Technological Acceptance Model (TAM) Terhadap Adopsi Aplikasi Trading Cryptocurrency Studi Kasus: Indodax Trading Platform

Audi Ramadhan, Chandra Indira Septiarani, Faisal Dias, Deden Yoga Pratama

Sari


Aplikasi trading cryptocurrency merupakan sebuah aplikasi yang relatif baru yang ditandai dengan munculnya banyak cryptocurrency seperti Bitcoin, Ethereum dan lain sebagainya. Oleh sebab itu, analisis penerimaan teknologi pada aplikasi tersebut sangat penting untuk dikaji lebih dalam. Penelitian ini bertujuan untuk menganalisis dan mengukur penerimaan aplikasi trading cryptocurrency yaitu Indodax Trading Platform dengan menggunakan Technology Acceptance Model (TAM) yang diintegrasikan dengan faktor resiko dan kepercayaan. Penelitian ini merupakan penelitian kuantitatif asosiatif dengan menggunakan kuesioner untuk mendapatkan data primer. Sampel yang digunakan pada penelitian ini sebesar 134 dengan menggunakan teknil analisis Semi Equation Model – Partial Least Square (SEM-PLS). Hasil dari penelitian ini yaitu adanya pengaruh dari perceived usefulness dan trust terhadap penggunaan aplikasi trading cryptocurrency. Sedangkan resiko dan perceived ease of use tidak berpengaruh terhadap penggunaan aplikasi trading cryptocurrency.

Teks Lengkap:

PDF

Referensi


Ayo, C. K., Mbarika, V. W., & Oni, A. A. (2015). The Influence of Trust and Risk on Intention to Use E-Democracy in Nigeria. Mediterranean Journal of Social Sciences, 6(6), 477–486. https://doi.org/10.5901/mjss.2015.v6n6s1p477

Belkhamza, Z., & Wafa, S. A. (2009). The Effect of Perceived Risk on the Intention to Use E-commerce: The Case of Algeria. Journal of Internet Banking and Commerce, 14(1).

Chao, C. (2019). Factors Determining the Behavioral Intention to Use Mobile Learning : An Application and Extension of the UTAUT Model. Front. Psychol, 10, 1652. https://doi.org/10.3389/fpsyg.2019.01652

Chen, J. K. (2018). The influence of behavioural intention on third-party e-commerce payment. South African Journal of Economic and Management Sciences, 21(1), 1–9.

Chong, A. Y. (2013). A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption. Expert Systems With Applications, 40(4), 1240–1247. https://doi.org/10.1016/j.eswa.2012.08.067

Correa, P. R., Grandon, E. E., Santana, M. R., & Órdenes, L. B. (2019). Explaining the Use of Social Network Sites as Seen by Older Adults : The Enjoyment Component of a Hedonic Information System. International Journal of Environmental Research and Public Health, 16(10), 1673.

Davis, F. D. (1986). A TECHNOLOGY ACCEPTANCE MODEL FOR EMPIRICALLY TESTING NEW END-USER INFORMATION SYSTEMS: THEORY AND RESULTS.

Davis, F. D. (1989). Perceived Usefulness , Perceived Ease of Use , and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982

Fayad, R., & Paper, D. (2015). The Technology Acceptance Model E-Commerce Extension : A Conceptual Framework. Procedia Economics and Finance, 26, 1000–1006. https://doi.org/10.1016/S2212-5671(15)00922-3

Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50.

Gefen, D., Karahana, E., & Starub, D. W. (2003). TRUST AND TAM IN ONLINE SHOPPING: AN INTEGRATED MODEL. MIS Quarterly, 27(1), 51–90.

Girish, H. (1994). A replication of perceived usefulness and perceived ease of. Decision Sciences, 25(5/6), 863–874.

Harryanto, Muchran, M., & Ahmar, A. S. (2018). Application of TAM model to the use of information technology. International Journal of Engineering & Technology, 7(2.9), 37–40.

Hartono, E., Holsapple, C. W., Kim, K., Na, K., & Simpson, J. T. (2014). Measuring perceived security in B2C electronic commerce website usage : A respeci fi cation and validation. Decision Support Systems, 62, 11–21. https://doi.org/10.1016/j.dss.2014.02.006

Hu, P. J., Chau, P. Y. K., Sheng, O. R. L., & Tam, K. Y. (1999). The Technology Examining Acceptance Model Using Physician of Acceptance Telemedicine Technology. Journal of Management Information Systems, 16(2), 91–112.

Jeon, E., & Park, H. (2015). Factors Affecting Acceptance of Smartphone Application for Management of Obesity. Healthcare Infotmatics Research, 21(2), 74–82.

Jogiyanto, H., & Abdillah, W. (2009). Konsep dan Aplikasi PLS (Partial Least Square) untuk Penelitian Empiris (I). Yogyakarta: BPFE.

Jubran, D., Djamhuri, A., & Baridwan, Z. (2016). THE INTENTION TO USE E-GOVERNMENT SYSTEM (E-EXPORTING) IN SHIPPING AND EXPORTING COMPANY IN LIBYA. The International Journal of Accounting and Business Society, 24(2), 13–34.

