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Structural Equation Modelling based data fusion for technology forecasting: A National Research and Education Network example

机译:基于结构方程模型的技术预测数据融合:一个国家研究和教育网络示例

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This paper presents an example model instantiation of Staphorst, Pretorius and Pretorius' framework for Structural Equation Modelling (SEM) based Data Fusion (DF) for Technology Forecasting (TF) in the National Research and Education Network (NREN) technology domain. The paper's example NREN model instantiation is constructed through deductive reasoning from knowledge gained during action research in the South African National Research Network (SANReN), as well as secondary data from TERENA's NREN compendiums for global NREN infrastructure and services trends. A variety of technology related measurements are employed in the example NREN model instantiation as indicators for technology related model constructs, such as the level of core network traffic in an NREN. Indicators for context related model constructs include, amongst others, the range of institutions an NREN is mandated to connect. For confirmatory purposes the secondary data published by TERENA in its yearly NREN compendium series is then used in the Partial Least Squares (PLS) regression analysis to determine the indicator loadings and path coefficients of the example NREN model instantiation. A reliability and validity analysis of the example NREN model instantiation is also considered.
机译:本文介绍了在国家研究与教育网络(NREN)技术领域中基于结构方程模型(SEM)的数据融合(DF)技术预测(TF)的Staphorst,Pretorius和Pretorius框架的示例模型实例。本文的示例NREN模型实例化是通过在南非国家研究网络(SANReN)的行动研究过程中获得的知识进行演绎推理,以及从TERENA的NREN纲要中获取的有关全球NREN基础设施和服务趋势的辅助数据而构造的。在示例NREN模型实例化中采用了各种与技术相关的度量作为与技术相关的模型构造的指标,例如NREN中核心网络流量的水平。与情境相关的模型构建的指标包括(除其他外)NREN被要求联系的机构范围。为了进行验证,然后将TERENA在其年度NREN汇编系列中发布的辅助数据用于偏最小二乘(PLS)回归分析中,以确定示例NREN模型实例化的指标负载和路径系数。还考虑了示例NREN模型实例的可靠性和有效性分析。

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