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The Role of Digitization in Corporate Finance
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The Role of Digitization in Corporate Finance

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Economics and Finance".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 19538

Special Issue Editors

Dr. Mihaela Brîndușa Tudose

E-Mail Website
Guest Editor
Associate Professor, Engineering and Management Department, Faculty of Design Industrial and Business Management, Gheorghe Asachi Technical University of Iasi, 700050 Iasi, Romania
Interests: public and private finance; financial management; performance management; micro and macroeconomics; entrepreneurship
Dr. Valentina Diana Rusu

E-Mail Website
Guest Editor
Senior Scientific Researcher, Department of Social Sciences and Humanities, Institute of Interdisciplinary Research, Alexandru Ioan Cuza University of Iasi, Alexandru Lăpușneanu Street, No. 26, 700057 Iasi, Romania
Interests: entrepreneurship; SMEs; access to finance; innovation

Special Issue Information

Dear Colleagues,

We are honored to invite you to publish in the Special Issue of The Role of Digitization in Corporate Finance, managed by a distinguished group of guest editors who are specialists in the fields of finance and digitization.

Topics of interest include, but are not limited to, the following:

  1. Qualitative and quantitative studies and research on causal relationships between digitization/fintech and
    • financial literacy (young people, adults, entrepreneurs, and SMEs);
    • speed of adjustment of the financial structure of the companies;
    • green finance;
    • eligibility for different sources of funding;
    • costs of financing.
  2. The mediating role of the digitization of financial services/operations in the relationships between
    • risks and business performance,
    • business agility and the objective structure of financing.
  3. Additional research questions:
    • Does digitization change the foundations of financing theories (trade of theory, pecking order theory, agency theory, etc.)?
    • What are the advantages and limits of digitization in the field of corporate finance?
    • Does digitization change the structure of key financial performance indicators?

Dr. Mihaela Brîndușa Tudose
Dr. Valentina Diana Rusu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Risk and Financial Management is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digitization
  • financial structure
  • speed of adjustment of financial structure
  • financial theories
  • financial management
  • financial performance
  • costs of capital

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Published Papers (5 papers)

