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Perbandingan Metode Pengujian Teori TAM Pada Penerimaan Teknologi E-Money di Pontianak

*Irawan Wingdes  -  STMIK Pontianak, Indonesia
Sandy Kosasi  -  STMIK Pontianak, Indonesia
I Dewa Ayu Eka Yuliani  -  STMIK Pontianak, Indonesia
Open Access Copyright (c) 2021 JSINBIS (Jurnal Sistem Informasi Bisnis)

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Abstract

As a researcher, one could analyze Technology Acceptance Model (TAM) by utilizing several methods. Such methods are summated scales regression, factor analysis score regression, covariance-based SEM, and PLS-based SEM. However, there exists less effort to compare the difference in estimates of these methods in a single dataset. The differing estimates could therefore lead to type I statistical errors. This research purpose was to compare these methods objectively with a single dataset. The dataset tested was derived from e-money research in Pontianak, with 280 data collected at refueling stations during May, June, July 2020. This research contributes to proofing how method choices will produce a differing interpretation even though tested on the same dataset. Summated scale regression and PLS-based SEM produced similar estimation results but differed from factor analysis score regression and covariance-based SEM. Further testing implies that the different estimates are due to the elimination of indicators, which is method-specific. Therefore, method justification, completeness of research report, and research context are crucial for accounting limitation of the method chosen. PLS-based SEM was a suitable method for data utilized with 50,3% variability in usefulness, 58% variability in intention to use is accounted for from the research model.  

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Keywords: TAM; Regression; Factor Analysis; SEM.

Article Metrics:

  1. Baptista, G., Oliveira, T., 2015. Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior 50, 418–430
  2. Blessing, L. T. M., Chakrabarti, A., 2009. DRM, a design research methodology. New York, Springer
  3. Bollen, K. A., 1989. Structural Equations with Latent Variables. New York, John Wiley & Sons
  4. Carsey, T.M., Harden, J.J., 2014. Monte Carlo Simulation and Resampling Methods for Social Science. New York. Sage
  5. Cash, P., 2020. Where next for design research? Understanding research impact and theory building. Design Studies 68, 113–141
  6. Davis, F.D., Bagozzi, R.P., Warshaw, P.R., 1983. User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982–1003
  7. Dwivedi, Y.K., Rana, N.P., Jeyaraj, A., Clement, M., Williams, M. D., 2019. Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): towards a revised theoretical model. Information Systems Frontiers, 21(3), 719–734
  8. Elsevier, 2020. ScienceDirect Search Keyword Technology Acceptance Model. Website: https://www.sciencedirect.com/search?qs=technology acceptance model, diakses 2 Nov 2020
  9. Gorsuch, R.L., 1983. Factor Analysis. New York. Lawrence Erlbaum Associates
  10. Hair, J.F., 2010. Multivariate data analysis. New York. Prentice Hall
  11. Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., 2014. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). New York. Sage Publishing
  12. Ishak, 2019. Wali Kota Pontianak Edi Kamtono Ingin Cegah Kegaduhan, Isi BBM di SPBU Pontianak Tak Wajib Cashless. Website: https://pontianak.tribunnews.com/2019/09/05/wali-kota-pontianak-edi-kamtono-ingin-cegah-kega duhan-isi-bbm-di-spbu-pontianak-tak-wajib-cash less?page=all, diakses 1 Nov 2020
  13. Kline, R.B., 2011. Principles and Practice of Structural Equation Modeling. In Clinical orthopaedics and related research. New York. The Guilford Press
  14. Lok, C.K., 2015. Adoption of Smart Card-Based E-Payment System for Retailing in Hong Kong Using an Extended Technology Acceptance Model. E-Services Adoption: Processes by Firms in Developing Nations 23B, 255–466
  15. Lowry, P.B., Gaskin, J., 2014. Partial least squares (PLS) structural equation modeling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE Transactions on Professional Communication, 57(2), 123–146
  16. Matsunaga, M., 2011. How to Factor-Analyze Your Data Right : Do’ s , Don’t s , and How-To’ s. International Journal of Psychological Research 3(1), 97–110
  17. Mortimer, G., Neale, L., Hasan, S.F.E., Dunphy, B., 2015. Investigating the factors influencing the adoption of m-banking: a cross cultural study. International Journal of Bank Marketing 33(4), 545–570
  18. Rigdon, E.E., Sarstedt, M., Ringle, C.M., 2017. On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations. Marketing ZFP 39(3), 4–16
  19. RISTEK DIKTI., 2020. Garba Rujukan Digital (GARUDA) Search Keyword Technology Acceptance Model. Website: http://garuda.riste kbrin.go.id /documents?q=technology+accep tance+model+,diakses 1 Nov 2020
  20. Rönkkö, M., McIntosh, C.N., Antonakis, J., Edwards, J.R., 2016. Partial least squares path modeling: Time for some serious second thoughts. Journal of Operations Management, 47, 9–27
  21. Ropovik, I., 2015. A cautionary note on testing latent variable models. Frontiers in Psychology 6, 1–8
  22. Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., Gudergan, S.P. 2016. Estimation issues with PLS and CBSEM: Where the bias lies! Journal of Business Research, 69(10), 3998–4010
  23. Shevlin, M., Miles, J.N.V., Bunting, B.P., 1997. Summated rating scales: A Monte Carlo investigation of the effects of reliability and collinearity in regression models. Personality and Individual Differences, 23(4), 665–676
  24. Syahroni., 2018. Pelayanan E-money di SPBU kota Pontianak Memperlambat Transaksi. Website: http://pontianak.tribunnews.com/2018/01/01/pelayanan-e-money-di-spbu-kota-pontianak-memp erlambat-transaksi, diakses 1 Nov 2020
  25. Tabachnick, B.G., Fidell, L.S., 2013. Using Multivariate Statistics. Boston, Prentice Hall
  26. Tarka, P., 2018. An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences. Quality and Quantity 52(1), 313–354
  27. Tóth-Király, I., Bõthe, B., Rigó, A., Orosz, G., 2017. An illustration of the Exploratory structural equation modeling (ESEM) framework on the passion scale. Frontiers in Psychology 8, 1-15
  28. Velicer, W.F., Jackson, D.N., 1990. Component Analysis versus Common Factor Analysis: Some Issues in Selecting an Appropriate Procedure. Multivariate Behavioral Research 25(1), 1–28
  29. Venkatesh, V., Davis, F.D., 2000. Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204

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