Technology Acceptance Readiness Analysis in the Context of Digital Tourism Village using Machine Learning Approach

Digital tourism village potentially accelerates rural development hence improving a country's economy. The Indonesian government has developed hundreds of tourism villages in recent years but has yet to popularize the development of digital villages. Technology design and development are pivotal factors in tourism villages' digitalization. Therefore, the development digital tourism village must consider village readiness by measuring technology adoption readiness or technology acceptance of the corresponding stakeholders. This paper presents the technology acceptance analysis in the context of a digital tourism village. We use a quantitative analysis approach using the TAM-UTAUT model with data collected from a questionnaire of 101 villagers (n=101) in Pasanggrahan Village, West Java, Indonesia. This research uses machine learning with clustering procedures to analyze the level of technology adoption readiness by implementing K-means Clustering algorithm. In addition, to observe the significance of each influencing factor to the technology adoption readiness level, feature importance analysis approach using Extra tree classifier algorithm is employed. The research finds that attitude toward use, perceived ease of use, and facilitating condition-have a considerable impact on the degree of readiness for technology adoption. On the other hand, the perceived utility and social impact are found to have minimal bearing on the preparedness level for technology adoption. Perceived ease of use and facilitating conditions are the most important factors to afford the acceleration of technology adoption readiness. The research contributes to the development of a digital tourism village and the analysis of technology adoption readiness using machine learning.