Juniwati. (2014). Influence of Perceived Usefulness , Ease of Use , Risk on Attitude and Intention to Shop Online. European Journal of Business and Management, 6(27), 218–229.

Lee, M. (2009). Predicting and explaining the adoption of online trading : An empirical study in Taiwan. Decision Support Systems, 47(2), 133–142. https://doi.org/10.1016/j.dss.2009.02.003

Liao, C., Lin, H., & Liu, Y. (2010). Predicting the Use of Pirated Software : A Contingency Model Integrating Perceived Risk with the Theory of Planned Behavior. Journal of Business Ethics, 91, 237–252. https://doi.org/10.1007/s10551-009-0081-5

Lin, J., Wang, B., Wang, N., & Lu, Y. (2014). Understanding the evolution of consumer trust in mobile commerce: a longitudinal study. Information Technology and Management, 15(1), 37–49. https://doi.org/10.1007/s10799-013-0172-y

Littler, D., & Melanthiou, D. (2006). Consumer perceptions of risk and uncertainty and the implications for behaviour towards innovative retail services: The case of Internet Banking. Journal of Retailing and Consumer Services, 13(6), 431–443. https://doi.org/10.1016/j.jretconser.2006.02.006

Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). AN INTEGRATIVE MODEL OF ORGANIZATIONAL TRUST. Academy of Management Review, 20(3), 709–734.

Neuman, W. L. (2011). Social Research Methods: Qualitative and Quantitative Approaches (seventh). Edinburgh: Pearson Education Limited.

Paqih, K. M. S. (2011). Integrating Perceived Risk and Trust with Technology Acceptance Model : An Empirical Assessment of Customers ’ Acceptance of Online Shopping in Jordan. 2011 International Conference on Research and Innovation in Information Systems, 1–5. IEEE.

Pavlou, P. A. (2003). Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model. International Journal of Electronic Commerce, 7(3), 69–103.

Phatthana, W., & Mat, N. K. N. (2011). The Application of Technology Acceptance Model ( TAM ) on health tourism e- purchase intention predictors in Thailand. 2010 International Conference on Business and Economics Research, 1, 196–199.

Rana, N., Dwivedi, Y., Percy, N., & Williams, M. (2014). Measuring Intention To Use And Satisfaction With Electronic District System : Validation Of A Combined Model Of IS Success. UK Academy for Information Systems Conference Proceedings.

Roy, S. (2017). APP ADOPTION AND SWITCHING BEHAVIOR: APPLYING THE EXTENDED TAM IN SMARTPHONE APP USAGE. Journal of Information Systems and Technology Management, 14(2), 239–261. https://doi.org/10.4301/S1807-17752017000200006

Sharma, S. K., & Sharma, M. (2019). Examining the role of trust and quality dimensions in the actual usage of mobile banking services : An empirical investigation. International Journal of Information Management, 44, 65–75.

Siregar, S. (2013). Metode Penelitian Kuantitatif: Dilengkapi dengan Perbandingan Perhitungan Manual dan SPSS. Jakarta: Kencana Prenada Media Group.

Syahrum, & Salim. (2012). METODOLOGI PENELITIAN KUANTITATIF (p. 176). p. 176.

Thakur, K. K., & Banik, G. G. (2018). Cryptocurrency : Its Risks And Gains And The Way Ahead. IOSR Journal of Economics and Finance, 9(2), 38–42. https://doi.org/10.9790/5933-0902013842

Venkatesh, V., Aloysius, J., Hoehle, H., & Burton, S. (2017). Design and Evaluation of Auto-ID Enabled Shopping Assistance Artifacts: Two Retail Store Laboratory Experiments. MIS Quarterly, 41(1), 83–113. Retrieved from http://www.vvenkatesh.com/wp-content/uploads/dlm_uploads/2015/11/Venkatesh-et-al.-MISQ-20172.pdf

Weng, F., Yang, R., Ho, H., & Su, H. (2018). A TAM-Based Study of the Attitude towards Use Intention of Multimedia among School Teachers. Applied System Innovation, 1(3), 36. https://doi.org/10.3390/asi1030036

Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232. https://doi.org/10.1016/j.chb.2016.10.028

Xie, Q., Song, W., Peng, X., & Shabbir, M. (2017). Predictors for e-government adoption : integrating TAM , TPB , trust and perceived risk. The Electronic Library, 35(1), 2–20. https://doi.org/10.1108/EL-08-2015-0141




DOI: https://doi.org/10.31294/ijcit.v4i2.6730

##submission.copyrightStatement##

##submission.license.cc.by-sa4.footer##

P-ISSN: 2527-449X E-ISSN: 2549-7421
Statistik Pengunjung Jurnal IJCIT
 

Dipublikasikan oleh LPPM Universitas Bina Sarana Informatika

Jl. Kramat Raya No.98, Kwitang, Kec. Senen, Kota Jakarta Pusat, DKI Jakarta 10450
Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License