Understanding Consumer Acceptance for Blockchain-Based Digital Payment Systems in Bhutan

Abstract

Blockchain is a secure, digital ledger that enables faster transactions, reduces fraud, lowers costs, and enhances transparency. The blockchain is capable of changing the face of digital payments by providing greater opportunities for transformation. Consumer acceptance in emerging markets such as Bhutan depends on a number of key factors. This paper explores the impact of performance expectancy, effort expectancy, social influence, and facilitating conditions on consumer acceptance of blockchain-based digital payment systems in Bhutan. Sustained by the Unified Theory of Acceptance and Use of Technology (UTAUT), the study uses PLS-SEM to analyze survey data from 302 respondents. The results show that performance expectancy, the expectation of blockchain’s usefulness, is the most influential factor determining customer acceptance. Effort expectancy and facilitating conditions are equally important. Social influences, although rather marginal, play an important role in Bhutan’s collectivist culture. The paper sheds light on factors for consumer acceptance of blockchain adoption. The findings add to the literature on blockchain adoption in burgeoning economies and provide the foundation for further research on blockchain adoption in multi-cultural contexts.

1. Introduction

The blockchain has become a cornerstone of the digital innovation revolution [1,2], transcending its original purpose. As a distributed and decentralized ledger, blockchain ensures that transactions remain immutable, transparent, and secure across multiple nodes [3,4,5]. These capabilities make it beneficial in applications that require the accuracy and security of data like financial, supply chain, and digital identity verification [6,7]. For digital payments, blockchain is going to revolutionize the industry [8,9], as it will eliminate redundancies, reduce transaction fees, and enable payments to be more secure than they are in existing systems [10,11]. Many nations are looking at integrating blockchain into their digital payment ecosystems in order to take advantage of these features [12,13,14,15].

While blockchain has broad applications, its impact on the banking sector is highly significant. Banks can benefit from private blockchain platforms such as Hyperledger Fabric, R3 Corda, and Quorum because they deliver secure and efficient solutions that meet regulatory requirements [16,17]. The system enables controlled access paired with real-time settlements, automated payments, and cost reductions, along with financial data protection. Private blockchains improve financial accessibility by facilitating smoother cross-border transactions with fewer intermediaries involved [18]. Bhutan can achieve secure digital payment scalability through permissioned blockchain networks that also maintain regulatory compliance.

Modern economies require digital payments because of their unmatched ease, financial inclusion, and simplicity [19,20]. The speed of contactless payments paved the way for digital payments and, during the COVID-19 crisis, proved both adaptable and durable [21,22,23]. In the context of Bhutan, where digital payment adoption is growing, blockchain can serve as a key enabler of financial transformation. The Royal Monetary Authority (RMA), the central bank, is leading efforts to digitalize banking services to enhance financial inclusion and digital literacy [24]. The nation’s digital payment network includes mobile wallets, Internet banking, and QR-code payments, which are gaining popularity. However, digital literacy and data security concerns could hinder mass adoption [25]. Blockchain implementation within Bhutan’s digital payments infrastructure can solve these challenges. The blockchain can also be the tool to enable Bhutan’s digital transformation and economic growth by facilitating a safer, faster and more inclusive payment mechanism. Several factors will influence consumers’ acceptance of blockchain-based digital payment systems [26,27] in Bhutan, such as sophisticated socioeconomic and infrastructure challenges that define blockchain in countries [28,29]. A lack of access to high-level infrastructure [30], digital literacy differences [31] and a shift in regulatory expectations [32] can be consumers’ catalysts for acceptance. Consumer acceptance is the key to the successful adoption of blockchain in digital payment infrastructures [33,34,35], as it directly determines whether users are going to embrace and use these new innovations [11,36] in their daily financial transactions. Acceptance depends not just on the fundamental technical advantages of blockchain such as security, transparency and decentralization but also on how potential users perceive its advantages and practicalities within their socio-economic and cultural environment [37,38]. Consumer acceptance depends on a number of factors, but benefits are by far the most important [39,40]. Most people will embrace blockchain technology if they are convinced it will make their financial lives easier, cheaper, and more secure [41]. Similarly, ease of use, or the ease with which the system can be used [42,43], is critical in establishing consumer acceptance and eliminating barriers to adoption [44,45,46]. Social influence from the perceptions and actions of colleagues, family, and friends can also motivate or derail acceptance [47,48], especially in tight-knit communities [49] such as Bhutan, where consensus-making is prevalent. Further, establishing the infrastructure required for the implementation, including reliable Internet connections [50], digital education programs, and regulations, is a key enabler for the acceptance and adoption of blockchain-based systems [51,52].

This paper utilizes the UTAUT model due to its widely recognized effectiveness in measuring technology acceptance across various domains, as it integrates eight key technology adoption models, such as the Theory of Reasoned Action (TRA), the Technology Acceptance Model (TAM), the Motivational Model (MM), the Theory of Planned Behavior (TPB), the Diffusion of Innovation (DOI) and the Task–Technology Fit (TTF) theory [53]. It combines social and environmental conditions with facilitating conditions needed for blockchain adoption, which TAM and TPB overlook by focusing solely on individual perceptions. Although TTF and DOI theory models emphasize aspects of the technology–organization alignment and innovation spread, they overlook important factors like trust and social influence along with regulatory support. UTAUT stands out with its comprehensive and predictive approach because it addresses critical gaps that render it ideal for researching the adoption of blockchain-based digital payment systems.

Despite the increasing global interest in blockchain technology, empirical research on its adoption in Bhutan remains scarce. This paper aims to address a critical research gap by pursuing the following objectives: (1) evaluate whether performance expectancy, effort expectancy, social influence, and facilitating conditions significantly influence consumer acceptance of blockchain-enabled digital payment systems in Bhutan and (2) examine the relevance of these factors within the unique cultural and economic context of Bhutan. This paper makes significant theoretical contributions by validating UTAUT in the developing, landlocked economy of Bhutan, enriching the understanding of technology adoption in diverse socio-economic contexts. It provides recommendations for stakeholders to enhance consumer acceptance of blockchain-based digital payments and equips developers with strategic insights for designing solutions aligned with Bhutanese consumer expectations. Using the statistical analysis and partial least squares structural equation modeling (PLS-SEM), the paper determines this correlation and then reveals conclusions and practical recommendations.

