Determinants of MSME Income in Padang City: An Economic Perspective
DOI:
https://doi.org/10.54099/ijmdb.v5i1.1825Keywords:
Income, Business Capital, Education, Digital TechnologyAbstract
This study aims to examine the factors influencing the income of Micro, Small, and Medium Enterprises (MSMEs) in Padang City from an economic perspective. The variables analyzed include business capital, education level, and digital technology as the main determinants of income. In addition, digital technology is also positioned as a mediating variable that links the effects of business capital and education on income.
This research employs a quantitative approach using multiple linear regression analysis and mediation testing through the Sobel test. Data were collected from 200 MSME actors in Padang City using questionnaires. The results show that business capital and education have a positive and significant effect on income. Digital technology is also proven to have a significant influence and acts as a mediator in the relationship.
The findings indicate that the increase in MSME income is not only determined by traditional economic factors but also by the level of digital technology utilization. Therefore, improving digital literacy and access to technology is an important aspect in strengthening MSME competitiveness.
References
Asian Development Bank. (2022). Financing small and medium enterprises in Asia. ADB Publishing.
Agasta, P. M. V. E., & Gorda, E. S. (2024). The impact of capital and innovation on MSME income. International Journal of Economics Development Research.
Becker, G. S. (2015). Human capital: A theoretical and empirical analysis, with special reference to education (3rd ed.). University of Chicago Press.
Beck, T., Demirgüç-Kunt, A., & Maksimovic, V. (2015). Financial and legal constraints to growth: Does firm size matter? Journal of Finance, 60(1), 137–177.
Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2016). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 40(1), 1–14. https://doi.org/10.25300/MISQ/2016/40:1.03
Dhiman, P., Ma, J., Qi, C., Bullock, G., Sergeant, J. C., Riley, J. R., & Collins, G. S. (2023). Sample size requirements for developing prediction models. BMC Medical Research Methodology, 23, 188.
Hartmann, D., et al. (2015). Linking economic complexity, institutions and income inequality. arXiv preprint.
Jenkins, D. G., & Quintana-Ascencio, P. F. (2020). A solution to minimum sample size for regressions. PLOS ONE, 15(2), e0229345.
https://doi.org/10.1371/journal.pone.0229345
Kline, R. B. (2021). Principles and practice of structural equation modeling (5th ed.). Guilford Press.
Lokuge, S., & Duan, S. X. (2023). Exploring the enablers of digital transformation in SMEs. arXiv preprint. https://arxiv.org/abs/2302.12506
Mankiw, N. G. (2018). Principles of economics (8th ed.). Cengage Learning.
OECD. (2021). The digital transformation of SMEs. OECD Publishing. https://doi.org/10.1787/bdb9b9c7-en
OECD. (2024). SME and entrepreneurship outlook 2024. OECD Publishing. https://doi.org/10.1787/6f3c4b7a-en
OECD. (2026). Financing SMEs and entrepreneurs. OECD Publishing.
Romer, P. M. (2018). Endogenous technological change. Journal of Political Economy, 98(5), S71–S102.
Suryani, E., & Hendryadi. (2020). Digital literacy and MSME performance in Indonesia. Journal of Business and Economics, 10(3), 120–130.
Tambunan, T. (2019). Recent evidence of the development of micro, small and medium enterprises in Indonesia. LP3ES.
Todaro, M. P., & Smith, S. C. (2020). Economic development (13th ed.). Pearson.
World Bank. (2020). SME finance and development report. World Bank Group.
World Bank. (2022). Digital economy for SMEs: Global report. World Bank Publications.
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Copyright (c) 2026 Yulina Eliza, Yass Andria, Deltri Apriyeni, Evi Adriani
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