## 6 Discussion
### Cross-Sectional Domains  
Blockchain technology has been employed in many domains, as discussed in Sections 3.2, 4.2 and 5.2). For the research, blockchain technology was mostly found in articles related to government services, followed by supply chain and traceability. The government services included voting systems, lottery systems, land registration, and national digital identification (NDID). For the project, a financial domain was the majority. Similarly, blockchain courses mostly covered financial topics such as cryptocurrenncy, apart from the basic concept of blockchain that was introductory in most of the courses. It is noteworthy to mention that the blockchain courses and projects aimed at the same direction, whereas the blockchain research did not. It shows that, in Thailand, the blockchain in each aspect was not complementary as expected. The research was supposed to be a resource for financial project implementation; however, it focused on the government services as well as supply chain and traceability. Although blockchain courses mostly involved finance, few courses were a platform for fostering experts to execute the project. Instead, it seems to be providing more for the general public.  
Three possible reasons of this situation are research applicability, business confidentiality, and bias in data collection of financial articles. First, there are a large number of research works on finance worldwide, and they are applicable for the financial blockchain project implementation in Thailand. Adopting compatible existing studies might be a more reasonable course of action than conducting a localized research, which costs time and resources. As a result, the research articles in finance were not a majority, unlike in projects and courses. Second, research in the financial domain in Thailand might not be able to be publicized due to the business confidentiality. Financial blockchain projects were mostly executed by banks and firms, as shown in Figure 14. Thus, the imbalance between the small number of research and the large number of projects and courses occurred. Last, collecting data on Google search engine, which is a platform dominated by advertisements, could bias the data collection. Since big projects like financial projects of banks and projects owned by government normally receive more spotlights than other domains with small stakeholders, the financial domain could easily outnumber the other domains in the analysis.  
\begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt}} \hline \hline
**Events** & **Descriptions** \\ \hline an article’s publication date & The publication date of the research article. \\ \hline a course’s instruction dates & The dates that instructions occur. Some courses were one-day, while some spanned multiple consecutive dates. Some courses were in a series, offering the same lectures or workshops multiple times. In virtual courses, the dates are the announcement of the courses. \\ \hline a project’s start date & The first date of the project. Due to the incomplete information, this date could be the first time that a project was initiated. If the beginning of the project was not mentioned, the opening ceremony or the first press release will be considered. - Otherwise, the first time that a project was on the press will be used. \\ \hline a project’s updated date & A date that the project’s information was updated to the public. This could be the date when an article was published, when an event was set up to show project’s progress, or when a project that was mentioned in other project’s articles. \\ \hline a project’s end date & The mark of the end of a project. A project could be announced success and conclude with a report. \\ \hline \hline \end{tabular}
\end{table}
Table 6: A table of events and their descriptions.  
Figure 17: A visualization showing timelines of research articles, courses, and projects about blockchain in Thailand. Some courses and projects were excluded due to imprecise timeline.