Internal capabilities, digital transformation, and SME export performance: Evidence from Vietnam’s manufacturing industries
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DOIhttp://dx.doi.org/10.21511/ppm.24(2).2026.37
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Article InfoVolume 24 2026, Issue #2, pp. 550-561
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Type of the article: Research Article
Abstract
Export upgrading has become a pressing concern for small and medium-sized enterprises (SMEs) in emerging economies. Digital transformation and artificial intelligence (AI) are often presented as fast-track solutions. Yet evidence on whether these technologies actually improve export performance remains inconclusive. In many industries, technology adoption does not automatically translate into stronger foreign market outcomes, especially where internal capabilities differ substantially.
The purpose of this study is to examine how digital transformation, AI adoption, innovation activity, labor productivity, and foreign direct investment (FDI) relate to SME export performance in Vietnam’s manufacturing sector over the period 2015–2023. Using industry-level panel data (63 observations) and pooled OLS and fixed-effects estimations, the analysis evaluates both internal capability factors and external structural influences.
The results reveal a clear pattern. Innovation is positively associated with export performance (β = 45.61, p < 0.01), and labor productivity exerts a significant positive effect (β = 24.57, p < 0.05). By contrast, digital transformation, AI adoption, and FDI do not display statistically significant direct effects in the baseline specification. The explanatory power of the model remains substantial (R² between 0.642 and 0.701), suggesting that capability-related factors account for a meaningful share of export variation across industries.
Taken together, the findings indicate that technology adoption alone is insufficient. In practice, SMEs cannot simply invest in digital tools and expect immediate export gains. Sustained innovation efforts and productivity-enhancing routines appear to be the more decisive foundations of export competitiveness.
- Keywords
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JEL Classification (Paper profile tab)F14, L25, O33
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References28
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Tables5
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Figures0
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- Table 1. Descriptive statistics of the study variables
- Table 2. Correlation matrix of explanatory variables
- Table 3. Pooled OLS regression results
- Table 4. Variance inflation factor (VIF) results
- Table 5. Results of White’s test for heteroskedasticity
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