Institute of Transportation, MOTC

       Due to the changes in tourism and consumer demand, the government is committed to promoting and mentoring the industry, in an attempt to launch a new type of digital tourism service -Taiwan Pass. Faced with challenges, the positioning of Taiwan Pass and the key factors for its success are very important issues. This research uses focus group to collect opinions and uses natural language processing to conduct text mining to extract keywords. Use word frequency analysis to extract important opinions as key factors, and use data mining for semantic similarity analysis. By understanding the degree of discrepancy of opinions participants, so the impact and influence of the industry can be reduced. The research results show that a total of five issues were generated, and the content of the issues was compared for homogeneity. The results show that issue 1 (considerations about the architecture, budget, time, and operation model of the platform) has the highest homogeneity, followed by issue 2 (integration of food, accommodation, travel, shopping, and
transportation, platform API connected and security issues), topic 4 (MaaS experience) and topic 5 (Umaji, Taiwan Pass development experience), topic 3 (digitalization of platform services, development technical specifications of QRcode). This research also proposes the operating positioning policy of Taiwan Pass as a reference for the promotion of Taiwan Pass in the future.