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Economy 
Vol. 12, No. 2, 26-39, 2025 

ISSN(E) 2313-8181: / ISSN(P) 2518-0118: 
DOI: 10.20448/economy.v12i2.6778 

© 2025 by the authors; licensee Asian Online Journal Publishing Group 

 
 

 
 
 
Role of digital tax platforms adoption in enhancing revenue generation and capital 
projects funding in emerging markets 

 
Muyiwa Emmanuel DAGUNDURO1  

Gbenga Ayodele FALANA2  

Israel S. AKINADEWO3  

Oluyinka Isaiah OLUWAGBADE4  

Gbenga Olanrewaju AKINBOBOYE5  

 

 
( Corresponding Author) 

 
1,2,4,5Department of Accounting, College of Social and Management Sciences, Afe Babalola University, Ado-Ekiti, 
Ekiti State, Nigeria. 
Email: dagundurome@pg.abuad.edu.ng  
Email: falanaga@pg.abuad.edu.ng  
Email: oluwagbadeoi@abuad.edu.ng 
Email: akinboboyegbenga@pg.abuad.edu.ng  
3Department of Accounting, College of Social and Management Sciences, Osun State University, Ilesa, Osun State, 
Nigeria. 
Email: omoeri_akinadewo@unilesa.edu.ng  

 
Abstract 

Tax revenue plays a significant role in funding government activities, especially in emerging 
economies where public investment is essential for infrastructure development and economic 
progress. This paper assessed the effectiveness of digital tax platforms, specifically electronic tax 
filing, automated tax payment systems, and blockchain-based tax solutions on revenue generation 
and capital projects funding in Nigeria. This study employed survey research design using 
primary data collected via structured questionnaires. The sample included 4,352 individuals 
comprising tax officials from FIRS, federal government officials in finance and infrastructure, and 
IT experts involved in digital tax platforms. A multistage sampling method, combining purposive 
and random techniques, was used to arrive at 384 respondents as sample size. Data analysis 
involved descriptive statistics and multivariable regression. This found that digital tax platforms 
which comprised of electronic tax filing, automated tax payment systems, and blockchain-based 
tax solutions had a positive and significant effects on revenue generation and capital projects 
funding in Nigeria. This study concluded that digital tax platforms significantly improve both 
revenue generation and capital project funding in Nigeria. It was therefore recommended that the 
government should expand and modernize its digital tax infrastructure nationwide to ensure 
broader adoption among taxpayers and administrators. 

 
Keywords: Automated tax payment systems, Blockchain-based tax solutions, Capital projects funding, Digital tax platforms, Electronic tax 
filing, Revenue generation. 

 

Contents 
1. Introduction ...................................................................................................................................................................................... 27 
2. Literature Review and Hypothesis Development ...................................................................................................................... 27 
3. Data and Methods ............................................................................................................................................................................ 31 
4. Data Analysis and Discussion of Findings .................................................................................................................................. 33 
5. Conclusion and Recommendations ............................................................................................................................................... 37 
References .............................................................................................................................................................................................. 37 
 

 
 
 
 
 
 
 
 
 
 

https://www.doi.org/10.20448/economy.v12i2.6778
https://orcid.org/0000-0002-1177-7101
https://orcid.org/0000-0001-8512-6769
https://orcid.org/0000-0002-2094-6843
https://orcid.org/0000-0001-8453-4728
https://orcid.org/0009-0003-3937-7235


Economy, 2025, 12(2): 26-39 

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Citation: DAGUNDURO, M. E., FALANA, G. A., AKINADEWO, I. S., 
OLUWAGBADE, O. I., & AKINBOBOYE, G. O. (2025). Role of digital 
tax platforms adoption in enhancing revenue generation and capital 
projects funding in emerging markets. Economy, 12(2), 26-39. 

10.20448/economy.v12i2.6778 
History:  
Received: 22 April 2025 
Revised: 8 May 2025 
Accepted: 5 June 2025 
Published: 16 June 2025 
Licensed: This work is licensed under a Creative Commons Attribution 

4.0 License  
Publisher:  Asian Online Journal Publishing Group 

 

Funding: This research did not receive any dedicated funding or financial 
assistance. 
Institutional Review Board Statement: Not applicable. 
Transparency: The   authors   confirm   that   the   manuscript   is   an   honest, 
accurate, and transparent account of the study; that no vital features of the study 
have been omitted; and that any discrepancies from the study as planned have 
been explained. The corresponding author can make the study data available 
upon reasonable request. 
Data Availability Statement: The corresponding author can make the study 
data available on reasonable request. 
Competing Interests: The authors declare that there is no competing interests. 
Authors’ Contributions: All authors equally participated in the conception and 
design of the study. They have all reviewed and approved the final version of the 
manuscript for publication. 

 

Contribution of this paper to the literature 
This study provides empirical evidence on the efficacy of digital tax platforms in enhancing government 
revenue and public investment in a developing country like Nigeria. It bridges the gap between 
technological innovation and public finance performance, contributing to both academic and practical 
understanding of digital transformation in tax administration. 

 
1. Introduction 

Tax revenue is a critical source of government financing, particularly in emerging markets where 
infrastructural development and economic growth heavily depend on public investment (Awotomilusi, Oso, 
Oluwagbade, & Dagunduro, 2023; Dagunduro, Abbood, Dakhil, & Falana, 2025). However, traditional tax 
collection methods in many developing economies, including Nigeria, are often characterized by inefficiencies such 
as tax evasion, corruption, inadequate record-keeping, and weak enforcement mechanisms (Okoye & Akenabor, 
2023). In response to these challenges, governments worldwide are increasingly leveraging digital tax platforms to 
enhance revenue generation, improve tax compliance, and streamline the allocation of funds for capital projects 
(Dakhil, Dagunduro, Abbood, & Falana, 2025; Falana, Dakhil, Abbood, & Dagunduro, 2024; World Bank, 2023). 
The adoption of digital tax platforms, including electronic tax filing (e-filing), automated tax payment systems, and 
blockchain-based tax solutions, has shown significant promise in reducing revenue leakages and increasing 
government tax revenues in various economies (Akinadewo, Kayode, Dagunduro, & Akinadewo, 2023; Aluko, 
Igbekoyi, Dagunduro, Falana, & Oke, 2022; Organisation for Economic Co-operation and Development (OECD), 
2023).  

In recent years, Nigeria has made considerable efforts to digitize its tax system, particularly through the 
introduction of the TaxPro-Max platform by the Federal Inland Revenue Service (FIRS) and various state-level e-
tax initiatives (Federal Inland Revenue Service (FIRS), 2023). These digital innovations aim to simplify tax 
compliance, expand the tax base, and increase voluntary tax payments. Empirical evidence suggests that digital tax 
systems improve revenue mobilization by reducing bureaucratic bottlenecks and encouraging tax compliance 
among individuals and businesses (Adebayo & Yusuf, 2024; Lawal, Igbekoyi, & Dagunduro, 2024). However, 
despite these advancements, Nigeria still faces challenges such as digital illiteracy, inadequate technological 
infrastructure, and taxpayer resistance to digital tax reforms (Eze & Nwankwo, 2024; Ige, Igbekoyi, & Dagunduro, 
2023). This study seeks to investigate the extent to which digital tax platforms have contributed to revenue 
generation and the financing of capital projects in Nigeria. 

