{"title":"Smart City Measurement: Identification of Smart Economy Performance Indicators in Indonesia","authors":"Bima Ajie Bahari, T. D. Susanto, Janti Gunawan","doi":"10.2991/AEBMR.K.210510.046","DOIUrl":null,"url":null,"abstract":"The concept of smart city is believed to be one of the solutions to overcome problems in urban areas. Although much research has been carried out, there is still no agreed international standards regarding models, concepts, indicators, ways to measure smart city performance and the characteristics of each country that are different. In Indonesia, there is a smart city model that consists of 6 dimensions. One of the dimensions is smart economy, where there are three sub-dimensions to make it more specific and targeted. The three sub-dimensions are industry, welfare, and transactions. Also, there are factors of each subdimensions for support purpose. Smart economy has goal to develop competitive, superior, and adaptive economic ecosystems. This study aims to identify indicators of the application of the smart economy in Indonesia. Literature reviews related to smart economy will be used, and article sources come from leading online databases. The purpose of the literature review is to find indicators of other research findings outside Indonesia that are relevant to this study. Hundreds of articles have been found and filtered into 30 articles only. From 30 literatures, synthesis analysis was carried out to look for indicators of findings and mapped according to sub-dimensions and factors in Indonesia's smart economy. As a result, there are 18 indicators found. Indicators resulting from this research are expected to contribute both in theory and practice. In addition, the indicators found are expected to help the government develop smart cities in Indonesia.","PeriodicalId":287694,"journal":{"name":"Proceedings of the 2nd International Conference on Business and Management of Technology (ICONBMT 2020)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Conference on Business and Management of Technology (ICONBMT 2020)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/AEBMR.K.210510.046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The concept of smart city is believed to be one of the solutions to overcome problems in urban areas. Although much research has been carried out, there is still no agreed international standards regarding models, concepts, indicators, ways to measure smart city performance and the characteristics of each country that are different. In Indonesia, there is a smart city model that consists of 6 dimensions. One of the dimensions is smart economy, where there are three sub-dimensions to make it more specific and targeted. The three sub-dimensions are industry, welfare, and transactions. Also, there are factors of each subdimensions for support purpose. Smart economy has goal to develop competitive, superior, and adaptive economic ecosystems. This study aims to identify indicators of the application of the smart economy in Indonesia. Literature reviews related to smart economy will be used, and article sources come from leading online databases. The purpose of the literature review is to find indicators of other research findings outside Indonesia that are relevant to this study. Hundreds of articles have been found and filtered into 30 articles only. From 30 literatures, synthesis analysis was carried out to look for indicators of findings and mapped according to sub-dimensions and factors in Indonesia's smart economy. As a result, there are 18 indicators found. Indicators resulting from this research are expected to contribute both in theory and practice. In addition, the indicators found are expected to help the government develop smart cities in Indonesia.