Digital transformation necessitates the development of a robust capability, as well as the resolution of complex convergence issues between the digital system and the existing legacy systems within the transforming enterprise. This study seeks to expand upon the existing conceptualization of digital transformation capability by introducing a novel model grounded in dynamic capability theory. To explore the development of digital transformation capability construction, this study conducted a multi-phase empirical investigation involving organizations that have either already undergone or are currently in the midst of digital transformation. The empirical findings reveal that digital transformation capabilities are constructed from three primary dimensions: sensing, organizing, and restructuring. Furthermore, this study assessed the criterion validity of a reflective measurement model designed to describe digital transformation capability and its impact on well-established organizational performance metrics. The results confirm the validity of this model in capturing the essence of digital transformation capability and its significant influence on organizational performance. By providing a deeper understanding of the underlying mechanisms and dimensions of digital transformation capability, this study offers valuable insights for both academic researchers and practitioners seeking to navigate the digital transformation journey.

Jiatong Yu, Mengman Lin, Taesoo Moon. Construct Development of Digital Transformation Capability: Dynamic Capability Perspective. Academic Journal of Business & Management (2026), Vol. 8, Issue 2: 45-51. https://doi.org/10.25236/AJBM.2026.080206.

[1] Vial, G. Understanding digital transformation: A review and a research agenda. J. Strateg. Inf. Syst. 2019, 28, 118-144.

[2] Michelotto, F.; Joia, L.A. Organizational Digital Transformation Readiness: An Exploratory Investigation. J. Theor. Appl. Electron. Commer. Res. 2024, 19, 3283-3304.

[3] Li, T.; Ni, L.; Xu, Y. Enterprise Digital transformation drivers: Market or government? A case study from China. J. Theor. Appl. Electron. Commer. Res. 2025, 20, 131.

[4] Teece, D.J.; Pisano, G.; Shuen, A. Dynamic capabilities and strategic management. Strateg. Manag. J. 1997, 7, 509-533.

[5] Karimi, J.; Walter, Z. The role of dynamic capabilities in responding to digital disruption: A factor-based study of the newspaper industry. J. Manag. Inf. Syst. 2015, 1, 39-81.

[6] Freitas, J.C.; Macada, A.C.G.; Brinkhues, R.A.; Zimmermann Montesdioca, G. Digital capabilities as driver to digital business performance. In Proceedings of the 22nd Americas Conference on Information Systems (AMCIS), San Diego, CA, USA, 11-14 August 2016.

[7] Pagoropoulos, A.; Maier, A.; McAloone, T.C. Assessing transformational change from institutionalising digital capabilities on implementation and development of product - service systems: Learnings from the maritime industry. J. Clean. Prod. 2017, 166, 369-380.

[8] Bollen, K.A.; Lennox, R. Conventional wisdom on measurement: A structural equation perspective. Psychol. Bull. 1991, 10, 305-314.

[9] Yang, Y.; Chen, N.; Chen, H. The digital platform, enterprise digital transformation, and enterprise performance of cross-border e-commerce-from the perspective of digital transformation and data elements. J. Theor. Appl. Electron. Commer. Res. 2023, 18, 777-794.

[10] Liu, X. Multilevel and longitudinal modeling with ibm spss. Int. J. Res. Method Educ. 2011, 34, 211-213.

[11] Fornell, C.; Larcker, D.F. Structural equation models with unobservable variables and measurement error: Algebra and statistics. J. Mark. Res. 1981, 18, 382-388.

[12] Sarstedt, M.; Hair, J.F., Jr.; Cheah, J.H.; Becker, J.M.; Ringle, C.M. How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australas. Mark. J. 2019, 27, 197-211.

[13] Hair, J.; Hollingsworth, C.L.; Randolph, A.B.; Chong, A.Y.L. An updated and expanded assessment of PLS-SEM in information systems research. Ind. Manag. Data Syst. 2017, 117, 442-445.