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001461299 001__ 1461299
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001461299 019__ $$a1372396497
001461299 020__ $$a9811993696$$q(electronic bk.)
001461299 020__ $$a9789811993695$$q(electronic bk.)
001461299 020__ $$z9789811993688
001461299 0247_ $$a10.1007/978-981-19-9369-5$$2doi
001461299 035__ $$aSP(OCoLC)1372368432
001461299 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dEBLCP$$dUKAHL$$dOCLCF$$dN$T
001461299 049__ $$aISEA
001461299 050_4 $$aG155.A1
001461299 08204 $$a338.4/7910285$$223/eng/20230317
001461299 24500 $$aTourism analytics before and after COVID-19 :$$bcase studies from Asia and Europe /$$cYok Yen Nguwi, editor.
001461299 264_1 $$aSingapore :$$bSpringer,$$c[2023]
001461299 264_4 $$c©2023
001461299 300__ $$a1 online resource (viii, 246 pages) :$$billustrations (chiefly color)
001461299 336__ $$atext$$btxt$$2rdacontent
001461299 337__ $$acomputer$$bc$$2rdamedia
001461299 338__ $$aonline resource$$bcr$$2rdacarrier
001461299 504__ $$aIncludes bibliographical references.
001461299 5050_ $$aIntro -- Contents -- Hong Kong Tourism Under COVID-19 -- Data Preparation -- Modeling and Results Comparison -- Feature Importance -- Business Analysis -- Impact on Airlines: Case Study on Cathay Pacific and Dragon Air -- Conclusion and Future Studies -- References -- Tourism Analytics, the Case for Hainan China -- Impacts on Tourism Industry -- Analytics Methodology -- Model Selection -- Conclusions -- Reference -- Impacts of COVID-19 on Food, Aviation, and Accommodation in Europe -- Dataset and Analysis -- Methodology and Experimental Results -- Recommendation and Conclusion -- References
001461299 5058_ $$aTourism Rebounds Analysis-Lessons from Baltics Countries -- Business Understanding and Approach -- Data Model Analysis -- Tourism Income Baseline Growth Trajectory 2020-2021, Without COVID -- XGBoost -- Model Evaluation -- Prediction of International Arrivals in 2020 and 2021-an Outlook Without COVID-19 -- The Case of Travel Bubble in Estonia -- Business Case Analysis -- Policies Effectiveness Quantitative Analysis -- Qualitative Analysis of Other Measures for Consideration -- Conclusion -- References -- Compare and Contrast the Impact of COVID-19 from Small to Large Country
001461299 5058_ $$aTourism in Singapore -- Tourism in China -- Tourism Analytics-The Case for South Africa -- References -- Hotel Booking Cancellation Analytics on Imbalanced Data -- Data Preparation -- Data Visualization -- Machine Learning -- Business Insights and Solutions -- Conclusion -- References -- Tourism Prediction Analytics -- Dataset and Analysis -- Current Situation of COVID-19 -- Prediction of COVID-19 -- Development of Tourism/Hotel Industry -- Seasonality of Arrivals -- Age of Visitors -- Purpose of Trips -- Places of Interest -- Hotel Industry -- Impact of COVID-19 on Singapore's hotel industry
001461299 5058_ $$aDescriptive Analysis -- Time Series Prediction -- Recommendation -- Conclusion -- References -- Marketing Segmentation and Targeted Marketing for Tourism -- Visualization with Descriptive Analytics -- Business Solutions Using Machine Learning -- Conclusion -- References -- Machine Learning for Tourism -- Visualization-Based Analysis -- Time Series Analysis -- Machine Learning Analysis -- Recommendation -- Data Visualization on Tourism -- Data Sources -- Data Visualization and Analysis -- Recommendation -- Conclusion -- References -- Sustaining Tourism Sector Through Domestic Tourism and Analytics
001461299 5058_ $$aDataset and Analysis -- Proposed Solution: Analytics-Enabled Domestic Tourism Model -- References -- Tourism Analytics with Price and Room Booking Simulation -- Analytics Approach on Tourism -- Price, Room Booking and Revenue Simulation -- Scenario 1 -- Scenario 2 -- Scenario 3 -- Conclusion -- Recommendation -- References -- Tourism Arrival Prediction -- Proposed Solutions -- Fiscal Stimulus -- Domestic Tourism -- Travel Bubble -- Reshape the Travel Activities -- References
001461299 506__ $$aAccess limited to authorized users.
001461299 520__ $$aThis book is compilation of different analytics and machine learning techniques focusing on the tourism industry, particularly in measuring the impact of COVID-19 as well as forging a path ahead toward recovery. It includes case studies on COVID-19's effects on tourism in Europe, Hong Kong, China, and Singapore with the objective of looking at the issues through a data analytical lens and uncovering potential solutions. It adopts descriptive analytics, predictive analytics, machine learning predictive models, and some simulation models to provide holistic understanding. There are three ways in which readers will benefit from reading this work. Firstly, readers gain an insightful understanding of how tourism is impacted by different factors, its intermingled relationship with macro and business data, and how different analytics approaches can be used to visualize the issues, scenarios, and resolutions. Secondly, readers learn to pick up data analytics skills from the illustrated examples. Thirdly, readers learn the basics of Python programming to work with the different kinds of datasets that may be applicable to the tourism industry.
001461299 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed March 17, 2023).
001461299 647_7 $$aCOVID-19 Pandemic$$d(2020-)$$2fast$$0(OCoLC)fst02024716
001461299 650_0 $$aTourism$$xData processing.
001461299 650_0 $$aCOVID-19 Pandemic, 2020-$$xEconomic aspects$$vCase studies.
001461299 650_0 $$aCOVID-19 Pandemic, 2020-$$xSocial aspects$$vCase studies.
001461299 655_7 $$aCase studies.$$2fast$$0(OCoLC)fst01423765
001461299 655_0 $$aElectronic books.
001461299 7001_ $$aNguwi, Yok Yen,$$eeditor.
001461299 77608 $$iPrint version:$$aNguwi, Yok Yen$$tTourism Analytics Before and after COVID-19$$dSingapore : Springer,c2023$$z9789811993688
001461299 852__ $$bebk
001461299 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-9369-5$$zOnline Access$$91397441.1
001461299 909CO $$ooai:library.usi.edu:1461299$$pGLOBAL_SET
001461299 980__ $$aBIB
001461299 980__ $$aEBOOK
001461299 982__ $$aEbook
001461299 983__ $$aOnline
001461299 994__ $$a92$$bISE