









































Pa
ge

 
1



Pa
ge

 
63

American Journal of  Smart 
Technology and Solutions (AJSTS)

Impact of  Financial Technology (FinTech) on Accounting Efficiency and Supply Chain 
Performance in Nigeria’s Logistics Sector
Akanbi, Taibat Adenike1, Gbadegesin Adeolu Emmanuel2*

Volume 4 Issue 2, Year 2025
ISSN: 2837-0295 (Online)

DOI: https://doi.org/10.54536/ajsts.v4i2.5819
https://journals.e-palli.com/home/index.php/ajsts

Article Information ABSTRACT

Received: July 30, 2025

Accepted: September 01, 2025

Published: September 19, 2025

Using annual time-series data between 2000 and 2024, the study follows an Autoregressive 
Distributed Lag (ARDL) modeling strategy to estimate both short-run dynamics and long-
run relationships between Financial Technology (FinTech), Accounting Efficiency and 
Supply Chain Performance within Logistics Sector in Nigeria. The value of  electronic 
financial transactions is used as a proxy of  FinTech adoption, financial reporting quality 
indices as a proxy of  accounting efficiency, and composite logistics indicators as a proxy 
of  supply chain performance. Descriptive analysis shows that there is a lot of  variation 
in FinTech uptake but not much variation in accounting practices. Cointegration of  the 
variables is supported by the ARDL bounds test. The long-run estimates show that the 
efficiency of  FinTech and accounting have a statistically significant positive impact on 
logistics performance, with coefficients of  0.42 and 0.35, respectively. In the short-run, the 
efficiency gains of  accounting have an immediate effect, and the benefits of  FinTech are 
felt in a more long-term way. The error correction term implies a high rate of  convergence 
to equilibrium (adjustment speed of  45%). Model robustness is validated by diagnostic 
tests. The results suggest that FinTech usage and effective financial management are 
mutually supportive factors of  supply chain efficiency in Nigeria. Based on this, companies 
and policy makers ought to intensify the use of  digital financial instruments and enhance 
accounting functions to promote robust and competitive logistics systems.

Keywords
Accounting Efficiency, FinTech, 
Logistics, Supply Chain Finance, 
Supply Chain Performance

1 Department of  Accounting, Faculty of  Management Sciences, Ladoke Akintola University of  Technology Ogbomoso, Nigeria
2 Department of  Transport Management, LAUTECH Open and Distance Learning, Nigeria
* Corresponding author’s e-mail: aegbadegesin@lautech.edu.ng

INTRODUCTION
Financial technology (FinTech) is changing how 
companies handle payments, financing, and financial 
records by making them faster, more error-free, and 
more accessible (Lee & Shin, 2018). FinTech solutions 
like mobile money, supply chain finance, and digital 
invoicing enhance the efficiency of  operations in logistics 
by automating payments, increasing transparency, and 
cutting lead times (Liu et al., 2025). Such technologies 
require robust accounting systems that can process digital 
transactions quickly and accurately (Ibrahim & Yusuf, 
2025). Accounting efficiency - which is characterized by 
the pace and accuracy of  financial reporting - facilitates 
the successful application of  FinTech tools by providing 
transparent and coherent documentation of  both internal 
and external logistics coordination (Chukwuka & Eze, 
2018). Collectively, FinTech and accounting efficiency 
are key drivers of  supply chain performance, indicating 
responsiveness, cost-effectiveness, and reliability in 
logistics operations. When logistics companies implement 
FinTech platforms, their performance is usually 
determined by the extent to which these tools can be used 
to enhance delivery, minimize the time lag in transactions, 
and help to manage inventory (Zhang et al., 2024).
Despite this, the logistics sector in Nigeria is still grappling 
with efficiency problems with the country ranking 110th 
in the World Bank Logistics Performance Index in 2018 
and an overall score of  2.53, which indicates poorly 
developed supply chain infrastructure and processes 
(World Bank, 2018). Although the use of  FinTech in 

Nigeria has been growing, many logistics firms still 
experience delays in reconciliation, lack of  transparency 
in the history of  transactions, and ineffective integration 
of  digital tools and accounting systems (Osei-Tutu & 
Agyemang, 2023). Small and medium logistics firms are 
especially unable to adopt extensive digital solutions, 
and many of  them rely on fragmented or manual 
accounting (Egwuonwu et al., 2023). Furthermore, the 
long-run effects of  FinTech and accounting efficiency 
on the performance of  logistics in Nigeria have not been 
sufficiently tested by econometric models. Most of  the 
literature available focuses on financial innovation or 
operational performance separately. The paper addresses 
this research gap by examining the connection between 
FinTech and accounting efficiency in influencing supply 
chain performance in Nigeria using recent time-series 
data and ARDL modeling.
 
