Dampak Kemudahan dan Risiko Sistem Pembayaran QR Code: Technology Acceptance Model (TAM) Extension

Ayatulloh Michael Musyaffi, Kayati Kayati

Abstract


Abstract. Mobile Payment has developed quickly and easily. One of them by using a QR Code by scanning the Bar Code through the Smartphone camera. Unfortunately, there is inherent risk especially in the aspect of theft of financial and non-financial data. Therefore, this study aims to examine user acceptance in terms of the ease and risk of QR Code Payments. The target of respondents in this study were all users of Payment methods using QR Codes in Indonesia with 100 respondents with a simple random sampling method through online distribution and structured interviews. The method used in this study used the Structural Equation Model (SEM) - Partial Least Square (PLS). The findings in this research show that there is a contribution to the Technology Acceptance Model (TAM) model, especially Perceived Ease of use factor that further strengthens the acceptance of Pay by QR. While risk perception does not have a significant impact on intention to use the Pay by QR system.

 

Keywords: Behavioural Intention; Pay by QR; Perceived Ease of use; Perceived Risk; TAM.

 

Abstrak. Model pembayaran mobile telah berkembang secara signifikan dan semakin mudah. Salah satunya adalah pembayaran dengan menggunakan kode QR dengan men-scan kode QR melalui kamera Smartphone. Sayangnya dibalik kemudahan penggunaan pembayaran QR, terdapat resiko yang melekat terutama dalam aspek pencurian data keuangan maupun non keuangan. Atas dasar inilah penelitian ini diadakan dengan tujuan untuk menguji penerimaan pengguna yang dilihat dari sisi kemudahan dan resiko pembayaran kode QR. Target responden riset ini adalah seluruh pengguna metode pembayaran menggunakan kode QR di Indonesia dengan jumlah responden sebayak 100 dengan meteode simple random sampling melalui penyebaran online dan wawancara secara terstruktur. Metode yang digunakan dalam penelitian ini menggunakan Struktural Equation Model (SEM) – Partial Least Square (PLS). Temuan dalam riset menunjukan adanya kontribusi terhadap model Technology Acceptance Model (TAM) terutama faktor kemudahan yang semakin memperkuat penerimaan penggunaan Pay by QR. Sementara persepsi resiko tidak memiliki dampak yang signifikan terhadap niat menggunakan sistem Pay by QR.

 

Katakunci: Behavioural Intention; Pay by QR: Mobile Payment; Persepsi Kemudahan; Persepsi Resiko; TAM;


Keywords


Behavioural Intention; Pay by QR; Perceived Ease of use; Perceived Risk; TAM.

Full Text:

PDF

References


Agusta, J., & Hutabarat, K. (2018). Mobile Payment In Indonesia: Race to Big Data Domination. Jakarta.

Alalwan, A. A., Dwivedi, Y. K., Rana, N. P. P., & Williams, M. D. (2016). Consumer adoption of mobile banking in Jordan. Journal of Enterprise Information Management, 29(1), 118–139. https://doi.org/10.1108/JEIM-04-2015-0035

Balouchi, M., Aziz, Y. A., Hasangholipour, T., Khanlari, A., Rahman, A. A., Raja, R. N., & Yusof. (2017). Explaining and predicting online tourists’ behavioral intention in accepting consumer generated contents. Journal of Hospitality and Tourism Technology.

Ben Mansour, K. (2016). An analysis of business’ acceptance of internet banking: an integration of e-trust to the TAM. Journal of Business & Industrial Marketing, 31(8), 982–994. https://doi.org/10.1108/JBIM-10-2016-271

Boonsiritomachai, W., & Pitchayadejanant, K. (2017). Determinants affecting mobile banking adoption by generation Y based on the Unified Theory of Acceptance and Use of Technology Model modified by the Technology Acceptance Model concept. Kasetsart Journal of Social Sciences. https://doi.org/10.1016/J.KJSS.2017.10.005

Chauhan, V., Yadav, R., & Choudhary, V. (2019). Analyzing the impact of consumer innovativeness and perceived risk in internet banking adoption: A study of Indian consumers. International Journal of Bank Marketing, 37(1), 323–339.

Cheng, T. C. E., Lam, D. Y. C., & Yeung, A. C. L. (2006). Adoption of Internet Banking: An Empirical Study in Hong Kong. Decision Support Systems, 42(3), 1558–1572. https://doi.org/10.1016/j.dss.2006.01.002

Chitungo, S., & Munongo, S. (2013). Extending the Technology Acceptance Model to Mobile Banking Adoption in Rural Zimbabwe. Journal of Business Administration and Education, 3(1), 51–79.

Damghanian, H., Zarei, A., & Siahsarani Kojuri, M. . (2016). Impact of perceived security on trust, perceived risk, and acceptance of online banking in Iran. Journal of Internet Commerce, 15(3), 214–238.

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

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, 22(14), 1111–1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x

Gasson, S. (1999). The Reality Of User-Centered Design. Journal of End User Computing, (4), 3–13. https://doi.org/10.4018/joeuc.1999100101

Gerrard, P., Cunningham, J. ., & Devlin, J. . (2006). Why consumers are not using internet banking. Journal of Services Marketing, 20(3), 160–168.

Ghozali, I. (2013). Partial Least Square. Universitas Diponegoro.