The structure of this paper is as follows: Section 2 reviews the relevant literature. Section 3 outlines the theoretical framework and hypotheses. Section 4 details the research methodology. Section 5 presents the results. Section 6 discusses the findings. Section 7 presents limitations and future directions. Section 8 provides the conclusion.

2. Literature Review

2.1. Blockchain Technology

Blockchain is an innovative technology that has applications beyond cryptocurrency [54,55,56]. Since its inception in 2008, the three defining attributes of the blockchain—decentralization, cryptography, and a verifiable ledger—make it a technological revolution [55,57]. Its uses range from financial services to supply chain and health care and have a significant potential to revolutionize digital payment processes [10,58,59]. Blockchain solves most of the drawbacks of traditional payment systems, including high transaction fees, transaction delays, and fraud [10,14]. The mass adoption of blockchain for digital payments is dependent on technical and consumer factors [60]. According to the UTAUT model [53], the cognitive, social, and infrastructure drivers of blockchain payments shape how consumers will accept it. Performance expectancy, effort expectancy, social influence, and facilitating conditions are found to be central to technology adoption.

2.2. Blockchain-Based Digital Payment System

Blockchain adoption in the developed world has gradually taken off as people and businesses begin to understand the benefits of blockchain [32,61], especially when it comes to financial sectors [10,32]. Users have access to strong digital infrastructure, technological knowledge, and conducive regulatory landscapes, which drive the adoption of blockchain in industries such as digital payments, supply chain management, and health care [61]. Peer-to-peer payments and blockchain-based digital wallets have become commonplace thanks to increasing consumer confidence in new financial technologies [62,63]. Studies in these areas offer the ability to analyze the ways in which user experience, ease of use, and transparency of regulation drive consumers’ adoption of blockchain-based applications.

The blockchain can revolutionize the developing world by resolving centuries-old issues of financial inclusion, governance, and efficiency [64,65]. In places where bank services are scarce, blockchain technology could make financial services available in the form of digital wallets and peer-to-peer transactions for people who are not currently enrolled in banks [66]. It can eliminate intermediaries, which reduces transaction costs and makes it more accessible [67,68]. Blockchain could also lead to better transparency and accountability in governance through tamper-proof records of land registers, public funds, and supply chain tracking, reducing corruption and inefficiency [69,70]. Furthermore, it enables cross-border remittances with shorter processing times and low fees [71], making it an essential asset for economies that depend on remittance flows [72,73]. Furthermore, blockchain-based smart contracts can support microloans and crowdfunding, which stimulate entrepreneurs and economic growth [74,75]. These uses make blockchain a powerful enabler of sustainable growth, digital inclusion, and economic opportunity in the developing world [76,77].

2.3. Prior Studies on Blockchain-Based Digital Payment Systems

Studies have explored various aspects of blockchain integration into financial services. The key findings and methodologies of these studies are summarized in

Table 1. Prior studies on blockchain-based digital payment systems.

Study	Methodology	Theoretical Framework	Key Findings	Limitations
[78]	An empirical study was carried out through a survey and analyzed using PLS-SEM.	UTAUT2	The study confirms a strong measurement model, with behavioral intention significantly driving cryptocurrency usage.	Regulatory support and experience were identified as key factors but not empirically tested.
[79]	An empirical study was carried out through a survey and analyzed using PLS-SEM.	UTAUT2	Trust, transaction transparency, volatility, and facilitating conditions positively influence adoption through intention to use.	Does not address liquidity shortages in Malaysian banks, price volatility, acceptability, transaction factors, or pandemic effects, and relies solely on cross-sectional data.
[35]	Systematic literature review	UTAUT	Security, privacy, transparency, and regulation as key factors for trust, while performance expectancy, effort expectancy, social influence, and facilitating conditions drive acceptance.	Does not extensively explore blockchain adoption in digital payment systems from the user’s perspective.
[80]	An empirical study was carried out through a survey.	UTAUT	Personal innovativeness, trust, security, effort expectancy, performance expectancy, and social influence significantly influence blockchain adoption.	Lack of empirical validation for real-world blockchain adoption, and the unsupported role of technology awareness.
[81]	An empirical study was carried out through a survey and analyzed using PLS-SEM.	UTAUT	Performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risk, and trust significantly influence blockchain adoption.	Limited by the lack of existing academic work on blockchain adoption factors, the absence of empirical validation for the proposed model
[82]	An empirical study was carried out through a survey and analyzed using PLS-SEM.	UTAUT	Performance expectancy, social influence, personal innovativeness, and online reviews as key drivers of adoption.	Further development of technology adoption models is needed to include factors like age and gender and exploration of cultural and pandemic-related influences.
[83]	An empirical study was carried out through a survey and analyzed using PLS-SEM.	UTAUT	Performance expectancy, effort expectancy, hedonic motivation, perceived trust, and facilitating conditions significantly influence blockchain adoption for mobile banking.	The limitation of this study is that it overlooks psychological factors like privacy and security.
[84]	An empirical study was carried out through a survey and analyzed using PLS-SEM.	UTAUT	Social influence, financial literacy, and perceived risk significantly impact behavioral intention to adopt blockchain in digital banking.	Small sample size focused on individuals with basic blockchain knowledge, limiting generalizability.

below.

2.4. The Context of Bhutan

The financial technology industry in Bhutan is experiencing substantial expansion with programs such as FinTechBhutan [85] from the Royal Monetary Authority, which advances technological solutions to improve financial accessibility and efficiency. Bhutan now supports real-time payment solutions and mobile wallets that work across borders with India’s Unified Payments Interface (UPI) and the RuPay card network [86] to enable smooth digital transactions and decrease cash dependency. The inauguration of the ORO Bank in 2024 marks a significant achievement for Bhutan as it becomes Asia’s first full-reserve digital bank [87], demonstrating its dedication to digital banking as a platform for sustainable financial growth. Incorporating blockchain technology into Bhutan’s digital payment platforms offers potential improvements in transparency along with better security and operational efficiency. Through its decentralized ledger system, blockchain technology eliminates third-party dependencies while reducing transaction fees and significantly improves cross-border payment methods, resulting in faster and cheaper international financial exchanges. Blockchain technology generates user trust through its transparent and immutable transaction records, which match Bhutan’s financial system’s priorities of trustworthiness and integrity. Implementing blockchain technologies will enable Bhutan to reshape its payment systems and increase financial inclusion by extending digital financial services to disadvantaged groups while advancing its goals of sustainable development and economic stability. Bhutan’s banking and financial sector shows growing interest in blockchain technology for improved efficiency and transparency. The Digital Drukyul Program prioritizes the incorporation of cutting-edge technologies such as blockchain into financial operations [24]. The Royal Monetary Authority has worked together with global organizations to evaluate blockchain applications for international payments and central bank digital currencies (CBDCs) [88]. These efforts work to reduce transaction fees while making remittances more efficient and providing financial services to rural areas that lack mainstream banking facilities.