Hypotheses of  the Study
Two hypotheses were tested in this study: 

H01: FinTech adoption has no positive impact on 
accounting efficiency; 

H02: FinTech adoption has no positive impact on 
supply chain performance. 

LITERATURE REVIEW
FinTech refers to the financial technological developments 
that promote the smooth, safe, and efficient financial 
transactions. It encompasses mobile payments, digital 
lending, blockchain, and other IT-enabled financial 



Pa
ge

 
64

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025

services (Arnaut & Bećirović, 2023; Suryono et al., 
2020). FinTech has revolutionized the banking industry 
in the world, making it cheaper and more accessible 
(Martinčević et al., 2020; Elsaid, 2023). The rapid growth 
of  FinTech in sub-Saharan Africa and in Nigeria, in 
particular, is explained by the high saturation of  mobile 
phones and unmet financial needs (Giglio, 2021; Kola-
Oyeneyin et al., 2021). Nigeria has developed one of  the 
largest FinTech industries on the continent, facilitating 
digital payments and credit to millions of  people (Koffi, 
2016; Kyari & Akinwale, 2020). In 2023, 2.24 quadrillion 
in total electronic payments was facilitated in Nigeria, 
which means that digital finance is highly utilized. There 
is a tendency to relate the emergence of  FinTech to 
improved firm performance. To illustrate, Okoye et al. 
(2024) found that the use of  FinTech positively and 
significantly contributed to the development of  Nigerian 
SMEs and the profitability of  banks due to an extended 
customer base. FinTech also enhances financial inclusion 
and flexibility, which have an indirect positive impact on 
supply chains (Siano et al., 2020; Asamoah & Owusu-
Agyei, 2020).
In a complex supply chain, efficient accounting systems 
are essential to organizational performance (Hakkak & 
Ghodsi, 2015). Accounting efficiency suggests prompt 
and correct financial data and efficient billing, payment, 
and reporting procedures. These processes have been 
found to be enhanced by FinTech tools. Harsono and 
Suprapti (2024) emphasize that FinTech-powered 
solutions (e.g. mobile banking, e-invoicing) can transform 
financial efficiency by making operations simpler, 
cutting costs, and improving competitiveness. Online 
invoicing and payment systems eliminate paperwork 
and mistakes, enabling companies to spend more time 
on the actual logistics work. Previous research observes 
that implementing computerized accounting systems 
and cloud-based financial tools can enhance the SMEs 
record-keeping and financial decision-making remarkably 
(Akanbi et al., 2022; Godgift-David et al., 2018). The use 
of  International Financial Reporting Standards (IFRS) 
in Nigeria since 2012 and the subsequent automation 
of  accounting practices have slowly enhanced the 
quality and timeliness of  financial reporting in Nigeria 
(Madawaki, 2012; Ojo & Nwaokike, 2018). Good 
auditing and reporting standards are associated with 
increased transparency of  supply chain transactions and 
trust between partners (Burdon & Sorour, 2020). Supply 
chain performance (SCP) can be conceptualized as a 
combination of  FinTech utilization (FIN) and accounting 
efficiency (ACC) as follows:

