Determinants of Digital Payment
Adoption and Its Operational Effects on Retail SMEs in India
Ms. Daniya Javed1*, Dr. Nishtha
Pareek2
1 Research Scholar, Banasthali Vidyapith,
Rajasthan, India
daniyaj@gmail.com
2 Associate Professor, Department of
commerce and Management, Banasthali Vidyapith, Rajasthan, India
Keywords:
Digital
payments, Operational effects, Retail SME, Digital payment technologies, Business performance, Perceived usefulness.
Digital payments comprise a combination of various electronic payment means, mobile money transfer, digital wallets, and cryptocurrencies. According to an RBI definition, a digital transaction is an act that occurs in a manner in which money is not given and taken in hard cash from and to each party and is done through digital means. The shift from dealing with paper money to financial electronic channels implies a shift in consumer preference and is driven mainly by e-payment technology, which has greatly influenced financial inclusion even in retail segments. Organized entities have increasingly relied on this technology in order to fully benefit from the digital economy, even though limitations to their universal use still persist. Digital payments have influenced consumer attitudes towards cash in India in a way in which cash is increasingly treated and considered an investment instead of an alternative form of money, even though cash is in circulation. The future of money is all about efficiency, convenience, and competitiveness, which is mainly influenced by innovations in IMPS and UPI technology and has greatly influenced cash retail electronic transactions even after the demonetization process. Digital payment platforms have experienced a 61% compound annual growth rate in terms of volume and 19% in terms of business from 2014 to 2019 (Mahesh & Bhat, 2021b).
As per “The Payments and Settlements System Act, 2007,” the National Payments Corporation of India was used by the Reserve Bank of India and the Indian Banks Association to oversee retail payments in India. This acted as an aid to NPCI for making Unified Payment Interface, or “UPI,” which is an electronic platform for all banking operations and retail payments using mobile applications of member banks (India, 2020). Established by on April 11, 2016, Reserve Bank of India Governor Dr. Raghuram G. Rajan, “Today, we take another step towards building a Less-Cash Economy, by offering to all Indians, through our banks, a system of payments that is secure, fast, and cost-free,” UPI has experienced tremendous growth to support “227 banks and handle 2,807.51 million transactions worth Rs.5,47,373.17 crore per month as of June 2021(UPI Official Website, 2022,” even with the facility of instantly sending money regarding different modes of payments such as AADHAR Card Holder Payments, QR Code-based Payments, and Virtual Payments Address without any costs. As of October 2023, “UPI handled around 17,15,768.34 crore, and is set to reach One Billion daily transactions (Mahesh & Bhat, 2021a).
Small and Medium Enterprises (SMEs) make substantial contributions to the global economy, especially in the region of South-East Asia, as mentioned by the Asian Development Bank. But the impact of Covid-19 pandemic effects has adversely affected international business; however, the mentioned sector is a significant tool for recovery in developing economies. The pandemic impact has also created a result-driven approach towards online payments, where 80% of customers have adopted online payment methods, which resulted in a 15% surge among 54% of mentioned businesses who adopted these methods (Michael et al., 2024).
Advantages:
· SMEs are vital contributors to the global economy, using more than 60% of the labour force and comprising 90% of enterprises.
· They are pivotal in alleviating poverty and fostering sustainable economic development, especially in rural regions.
· SMEs address the needs of marginalized groups, including women, disabled individuals, and uneducated populations, aiding in local development and combating inequality.
Challenges:
· Economic circumstances
· Financial Performance
· Human resources
· Data security and asset management
· Operational performance (Virglerova et al., 2022).
(Hussain, 2025) aimed to identify what all is being hindered by while preventing the usage of DPSs in India by making use of qualitative methods like semi-structured interviews, theme analysis, and more. The outcome obtained has revealed the list of factors, which have been identified under themes, is the Digital Divide (DD), which is linked to accessibility, capability, and innovativeness, and then Socio-Demographic Divide (SD), which is linked to education, geographical, gender, age, and earning, along with psychological factors associated with usability and trust, as well as awareness and financial reliance.
This study was carried out among 403 unorganized retailers and shows that the increased use of digital payment technology will provide a beneficial outcome impact on their revenues. The study showed that current expenditure on technology will improve this impact and that card and internet-based technologies should be included. Both technologies will be able to demonstrate improvements in financial performance. This will improve financial performance by 9.6 percent. It is clear that the study shows the digital technology that unorganized retailers (Adhikary et al., 2021).
