Bengkel smartPLS 2011

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Adi Ali

Bengkel smartp

Educação Tecnologia

Introduction to SmartPLS By: Azwadi Ali Department of Accounting and Finance, Faculty of Management and Economics, Universiti Malaysia Terengganu. FPE, UMT. 23 December 2010.

Introduction to SmartPLS ,[object Object],[object Object],[object Object],[object Object],[object Object]

Structural Equation Modeling (SEM) ,[object Object],[object Object]

Structural Equation Modeling (SEM) ,[object Object]

Latent Constructs (variables) ,[object Object],[object Object],[object Object],[object Object],[object Object]

Structural Model ,[object Object],[object Object],[object Object],[object Object],[object Object]

Structural Model ,[object Object],[object Object],[object Object],[object Object]

Measurement Model ,[object Object],[object Object],[object Object],[object Object]

Reflective vs Formative ,[object Object]

Reflective vs Formative Example: Computer Self-Efficacy Reflective – I am capable at performing tasks on my computer. I feel confident in my ability to perform computer-related tasks. Formative – I am confident at my ability to perform tasks in MS Word. I am skillful at using Excel. Example: System Quality Reflective – Overall, I would rate the system quality of the system highly. The quality of the system is appropriate for my needs. Formative – Reliability, Ease of Use, Complexity, Accessibility, Responsiveness

Partial Least Squares ,[object Object],[object Object],[object Object],[object Object],[object Object]

Using SmartPLS ,[object Object],[object Object],[object Object],[object Object],[object Object]

Research hypotheses H1: ‘Information usefulness’ is positively related to ‘attitude towards IR Websites’ H2: ‘Usability’ is positively related to ‘attitude towards IR Websites’ H3: ‘Attractiveness’ is positively related to ‘attitude towards IR Websites’ H4: ‘Attitude towards IR Websites’ is positively related to ‘intention to re-use IR Website’

Model Fit Construct Structural Model Model Quality (H 2 ) (Q 2 ) INT 0.408993 a (0.828074) b 0.336686 c 0.828182 d (0.332465) e AT_ST 0.784225 (0.685600) 0.271908 0.685665 (0.532704) IU 0.995844 (0.594612) 0.456906 0.602816 (0.603847) COG 0.938884 (0.790545) 0.742018 0.790584 (0.737104) AFT 0.678615 (0.847454) 0.570006 0.847526 (0.565652) IQ - (0.687052) - 0.705153 (-) CRD - (0.558615) - 0.564710 (-) USB - (0.789696) - 0.789634 (-) ATR - (0.812278) - 0.812301 (-) Average 0.761312 0.714539 f 0.475505 0.736286 (0.554354) GoF g 0.737555

A simple application of SmartPLS ,[object Object],[object Object],[object Object]

Measurement model - convergent ,[object Object],[object Object],[object Object],[object Object],[object Object]

Measurement model - discriminant ,[object Object],[object Object],[object Object],[object Object]

Structural model ,[object Object],[object Object],Goodness of Fit ,[object Object],[object Object],[object Object]

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Bengkel smartPLS 2011

1. Introduction to SmartPLS By: Azwadi Ali Department of Accounting and Finance, Faculty of Management and Economics, Universiti Malaysia Terengganu. FPE, UMT. 23 December 2010.

10.

11.

12. Reflective vs Formative Example: Computer Self-Efficacy Reflective – I am capable at performing tasks on my computer. I feel confident in my ability to perform computer-related tasks. Formative – I am confident at my ability to perform tasks in MS Word. I am skillful at using Excel. Example: System Quality Reflective – Overall, I would rate the system quality of the system highly. The quality of the system is appropriate for my needs. Formative – Reliability, Ease of Use, Complexity, Accessibility, Responsiveness

13.

14. Morning Break (rilek dulu)

15.

16. Research Model

17. Research hypotheses H1: ‘Information usefulness’ is positively related to ‘attitude towards IR Websites’ H2: ‘Usability’ is positively related to ‘attitude towards IR Websites’ H3: ‘Attractiveness’ is positively related to ‘attitude towards IR Websites’ H4: ‘Attitude towards IR Websites’ is positively related to ‘intention to re-use IR Website’

18. Research Model with Indicators

19. Sample Results

20. Model Fit Construct Structural Model Model Quality (H 2 ) (Q 2 ) INT 0.408993 a (0.828074) b 0.336686 c 0.828182 d (0.332465) e AT_ST 0.784225 (0.685600) 0.271908 0.685665 (0.532704) IU 0.995844 (0.594612) 0.456906 0.602816 (0.603847) COG 0.938884 (0.790545) 0.742018 0.790584 (0.737104) AFT 0.678615 (0.847454) 0.570006 0.847526 (0.565652) IQ - (0.687052) - 0.705153 (-) CRD - (0.558615) - 0.564710 (-) USB - (0.789696) - 0.789634 (-) ATR - (0.812278) - 0.812301 (-) Average 0.761312 0.714539 f 0.475505 0.736286 (0.554354) GoF g 0.737555

21.

22. Lunch Break

23.

24.

25.

26.

27. End of Workshop

Bengkel smartPLS 2011

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