While existing studies have examined the general relationship between taxation and economic development, 
limited research has focused on the specific impact of digital tax platforms on revenue mobilization and capital 
project funding in emerging markets (Agwu, Olanrewaju, & Okonkwo, 2024). Moreover, studies in developed 
economies have highlighted the efficiency of digital tax systems in improving revenue collection, but their 
applicability to developing economies with weaker technological infrastructure remains underexplored 
(International Monetary Fund (IMF), 2023). This study, therefore, aims to bridge this gap by providing empirical 
evidence on how digital tax platforms influence government revenue generation and capital expenditure in Nigeria. 

This paper contributes to the existing literature by assessing the effectiveness of digital tax platforms in 
enhancing tax compliance, increasing tax revenue, and improving capital project funding in Nigeria. By examining 
the challenges and opportunities associated with digital tax adoption, this study offers valuable insights for 
policymakers, tax administrators, and stakeholders in emerging markets. The findings are expected to inform 
strategies for optimizing digital tax infrastructure and leveraging technology for sustainable fiscal development. 
 

2. Literature Review and Hypothesis Development 
This section serves as a critical foundation for the research by summarizing and analyzing existing studies 

related to the research topic. This section identifies key theories, concepts, and empirical findings from prior 
research, thereby contextualising the study within the broader academic discourse. These hypotheses guide the 
research methodology and help in investigating the relationship between the variables under study. The section 
provides a clear rationale for the study’s objectives and how it contributes to advancing knowledge in the field. 
 

2.1. Theoretical Framework 
This study was rooted in the technology acceptance model (TAM) and public finance theory. The Technology 

Acceptance Model (TAM) is a framework used to assess how customers' attitudes influence the adoption of new 
technology. Developed by Davis (1989) at the University of Michigan's Graduate School of Business 
Administration, the model suggests that the likelihood of adopting technology is determined by two key factors: 
perceived ease of use and perceived usefulness (Davis, 1989). Recent studies have applied the technology acceptance 
model to examine the impact of digital tax platforms on revenue generation and capital expenditure. Wulandari 
and Dasman (2023) investigated the correlation between digital taxation systems, TAM, and taxpayer compliance, 

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with internet understanding as a mediating variable. The research found that the tax digitization system positively 
influences internet understanding, and the technology acceptance model significantly affects taxpayer compliance. 
However, the direct effect of the tax digitization system on taxpayer compliance was positive but not significant. 
Umar, Bappi, and James (2023) examined the effect of information and communication technology (ICT) on 
revenue generation in the Gombe State Internal Revenue Service. The study adopted a technology acceptance 
model as its theoretical framework. Through survey research and analysis using SPSS, the findings revealed that 
ICT infrastructure availability significantly enhances revenue collection efficiency. Abdulkadir, Bello, and Yusuf 
(2024) examined the impact of the unified theory of acceptance and use of technology (UTAUT) on tax 
professionals' responses to digitalization and automation in tax administration processes in Sub-Saharan Africa. 
The study found that automating tax administration processes positively affects revenue optimization.  

The technology acceptance model has proven to be highly relevant and applicable in understanding the 
adoption of digital tax platforms, particularly in the context of revenue generation and capital expenditures in 
emerging economies. In emerging markets, where digital infrastructure may still be developing, TAM provides 
valuable insights into how taxpayers and government agencies perceive the utility of digital tax systems. For 
instance, Wulandari and Dasman (2023) demonstrated that digital tax systems, when perceived as useful and easy 
to use, positively influence taxpayer compliance, which directly impacts revenue generation. Moreover, Umar et al. 
(2023) highlighted that the adoption of ICT and digital tax platforms by revenue services in Gombe State, Nigeria, 
significantly improved the efficiency of revenue collection. This efficiency is critical for capital expenditure funding, 
as increased tax revenue can be allocated to essential infrastructure and development projects. Despite its 
applicability, TAM has been critiqued for a few limitations. First, it largely focuses on individual perceptions and 
may overlook organizational and contextual factors, which can be critical in governmental and institutional 
settings (Venkatesh, Morris, Davis, & Davis, 2003). For example, in the case of capital expenditure, the decision to 
invest in digital tax systems may also depend on the political climate, regulatory frameworks, and government 
capacity, factors that TAM does not directly address (Venkatesh et al., 2003). Second, TAM assumes that user 
behavior is rational and uniform, which may not always be the case, especially in the context of emerging 
economies where there may be resistance to technological change or lack of awareness (Gefen & Straub, 2000). 
Finally, while TAM effectively captures the initial acceptance of technology, it often fails to account for the long-
term engagement and evolving user satisfaction with the technology (Venkatesh & Bala, 2008). These critiques 
suggest that while TAM provides valuable insights into technology adoption, it should be used in conjunction with 
other frameworks to capture the broader socio-economic and political dynamics that influence digital tax systems' 
impact on revenue generation and capital expenditures. 

Figure 1 illustrates the process by which individuals adopt and use new technology. It begins with external 
variables that influence two key perceptions: perceived usefulness (the belief that technology will improve 
performance) and perceived ease of use (the belief that using the technology will require minimal effort). These 
perceptions shape the user’s attitude toward using the technology, which in turn affects their behavioral intention 
to use it. Ultimately, this intention leads to the actual use of the system. TAM is widely used to understand and 
predict user behavior toward technology adoption. 

 

 
Figure 1. Technology Acceptance model (TAM). 

 
Public finance theory has evolved through the contributions of numerous economists and does not have a 

single specific founder. Early contributions to the field can be traced to Smith (1776) who in The Wealth of Nations 
laid the foundation for the theory of taxation and government expenditures, emphasizing the importance of 
equitable and efficient taxation in fostering national prosperity. Smith's ideas on taxation and government spending 
were pivotal in shaping the understanding of public finance. Later, Musgrave (1959) further developed the field by 
analyzing the role of government in resource allocation, stabilization, and redistribution of wealth, which is often 
considered the modern foundation of public finance theory. Musgrave's work helped establish a more 
comprehensive understanding of the government's role in managing the economy and distributing resources for 
societal welfare. Public finance theory focuses on how governments raise and allocate funds to meet the needs of 
the public, including revenue generation through taxes, expenditure management, and debt administration. This 
field addresses crucial issues such as the effectiveness of taxation policies, government budgetary allocations, and 
the efficiency of government spending to ensure societal well-being (Musgrave, 1959). The insights from both 
Smith and Musgrave continue to shape modern public finance practices, including the design and implementation 
of fiscal policies aimed at achieving economic stability and social equity. These contributions remain essential in 
understanding the role of government in financing public goods and services. 