(Soormo et al., 2024) examined to understand the factors that influence QR code payment, evaluate the role of the dual-stage SEM & ANN approaches, use a quantitative approach to study the elements which influence QR code payment. They survey owners of 400 Micro, Small, and Medium Enterprise owners in the four main cities of Sindh Province, Pakistan. They analyze the factors that come under "Performance Expectancy, Price Value, Hedonic Motivation, Habit, Facilitating Conditions, and Social.
(Pare, 2022) aimed to establish the significant factors that contribute to the adoption of digital payments among micro entrepreneurs in India. The comprehension of digital payments was formed is directly proportional to the educational qualifications, technological know-how, and awareness of the people, and higher adoption rates are recorded in regions with better education levels. A larger number of smartphone users also has a positive impact on this adoption. SMEs are a crucial element in the socioeconomic development of countries; the definition differs from country to country based on income, assets, expenditure, or number of employees. Micro, Small, and Medium Enterprises, if considered in the context of India, constitute a major share of the agricultural sector.
(Phatak, 2023) examined the use of finance technology as a part of the business operations, where the use of finance technology has a vast potential for sales turnover enhancement and customer satisfaction. From a structured survey done through questionnaires for 300 entities of the business sector of the city of Pune, Maharashtra, the impact of electronic payment systems brings enhancement in sales turnover, customer satisfaction, decrease in transaction fees and enhancement of company efficiency.
There has been an upward trend in the development of fintech apps, particularly digital payment apps used by MSMEs to perform their business transactions. This research paper has outlined the digital transformation of MSMEs in Blitar City, Indonesia, using a sampling method of 100 respondents drawn from a population of 4,793 MSMEs. SmartPLS analysis using SEM technology indicated that functional barriers created a significant effect on use, value, and risk factors, whereas psychological barriers created an effect on tradition and image. It should be remembered that functional barriers created insignificant effects on use, whereas psychological barriers created a positive effect on digital payment transaction use (Widayani, 2022).
(Jayarathne et al., 2025) analysed the factors which affect the adoption of mobile payments during the early stages of the COVID-19 pandemic from a customer and retail point of view and also from rural and urban areas. The authors concentrated on a mixed methodology of surveys and interviews and discovered that on the customer side, Hedonic Motivation (HM), Performance Expectancy and Facilitating Conditions (PEFC), and Perceived Security of Technology are the constructs. Barriers from the retailer side are unawareness and ignorance of customers and employees regarding management's orientation and poor computer literacy skills among customers. Although the motivating factors in this research are Performance Expectancy and Facilitating Conditions, they depend on whether it is rural or urban. This particular research work is unique since it compared two environments for the first time in rural and urban areas with all the diversity in research methodology.
Despite existing examination of the deployment of digital payment systems in India and emerging nations as a whole means many existing limitations are left unexplored. The existing research has mainly addressed the financial performance aspects of technological innovations such as cards and QR code systems or explored the challenges on the part of the customer and unorganized retailers. There is a major identified deficit in the existing research regarding retail SMEs in the Indian setting as a distinct group in the wake of unique operational challenges and infrastructure constraints. The existing research on the subject also explored the aspects of specific determinants of adoption or operation without a comprehensive framework in which the determinants of adoption are considered in relation to the various major infrastructural aspects of operational performance in terms of cost efficiency, customer contentment, or sales accretions. The research also remained restricted in terms of geographical spread and in turn left the existing research outcomes highly non-generalizable in a geographical context. There also exists a need for rigorous quantitative investigation in terms of the current studies on the impediments and enablers of digital transactions adoption in several facets including as the digital divide and sociodemographic aspects in the specific retail SME context.
This
research analysed the determinants affecting the adoption of digital payments via
a quantitative approach and its functionality effects on retail SMEs in India.
In fact, it demands the total sample number 384 retail SME owner/manager and
digital payment integrators for conducting data acquisition for this
investigation. Data is gathered by administering a questionnaire survey on the
specified subject study by virtue of 5-point Likert scale factor involving
total constructs on 5 factors – Perceived Usefulness (PU), Peruced Ease Of Use
(PEOU), Security / Trust (ST), Digital Payment Adoption (DPA), & Lastly:
Operational Efficiency (OE) & Business Performance(BP).
