Aptisi Transactions on Technopreneurship (ATT)
Vol 8 No 3 (2026): November

Scaling Up Micro Enterprises Key Success Factors and AI-Driven Development Model

Hanung Eka Atmaja (Tidar University)
Sofyan Ashari Nur (Tidar University)
Dinar Melani Hutajulu (Tidar University)
Khairul Ikhwan (Tidar University)
Suddin Lada (Universiti Malaysia Sabah)
Raina Dewi Aldianti (Tidar University)



Article Info

Publish Date
30 Sep 2026

Abstract

In the development of MSMEs, there is a gap: micro businesses dominate in terms of quantity, but there has been no significant increase in those that have scaled up to become small or medium-sized businesses. Therefore, this study aims to analyze key factors for increasing the scalability of micro businesses and to examine an artificial intelligence-based micro business development model for upgrading to small and medium-sized businesses. This study employs a mixed-method approach with an explanatory sequential design. The population includes micro-enterprises in four regions with the highest number of SMEs: West Java, Central Java, East Java, and Jakarta, totalling 2,387,288 micro enterprises. A sample of 385 respondents was selected using a sampling technique. Proportionate stratified random sampling was used to ensure a representative sample distribution across each province. Qualitative data were collected through purposive sampling with two groups of micro businesses: those that successfully scaled up and those that did not. The analysis results indicate that sustainable leadership and absorptive capacity significantly influence the scalability of micro businesses, while innovation capacity does not. Furthermore, it was found that AI adoption can strengthen the influence of innovation capacity on the scalability of micro businesses. Additionally, the findings indicate that there are six strategic steps to enhance the scalability of AI-based micro businesses awareness, digital readiness assessment, simple AI pilot project, scaling up digital systems, partnerships and ecosystems, and monitoring and feedback loops.

Copyrights © 2026






Journal Info

Abbrev

att

Publisher

Subject

Humanities Computer Science & IT Economics, Econometrics & Finance Education Social Sciences

Description

APTISI Transactions on Technopreneurship (ATT) is an international triannual open access scientific journal published by  Pandawan Sejahtera Indonesia. ATT publishes original scientific researchers from scholars and experts around the world with novelty based on the theoretical, experimental, ...