Difference between revisions of "Macao Travels-Proposal"

From Visual Analytics for Business Intelligence
Jump to navigation Jump to search
Line 231: Line 231:
 
! style="font-weight: bold;color:#000000;" | Explanation
 
! style="font-weight: bold;color:#000000;" | Explanation
 
|-
 
|-
| [[File:R studio logo.png|200px|center]]
+
| [[File:R studio logo.png|200px|center]]<center>R Studio</center>
 
||  
 
||  
 
To overcome this challenge, our team conducted background research on this topic (tourism) and gathered some design inspirations that we can consider using for our visualization. After this, we started planning out how the visualization will look and learn how to integrate different charts and enhance the interactivity by creating storyboards.  
 
To overcome this challenge, our team conducted background research on this topic (tourism) and gathered some design inspirations that we can consider using for our visualization. After this, we started planning out how the visualization will look and learn how to integrate different charts and enhance the interactivity by creating storyboards.  
 
|-
 
|-
| [[File:R shiny.png|100px|center]]
+
| [[File:R shiny.png|100px|center]]<center>R Shiny</center>
 
||  
 
||  
 
To address this challenge, the team will focus on learning more about R and RShiny from online tools such as Datacamp (independent learning). We will also seek help from our Prof. Kam, fellow peers, YouTube tutorials and make use of Google for any queries.
 
To address this challenge, the team will focus on learning more about R and RShiny from online tools such as Datacamp (independent learning). We will also seek help from our Prof. Kam, fellow peers, YouTube tutorials and make use of Google for any queries.
 
|-
 
|-
| [[File:Canva logo.png|100px|center]]
+
| [[File:Canva logo.png|100px|center]] <center>Canva</center>
 
||  
 
||  
 
The current datasets must be cleaned as the data is messy and the format is not proper. Since our project requires a total of 26 datasets, we will face key issues in preparing the data for visualisation. Our team plans to split up the data cleaning work into different segments and work on it individually, before coming together to check the datasets together, and promptly proceed to merge them if needed.
 
The current datasets must be cleaned as the data is messy and the format is not proper. Since our project requires a total of 26 datasets, we will face key issues in preparing the data for visualisation. Our team plans to split up the data cleaning work into different segments and work on it individually, before coming together to check the datasets together, and promptly proceed to merge them if needed.

Revision as of 22:29, 10 November 2019

VA Project Logo1.png

Back to Project Home


Home

 

Proposal

 

Poster

 

Application

 

Research Paper


Problem Statement

Macao’s tourism industry has always been one of the most important industries driving economic progress, with visitor arrivals in Macao reporting around 35 million visitors in 2018 and tourism revenues in Macao reached an all-time high of 18,352 MOI Million in the third quarter in 2018. Another key aspect of tourism in Macao is its gaming industry. The gaming industry is the major driving force for Macao’s economy. The most densely populated region in the world heavily relies on the popularity of being a gambling destination - 40% of Macao’s GDP comes from the gaming industry and more than 70% of tax revenues are collected from casinos. Despite the rapid growth, the Macao SAR Government has the vision to build it into a World Centre of Tourism and Leisure in the next 15 years.

Motivation

Ever since the establishment of the Macao Special Administrative Region (Macao SAR), special emphasis has been placed on the development of the city’s tourism industry, which has been a catalyst for continued growth over the last decade.

Our main motivation is to address the lack of a convenient and comprehensive platform to study the correlation and trends amidst Macao’s most important industry to their financial growth. The current visualization tool employed by Macao’s Government is inadequate and difficult to visualize trends and uncover patterns for the tourism industry. The Macao Government Tourism only provides the market report and basic info-graphics on tourist arrivals and hotel statistics. Furthermore, Macao’s government does not have a proper visualization tool for its gaming industry, which is a huge component of the tourism industry in Macao. This project provides an interactive visualization to better analyze Macao’s tourism industry, consisting of lodging, gaming and tourism spending. Through our visualization, we aim to identify the relation between the tourism industry, and its two biggest components: hotel and gaming industry, as well as to uncover trends and patterns that the Government of Macao can utilize to further boost their economy by optimizing marketing campaigns. We aim to answer questions such as how much resources should be allocated to Macao’s tourism industry, or where do most of Macao’s main contributors to its tourism industry come from?

Objectives

This project aims to provide insights into the following:

  1. Gain insights on the monthly/yearly visitor arrivals to Macao over the past 10 years
  2. Identify tourist preference for hotels and hotel's occupancy rate
  3. Breakdown of tourists’ expenditure to find out which country is spending the most and which area they are spending the most on (e.g. Shopping, F&B)
  4. Gain insights on Macao’s gaming industry and which country contributes most to the gaming industry

Background survey of related works

Visualizations Insights and Explanation
V1.jpg


Source: https://mbienz.shinyapps.io/tourism_dashboard_prod//center>

This visualization allows users to find out how many international tourists are coming into Macao every year. Furthermore, the plotting of both a 12-month rolling average and observation on the same graph enables us to have a quick and clear overview. However, one drawback of the visualization is that it does not allow us to plot different countries on the same graph. Hence, this visualization is only limited to viewing the overall incoming tourist into Macao and users are unable to visualize the incoming number of tourists from each country individually. To overcome this drawback, my team will have a similar line chart that allows users to view the incoming tourist from each country.