Figure 3.1 Conceptual
framework
·
To identify how perceived usefulness, ease of use, and
security/trust influence the adoption of digital payments by retail SMEs.
·
To examine how digital payment adoption affects the
operational efficiency of retail SMEs.
·
To determine how operational efficiency contributes to
the business performance of retail SMEs.
·
H1a: Perceived usefulness has a positive influence on the
adoption of digital payments by retail SMEs.
·
H1b: Perceived ease of use has a positive influence on the
adoption of digital payments by retail SMEs.
·
H1c: Security/trust has a positive influence on the adoption
of digital payments by retail SMEs.
·
H2: Digital payment adoption has a positive effect on the
operational efficiency of retail SMEs.
·
H3: Operational efficiency has a positive impact on the
business performance of retail SMEs.
The research
population included shop managers, digital payment integrators, and retail
small and medium-sized enterprise owners. A purposive sample technique was used
to choose persons meeting the inclusion criteria. A total of 384 individuals
were chosen according to statistically determined sample size criteria. The
data collection process included securing informed consent and thereafter
distributing a self-made survey. The poll included both closed-ended and open-ended
questions.
Inclusion Criteria:
·
Indian retail small and
medium-sized businesses that either already utilize or may use digital payment
systems.
·
Payment methods in SMEs
are chosen or managed by owners, managers, or important decision-makers.
·
Companies that have been
in business for a minimum of a year must have enough expertise with payment
procedures.
Exclusion
Criteria:
·
Big businesses or small,
unofficial sellers who don't fit within the retail SME category.
·
SMEs that don't deal
directly with customers (such as business-to-business wholesalers without an
online payment system).
·
Respondents who do not
directly participate in the SME's operational, financial, or payment-related
decision-making.
Data has been
collected using a standardised questionnaire. A questionnaire has been formulated
with a 5-point Likert scale to elicit respondents' thoughts on different
research subjects being examined. The questionnaire has a collection of both
open-ended and closed-ended questions. Questions have been meticulously
designed to elicit significant information on specified study factors. The
details of the variables and the corresponding measurement items used for the
analysis are presented below.
|
S.No. |
Constructs |
Statements |
|
1 |
‘Perceived
Usefulness’ |
5 |
|
2 |
Perceived
Ease of Use |
5 |
|
3 |
Security/Trust |
5 |
|
4 |
Digital
Payment Adoption |
5 |
|
5 |
Operational
Efficiency |
5 |
|
6 |
Business
Performance |
5 |
· Perceived Usefulness: The core concept of the model is perceived usefulness. It is explained by the phrase, "an individual's belief that using a particular system will improve their work performance," which is widely regarded as a very important aspect within the framework of technological adoption. For example, e-banking or e-shopping (Noordiana et al., 2020).
· Perceived Ease of Use: Perceived absence of mental and physical efforts required in using technology is related to the friendly and usability characteristic of technology or system to produce effective results (Noordiana et al., 2020).
·
Security/Trust:
Security is perceived as a very
critical factor for digital payments and is integral for the demonstration of
greater confidence and interest among the target customers. Without this
security, the clients may be lost due to the obvious preference for more
trusted applications over the new entity that could reduce their acceptability
for services (Halimatus & Soegoto,
2021).
· Digital Payment Adoption: Various digital payment methods exist that involve electronic payment, mobile payment, e-wallet, or QR-based payment methods. Generally, consumer type-based adoption has dominated the growth of these payment methods. The slow pace witnessed in the execution of digital payment systems in impoverished countries may be ascribed to the low internet power infrastructure. (Susanto et al., 2022).
· Operational Efficiency: Operational efficiency is concerned with the way managers can turn inputs into products or services. The demands for maximum output at the lowest price need to be fulfilled by the managers. Value-adding processes maximize the value of the organization by utilizing the resource at its optimal utilization (Keya, 2021).
·
Business
Performance: The appearance of opportunities within markets
is a result of market nature; hence, entrepreneurs possess the ability to make
estimates regarding expectations. Awareness of being entrepreneurs is explained
by the following:the alertness to the environment regarding weaknesses in
markets, rather than seeking opportunities (Raharja, 2020).
