The emergence of digital payment systems within the Indian banking sector has brought significant changes in consumer behaviour, particularly in the adoption and usage patterns of government-led digital payment services such as Unified Payments Interface (UPI), Bharat Interface for Money (BHIM), Aadhaar Enabled Payment System (AePS) and RuPay. The COVID-19 pandemic further accelerated the adoption of digital payment mechanisms, as government policies and initiatives encouraged consumers to shift from conventional payment methods towards digital alternatives [1]. Moreover, increased internet accessibility, widespread smartphone adoption and continuous government interventions have strengthened the role of digital payments as a vital component of India’s financial ecosystem [2]. Despite the rapid growth of digital payment platforms, differences remain in consumer experiences and perceptions regarding the use of government-led digital payment services provided through public sector banks and private sector banks. Consumer cognitive perceptions and levels of understanding influence their decision-making processes and adoption behaviour at different stages [3]. Furthermore, challenges such as inadequate awareness, security concerns, fraudulent activities and technical difficulties continue to limit the broader acceptance of digital payment services. Therefore, it is essential to critically examine consumer perceptions regarding the adoption of government-led digital payment services and understand the variations between public and private sector banking channels. Although previous studies have extensively examined consumer behaviour towards digital payments, limited research has focused on government-driven digital payment platforms and the differences in consumer experiences across public and private sector banks. This research gap highlights the necessity of investigating consumer perceptions, adoption determinants and challenges associated with government-led digital payment services.

The adoption of digital payment systems has been extensively studied from the perspectives of consumer behaviour, technological acceptance, trust, financial inclusion and government intervention. Yiing Jia Loke et al. [4], examined digital financial service adoption using the UTAUT framework and found that performance expectancy, effort expectancy, social influence, trust and government intervention significantly influence adoption, with trust acting as a major mediator. Vivek Sharma and Aamir Aijaz [1], highlighted that government policies, reforms and awareness initiatives during COVID-19 accelerated digital payment adoption, emphasizing the need for continued policy support. Similarly, Pradeep and Aditi identified demonetization, smartphone penetration and internet accessibility as major contributors to digital payment growth. Consumer perception and usability emerged as important factors in digital payment adoption. Sakshi Gohel et al. [2], found that convenience and security encourage adoption, whereas network issues and lack of awareness remain barriers. Mallika and Wijeweera [5], confirmed that usefulness, ease of use, trust and mobility influence mobile wallet adoption. Pilar Carbonell et al. [3], observed that usefulness, accessibility and affordability affect both adoption intention and actual usage behaviour. Mohd. Imran Sharif and Dr. Balasubramanian [6], emphasized the importance of service quality, technical support and customer satisfaction in strengthening trust in banking services. Demographic and behavioural factors also influence digital payment adoption. Cho Yoon Cheong [7], highlighted generational differences, where younger users focus on convenience and personalization. Ida Claudia Panetta et al. [8] identified usability, cognitive limitations and security concerns as barriers among older users. Dr. Naveen Prasadula [9], revealed that financial literacy, awareness, skills and gender differences affect cashless payment usage. Government initiatives have played a crucial role in promoting financial inclusion through digital payments. Anukriti Mishra and Kranti Singh [10], found that UPI growth and PMJDY account penetration improved financial inclusion. Koustub Kanti Ray [11], identified reliability, assurance and social connectivity as important factors influencing perceptions towards PMJDY. Kobe Lee et al. [12] highlighted that digital literacy gaps and trust issues continue to affect mobile banking adoption. Abhishek Agarwal [13], discussed the opportunities and challenges associated with electronic payments and suggested policy measures for improving adoption. Technological advancements in fintech and artificial intelligence have further transformed digital payment ecosystems. Ghunaimi Hisham et al. [14], identified security and ease of use as major drivers of mobile payment adoption among SMEs, while cost and authentication issues remained barriers. K. Gunawardena [15], emphasized the role of digital and AI literacy in enhancing mobile banking adoption. Dr. Sumit and Dr. Shailendra reported that digital banking services improve customer convenience, efficiency and loyalty. Bibliometric and systematic studies also provide broader insights into digital payment research. Ruchika and Neha identified UPI as a dominant theme in Indian digital payment presearch and suggested further exploration of perceived risk and technology acceptance factors. Sina and Vennila [16], found that convenience and user-friendly digital platforms are essential for sustainable banking adoption in rural areas. Although previous studies provide valuable insights into digital payment adoption, most research focuses on general digital payment systems or private fintech platforms. Limited studies have examined government-led digital payment services such as UPI and BHIM while comparing consumer perceptions across public and private sector banks. Therefore, this study attempts to address this research gap by analysing consumer perceptions, adoption factors and challenges associated with government-led digital payment services in the Indian banking sector.