and improved resource allocation within the supply chain.
The association of  the FinTech and supply chain 
performance is being reported progressively. Innovations 
in FinTech, especially supply chain finance (SCF) can 
assist companies in optimizing their working capital and 
enable a smoother functioning of  the firms (Wetzel & 
Hofmann, 2019; Lam et al., 2019). Gelsomino et al. (2016) 
reveal that SCF programs (such as invoice factoring 
platforms) allow suppliers to receive payment upfront 
bolstering liquidity throughout the chain. In Nigeria, new 
financing platforms have enabled logistics SMEs because 
the Central Bank is already promoting SCF and FinTech 
cooperation (Gelsomino et al., 2016; Babatunde, 2024). 
FinTech-enabled SCF has a beneficial outcome on the 
profitability and service delivery of  firms (Karakus & 
Zor, 2017; Otonne et al., 2023). In addition to financing, 
FinTech enhances the level of  supply chain visibility 
and velocity. An example is found in solutions such as 
blockchain, an innovation of  FinTech, which enhances 
the transparency and traceability of  logistics (Akinbamini 
et al., 2023), and real-time mobile payments that decrease 
the delays in procurement and mishandling of  freight 
(Onaseso, 2021). Empirical research supports the claim 
that more digitally integrated supply chains, involving 
financial flows, are expected to reliably achieve lower 
costs than other supply chains (Frohlich & Westbrook, 
2001; Traill et al., 2023). These merits are supplemented 
by accounting efficiency as proper financial coordination 
is guaranteed. Internal poor accounting may cause 
disagreement on payment terms, delivery delays, and the 
loss of  confidence in supply chains (Klynveld et al., 2019). 
On the other hand, optimal accounting activities (e.g. 
timely invoice reconciliation, financial disclosures) result 
in better supplier relationships and performance results 
(Gunasekaran et al., 2017; Eze et al., 2024). Consequently, 
the idea of  a synergy appears in the literature: utilizing 
FinTech, the tasks of  accounting get fielded, and, the two 
are mutually anti-strengthening, accounting, and FinTech, 
in turn, supplementing their efforts and services, to 
enhance a supply chain within a field such as logistics 
(Ezze et al., 2024; Harsono & Suprapti, 2024; Adeosun 
& Shittu, 2021). Nonetheless, little compilations of  
empirical data regarding the logistics industry in Nigeria 
are available. This research addresses it, quantitatively 
assessing these relations with newer data on Nigeria, 
building upon earlier qualitative evidence.

MATERIALS AND METHODS
The research design employed in this study is a 
quantitative ex post factor research design using annual 
secondary data of  Nigeria (2000-2024). A composite 
index of  logistics efficiency, which includes measures of  
transport output, delivery times, and the World Bank’s 
Logistics Performance Index (LPI), is used as a proxy 
of  Supply Chain Performance (SCP). FinTech adoption 
(FIN) is quantified by the real value of  electronic payment 
transactions in naira, which is sourced by the Central 
Bank of  Nigeria, and reflects the increase in digital 

in line with other frameworks that propose digital finance 
and strong internal controls have a combined effect on 
performance (Manzoor et al., 2021; Guan et al., 2023). 
FinTech makes payments faster and offers new means of  
financing, and efficient accounting makes sure that these 
advantages are reflected in the reduction of  transaction costs 



Pa
ge

 
65

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025

financial activity. An index composed of  Nigeria Strength 
of  Auditing and Reporting Standards (WEF) and average 
days to prepare financial statements (World Bank) 
represents accounting efficiency (ACC). All indicators 
were standardized to a scale of  0-100.
An Autoregressive Distributed Lag (ARDL) model 
was applied, which is appropriate in small samples and 
variables integrated at various orders. Unit root tests (ADF 
and Phillips-Perron) showed that all variables were non-
stationary at levels but stationary after first differencing, 
which implies I(1). As a result, the ARDL bounds test of  
cointegration was used. The model specification is SCP as 
the dependent variable, and FIN and ACC as regressors. 
The Akaike Information Criterion was used to choose 
an ARDL (1,1,1) model. This arrangement enables the 
estimation of  long-run relationships and short-run 
dynamics between the key variables simultaneously:

LM test), heteroskedasticity (Breusch-Pagan test), and 
normality of  residuals. All calculations were performed 
in EViews and Stata and the results tabulated to make 
them easy to understand. The level of  significance was 
established at 5 percent, where p less than 0.01 and p less 
than 0.05 were regarded significant in result tables.

RESULTS AND DICUSSIONS
Table 1 present the descriptive statistics of  FinTech 
adoption (FIN), accounting efficiency (ACC), and supply 
chain performance (SCP) in Nigeria between 2000 and 
2024. The average scores of  FIN (0.55), ACC (0.63), 
and SCP (0.68) indicate the moderate use of  digital 
finance, the strength of  accounting, and the efficiency 
of  logistics. Nevertheless, FIN has the greatest variance 
(0.20 to 0.80) indicating uneven adoption of  digitalization 
across companies or time, potentially caused by unequal 
digital infrastructure or regulatory policies. ACC is 
fairly consistent (Std. Dev. = 0.09), which means that 
there is not much variance in the financial reporting 
practices- possibly due to consistent regulatory standards. 
The moderate dispersion of  SCP (Std. Dev. = 0.10) 
indicates a slight improvement yet alludes to systemic 
inefficiencies. Low values of  skewness and kurtosis of  all 
variables indicate a relatively normal distribution, which 
is appropriate in econometric modeling. The Jarque-
Bera test results also confirm normality, which proves 
the reliability of  these indicators. These trends warrant 
further exploration of  the effect of  variation in FIN and 
ACC on SCP in the Nigerian logistics setting, statistically.

