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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">PBES</journal-id><journal-title-group><journal-title>Proceedings of Business and Economic Studies</journal-title></journal-title-group><issn>2209-2641</issn><eissn>2209-265X</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/pbes.v8i3.11188</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Digital Intelligence Empowerment and New Quality Productivity of Listed Enterprises in Fujian Province</title><url>https://artdesignp.com/journal/PBES/8/3/10.26689/pbes.v8i3.11188</url><author>CaiDixin,ChenBaowen</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>8</volume><issue>3</issue><history><date date-type="pub"><published-time>2025-07-15</published-time></date></history><abstract>This paper examines the impact of digital intelligence transformation on new quality productivity in enterprises in Fujian Province. It highlights the challenges these enterprises face, such as limited talent and infrastructure, in adopting technologies like cloud computing, big data, and artificial intelligence. The research finds that digital intelligence can enhance innovation, efficiency, and market adaptability, driving significant improvements in productivity. The study emphasizes the need for organizational changes and government support to overcome barriers and accelerate transformation, offering valuable insights for both academia and industry.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Tang J, 2024, New Quality Productivity and China’s Strategic Shift Towards Sustainable and Innovation-Driven Economic Development. Journal of Interdisciplinary Insights, 2(3): 36–45.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B2" content-type="article"><label>2</label><element-citation publication-type="journal"><p>Wei L, 2024, Accelerating the Cultivation of the New Quality Productive Forces to Advance High-Quality Development. Economic Theory and Business Management, 44(4): 1.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B3" content-type="article"><label>3</label><element-citation publication-type="journal"><p>Liu Y, He Z, 2024, Synergistic Industrial Agglomeration, New Quality Productive Forces and High-Quality Development of the Manufacturing Industry. International Review of Economics &amp; Finance, 94: 103373.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B4" content-type="article"><label>4</label><element-citation publication-type="journal"><p>Acemoglu D, Restrepo P, 2018, The Race Between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment. American Economic Review, 108(6): 1488–1542.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B5" content-type="article"><label>5</label><element-citation publication-type="journal"><p>Ghasemaghaei M, Calic G, 2020, Assessing the Impact of Big Data on Firm Innovation Performance: Big Data Is Not Always Better Data. Journal of Business Research, 108: 147–162.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B6" content-type="article"><label>6</label><element-citation publication-type="journal"><p>Czarnitzki D, Fernández GP, Rammer C, 2023, Artificial Intelligence and Firm-Level Productivity. Journal of Economic Behavior &amp; Organization, 211: 188–205.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B7" content-type="article"><label>7</label><element-citation publication-type="journal"><p>Björkdahl J, 2020, Strategies for Digitalization in Manufacturing Firms. California Management Review, 62(4): 17–36.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B8" content-type="article"><label>8</label><element-citation publication-type="journal"><p>Bag S, Rahman MS, Gupta S, et al., 2023, Understanding and Predicting the Determinants of Blockchain Technology Adoption and SMEs’ Performance. The International Journal of Logistics Management, 34(6): 1781–1807.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B9" content-type="article"><label>9</label><element-citation publication-type="journal"><p>Zhang X, Li J, Xiang D, et al., 2023, Digitalization, Financial Inclusion, and Small and Medium-Sized Enterprise Financing: Evidence From China. Economic Modelling, 126: 106410.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B10" content-type="article"><label>10</label><element-citation publication-type="journal"><p>Zhao N, Hong J, Lau KH, 2023, Impact of Supply Chain Digitalization on Supply Chain Resilience and Performance: A Multi-Mediation Model. International Journal of Production Economics, 259: 108817.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