The
empirical results of the research examining the variables affecting the
acceptance of digital payments and their operational ramifications are covered
in this part on retail SMEs within an Indian context. Results are presented
systematically, commencing with an elucidation of the demographic attributes of
the sampled companies, after which csonfirmatory factor analysis is used to
evaluate the measurement model and descriptive statistics, and reliability
analysis. Follow-on research includes Kaiser-Meyer-Olkin and Bartlett's test
for assessing sampling adequacy and analysis of construct validity based upon
AVE and composite reliability estimates. The hypotheses are tested by means of
structural equation modeling for determining the relationships between
perceived value, perceived usability, security/trust, digital payment adoption,
operational efficiency, and company performance. Each set of findings, it is noted,
together provide a comprehensive knowledge of how perceived operational and
technical competence affects the uptake of digital payment solutions and their
consequent performance effects in retail SMEs.
Table 1 Demographic variables
|
Demographic |
Groups |
Frequency |
Percent |
|
Type of
Retail Business |
Grocery
/ Supermarket |
116 |
30.2 |
|
Clothing
& Apparel |
80 |
20.8 |
|
|
Electronics
& Mobile Stores |
96 |
25.0 |
|
|
Pharmacy
/ Medical Shops |
60 |
15.6 |
|
|
General
& Other Retail Outlets |
32 |
8.3 |
|
|
Total |
384 |
100.0 |
|
|
Business
Experience |
Less
than 2 years |
172 |
44.8 |
|
2 – 5
years |
90 |
23.4 |
|
|
5 – 10
years |
62 |
16.1 |
|
|
Above
10 years |
60 |
15.6 |
|
|
Total |
384 |
100.0 |
|
|
Number
of Employees |
1 – 5
employees |
84 |
21.9 |
|
6 – 10
employees |
156 |
40.6 |
|
|
11 – 20
employees |
119 |
31.0 |
|
|
More
than 20 employees |
25 |
6.5 |
|
|
Total |
384 |
100.0 |
|
|
Monthly
Sales Turnover |
Below
₹1,00,000 |
181 |
47.1 |
|
1,00,000
– 5,00,000 |
124 |
32.3 |
|
|
5,00,000
– 10,00,000 |
51 |
13.3 |
|
|
Above
10,00,000 |
28 |
7.3 |
|
|
Total |
384 |
100.0 |
|
|
Experience
with Digital Payment Usage |
Less than
1 year |
224 |
58.3 |
|
1 – 3
years |
68 |
17.7 |
|
|
3 – 5
years |
46 |
12.0 |
|
|
More
than 5 years |
46 |
12.0 |
|
|
Total |
384 |
100.0 |
The demographic makeup of the
responders suggests a varied representation of retail SMEs. The grocery/
supermarket stores, on the one hand, topped the list with the highest
percentage of 30.2%, followed by electronics & mobile stores with 25.0%,
clothing/apparel stores with 20.8%, pharmacies/medical stores with 15.6%, and
general/other retail stores with 8.3%. Another notable feature of the sample
population was its relatively young age, where a vast majority of respondents
have remained in the market for less than two years, that is, 44.8%, followed
by those having remained for two to five years, amounting to 23.4%, for five to
ten years, comprising 16.1%, and more than ten years, contributing 15.6% of the
sample population. Moreover, the sample population was represented by a diverse
range of company sizes, with 40.6% of sample population having a company size
of 6-10, followed by 11-20, comprising 31.0%, of the sample, of sizes 1-5,
contributing 21.9%, followed by more than 20, contributing 6.5% sample
population. Moving on, the sample population was observed to be divergent in
regard to their financial requirements, where more than half of the sample,
that is, 47.1%, of all enterprises have sales turnover below Rs. 100,000,
succeeded by Rs. 100,000 to Rs. 500,000, which contributes 32.3%, and then Rs.
500,000-Rs. 1,000,000, consisting 13.3%, followed by more than Rs.10, 00,000,
contributing 7.3%, sales turnover. Furthermore, the sample was observed to be
divergent in regard to their awareness of the digital payment systems, where a
vast segment of a sample population has remained unaware of the said systems
for a less period of time, that is, for less than a year, contributing 58.3%,
followed by one to three years, comprising 17.7%, followed by three to five
years, contributing 12.0%, followed by more than five years, contributing 12.0.