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Several recent studies have applied public finance theory to examine the impact of digital technologies on 
revenue generation and capital expenditure. Okiakpe, Empere, and Etale (2024) investigated how public sector 
capital expenditure influences tax revenue generation, specifically petroleum profit tax (PPT), in Nigeria. Guided 
by public finance and Keynesian theories, the study utilized a quasi-experimental design and analyzed secondary 
data from the National Bureau of Statistics and the Central Bank of Nigeria. The findings revealed significant 
positive relationships between capital expenditures on road construction, power, and security with PPT, 
underscoring the role of public investment in enhancing tax revenues. Iorlaha (2024) conducted a conceptual and 
theoretical review of Nigeria's tax reforms and their impact on revenue generation. The study examined reforms 
such as the 2012 and 2017 National Tax Measures and the 2017 Voluntary Asset and Income Declaration Scheme 
(VAIDS), analyzing them through the lenses of the Laffer Curve Theory and Behavioral Economics Theory. The 
review found that while tax reforms positively influenced revenue generation, challenges like infrastructure deficits 
and digital literacy gaps persisted, suggesting the need for a comprehensive approach integrating policy, 
technology, and behavioral insights. Nwolu, Akani, and Ironkwe (2024) examined the impact of digital technologies 
on tax revenue in Nigeria. Employing a mixed-method research design, the study focused on the management staff 
of the Federal Inland Revenue Service in Abuja. The analysis indicated that digital technologies significantly 
influenced companies' income tax and capital gains tax revenues.  

Public finance theory is highly relevant in understanding the effect of digital tax platforms on revenue 
generation and capital expenditures in emerging economies. This theory emphasizes the role of government 
policies, taxation, and public expenditure in economic stability and development (Musgrave & Musgrave, 2022). 
Digital tax platforms, as an extension of modern public finance mechanisms, streamline tax collection, reduce 
leakages, and improve compliance, leading to increased government revenue (Tanzi, 2023). In emerging economies, 
where informal economic activities and tax evasion are prevalent, the adoption of digital tax platforms enhances 
transparency and minimizes revenue losses (Bird & Zolt, 2023). Moreover, increased tax revenue from digital 
platforms enables governments to fund critical capital expenditures, such as infrastructure, education, and 
healthcare, which are essential for economic growth and social welfare (Fjeldstad & Moore, 2023). Thus, public 
finance theory provides a strong foundation for evaluating how digitalization in tax administration supports 
sustainable revenue generation and efficient public spending in developing nations. 

Despite its relevance, public finance theory faces several critiques when applied to digital tax platforms in 
emerging economies. First, the theory assumes that increased tax revenue automatically translates into improved 
public services, but in many developing countries, corruption and inefficient governance hinder the effective 
allocation of resources (Gupta & Tareq, 2023). Second, while digital tax platforms enhance compliance, they may 
disproportionately burden small businesses and informal sector operators who lack the digital literacy or resources 
to comply, potentially leading to reduced economic participation (Moore, Prichard, & Fjeldstad, 2023). Third, 
public finance theory often overlooks the socio-political dynamics influencing tax policies, such as resistance from 
powerful interest groups that benefit from tax loopholes (Besley & Persson, 2023). These limitations suggest that 
while public finance theory provides valuable insights into the benefits of digital tax platforms, it must be 
supplemented with governance and institutional frameworks to ensure equitable and effective revenue utilization. 
 

2.2. Role of Digital Tax Platforms in Enhancing Revenue Generation and Capital Projects Funding 
The empirical studies collectively explore the relationship between tax revenue and government expenditure, 

particularly capital expenditure, across different national contexts. While they vary in scope and methodology, 
common patterns and divergences emerge regarding how tax income affects public investment and economic 
growth. Craig, Adetola, and Maminu (2020) investigated tax revenues and capital expenditures in the Nigerian 
economy, analyzing the effect of oil and non-oil tax revenues on capital expenditure using secondary data and 
linear regression. The study found that non-oil revenue had a significant positive impact on capital expenditure, 
suggesting the growing importance of diversifying revenue sources. In contrast, oil tax revenues and total tax 
revenues did not show a statistically significant relationship with capital expenditure, pointing to volatility and 
overdependence on oil-based revenues in Nigeria. Maharani, Romli, and Meiriasari (2021) studied the South 
Sumatra provincial government in Indonesia using multiple linear regression to examine the impact of local taxes, 
general allocation funds, and special allocation funds on capital expenditure. The findings showed that only general 
allocation funds positively influenced capital expenditure, while local taxes and special allocation funds did not. 
This suggests that intergovernmental fiscal transfers played a more critical role in driving public investment than 
local tax revenues in that region. Gurdal, Aydin, and Inal (2021) examined the broader fiscal dynamics in G7 
countries using panel causality tests. The study discovered a unidirectional causality from tax revenue to 
government expenditure and a bidirectional causality between economic growth and government expenditure. 
However, tax revenue did not cause economic growth in the time domain. In the frequency domain, a bidirectional 
causality was observed between tax revenue and economic growth, especially in the long run. This implies that tax 
policy is effective when aligned with broader macroeconomic goals, though its short-term effects can be limited.  

Alim, Setiyantono, and Zakiah (2021) focused on Indonesia over a 20-year period, applying the VAR model and 
Granger causality test to determine the relationship between tax income and government spending. The findings 
revealed a short-term relationship between the two variables but no long-term equilibrium. Moreover, government 
expenditure showed instability over time, and no strong causal link was found. This suggests potential 
inefficiencies in fiscal policy implementation and instability in revenue allocation patterns. Craig et al. (2020) and 
Maharani et al. (2021) both identified that certain revenue types (non-oil in Nigeria, general allocation funds in 
Indonesia) are more effective in financing capital expenditure, while other sources (oil revenues, special funds, and 
local taxes) show limited impact. Gurdal et al. (2021) and Alim et al. (2021) extended the discussion to include 
economic growth and broader expenditure patterns, revealing that the strength and direction of the relationship 
between tax revenue and spending vary significantly by region and economic stability. While Craig et al. (2020) 
and Maharani et al. (2021) showed positive but selective effects on capital expenditure, Alim et al. (2021) findings 
indicated instability and weak long-term alignment, and Gurdal et al. (2021) analysis suggested that fiscal 
relationships are sensitive to time horizons and economic maturity. 



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Malhotra, Mishra, and Vyas (2022) examined the Tax Increment Financing (TIF) model in Indian cities, 
especially within the Smart Cities Mission. The study emphasized how TIF could empower Urban Local Bodies 
(ULBs) to leverage future tax revenues and urban land value appreciation to finance infrastructure sustainably. The 
TIF model was presented as both theoretically and practically viable, particularly in contexts where current tax 
revenues are insufficient. Case studies from other countries supported the feasibility of adopting this innovative 
financing strategy in India. Akinola and Akinrinola (2023) analyzed the effects of tax revenue and infrastructure 
investment (using Gross Capital Formation) on economic growth in Nigeria. Using the ARDL model, they found a 
significant long-run relationship, especially highlighting the positive role of the Petroleum Profit Tax (PPT). 
However, Gross Capital Formation (GCF) and Company Income Tax (CIT) had no significant impact, suggesting 
inefficiencies in how these components contribute to growth. VAT was only marginally significant. Aisien, 
Otusanya, and Ala-Peters (2024) explored the relationship between tax revenue mobilization and infrastructural 
development in Nigeria using OLS regression. The study found that CIT, VAT, and Capital Gains Tax 
significantly contributed to infrastructure development, while PPT did not. This contrasts with Akinola and 
Akinrinola (2023) where PPT was a key growth driver. The findings underscore differences in tax effectiveness 
depending on whether the goal is GDP growth or physical infrastructure development. Aworetan, Alade, and 
Agbaje (2024) assessed the Granger causality between tax revenue, foreign aid, and capital expenditures in 
southwestern Nigerian states. The results showed that tax revenue had a significant causal relationship with 
capital expenditure, while foreign aid did not, suggesting that internally generated revenue, rather than external 
aid, drives sustained capital investment at the subnational level.  