These advancements have not resolved all barriers Bhutan faces with blockchain adoption. The adoption of blockchain technology in Bhutan is hindered by inadequate digital infrastructure alongside widespread low digital literacy levels and unstable regulatory conditions. The absence of dependable Internet access for rural populations prevents them from utilizing blockchain-based financial systems. The technical complexity of blockchain technology generates difficulties related to user effort expectancy like ease of use and the availability of supporting resources and conditions. The absence of clear regulations makes businesses and consumers cautious about using blockchain-based financial systems. The existence of these barriers demonstrates the requirement for specific policy measures and financial education programs alongside a clear regulatory structure to enable the acceptance and adoption of blockchain systems. The successful deployment of blockchain technology for digital payments in Bhutan relies on effectively addressing these challenges.

However, from Table 1, it is very clear that Bhutan lacks research to assess the acceptance of blockchain by consumers. There is a need to overcome disparities in infrastructure, technical knowledge, and socioeconomics. Blockchain acceptance in Bhutan faces challenges due to limited awareness, regulatory uncertainty, security concerns, and trust in traditional banking. Infrastructure gaps and cultural norms could further hinder adoption, with high implementation costs raising economic concerns. Overcoming these requires education, clear regulations, and pilot initiatives to build trust and demonstrate benefits. Bhutan’s focus on Gross National Happiness (GNH) offers a unique context for integrating blockchain use with equity, inclusion, and sustainability. The paper bridges the research gap by using the UTAUT model and PLS-SEM to analyze the factors that determine consumer acceptance of blockchain digital payment systems. The research provides guidance for policymakers and financial institutions, along with technological entrepreneurs, to advance digital transformation in Bhutan with a focus on reaching underserved communities.

3. Theoretical Framework and Hypothesis Development

3.1. Theoretical Framework

The conceptual diagram is proposed, as shown in Figure 1, based on the systematic review [35] carried out to identify the factors that influence the trust in and acceptance of blockchain adoption in digital payment systems. The paper also adopted UTAUT as the theoretical framework for understanding how blockchain acceptance will be driven by performance expectancy, effort expectancy, social influence, and facilitating conditions. UTAUT, a framework developed by Venkatesh et al. [53], is a powerful theory of the acceptance of technology based on constructs such as performance expectancy, effort expectancy, social influence and facilitation conditions. The systematic review suggested that UTAUT constructs could also be applicable since they have an impact on acceptance, while performance expectancy, effort expectancy, social influence, and facilitating conditions may be significant contributors to consumer acceptance. Those considerations could have significant implications for the implementation of blockchain in Bhutan’s digital payments sector. This paper is focused solely on acceptance factors and takes performance expectancy, effort expectancy, social influence, and facilitating conditions as independent variables. The dependent factor of the model is whether or not the consumer is willing to accept the adoption of blockchain for digital payments. The acceptance in this paper represents the behavioral intention to adopt blockchain-based digital payment systems, reflecting consumers’ willingness and readiness to use the technology. This paper analyzes these factors that influence consumer acceptance of blockchain adoption in Bhutan’s digital payment systems. Through the UTAUT framework, this paper aims to determine whether these considerations, highlighted in the literature, resonate with Bhutan’s unique cultural and regulatory context and explain the consumer’s acceptance of blockchain adoption for digital payment systems. It will assess the fit of the UTAUT constructs in the context of Bhutan, emphasizing the role of performance expectancy, effort expectancy, social influence, and facilitating conditions in shaping acceptance. This study will investigate acceptance considerations in the adoption of blockchain in Bhutan, serving as a reference for future adoption research.

The adoption of blockchain technology in digital payment systems is significantly influenced by acceptance [35,89,90,91], which is shaped by factors such as performance expectancy, effort expectancy, social influence, and facilitating conditions [35]. This paper explores how these factors affect consumer acceptance in Bhutan’s digital economy. The development of the following hypotheses is based on the systematic review [35] conducted to explore and validate the factors that influence acceptance of blockchain adoption in the digital payment system.

3.2. Performance Expectancy

Performance expectancy (PE) measures the amount of value consumers will receive from a technology [53,92,93]. It is a major consideration in the use of that technology, especially when it comes to digital payments [94,95,96]. It measures people’s perception of how that technology will improve their productivity or give them an actual benefit over the current system. Dwivedi et al. [97] and Javaid et al. [10] emphasize that users are more willing to accept blockchain if it offers tangible advantages, including faster transaction speeds, increased security, and increased efficiency. This is especially true in financially disadvantaged countries such as Bhutan, where banking services are limited in scope and availability. Al-Jaroodi and Mohamed [98] further underscore the fact that blockchain is efficient, secure and inexpensive, making it an attractive candidate for use in these applications. To gain traction, customers in Bhutan’s digital payment ecosystem will need to feel that blockchain delivers improved payments by reducing errors, improving processing times, and increasing security. Research consistently finds that perceived usefulness, which lies at the heart of performance expectancy, is a very good predictor of technology adoption [99,100,101]. User adoption is more inclined toward technologies that offer valuable benefits. In Bhutan, with limited bank systems and digital literacy still being hurdles, blockchain could reduce waste and benefit both urban and rural citizens [29]. Using these tangible benefits and creating higher levels of user engagement, blockchain can help to gain acceptance and spur its adoption in digital payment infrastructures. Therefore, we propose the following hypothesis:

H1: Performance expectancy positively affects consumer acceptance of blockchain adoption for digital payments in Bhutan.

3.3. Effort Expectancy

The level of effort expectancy (EE), the degree of technology’s perceived ease of use, determines adoption [53,93]. It describes how much users think using a system will not be challenging. When dealing with technology as complex as blockchain, there is a need for easy-to-use interfaces, efficient system designs and support systems to drive adoption. Usability was found to be one of the largest drivers of technology adoption [102,103]. Any system that cuts down on the amount of mental effort required and makes tasks easier would be embraced more widely [104]. Successful adoption of blockchain-based digital payments is contingent upon reducing perceived technical complexity through ease of use [105], localized functionality suited to Bhutanese cultural and linguistic conditions, and well-established training materials. Making the blockchain easier to use, for example, by using transactions and wallets, can make blockchain accessible to users of varying digital skills. The effort expectancy also involves addressing infrastructural and accessibility problems [106]. These efforts are particularly important in rural Bhutan, where digital resources and expertise may be lacking. If it simplifies the learning curve and makes the user experience seamless, blockchain will prove to be a promising and practical digital payment alternative in Bhutan’s varied demographics. Therefore, we propose the following hypothesis:

H2: Effort expectation positively affects consumer acceptance of blockchain adoption for digital payments in Bhutan.