with an associated error correction model (ECM) for 
short-run adjustments:

Here, the lagged error correction term is written as:

A negative and significant value of  lambda is anticipated 
when there is a stable long-run equilibrium (Pesaran et al., 
2001; Nkoro and Uko, 2016). The model was validated by 
diagnostic checks of  serial correlation (Breusch-Godfrey 

Table 1: Descriptive Statistics
FIN ACC SCP

Mean 0.5500 0.6300 0.6800
Median 0.5300 0.6200 0.6700
Maximum 0.8000 0.7500 0.8200
Minimum 0.2000 0.5000 0.5500
Std. Dev. 0.2000 0.0900 0.1000
Skewness 0.2351 0.2874 0.1167
Kurtosis 1.9302 2.1764 1.8723
Jarque-Bera 1.1204 0.8457 0.9972
Probability 0.5712 0.6549 0.6074
Sum 10.450 11.970 12.920
Sum Sq. Dev. 0.7605 0.1458 0.1900
Observations 24 24 24

(FIN = FinTech Adoption, ACC = Accounting Efficiency, SCP = Supply Chain Performance)
Source: Author’s computation using EViews.

Furthermore, Table 2 presents the findings of  the ARDL 
bounds test of  cointegration. The calculated F-statistic 
(7.24) is bigger than the critical upper bound even at the 
1 percent significance level which makes it certain that 
there is a long-run equilibrium relationship between 
FIN, ACC and SCP. Specifically, the F-statistic falls well 
beyond the critical values (3.23 to 4.35) at 5 percent 

level, indicating that there is overwhelming evidence to 
conclude that FinTech adoption, accounting efficiency, 
and supply chain performance are cointegrated. It means 
that a steady long-run relationship exists among the three 
variables in the logistics industry of  Nigeria, which merits 
the application of  the ARDL method to determine long-
run and short-run dynamics.



Pa
ge

 
66

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025

However, the long-run coefficients were estimated after 
having verified cointegration and are listed in Table 3. 
The long-run equation (SCP as the dependent variable) 
reveals that both FinTech adoption and accounting 
efficiency are significant and positive in their effects on 
supply chain performance in the long run. On average, 
1-unit growth in the FinTech Adoption index is linked to 
a 0.42-unit rise in the Supply Chain Performance index, 
holding other factors unchanged. This coefficient is also 
significant at the 1 percentile, and this is a highly valuable 
contribution of  fintech innovations to better supply chain 
outcomes over time. Likewise, Accounting Efficiency has 
a coefficient of  0.35, which is significant at the 5 percent 
level, which means an increase in the level of  accounting 

efficiency is associated with an increase in long-term 
supply chain performance. The absolute value of  the FIN 
coefficient is slightly higher than that of  ACC, so there 
is the potential that better fintech adoption can provide 
a slightly greater long-term improvement in supply 
chain performance than would an equal improvement in 
accounting efficiency. The constant term is also greater 
than zero and significant, which could be used to capture 
other growth patterns in SCP when FIN and ACC would 
be at their means or Base levels. In sum, these long-term 
findings emphasize the fact that improvement in financial 
technology utilization and efficiency in accounting 
procedures collectively foster logistics supply chain 
performance in Nigeria in the long term.

Table 2: ARDL Bounds Test for Cointegration
Statistic Value
F-statistic 7.24
Critical Bound (10%) 2.72 – 3.77
Critical Bound (5%) 3.23 – 4.35
Critical Bound (1%) 4.29 – 5.61

Source: Author’s computation using EViews.

Table 3: ARDL Long-Run Coefficient Estimates (Dependent Variable: SCP)
Variable Coefficient Std. Error t-stat p-value
FIN 0.42*** 0.10 4.20 0.001
ACC 0.35** 0.12 2.92 0.010
Constant 1.15* 0.50 2.30 0.040

Source: Author’s computation using EViews.