Figure 4.1 CFA model
The
measurement model for confirmatory factor analysis offers sound psychometric
evidence for constructs of Perceived Usefulness, Perceived Ease of Use,
Security/Trust, Digital Payment Adoption, Operational Efficiency, and Business
Performance. All correlated observables show substantial loading on their
corresponding latent constructs. The values for standardized factor loading for
all observables are for the most part well above 0.60. This therefore supports
sound convergent validity for measurement models. The values for
inter-construct correlation show substantial and positive values among all
constructs. The existence of considerable associations among constructs is
evident. The values for constructs of Perceived Usefulness, Perceived Ease of
Use, and Security/Trust have significant and positive correlations with Digital
Payment Adoption. Consequently, it demonstrates significant backing from
favourable opinions and trust about the implementation of electronic payment
systems by small enterprises. The Digital Payment values acceptance show
substantial and favorable associations with constructs for Operational
Efficiency and Business Performance. Therefore, it is proof that there is substantial
support from digital payment system-based companies whose efficiency is highly
high and whose performance is highly superior. The measurement model structure
supports all theoretical propositions. The refinement of patterns for loadings
and constructs supports reliability and validity. The model is therefore sound
for further hypotheses testing. This is for accompaniment of structural
equation modeling.
Table 2 Descriptive Statistics,
Reliability, and Inter-Variable Correlations
|
Variables |
Mean |
Perceived Usefulness |
Perceived Ease of Use |
Security Trust |
Digital Payment Adoption |
Operational Efficiency |
Business Performance |
|
Perceived Usefulness |
3.6073 |
.849 |
|
|
|
|
|
|
Perceived Ease of Use |
3.7031 |
.639 |
.891 |
|
|
|
|
|
Security Trust |
3.6833 |
.653 |
.639 |
.831 |
|
|
|
|
Digital Payment Adoption |
3.6448 |
.711 |
.668 |
.774 |
.798 |
|
|
|
Operational Efficiency |
3.7557 |
.633 |
.551 |
.595 |
.703 |
.818 |
|
|
Business Performance |
3.8005 |
.650 |
.589 |
.614 |
.709 |
.855** |
.820 |
|
**. Correlation is significant
at the 0.01 level (2-tailed). |
|||||||
Figure 4.2: Descriptive
Statistics, Reliability, and Inter-Variable Correlations
The descriptive
statistics and results of the correlation analysis, it is observed that there
exist strong correlations among the major variables related to retail SMEs'
adoption and operation of digital payments.
All the average scores of the variables lie between 3.60 and 3.80,
indicating that all the respondents generally hold positive views about
USEFULNESS of information and communication technology (ICT), CONVENIENCE of
usage of ICT, SECURITY of financial transactions using ICT, ADOPTATION of
digital payments, OPERATIONAL EFFICIENCY of digital payments, and BUSINESS
PERFORMANCE of the business. The alpha
reliabilities of all the variables are found to be very high, having a value of
0.849 for digital payments' perceived usefulness and perceived usability are
0.891 and 0.891, in that order 0.831 for Security Trust of the proposed digital
payments system, and 0.798 for adoption of digital payments. This yields a near perfect internal validity,
indicating a high degree of accuracy.
Results of the correlation analysis show strong and positive
correlations among all the variables at significance levels of 0.01, indicating
a high dependence on all the variables.
For instance, PERCEIVED USEFULNESS is positively correlated with digital
payment adoption, with a correlation value of 711, while adoption and security
trust have a strong relationship of the proposed digital payments system,
having a correlation coefficient of 774.
The positively correlated implementation of digital payments with OPERATIONAL
EFFICIENCY, having a correlation coefficient of 703, and adoption of digital
payments with overall BUSINESS PERFORMANCE of organisation/enterprise, having a
correlation coefficient of 709, indicate a very crucial and pivotal role played
by the proposed digital payments system.
OPERATIONAL EFFICIENCY is positively correlated with overall BUSINESS
PERFORMANCE with a very high dependence, having a correlation coefficient of
855.
