Difference between revisions of "G1-Group05 Proposal"

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[[G1-Group05|<font color="#872b2b"><strong>HOME</strong></font>]]
 
[[G1-Group05|<font color="#872b2b"><strong>HOME</strong></font>]]
  
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[[G1-Group05_Proposal|<font color="#872b2b"><strong>PROPOSAL</strong></font>]]
 
[[G1-Group05_Proposal|<font color="#872b2b"><strong>PROPOSAL</strong></font>]]
  
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=<div style="margin-top: 10px;font-family: Century Gothic;font-weight:bold;text-align:center;font-size:20px; border: 5px solid #00000000; border-radius:8px;text-align:center; background-color: #872b2b; color: white; padding: 2px"><span style="font-size:24px;"></span>About Areas Studied</div>=
 
=<div style="margin-top: 10px;font-family: Century Gothic;font-weight:bold;text-align:center;font-size:20px; border: 5px solid #00000000; border-radius:8px;text-align:center; background-color: #872b2b; color: white; padding: 2px"><span style="font-size:24px;"></span>About Areas Studied</div>=
 
 
 
<font size="4">
 
<font size="4">
Digitisation<br>
+
Our group studied 14 franchise outlets, 9 of which were located in Taipei and 5 in the Yilan region of Taiwan. The areas we received were mostly clustered together. This allows us to take away certain assumptions, and instead focus on seeing how the points-of-interest and trade area properties impact annual sales.
Stores alr have their own trade area based on delivery services (operational trade area) --> Manually digitise outer boundary, then inner boundary
 
 
 
 
Trade Area Analysis
 
* Buffer trade area --> Mutually exclusive (like today's lesson)
 
* Varied distance trade area
 
  
 
Comparative Analysis
 
Compare btw theoretical & operational trade area
 
* Points of interests (POI) within each TA (eg. Biz establishments) -- Use facility type codes in code book "Map Releases - Taiwan PDF"
 
              Point in polygon count for each POI of interest --> Run as Batch Process
 
 
* Sales figures
 
* Drive time
 
 
</font>
 
 
=<div style="margin-top: 10px;font-family: Century Gothic;font-weight:bold;text-align:center;font-size:20px; border: 5px solid #00000000; border-radius:8px;text-align:center; background-color: #872b2b; color: white; padding: 2px"><span style="font-size:24px;"></span>Scope of  Work</div>=
 
=<div style="margin-top: 10px;font-family: Century Gothic;font-weight:bold;text-align:center;font-size:20px; border: 5px solid #00000000; border-radius:8px;text-align:center; background-color: #872b2b; color: white; padding: 2px"><span style="font-size:24px;"></span>Scope of  Work</div>=
 +
<font size="4">
  
 +
Our main tool to perform our analyses was QGIS, a free and open-source geographic information system. To support our findings with more in-depth calculations, we used SAS Enterprise Guide.
  
<font size="4">
 
 
Data Preparation
 
Data Preparation
* Digitisation of trade areas
+
* Digitisation of operational trade
* Ideal trade area
+
* Data Cleaning
* Operational trade area
+
* Trade Area Buffer Creation
 +
* Count POI in Polygons
  
 
Performing GIS Analysis
 
Performing GIS Analysis
* Comparison between ideal & operational trade area
+
* Vector-Based Analysis
* POI within each TA
+
* Raster-Based Analysis
* Sales figures
+
* Trade Area Analysis
* Drive time
+
* Multiple Linear Regression
 +
* POI-Sales Analysis
 +
* Drive Time Analysis
  
 
Project Deliverables
 
Project Deliverables
* Preparing report of survey
+
* Poster
* Preparing poster and materials for townhall presentation
+
* Full Report
 +
* Summarised Report
 +
 
 
</font>
 
</font>
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=<div style="margin-top: 10px;font-family: Century Gothic;font-weight:bold;text-align:center;font-size:20px; border: 5px solid #00000000; border-radius:8px;text-align:center; background-color: #872b2b; color: white; padding: 2px"><span style="font-size:24px;"></span>Project Timeline</div>=
 
=<div style="margin-top: 10px;font-family: Century Gothic;font-weight:bold;text-align:center;font-size:20px; border: 5px solid #00000000; border-radius:8px;text-align:center; background-color: #872b2b; color: white; padding: 2px"><span style="font-size:24px;"></span>Project Timeline</div>=
 
[[File:TimelineG1G5.png|1200px|frameless|center]]
 
[[File:TimelineG1G5.png|1200px|frameless|center]]
<br>
 
 
=<div style="margin-top: 10px;font-family: Century Gothic;font-weight:bold;text-align:center;font-size:20px; border: 5px solid #00000000; border-radius:8px;text-align:center; background-color: #872b2b; color: white; padding: 2px"><span style="font-size:24px;"></span>Project Reference</div>=
 