• To identify the key dimensions of consumer perception towards government-led digital payment services
• To analyse the influence of consumer perception factors on the adoption of government-led digital payment services
• To compare consumer perception and adoption behaviour between public and private sector bank customers

     Hypotheses Of the Study

• H1: Consumer perception towards government-led digital payment services is influenced by multiple underlying factors
• H2: Consumer perception factors have a significant influence on the adoption behaviour of government-led digital payment services
• H3: (Comparison): Independent Samples t-test
  There is a significant difference in consumer perception and adoption behaviour of government-led digital payment services between public and private sector bank customers.

A mixed-method approach is adopted by employing both qualitative and quantitative analysis. A survey questionnaire was designed to measure the demographic profile, consumer awareness and usage of digital payment services, consumer perception towards government-led initiatives in digital payment services, to evaluate consumers’ satisfaction and experiences with digital payment services, to evaluate the contraints and hardships experienced by consumers in using digital payments and to compare perceptions on public (SBI Bank) versus private sector (HDFC Bank). The study relies on data collected from original and published sources. Primary data is collected directly from the consumers of HDFC and SBI banks. From the population of the study, the data was obtained from a sample of 390 consumers. To ensure an appropriate sample size, 222 consumers of SBI Bank and 168 consumers of HDFC Bank are selected using stratified, cluster and convenience sampling. The consumers of these banks belong to various organisations, commercial zones and residential areas in Hyderabad, Telangana. The secondary data is collected from bank websites, RBI publications, Fintech reports and Government publications.

The collected data was examined using descriptive statistical tools such as frequencies, percentages, mean and standard deviation for preliminary analysis and inferential analysis of data is made using exploratory factor analysis, SEM and t-test (Table 1).

Table 1: Demographic Profile

Hypothesis 1

Consumer perception towards government-led digital payment services is influenced by multiple underlying factors.

An Exploratory Factor Analysis of Consumer Perception Variables towards Government-Led Digital Payment Services

Exploratory Factor Analysis (EFA) was performed to identify the underlying dimensions that shape consumer perception towards government-led digital payment services. The analysis included 90 perception items covering awareness, trust, security, usability, bank support and challenges. Principal Component Analysis (PCA) with eigenvalue greater than 1 was applied using listwise deletion (N = 390). EFA was executed to extract meaningful components and validate factorability for Hypothesis 1 (Figure 1) (Table 2).

Table 2: KMO and Bartlett’s Test for Factorability

Figure 1: Demographic Profile

Figure 2: KMO and Bartlett’s Test for Factorability

Interpretation

The value of KMO measure 0.941 demonstrates an exceptional sampling adequacy confirming that the pattern of correlation among the perception variables is compact and suitable for extraction of factors. Bartlett’s Test of Sphericity is significant (p = 0.000<0.05), demonstrating that the correlation matrix is deviating from identity matrix thereby by confirming the presence of sufficient inter-correlations. Therefore, the perception dataset is significantly appropriate for factor analysis, supporting the use of EFA for testing Hypothesis (Table 3).

Table 3: Rotated Component Matrix–Factor-wise Item Loadings (Loading≥0.60)

Source: Primary Data

Interpretation

The Rotated Component Matrix provides a clean factor structure where item blocks load strongly onto their expected constructs:

• Trust items (TR1–TR15) form a clear Trust factor (highest loading TR1 = 0.746)
• SE items form a strong Security/Self-Efficacy factor (SE3 = 0.766; SE6 = 0.762)
• AW items load strongly as Awareness (AW7 = 0.766; AW4 = 0.752)
• US items load as Usability (US5 = 0.739; US1 = 0.729).
• BS items load as Bank Support/Infrastructure Support (BS7 = 0.749; BS2 = 0.747)
• CH items form a distinct Challenges factor (CH1 = 0.761; CH3 = 0.731)

Hypothesis 2

Consumer perception factors have a significant influence on the adoption behaviour of government-led digital payment services.

Mean Score Analysis of Consumer Adoption Level towards Government-Led Digital Payment Services

Understanding the level of adoption of government-led digital payment services is essential to assess the success of India’s digital financial inclusion initiatives.

The high level of adoption is not only confined to awareness and accessibility but also other aspects like usability, trust and acceptance behavioural among consumers. In the present analysis, adoption behaviour of consumers was measured applying 15 statements related to convenience, frequency of usage and integration of digital payments in their routine life of financial activities. In order to evaluate the overall adoption level, a composite adoption score was calculated by summing up the responses across these 15 items of each respondent. In order to determine whether the consumers exhibit a low, moderate, or high level of adoption, mean score analysis was employed. The statistical analysis revealed that the consumers demonstrate a moderate to high level of adoption of government-led digital payment services and this analysis supports Hypothesis -2 strongly (Table 4, Figure 3).