Ajagun, Kehinde, and Jinadu (2025) evaluated the impact of oil and non-oil tax revenues on capital expenditure 
in Nigeria. Both revenue types were found to positively affect capital expenditure, supporting the idea that a 
diversified revenue base contributes to development financing. The study complements the findings of Aworetan et 
al. (2024) by reinforcing the link between tax revenues and capital spending. Aisien et al. (2024); Aworetan et al. 
(2024) and Aisien et al. (2024) confirm the significant effect of tax revenue on capital/infrastructure spending, 
reinforcing a pattern of reliance on internal revenue generation. Akinola and Akinrinola (2023) distinguish between 
infrastructure as a growth driver and tax revenue as a standalone growth input. Interestingly, while PPT was 
significant for economic growth, it was not significant for infrastructure in Aisien et al. (2024) highlighting a 
mismatch in fiscal transmission mechanisms. Malhotra et al. (2022) introduce a futuristic dimension to the 
conversation through the TIF model, offering an alternative to traditional tax-based funding. This study bridges 
the gap between theory and practice by integrating land value capture and municipal bonds, suggesting that 
innovative tools are essential when conventional tax systems fail to deliver sufficient surplus. While studies like 
Akinola and Akinrinola (2023) and Ajagun et al. (2025) focused on national-level analysis, Aworetan et al. (2024) 
and Malhotra et al. (2022) draw attention to state and municipal challenges. These studies emphasize that 
subnational governments often struggle with inadequate fiscal autonomy and highlight the potential of localized 
solutions like TIF or improving internal revenue mobilization. 

Amaglobeli, Crispolti, and Klemm (2023) investigated the effect of digital tax reporting on revenue 
mobilization in developing countries, employing a survey research design and analyzing the data using linear 
regression. The findings revealed a positive relationship between digital tax reporting and revenue mobilization, 
indicating that enhanced tax administration capabilities are facilitated by advanced reporting systems. Similarly, 
Mbise and Baseka (2022) investigated how digital tax reporting influences tax compliance, focusing on SMEs. 
Using a survey research design and regression analysis, the study found a significant positive effect of digital tax 
reporting on tax compliance, emphasizing improvements in efficiency and accuracy due to digital platforms. Edori 
(2023) focused on the ease of tax compliance with electronic tax services, such as e-registration, e-tax payment, and 
e-filing. Using data from 106 participants analyzed through Pearson Product-Moment Correlation, the study 
demonstrated that these e-tax services significantly improved the ease of tax compliance. Strong correlations were 
observed between e-registration, e-filing, and ease of compliance, indicating that these services have made it easier 
for taxpayers to manage their tax obligations. However, Abdulkadir and Alabede (2022) offered a nuanced 
perspective, revealing that although digital tax awareness and perceived ease of use positively affected compliance 
attitudes, poor service quality hindered overall compliance. This suggests that while digital tools can improve tax 
processes, the effectiveness of these tools is contingent upon their quality and user experience, particularly in 
informal sectors where digital literacy remains a barrier. Building on the theme of technological advancement, 
Manani and Mose (2024) emphasized the role of blockchain-related features, such as data immutability and 
information transparency, in strengthening revenue administration in Nairobi City County. The findings echoed 
the importance of secure and transparent data management in improving public efficiency. Similarly, Sutarman, 
Juliastuti, Yati, and Pasha (2025) focused specifically on blockchain’s application in tax administration, finding that 
it enhanced transparency, reduced data manipulation, and supported accurate tax reporting and smart contract-
enabled automation. 

Studies conducted by Craig et al. (2020) and Akinola and Akinrinola (2023) emphasized the growing 
importance of non-oil revenues for capital expenditure in Nigeria, yet the role of digital tax platforms in optimizing 
revenue generation remains underexplored. While these studies show a significant impact of non-oil taxes on 
capital spending, the potential for digital tax platforms to enhance the efficiency and transparency of tax collection 
processes, particularly in increasing non-oil tax contributions, is largely missing from the discussion. This research 
gap highlights the need to explore how digital platforms can transform tax administration to generate more stable 
and predictable revenue streams for capital projects. Furthermore, studies such as those by Aworetan et al. (2024) 
and Aisien et al. (2024) point to the significant role of internal revenue in funding infrastructure projects, yet they 
do not consider how digital tax platforms can enhance this process. Although these studies acknowledge the 
importance of tax revenues in capital expenditure, they do not delve into the specific mechanisms through which 
digital tax systems might improve revenue mobilization, particularly in a developing country context like Nigeria. 
This study intends to fill this gap by investigating how digital tax platforms can streamline tax reporting, improve 
tax compliance, and ultimately lead to more effective funding for capital projects. Finally, while studies by 
Amaglobeli et al. (2023) and Mbise and Baseka (2022) explore the broader impact of digital tax reporting on tax 



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mobilization and compliance, their focus is often on the national level or smaller enterprises like SMEs. However, 
little attention has been paid to the effect of digital platforms on the broader fiscal health of governments, 
particularly in funding capital projects through efficient revenue generation. This study seeks to bridge this gap by 
analyzing how digital tax platforms can be leveraged not only for improved tax compliance but also for financing 
critical public sector investments and capital projects, thus providing a comprehensive framework for using digital 
solutions in enhancing government revenue and infrastructure funding. Based on the above facts, it was therefore 
hypothesized that: 

Ho1: Digital tax platforms adoption has no significant effect on revenue generation and capital projects funding in Nigeria. 
 

2.3. Conceptual Framework 
Figure 2 illustrates the relationship between digital tax platforms (independent variable) and revenue 

generation and capital projects funding (dependent variable) while grounding the study in the technology 
acceptance model (TAM) and public finance theory as theoretical foundations. The independent variable, digital tax 
platforms, is measured through three key components: electronic tax filing, automated tax payment systems, and 
blockchain-based tax solutions. These elements represent advancements in tax administration aimed at improving 
efficiency, compliance, and transparency. The arrows indicate the influence of these digital tax solutions on revenue 
generation and capital project funding. The dependent variable, revenue generation and capital projects funding, 
reflects the outcomes of implementing digital tax systems, emphasizing increased tax revenue, better financial 
management, and improved public infrastructure funding. The Technology Acceptance Model (TAM) explains the 
adoption of digital tax systems by taxpayers and institutions. At the same time, public finance theory provides an 
economic perspective on how tax policies and digitalisation contribute to government revenue and expenditure 
efficiency. 

 

 
Figure 2. Conceptual framework. 