 
<br>
 
<br>
  
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{| class="wikitable"
 
{| class="wikitable"
 
|-
 
|-
! Data Name !! Data Format !! Source
+
! Data !! Data Format !! Data Source
 
|-
 
|-
 
|-style= "background-color:#E98074"
 
|-style= "background-color:#E98074"
!scope="row" colspan="4"|<b>''Landuse (2008/2014/2019)''</b>
+
!scope="row" colspan="4"|<b>''Admin Boundary''</b>
 
|-
 
|-
 
|-
 
|-
| URA Planning Areas (2008) || Shape files || https://data.gov.sg/dataset/master-plan-2008-planning-area-boundary-no-sea
+
| Country MOI || Shapefile (.shp) || Prof Kam & Client
 
|-
 
|-
 
|-
 
|-
| URA Planning Areas (2014) || Shape files || https://data.gov.sg/dataset/master-plan-2014-planning-area-boundary-web
+
| Town MOI || Shapefile (.shp) || Prof Kam & Client
 
|-
 
|-
 
|-
 
|-
| URA Planning Areas (2019) || Reference || https://www.ura.gov.sg/Corporate/Planning/Draft-Master-Plan-19
+
| Village MOI || Shapefile (.shp) || Prof Kam & Client
 
|-
 
|-
 
|-style= "background-color:#E98074"
 
|-style= "background-color:#E98074"
!scope="row" colspan="4"|<b>''Population''</b>
+
!scope="row" colspan="4"|<b>''Taiwan Stores''</b>
 
|-  
 
|-  
| Population (2015) || CSV || https://www.singstat.gov.sg/find-data/search-by-theme/population/geographic-distribution/latest-data
+
| Taiwan Stores (inclusive of our 14 stores) || Geopackage (.gpkg) || Prof Kam & Client
 
|-
 
|-
| Population (2019) || CSV || https://www.singstat.gov.sg/-/media/files/publications/population/population2019.pdf
+
|-style= "background-color:#E98074"
 +
!scope="row" colspan="4"|<b>''Location Maps''</b>
 +
|-
 +
| Taiwan Stores (inclusive of our 14 stores) || PowerPoint Slides (.ppt) || Client
 +
|-
 +
|-style= "background-color:#E98074"
 +
!scope="row" colspan="4"|<b>''Point of Interest (POI)''</b>
 +
|-
 +
| ATM || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Bank|| Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Bar/Pub|| Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Bookstore || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Bowling Centre|| Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Bus Station || Shapefile (.shp)  ||  Prof Kam & Client
 
|-
 
|-
 +
| Business Facility || Shapefile (.shp)  ||  Prof Kam & Client
 
|-
 
|-
| Profession || CSV || https://www.tablebuilder.singstat.gov.sg/publicfacing/createSpecialTable.action?refId=8321
+
| Cinema || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Clothing Store || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Coffee Shop|| Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Commuter Rail Station || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Consumer Electronics Store || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Convenience Store || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Department Store || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Government Office || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Grocery Store || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Higher Education || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Hospital || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Hotel || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Industrial Zone || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Medical Service || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Nightlife || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Performing Arts || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Pharmacy || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Residential Area/Building || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Restaurant || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| School || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Shopping || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Speciality Store || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Sports Centre || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Sports Complex || Shapefile (.shp)  ||  Prof Kam & Client
 +
|-
 +
| Train Station || Shapefile (.shp)  ||  Prof Kam & Client
 
|-
 
|-
 
|-style= "background-color:#E98074"
 
|-style= "background-color:#E98074"
!scope="row" colspan="4"|<b>''Education & Healthcare Services''</b>
+
!scope="row" colspan="4"|<b>''Sales Data''</b>
 +
|-
 +
| Trade Area Annual Sales Data || Comma-Separated Values (.csv)  || Prof Kam & Client
 
|-
 
|-
| Childcare Services || Shapefile||  https://data.gov.sg/dataset/listing-of-centres
 
 
 
|}
 
|}

Latest revision as of 13:15, 23 November 2019

HOME

PROPOSAL

POSTER

WEB MAPS

FINAL REPORT

Proposal

About Taipei and Yilan

Taipei, the capital of Taiwan, is the most populated city in Taiwan with around 7 million people in the city and surrounding areas. In contrast, Yilan is a county in northeastern Taiwan. Even though its land area is 8 times the size of Taipei, it has a low population of around 450,000 people. Joining together both counties is Jiang Yushui Expressway (National Freeway 5).

