Ni Kadek Mila Agustini
Management Study Program, Universitas Ngurah Rai, Indonesia

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Subjective Performance of Micro, Small, and Medium Enterprise: Financial Literacy, Financial Management, and Perceived Business Income Capacity Ade Maharini Adiandari; Ni Kadek Mila Agustini
Jurnal Ekonomi, Manajemen, dan Bisnis Vol. 4 No. 2 (2026): Jurnal Ekonomi, Manajemen dan Bisnis
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Kalibra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/emis.v4i2.684

Abstract

Micro, small, and medium-sized enterprises (MSMEs) operating in traditional production clusters often rely on owner-managers’ financial capability, daily financial routines, and income capacity to sustain business performance. However, evidence remains limited on how these factors are jointly associated with MSME performance in highly localized, owner-managed manufacturing clusters. This study examines the associations of financial literacy, financial management, and perceived business-income capacity with subjective performance among concrete sanggah manufacturing MSMEs in Desa Adat Kapal, Indonesia. Using a quantitative cross-sectional design, data were collected from the full population of 30 MSME owners through a structured questionnaire and analyzed using validity and reliability tests, classical assumption tests, and multiple linear regression. Financial literacy (β = 0.355, p = 0.014), financial management (β = 0.319, p = 0.042), and perceived business-income capacity (β = 0.354, p = 0.010) were positively associated with subjective MSME performance. The model accounted for 69.7% of the observed variance (adjusted R² = 0.662). These results provide context-specific evidence that owner-manager capability, financial routines, and perceived resource capacity are jointly relevant to performance perceptions. MSME-development programs may therefore combine financial-literacy education, simple bookkeeping and control practices, and income-capacity support, while future studies should verify these associations using objective, longitudinal, and multi-source data.