 

3. Data and Methods 
This study adopted a survey research design, utilizing primary data collected through the distribution of a 

structured questionnaire, which was developed in line with the study’s objectives. The survey research design was 
chosen for its effectiveness in collecting data from a large and diverse population, ensuring a broad representation 
of key stakeholders involved in the digital tax platform ecosystem. The target population consisted of 4,352 
individuals, including 3,145 tax officials from the Federal Inland Revenue Service (FIRS), as of December 31, 2023, 
based on FIRS data. Additionally, 638 federal government officials responsible for budgeting, financial planning, 
and infrastructure development, as well as 569 technology and IT experts involved in the development, 
implementation, and maintenance of digital tax platforms, were included. The technical expertise of these IT 
professionals is crucial for understanding the infrastructure, capabilities, and limitations of existing tax 
technologies and for identifying opportunities to enhance tax collection and revenue generation through 
technological innovations. By focusing on tax officials, government policymakers, and technology experts, the 
study aims to gather comprehensive insights from different perspectives, allowing for a well-rounded analysis of 
how digital tax platforms impact revenue generation and capital project funding. The inclusion of IT professionals 
is particularly significant as their expertise is vital for assessing the technological aspects of tax systems and 
identifying potential areas for improvement and innovation. The study used a multistage sampling approach that 
combined purposive and simple random sampling techniques. Purposive sampling was employed to target 
individuals or units directly or indirectly involved in digital platforms and tax revenue administration. Following 
this, simple random sampling was applied to assign a cluster sample. This approach helped reduce bias and 
enhanced the generalizability of the findings. To determine the appropriate sample size for the population, with a 
95% confidence level and a margin of error of 0.05, the researcher applied the Fisher, Laing, and Stoeckel (1983) 
formula. The formula used is. 

n = [Z² * p (1-p) / E²]. 
n = [1.962. 0.5(1-0.5)/0.052]. 
n = 384.16. 



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Where: n = The required sample size, Z = The Z-score corresponding to the desired confidence level (For a 
95% confidence level, Z ≈ 1.96), p = The estimated proportion of the population (0.5, chosen for maximum sample 
size) E = The margin of error. 

Table 1 presents the population of the study along with the sample proportion drawn from it. It outlines the 
total number of individuals or entities considered in the research and specifies how the sample was distributed or 
selected across different groups or categories, ensuring representativeness and reliability in the findings. 
 
Table 1. Population and sample proportion. 

Strata Targeted population Sample proportion 

Tax officials 3,145 277 
Federal government officials 638 56 
Technology and IT experts 569 51 
Total 4,352 384 

  

The study employed both descriptive and inferential analysis techniques for data evaluation. Descriptive 
statistics, including measures of central tendency (mean) and dispersion (standard deviation), were used to 
summarize the data. Additionally, ordinary least square (OLS) regression analysis was performed to assess the 
statistical significance of the relationships between the independent variables and the dependent variables. 
 

3.1. Reliability and Validity of Research Instrument 
In Table 2, reliability was assessed using Cronbach's Alpha. Revenue, capital, e-filling, autopayment and 

blockchain were shown by the Cronbach's Alpha test scores of 0.7986, 0.8008, 0.7893, 0.7922, and 0.7971, 
suggesting that the survey is suitable for high-stakes evaluations. Overall, the test's dependability was 83%. This 
indicates good internal consistency among the items. 
 
Table 2. Cronbach's alpha. 

Item Alpha 

Revenue generation 0.7986 
Capital projects funding 0.8008 
Electronic tax filing 0.7893 
Automated tax payment systems 0.7922 
Blockchain-based tax solutions 0.7971 
Overall test 0.8295 

  

3.2. Model Specification 
To create an econometric model where the independent variable is Digital Tax Platforms (which includes 

electronic tax filing, automated tax payment systems, and blockchain-based tax solutions), and the dependent 
variables are Revenue Generation and Capital Projects Funding. This study developed two separate models to 
reflect relationships. 
 

3.2.1. Econometric Model for Revenue Generation 
Revenue Generation (RG) is influenced by the adoption of Digital Tax Platforms (DTP), which include. 
Electronic Tax Filing (ETF). 
Automated Tax Payment Systems (ATPS). 
Blockchain-based Tax Solutions (BTS). 
The relationship was represented as: 

𝑅𝐺 =  𝛽0  + 𝛽1𝐸𝑇𝐹 +  𝛽2𝐴𝑇𝑃𝑆 +  𝛽3𝐵𝑇𝑆 +  𝜖 
Where: 
RG        = Revenue Generation (Measured by the total revenue generated from taxes). 
ETF      = Electronic Tax Filing (A measure of adoption or frequency of usage of e-filing). 
ATPS   = Automated Tax Payment Systems (A measure of usage or adoption level of automated systems). 
BTS      = Blockchain-based Tax Solutions (A measure of blockchain adoption in tax collection). 

β0          = Intercept (Constant term). 

β1, β2, β3 = Coefficients for each independent variable (Measures of impact of each digital platform on revenue 
generation). 

ϵ\epsilon = Error term (Captures unobserved factors affecting revenue generation). 
 

3.2.2. Econometric Model for Capital Projects Funding 
The model for Capital Projects Funding (CPF) was defined as a function for the adoption of Digital Tax 

Platforms (DTP). 

𝐶𝑃𝐹 = 𝛼0  + 𝛼1𝐸𝑇𝐹 +  𝛼2𝐴𝑇𝑃𝑆 + 𝛼3𝐵𝑇𝑆 +  𝜈 
Where: 
CPF   = Capital Projects Funding (Measured by the availability of funds for capital projects). 
ETF   = Electronic Tax Filing. 
ATPS = Automated Tax Payment Systems. 
BTS   = Blockchain-based Tax Solutions. 

α0       = Intercept (Constant term). 

α1, α2, α3 = Coefficients for each independent variable (Measures of the impact of each platform on capital 
projects funding). 

ν = Error term (Captures unobserved factors affecting capital projects funding). 
 



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3.3. Data Analysis Techniques 
This study employed both descriptive statistics (mean, median, variance, standard deviation, skewness, and 

kurtosis) and inferential statistics (regression, correlational analysis, and others) to analyse the data. 
 

4. Data Analysis and Discussion of Findings 
This section presents the analysis's findings, as well as their implications. 
 

4.1. Demographic Information  
Table 3 displays demographic statistics in percentages and frequencies according to the respondents' 

backgrounds. There were 384 responses. 25.52% of respondents were government officials, while 24.22% of the 
sample were tax officials. Technology/IT Experts are the smallest group at 22.40%. 27.86% of respondents did not 
specify their roles. On the other hand, the highest number of respondents (29.69%) work at the Federal Inland 
Revenue Service (FIRS), while 27.60% of participants are from agencies or organisations not explicitly listed. The 
Ministry of Finance accounts for 23.18%, and the Ministry of Budget and National Planning accounts for 19.53% of 
respondents. Similarly, 24.48% of the respondents had under 5 years of experience. While 19.53% had between 6 to 
10 years of experience. A good spread exists across the mid-experience ranges (11–20 years), with each range 
contributing around 20% of the sample. About 35.42% of respondents have over 20 years of experience, indicating a 
mature and experienced sample. Conversely, 26.04% of the samples were not too familiar with tax digitalization. 
While 25.78% of the samples were somewhat familiar with digital tax platforms, 23.96% were familiar with tax 
digitalization. 24.22% of respondents were experienced in using digital tax platforms.  

