Assessing Data Sharing's Model Fitness Towards Open Data by using Pooled CFA

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.

[1]  Giuseppe Reale Opportunities and Differences of Open Government Data Policies in Europe , 2014 .

[2]  Liang Chen,et al.  Using EPPM to Evaluate the Effectiveness of Fear Appeal Messages Across Different Media Outlets to Increase the Intention of Breast Self-Examination Among Chinese Women , 2018, Health communication.

[3]  I. Ajzen The theory of planned behavior , 1991 .

[4]  Sik Sumaedi,et al.  An analysis of library customer loyalty , 2013 .

[5]  Mustafa Mamat,et al.  The Likert scale analysis using parametric based Structural Equation Modeling (SEM) , 2016 .

[6]  Chun-Liang Chen,et al.  An integrated perspective of TOE framework and innovation diffusion in broadband mobile applications adoption by enterprises , 2017 .

[7]  Shugufta Abrahim,et al.  Structural equation modeling and confirmatory factor analysis of social media use and education , 2019, International Journal of Educational Technology in Higher Education.

[8]  Muhammad Arslan Sarwar,et al.  Impact Of High Involvement Work Practices On Employee Performances In Health Sector, Pakistan , 2020 .

[9]  Abdul Khader Jilani Saudagar,et al.  Measuring the Data Openness for the Open Data in Saudi Arabia e-Government – A Case Study , 2016 .

[10]  Ana Sofia Figueiredo,et al.  Data Sharing: Convert Challenges into Opportunities , 2017, Front. Public Health.

[11]  Milena Krumova,et al.  Higher Education 2.0 and Open Data: a Framework for University Openness and Co-creation Performance , 2017, ICEGOV.

[12]  M. Subandi,et al.  International Journal of Asian Social Science , 2020 .

[13]  C. Stein,et al.  Structural equation modeling. , 2012, Methods in molecular biology.

[14]  R. Walker ANOTHER ROUND OF GLOBALIZATION IN SAN FRANCISCO , 1996 .

[15]  Asyraf Afthanorhan,et al.  An evaluation of measurement model for medical tourism research: the confirmatory factor analysis approach. , 2015 .