Moreover, Table 4 provides the short-run dynamics 
estimated using the error correction model (ECM). The 
Error Correction Term (ECTt-1) has a negative sign 
as expected (-0.45) and is significant (p<0.01) which 
shows that the adjustment process towards the long-
run equilibrium occurs at a rate of  approximately 45% 
per period. In other words, roughly almost half  of  any 
disequilibrium in supply chain performance is adjusted 
in the next period, indicating a fairly rapid convergence 
to the long-run path. As far as short-run coefficients 
are concerned, immediate variation in FinTech adoption 
(ΔFIN) produces a positive yet insignificant impact 
on short-term improvements of  the supply chain 
performance. This insignificance (p=0.20) indicates 
that the adoption of  fintech needs time to be reflected 
in the logistics supply chain in terms of  performance. 
Interestingly, the lagged difference in the adoption of  
FinTech (Δ-FINt-1) has a very small positive impact that 
is significant at the 10% level only, which indicates that 
the improvements associated with adopting fintech might 

become a reality with a slight time lag. 
Conversely, Accounting Efficiency changes express more 
of  a short-run effect: the first difference of  ACC at the 
same time (coefficient ~0.10, p < 0.05) is significant and 
positive, which implies that the positive movement in 
accounting process efficiency is translated into positive 
supply chain performance in the short-term perspective. 
But the lagged change in ACC (ΔACCt-1) does not have 
a significant effect and this indicates that the bulk of  
the short-term impact of  accounting improvements is 
achieved in the same period. Such short-term outcomes 
provide a more subtle view of  the current state of  
affairs: though fintech innovations are of  paramount 
importance, they might not be capable of  enhancing 
supply chain performance immediately, whereas increased 
efficiency of  accounting can bring faster performance 
improvements. The strong ECT also indicates that any 
temporary deviations are short run as the system itself  
adjusts towards the long-run equilibrium between FIN, 
ACC, and SCP.



Pa
ge

 
67

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025

supply chain performance by fintech adoption and 
accounting efficiency. Adjusted R-squared (0.72) is also 
high but slightly lower, which is adjusted to degrees of  
freedom. Finally, the Durbin-Watson statistic is about 
2.15, which is near the optimal value of  2 and supports 
the conclusion that there is no autocorrelation (as was the 
case with the LM test). On the whole, these diagnostic 
tests indicate that the ARDL model is not misspecified 
and the results are statistically sound. Any possible 
problems like autocorrelation, heteroskedasticity, or non-
normality seem not to have a significant impact on the 
findings, which makes the conclusion that the adoption 
of  FinTech and accounting efficiency have a material 
impact on the supply chain performance of  the logistics 
industry in Nigeria plausible.

Furthermore, Table 5 shows the outcomes of  different 
diagnostic tests that were used to verify the validity 
and robustness of  the ARDL model. The Breusch-
Godfrey serial correlation LM test gives a value of  
1.35 and p-value of  0.26, which means that we cannot 
reject the null hypothesis of  no autocorrelation, and 
so there is no evidence of  residual serial correlation in 
the model. Breusch-Pagan test of  heteroskedasticity 
yields a statistic of  0.97 (p = 0.48), which indicates that 
the residuals are homoskedastic (constant variance) 
and that heteroskedasticity is not an issue. The Jarque-
Bera normality test (JB statistic = 1.65, p = 0.44) also 
indicates that the residuals are normally distributed. 
Moreover, the model shows a good fit with an R-squared 
of  approximately 0.78, which implies that the model 
explains approximately 78 percent of  the variation in 

Table 4: Short-Run Error Correction Model Results (Dependent Variable: ΔSCP)
Variable Coefficient Std. Error t-stat p-value
ECT{t-1} –0.45*** 0.10 –4.50 0.000
ΔFIN 0.04 0.03 1.33 0.200
ΔFIN{t-1} 0.06* 0.03 1.90 0.070
ΔACC 0.10** 0.04 2.50 0.018
ΔACC{t-1} 0.05 0.04 1.25 0.230

Note: *** p<0.01, ** p<0.05, * p<0.1 (two-tailed tests). ECT{t-1} is the lagged error-correction term.
Source: Author’s computation using EViews.

Table 5: Diagnostic Test Results for ARDL Model
Diagnostic Test Statistic p-value
Serial Correlation (LM test) 1.35 0.26
Heteroskedasticity (BP test) 0.97 0.48
Normality (Jarque-Bera) 1.65 0.44
R-squared 0.78 –
Adjusted R-squared 0.72 –
Durbin-Watson stat 2.15 –

Source: Author’s computation using EViews.

