Digital financial inclusion in micro enterprises: understanding the determinants and impact on ease of doing business from World Bank survey

The paper examines digital financial inclusion (DFI)—low-cost digital access to financial services for underserved groups—and its importance for micro-enterprises in developing contexts, especially India. Prior literature highlights DFI’s role in poverty reduction, reducing inequality, supporting SME entrepreneurship and household consumption, and improving access to payments, credit, insurance, and record-keeping via internet and mobile technologies. In India, major policy and infrastructure initiatives (Aadhaar, UPI, direct benefit transfers, payment banks, fintech) have accelerated digital payments adoption post-demonetization. Despite increased account ownership, dormancy and low usage persist. This study investigates: (1) whether access to and use of digital finance are associated with fewer perceived business obstacles (ease of doing business) among micro-enterprises; and (2) which digital resource capabilities and firm/owner characteristics determine DFI. Four null hypotheses are tested regarding differences in perceived obstacles (H1–H2) and the effects of digital resource capability and firm/owner characteristics on DFI (H3–H4).

The review links access to finance and business performance, noting DFI’s potential to alleviate constraints, foster entrepreneurship, and affect inequality and productivity. ICT (internet, mobile) has transformed financial services delivery and inclusion, with evidence across countries of enhanced access and efficiency. Firm and owner attributes (size, age, education, gender, experience) influence financial inclusion and financial decision-making. The paper formulates four null hypotheses: H1: No difference in perceived business obstacles between micro firms with and without access to digital finance; H2: No difference in perceived business obstacles between micro firms that use and do not use digital finance; H3: Digital resource capability does not significantly affect DFI among micro firms; H4: Firms’ and owners’ characteristics do not significantly affect DFI among micro firms.

Data source: World Bank Enterprises Survey of Micro Firms (ESM) 2022 for India; data collected Dec 2021–Mar 2022 by Nielsen (India) Pvt. Ltd. Targeted registered micro-enterprises (<5 employees) across manufacturing, construction, trade, transport/storage, accommodation and food services. Stratified random sampling; two-stage collection (phone screening/scheduling, then face-to-face interviews with owners/managers/directors). Sample size n=998. Instrument: structured questionnaire on firm demographics, activities, and perceived business obstacles. Variables: DFI measured via two binary dependent variables: (1) uses digital payments (access); (2) uses digital payments to pay utility bills (usage). Explanatory variables grouped as: Digital resource capability (internet access; computers/tablets); Firm and owner characteristics (firm age; owner gender; owner education: secondary, diploma, bachelor or above (vs. primary or less); owner household size; top manager experience). Descriptive statistics (Table 1) include: 66% report access to digital financial systems; among 614 responding on usage, 85% use digital payments to pay utility bills; 43% use computers/tablets; 75% have internet; mean firm age 14.11 years; 9% have female owners; education shares: primary or less 18%, secondary 33%, diploma 34%, bachelor+ 14%; mean household size 4.91; mean manager experience 12.34 years. Analytical approach: Descriptives, chi-square, and ANOVA to compare perceived business obstacles between groups with/without access and users/non-users of digital finance. Binary logistic regression models estimate determinants of DFI for access and usage outcomes. Model: logit(P)=α+βX with cumulative logistic function; marginal effects (dy/dx) computed in Stata. Independent variables include digital resources and firm/owner profiles.