In the same vein, 50. 52% of the sample participated in the development, implementation, or maintenance of a 
digital tax platform, while 49.48% did not participate in the development of digital tax platforms. Also, 23.96% of 
the firms sampled fully implemented digital tax platforms. While 25% of firms sampled partially implemented tax 
platforms, 25.26% were in the process of implementation. However, 25.78% did not implement digital platforms 
yet. In terms of objectives, 17.97% of the sampled respondents stated that improving tax collection efficiency was 
the main goal of setting up digital tax platforms in their firms. While 16.41% of respondents asserted that 
enhancing revenue generation informed digitalization of tax in their firms. 15.63% of the respondents opined that 
to facilitate easier tax filing for taxpayers, informed digitalization tax platforms in their organisations. 15.89% of 
respondents indicated that improving transparency in tax processes formed the basis of tax platforms' 
digitalization. 20.57% of the sampled respondents stated that reducing corruption and fraud was the main objective 
of using digital tax platforms in their organisations. 13.54% of the respondents did not specify.  

Furthermore, 30.21% of the respondents emphasised that digital tax platforms did not contribute to the 
funding of capital projects. While 22.92% and 23.7% stated that digital tax platforms contributed to the funding of 
capital projects to a small and moderate extent. 23.18% of the sample stated that digital tax platforms contributed 
to the funding of capital projects to a great extent. In terms of challenges encountered during the use of the digital 
tax platform, 16.67% of the sampled respondents stated that they encountered a lack of technical infrastructure 
during digital tax platform adoption. 14.84% stated that poor internet connectivity contributed to the challenges of 
the digital tax platform. While 16.41% opined that limited training and capacity building was the bane of digital 
tax, 18.75% of the respondents suggested that resistance to change from employees or taxpayers accounted for 
these challenges. Again, 14.58% of the respondents stated there was limited awareness among taxpayers, while 
18.75% did not specify. However, 28.13% of the respondents believed the adoption of digital tax platforms would 
enhance the sustainability of funding for capital projects. While 31.77% of the respondents did not believe the 
adoption of digital tax platforms would enhance the sustainability of funding for capital projects, 40.10% of the 
respondents were indifferent.  
 
Table 3. Frequency distributions. 

Role Frequency Percent Cumulative percent 

1 93 24.22% 24.22% 
2 98 25.52% 49.74% 
3 86 22.40% 72.14% 
4 107 27.86% 100.00% 
Total 384 100.00%  
Organisation 
1 114 29.69% 29.69% 
2 89 23.18% 52.86% 
3 75 19.53% 72.40% 

4 106 27.60% 100.00% 
Total 384 100.00%  
Experience 
1 94 24.48% 24.48% 
3 75 19.53% 44.01% 
4 79 20.57% 64.58% 
5 136 35.42% 100.00% 
Total 384 100.00%  
Familiarity level 
1 100 26.04% 26.04% 
2 99 25.78% 51.82% 
3 92 23.96% 75.78% 
4 93 24.22% 100.00% 
Total 384 100.00%  
Participation 
1 194 50.52% 50.52% 



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2 190 49.48% 100.00% 
Total 384 100.00%  
Adoption status 
1 92 23.96% 23.96% 

2 96 25.00% 48.96% 
3 97 25.26% 74.22% 
4 99 25.78% 100.00% 
Total 384 100.00%  
Objective 
1 69 17.97% 17.97% 
2 63 16.41% 34.38% 
3 60 15.63% 50.00% 
4 61 15.89% 65.89% 
5 79 20.57% 86.46% 
6 52 13.54% 100.00% 
Total 384 100.00%  
Contribution level 
1 116 30.21% 30.21% 
2 88 22.92% 53.13% 
3 91 23.70% 76.82% 
4 89 23.18% 100.00% 
Total 384 100.00%  
Challenge 
1 64 16.67% 16.67% 
2 57 14.84% 31.51% 
3 63 16.41% 47.92% 
4 72 18.75% 66.67% 
5 56 14.58% 81.25% 
6 72 18.75% 100.00% 
Total 384 100.00%  
Belief level 
1 108 28.13% 28.13% 
2 122 31.77% 59.90% 
3 154 40.10% 100.00% 
Total 384 100.00%  

  

4.2. Descriptive Statistics 
In Table 4, the means range from 2.87 to 2.94, indicating that respondents generally provided moderate to 

slightly above-average ratings for the items under study. This indicates neutral to slightly positive perceptions of 
the listed digital tax platform features. In terms of dispersion, the standard deviations range from 0.70 to 0.77, 
showing moderate variability in responses. There is no extreme spread, which supports the reliability indicated by 
your Cronbach’s alpha. However, the minimum is 0, and maximums are all slightly below or equal to 5, which 
suggests respondents used scale-like measurement. 
 
Table 4. Descriptive statistics. 

Variable Obs. Mean Std. dev. Min. Max. 

Revenue generation 384 2.930 0.747 0 4.571 
Capital projects funding 384 2.924 0.769 0 5.000 
Electronic tax filing 384 2.879 0.704 0 4.285 
Automated tax payment systems 384 2.874 0.723 0 4.571 
Blockchain-based tax solutions 384 2.941 0.756 0 4.429 

 

4.3. Test of Variable 
The outcomes of both pre- and post-estimation tests to guarantee the reliability and validity of the study's 

findings for models 1 and 2, respectively. 
 

4.3.1. Model 1’s Correlation Analysis 
Table 5 shows the results of a pairwise correlation coefficient test performed on independent variables. The test 

results indicated a significant positive association between revenue generation and electronic tax filing, automated 
tax payment systems and blockchain-based tax solutions, respectively. While the coefficient values range from 
0.4523 to 0.5449 and a p-value of 0.0000, these findings suggest that as one part of digital tax infrastructure 
improves, others tend to follow suit. The moderate and significant correlations indicate that the variables are 
connected but not collinear, making them appropriate for further multivariate analysis. 
 
Table 5. Model 1’s correlation analysis. 

Variable 
Revenue 

generation 
Electronic tax 

filing 
Automated tax payment 

systems 
Blockchain-based tax 

solutions 

Revenue generation 1.0000    
Electronic tax filing 0.4523* 1.0000   
Automated tax payment 
systems 0.5449* 0.5064* 1.0000  
Blockchain-based tax 
solutions 0.4882* 0.5343* 0.4846* 1.0000 



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4.3.2. Model 1’s Post-Estimation Test 
Also, based on the results of the previous correlation investigation, the degree of multicollinearity in the data 

distribution was estimated using the variance inflation factor (VIF) analysis. In this regard, there is no 
multicollinearity since the mean VIFs of these variables are 1.53. Likewise, the constant variance of residuals with 
fitted values was evaluated using the Breusch-Pagan/Cook-Weisberg test. With a chi-square of 2.95 and a p-value 
of 0.0860, the results demonstrated significant evidence of homoscedasticity. To ascertain whether the variables 
have a normal distribution, the Skewness/Kurtosis tests for Normality test were employed. Since the p-value of 
0.3058 was more than the 0.05 significant level, the null hypothesis of normalcy was accepted. Similarly, the 
Durbin-Watson test, which has values between 0 and 4, finds autocorrelation in data distributions. A score of 
2.0617 implies marginally positive autocorrelation in residuals, whereas a value of 2 indicates no autocorrelation. 
According to the study's findings, autocorrelation does not exist.  
 
