{"title":"科技孵化器失效的原因——大数据背景下科技孵化平台失效机理与实证研究","authors":"Lv Bo, Zhi Yechao, Guo Qiaoling","doi":"10.11648/J.AJMSE.20190404.12","DOIUrl":null,"url":null,"abstract":"In recent years, the technology incubation platform is facing a new ecological environment. The background of big data brought by cloud computing and big data has increased the random disturbance effect on technology incubation platform. The failure of some technology incubation platforms has caused academic controversies. This paper conducts theoretical research and empirical test for these academic controversies, and the empirical conclusions of this paper provide a more comprehensive and reasonable explanation for current academic controversies. In order to describe the failure phenomena of technology incubation platform, this paper innovatively proposes the concept of failure effects and failure coefficients, constructs failure effects model and deduces the failure mechanism formula by using the principle of Stochastic Frontier Analysis (SFA). On the basis of literature research, combined with the background characteristics of the big data, 4 dependent variables and 14 random influence variables were selected, and the Chinese technology incubator platform was taken as an example to empirically analyze failure effects model. The paper finds that the independent variables can be divided into three categories: positive, negative and partially irrelevant. When corresponding to negatively correlate variables or unrelated variables, dependent variables will show the failure phenomenon, that is, partial failure of technology incubation platform.","PeriodicalId":438321,"journal":{"name":"American Journal of Management Science and Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reasons for the Failure of Technology Incubator - Failure Mechanism and Empirical Study of Technology Incubation Platform Under the Background of Big Data\",\"authors\":\"Lv Bo, Zhi Yechao, Guo Qiaoling\",\"doi\":\"10.11648/J.AJMSE.20190404.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, the technology incubation platform is facing a new ecological environment. The background of big data brought by cloud computing and big data has increased the random disturbance effect on technology incubation platform. The failure of some technology incubation platforms has caused academic controversies. This paper conducts theoretical research and empirical test for these academic controversies, and the empirical conclusions of this paper provide a more comprehensive and reasonable explanation for current academic controversies. In order to describe the failure phenomena of technology incubation platform, this paper innovatively proposes the concept of failure effects and failure coefficients, constructs failure effects model and deduces the failure mechanism formula by using the principle of Stochastic Frontier Analysis (SFA). On the basis of literature research, combined with the background characteristics of the big data, 4 dependent variables and 14 random influence variables were selected, and the Chinese technology incubator platform was taken as an example to empirically analyze failure effects model. The paper finds that the independent variables can be divided into three categories: positive, negative and partially irrelevant. When corresponding to negatively correlate variables or unrelated variables, dependent variables will show the failure phenomenon, that is, partial failure of technology incubation platform.\",\"PeriodicalId\":438321,\"journal\":{\"name\":\"American Journal of Management Science and Engineering\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Management Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11648/J.AJMSE.20190404.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Management Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/J.AJMSE.20190404.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reasons for the Failure of Technology Incubator - Failure Mechanism and Empirical Study of Technology Incubation Platform Under the Background of Big Data
In recent years, the technology incubation platform is facing a new ecological environment. The background of big data brought by cloud computing and big data has increased the random disturbance effect on technology incubation platform. The failure of some technology incubation platforms has caused academic controversies. This paper conducts theoretical research and empirical test for these academic controversies, and the empirical conclusions of this paper provide a more comprehensive and reasonable explanation for current academic controversies. In order to describe the failure phenomena of technology incubation platform, this paper innovatively proposes the concept of failure effects and failure coefficients, constructs failure effects model and deduces the failure mechanism formula by using the principle of Stochastic Frontier Analysis (SFA). On the basis of literature research, combined with the background characteristics of the big data, 4 dependent variables and 14 random influence variables were selected, and the Chinese technology incubator platform was taken as an example to empirically analyze failure effects model. The paper finds that the independent variables can be divided into three categories: positive, negative and partially irrelevant. When corresponding to negatively correlate variables or unrelated variables, dependent variables will show the failure phenomenon, that is, partial failure of technology incubation platform.