Digital Transformation and AI Implementation Effects on SME Financial Performance in Emerging Economies

Shela Fatimah; Diana Puspitasari

doi:10.69725/jebi.v2i4.321

Authors

Shela Fatimah Department of Management, Faculty of Economics and Business, Universitas Dian Nuswantoro, Semarang, Indonesia, 50131
Diana Puspitasari Department of Management, Faculty of Economics and Business, Universitas Dian Nuswantoro, Kota Semarang, Indonesia, 50131

DOI:

https://doi.org/10.69725/jebi.v2i4.321

Keywords:

Digitalised transformation, Artificial intelligence, Operational performance MSMEs, Firm Performance.

Abstract

Purpose: This paper examines the impact of digital transformation and AI capabilities on MSME financial performance in an emerging economy via operational efficiency.

Method: A quantitative survey is used as a method of data collection for the study and PLS-SEM is used to test the mediation and moderation.

Findings: Results show that digital transformation capability, AI usage intensity, IT infrastructure preparedness and TTMS' (i.e., top management teams) digital competency drive operational efficiency, which in turn enhances financial performance. No direct financial implications from using AI or digital transformation capability are identified, highlighting that technological value is mainly achieved through operational efficiencies. On the other hand, IT infrastructure preparedness and digital management competence demonstrate both a direct and an indirect effect on performance. Environmental uncertainty has no direct effects on financial performance and does not moderate the relationships under study, indicating that digital and AI capabilities serve as basic rather than contingent drivers in this setting.

Novelty: This work adds by disambiguating the mediating role of digital value creation in MSME and by questioning the tacit boundary condition effect of environmental uncertainty in emerging economy context.

Implications: The findings emphasize therefore the necessity for integrating digital and AI strategy at heart of business process and developing managerial digital competencies to achieve durable performance improvements.

Downloads

Download data is not yet available.

Author Biographies

Shela Fatimah, Department of Management, Faculty of Economics and Business, Universitas Dian Nuswantoro, Semarang, Indonesia, 50131

Shela Fatimah is an undergraduate researcher in the Management program, Faculty of Economics and Business, Universitas Dian Nuswantoro, Semarang, Indonesia. Her research interests focus on digital payment systems, financial technology adoption, and consumer financial behavior, particularly among Generation Z. She is currently engaged in empirical research examining the impact of QRIS implementation on transaction volume and changes in financial behavior in emerging market contexts. Her academic work reflects a strong interest in the intersection of digital finance, behavioral economics, and technology-driven financial inclusion.
Diana Puspitasari, Department of Management, Faculty of Economics and Business, Universitas Dian Nuswantoro, Kota Semarang, Indonesia, 50131

Diana Puspitasari, S.E., M.M. is a lecturer in the Department of Management, Faculty of Economics and Business, Universitas Dian Nuswantoro, Indonesia. Her academic expertise includes financial management, macroeconomic policy analysis, and applied econometrics. She has published in nationally and internationally indexed journals and actively supervises research in monetary economics and financial risk management. Her research emphasizes the integration of macroeconomic theory with empirical analysis to support evidence-based policy and managerial decision-making.

References

Al-Ayed, S. (2024). Green innovation influenced by employee innovative work behavior via moderating role of innovative leaderships. Cogent Business & Management, 11(1), 2393741. https://doi.org/10.1080/23311975.2024.2393741 DOI: https://doi.org/10.1080/23311975.2024.2393741

Albannai, N. A. A., Raziq, M. M., Malik, M., & Abrar, A. (2025). Future Trends in Digital Leadership: Cultivating Innovation, Leveraging AI and Achieving Competitive Advantage: A Qualitative Study. Journal of Information & Knowledge Management, 24(05), 2550044. https://doi.org/10.1142/S0219649225500443 DOI: https://doi.org/10.1142/S0219649225500443

Amadasun, D. O. E., & Mutezo, A. T. (2022). Influence of access to finance on the competitive growth of SMEs in Lesotho. Journal of Innovation and Entrepreneurship, 11(1), 1–20. https://doi.org/10.1186/s13731-022-00244-1 DOI: https://doi.org/10.1186/s13731-022-00244-1

Appel, R. E. (2024). Generative AI regulation can learn from social media regulation.

Bag, S., Rahman, M. S., Srivastava, G., Giannakis, M., & Foropon, C. (2023). Data-driven digital transformation and the implications for antifragility in the humanitarian supply chain. International Journal of Production Economics, 266, 109059. https://doi.org/https://doi.org/10.1016/j.ijpe.2023.109059 DOI: https://doi.org/10.1016/j.ijpe.2023.109059

Chen, J., & Tajdini, S. (2025). A moderated model of artificial intelligence adoption in firms and its effects on their performance. Information Technology and Management, 26(3), 407–419. https://doi.org/10.1007/s10799-024-00422-5 DOI: https://doi.org/10.1007/s10799-024-00422-5

Dubey, R., Bryde, D. J., Dwivedi, Y. K., Graham, G., Foropon, C., & Papadopoulos, T. (2023). Dynamic digital capabilities and supply chain resilience: The role of government effectiveness. International Journal of Production Economics, 258, 108790. https://doi.org/https://doi.org/10.1016/j.ijpe.2023.108790 DOI: https://doi.org/10.1016/j.ijpe.2023.108790

