Transactions on Data Analysis in Social Science

Transactions on Data Analysis in Social Science

Emerging Technologies and Financial Management Performance: Survey Evidence from Companies Listed on the Shanghai Stock Exchange

Document Type : Original Article

Authors
Department of Accounting and Finance, Faculty of Management and Economics, Nanjing University, Nanjing, China.
10.22034/tdas.2025.255760
Abstract
Purpose. This study examines how the use of three emerging technologies (artificial intelligence [AI], big data analytics, and blockchain) is associated with financial management performance in companies listed on the Shanghai Stock Exchange (SSE), and whether firms with higher technology utilization report better financial outcomes than firms with lower utilization. Design/methodology/approach. A cross-sectional descriptive survey was conducted among financial managers and corporate accountants (n = 200) using a researcher-developed questionnaire whose content validity, construct validity, and reliability were assessed. Data were analyzed with SPSS (descriptive statistics, Pearson correlations, linear regression, independent-samples t-tests) and SmartPLS (structural model). Findings. Technology utilization was positively and significantly associated with financial efficiency and profitability. AI showed the largest coefficients (0.45 for financial efficiency; 0.41 for profitability), followed by big data analytics (0.38; 0.35) and blockchain (0.32; 0.29). Reduced human error (0.39) and faster financial operations (0.36) were also positively associated with profitability. Firms with high technology utilization reported a return on assets 6.4 percentage points higher and a net profit margin 7.6 percentage points higher than low-utilization firms. Originality/value. The study compares the three technologies on the same two outcome dimensions within one emerging-market setting, and links technology use to operational mechanisms (error reduction and processing speed) rather than treating “fintech” as a single construct. Practical implications. The results support investment in emerging technologies, development of digital competencies among finance staff, and re-engineering of financial processes. Because the design is cross-sectional and based largely on self-reported data, the findings indicate association rather than causation.
Keywords

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Volume 7, Issue 4
Autumn 2025
Pages 272-283

  • Receive Date 10 April 2025
  • Revise Date 29 July 2025
  • Accept Date 12 September 2025