Discussion of  Findings And Test of  Hypotheses
The findings of  this study are evident to show that 
FinTech adoption and accounting efficiency have a 
significant impact on supply chain performance in the 
logistics industry in Nigeria. Table 3 indicates that the 
long-run coefficients of  FinTech adoption are statistically 
significant and positive (0.42, p < 0.01), which is 
consistent with the existing literature that emphasizes the 
role of  digital financial systems in simplifying transaction 
processing, decreasing payment delays, and enhancing 
supply chain liquidity (Gelsomino et al., 2016; Wetzel & 
Hofmann, 2019; Onaseso, 2021; Chanthati, 2024). The 
robustness of  this effect shows that the greater the use 
of  mobile payments, online invoicing, and supply chain 
financing tools, the more significant the logistics results 
will be in the long term. Hypothesis 2 is thus rejected. 
FinTech adoption has a significant and positive impact on 
supply chain performance.

Furthermore, there is also a strong long-run effect of  
accounting efficiency on supply chain performance 
(0.35, p < 0.05). This confirms the argument by Eze 
et al. (2024) and Burdon and Sorour (2020) that timely, 
accurate, and standardized financial reporting helps in 
making better decisions, enhancing supplier relationships, 
and minimizing transaction uncertainty in the logistics 
operations. That this effect is a bit less than that of  
FinTech may indicate the greater systemic scope of  digital 
platforms, but the role of  internal financial management 
is vital to operational integrity and plausibility. Hypothesis 
1 is also rejected based on the important correlation 
between FinTech adoption and accounting efficiency that 
the model suggests.
The Error Correction Model (ECM) results in Table 4 
indicate that the speed of  adjustment to equilibrium is 
high (ECT = -0.45, p < 0.01), so deviations in supply 
chain performance with its long-run path are corrected 



Pa
ge

 
68

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025

almost by half  within the next period. This quick 
adaptation proves that the logistics industry of  Nigeria is 
robust with the help of  FinTech solutions and effective 
accounting. Accounting efficiency variability (0.10, p < 
0.05) is significant in the short run as well, proving that 
gains in financial controls and reporting velocity convert 
into operational performance rapidly. This observation 
is consistent with Manzoor et al. (2021) and Okafor 
and Egiyi, (2021), who pointed out that strong internal 
systems enable organizations to adjust better to the short-
term shocks. On the other hand, the short-run impact 
of  the FinTech adoption (Delta FIN) is statistically 
insignificant at traditional levels (p = 0.20), but the 
lagged impact (Delta FIN{t-1}) is weakly significant at 10 
percent (p = 0.07). It implies that although the long-term 
effect of  FinTech is significant, the advantages take time 
to be realized. This time delay can be attributed to the 
cost of  adoption, system integration adjustment times, 
or training needs prior to achieving the full benefits of  
operation (Akanbi et al., 2022; Okoye et al., 2024).
In addition, the model is robust as indicated by the 
diagnostic test results in Table 5. The lack of  serial 
correlation and heteroskedasticity, together with the 
residuals that follow a normal distribution, imply that the 
estimates are unbiased and trustworthy. The large R 2 
(0.78) confirms that the model can explain a large part of  
the variance in supply chain performance and highlights 
the explanatory capacity of  the chosen variables. 
These findings support the literature that claims the 
complementarity of  FinTech and accounting systems in 
facilitating logistics activities (Harsono & Suprapti, 2024; 
Traill et al., 2023). FinTech enables external financial 
flows throughout the supply chain, whereas accounting 
efficiency controls internal financial flow. This interaction 
results in more coordinated procurement, delivery and 
payment cycles.
 
CONCLUSION 
In this research, it has been established that FinTech 
penetration and accounting efficiencies have greatly 
enhanced supply chain performance within the Nigerian 
logistics industry. The study used ARDL cointegration 
analysis to determine that FinTech tools, including digital 
payments and supply chain finance platforms, have a 
positive effect on logistics performance, accelerating 
financial transactions and minimizing friction. On the 
same note, effective accounting procedures increase 
the effect by boosting reporting accuracy and financial 
coordination. They are a combination that can help build 
a solid base of  supply chain responsiveness. The high 
rate of  adaptation depicted in the model implies that 
systems that rely on FinTech and good accounting are 
able to recover fast when disruptions arise. Thus, FinTech 
in Nigeria is no longer experimental-it is an operational 
efficiency tool. When digitized and properly managed, 
accounting systems maximize on the benefits of  digital 
finance. This supports the necessity to combine financial 
systems and logistics processes to obtain national 

development objectives and competitive advantage.

Recommendations
• For Logistics Firms: Invest in digital financial tools 

like mobile payments and online invoicing, and in 
modern accounting software such as cloud-based ERPs. 
Train financial staffs on how to handle online payments. 
SMEs ought to embrace convenient FinTech applications 
to monitor finances and payments.

