This 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.
Author(s): Yok Yen Nguwi
Publisher: Springer
Year: 2023
Language: English
Pages: 248
City: Singapore
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
Tourism 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
Tourism 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
Descriptive 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
Dataset 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