V2.jpg


Source: https://ourworldindata.org/tourism

The used of an area chart is an effective way of displaying the total international tourist arrivals by region. The area allows users to see the tourist arrivals breakdown for each region – each colour on the chart represents a specific region. This allows users to get a rough gauge of the number of tourists coming from the different regions just by looking at the area on the chart.

Macau777-2.png


Source: https://dataplus.macaotourism.gov.mo/

This visualization is a combo chart that comprises two charts in one - a time-series line chart, and a bar chart, which compares the international visitor arrival with the year on year change of each country. However, this visualization looks confusing (as there are too many lines displayed on the same graph) and it is hard to compare visitor arrivals across the different countries. One possible way to show the number of international visitors arriving from each region (e.g. Asia, Europe) and subsequently break this down the regions and enable users to visualize the yearly visitor arrivals of each country (e.g. France, Spain, Germany).


Design Inspirations

Visualizations Explanation
Treemap
Treemapp.png


Source: https://www.dataplusscience.com/UsingTreemaps.html

Treemap diagrams can be used to visualize hierarchical and part-to-whole relationships very effectively. We can use it to visualize the number of tourists coming from different regions and countries and the total spending by different visitors going into Macao. One advantage of using a treemap is that we can easily derive the top 3 visiting countries. However, it does not provide us with time series analysis, and it is hard to compare the arrival of tourists across different years. Furthermore, the hierarchy of the treemap has only 2 levels. As such, the level of detail and interaction may be limited.

Radar Chart
Rc.jpg


Source: https://www.slideteam.net/spider-chart-allocated-budget-and-actual-spending.html

A radar chart is used to compare multiple quantitative variables and it is useful to identify variables with similar values and outliers amongst each variable. For our project, we can make use of the radar chart to display the breakdown of tourist spending into different categories (e.g. shopping, F&B, etc). The ability to overlay the spending of different countries allows us to easily compare and identify countries with the highest spending in Macao. However, having too many overlays on a chart may cause the chart to be complicated and tedious to visualize. As such, our team may consider splitting the countries based on their region.

Map
V3.png


Source: https://ourworldindata.org/tourism

By using a map, we can better represent and display geographical locations data. The world map also allows us to visualize where tourists are coming from and the distance to get to Macao. Furthermore, it uses colors and legend to differentiate between the allocated budget and actual spending. We can use a similar approach where each color represents the spending of each country.

Heatmap
Heatmap1.jpg


Source: https://www.kdnuggets.com/2016/03/4-lessons-brilliant-data-visualization.html

A heatmap is a graphical representations of data that utilize color-coded systems to allow users to better visualize the volume of events and it serves the purpose of directing user’s attention towards areas on the visualization that matter most. Our team has decided to incorporate the use of the heatmap to identify tourist preference for the different hotel types (e.g. 5-star, 4-star, etc) as it allows us to quickly understand tourists’ behaviors and patterns.

Proposed Storyboard

Visualizations Explanation
Storyboard 1 - Economic Contribution
Economic Contribution.jpg


  • The purpose is to show the comparison between Macao’s GDP and tourists spending and expenditure
  • Provide an overview of the total visits, spending and hotel occupancy in Macao.
  • There is a slider at the bottom of the visualization for users to select the period they want to analyse
  • Charts used: Combo chart, Area chart
Storyboard 2 - Tourist Spending
Tourist Spending.jpg
Tourist Spending 1.jpg


  • Aims to show the breakdown of tourist spending by countries and category (e.g. entertainment, F&B)
  • When users hover over a specific point on the map, they will be able to view the spending of that country.
  • Filters are present on the visualization to allow users to select a region or year that they wish to analyse. Based on the user selection, the visualization will display the results accordingly.
  • Charts used: Radar chart, Map, Bar chart, Stacked bar char, Line chart
Storyboard 3 - Tourist Arrivals
Tourist Arrivals.jpg


  • The point of this visualization is to show the trend of visitor arrivals into Macao every year.
  • Users can gather insights such as the arrivals trends of each country and the top 10 countries visiting Macao every year.
  • Charts used: Packed bar chart, Line chart, Treemap, Bar chart
Storyboard 4 - Purpose of Visit
Purpose of Visit.jpg


  • Aims to provide the purpose of arrival through trend line charts and stacked bar chart
  • Users can use the slider to select the period they want to analyse
  • Charts used: Stacked bar chart, Line chart
Storyboard 5 - Accommodation
Accommodation.jpg
Accommodation 1.1.jpg


