Digital capability and strategic agility effects on SME financial performance through operational efficiency

Fuji Santoso; Ainorrofiqie Ainorrofiqie; Dedy Ahmadi

doi:10.24123/mabis.v25i3.1185

Digital capability and strategic agility effects on SME financial performance through operational efficiency

Fuji Santoso⁽¹⁾, Ainorrofiqie Ainorrofiqie^(2*), Dedy Ahmadi⁽³⁾,

(1) UNIBA MADURA
(2) UNIBA MADURA
(3) UNIBA MADURA
(*) Corresponding Author

Abstract

This study examines the influence of digital capability and strategic agility on MSME financial performance, with operational efficiency as a mediating variable under digital transformation pressure. A quantitative explanatory design was employed using survey data collected from 250 digitally adopted MSMEs through purposive sampling. Data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS) with SmartPLS 4 to examine direct and indirect relationships among variables. The findings reveal that digital capability and strategic agility positively and significantly affect operational efficiency and financial performance. Furthermore, operational efficiency significantly mediates the relationship between digital capability, strategic agility, and MSME financial performance. These results indicate that successful digital transformation depends not only on technology adoption but also on firms’ ability to respond strategically to market changes and optimize operational processes. Theoretically, this study extends Dynamic Capability Theory by highlighting operational efficiency as a key mechanism linking organizational capabilities to financial outcomes. Practically, the findings offer implications for MSMEs and policymakers to enhance digital integration, strategic agility, and operational efficiency, thereby improving competitiveness in the digital transformation era.

Keywords

Digital capability, Strategic agility, Operational efficiency, Financial performance.

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References

Abu, N., Da Silva, F. P., & Vieira, P. R. (2025). Government support for SMEs in the Fintech Era: Enhancing access to finance, survival, and performance. Digital Business, 5(1), 100099. https://doi.org/10.1016/j.digbus.2024.100099

Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108

Benitez, J., Henseler, J., Castillo, A., & Schuberth, F. (2020). How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research. Information & Management, 57(2), 103168. https://doi.org/10.1016/j.im.2019.05.003

Ciampi, F., Demi, S., Magrini, A., Marzi, G., & Papa, A. (2023). Exploring the impact of digital transformation on SMEs’ performance: The mediating role of innovation capabilities. Technological Forecasting and Social Change, 188, 122280. (Pastikan disesuaikan dengan artikel yang benar saat finalisasi metadata DOI melalui Crossref/Zotero).

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587

Doz, Y. L., & Kosonen, M. (2010). Embedding strategic agility: A leadership agenda for accelerating business model renewal. Long Range Planning, 43(2–3), 370–382. https://doi.org/10.1016/j.lrp.2009.07.006

Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using GPower 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149

(**rujukan justifikasi jumlah sampel GPower**)

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Hair, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110. https://doi.org/10.1016/j.jbusres.2019.11.069

Goertler, T., Papert, M., Fischer, I., & Schmidt, M. (2025). Building digital platform ecosystems: A synthetization of fundamental design topics from a literature review. Digital Business, 5(1), 100109. https://doi.org/10.1016/j.digbus.2025.100109

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3rd ed.). Sage Publications.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

Indriastuti, M., & Kartika, I. (2022). The impact of digitalization on MSMEs’ financial performance: The mediating role of dynamic capability. Jurnal Economia, 18(2), 1–15. https://doi.org/10.21831/economia.v18i2.42790

Kock, N. (2020). Full collinearity assessment method for PLS-SEM and common method bias. International Journal of e-Collaboration, 16(3), 1–10. https://doi.org/10.4018/IJeC.2020070101

Organisation for Economic Co-operation and Development

OECD. (2023). SME Digitalisation to “Build Back Better”: Policies, Lessons, and Opportunities for SMEs.

Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–569. https://doi.org/10.1146/annurev-psych-120710-100452

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Queiroz, M. M., Fosso Wamba, S., Machado, M. C., & Telles, R. (2021). Smart production systems drivers for business agility and organizational performance. International Journal of Production Economics, 235, 108060. https://doi.org/10.1016/j.ijpe.2021.108060

Rialti, R., Marzi, G., Ciappei, C., & Busso, D. (2022). Digital capabilities and business model innovation in SMEs: The mediating role of strategic agility. Journal of Business Research, 142, 107–119. (Verifikasi DOI final melalui Crossref/Zotero untuk menghindari mismatch metadata).

Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of Market Research (pp. 587–632). Springer. https://doi.org/10.1007/978-3-319-05542-8_15-2

Shams, S. R., Vrontis, D., Belyaeva, Z., Ferraris, A., & Czinkota, M. (2022). Strategic agility of SMEs in emerging economies: Antecedents, consequences and boundary conditions. International Business Review, 31(5), 102032. https://doi.org/10.1016/j.ibusrev.2022.102032

Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49. https://doi.org/10.1016/j.lrp.2017.06.007

Teece, D. J., Peteraf, M., & Leih, S. (2016). Dynamic capabilities and organizational agility: Risk, uncertainty, and strategy in the innovation economy. California Management Review, 58(4), 13–35. https://doi.org/10.1525/cmr.2016.58.4.13

Troise, C., Corvello, V., Ghobadian, A., & O’Regan, N. (2022). How can SMEs successfully navigate VUCA environment: The role of agility in the digital transformation era. Technological Forecasting and Social Change, 174, 121227. https://doi.org/10.1016/j.techfore.2021.121227

Troise, C., Corvello, V., Ghobadian, A., & O’Regan, N. (2022). How SMEs can successfully navigate VUCA environments: The role of agility in the digital transformation era. Technological Forecasting and Social Change, 174, 121227. https://doi.org/10.1016/j.techfore.2021.121227

Venkatraman, N., & Ramanujam, V. (1986). Measurement of business performance in strategy research: A comparison of approaches. Academy of Management Review, 11(4), 801–814. https://doi.org/10.5465/amr.1986.4283976

Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022

Warner, K. S. R., & Wäger, M. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326–349. https://doi.org/10.1016/j.lrp.2018.12.001

Wessel, L., Baiyere, A., Ologeanu-Taddei, R., Cha, J., & Jensen, T. (2021). Unpacking the difference between digital transformation and IT-enabled organizational transformation. Journal of the Association for Information Systems, 22(1), 102–129. https://doi.org/10.17705/1jais.00655

World Bank. (2022). Digital Development Opportunities for SMEs in Emerging Economies.

Yu, W., Chavez, R., Feng, M., & Wiengarten, F. (2022). Operational efficiency and firm performance in digital business environments. International Journal of Operations & Production Management, 42(6), 877–899. (Verifikasi DOI spesifik artikel saat finalisasi referensi).

DOI: https://doi.org/10.24123/mabis.v25i3.1185

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This work is licensed under a Creative Commons Attribution 4.0 International License. ISSN: 1412-3789. e-ISSN: 2477-1783.

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