2016 | 3 (53) | 21-31
Article title

Informacja a priori w ocenie jakości modeli TAM na przykładzie platformy Moodle

Title variants
A priori information in the assessment of TAM quality models on the example of Moodle platform
Languages of publication
The article is devoted to the role of a priori information on the basis of a meta- -analysis in the evaluation of the fit and accuracy of Technology Acceptance Model (TAM). This type of model is particularly used to analyze the attitudes and behavior towards new technologies (Moodle platform). In model construction three approaches are compared: structural model with the latent variables (SEM), Bayesian SEM with informative priors based on metanalysis. The aim of the paper is to assess the role of information a priori (subjective knowledge of the researcher and the results of past studies) to assess the stability of the model parameters and fit of the model. Use of information about the prior distributions of parameters and values of point estimates allows to determine the starting points of estimation process and is an essential condition for building a model in bayesian approach. In the process of modeling two models are compared: one built solely on the basis of data (without prior information) and the other that use subjective knowledge of the researcher.
Physical description
  • Chin W.W., Johnson N., Schwarz A., 2008, A fast form approach to measuring technology acceptance and other constructs, MIS Quarterly, vol. 32, no. 4, s. 687-703.
  • Davis F.D., 1989, Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, vol. 13, no. 3, s. 319-340.
  • Davis F.D., Bagozzi R.P., Warshaw P.R., 1989, User acceptance of computer technology: A comparison of two theoretical models, Management Science, vol. 35, no. 8, s. 982-1003.
  • Kaczmarczyk S., 2007, Zastosowanie badań marketingowych, PWE, Warszawa.
  • Kaplan D., Depaoli S., 2012, Bayesian Structural Equation Modeling, [w:] Handbook of Structural Equation Modelling, Hoyle R.H. (red.), NY, Guilford, New York.
  • King W.E., He J., 2006, A meta-analysis of the technology acceptance model, Information and Management, 43, s. 740-755.
  • Lee S.Y., 2007, Structural Equation Modeling. Bayesian Approach, Wiley.
  • Moodle, 2016a, Moodle Statistics, (28.06.2016).
  • Moodle, 2016b, Philosophy, (28.06.2016).
  • Rossi P., Allenby G., McCulloch R., 2005, Bayesian Statistics and Marketing, Wiley.
  • Sagan A., 2010, Bayesowska rewolucja w badaniach marketingowych ze zmiennymi ukrytymi − porównanie podejść, [w:] Marketing. Rozwój działań, Dąbrowski D. (red.), Politechnika Gdańska.
  • Sagan A., Grabowski M., 2015, TAM Model as an Assessment Method for Moodle e-Learning Platform, [w:] IT for Practice 2015, Ministr J. (red.), Technical University, Ostrava.
  • Sharma R., Yetton P., Crawford J., 2009, Estimating the effect of common method variance: The method–method pair technique with an illustration from TAM research, MIS Quarterly, vol. 33, no. 3, s. 473-490.
  • Van de Schoot R., Kaplan D., Denissen J., Asendorpf J.B., Neyer F.J., van Aken M.A.G., 2014, A gentle introduction to Bayesian analysis: Applications to developmental research, Child Development, 85, s. 842-860.
  • Wu J., Lederer A., 2009, A meta-analysis of the role of environment-based voluntariness in information technology acceptance, MIS Quarterly, vol. 33, no. 2, s. 419-432.
  • Zachowania konsumenta. Koncepcje i badania europejskie, 2001, Lamkin M., Foxall G., van Raaij F., Heilbrun B. (red.), PWN, Warszawa.
Document Type
Publication order reference
YADDA identifier
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.