# A Systematic Review on Blockchain Adoption
## 5 Discussion  
It is imperative to understand what impacts the adoption of new technologies, such as Blockchain. Adopting any technology relies on the determinants affecting its users [73; 74; 75]. A forecasting report illustrates the positive evolution of the Blockchain market between 2017 and 2024 [76]. While this magnitude was USD 800 million in 2017, it is estimated to reach USD 20,550 million in 2024. Therefore, it is vital to gain more insights into what impacts the adoption of Blockchain technologies across many sectors to improve and sustain their usage. Hence, this systematic review was carried out to analyze the adoption of Blockchain technologies from the lenses of technology adoption theories/models. The results showed that questionnaire surveys represent the primary research method used in 77% of the analyzed Blockchain adoption studies. These outcomes agree with some of the earlier systematic reviews in the technology adoption domain [77; 78; 79; 80], which concluded that questionnaire surveys were the most common data collection method. In terms of the Blockchain, these results contradict what [PERSON] et al. [81] reported, in which comparative studies were the primary method used in most of the analyzed articles. Drawing upon the findings of this systematic review, it is suggested that further research would consider the mixed-research approach by involving interviews or focus groups  
Figure 6: Distribution of studies by participants. besides using questionnaire surveys. This is because qualitative approaches provide more insights into the cause-effect relationships among the factors affecting Blockchain adoption. Regarding the main domains/sectors through which the analyzed studies were carried out, supply chain management dominates the list with 12 studies, followed by education and agriculture, with three studies each. While our findings agree with [82], who found that supply chain management is the dominating sector concerning studies related to Blockchain adoption, it contradicts what is reported by [81], who suggested that banking and finance was the primary sector. Regardless of the differences between this review and the previously conducted reviews, understanding Blockchain adoption across many domains is still in short supply due to the limited number of applications. Concerning the prevailing technology adoption theories/models, the results pointed out that the TAM is the most common model in studying Blockchain adoption, with 14 studies. This is followed by the TOE (\(n=8\)), UTAUT (\(n=7\)), and IDT (\(n=5\)). In the same vein, [PERSON] [82] found that TAM and TOE were the most dominating models in studying Blockchain adoption. TAM is still a valid model to evaluate large-scale emerging technologies [83, 84], where Blockchain is not an exception. These results indicate that studies focusing on the individual level have mainly relied on TAM, while those examining the organizational level have relied on TOE. Further research might consider other adoption models that have yet to be used in the existing literature, such as UTAUT2, ECM, PMT, etc. For the influential factors affecting Blockchain adoption, trust was seen to be the most common factor affecting the adoption of Blockchain technologies (\(n=17\)). This was followed by the perceived cost and social influence, with 11 studies each, as well as facilitating conditions (\(n=10\)), performance expectancy, effort expectancy, and information security, with seven studies each. Studies on the individual level have examined trust, social influence, performance expectancy, effort expectancy, and information security. In contrast, those focusing on the organizational level studied mainly the organizational perspective's factors in delivering Blockchain-based services, such as trust, perceived cost, and facilitating conditions. Still, there is abundant room for other factors to be investigated from the perspective of other technology adoption theories/models and Blockchain-related specific characteristics.