Digital Transformation Capability and Bank Innovation Performance: The Mediating Role of Financial Innovation——A Case of Industrial and Commercial Bank of China, Guangdong Branch
Main Article Content
Abstract
This research aimed to: 1) identify the influence relationship among the three variables, including the effect of DTC on BIP; the effect of FI on BIP; and the effect of DTC on FI; and 2) explore the mediating effect of financial innovation on the relationship between the digital transformation capability and bank innovation performance. The study sample comprised the Guangdong Branch of ICBC, selected via stratified random sampling. Data were collected by distributing a five-point Likert-scale questionnaire to bank managers via an online platform, yielding 400 valid responses. Descriptive statistics and structural equation modeling (SEM) were employed for data analysis. The findings revealed that: 1) digital transformation capability positively influenced financial innovation (β = 0.961), which in turn positively influenced bank innovation performance (β = 0.742). Digital transformation capability also has a certain impact on bank innovation performance (β = 0.214); and 2) financial innovation served as a mediator between digital transformation capabilities and bank innovation performance, with an indirect effect of 0.714. The theoretical contribution of this study lies in breaking the fragmented approach of the four major theories and constructing a unified framework with a progressive relationship: identifying heterogeneous digital resources based on RBV and considering organizational context based on TOE; emphasizing the dynamic reorganization of resources by organizations based on DCT; explaining the transmission medium (indirect effect) of value creation based on FIT; and ultimately focusing on innovation performance.
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Views and opinions appearing in the Journal it is the responsibility of the author of the article, and does not constitute the view and responsibility of the editorial team.
References
Abdurrahman, A. (2025). Examining the impact of digital transformation on digital product innovation performance in banking industry through the integration of resource-based view and dynamic capabilities. Journal of Strategy & Innovation, 36(1), 200540. https://doi.org/10.1016/j.jsinno.2025.200540
Bartlett, M. S. (1950). Tests of significance in factor analysis. British Journal of Psychology, (3), 77-85. https://doi.org/10.1111/j.2044-8317.1950.tb00285.x
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen and J. S. Long (Eds.), Testing structural equation models (pp. 136-162). SAGE.
Ciftci, M., Lev, B., & Radhakrishnan, S. (2011). Is research and development mispriced or properly risk adjusted?. Journal of Accounting, Auditing & Finance, 26(1), 81-116. https://doi.org/10.1177/0148558X11400581
Drechsler, K., Gregory, R., Wagner, H., & Tumbas, S. (2020). At the crossroads between digital innovation and digital transformation. Communications of the Association for Information Systems, 47, 521-538. https://doi.org/10.17705/1CAIS.04723
Ferreira, J. J., Fernandes, C. I., & Ferreira, F. A. (2019). To be or not to be digital, that is the question: Firm innovation and performance. Journal of Business Research, 101, 583-590. https://doi.org/10.1016/j.jbusres.2018.11.013
Freedman, D. A. (1981). Bootstrapping regression models. The Annals of Statistics, 9(6), 1218-1228. http://www.jstor.org/stable/2240411
Guo, L., & Xu, L. (2021). The effects of digital transformation on firm performance: Evidence from China’s manufacturing sector. Sustainability, 13(22), 12844. https://doi.org/10.3390/su132212844
Hair, J. F., Babin, B. J., Anderson, R. E., & Black, W. C. (2019). Multivariate data analysis (8th ed.). England: Pearson Prentice.
Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36. https://doi.org/10.1007/BF02291575
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
Levallet, N., & Chan, Y. (2022). Uncovering a new form of digitally-enabled agility: An improvisational perspective. European Journal of Information Systems, 31(6), 681-708. https://doi.org/10.1080/0960085X.2022.2035262
Schumacker, R., & Lomax, R. (2010). A beginner’s guide to structural equation modeling (3rd ed.). Lawrence Erlbaum Associates.
Tibbe, T. D., & Montoya, A. K. (2022). Correcting the bias correction for the bootstrap confidence interval in mediation analysis. Frontiers in Psychology, 13, 810258. https://doi.org/10.3389/fpsyg.2022.810258
Urban, B., & Mateyo, K. (2025). The role of entrepreneurial culture, digital orientation, and digital capabilities in fostering digital innovation: A focus on the financial services sector in South Africa. International Journal of Technological Learning, Innovation and Development, 16(3), 217-237. https://doi.org/10.1504/IJTLID.2025.148088
WallStreetMojo. (2025, Mar 3). Financial innovation?. WallStreetMojo. https://www.wallstreetmojo.com/financial-innovation/#1
Yamane, T. (1973). Statistics: an introductory analysis (3rd ed.). Harper and Row.
Yan, P., & Yong, C. (2025). FinTech and corporate digital technology innovation. Finance Research Letters, 85(B). https://doi.org/10.1016/j.frl.2025.108007
Yang, Y., & Wang, L. (2026). Digital intelligence transformation, financial innovation, and the effectiveness of enterprise risk management. International Review of Financial Analysis, 110. https://doi.org/10.1016/j.irfa.2025.104865
Yuan, X., Puah, C. H., & Marikan, D. A. B. A. (2025). An empirical study on the impact of financial technology on the profitability of China’s listed commercial banks. Journal of Risk and Financial Management (JRFM), 18(8), 440. https://doi.org/10.3390/jrfm18080440