{"title":"熵、异质性及其对技术进步的影响","authors":"Wonchang Hur","doi":"10.1016/j.joi.2024.101506","DOIUrl":null,"url":null,"abstract":"<div><p>This study seeks to determine whether the entropy of patent assignees and the heterogeneity of patented technology within a technology domain positively contribute to the domain's influence on others. This question is motivated by the diversity-performance debates that have been explored across diverse disciplines. Three entropy indices are considered: Shannon, Herfindahl, and Lorenz indices. In addition, the semantic heterogeneity index is developed by employing a pre-trained deep neural network for word embedding. This study investigates about 2 million patents from 1976 to 2021 in the eight Cooperative Patent Classification (CPC) sections that constitute the entire patent landscape. The major findings are two folds. First, the semantic heterogeneity of knowledge created within a technology domain has a positive impact on its influence on others. Second, a negative impact can be exerted on a domain's influence, as the entropy of inventing entities increases. This suggests that a technology domain tends to be more influential when inventions are concentrated among a few prolific entities rather than being distributed across small entities.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Entropy, heterogeneity, and their impact on technology progress\",\"authors\":\"Wonchang Hur\",\"doi\":\"10.1016/j.joi.2024.101506\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study seeks to determine whether the entropy of patent assignees and the heterogeneity of patented technology within a technology domain positively contribute to the domain's influence on others. This question is motivated by the diversity-performance debates that have been explored across diverse disciplines. Three entropy indices are considered: Shannon, Herfindahl, and Lorenz indices. In addition, the semantic heterogeneity index is developed by employing a pre-trained deep neural network for word embedding. This study investigates about 2 million patents from 1976 to 2021 in the eight Cooperative Patent Classification (CPC) sections that constitute the entire patent landscape. The major findings are two folds. First, the semantic heterogeneity of knowledge created within a technology domain has a positive impact on its influence on others. Second, a negative impact can be exerted on a domain's influence, as the entropy of inventing entities increases. This suggests that a technology domain tends to be more influential when inventions are concentrated among a few prolific entities rather than being distributed across small entities.</p></div>\",\"PeriodicalId\":48662,\"journal\":{\"name\":\"Journal of Informetrics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Informetrics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1751157724000191\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Informetrics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1751157724000191","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Entropy, heterogeneity, and their impact on technology progress
This study seeks to determine whether the entropy of patent assignees and the heterogeneity of patented technology within a technology domain positively contribute to the domain's influence on others. This question is motivated by the diversity-performance debates that have been explored across diverse disciplines. Three entropy indices are considered: Shannon, Herfindahl, and Lorenz indices. In addition, the semantic heterogeneity index is developed by employing a pre-trained deep neural network for word embedding. This study investigates about 2 million patents from 1976 to 2021 in the eight Cooperative Patent Classification (CPC) sections that constitute the entire patent landscape. The major findings are two folds. First, the semantic heterogeneity of knowledge created within a technology domain has a positive impact on its influence on others. Second, a negative impact can be exerted on a domain's influence, as the entropy of inventing entities increases. This suggests that a technology domain tends to be more influential when inventions are concentrated among a few prolific entities rather than being distributed across small entities.
期刊介绍:
Journal of Informetrics (JOI) publishes rigorous high-quality research on quantitative aspects of information science. The main focus of the journal is on topics in bibliometrics, scientometrics, webometrics, patentometrics, altmetrics and research evaluation. Contributions studying informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, economics and econometrics, and network science, are especially encouraged. JOI publishes both theoretical and empirical work. In general, case studies, for instance a bibliometric analysis focusing on a specific research field or a specific country, are not considered suitable for publication in JOI, unless they contain innovative methodological elements.