# Understanding Consumer Acceptance for Blockchain-Based Digital Payment Systems in Bhutan
## 5 Results
### 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 shows the key constructs PE, EE, SI, and FC with their respective varying impact on ACC.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **ACC** & **EE** & **FC** & **PE** \\ \hline EE & 0.869 & & & \\ FC & 0.833 & 0.846 & & \\ PE & 0.876 & 0.890 & 0.800 & \\ SI & 0.795 & 0.793 & 0.755 & 0.732 \\ \hline \hline \end{tabular}
\end{table}
Table 4: HTMT ratio.  
Figure 2: Structural model result.  
PE \(\rightarrow\) 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 \(\rightarrow\) 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 \(\rightarrow\) 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 \(\rightarrow\) 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.