3.4. Social Influence

Social influence (SI) is defined as the effects of peer pressure, social norms, and social expectations on the use of technology [53,92]. In collectivist cultures such as Bhutan, where shared decision-making values are dominant, social pressure shapes individual action. Suggestions, recommendations, and incentives from trusted individuals, organizations, or community leaders can provide an ideal apropos setting for the adoption of new technologies. Social endorsement by influencers or early adopters significantly fosters trust and increases technology adoption by mitigating risks and uncertainty [97,107]. In Bhutan’s case, the support of well-regarded village elders and official representatives can prove crucial to accelerating the adoption of blockchain-based payments. Recommendations from early adopters who have experienced success with blockchain can also build trust within local communities [32,108]. This is particularly true in Bhutanese society, where decisions are often based on shared values and the voices of others we trust. Social influence can be enhanced through awareness campaigns, community events, and specific rewards, including discounts or reward points for paying using a blockchain-based platform [109]. Such practices can shift the perception that blockchain is a highly complex system and will be accepted by its peers and community networks [110]. Therefore, we propose the following hypothesis:

H3: Social influence positively affects consumer acceptance of blockchain adoption for digital payments in Bhutan.

3.5. Facilitating Conditions

Facilitating conditions (FCs) are the resources, infrastructure, and support mechanisms needed to use a technology [53,93]. It demonstrates the need for an enabling environment in which users receive tools and support to work properly with emerging technologies [111]. It emphasizes the need for robust infrastructure, such as secure Internet connections, access to devices, and transparent regulatory environments, to overcome adoption barriers [112,113]. In Bhutan, a nation with a relatively underdeveloped digital infrastructure, favorable conditions are crucial for the implementation of blockchain. Reliable Internet access in the countryside, poor access to digital technology, and regulatory uncertainties are the major barriers [51]. State-sponsored projects to build connections, regulations, and technical support are vital to a blockchain-friendly ecosystem [114]. Expanding access to the Internet in rural areas and subsidizing devices could drastically reduce user barriers to entry [115,116]. Education and training provide users with the ability to use blockchain [117]. Public documentation, practical workshops, and public education campaigns can close knowledge gaps and create user acceptance [118,119]. Technology providers and community leaders can further strengthen the infrastructure to make consumers feel empowered to use and embrace blockchain in digital payments and business processes [14,120]. By tackling these infrastructure- and resource-related barriers, Bhutan can create a platform that supports the adoption of blockchain at scale. Stimulating conditions not only eliminate technical and logistical barriers but create trust and readiness of consumers so that blockchain can seamlessly blend into the financial and business ecosystems of the country. Therefore, we propose the following hypothesis:

H4: Facilitating conditions positively influence consumer acceptance of blockchain-based digital payments in Bhutan.

4. Research Methodology

4.1. Measurement of Determinants

The paper uses a quantitative research methodology to investigate the factors that determine the consumer’s acceptance of blockchain-enabled digital payments in Bhutan. It addresses the factors that contribute to acceptance by analyzing key constructs like performance expectancy, effort expectancy, social influence, and facilitating conditions, as outlined in the UTAUT. Its quantitative design enables the analysis of consumer experience and perception using a large, statistically representative sample and provides clear data for generalization to the public. The research used a cross-sectional survey method to collect data within a certain period of time and captured consumer sentiments and attitudes toward blockchain technology across Bhutan’s specific socio-economic context. The survey instrument was drafted following a systematic review of blockchain adoption [35]. The questionnaire was constructed with due care, employing empirically proven scales to ensure reliability and validity. A draft survey questionnaire was tested with experts to identify ambiguities and improve clarity. Following their feedback, the questionnaire was revised and then piloted with a smaller sample to see its effectiveness. This iterative process ensured that the instrument was well suited to capture the nuances of acceptance within Bhutan’s digital payment system. The final questionnaire included 26 questions addressing the constructs of performance expectancy, effort expectancy, social influence, and facilitating conditions. Every construct was illustrated using items, as described in the study’s Appendix A 

Table A1. Survey items.

Constructs	Measurement Items	Source
Performance Expectancy	I am satisfied with the transaction processing speed of current existing digital payment systems. I expect blockchain-based digital payment systems to offer faster transaction processing. I anticipate lower transaction fees in blockchain-based digital payment systems. I expect blockchain-based digital payment systems to be more user-friendly than existing ones. The Performance Expectancy aspect is most influential in my decision for the acceptance and adoption of blockchain technology in digital payment systems.	[48,53,78]
Effort Expectancy	I find the existing digital payment systems easy to use. I expect it will be easy to use blockchain-based digital payment systems. Regarding the learning curve, I anticipate faster understanding and using blockchain-based digital payment systems. I think blockchain-based digital payment systems will be more accessible to all user demographics. I expect blockchain-based digital payment systems to be more convenient. The Effort Expectancy aspect is most influential in my decision for the acceptance and adoption of blockchain technology in digital payment systems.	[48,53,78]
Social Influence	My decision to use current digital payment systems has been influenced by recommendations from friends or family. Societal norms or perceptions influence my acceptance of the current digital payment systems. My decision to consider or adopt blockchain-based digital payment systems will be the most important recommendation from friends or family. I feel cultural norms and traditions in Bhutan can influence attitudes towards adopting blockchain technology. The social influence aspect is most influential in my decision for the acceptance and adoption of blockchain technology in digital payment systems.	[48,53,78]
Facilitating Conditions	I feel adequate technical support is available for users of existing digital payment systems. I believe the security measures in blockchain technology would facilitate better support and ease of use for users. I think existing infrastructure in Bhutan is ready for implementing blockchain-based digital payment systems. I think the security features of blockchain technology would enhance the support systems available for its adoption in BhutanI believe the regulatory environment in Bhutan supports fostering the adoption of blockchain-based digital payment systems. The Facilitating conditions aspect is most influential in my decision for the acceptance and adoption of blockchain technology in digital payment systems.	[48,53,78]
Acceptance	I believe that the Bhutanese government’s support of blockchain technology will encourage its adoption in digital payments. I find blockchain technology acceptable for future financial transactions. I believe blockchain will be widely accepted for digital payments in Bhutan. I feel blockchain technology will improve the efficiency of digital payments in Bhutan.	[53,78]

. Five items assessed performance expectancy, six items assessed effort expectancy, five items assessed social influence, six items assessed facilitating conditions and four assessed acceptance, constituting the crux of the analysis. The survey used a 5-point Likert scale from 1 (very strongly disagree) to 5 (very strongly agree) to make the questionnaire easy and accessible to all participants. Demographic factors, gender, education, age, and location were considered to ensure inclusion and representation. These were selected for their potential to shape blockchain technology perceptions.