Gubernur bank Indonesia, G. ubernur B. Peratura Bank Indonesia tentang Uang Elektronik, Pub. L. No. 20/6/PBI/2018, 35 (2018). Indonesia.

Hair, J. F., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128

Hu, J., & Zhang, Y. (2016). Chinese students’ behavior intention to use mobile library apps and effects of education level and discipline. Library Hi Tech, 34(4), 639–656. https://doi.org/10.1108/LHT-06-2016-0061

Huang, J., Lin, Y., & Chuang, S. (2007). Elucidating user behavior of mobile learning: A perspective of the extended technology acceptance model. The Electronic Library, 25(5), 585–598.

Hussain Chandio, F., Irani, Z., Abbasi, M. S., & Nizamani, H. A. (2013). Acceptance of online banking information systems: an empirical case in a developing economy. Behaviour & Information Technology, 32(7), 668–680. https://doi.org/10.1080/0144929X.2013.806593

Igbaria, M., & Tan, M. (1997). The consequences of information technology acceptance on subsequent individual performance. Information and Management, 32(3), 113–121. https://doi.org/10.1016/S0378-7206(97)00006-2

isaac, osama, Abdullah, Z., Thurasamy, R., & Mutahar, A. M. (2017). Internet usage, user satisfaction, task-technology fit, and performance impact among public sector employees in Yemen. International Journal of Information and Learning Technology, 34(3), IJILT-11-2016-0051. https://doi.org/10.1108/IJILT-11-2016-0051

Lim, N. (2003). Consumers’ perceived risk: Sources versus consequences. Electronic Commerce Research and Applications, 216–228.

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. https://doi.org/10.1016/j.jretconser.2006.02.006

Lu, C., Huang, S., & Lo, P. (2010). An empirical study of on-line tax filing acceptance model : Integrating TAM and TPB. African Journal of Business Management, 4(May), 800–810. Retrieved from http://www.academicjournals.org/AJBM

Lu, Y., Yang, S., Chau, P. Y. ., & Cao, Y. (2015). Determinants of behavioral intention to mobile payment : Evidence from. Information & Management, 48, 393–403.

Makki, A. M., Ozturk, A. B., & Singh, D. (2016). Role of risk, self-efficacy, and innovativeness on behavioral intentions for mobile payment systems in the restaurant industry. Journal of Foodservice Business Research, 19(5), 454–473. https://doi.org/10.1080/15378020.2016.1188646

Marakarkandy, B., Yajnik, N., & Dasgupta, C. (2017). Enabling internet banking adoption: An empirical examination with an augmented technology acceptance model (TAM). Journal of Enterprise Information Management, 30(2), 263–294. https://doi.org/10.1108/JEIM-10-2015-0094

MDI Ventures Sekuritas, & Mandiri Research. (2018). Mobile Payments in Indonesia: Race to Big Domination. Retrieved from https://www.mdi.vc/mobilepaymentindonesia.pdf

Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management, 38(4), 217–230. https://doi.org/10.1016/S0378-7206(00)00061-6

Motaghian, H., Hassanzadeh, a, & Moghadam, D. K. (2013). Factors affecting university instructors’ adoption of web-based learning systems: Case study of Iran. Computers & Education, 61, 158–167. https://doi.org/10.1016/j.compedu.2012.09.016

Mowen, J. C., & Minor, M. (2002). Perilaku konsumen. Jakarta: Erlangga 90.

Muñoz-Leiva, F., Climent-Climent, S., & Liébana-Cabanillas, F. (2017). Determinants of intention to use the mobile banking apps: An extension of the classic TAM model. Spanish Journal of Marketing - ESIC, 21(1), 25–38. https://doi.org/10.1016/j.sjme.2016.12.001

Musyaffi, A. M., Muna, A., & Fariani, N. (2016). Pengaruh persepsi kemudahan dan Persepsi Kegunaan terhadap Penerimaan Pengguna Sistem Informasi Akademik Terpadu. JRAK: Jurnal Riset Akuntansi Dan Komputerisasi Akuntansi, 7(2), 71–82.

Omwansa, T., Lule, I., & Waema, T. (2015). The Influence of Trust and Risk in Behavioural Intention to Adopt Mobile Financial Services among the Poor. International Arab Journal of E-Technology.

Pai, F.-Y., & Huang, K.-I. (2011). Applying the Technology Acceptance Model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650–660. https://doi.org/10.1016/j.techfore.2010.11.007

Patel, K. J., & Patel, H. J. (2017). Adoption of internet banking services in Gujarat: an extension of TAM with perceived security and social influence. International Journal of Bank Marketing, 36(1), 147–169. https://doi.org/https://doi.org/10.1108/IJBM-08-2016-0104

Peterson, R. A., Balasubramanian, S., & Bronnenberg, B. J. (1997). Exploring the Implications of the Internet for Consumer Marketing. Journal of the Academy of Marketing Science, 25(4), 329–346.

Rosnidah, I., Muna, A., Musyaffi, A. M., & Siregar, N. F. (2019). Critical Factor of Mobile Payment Acceptance in Millenial Generation: Study on the UTAUT model. In International Symposium on Social Sciences, Education, and Humanities (ISSEH 2018). Atlantis Press. https://doi.org/https://doi.org/10.2991/isseh-18.2019.30

Setlur, B., Iyer, G., & Varadan, S. (2014). Informed Manufacturing : The Next Industrial Revolution - COGNIZANT. