{"title":"1976-1989年美国生物技术企业人口动态和地理分布的基本原理","authors":"L. Zucker, M. Darby, Yusheng Peng","doi":"10.3386/W6414","DOIUrl":null,"url":null,"abstract":"Population ecology models are elegant in form and adequate in describing aggregate data, but poor in telling stories and predicting the location of growth. Fundamentals models emphasizing the variables central to resource mobilization, such as intellectual human capital, can predict where and when biotechnology enterprises emerge and agglomerate. Density dependence and previous founding dependence proxy many underlying processes; the legitimation and competition interpretation is more conjectural than empirically tenable. We argue and demonstrate for biotechnology that an alternative model based on the fundamentals related to resource reallocation and mobilization provides a stronger frame to explore industry formation. Fundamentals models outperform population ecology models in the estimations, while a combined model driven by fundamentals but incorporating weak population dynamics does best. In repeated dynamic simulations, the population ecology model predictions are essentially uncorrelated with the panel data on biotechnology entry by year and region while the combined model has correlation coefficients averaging above 0.8.","PeriodicalId":432021,"journal":{"name":"Kauffman Data: COMETS (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1998-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Fundamentals or Population Dynamics and the Geographic Distribution of U.S. Biotechnology Enterprises, 1976-1989\",\"authors\":\"L. Zucker, M. Darby, Yusheng Peng\",\"doi\":\"10.3386/W6414\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Population ecology models are elegant in form and adequate in describing aggregate data, but poor in telling stories and predicting the location of growth. Fundamentals models emphasizing the variables central to resource mobilization, such as intellectual human capital, can predict where and when biotechnology enterprises emerge and agglomerate. Density dependence and previous founding dependence proxy many underlying processes; the legitimation and competition interpretation is more conjectural than empirically tenable. We argue and demonstrate for biotechnology that an alternative model based on the fundamentals related to resource reallocation and mobilization provides a stronger frame to explore industry formation. Fundamentals models outperform population ecology models in the estimations, while a combined model driven by fundamentals but incorporating weak population dynamics does best. In repeated dynamic simulations, the population ecology model predictions are essentially uncorrelated with the panel data on biotechnology entry by year and region while the combined model has correlation coefficients averaging above 0.8.\",\"PeriodicalId\":432021,\"journal\":{\"name\":\"Kauffman Data: COMETS (Topic)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Kauffman Data: COMETS (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3386/W6414\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kauffman Data: COMETS (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3386/W6414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fundamentals or Population Dynamics and the Geographic Distribution of U.S. Biotechnology Enterprises, 1976-1989
Population ecology models are elegant in form and adequate in describing aggregate data, but poor in telling stories and predicting the location of growth. Fundamentals models emphasizing the variables central to resource mobilization, such as intellectual human capital, can predict where and when biotechnology enterprises emerge and agglomerate. Density dependence and previous founding dependence proxy many underlying processes; the legitimation and competition interpretation is more conjectural than empirically tenable. We argue and demonstrate for biotechnology that an alternative model based on the fundamentals related to resource reallocation and mobilization provides a stronger frame to explore industry formation. Fundamentals models outperform population ecology models in the estimations, while a combined model driven by fundamentals but incorporating weak population dynamics does best. In repeated dynamic simulations, the population ecology model predictions are essentially uncorrelated with the panel data on biotechnology entry by year and region while the combined model has correlation coefficients averaging above 0.8.