Table 6. Estimation test results. 

Test F-statistics P-value 

Breusch-Pagan / Cook-Weisberg test for Heteroscedasticity  2.95 0.0860 
 Skewness/Kurtosis tests for normality 2.37 0.3058 
Durbin-Watson D-statistic 2.0617 - 
VIF 1.53 - 

 

4.3.3. Model 2’s Correlation Analysis 
The findings of a pairwise correlation coefficient test on independent variables are displayed in Table 7. The 

test results showed that capital project funding was significantly positively correlated with automated tax payment 
systems, blockchain-based tax solutions, and electronic tax filing, respectively. These results imply that when one 
aspect of the digital tax infrastructure gets better, others tend to follow suit, even though the coefficient values 
range from 0.4523 to 0.5434 and the p-value is 0.0000. The variables are suitable for additional multivariate 
analysis since the moderate and significant correlations show that they are related but not collinear. 
Autocorrelation in data distributions is also detected by the Durbin-Watson test, which has values ranging from 0 
to 4. While a score of 2 denotes no autocorrelation, a score of 2.0617 suggests slightly positive autocorrelation in 
the residuals. The results of the investigation show that there is no autocorrelation.  

 
Table 7. Model 2’s correlation analysis. 

Variable 
Capital project 

funding 
Electronic tax 

filing 
Automated tax payment 

systems 
Blockchain-based tax 

solutions 

Capital project funding 1.0000    
Electronic tax filing 0.5434* 1.0000   
Automated tax payment 
systems 0.4715* 0.5064* 1.0000  
Blockchain-based tax 
solutions 0.4566* 0.5343* 0.4846* 1.0000 

 

4.3.4. Model 2’s Post-Estimation Test 
In Table 8, the variance inflation factor (VIF) analysis was used to quantify the degree of multicollinearity in 

the data distribution based on the findings of the prior correlation inquiry. Given that these variables mean VIFs 
are 1.53, multicollinearity is not present in this context. Similarly, the Breusch-Pagan/Cook-Weisberg test was 
used to assess the constant variance of residuals with fitted values. With a p-value of 0.6914 and a chi-square of 
0.16, the results showed strong evidence of homoscedasticity. The Skewness/Kurtosis tests for normality were 
used to determine whether the variables had a normal distribution. The null hypothesis of normalcy was accepted 
because the p-value of 0.6886 was greater than the 0.05 significant level. The Durbin-Watson test, which has 
values between 0 and 4, can also identify autocorrelation in data distributions. A score of 1.9685 indicates 
somewhat positive autocorrelation in the residuals, whereas a score of 2 indicates no autocorrelation. The 
investigation's findings indicate that autocorrelation does not exist.  
 
Table 8. Estimation test results. 

Test F-statistics P-value 

Breusch-Pagan / Cook-Weisberg test for Heteroscedasticity  0.16 0.6914 
 Skewness/Kurtosis tests for normality 0.75 0.6886 
Durbin-Watson D-statistic 1.9685 - 
VIF 1.53 - 

 

4.4. Digital Tax Platforms Adoption and Revenue Generation  
As shown in Table 9, the linear regression model, with revenue generation as the dependent variable (Y) and 

digital tax platform adoption as the independent variable (X), has an F-statistic of 76.26 and a p-value of 0.0000. 
The F-statistics are significant (p < 0.05), indicating that the model explains a significant portion of the variation in 
revenue generation. The R-squared of 0.376 (37.6%) indicates that 37.6% of the variance in revenue generation is 
explained by the model. Similarly, the coefficient of electronic tax filing is 0.153 (p = 0.005). This indicates that a 
one-unit increase in electronic filing relates to a 0.153-unit increase in income, assuming all other variables remain 
constant. The Automated Tax Payment Systems coefficient is 0.368 with a p-value of 0.000. This implies that A 
one-unit increase in automated tax payment results in a 0.368 rise in revenue. The Blockchain’s coefficient is 0.236 
with a p-value of 0.000. This suggests that a unit increase in blockchain use corresponds to a 0.236 increase in 
revenue creation. While automated tax payment systems had the strongest effect on revenue, electronic filing, 
automated payment, and blockchain solutions are significant contributors to revenue generation.  



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4.5. Digital Tax Platforms Adoption and Capital Projects Funding 
In Table 9, the F-statistics for the linear regression model with capital project funding as the dependent 

variable (Y) and digital tax platform adoption as the independent variable (X) is 72.99, with a p-value of 0.0000. 
The F-statistics are substantial (p < 0.05), suggesting that the model explains a large percentage of the volatility in 
income creation. The model explains 36.6% of the variance in revenue generation (R-squared = 0.366). Similarly, 
the coefficient for electronic tax filing is 0.376 (p=0.000). This means that a one-unit increase in electronic filing 
corresponds to a 0.376-unit gain in capital project funding, providing all other factors are unchanged. The 
Automated Tax Payment Systems coefficient is 0.229 and has a p-value of 0.000. This means that a one-unit 
increase in automated tax payment results in a 0.229 rise in capital project funding. The Blockchain’s coefficient is 
0.171 with a p-value of 0.000. This shows that a unit increase in blockchain adoption equates to a 0.171 rise in 
capital project funding. While electronic tax filing had the strongest effect on capital projects, all predictors are 
significant contributors to capital project funding. 
 
Table 9. Multivariable regression analysis. 

  Variable Coef. Std. err.       t P>t [95% Conf Interval] 

Revenue generation 
Electronic tax filing 0.153 0.054      2.840 0.005 0.047 0.259 
Automated tax payment systems 0.368 0.051      7.240 0.000 0.268 0.468 
Blockchain-based tax solutions 0.236 0.045      4.750 0.000 0.138 0.333 
_cons 0.739 0.150      4.920 0.000 0.444 1.035 
Capital project funding 

Electronic tax filing 0.376 0.056      6.710 0.000 0.266 0.486 
Automated tax payment systems 0.229 0.053      4.350 0.000 0.126 0.333 
Blockchain-based tax solutions 0.171 0.051      3.320 0.001 0.070 0.272 
_cons 0.679 0.156      4.350 0.000 0.372 0.985 
Equation Obs. Parms RMSE R-sq F P-value 
Revenue 384 4 0.592 0.376 76.260 0.000 
Capital 384 4 0.615 0.366 72.990 0.000 

 

