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  2. University of Kragujevac
  3. Faculty of Hotel Management and Tourism, Vrnjačka Banja
Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/15413
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dc.contributor.authorPaunovic, Marija-
dc.date.accessioned2023-01-19T12:22:10Z-
dc.date.available2023-01-19T12:22:10Z-
dc.date.issued2021-
dc.identifier.citationPaunovic, M. (2021). MATHEMATICAL MODELLING AND STATISTICAL ANALYSIS IN POST - COVID-19 TOURISM RECOVERY. Tourism International Scientific Conference Vrnjačka Banja - TISC, 6(1), 334-349. https://doi.org/10.52370/TISC21334MPen_US
dc.identifier.isbn9788689949469en_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/15413-
dc.description.abstractThe COVID-19 pandemic, along with responses to pandemic control in the form of a national blockade with widespread application of travel restrictions, has made tourism one of the most vulnerable sectors. With increasing mitigation measures in many countries regarding tourism and travel restrictions in some segments, different tourism recovery programs are being launched according to the specifics of each country. The paper will consider various proposed measures through different impact factors set in order to accelerate the recovery of the tourism sector. Selected mathematical models will be presented and discussed.en_US
dc.language.isoenen_US
dc.publisherUniversity of Kragujevac, Faculty of Hotel Management and Tourismen_US
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.sourceThe Sixth international scientific conference Tourism challenges amid covid-19, Vrnjačka Banja, june 3-5th, 2021en_US
dc.sourceThe Sixth International Scientific Conference - TOURISM CHALLENGES AMID COVID-19en_US
dc.subjectMathematical modellingen_US
dc.subjectMarkov chainen_US
dc.subjectStringency Indexen_US
dc.subjectforecastingen_US
dc.subjectpandemic effectsen_US
dc.subjectgovernment policyen_US
dc.titleMATHEMATICAL MODELLING AND STATISTICAL ANALYSIS IN POST - COVID-19 TOURISM RECOVERYen_US
dc.typeconferenceObjecten_US
dc.description.versionPublisheden_US
dc.identifier.doi10.52370/TISC21334MPen_US
dc.type.versionPublishedVersionen_US
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