{"title":"利用卫星图像数据和谷歌数据库在玛琅市的咖啡馆市场占有率","authors":"A. Hasyim, E. Kurniawan, W. Purnamasari","doi":"10.21776/ub.civense.2022.00501.6","DOIUrl":null,"url":null,"abstract":"Cafes in Malang City have a very large quantity. Almost every main road corridor in Malang City has a small, medium, or large cafe. In a competitive situation, location factors can be critical, making it very important. Therefore, a study is needed to analyze the market share of cafes in Malang City from its spatial elements. This study aims to determine the spatial factors that affect the market share of cafes based on sample data in the form of upper-middle-class cafes in Malang City. The variables used to measure the market share of the café sample spatially are proximity to universities, building density, road hierarchy, rating, and several competitors. This study uses Google Satellite Image Data sources and remote sensing methods for processing spatial data and analyzes it using Multiple Linear Regression Analysis. Based on the analysis results, it is known that all variables are positive. The variables that have the most influence on the market share of the café sample are building density, university proximity, and road hierarchy","PeriodicalId":432135,"journal":{"name":"Civil and Environmental Science","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cafe market share using satellite image data and Google Database in Malang City\",\"authors\":\"A. Hasyim, E. Kurniawan, W. Purnamasari\",\"doi\":\"10.21776/ub.civense.2022.00501.6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cafes in Malang City have a very large quantity. Almost every main road corridor in Malang City has a small, medium, or large cafe. In a competitive situation, location factors can be critical, making it very important. Therefore, a study is needed to analyze the market share of cafes in Malang City from its spatial elements. This study aims to determine the spatial factors that affect the market share of cafes based on sample data in the form of upper-middle-class cafes in Malang City. The variables used to measure the market share of the café sample spatially are proximity to universities, building density, road hierarchy, rating, and several competitors. This study uses Google Satellite Image Data sources and remote sensing methods for processing spatial data and analyzes it using Multiple Linear Regression Analysis. Based on the analysis results, it is known that all variables are positive. The variables that have the most influence on the market share of the café sample are building density, university proximity, and road hierarchy\",\"PeriodicalId\":432135,\"journal\":{\"name\":\"Civil and Environmental Science\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Civil and Environmental Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21776/ub.civense.2022.00501.6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Civil and Environmental Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21776/ub.civense.2022.00501.6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cafe market share using satellite image data and Google Database in Malang City
Cafes in Malang City have a very large quantity. Almost every main road corridor in Malang City has a small, medium, or large cafe. In a competitive situation, location factors can be critical, making it very important. Therefore, a study is needed to analyze the market share of cafes in Malang City from its spatial elements. This study aims to determine the spatial factors that affect the market share of cafes based on sample data in the form of upper-middle-class cafes in Malang City. The variables used to measure the market share of the café sample spatially are proximity to universities, building density, road hierarchy, rating, and several competitors. This study uses Google Satellite Image Data sources and remote sensing methods for processing spatial data and analyzes it using Multiple Linear Regression Analysis. Based on the analysis results, it is known that all variables are positive. The variables that have the most influence on the market share of the café sample are building density, university proximity, and road hierarchy