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Bridging BI and AI Enhancing Operational Efficiency in the Chinese Financial Sector
Mid Sweden University, Faculty of Human Sciences, Department of Economics, Geography, Law and Tourism.ORCID iD: 0000-0001-5731-0489
2024 (English)In: Journal of Global Information Management, ISSN 1062-7375, E-ISSN 1533-7995, Vol. 32, no 1, p. 1-27Article in journal (Refereed) Published
Abstract [en]

This study explores the impact of Business Intelligence (BI) systems on operational efficiency (OE) and the transition to Artificial Intelligence (AI) technologies in financial firms from Shanghai and Shenzhen stock markets (2007-2021). It investigates whether existing BI platforms underpin AI adoption, using Data Envelopment Analysis as a proxy for OE and the frequency of terms like Big Data and data mining in annual reports to indicate BI usage. Employing Heckman's two-stage and Hausman firm fixed effect model addresses potential endogeneity. Results show significant OE improvements post-BI adoption, with increasing benefits over time and enhanced by R&D intensity. Additionally, this research extends to global information management, linking BI capabilities with AI readiness and offering insights into strategic technology management in the financial sector, aligning with shifts towards AI in business, thereby impacting local and global information strategies. 

Place, publisher, year, edition, pages
IGI Global , 2024. Vol. 32, no 1, p. 1-27
Keywords [en]
Artificial Intelligence Adoption, Business Intelligence Systems, Data Envelopment Analysis, Global Technology Management, Operational Efficiency, Technological Transition in Business
National Category
Business Administration
Identifiers
URN: urn:nbn:se:miun:diva-53785DOI: 10.4018/JGIM.366871ISI: 001447438000003Scopus ID: 2-s2.0-85216467330OAI: oai:DiVA.org:miun-53785DiVA, id: diva2:1936556
Available from: 2025-02-11 Created: 2025-02-11 Last updated: 2025-03-27

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
  • de-DE
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More languages
Output format
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