Quantitative Impact Assessment of Digital Payment Solutions on Small Business Revenue Panel Data Analysis From 1,200 U.S. SMES

Abstract

This study assessed the revenue impact of Digital Payment Solutions (DPS) using a longitudinal panel dataset of 1,200 U.S. small and medium-sized enterprises (SMEs) observed over 14,400 firm-period observations. The sample included SMEs from retail (30.0%), food service (20.0%), personal services (17.5%), professional services (16.7%), and repair-based industries (15.8%), with 70.0% employing fewer than 20 employees. Descriptive results showed mean logged revenue of 10.42 (SD = 0.88) and an average digital sales share of 49.6% (SD = 24.3%). DPS adoption increased from 68.0% in the early period to 85.0% by the final period. Reliability analysis confirmed strong internal consistency for the main constructs, including DPS intensity (α = 0.86), breadth (α = 0.79), and integration (α = 0.82). Two-way fixed effects regression models controlling for firm size, age, sector, location, channel mix, and competitive density indicated that DPS adoption was positively associated with revenue (β = 0.082, p < 0.001), corresponding to an average revenue increase of approximately 8.2% relative to pre-adoption levels. Usage intensity demonstrated the strongest effect (β = 0.214, p < 0.001). Payment breadth was also significant (β = 0.036, p = 0.010), while integration showed a moderate positive effect (β = 0.051, p = 0.020). Dynamic models confirmed revenue persistence (lagged revenue β = 0.641, p < 0.001) and maintained coefficient stability. The baseline model explained 42% of within-firm revenue variation (within R² = 0.42). Overall, findings provided robust quantitative evidence that DPS adoption, particularly when used intensively and integrated operationally, was positively associated with SME revenue performance in the U.S. context.