Arturo Melo, Carolyn L. Beck, J. I. Peña, Philip E. Paré
{"title":"大学知识向地区转移是一个网络传播过程","authors":"Arturo Melo, Carolyn L. Beck, J. I. Peña, Philip E. Paré","doi":"10.1109/SYSENG.2018.8544398","DOIUrl":null,"url":null,"abstract":"In developing countries it is necessary to understand how knowledge transfer (KT) occurs via human capital from universities to regions. This transfer can be viewed as diffusion process and is one essential factor in explaining regional innovation and resulting socioeconomic developments. This phenomenon has been studied at the organizational level, however there are few contributions that consider spreading process models over networks in the macro context. This paper presents a KT model of human capital from university nodes to productive organization nodes for seven Colombian regions, and examines how the proportion of graduates absorbed by each region generates new knowledge products. The phenomenon we consider is based on the susceptible-infected-susceptible (SIS) epidemic process, where the spread parameters are related to the knowledge absorption capacity and the ineffectiveness or unused knowledge of the previous spreading process in the region. In addition, the model tries to explain the dependence of knowledge products (KP) with Science, Technology, Engineering and Math (STEM) graduates and the productive structure complexity. To validate the model, we have used the data of13 consecutive years obtained from the Education Ministry, as well as from the Science and Technology Observatory of Colombia. Our findings reflect that the proposed model explains the KT phenomenon, where each node or region is a heterogeneous node, because they have different absorption and ineffectiveness parameters, as well as, diverse productive structure configurations.","PeriodicalId":192753,"journal":{"name":"2018 IEEE International Systems Engineering Symposium (ISSE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Knowledge Transfer from Universities to Regions as a Network Spreading Process\",\"authors\":\"Arturo Melo, Carolyn L. Beck, J. I. Peña, Philip E. Paré\",\"doi\":\"10.1109/SYSENG.2018.8544398\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In developing countries it is necessary to understand how knowledge transfer (KT) occurs via human capital from universities to regions. This transfer can be viewed as diffusion process and is one essential factor in explaining regional innovation and resulting socioeconomic developments. This phenomenon has been studied at the organizational level, however there are few contributions that consider spreading process models over networks in the macro context. This paper presents a KT model of human capital from university nodes to productive organization nodes for seven Colombian regions, and examines how the proportion of graduates absorbed by each region generates new knowledge products. The phenomenon we consider is based on the susceptible-infected-susceptible (SIS) epidemic process, where the spread parameters are related to the knowledge absorption capacity and the ineffectiveness or unused knowledge of the previous spreading process in the region. In addition, the model tries to explain the dependence of knowledge products (KP) with Science, Technology, Engineering and Math (STEM) graduates and the productive structure complexity. To validate the model, we have used the data of13 consecutive years obtained from the Education Ministry, as well as from the Science and Technology Observatory of Colombia. Our findings reflect that the proposed model explains the KT phenomenon, where each node or region is a heterogeneous node, because they have different absorption and ineffectiveness parameters, as well as, diverse productive structure configurations.\",\"PeriodicalId\":192753,\"journal\":{\"name\":\"2018 IEEE International Systems Engineering Symposium (ISSE)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Systems Engineering Symposium (ISSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SYSENG.2018.8544398\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Systems Engineering Symposium (ISSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYSENG.2018.8544398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Knowledge Transfer from Universities to Regions as a Network Spreading Process
In developing countries it is necessary to understand how knowledge transfer (KT) occurs via human capital from universities to regions. This transfer can be viewed as diffusion process and is one essential factor in explaining regional innovation and resulting socioeconomic developments. This phenomenon has been studied at the organizational level, however there are few contributions that consider spreading process models over networks in the macro context. This paper presents a KT model of human capital from university nodes to productive organization nodes for seven Colombian regions, and examines how the proportion of graduates absorbed by each region generates new knowledge products. The phenomenon we consider is based on the susceptible-infected-susceptible (SIS) epidemic process, where the spread parameters are related to the knowledge absorption capacity and the ineffectiveness or unused knowledge of the previous spreading process in the region. In addition, the model tries to explain the dependence of knowledge products (KP) with Science, Technology, Engineering and Math (STEM) graduates and the productive structure complexity. To validate the model, we have used the data of13 consecutive years obtained from the Education Ministry, as well as from the Science and Technology Observatory of Colombia. Our findings reflect that the proposed model explains the KT phenomenon, where each node or region is a heterogeneous node, because they have different absorption and ineffectiveness parameters, as well as, diverse productive structure configurations.