Digital Transformation, Asymmetric Information and Debt Financing Costs for Small and Medium-sized Enterprises: Evidence from Machine Learning Text Analysis

DOI

10.2991/978-94-6239-602-9_42How to use a DOI?

Keywords

Digital transformation; Debt financing costs; Small and medium-sized enterprises; Asymmetric information; Machine learning text analysis; Moderating effects

Abstract

This study employs machine learning text analysis to construct a comprehensive Digital Transformation Index (DTI) encompassing three dimensions—technology application, strategic orientation, and organisational change—based on data from small and medium-sized enterprises listed on the Shanghai and Shenzhen A-share markets between 2019 and 2023. It empirically examines the impact of digital transformation on debt financing costs for SMEs and its underlying mechanisms. Findings reveal that digital transformation significantly reduces corporate debt financing costs, with each one-unit increase in DTI lowering debt financing costs by an average of 0.0098 percentage points. This effect is more pronounced in private enterprises and regions with advanced fintech ecosystems, indicating that ownership structure and regional fintech sophistication exert significant moderating effects. Mechanism analysis indicates that digital transformation primarily reduces financing costs through two parallel pathways: alleviating information asymmetry and enhancing analyst tracking capabilities. The mediating effect accounts for 65.2% of the total effect. This study provides theoretical and empirical evidence for understanding the financial empowerment effects of digital transformation, offering valuable insights for SME digital practices and financial institutions’ credit decision-making.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ziyue An
PY  - 2026
DA  - 2026/03/13
TI  - Digital Transformation, Asymmetric Information and Debt Financing Costs for Small and Medium-sized Enterprises: Evidence from Machine Learning Text Analysis
BT  - Proceedings of the 2025 7th International Conference on Economic Management and Model Engineering (ICEMME 2025)
PB  - Atlantis Press
SP  - 475
EP  - 490
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-602-9_42
DO  - 10.2991/978-94-6239-602-9_42
ID  - An2026
ER  -