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• W3197600547 abstract "ABSTRACTThis study aims to investigate the different impacts of the COVID-19 pandemic on Indonesia’s tourism industry, as this and its supporting sectors are the most affected by the COVID-19 pandemic worldwide, by clustering the provinces based on the room occupancy rate (ROR) to understand provinces specific impacts. Several big data sources are employed to study the different impacts of the pandemic on two tourists’ most popular provinces, i.e. Bali and Yogyakarta. A number of tourism indicators such as number of international arrivals, ROR from the BPS statistics Indonesia, combined with data from Google mobility index, Google trend, flight tracker and reviews from Tripadvisor and Booking.com are presented. Provinces are clustered by ROR category using the dynamic time warping method. The COVID-19 pandemic has obviously impacted the tourism industry and its supporting sectors in across Indonesia. However, this study explains the different patterns of the impact in different provinces. Furthermore, this study proves that big data sources are shown to be a good proxy to infer the impact of the pandemic on tourism.KEYWORDS: Warping Dynamic Timebig dataweb scrapingTripadvisorbooking.com Disclosure statementNo potential conflict of interest was reported by the author(s)." @default.
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• W3197600547 date "2021-08-27" @default.
• W3197600547 modified "2023-09-30" @default.
• W3197600547 title "Impact of COVID-19 pandemic on tourism in Indonesia" @default.
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• W3197600547 doi "https://doi.org/10.1080/13683500.2021.1968803" @default.
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