Table 3 KMO and Bartlett's Test
|
KMO and Bartlett's Test |
||
|
‘Kaiser-Meyer-Olkin Measure of
Sampling Adequacy’ |
0.958 |
|
|
‘Bartlett's Test of Sphericity’ |
‘Approx. Chi-Square’ |
7864.197 |
|
df |
435 |
|
|
Sig. |
0 |
|
The
Kaiser-Meyer-Olkin test and Bartlett's Test of Sphericity were used to assess
the appropriateness of the data for factor analysis. 0.958 is the Kaiser-Meyer
Olkin value is outstanding; hence, it gives a set of variables whose
correlation is strong enough to give trustful factor extraction. A relatively
higher value in KMO indicates that the correlation structure is more
convergent, thus very suitable for factor analysis. A statistically significant
result with a Chi-Square value is obtained from the Bartlett's Test of
Sphericity of roughly 7864.197 and 435 with a predetermined significance
threshold of fewer than degrees of freedom p<0.001. From this, the huge
significance makes rejection of the null hypothesis crystal clear, which states
that the correlation matrices are all equal, thus showing strongly associated
inter-variables. Overall, the findings provide substantial evidence to
substantiate the adequacy of furthering factor analysis on the given dataset.
Table 4 Reliability Validity Test
|
Variables |
AVR |
CR |
|
Perceived Usefulness |
0.722 |
0.845 |
|
Perceived Ease of Use |
0.794 |
0.868 |
|
Security Trust |
0.692 |
0.834 |
|
Digital Payment Adoption |
0.638 |
0.810 |
|
Operational Efficiency |
0.670 |
0.824 |
|
Business Performance |
0.673 |
0.826 |
The
constructs exhibited adequate reliability and validity, demonstrating acceptable
internal consistency and convergent validity across all variables. Perceived
Usefulness had an AVE of 0.722 and a CR of 0.845, reflecting very good
dependability. Perceived Ease of Use had equally strong results, with an AVE of
0.794 and a CR of 0.868, showing a significant level of uniformity among its
measurement items. Security Trust had an AVE of 0.692 and a CR of 0.834, thus
showing satisfactory convergent validity. The adoption of digital payments had
an AVE of 0.638 and a CR of 0.810, meeting the criteria on construct
dependability. Operational Efficiency had an AVE of 0.670 and a CR of 0.824
while Business Performance had an AVE of 0.673 and a CR of 0.826, indicating
adequate reliability and validity. Because all AVE scores were above the
acceptable threshold of 0.50, and all CR scores were above 0.80, the constructs
used in this investigation are both trustworthy and valid to be taken into
further analysis.
|
S. No |
Hypothesis |
Co-efficient Value |
P-value |
Results |
|
“Perceived usefulness has a beneficial impact on
the adoption of digital payments by retail SMEs” |
0.840 |
*** |
Hypothesis Accepted |
|
|
H1b |
“Perceived simplicity of use positively impacts
the uptake of digital payments by retail SMEs” |
0.788 |
*** |
Hypothesis Accepted |
|
H1c |
“Security/trust has a favourable impact on has a
positive influence on the adoption of digital payments by retail small and
medium-sized enterprises (SMEs)” |
0.952 |
*** |
Hypothesis Accepted |
|
H2 |
“The implementation of digital payments
positively impacts the operational efficiency of retail SMEs” |
0.813 |
*** |
Hypothesis Accepted |
|
H3 |
“Operational efficiency has a positive impact on
the business performance of retail SMEs” |
0.982 |
*** |
Hypothesis Accepted |
H1a: The hypothesis test
findings indicate a robust and significant Correlation with perceived utility
and the use of digital payment systems by small and medium-sized enterprises retail
organisations. The strength of influence 0.840 shows a strongly positive
influence, which shows it is more beneficial for retail SMEs to comprehend
digital payment systems, and the probability or likelihood of them adopted
significantly increases. Another point to be noted is regarding the
significance level of p (<0.001), which is marked as *** and shows a
strongly significant influence on the result. From the strongly significant influence
and high level of significance, it is concluded that Hypothesis H1a is accepted
and it strongly confirms that perceived utility is a critical element exerting
a major effect on the implementation of digital payment systems among small and
medium firms in the retail sector.
H1b: The
hypothesis test findings demonstrate that Perceived Ease of Use significantly
influences the uptake of digital payments positively by retail SMEs, evidenced
by a high coefficient value of 0.788. This illustrates that as digital payment
methods are more comprehensible and manageable for shops, their propensity to
embrace these systems rises markedly. The association is statistically
significant, as shown by the p-value of *** (p < 0.001), demonstrating that
the effect is unlikely to be attributable to chance. Consequently, H1b is
validated, confirming Perceived Ease of Use as a significant predictor
influencing digital payment acceptance among retail SMEs.
