<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In the digital economy era, digital transformation aligns with sustainable development and national policies. This research examines enterprise economic output through human and physical capital driven by digital transformation. Utilizing the TrAdaBoost algorithm in transfer learning, we predict economic risks for enterprises. We propose an optimization path for digital economic management systems. Furthermore, we empirically analyze the current financial management and challenges of digital transformation at Company X, laying the groundwork for identifying and analyzing digital transformation risks. Our findings indicate the significant influence of risk-free interest rate (0.1781), GDP (0.1732), and money supply (0.1668) on enterprise economic risk, guiding enterprises to mitigate these impacts during digital transformation.</p>
</abstract>

In the digital economy era, digital transformation aligns with sustainable development and national policies. This research examines enterprise economic output through human and physical capital driven by digital transformation. Utilizing the TrAdaBoost algorithm in transfer learning, we predict economic risks for enterprises. We propose an optimization path for digital economic management systems. Furthermore, we empirically analyze the current financial management and challenges of digital transformation at Company X, laying the groundwork for identifying and analyzing digital transformation risks. Our findings indicate the significant influence of risk-free interest rate (0.1781), GDP (0.1732), and money supply (0.1668) on enterprise economic risk, guiding enterprises to mitigate these impacts during digital transformation.

Path optimization of enterprise economic management system in digital transformation

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In the digital economy era, digital transformation aligns with sustainable development and national policies. This research examines enterprise economic output...

Path optimization of enterprise economic management system in digital transformation

Online veröffentlicht: 22. Mai 2024

Seitenbereich: -

Eingereicht: 27. Jan. 2024

Akzeptiert: 08. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1134

Schlüsselwörter
Digital transformation, Transfer learning, TrAdaBoost algorithm, Enterprise economic management

© 2024 Guang Yang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Path optimization of enterprise economic management system in digital transformation

Online veröffentlicht: 22. Mai 2024

Seitenbereich: -

Eingereicht: 27. Jan. 2024

Akzeptiert: 08. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1134

SchlüsselwörterDigital transformation, Transfer learning, TrAdaBoost algorithm, Enterprise economic management

© 2024 Guang Yang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Digital transformation, Transfer learning, TrAdaBoost algorithm, Enterprise economic management