Project Motivation

Our client is part of the International Food and Beverage franchise that is currently present in Taiwan. Our client has provided us with data to analyse each outlet and their respective trade areas have impacted the franchise's business in Taipei and Yilan. By understanding the trade areas of each location better, we can identify what influences the performance of each outlet.

Our project aims to digitise and delineate the trade areas, as well as study the points of interest per area. We can then provide useful information for our client by analysing effect the different points of interests have on sales. This information will allow for more informed business decision-making, especially when assessing the success of their current outlets considering the viability of a potential new outlet location.

Project Objectives

Highway to Taipei aims to achieve the following objectives by the end of the project:

  1. Digitise and delineate Operational Trade Areas
  2. Analyse the overlapping trade areas of the outlets
  3. Extract significant POIs
  4. Analyse impact of POIs in each trade area of each outlet
  5. Perform drive time analysis & impact on trade areas
  6. Create GIS maps for data visualisation
  7. Summarise findings in a poster & report

About Areas Studied

Our group studied 14 franchise outlets, 9 of which were located in Taipei and 5 in the Yilan region of Taiwan. The areas we received were mostly clustered together. This allows us to take away certain assumptions, and instead focus on seeing how the points-of-interest and trade area properties impact annual sales.

Scope of Work

Our main tool to perform our analyses was QGIS, a free and open-source geographic information system. To support our findings with more in-depth calculations, we used SAS Enterprise Guide.

Data Preparation

  • Digitisation of operational trade
  • Data Cleaning
  • Trade Area Buffer Creation
  • Count POI in Polygons

Performing GIS Analysis

  • Vector-Based Analysis
  • Raster-Based Analysis
  • Trade Area Analysis
  • Multiple Linear Regression
  • POI-Sales Analysis
  • Drive Time Analysis

Project Deliverables

  • Poster
  • Full Report
  • Summarised Report

Project Timeline

TimelineG1G5.png


Data Sources


Data Data Format Data Source
Admin Boundary
Country MOI Shapefile (.shp) Prof Kam & Client
Town MOI Shapefile (.shp) Prof Kam & Client
Village MOI Shapefile (.shp) Prof Kam & Client
Taiwan Stores
Taiwan Stores (inclusive of our 14 stores) Geopackage (.gpkg) Prof Kam & Client
Location Maps
Taiwan Stores (inclusive of our 14 stores) PowerPoint Slides (.ppt) Client
Point of Interest (POI)
ATM Shapefile (.shp) Prof Kam & Client
Bank Shapefile (.shp) Prof Kam & Client
Bar/Pub Shapefile (.shp) Prof Kam & Client
Bookstore Shapefile (.shp) Prof Kam & Client
Bowling Centre Shapefile (.shp) Prof Kam & Client
Bus Station Shapefile (.shp) Prof Kam & Client
Business Facility Shapefile (.shp) Prof Kam & Client
Cinema Shapefile (.shp) Prof Kam & Client
Clothing Store Shapefile (.shp) Prof Kam & Client
Coffee Shop Shapefile (.shp) Prof Kam & Client
Commuter Rail Station Shapefile (.shp) Prof Kam & Client
Consumer Electronics Store Shapefile (.shp) Prof Kam & Client
Convenience Store Shapefile (.shp) Prof Kam & Client
Department Store Shapefile (.shp) Prof Kam & Client
Government Office Shapefile (.shp) Prof Kam & Client
Grocery Store Shapefile (.shp) Prof Kam & Client
Higher Education Shapefile (.shp) Prof Kam & Client
Hospital Shapefile (.shp) Prof Kam & Client
Hotel Shapefile (.shp) Prof Kam & Client
Industrial Zone Shapefile (.shp) Prof Kam & Client
Medical Service Shapefile (.shp) Prof Kam & Client
Nightlife Shapefile (.shp) Prof Kam & Client
Performing Arts Shapefile (.shp) Prof Kam & Client
Pharmacy Shapefile (.shp) Prof Kam & Client
Residential Area/Building Shapefile (.shp) Prof Kam & Client
Restaurant Shapefile (.shp) Prof Kam & Client
School Shapefile (.shp) Prof Kam & Client
Shopping Shapefile (.shp) Prof Kam & Client
Speciality Store Shapefile (.shp) Prof Kam & Client
Sports Centre Shapefile (.shp) Prof Kam & Client
Sports Complex Shapefile (.shp) Prof Kam & Client
Train Station Shapefile (.shp) Prof Kam & Client
Sales Data
Trade Area Annual Sales Data Comma-Separated Values (.csv) Prof Kam & Client