H1c: The
results for this model show that Security/Trust has a considerable influence on
the acceptance of digital payment methods for SME retail businesses. Indeed,
the hypothesis H1c predicted that an improvement would provide a beneficial
influence on the comprehensive acceptance of digital payment systems, as well
as the outcomes strongly support this hypothesis. The coefficient of 0.952
represents an extremely positive correlation and shows that with an improvement
in perceptions of security and trust, there is an increased significant
probability of adopting digital payment systems. Further, with the p-value
represented by *** it shows that it is significant at its most extreme level.
Therefore, it confirms that Security/Trust is a significant aspect that
favourably influences the implementation of digital payment systems by small
and medium-sized retail organisations.
H2: The
findings from the regression study provide robust empirical evidence for
Hypothesis H2, which posits the use of digital payments enhances operational
efficiency of small and medium retail firms. The coefficient value of 0.813
indicates a significant positive impact, implying that increased digital
payment acceptance is closely linked to improved operational efficiency.
Furthermore, the p-value denoted by *** verifies that this association is statistically
significant at standard significance thresholds. Consequently, Hypothesis H2 is
affirmed, substantiating the conclusion the digital payment solutions
substantially growing the operational efficiency of retail small and
medium-sized organisations.
H3: The
research indicated that Operational Efficiency substantially improves the Business
Performance of retail SMEs, as evidenced by a high coefficient value of 0.982.
This illustrates that advancements in operational efficiency are intricately
linked to significant increases in business performance. Moreover, the
association is statistically significant, as indicated by the *** p-value,
which provides robust evidence against the null hypothesis. Consequently,
Hypothesis H3 is accepted, substantiating the assertion that operational
efficiency significantly contributes to enhancing the overall performance
outcomes of retail SMEs.
DISCUSSION
This study
indicates that multiperception and operational skills profoundly influence the
implementation and efficacy of digital payment systems in small and
medium-sized organisations retailers is extremely important. The positive
support for the perceived usefulness construct (H1a) indicates that, being
capable in terms of operational, strategic values through digital technology,
SME retailers can easily adopt digital payments. Moreover, the support for thess
ease of use construct (H1b) indicates that simple digital interfaces are
important in terms of the success of digital payments, reducing resistance
stemming from the complexity of the technology itself. Furthermore, the
importance of security, trust, and critically valued digital financial
processes (H1c) support views that reliant, trustworthy, and safe digital
financial processes are preferred by SME retailers, thus using digital payments
when trusted to be secured. Besides that, support for H2 indicates that
implementing digital payments can enhance operational efficiencies in SME
retailers in respect to efficient digital payment implementation that can
reduce human efforts through accurate threshold values. Additionally, support
for H3 indicates that the creation of operational efficiencies can lead to
improvements in terms of businesses, thus implying that efficient businesses
are accurately linked with improved conditions of businesses or businesses in
terms of great prosperity. Overall, all findings support that SME retailers
have a strong performance-technology linkage in ensuring improved conditions of
businesses through successful digital payments stimulated by positive-attitude
valued constructs.
CONCLUSION
The findings
of this research consist of substantial empirical proof that digital payments
offer a fundamental motivator for operational improvement in retail SMEs in
India. From the population demographics, it is seen to comprise mainly young
SMEs of different experience backgrounds in digital payments, indicating that
this young and emerging population is slowly and steadily prepared for
technological advancements in this new realm of digital payments. The testing
for measures on CFA, Reliability, KMO, and Bartlett’s Test shows the acceptance
that all variables considered and used for analysis in this study are valid,
reliable, and of significant goodness for Structural Equation Modelling. The
testing of this hypothesis is extremely supportive of this structure,
accentuating that basic mastery perceptions of utility, user-friendliness, and
security or trust of systems and solutions have significant milestones in
making this hypothesis and resultant proposal acceptable for consideration in
this analysis. Digital payments have actually made operations simple and
efficient and hence have significantly improved business performance. The
significance, power, and/or value of coefficients covary in firm beliefs that
opinions and related operational improvements from technology have addressed an
important aspect in making an operational difference for SMEs. The beliefs of
this study probate that digital payments are acting and working as operational
managers to further enhance an operational improvement in generalized business
performance in retail SMEs. These online payments have enhanced from being a
mere operation solution process, as they are operating in a totally different
new environment of being efficient and effective. The implementation of secure,
easy, and fruitful online payments for SME retail businesses can enable and
empower them to have improved operations for complete customer bliss and
happiness in the ever-growing.
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