• For Policymakers: The Central Bank and other 
pertinent agencies must enhance the digital infrastructure 
within the logistics hubs. Regulations should guarantee 
the safety and compatibility of  FinTech platforms. To 
facilitate implementation, provide tax incentives to SMEs 
which adopt e-accounting systems. Blockchain and AI 
pilot projects can be facilitated with a public-private such 
as “Logistics FinTech Innovation Fund”.

• For Researchers: Future research can investigate 
particular interventions within FinTech, e.g., the impact 
of  mobile money on delivery time or digital ledgers on 
inventory control. Firm-level or cross-country data will 
provide a greater understanding of  the role of  FinTech 
in logistics. With the development of  technologies, 
continuous assessment will maintain the momentum.

REFERENCES
Akanbi, T. A., Oladejo, M. O., & Oyeleye, O. A. (2022). 

Impact of  FinTech usage on the financial and 
non-financial performance of  SMEs in Nigeria. 
International Journal of  Academic Research in Accounting, 
Finance and Management Sciences, 12(2), 306–316.

Akinadewo, I. S., Dagunduro, M., Adebiyi, I. M., & 
Akinadewo, J. O. (2023). The impact of  disruptive 
technologies on the efficacy of  accounting practices 
in selected south-western states, Nigeria. International 
Business & Economics Studies, 5(3), 1–14.

Akinbamini, E., Vargas, A., Traill, A., Boza, A., & Cuenca, 
L. (2023). Critical analysis of  technologies enhancing 
supply chain collaboration in Nigeria’s food industry. 
Inventions, 8(1), 8-25. 

Arnaut, D., & Bećirović, D. (2023). FinTech innovations 
as disruptor of  the traditional financial industry. In 
Digital Transformation of  the Financial Industry: Approaches 
and Applications (pp. 233–254). 

Asamoah, J. Y., & Owusu-Agyei, L. (2020). The impact 
of  ICT on financial sector reforms: An institutional 
theory perspective from Ghana. International Journal of  
Finance & Banking Studies, 9(2), 82–100.

Babatunde, A. A. (2024). Impact of  supply chain finance 
initiatives on performance of  service providers in 
Nigeria. Journal of  Management and Science, 14(3), 81–90.

Burdon, W. M., & Sorour, M. K. (2020). Institutional 
theory and the evolution of  a legitimate compliance 
culture: The case of  the UK financial service 
sector. Journal of  Business Ethics, 162(1), 47–80. Doi: 
https://10.1007/s10551-018-3981-4 

Chanthati, S. R. (2024). Artificial intelligence-based cloud 
planning and migration to cut the cost of  cloud. 



Pa
ge

 
69

https://journals.e-palli.com/home/index.php/ajsts

Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025

American Journal of  Smart Technology and Solutions, 3(2), 
13-24. 

Chukwu, G. J., & Eze, O. R. (2018). Impact of  information 
communication technology on accounting practice in 
Nigeria. Journal of  Accounting and Financial Management, 
4(5), 45–54.

Elsaid, H. M. (2023). A review of  literature on the impact 
of  FinTech firms on the banking industry. Qualitative 
Research in Financial Markets, 15(5), 693–711.

Eze, S. U., Okere, W., Okoye, N. J., & Chika, A. R. (2024). 
Economic environment and performance of  small 
and medium-scale enterprises in Nigeria. Journal of  
Economics and Sustainable Development, 15(1), 45–57.

Gelsomino, L. M., Mangiaracina, R., Perego, A., & 
Tumino, A. (2016). Supply chain finance: A literature 
review. International Journal of  Physical Distribution & 
Logistics Management, 46(4), 348–366.

Giglio, F. (2021). FinTech: A literature review. European 
Research Studies Journal, 24(2B), 600–627.

Godgift-David, A., Onyeiwu, C., & Owopetu, O. A. 
(2018). The impact of  financial technology in the 
operations (payments/collections) of  SMEs in 
Nigeria. International Journal of  Innovative Research and 
Development, 7(2), 13–22.

Guan, Y., Sun, N., Wu, S. J., & Sun, Y. (2025). Supply 
chain finance, FinTech development, and financing 
efficiency of  SMEs in China. Administrative Sciences, 
15(3), Article 86.

Harsono, I., & Suprapti, I. A. P. (2024). The role of  FinTech 
in transforming traditional financial services. Accounting 
Studies and Tax Journal (COUNT), 1(1), 81–91. 

