G2-Group14 Proposal

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PROJECT MOTIVATION

Big Data, in today’s context, is indispensable. Businesses are realising its importance and how they should utilize data they have captured over the years by applying analytics. Over the years, Big Data analytics has helped organisations process their data; discovering insights, trends and uncovering potential opportunities. This has benefited these organisations by improving their decision-making and problem solving processes. When the opportunity to work with an international restaurant franchise arose, our team was more than keen to take on the challenge. With the relevant data readily provided by our client, we will then employ skills like delineating and digitizing the trade areas of our allocated stores, then analyse how other relevant factors such as competitions and human traffic can affect their business across Taipei. In this project, we are excited to apply skill sets that we have acquired in our Geospatial classes to help identify potential hotspots and potential problems that might be occurring. We hope that our analysis can provide the client with valuable insights, and that our proposed recommendations can aid them with their business strategies and decisions in the coming years. PROJECT OBJECTIVE The project aims to conduct a thorough analysis of the 13 of our client’s restaurant stores located near the Tamsui River in Taiwan to evaluate the success of each individual store based on their location. We will come up with the following: Digitized maps on the Quantum Geographic Information System (QGIS) software, based on the subzones labelled and provided to us by the international franchise Business profiles of each store and their relative performance to each other through extracting out relevant POIs within the trade area and subzones Setting up buffer zones to evaluate the possibility of creating an accurate business profile of each store through the use of such buffer tools, rather than digitizing the actual map areas given to us Analyze, research and provide recommendations to our client through the creation of an interesting and informational poster filled with QGIS maps for better visualization, as well as a thorough project report. PROJECT DATA SETS Name of Data Format of Data Geographic Representation Source Stores Taiwan_Stores .shp Point Professor Kam Tin Seong Land Segregation & Roads streets .shp Line - MultiLineString Professor Kam Tin Seong VILLAGE_MOI_121_1080726 .shp Polygon - MultiPolygon Professor Kam Tin Seong VILLAGE_MOI_1080726 .shp Polygon - MultiPolygon Professor Kam Tin Seong TOWN_MOI_108072 .shp Polygon - MultiPolygon Professor Kam Tin Seong COUNTY_MOI_1080726 .shp Polygon - MultiPolygon Professor Kam Tin Seong Points of Interest Business Business Facility - 5000 .shp Point Client Industrial Area - 9991 .shp Point Client Entertn Bar or Pub - 9532 .shp Point Client Cinema - 7832 .shp Point Client Nightlife - 5813 .shp Point Client Performing Arts - 7929 .shp Point Client CommSvc Government Office - 9525 .shp Point Client Park Recreational Bowling Centre - 7933 .shp Point Client Sports Complex - 7940 .shp Point Client Sports Centre - 7997 .shp Point Client EduInsts Higher Education - 8200 .shp Point Client School - 8211 .shp Point Client FinInsts ATM - 3578 .shp Point Client Bank - 6000 .shp Point Client Hospital Hospital - 8060 .shp Point Client Medical Service - 9583 .shp Point Client Restrnts Coffee Shop - 9996 .shp Point Client Restaurant - 5800 .shp Point Client TransHubs Bus Station - 4170 .shp Point Client Commuter Rail Station - 4100 .shp Point Client Train Station - 4013 .shp Point Client Shopping Bookstore - 9995 .shp Point Client Clothing Store - 9537 .shp Point Client Electronics Store - 9987 .shp Point Client Convenience Store - 9535 .shp Point Client Department Store - 9545 .shp Point Client Grocery Store - 5400 .shp Point Client Pharmacy - 9565 .shp Point Client Shopping - 6512 .shp Point Client Specialty Store - 9567 .shp Point Client Travel Destination Hotel - 7011 .shp Point Client MiscCategories Residential Area or Building - 9590 .shp Point Client Trade Areas CU-20171212寬52高42(鋁)含框 .pptx - Client LF-20190416寬60高76(鋁) .pptx - Client LU-20190318寬70高90(木) .pptx - Client SC-20171124寬74高90(鋁)含框 .pptx - Client SZ-20190830寬88.5高100(鋁)含框 .pptx - Client LW-20180109寬110高76.5(木) .pptx - Client WG-20150722寬60高比例(鋁) .pptx - Client BL .pptx - Client DC .pptx - Client DJ .pptx - Client DS .pptx - Client FW-20171115寬75高80(鋁)含框 .pptx - Client ZT-20190323寬76高等比(鋁)含框 .pptx - Client FUNCTIONS AND ANALYSIS Functions Employed Analysis Conducted Choropleth Mapping Revenue Analysis for each of the allocated stores Revenue Analysis for each POD in their trade areas Count by Polygon – the generation of the 32 main POI variables Generation of the Business Profiles for the stores Relationship between the Total Number of POIs and Revenue Network OD-Matrix (Layers as Table (M:N)) Relationship between the Average Shortest Distance of the POIs from the stores and Revenue Multi-Linear Regression (using SAS Enterprise Guide) Relationship between Important Variables and Revenue Linear Regression (using SAS Enterprise Guide) Relationship between Area of Trade and Revenue Hub Lines / Distance Relationship between Competitors and Revenue Buffer Generation for 2.5KM, 3.0KM and 3.5KM Analysis of the use of Buffers as a Theoretical Trade Area Iso-Areas as Contours (from Layer) Analysis of the use of Network Service Area as a Theoretical Trade Area Comparison between the use of Theoretical Trade Areas and the Actual Digitised Trade Areas Errors - Data gap discovered for the Population Data PROJECT TIMELINE TOOLS USED QGIS - Our platform to analyze and edit spatial information, in addition to composing and exporting graphical maps SAS Enterprise Guide - Our platform to generate and calculate Multi-Regression Lines and Col-linearity between Points of Interests Microsoft Excel - Our platform for data cleaning and calculations Microsoft PowerPoint - Our platform to construct the Poster and Executive Report Microsoft Word - Our platform for Final Report Google Docs - Our platform for weekly discussions and report write up Google Forms - Our platform for FeedBack during Townhall Presentation REFERENCES About: https://www.trip.com/travel-guide/taipei/tamsui-river-23866567/ https://guidetotaipei.com/visit/tamsui-fishermans-wharf-%E6%B7%A1%E6%B0%B4%E6%BC%81%E4%BA%BA%E7%A2%BC%E9%A0%AD