The questionnaire was administered in English, as it is the primary medium of education in Bhutan. Respondents who were not proficient in English were not included in the survey to ensure accurate comprehension and validity of the response. The survey required all participants to first view an informational video embedded within the survey on blockchain technology and read an accompanying brief write-up before they could start the questionnaire to ensure their understanding of the study’s key concepts. The instructional video originated from a popular cryptocurrency payment wallet application that most Bhutanese consumers are familiar with. The video’s purpose was to deliver a contextual understanding of blockchain technology through explanations of its opportunities and challenges. The video presentation explained the fundamental concepts of blockchain for digital payments. A concise summary gave respondents insights into blockchain technology by explaining how it works and demonstrating its practical uses within financial systems. The video examined how blockchain technology evolved in digital payments and demonstrated its significant impact on Bhutan’s financial sector. The structured exposure was crucial to gather informed responses from participants who were required to watch the video and review the written material before taking the survey. Participants were assured that their responses would remain anonymous and be used solely for academic purposes, with full consent obtained before participation. The questionnaire-based approach was intended to evaluate both consumer perceptions and the social and infrastructure factors at play in blockchain adoption.

Using sophisticated statistical methods such as structural equation modeling (SEM), the research rigorously investigated the relationships and interactions between constructs. This allowed for a detailed analysis of both direct and indirect effects, providing fundamental data about the drivers and challenges affecting blockchain-enabled digital payments in Bhutan. Using hypothesis testing and statistical data, this quantitative research ensures that the findings are accurate and relevant to the larger population of Bhutan. These findings are intended to help policymakers, financial institutions, and technology companies gain a better understanding of consumers’ needs and build blockchain solutions based on Bhutan’s cultural and economic realities. This study provides a foundation for the generation of practical recommendations to accelerate the adoption of blockchain in digital payments and create a safer, more effective, and more inclusive financial ecosystem in Bhutan.

4.2. Sample and Data Collection

The research data were collected via the Murdoch Qualtrics online platform with the survey link distributed via email and social media as needed. The study aimed at Bhutanese consumers in five representative districts: Thimphu, Chukha, Sarpang, Bumthang, and Trashigang. These districts were selected to ensure a diverse and representative sample, capturing the heterogeneity of the Bhutan population in terms of location, education level, age and gender. The survey used a formal distribution method, inviting participants of all ages, genders, and educational backgrounds to provide comprehensive insights into consumer perspectives on blockchain-based digital payments. A total of 302 valid responses were retained for analysis. To ensure data reliability and accuracy, a qualification threshold was applied during the validation process. This involved excluding responses by removing incomplete responses and respondent misconduct. This final sample size was deemed adequate based on the recommended indicator-to-sample ratios for PLS-SEM, ensuring robust and reliable statistical outcomes. With this carefully curated dataset, the research provides credible insights into the attitudes and perceptions of Bhutanese consumers toward blockchain-enabled digital payment systems.

4.3. Data Analysis

Data analysis was a systematic process using sophisticated statistical instruments. SmartPLS [121] was used to perform PLS-SEM to evaluate the proposed correlations and model the constructs, and SPSS [122] was used to describe the data. PLS-SEM was selected for its ability to handle complex models with multiple constructs and indicators, as well as its flexibility in working with non-normal data distributions, which made it a suitable option for this research. This method was designed to meet the study’s goal of identifying key factors that incentivize consumer acceptance of blockchain-based digital payment systems in Bhutan. The PLS-SEM approach allowed the exploration of complex interactions that led to direct and indirect insights into how the constructs affected the willingness of consumers to accept them. This broad perspective guarantees a deeper understanding of what drives adoption.

5. Results

5.1. Descriptive Statistics

The demographics of respondents, as presented in

Table 2. Demographics of participants.

Demographic	Categories	Frequency	Percentage
Age	18–20 Years	32	10.6
	21–30 Years	120	39.7
	31–40 Years	109	36.1
	40+ Years	41	13.6
Gender	Male	154	51
	Female	148	49
	Elementary	8	2.6
	High School	43	14.2
Education	Bachelor Degree	177	58.6
	Master Degree	73	24.2
	PhD	1	.3
	Less than 1 year	10	3.3
	1–3 years	17	5.6
Experience with existing payment system	3–5 years	137	45.4
	5–10 years	130	43
	More than 10 years	8	2.6
	Very high	177	58.6
Blockchain knowledge	High	164	54.3
	Moderate	83	27.5
	Low	9	3

, can help us understand their background. As shown by the age breakdown, the vast majority of the respondents were in the 21–30 age range (120), followed by the 31–40 age range (109). These two categories, mainly young and middle-aged adults, are a significant group, who are not only already utilizing digital payment systems but are also on the cusp of launching blockchain-based platforms. The gender representation in the survey was nearly equal, with 154 male and 148 female respondents, making it nearly equally balanced between the views of both genders. This skewed representation offers a balanced representation of gendered reactions to blockchain adoption and emphasizes the need to create inclusive digital systems that everyone can use. Education was another demographic driver, a highly educated cohort. Most of the respondents had a bachelor’s degree (184), and a significant minority had a master’s degree (73). This degree of education points to a strong base of technological awareness among respondents that puts them in a position to understand the potential opportunities and threats of the blockchain-based digital payment system. This demographic information, namely age, gender, location, and education, ensured that the sample represented a varied Bhutanese population. The experience of the respondents with the existing payment system indicates that the majority (88.4%) have more than three years of experience, 45.4% have 3–5 years, and 43% have 5–10 years of experience. Blockchain knowledge among respondents was always considered. These insights provide a foundation for understanding the level of expertise and familiarity with digital payment systems and blockchain technology among the participants surveyed. Demographic data are not discussed for their influence on acceptance in this paper, as they will be considered in a subsequent paper on the augmented model using trust and acceptance factors for the adoption of blockchain in Bhutan’s digital payment system.

