Examining the Importance of AI-Based Criteria in the Development of the Digital Economy: A Multi-Criteria Decision-Making Approach. Journal of Soft Computing and Decision Analytics, 3 (1). pp. 72-95. ISSN 3009-3481

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Official URL: https://doi.org/10.31181/jscda31202555

Abstract

As one of the main pillars of global transformation in the contemporary world, the digital economy helps create new economic and business opportunities through new technologies. In addition to improving efficiency and reducing costs, this transformation plays a vital role in the economic growth and development of various countries. Artificial intelligence, as one of the key technologies in the development of the digital economy, has a profound impact on optimizing processes, increasing productivity, and enhancing customer experience. By processing big data and providing advanced analytics, this technology makes economic decisions faster and more accurately and affects various sectors of the digital economy. In this regard, 20 key AI-based criteria in the development of the digital economy were extracted from a review of previous studies and were placed in four general categories. The four general categories include structural, organizational, technological and economic. Hesitant Fuzzy Best Worst Method (HF-BWM) was used to rank the AI-based criteria in the development of the digital economy. “Investing in innovation (C16)”, “Potent processing capabilities (C1)”, “Process automation and intelligence (C11)”, “Identifying growth opportunities (C6)” and “Adapting business models to changes (C7)” ranked one to five, respectively. Managers in the digital economy should pay attention to investing in innovation and strengthening processing infrastructure to exploit new technologies and make more accurate decisions. Process intelligence, identifying new areas of growth and adapting the business model to market changes also help improve efficiency, reduce costs, exploit new opportunities and make organizations stable in the face of rapid changes and increasing competition.

Divisions:Concordia University > Faculty of Arts and Science > Economics
Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Concordia University > Gina Cody School of Engineering and Computer Science > Concordia Institute for Information Systems Engineering
Concordia University > Gina Cody School of Engineering and Computer Science > General Studies
Concordia University > John Molson School of Business > Accountancy
Concordia University > John Molson School of Business > Finance
Concordia University > John Molson School of Business > Management
Concordia University > John Molson School of Business > Marketing
Concordia University > John Molson School of Business > Supply Chain and Business Technology Management
Concordia University > Library
Concordia University > Research Units > Centre for Human Relations and Community Studies
Concordia University > Research Units > Centre for Oral History and Digital Storytelling
Concordia University > Research Units > Centre for Pattern Recognition and Machine Intelligence
Concordia University > Research Units > Centre for Research in Human Development
Concordia University > Research Units > Centre for Small Business and Entrepreneurial Studies
Concordia University > Research Units > Centre for the Study of Learning and Performance
Concordia University > Research Units > Desjardins Centre for Innovation in Business Finance
Concordia University > Research Units > Hexagram - The Institute for Research/Creation in Media Arts and Technologies
Concordia University > Research Units > Institute for Community Entrepreneurship and Development
Concordia University > Research Units > Karl Polanyi Institute of Political Economy
Item Type:Article
Refereed:Yes
Authors:Entezami, Mahmoudreza and Basirat, Sepideh and Moghaddami, Behzad and Bazmandeh, Danial and Charkhian, Dorsa
Journal or Publication:Journal of Soft Computing and Decision Analytics
Date:9 February 2025
Digital Object Identifier (DOI):10.31181/jscda31202555
Keywords:Digital Economy;Artificial Intelligence;Best Worst Method (BWM);Multi Criteria Decision Making; Digital Transformation.
ID Code:995072
Deposited By: Mahmoudreza Entezami
Deposited On:24 Feb 2025 17:29
Last Modified:24 Feb 2025 17:29
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