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The study utilizes robust neural network mechanisms to analyse and predict Filipinos' sharing tendencies of capacity-constrained resources on sharing economy platforms. Specifically, it underscores insights that supplement marketers' efforts in the peer-to-peer accommodation sector by clustering various groups with their preferred choice of shared resources. The literature answers market related gaps in the implementation of sharing economy enterprises in the tourism industry by advising possible avenues of consolidation. The investigation leads to further discourse by experimenting with demographic level data to split the market into groups for service design and delivery. The paper attempts to contribute to the existing corpus of knowledge by introducing machine learning algorithms in the sharing economy perspective. [ABSTRACT FROM AUTHOR]

The article presents the effects of Covid-19 world tourism in 2020. The goal of the paper is to research the consequences of the pandemic on the tourism sector. The paper presents and reviews the available information on how tourism was affected by the pandemic, endangered jobs, and ways in which countries are dealing with the consequences. The paper discusses possible measures and scenarios of the countries to mitigate the effects of the crisis and accelerate the recovery of tourism and the economy. Summarizing the findings, authors will conclude that the disruption in tourism from the pandemic had a huge impact on the wider economy, and countries’ governments reacted quickly. The scope of imposed measures expanded continuously during the crisis. At the end, recommendations are given for the priorities for renewal of tourism and protection of jobs, as recommendations for solidarity and promotion of mutual cooperation. [ABSTRACT FROM AUTHOR]