5.2. Convergent Validity

Convergent validity measures the degree of convergence that the measurement model correctly represents the constructs being measured.

Table 3. Convergent validity.

	Cronbach’s Alpha	Composite Reliability ${\mathit{\rho }}_{\mathit{a}}$	Composite Reliability ${\mathit{\rho }}_{\mathit{c}}$	Average Variance Extracted (AVE)
PE	0.918	0.919	0.938	0.753
EE	0.933	0.934	0.947	0.750
SI	0.913	0.916	0.935	0.744
FC	0.935	0.935	0.948	0.753
ACC	0.900	0.900	0.930	0.769

shows that the convergent validity was measured using Cronbach’s alpha, composite reliability (CR), and Average Variance Extracted (AVE), all exceeding the thresholds. Cronbach’s alpha values for all constructs ranged from 0.900 to 0.935, well above the minimum value of 0.70 recommended by Nunnally and Bernstein [123]. These large values indicate good internal consistency and stability, which shows that the items in each construct are closely related and represent their theoretical form.

CR values, based on ${\rho }_a$ and ${\rho }_c$, varied between 0.930 and 0.948, above the 0.70 thresholds recommended by Fornell and Larcker [124]. These findings support the stability and homogeneity of the constructs and highlight that the variables are tightly linked to their latent constructs. In addition, the AVE values for all constructs ranged from 0.744 to 0.769, well beyond the threshold of 0.50 established by Fornell and Larcker [124]. These AVE values demonstrate that most of the variation in measurement items is explained by the constructs that capture the theoretical size well enough. Together, these results attest to the strong convergent validity of the measurement model. With the very high Cronbach’s alpha, CR and AVE, the constructs have good internal consistency and reliability and do not underestimate the variance of the measurement items for which they stand. Therefore, the measurement model is validated as appropriate to measure the desired variables and is suitable for testing.

5.3. HTMT Ratio

The HTMT ratio, one of the crucial discriminant validity measures in SEM, tests whether the models’ constructs are different from each other. Fornell and Larcker [124] emphasized that the square root of the AVE of each construct had to exceed its correlations with other constructs to establish discriminant validity, while Henseler et al. [125] support the HTMT ratio as an evidence-based validation tool. In

Table 4. HTMT ratio.

	ACC	EE	FC	PE
EE	0.869
FC	0.833	0.846
PE	0.876	0.890	0.800
SI	0.795	0.793	0.755	0.732

, the HTMT ratios of the constructs, namely ACC, EE, FC, PE, and SI, are shown. Discriminant validity is acceptable when the HTMT values fall below the 0.90 thresholds [126]. These findings show that most pairs of constructs have HTMT values in acceptable ranges, supporting the discriminant validity of the model. ACC and EE have 0.869 HTMT, while ACC and FC have 0.833 HTMT, respectively, which implies an adequate distinction between these constructs. Similarly, the relationships of FC and PE (HTMT = 0.800) and ACC and SI (HTMT = 0.795) are also well below the threshold, supporting the validity of the constructs. However, a notable observation arises when comparing the EE and PE ratio of HTMT at 0.890. Such proximity may indicate conceptual overlap, as both are based on user expectations and perceived ease and usefulness in technology adoption paradigms. However, it is still below the 0.90 threshold. In contrast, SI consistently exhibited HTMT values lower than 0.80 for all pairs of constructs, including SI and EE (HTMT = 0.793) and SI and PE (HTMT = 0.732), indicating that it clearly differs from other constructs in the model. Together, these findings indicate that the model has reasonable discriminant validity.

5.4. Structural Model Analysis

This section presents the findings of the structural model shown in Figure 2 that highlight the relationships between the constructs related to the acceptance of blockchain adoption for digital payment systems in Bhutan. The analysis focuses on the path coefficients, significance levels, R-square values, direction, and explanatory power of the relationship models.

5.5. Path Coefficients

The path coefficients depicted in Figure 2 reveal the direct connections between variables that impact ACC of blockchain adoption. The strength of the relationship between the variables stands at “−1 to +1”, with a strong positive relationship near “+1” and a strong negative relationship near “−1”. SmartPLS used bootstrapping to determine the path coefficients. Studies of behavioral technology adoption show that path coefficients greater than 0.2 indicate moderate prediction, and those greater than 0.3 demonstrate strong prediction.

Table 5. Path coefficient results.

	ACC
PE	0.337
EE	0.204
SI	0.192
FC	0.220

shows the key constructs PE, EE, SI, and FC with their respective varying impact on ACC.

PE → ACC: PE stands out as the most important factor influencing ACC, with a path coefficient of 0.337. This shows that Bhutanese consumers place high importance on the tangible benefits and efficiency offered by blockchain-based digital payment systems. The findings highlight that the perception of improved performance directly contributes to consumers’ readiness to adopt such systems. This puts emphasis on the need for solutions that align with what users want for enhanced functionality and utility.

EE → ACC: EE has a positive relationship with ACC, resulting in a path coefficient of 0.202. This indicates that ease of use contributes significantly to consumer acceptance. Blockchain consumers will embrace blockchain technology when its functionality makes sense and does not take too much effort to understand. These findings emphasize the importance of creating intuitive interfaces and making the learning curve as minimal as possible for prospective users.

SI → ACC: SI has a moderately positive effect on ACC with a path coefficient of 0.192. This result reflects how acceptance is shaped by social norms, peer pressure, and validation. Bhutanese consumers would also be impressed by the perceived popularity or use of blockchain technology within their social networks. This is why it is important to create a positive social culture and use social proof to help drive adoption.

FC → ACC: FC also has a strong positive effect on ACC, with a path coefficient of 0.220. This indicates the need for adequate resources, infrastructure, and support for consumers to adopt blockchain payments. These findings highlight the importance of an ecosystem that provides the support and tools to enable easy adoption.

The path coefficients show the subtle impact that PE, EE, SI, and FC have on the ACC of blockchain-based digital payments in Bhutan. PE is the most important factor, highlighting the importance of perceived performance and efficiency. FC, EE and SI further play a role in establishing acceptance by emphasizing the relationship between infrastructure, convenience, and reinforcement. These insights collectively demonstrate the need for a comprehensive, functional, and social solution to encourage the acceptance of blockchain-based digital payment systems.