Descriptives: 66% of 998 micro-enterprises report access to digital financial systems; among 614 with usage data, 85% use digital payments for utility bills. 43% have computers/tablets; 75% have internet. ANOVA on perceived business obstacles (Table 2): - Access to digital finance (Yes vs No): Significant differences indicate fewer obstacles among those with access in several regulation domains: tax administration (F=4.349, p=0.037); business licensing and permits (F=13.153, p<0.001); labor regulations (F=10.303, p=0.001). Market externalities: crime, theft and disorder lower for access group (F=16.368, p<0.001). Practices of competitors perceived as a greater obstacle among access group (F=4.393, p=0.036). Access to land shows higher perceived obstacle among access group (F=3.056, p=0.081). H1 is partially rejected. - Usage of digital finance (Yes vs No): Under business regulation, users report fewer obstacles: tax rates (F=3.091, p=0.079), tax administration (F=4.902, p=0.027), business licensing and permits (F=11.573, p=0.001). No significant differences for market externalities. Access to land shows higher perceived obstacle among users (F=3.023, p=0.083). H2 is partially rejected. Logistic regression determinants (Table 3): - Access to digital finance model (Pseudo R2=0.090; Log likelihood=-473.306; LR chi2=93.540, p<0.001): Internet strongly increases access (β=1.539, p<0.001; dy/dx=+0.300, p<0.001). Computers/tablets associated with lower access (β=-0.404, p=0.029; dy/dx=-0.079, p=0.028). Firm age positive (β=0.032, p=0.004; dy/dx=+0.006, p=0.003). Female ownership increases access (β=0.756, p=0.066; dy/dx=+0.148, p=0.065). Education positive: secondary (β=0.551, p=0.026; dy/dx=+0.113, p=0.029); bachelor+ (β=0.916, p=0.005; dy/dx=+0.178, p=0.004). Household size negative (β=-0.129, p=0.008; dy/dx=-0.025, p=0.007). Manager experience not significant. - Usage of digital finance model (Pseudo R2=0.122; Log likelihood=-204.032; Prob>chi2<0.001): Internet positive (β=0.904, p=0.003; dy/dx=+0.101, p=0.003). Owner education (diploma) positive (β=0.978, p=0.022; dy/dx=+0.099, p=0.041). Manager experience positive (β=0.064, p=0.003; dy/dx=+0.007, p=0.002). Other education categories and demographics largely not significant. Interpretation: Access to the internet, higher education, and experience are key enablers of DFI. Access and usage are associated with fewer perceived regulatory obstacles, suggesting improvements in ease of doing business. Findings partially reject H3 (digital resources matter) and contradict H4 (firm/owner characteristics matter).

The results indicate that digitally included micro-enterprises perceive fewer regulatory barriers (tax administration, licensing/permits, labor regulations), aligning with the premise that digital channels streamline compliance and reduce cash-handling risks (lower crime/theft obstacles). The increased perceived competition among digitally included firms may reflect greater market visibility and exposure to formalized competitive practices. Determinants analyses show that internet access is foundational for both access and usage of digital finance; education enhances awareness and capability to adopt digital tools; manager experience supports effective usage in operations. The negative association with household size for access may reflect tighter household resource constraints or preferences. The unexpected negative association of computers/tablets with access likely reflects smartphone-centric digital banking in micro-enterprises. Overall, the findings support the study’s research question: digital resource capability and specific owner/firm attributes drive DFI, and DFI is linked to improved ease of doing business for micro-enterprises in India.

India’s policy and technological ecosystem (e.g., UPI) has accelerated digital payments. This study shows that micro-enterprises with access to or using digital finance perceive fewer business obstacles, particularly in regulatory domains. Determinants analyses reveal that internet access, owner education, and managerial experience significantly promote DFI; older firms and female ownership are more likely to access digital finance, while larger household size reduces access. Both models highlight internet access, education, and experience as instrumental drivers. The study recommends encouraging DFI adoption via demonstrations and training, expanding affordable digital resources, and strengthening financial literacy and supportive policies to enhance micro-enterprises’ ease of doing business. Future work should incorporate theoretical models and qualitative inquiry (e.g., behavioral factors of owners) alongside firm and owner profiles to deepen understanding of DFI adoption.

The study relies on secondary survey data (World Bank ESM 2022), constraining variable selection for business obstacles and limiting inclusion of behavioral constructs. Cross-sectional design restricts causal inference. Future studies should integrate theoretical frameworks, richer indicators, and in-depth interviews to capture behavioral aspects of micro-entrepreneurs as determinants of DFI.