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Research

18 pages, 744 KB  
Article
Evaluating the Impact of Intelligent Data Processing for Corporate Finance with the Use of Real Options Analysis
by Stanimir Ivanov Kabaivanov and Veneta Metodieva Markovska
J. Risk Financial Manag. 2026, 19(4), 292; https://doi.org/10.3390/jrfm19040292 - 18 Apr 2026
Viewed by 474
Abstract
Technological innovation is changing virtually every aspect of business practices and operational procedures. The introduction of large language models and various types of intelligent processing, commonly referred to as artificial intelligence, presents significant change to cope with. In this paper, we suggest an [...] Read more.
Technological innovation is changing virtually every aspect of business practices and operational procedures. The introduction of large language models and various types of intelligent processing, commonly referred to as artificial intelligence, presents significant change to cope with. In this paper, we suggest an estimation method, based on real options analysis (ROA), that improves the assessment and valuation of intelligent data processing’s impact on organizations. The presented approach can reflect direct and indirect effects from introducing artificial intelligence methods and is therefore better suited than traditional financial metrics for the assessment of contemporary intelligent tools and solutions. Using Monte Carlo simulation and American-style real options, we have estimated two sample use cases to compare the ROA results against other common valuation methods. Numerical experiments indicate that the suggested approach is capable of capturing both the direct and indirect impact of new technologies, which improves relevant financial and management decisions. Full article
(This article belongs to the Special Issue The Role of Digitization in Corporate Finance)
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20 pages, 529 KB  
Article
Fintech Firms’ Valuations: A Cross-Market Analysis in Asia
by Neha Parashar, Rahul Sharma, Pranav Saraswat, Apoorva Joshi and Sumit Banerjee
J. Risk Financial Manag. 2026, 19(1), 74; https://doi.org/10.3390/jrfm19010074 - 17 Jan 2026
Cited by 1 | Viewed by 1717
Abstract
This study investigates the valuation dynamics of 30 publicly listed fintech firms across six Asian economies from January 2021 to December 2025. It examines how intrinsic firm-level scale (market capitalization) and extrinsic macroeconomic conditions (GDP growth) jointly influence fintech valuation ratios, as reflected [...] Read more.
This study investigates the valuation dynamics of 30 publicly listed fintech firms across six Asian economies from January 2021 to December 2025. It examines how intrinsic firm-level scale (market capitalization) and extrinsic macroeconomic conditions (GDP growth) jointly influence fintech valuation ratios, as reflected in price-to-earnings (P/E), price-to-book (P/B), and price-to-sales (P/S) measures. It also identifies significant structural heterogeneity and distributional asymmetries in valuation outcomes by implementing a multi-method empirical strategy that includes a Panel Autoregressive Distributed Lag (ARDL) framework, two-way fixed-effects models with interaction terms, and quantile regression. The findings reveal a robust, positive long-run relationship between market capitalization and valuation multiples across all ratios, confirming that firm-level scale as reflected in market capitalization is the primary driver of market value. Critically, the analysis identifies a dual-regime landscape in the Asian fintech sector: developed markets (South Korea, Japan, and Singapore) are fundamentally firm-scale driven, where intrinsic scale is the superior predictor of valuation. In contrast, developing markets (China, India, and Indonesia) are primarily macro-growth driven, exhibiting high sensitivity to GDP growth as a macroeconomic indicator of market expansion. The quantile regression results demonstrate a winner-takes-all effect, where the impact of scale on valuation is significantly more pronounced for highly valued firms in the 75th percentile. These results challenge the efficacy of universal valuation models and provide a context-dependent navigational framework for investors, analysts, and policymakers to distinguish between structural scale and cyclical growth in the rapidly evolving Asian fintech ecosystem. Full article
(This article belongs to the Special Issue The Role of Digitization in Corporate Finance)
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30 pages, 2017 KB  
Article
Financial Risk Management and Resilience of Small Enterprises Amid the Wartime Crisis
by Valeriia Shcherbak, Oleksandr Dorokhov, Liudmyla Dorokhova, Kseniia Vzhytynska, Valentyna Yatsenko and Oleksii Yermolenko
J. Risk Financial Manag. 2026, 19(1), 37; https://doi.org/10.3390/jrfm19010037 - 5 Jan 2026
Cited by 3 | Viewed by 2476
Abstract
This study examines the financial resilience of small enterprises in Ukraine during the wartime crisis, addressing the lack of quantitative evidence on how regional military risks and adaptive strategies jointly shape SME stability. The analysis is based on a sample of 30 small [...] Read more.