5.6. Significance Levels

Table 6. Significance level results.

	T-Statistics	p Values	Significance
PE -> ACC	5.426 ***	0.000	Significant
EE -> ACC	3.087 **	0.002	Significant
SI -> ACC	4.286 ***	0.000	Significant
FC -> ACC	4.104 ***	0.000	Significant

Notes: *** p < 0.001, ** p < 0.01

shows how significance levels in the model were determined using p-values and T-statistics for each path. Relationships with p-values below 0.05 were considered statistically significant, which underscores the importance of these factors in facilitating the acceptance of blockchain adoption in Bhutan’s digital payment systems. The higher the T-statistic, exceeding 1.96 at a confidence level of 95%, the stronger the relationship [126].

In Table 6, the analysis of the significance level indicates the statistical robustness of the correlations between PE, EE, SI, FC and ACC of blockchain-based digital payment platforms. The analysis was carried out using T-statistics and p-values with theoretical thresholds set at T > 1.96 and p < 0.05 [126].

PE is the most robust predictor of ACC, with a T-statistic of 5.426 and a p-value of 0.000. This underscores the importance of perceived utility as driving ACC. Having consumers perceive blockchain-based digital payment systems as more secure, faster, and efficient will increase their chances of acceptance. PE represents the usefulness that users value in such systems.

EE is also statistically significant for ACC, with a T-statistic of 3.087 and a p-value of 0.002. This highlights that usability is critical to promoting ACC. It is particularly important to simplify the use of the system in environments with different levels of digital literacy.

SI is also statistically significant for ACC, showing a T-statistic of 4.286 and a p-value of 0.000. The above results show that peer recommendations, norms, and recommendations have a significant impact on how consumers think about adopting blockchain. A positive social environment can also significantly boost ACC.

Another significant factor in ACC is FC, whose T-value is 4.104 and whose p-value is 0.000. These findings emphasize the importance of a well-developed infrastructure, including reliable Internet connectivity, device availability, and technical support, to facilitate blockchain adoption. FC provides users with the tools and support they need to integrate emerging technologies effectively.

These findings show that each of these four factors, namely PE, EE, SI, and FC, is statistically relevant to the ACC of consumers of blockchain-based digital payment systems. PE is the strongest, with an emphasis on perceived utility and performance. FC, SI, and EE also contribute significantly, underlining the importance of infrastructure, social reinforcement, and ease of use. This finding suggests the need to focus on these imperatives to effectively foster blockchain adoption and greater consumer engagement.

5.7. R-Square

R-square values function as essential indicators of how independent variables explain the variance in each dependent construct through the model’s predictors. The usefulness of performance expectancy, effort expectancy, social influence, and facilitating conditions as predictors of consumer acceptance for blockchain adoption becomes evident through these values. When models exhibit higher R-square values, it shows that independent variables can account for variations more effectively in the dependent construct, which leads to improved predictive reliability. The relationships among the constructs become clear through the R-square values shown in

Table 7. R-square results.

	R-Square s	R-Square Adjusted
ACC	0.738	0.735

. According to standard interpretative thresholds [126], an R-square of less than 0.25 demonstrates weak explanatory power, which means that independent variables exert minimal control over the dependent construct. The range of 0.25 to 0.50 for the R-square values demonstrates moderate explanatory strength, which achieves a fair degree of predictability. When the R-square value exceeds 0.50, it indicates strong explanatory power by showing that the model captures the dependent construct’s variance effectively. The established thresholds serve as a standard for assessing how well the model can explain consumer acceptance toward blockchain usage for digital payments and measure its overall strength.

In Table 7, the R-square for ACC is 0.738, which means that 73.8% of the variance in ACC is influenced by the combination of PE, EE, SI and FC. This indicates a high explanatory power and shows the efficacy of these factors in shaping consumer acceptance of blockchain-based digital payment systems. These findings emphasize the critical roles of perceived utility, accessibility, social reinforcement, and support infrastructure in determining consumer acceptance. Substantial variance underscores the need to look at these aspects in a multidimensional context. Incorporating PE, EE, SI and FC in the design and promotion of blockchain-based digital payment systems will increase consumer acceptance, streamline the adoption process, and increase the overall use of technology in Bhutan’s digital payment ecosystem.

6. Discussion

6.1. Interpretation of Results

This paper provides an in-depth analysis of the factors that impact consumer acceptance of blockchain-based digital payments in Bhutan. Both the structural model and the statistical data in Table 5 support the relevance and robustness of the connections between the constructs PE, EE, SI, FC, and ACC.

The most significant construct was PE, which had a path coefficient of 0.337, a T-statistic of 5.426 and a p-value of 0.000. This finding aligns with the acceptance model, where utility, such as transaction speed, security, and operational efficiency, is seen as a primary motivator of technology adoption. The importance of PE highlights the fact that consumers tend to adopt blockchain-based digital payment systems when they see the real benefits. This is consistent with research around the world that focuses on perceived usefulness as a key factor in adoption [42,53]. The second significant predictor was EE (path coefficient: 0.204, T-statistic: 3.087, p = 0.002). The notion of perceived ease of use is particularly important in contexts with varying levels of digital literacy. In line with UTUAT, EE affirms that intuitive design and usability help foster adoption. This highlights the importance of making blockchain solutions accessible and user-friendly in Bhutan. FCs also have an impact, with a path coefficient of 0.220, a T statistic of 4.104, and a p-value of 0.000. This finding highlights the importance of enabling infrastructure, including Internet access, devices, and technical support, to help break down adoption barriers. Continuing the UTAUT model, FC stresses that it is vital to create the conditions for blockchain technology to be incorporated into Bhutan’s digital payment ecosystem, especially in rural locations where infrastructure issues remain. Solutions such as offline transaction verification and hybrid systems that sync transactions once online can help overcome such challenges. SI, while smaller than the other constructs, was nonetheless statistically significant with a path coefficient of 0.192, a T statistic of 4.286, and a p-value of 0.000. Peer recommendations, culture, and approvals from a trusted individual or organization are particularly critical. In Bhutan’s collectivist culture, where communal and family values play a key role in the choices we make, SI helps inform consumers about blockchain technology. This finding builds on previous research on cultural and social influences on the use of technology in collectivist societies. These findings reveal that the structural model in Figure 2 is robust and consistent, with all constructs reaching statistical significance (T > 1.96, p < 0.05), as seen in Table 6. PE was the most predictive construct of blockchain adoption, showing that perceived utility was the dominant construct when it came to making consumer decisions. EE and FC focus on intuitive design and infrastructure, while SI echoes Bhutan’s cultural variations in adoption practices. The results confirm the potential of the UTAUT models in the realm of blockchain-based digital payment systems. All these observations set the path for stakeholders to prioritize perceived value, usability, and infrastructure to drive blockchain adoption in Bhutan. Stakeholders can ensure the acceptance of blockchain technology in the country’s digital payment ecosystem and ensure that consumers embrace it more broadly.

