Open Access
Issue
E3S Web Conf.
Volume 90, 2019
7th Conference on Emerging Energy and Process Technology (CONCEPT 2018)
Article Number 03004
Number of page(s) 6
Section Safety
DOI https://doi.org/10.1051/e3sconf/20199003004
Published online 02 April 2019
  1. Segar, H., & Grover, V. (1993). Re-examining perceived ease ofuse measurements and perceived usefulness. Decision Sciences. [Google Scholar]
  2. Joreskog, K. G., & Sorbom, D. (1993). LISREL 8: Structural equation modelling with the SIMPLIS command language. Scientific Software International. [Google Scholar]
  3. Bagozzi, R. P., Yi, Y. & Phillips, L. W. (1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 421–458. [Google Scholar]
  4. Byrne, B. M. (2006). Structural equation modelling with EQS: Basic concepts, applications, and programming (2nd ed.). Structural Equation Modelling with EQS: Basic Concepts, Applications, and Programming (2nd Ed.). [Google Scholar]
  5. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis. [Google Scholar]
  6. Mohammad, W.A. & afthanorhan, W. (2014). International journal of asian social science pooled confirmatoryfactor using structural equation modeling on volunteerism program: a step by step approach Sabri Ahmad Ibrahim Mamat contribution/originality. [Google Scholar]
  7. Ahmad, S., Nur, N., Zulkurnain, A. & Khairushalimi, F. I. (2016). Assessing the Fitness of a Measurement Model Using Confirmatory Factor Analysis (CFA), 17(1), 159–168. [Google Scholar]
  8. Fornell, C. & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research [Google Scholar]
  9. Zainudin, A. (2012). Structural equation modeling using AMOS graphic. Shah Alam: Universiti Teknologi MARA Publication Centre (UPENA). [Google Scholar]
  10. Sekaran, U., & Bougie, R. (2010). Theoretical framework in theoretical framework and hypothesis development. Research Methods for Business: A Skill Building Approach, 80. [Google Scholar]
  11. Cronbach, L. J., & Furby, L. (1970). How we should measure “change”: Or should we? Psychological Bulletin, 74(1) [Google Scholar]
  12. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2). [Google Scholar]
  13. Kothari, C. R. (2004). Research methodology: Methods and techniques. New Age International. [Google Scholar]
  14. Colton, D. & Covert, R. W. (2007). Designing and constructing instruments for social research and evaluation. John Wiley & Sons. [Google Scholar]
  15. Nunnally, J. C., & Bernstein, I. H. (1967). Psychometric theory (Vol. 226). McGraw-Hill New York. [Google Scholar]
  16. Krejcie, R. V, & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. [Google Scholar]
  17. Hair, Joseph F.; Anderson, Ronald L.; Tatham, Anderson y Black, W. (1998). Multivariate Data Analysis [Google Scholar]

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