Abstract
This study demonstrates the step-by-step procedure to perform Pooled Confirmatory Factor Analysis (CFA) in the measurement part of Structural Equation Modelling (SEM). CFA is crucial for the SEM measurement model to obtain the acceptable model fit before modeling the structural model. There are two techniques in CFA; individual CFA and Pooled-CFA. Usually, Pooled-CFA is done due to the high number of constructs and items. If the model is too complicated and has so many constructs and items, then it is recommended to perform Pooled-CFA to simplify the model's looks yet easy to understand. The perception of Malaysia Technical University Network (MTUN) academics on data sharing towards open data was analysed by using pooled-CFA. There are three main constructs: data sharing with its 4 sub-constructs; (technological factor, organizational factor, environmental factor, and individual factor), mediator construct (open data licenses), and open data construct was analyzed in this research. Furthermore, second-order constructs' factor loadings towards their corresponding sub-constructs were investigated. This research collected the primary data of 442 respondents using a stratified random sampling technique. This paper will explain the theoretical framework before revealing the results of Pooled-CFA on data sharing towards open data.
Highlights
Open data initiatives have become ubiquitous in every country
In this study, the exact components that form data sharing were investigated through the process of survey distribution to Malaysia Technical University Network (MTUN) academics that were be confirmed through Confirmatory Factor Analysis (CFA)
The investigations were extended to the open data licenses (ODL) construct and MTUN_OD construct
Summary
Open data initiatives have become ubiquitous in every country. According to [1], Malaysia has embarked on the open government data framework by The Malaysian Administrative Modernisation and Management Planning Unit (MAMPU) in the year 2015. In the meantime, [3] has stated that the data producer is reluctant to share data might because it possesses challenges at many levels such as cultural, ethical, financial, and technical. Adding to these challenges, [4] has highlighted that the reluctance of data sharing perhaps due to disinterest from the universities. This study employs quantitative techniques; survey to Malaysia Technical University Network (MTUN) academics. There were 442 feedbacks received and there was a need to perform Confirmatory Factor Analysis (CFA) to confirm the factor that influence MTUN academics on data sharing
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