  • Aims to show the yearly number of hotel guests for each country and the percentage of hotel room types available in Macao.
  • A combo chart was used to allow users to visualize the total number of hotel guests and the occupancy rate every year.
  • More in-depth analysis can be made with the line chart that shows the comparison between the occupancy rate and the number of hotels against tourist arrivals. Users will be able to determine if the increase or decrease in tourist arrivals affects the occupancy rate and the number of hotels in Macao.
  • Charts used: Heatmap, Pie chart, Bar chart, Combo chart, Line chart
Storyboard 6 - Gaming
Gaming.jpg


  • The purpose of this visualization is to show Macao’s gaming revenue and the growth of its games. Furthermore, users can gather insights such as the top 10 games, determine whether the increase in tourist arrivals will affect the revenue of the gaming industry and the countries that contribute the most to the gaming industry in Macao.
  • Charts used: Combo chart, Line chart, and Bar chart


Datasets

We have obtained the following datasets for this research:

Dataset/Source Data Attributes Purpose
Gaming Statistics (CEIC)

(2009 - 2018)

  1. Number of Casinos and Gaming Table
  2. Gross Revenues
  3. Gross Receipts
  4. Betting Amounts
This dataset will allow us to see the popular games in the casinos. This can be joined with other datasets to draw a relation with the tourists that are driving the popular games.
Hotel Statistics(CEIC)

(2009 - 2018)

  1. Number of Hotels, Hotel Rooms and Hotel Beds
  2. Room Occupancy Rate
  3. Hotel Guests
  4. Average Hotel Room Rate
  5. Average Length of Stay
This dataset will allow us to determine the various statistics of hotel occupancy, which can be used to analyse visitor preference for hotels based on conditions such as price and star ratings.
Visitor Arrivals (CEIC)

(2009 - 2018)

  1. Overnight Arrivals
  2. Same Day Arrivals
  3. By Tour Package
  4. Mode of Transport

This dataset will let us see the arrivals of tourists and whether it is overnight or same day arrivals.

Resident Departures (CEIC)

(2009 - 2018)

  1. Mode of Transport
  2. Destinations

This dataset will be used to determine how residents depart, and to which country.

Visitor per Capita Spending (CEIC)

(2009 - 2018)

  1. Countries
  2. Type of Expenses
  3. Tourist Price Index
This dataset will allow us to determine what do tourists from each country spend in Macao.
Visiting Purposes (Data plus)

(2009 - 2018)

  1. Purpose of visit
This dataset will be used to understand the purpose of visit by the tourists into Macao.

Tools and Technologies

Tools and Technologies Explanation
R studio logo.png
R Studio

To overcome this challenge, our team conducted background research on this topic (tourism) and gathered some design inspirations that we can consider using for our visualization. After this, we started planning out how the visualization will look and learn how to integrate different charts and enhance the interactivity by creating storyboards.

R shiny.png
R Shiny

To address this challenge, the team will focus on learning more about R and RShiny from online tools such as Datacamp (independent learning). We will also seek help from our Prof. Kam, fellow peers, YouTube tutorials and make use of Google for any queries.

Canva logo.png
Canva

The current datasets must be cleaned as the data is messy and the format is not proper. Since our project requires a total of 26 datasets, we will face key issues in preparing the data for visualisation. Our team plans to split up the data cleaning work into different segments and work on it individually, before coming together to check the datasets together, and promptly proceed to merge them if needed.

Architectural Design


Technical Challenges

Key Technical Challenges Solution
Lack of experience in visualizing the data and implementing interactivity and animated designs in visualization application.

To overcome this challenge, our team conducted background research on this topic (tourism) and gathered some design inspirations that we can consider using for our visualization. After this, we started planning out how the visualization will look and learn how to integrate different charts and enhance the interactivity by creating storyboards.

Unfamiliarity with visualisation tools such as R and RShiny

To address this challenge, the team will focus on learning more about R and RShiny from online tools such as Datacamp (independent learning). We will also seek help from our Prof. Kam, fellow peers, YouTube tutorials and make use of Google for any queries.

Data Cleaning and transformation of data

The current datasets must be cleaned as the data is messy and the format is not proper. Since our project requires a total of 26 datasets, we will face key issues in preparing the data for visualisation. Our team plans to split up the data cleaning work into different segments and work on it individually, before coming together to check the datasets together, and promptly proceed to merge them if needed.

Timeline

VA Project Timeline (final).jpg

References

Macao Data:

  1. CEIC Database: https://insights-ceicdata-com.libproxy.smu.edu.sg/Untitled-insight/views
  2. Data Plus: https://dataplus.macaotourism.gov.mo/Indicator/VisitorsSummary/SummaryBar?lang=E

Macao Tourism Industry Development Master Plan: https://masterplan.macaotourism.gov.mo/home-en/index.html

Data Cleaning:

  1. Reading and Importing Excel Files into R: https://www.datacamp.com/community/tutorials/r-tutorial-read-excel-into-r