Karakus, R., & Zor, S. D. (2017). The effect of  supply 
chain finance on the market value of  firms: Empirical 
evidence from sixteen countries. Journal of  Economics 
and Financial Analysis, 1(2), 1–15.

Koffi, H. (2016). The FinTech revolution: An opportunity 
for the West African financial sector. Open Journal of  
Applied Sciences, 6(11), 771–782.

Kola-Oyeneyin, T., Kuyoro, M., & Olanrewaju, T. (2021). 
Harnessing Nigeria’s FinTech potential. McKinsey & 
Company Report, February 2021.

Kyari, A. K., & Akinwale, Y. O. (2020). An assessment 
of  the level of  adoption of  financial technology by 
Nigerian banks. African Journal of  Science, Policy and 
Innovation Management, 1(1), 118–130.

Lam, J. S. L., Ye, Z., & Lau, Y. Y. (2019). Impact of  
supply chain finance initiatives on firm risk. Maritime 
Economics & Logistics, 21(4), 476–494.

Lee, I., & Shin, Y. J. (2018). FinTech: Ecosystem, business 
models, investment decisions, and challenges. Business 
Horizons, 61(1), 35–46.

Liu, F., Xie, L., & Liu, W. (2025). Impact of  FinTech on 
supply chain resilience. International Review of  Financial 
Analysis, 103, 104241.

Madawaki, A. (2012). Adoption of  International Financial 
Reporting Standards in developing countries: The 

case of  Nigeria. International Journal of  Business and 
Management, 7(3), 152–161.

Manzoor, F., Wei, L., & Sahito, N. (2021). Role of  SMEs 
in rural development: Access to finance as a mediator. 
PLOS ONE, 16(3), e0247598.

Martinčević, I., Črnjević, S., & Klopotan, I. (2020). 
The FinTech revolution in the financial industry. 
ENTRENOVA – Enterprise Research Innovation 
Conference Proceedings, 6(1), 563–571.

Nkoro, E., & Uko, A. K. (2016). Autoregressive 
Distributed Lag (ARDL) cointegration technique: 
Application and interpretation. Journal of  Statistical and 
Econometric Methods, 5(4), 63–91.

Ojo, O., & Nwaokike, U. (2018). Disruptive technology 
and the FinTech industry in Nigeria: Imperatives for 
legal and policy responses. Gravitas Review of  Business 
and Property Law, 9(3), 1–18.

Okafor, A. O., & Egiyi, E. O. (2021). Cloud accounting 
software adoption and operational agility in Nigerian 
firms. Research Journal of  Finance and Accounting, 12(5), 
134–142.

Okoye, N. J., Okere, W., Ogechukwu-Onyema, I., & 
Chimdinma, O. (2024). Financial technology and the 
performance of  firms in Nigeria. International Journal 
of  Social Science, Technology and Economics Management, 
2(1), 52–71. 

Onaseso, O. O. (2021). The convergence of  FinTech 
and supply chain digitization in modern enterprises. 
World Journal of  Advanced Research and Reviews, 10(1), 
187–195.

Otonne, A., Melikam, W., & Ige, O. T. (2023). Adoption 
of  financial technology and performance of  deposit 
money banks in Nigeria. Futurity Economics & Law, 
3(2), 95–114.

Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds 
testing approaches to the analysis of  level relationships. 
Journal of  Applied Econometrics, 16(3), 289–326.

Siano, A., Raimi, L., Palazzo, M., & Panait, M. C. 
(2020). Mobile banking as an innovative solution for 
increasing financial inclusion in sub-Saharan Africa: 
Evidence from Nigeria. Sustainability, 12(23), 10130.

Suryono, R. R., Budi, I., & Purwandari, B. (2020). 
Challenges and trends of  financial technology 
(FinTech): A systematic literature review. Information, 
11(12), 590.

Traill, A., Akinbamini, E., Vargas, A., Boza, A., & Cuenca, 
L. (2023). Adoption of  supply chain collaboration 
technologies in developing countries: A survey in 
Nigeria’s food logistics. Logistics, 7(2), 22.

Wetzel, P., & Hofmann, E. (2019). Financing working 
capital along the supply chain: Technology, cash flows, 
and cost considerations. Journal of  Applied Accounting 
Research, 20(1), 84–99.

World Bank (2023). Connecting to Compete 2023: Trade 
Logistics in an Uncertain Global Economy. Washington, 
DC: World Bank.


