Digital Adoption and Labor Productivity in Thai Enterprises: A Quantile Regression Analysis from the World Bank Enterprise Survey 2025
Abstract
This study examines the relationship between digital technology adoption and labor productivity among Thai enterprises, using the World Bank Enterprise Survey (WBES) Thailand 2025 (813 firms). We estimate log labor-productivity equations using OLS and Quantile Regression (Q10–Q90), decomposing digital adoption into three pillars: Infrastructure (D1), Transaction (D2), and Integration (D3). The aggregate Digital Total Score is positively associated with labor productivity (β = 0.119, p < 0.01), equivalent to a 12.6 percent difference per one-point increase. This association varies across the productivity distribution: lower-to-middle quantile firms (Q10–Q50) associate more strongly with basic infrastructure, while upper-quantile firms (Q75–Q90) associate more strongly with integration — a digital-ladder-type pattern interpreted cautiously given the cross-sectional data. The interaction between the digital score and firm size is negative and significant (β = −0.083, p < 0.01), indicating a comparatively stronger association among smaller firms. As the data are cross-sectional, findings should be read as associations rather than causal effects. Results carry policy relevance for Thailand's digital transition, suggesting differentiated support instruments matched to firms' productivity position may outperform a uniform approach. The paper contributes by decomposing digital adoption into three pillars and documenting heterogeneous digital-productivity associations across the distribution.
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