Dubey, R., Gunasekaran, A., Childe, S. J., Bryde, D. J., Giannakis, M., Foropon, C., Roubaud, D., & Hazen, B. T. (2020). Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations. International Journal of Production Economics, 226, 107599. https://doi.org/https://doi.org/10.1016/j.ijpe.2019.107599 DOI: https://doi.org/10.1016/j.ijpe.2019.107599

Dwivedi, Y. K., Hughes, L., Kar, A. K., Baabdullah, A. M., Grover, P., Abbas, R., Andreini, D., Abumoghli, I., Barlette, Y., Bunker, D., Chandra Kruse, L., Constantiou, I., Davison, R. M., De’, R., Dubey, R., Fenby-Taylor, H., Gupta, B., He, W., Kodama, M., … Wade, M. (2022). Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action. International Journal of Information Management, 63, 102456. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2021.102456 DOI: https://doi.org/10.1016/j.ijinfomgt.2021.102456

Leso, B. H., Cortimiglia, M. N., Ghezzi, A., & Minatogawa, V. (2024). Exploring digital transformation capability via a blended perspective of dynamic capabilities and digital maturity: a pattern matching approach. Review of Managerial Science, 18(4), 1149–1187. https://doi.org/10.1007/s11846-023-00692-3 DOI: https://doi.org/10.1007/s11846-023-00692-3

Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment. British Journal of Management, 30(2), 272–298. https://doi.org/https://doi.org/10.1111/1467-8551.12343 DOI: https://doi.org/10.1111/1467-8551.12343

Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. https://doi.org/https://doi.org/10.1016/j.im.2021.103434 DOI: https://doi.org/10.1016/j.im.2021.103434

Miller, S., Hickson, D., & Wilson, D. (2008). From Strategy to Action: Involvement and Influence in Top Level Decisions. Long Range Planning, 41(6), 606–628. https://doi.org/https://doi.org/10.1016/j.lrp.2008.09.005 DOI: https://doi.org/10.1016/j.lrp.2008.09.005

Papagiannidis, E., Enholm, I. M., Dremel, C., Mikalef, P., & Krogstie, J. (2023). Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes. Information Systems Frontiers, 25(1), 123–141. https://doi.org/10.1007/s10796-022-10251-y DOI: https://doi.org/10.1007/s10796-022-10251-y

Scholta, H., Halsbenning, S., Distel, B., & Becker, J. (2020). Walking a Mile in Their Shoes—A Citizen Journey to Explore Public Service Delivery from the Citizen Perspective BT - Electronic Government (G. Viale Pereira, M. Janssen, H. Lee, I. Lindgren, M. P. Rodríguez Bolívar, H. J. Scholl, & A. Zuiderwijk (eds.); pp. 164–178). Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-57599-1_13

Teece, D. J. (2010). Chapter 16 - Technological Innovation and the Theory of the Firm: The Role of Enterprise-Level Knowledge, Complementarities, and (Dynamic) Capabilities. In B. H. Hall & N. B. T.-H. of the E. of I. Rosenberg (Eds.), Handbook of The Economics of Innovation, Vol. 1 (Vol. 1, pp. 679–730). North-Holland. https://doi.org/https://doi.org/10.1016/S0169-7218(10)01016-6 DOI: https://doi.org/10.1016/S0169-7218(10)01016-6

Teece, D. J. (2019). A capability theory of the firm: an economics and (Strategic) management perspective. New Zealand Economic Papers, 53(1), 1–43. https://doi.org/10.1080/00779954.2017.1371208 DOI: https://doi.org/10.1080/00779954.2017.1371208

Vial, G. (2023). Data governance and digital innovation: A translational account of practitioner issues for IS research. Information and Organization, 33(1), 100450. https://doi.org/https://doi.org/10.1016/j.infoandorg.2023.100450 DOI: https://doi.org/10.1016/j.infoandorg.2023.100450

Yadegaridehkordi, E., Nilashi, M., Shuib, L., Hairul Nizam Bin Md Nasir, M., Asadi, S., Samad, S., & Fatimah Awang, N. (2020). The impact of big data on firm performance in hotel industry. Electronic Commerce Research and Applications, 40, 100921. https://doi.org/https://doi.org/10.1016/j.elerap.2019.100921 DOI: https://doi.org/10.1016/j.elerap.2019.100921

Zhu, L., Gao, J., Fu, L., Yan, Y., & Lv, J. (2024). Application of Digital Technology to Chinese Traditional Furniture: A Review. Studies in Conservation, 69(7), 484–506. https://doi.org/10.1080/00393630.2023.2260629 DOI: https://doi.org/10.1080/00393630.2023.2260629

Zhu, S., Yu, T., Xu, T., Chen, H., Dustdar, S., Gigan, S., Gunduz, D., Hossain, E., Jin, Y., Lin, F., Liu, B., Wan, Z., Zhang, J., Zhao, Z., Zhu, W., Chen, Z., Durrani, T. S., Wang, H., Wu, J., … Pan, Y. (2026). Intelligent Computing: The Latest Advances, Challenges, and Future. Intelligent Computing, 2, 6. https://doi.org/10.34133/icomputing.0006 DOI: https://doi.org/10.34133/icomputing.0006