4.6. Discussion of Findings 
This multivariable regression analysis conducted found that digital tax platforms which comprised of electronic 

tax filing, automated tax payment systems, and blockchain-based tax solutions had a positive and significant effects 
on revenue generation and capital projects funding in Nigeria. The study found strong evidence that when Nigeria 
uses digital tax technologies like online filing, automated payments, and blockchain, it sees improvements in 
collecting more taxes (revenue generation) and is better able to fund public infrastructure or development projects 
(capital projects funding). This suggests that embracing digital tax innovations can enhance the financial 
performance and public service delivery of the government. The findings align with Tivde (2024) who reported 
that electronic taxation platforms significantly boosted total tax revenue, particularly in Company Income Tax 
(CIT), Value Added Tax (VAT), and Capital Gains Tax (CGT). Similarly, Etale, Bingilar, and Ifurueze (2021) 
found that e-tax clearance certificates, electronic filing, and e-tax identification improved corporate income tax 
revenue, supporting the idea that digital tax systems enhance revenue collection. Uguagu, Ayodele, and Ajayi 
(2023) showed that electronic tax systems reduced tax evasion and increased revenue. Mas’ud, Mohammed, and 
Gimba (2023) emphasized that the strategic use of e-tax data by State Internal Revenue Services improved states' 
per capita internally generated revenue. Falana et al. (2024) found that digital payment platforms and technical 
expertise significantly improved tax compliance in the Southwest informal sector. Dakhil et al. (2025) concluded 
that both voluntary tax compliance and enforcement strategies enhanced tax revenue generation. Dagunduro et al. 
(2025) revealed that electronic systems such as e-filing, billing, and payments had a positive effect on informal 
sector tax compliance in Nigeria. However, contrasting evidence from Akinadewo et al. (2023) indicated that while 
qualified personnel and tax law enforcement improved revenue generation, ICT had an inverse and insignificant 
impact on revenue in Kano and Ekiti States. Similarly, Ashafoke and Obaretin (2023) found that although there was 
a positive relationship between tax e-commerce and revenue generation, it was statistically insignificant. Only 
digital advertising among various digital tax channels showed a significant positive effect, suggesting that not all 
digital tax innovations equally enhance revenue. 

The positive and significant impact of digital tax platforms such as electronic tax filing, automated payment 
systems, and blockchain solutions on revenue generation and capital project funding aligns with the technology 
acceptance model (TAM). This model posits that perceived usefulness and ease of use are critical factors 
influencing the adoption of new technologies. In the Nigerian context, the adoption of e-taxation systems has been 
associated with increased efficiency in tax collection and public financial management. For instance, Tivde (2024) 
found that the introduction of electronic taxation platforms led to a statistically significant increase in total tax 
revenue collection in Nigeria, highlighting the perceived usefulness of these technologies among tax officials and 
stakeholders. Furthermore, the ease of use associated with these digital platforms has facilitated their adoption. 
Ezeala, Opara, and Omaliko (2024) reported that electronic tax systems significantly improved revenue generation 
concerning personal and company income taxes in Anambra State, Nigeria. This improvement suggests that users 
find these systems user-friendly, which is consistent with the TAM's emphasis on ease of use as a determinant of 
technology adoption. 

From the perspective of public finance theory, which emphasizes efficient revenue generation and allocation for 
public goods and services, the findings showed the fiscal benefits of digital tax platforms. The integration of digital 
technologies into tax administration has enhanced transparency and accountability, key principles in public finance. 
According to Akinyosoye, Adesoga, Olubisi, and Nwankwere (2024) tax digitalization dimensions had a positive 
and significant effect on revenue generation, with online payment systems being the most effective predictor. This 
enhancement in revenue collection capacity enables better funding for capital projects and public services, aligning 
with the theory's focus on optimal resource allocation. Moreover, the adoption of blockchain-based tax solutions 



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contributes to reducing tax evasion and fraud, further strengthening the integrity of the tax system. The increased 
revenue from these digital platforms allows for more effective allocation of public resources towards infrastructure 
development, promoting economic growth and social welfare central goals of public finance theory. The successful 
implementation of digital tax technologies in Nigeria is both behaviorally justified, as per the TAM, and fiscally 
sound, in line with public finance theory. The adoption of these platforms reflects user acceptance driven by 
perceived benefits and leads to improved financial outcomes, supporting efficient governance and public service 
delivery. 
 

5. Conclusion and Recommendations 
This study employed multivariable regression analysis to examine the impact of digital tax platforms 

comprising electronic tax filing, automated tax payment systems, and blockchain-based tax solutions on revenue 
generation and capital project funding in Nigeria. The results revealed a positive and statistically significant 
relationship between the adoption of these digital tax innovations and improved government revenue as well as the 
capacity to finance infrastructure and development projects. The study underscores the transformative potential of 
digital technologies in strengthening public financial management and enhancing service delivery. The study 
concluded that digital tax platforms significantly improve both revenue generation and capital project funding in 
Nigeria. Technologies such as e-filing, automated payment systems, and blockchain increase tax collection 
efficiency, reduce leakages, and promote accountability in public finance. These innovations enable the government 
to mobilize more domestic resources and allocate them more effectively towards development goals. It was 
therefore recommended that the government should expand and modernize its digital tax infrastructure 
nationwide to ensure broader adoption among taxpayers and administrators. Secondly, continuous training and 
capacity development programs for tax officials and IT staff should be institutionalized to optimize the use of 
digital platforms. Furthermore, clear guidelines on the implementation and oversight of digital tax platforms, 
especially blockchain systems, should be enacted to boost trust and compliance. Lastly, efforts should be intensified 
to sensitize the public to the benefits and use of digital tax systems to foster voluntary compliance. 

This study provides empirical evidence on the efficacy of digital tax platforms in enhancing government 
revenue and public investment in a developing country context. It bridges the gap between technological 
innovation and public finance performance, contributing to both academic and practical understanding of digital 
transformation in tax administration. The integration of blockchain technology into the tax ecosystem is 
highlighted as a key innovation that strengthens transparency and accountability. The findings reinforce the 
technology acceptance model (TAM) by showing that perceived usefulness and ease of use drive the adoption of 
digital tax platforms. It supports the public finance theory, demonstrating how improved revenue mechanisms 
enable efficient public spending and infrastructure development. For practitioners, the study advocates for an 
increased role of digital accounting tools and automation in public sector financial management, ensuring accuracy, 
real-time reporting, and enhanced audit trails. Policy makers are encouraged to prioritize digital transformation 
policies in tax administration, recognizing its role in improving fiscal sustainability and development financing. 
There is a need for collaborative policy formulation involving tax authorities, IT experts, and financial planners to 
create an ecosystem that supports innovation and compliance. Policies should also promote inter-agency data 
integration and interoperability to ensure seamless information flow and improved service delivery. 

Future research could investigate the sector-specific impacts of digital tax platforms on different industries 
(e.g., manufacturing, agriculture, digital economy). Cross-country comparisons in sub-Saharan Africa can offer 
deeper insights into the regional effectiveness of digital tax technologies. Tracking changes over time would help 
in understanding the long-term effects of digital tax implementation on fiscal performance and economic 
development. Further studies could explore how digital platforms influence taxpayer attitudes, trust, and 
compliance behavior. 
 

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