This study examines the financial resilience of small enterprises in Ukraine during the wartime crisis, addressing the lack of quantitative evidence on how regional military risks and adaptive strategies jointly shape SME stability. The analysis is based on a sample of 30 small agricultural enterprises from the eastern, central, and western regions of Ukraine using annual data for 2022–2024. To capture multidimensional resilience patterns, the study applies factor analysis, cluster analysis, and taxonomic assessment methods to evaluate financial performance, operational adaptability, and access to external resources. The findings show that resilience variation across the sample is strongly associated with enterprises’ ability to sustain revenue flows, control operating costs, and maintain a balanced capital structure. Three distinct resilience profiles were identified: high resilience in western regions (KT = 0.89), moderate resilience in central regions (KT = 0.81), and low resilience in eastern frontline regions (KT = 0.49). These results indicate substantial regional asymmetry linked to differentiated exposure to military threats. Building on these empirical insights, the study proposes a hybrid risk-management approach that integrates digitalization of financial operations, diversification of funding sources, and enhanced social engagement as mechanisms supporting adaptation under prolonged instability. The novelty of the research lies in combining regional risk exposure with multidimensional financial indicators to develop an evidence-based framework for assessing SME resilience in wartime conditions. Full article
(This article belongs to the Special Issue The Role of Digitization in Corporate Finance)
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22 pages, 535 KB  
Article
Digital Transformation Capability, Organizational Strategic Intuition, and Digital Leadership: Empirical Evidence from High-Tech Firms’ Performance in the Yangtze River Delta
by Yu Zhang, Trairong Swatdikun, Pankaewta Lakkanawanit, Shi-Zheng Huang and Heng Chen
J. Risk Financial Manag. 2025, 18(7), 405; https://doi.org/10.3390/jrfm18070405 - 21 Jul 2025
Cited by 3 | Viewed by 8134
Abstract
Despite growing scholarly interest in digital transformation, few studies have systematically explored the mechanisms linking digital transformation capability to firm performance. This study examines both the direct and indirect effects of digital transformation capability on firm performance, offering novel insights by incorporating organizational [...] Read more.
Despite growing scholarly interest in digital transformation, few studies have systematically explored the mechanisms linking digital transformation capability to firm performance. This study examines both the direct and indirect effects of digital transformation capability on firm performance, offering novel insights by incorporating organizational strategic intuition and digital leadership as mediating variables. These mediators align with the emerging emphasis on strategic risk management in the literature. A survey was conducted among 620 high-tech enterprises in the Yangtze River Delta using a structured questionnaire. The data were analyzed using SPSS 23.0 for descriptive and correlational statistics, SmartPLS 4.0 for structural equation modeling (SEM), and PROCESS 4.2 for mediation analysis. The results reveal a significant direct effect of digital transformation capability on firm performance. Mediation analysis further shows that organizational strategic intuition and digital leadership each significantly mediate this relationship, and a chain mediation pathway involving both variables is also confirmed. These findings deepen our understanding of how digital transformation capability drives performance outcomes and offer practical guidance for high-tech firms seeking sustainable competitive advantages in dynamic digital environments. This study advances the theoretical discourse by clarifying the pathways through which digital transformation capability affects firm performance and provides empirical evidence to inform strategic decision-making in high-tech management. Full article
(This article belongs to the Special Issue The Role of Digitization in Corporate Finance)
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16 pages, 2180 KB  
Article
A Multi-Stage Financial Distress Early Warning System: Analyzing Corporate Insolvency with Random Forest
by Katsuyuki Tanaka, Takuo Higashide, Takuji Kinkyo and Shigeyuki Hamori
J. Risk Financial Manag. 2025, 18(4), 195; https://doi.org/10.3390/jrfm18040195 - 4 Apr 2025
Cited by 7 | Viewed by 5703
Abstract
As corporate sector stability is crucial for economic resilience and growth, machine learning has become a widely used tool for constructing early warning systems (EWS) to detect financial vulnerabilities more accurately. While most existing EWS research focuses on bankruptcy prediction models, bankruptcy signals [...] Read more.
As corporate sector stability is crucial for economic resilience and growth, machine learning has become a widely used tool for constructing early warning systems (EWS) to detect financial vulnerabilities more accurately. While most existing EWS research focuses on bankruptcy prediction models, bankruptcy signals often emerge too late and provide limited early-stage insights. This study employs a random forest approach to systematically examine whether a company’s insolvency status can serve as an effective multi-stage financial distress EWS. Additionally, we analyze how the financial characteristics of insolvent companies differ from those of active and bankrupt firms. Our empirical findings indicate that highly accurate insolvency models can be developed to detect status transitions from active to insolvent and from insolvent to bankrupt. Furthermore, our analysis reveals that the financial determinants of these transitions differ significantly. The shift from active to insolvent is primarily driven by structural and operational ratios, whereas the transition from insolvent to bankrupt is largely influenced by further financial distress in operational and profitability ratios. Full article
(This article belongs to the Special Issue The Role of Digitization in Corporate Finance)
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