{"title":"探索城市高科技景观以克服标准产业分类:巴黎和多伦多的跨行业网络分析","authors":"Paola Antonelli, M. Cucculelli","doi":"10.2139/ssrn.3560763","DOIUrl":null,"url":null,"abstract":"Despite periodic updating, conventional administrative datasets and industry codes often fail to provide classifications for services and the emerging industries of the twenty-first century. For researchers, these data challenges present particular barriers to understanding the nature of business activities. For policymakers, these information gaps feed through into policy gaps, which can limit the ability to design effective interventions to encourage local entrepreneurship and innovation in high-technology sectors. The present paper worked with non-traditional data sources to avoid current classification systems. Using metadata about high-tech firms from CrunchBase, this paper studied the structure of cross-industry landscape, individual network characteristics, and major technological complementarities of high-tech industry networks. We investigate two of the most promising high-tech hubs, Paris and Toronto, to explore the potential of such approach. Results shed light on the complex networks of cross-sectoral horizontal and vertical linkages that characterize the two hubs and help policy makers and venture capitalists to deeply understand the business landscape of high-tech local companies.","PeriodicalId":136014,"journal":{"name":"Sustainable Technology eJournal","volume":"50 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring Urban High-Tech Landscapes to Overcome Standard Industrial Classification: A Cross-Industry Network Analysis in Paris and Toronto\",\"authors\":\"Paola Antonelli, M. Cucculelli\",\"doi\":\"10.2139/ssrn.3560763\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite periodic updating, conventional administrative datasets and industry codes often fail to provide classifications for services and the emerging industries of the twenty-first century. For researchers, these data challenges present particular barriers to understanding the nature of business activities. For policymakers, these information gaps feed through into policy gaps, which can limit the ability to design effective interventions to encourage local entrepreneurship and innovation in high-technology sectors. The present paper worked with non-traditional data sources to avoid current classification systems. Using metadata about high-tech firms from CrunchBase, this paper studied the structure of cross-industry landscape, individual network characteristics, and major technological complementarities of high-tech industry networks. We investigate two of the most promising high-tech hubs, Paris and Toronto, to explore the potential of such approach. Results shed light on the complex networks of cross-sectoral horizontal and vertical linkages that characterize the two hubs and help policy makers and venture capitalists to deeply understand the business landscape of high-tech local companies.\",\"PeriodicalId\":136014,\"journal\":{\"name\":\"Sustainable Technology eJournal\",\"volume\":\"50 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Technology eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3560763\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Technology eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3560763","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exploring Urban High-Tech Landscapes to Overcome Standard Industrial Classification: A Cross-Industry Network Analysis in Paris and Toronto
Despite periodic updating, conventional administrative datasets and industry codes often fail to provide classifications for services and the emerging industries of the twenty-first century. For researchers, these data challenges present particular barriers to understanding the nature of business activities. For policymakers, these information gaps feed through into policy gaps, which can limit the ability to design effective interventions to encourage local entrepreneurship and innovation in high-technology sectors. The present paper worked with non-traditional data sources to avoid current classification systems. Using metadata about high-tech firms from CrunchBase, this paper studied the structure of cross-industry landscape, individual network characteristics, and major technological complementarities of high-tech industry networks. We investigate two of the most promising high-tech hubs, Paris and Toronto, to explore the potential of such approach. Results shed light on the complex networks of cross-sectoral horizontal and vertical linkages that characterize the two hubs and help policy makers and venture capitalists to deeply understand the business landscape of high-tech local companies.