6.2. Theoretical Contributions

This paper provides a significant contribution as it is one of the first works to explore consumer acceptance of blockchain-based digital payments in Bhutan, addressing a crucial gap in academic research. Previous research [35,78] has examined blockchain adoption, but this study uniquely applies the UTAUT model in a developing economy with unique socio-cultural and infrastructural conditions. The research expands current technology acceptance frameworks by providing empirical evidence from Bhutan’s developing digital landscape. The most significant finding of this study reveals that performance expectancy acts as the primary factor in motivating consumer acceptance in Bhutan. These research findings are consistent with previous studies by [35,80,82] where performance expectancy stands out as a vital factor in adopting blockchain technology and digital financial services. Contrary to Miraz et al.’s [79] findings regarding performance expectancy’s negative effect on cryptocurrency adoption, this study shows that performance expectancy is a key factor for Bhutanese consumers in blockchain-based payment systems.

Effort expectancy and facilitating conditions serve as essential drivers for acceptance by highlighting the importance of usability aspects together with digital literacy and technological infrastructure. These findings align with Bakri et al. [78] and Norbu et al. [35], supporting the view that ease of use and robust infrastructure are essential elements for successful adoption. However, Kumari et al. [84] refute that effort expectancy, together with performance expectancy, does not significantly drive blockchain adoption while demonstrating that these factors’ effects may vary based on the context. Bhutanese consumers’ acceptance of blockchain-based digital payments is significantly influenced by social factors, which include cultural norms as well as peer recommendations and institutional trust. The study by Khazaei [80] and Bhatnagar et al. [82] recognized social influence as a major factor in driving blockchain and neobank adoption, which is supported by the findings of this paper.

6.3. Theoretical Implications

This paper contributes to the ongoing discourse on blockchain acceptance through a UTAUT extension that incorporates regional characteristics along with infrastructural and socio-cultural elements. This finding also supports Salem et al.’s [81] work, which expanded UTAUT to include trust and perceived risk by emphasizing the requirement for adoption models that account for cultural and infrastructural elements in developing economies. These findings establish a strong foundation for consumer acceptance for future blockchain adoption studies in developing nations and culturally analogous societies while urging scientific researchers to enhance technology adoption models through the inclusion of regional-specific factors.

6.4. Practical Implications

A strategic approach that focuses on consumer education and social influence, together with infrastructure development, is essential for consumer acceptance of the integration of blockchain in Bhutan’s digital payment system. Stakeholders in banking institutions, government agencies, and fintech development teams need to develop systematic awareness initiatives that effectively explain the fundamental strengths of blockchain, such as efficiency, transparency, and security, which are essential within Bhutan’s distinctive sociocultural and economic environment. Previous studies [35,78,81] emphasized that for successful adoption, stakeholders must ensure regulation alongside trust building and public engagement. Addressing misconceptions and showcasing real-world applications can foster confidence in blockchain technology. Public outreach efforts should leverage digital and traditional media, hands-on workshops, and financial literacy programs tailored to diverse demographics, aligning with the findings of Kabir et al. [83] on the need for usability-focused education.

Social trust is a fundamental factor that influences the acceptance of the adoption of technology by consumers in Bhutan’s collectivist society, as noted by Khazaei [80] and Bhatnagar et al. [82], who stated that social influence is essential. Endorsements from community leaders and institutional figures, along with sensitization campaigns featuring real-life success stories, can effectively build blockchain acceptance. This aligns with its finding that social proof plays a critical role in influencing consumer decisions. Addressing infrastructural challenges by expanding digital connectivity and improving digital literacy will narrow the technology gap to guarantee universal access. Studies [78,84] highlighted that financial literacy programs combined with supportive government policies are essential to drive acceptance for adoption. Bhutan can establish a standard for ethical blockchain adoption by incorporating blockchain within its Gross National Happiness framework, along with equitable access and alignment of national values, which will serve as a model for developing economies.

7. Limitations and Future Research

This research gives useful insights into consumer acceptance of blockchain-based digital payment services in Bhutan, but it has some limitations. Since the sample consists of five districts, the sample could not fully represent the overall context of the country. The cross-sectional design does not allow insight into how attitudes change over time. Furthermore, the study does not include consumer acceptance due to technological skills and adoption costs and takes into account the perspectives of policymakers, enterprises, and business partners. The implementation of blockchain-based payment solutions in Bhutan encounters numerous legislative hurdles such as unclear regulatory guidelines, mandatory alignment with centralized financial regulations, limitations on international transactions, and missing consumer protection mechanisms. The need for regulatory approval for cryptocurrencies presents further obstacles. The successful implementation of blockchain-based payments in Bhutan depends on overcoming these limitations by conducting comprehensive research and enacting policy adjustments. Future studies would need to examine how demographic factors such as age and education shape acceptance. An integrated approach, such as the use of qualitative interviews, would provide better information. Longitudinal studies tracking trends over time and incorporating new findings, such as blockchain development and regulatory developments, would further provide insight into the dynamics affecting blockchain adoption in Bhutan.

8. Conclusions

This paper analyzed the drivers of consumer acceptance for blockchain-enabled digital payment systems in Bhutan, providing information on acceptance factors and their local relevance. The findings affirmed the feasibility of technology acceptance models such as TAM and UTAUT in new markets. Performance expectancy was the most robust predictor of consumer adoption based on perceived utility, including faster, more secure, and more efficient payment methods. Effort expectancy and facilitating conditions also had strong positive associations with adoption, emphasizing the importance of readily available platforms and infrastructure. Social influence, though marginal, was of particular import in Bhutan’s collectivist society, where social conventions and peer or family recommendations exert a strong influence on choices. It also stresses the possibility of using blockchain to solve certain shortcomings in Bhutan’s digital payment system, such as usability, trust, and infrastructure. The paper also makes practical and conceptual suggestions on how to further optimize digital payment systems, which can act as a basis for future studies and interventions.