Table 4: Descriptive Statistics of Consumer Adoption Level

Source: Primary Data

Figure 3: Descriptive Statistics of Consumer Adoption Level

The results shown by descriptive analysis revealed that the score of overall adoption of government-led digital payment services ranges from 18.00 to 75.00, which has substantial variability among respondents’ adoption behaviour. The mean adoption score of 51.68 with a standard deviation of 13.35 suggests a reasonably dispersed yet centrally clustered distribution of adoption levels. The observed mean value of the adoption score, 51.68 derived from 15 Likert-scale items, lies well above the theoretical midpoint and shows that, on average, consumers demonstrate a moderate to high level of adoption of government-led digital payment services. The relatively high mean score reflects the frequency of usage and growing integration of digital payment platforms into routine financial transactions.

The value of standard deviation 13.35 signifies a natural difference in intensity of adoption across respondents and overall central tendency strongly slopes towards positive adoption behaviour of the consumers. Based on the above analysis, hypothesis-2 is accepted proving that the consumers exhibit moderate to high level of adoption of government-led digital payment services.

Hypothesis 3

There is a significant difference in consumer perception and adoption behaviour of government-led digital payment services between public and private sector bank customers.

The group statistics indicate that customers of private sector banks report a slightly higher mean adoption score (Mean = 52.33) compared to customers of public sector banks (Mean = 51.19). However, the difference in mean values is relatively small. The standard deviations for both groups are comparable, suggesting similar variability in adoption behaviour among public and private bank customers. This preliminary comparison indicates a marginal difference, which requires statistical testing to determine its significance (Table 5).

Table 5: Group Statistics: Adoption Behaviour by Bank Type

Source: Primary Data

Levene’s Test for Equality of Variances yields a non-significant result (Sig. = 0.468 > 0.05), indicating that the assumption of equal variances is satisfied. Therefore, the results obtained under the “equal variances assumed” condition are considered for interpretation. The t-test result shows that the difference in mean adoption scores between public and private sector bank customers is not statistically significant (t = -0.833, p = 0.405>0.05). The confidence interval for the mean difference includes zero, further confirming the absence of a significant difference. This implies that bank type does not significantly influence consumers’ adoption behaviour of government-led digital payment services. Hypothesis 3 is rejected. Although private sector bank customers exhibit a marginally higher mean adoption score, the difference is not statistically significant. Hence, there is no significant difference in adoption behaviour of government-led digital payment services between public and private sector bank customers (Table 6, Figure 4).

Table 6: Independent Samples t-Test for Adoption Behaviour

Figure 4: Independent Samples t-Test for Adoption Behaviour

To assess the success of Indian digital financial inclusion initiatives, understanding the level of adoption of government-led digital payment services is essential. From the analysis of primary data, the findings revealed that consumer perception towards government-led digital payment is shaped by multiple factors such as awareness, usability, trust, Bank support, security and challenges faced. To validate the conceptual framework of the study, the rotating component matrix provided a clear factor structure which strengthens the first hypothesis. This emphasises that consumer perception is not a single construct but a composition of interrelated dimensions. The analysis on adoption behaviour demonstrated a moderate to high level of adoption of government-led digital payment services among the consumers. This reinforces the second hypothesis, indicating that adoption behaviour is directly influenced by perception factors. Consistent with the prior literature, trust & security appear to be the strong drivers underscoring the significance of confidence in sustainable usage of digital platforms. Simultaneously, awareness & usability also played a crucial role, reflecting the necessity of instinctive design and effective communication in promoting adoption of digital payments. The comparative analysis of private and public sector banks in adoption behaviour revealed that consumers of private sector banks report slightly higher adoption compared to consumers of public sector banks. Since the difference is not substantial, this supports the third hypothesis that institutional affiliation may not be a decisive factor in shaping the adoption behaviour. Hence, there is no difference in adoption behaviour of government-led digital payment services between public and private sector bank consumers.

The present study illustrated that consumer perception on government-led digital payment services is shaped by multiple factors and these factors influence the adoption behaviour in their routine financial activities. The comparative analysis between public and private sector banks revealed marginal differences in adoption behaviour and suggested that the determinants at the consumer level are more typical than institutional affiliation in driving adoption. Overall, the findings of the study validate the intended hypothesis and emphasise the significance of multifaceted consumer perception in understanding consumer behaviour. The research contributes to the expansion of existing literature on digital payment adoption by providing empirical evidence from the context of both public and private banking. Hence, the results of the study convey major implications for policymakers, government, banks and IT providers. The study suggests that the government should enhance security and build trust in digital payment platforms by providing robust security and transparent communication, which strengthens consumer confidence. The government should enhance digital literacy programs, especially among the segments of lower adoption intensity. To facilitate effortless adoption, both public and private sector banks should focus on the best consumer services and infrastructure support. A further study is needed to explore demographic moderators such as age, income, education which may be helpful in understanding the variability in adoption behaviour. Alongside, longitudinal research may also be helpful to assess the progress of the consumer perception with the changes in government policy and technological advancements.

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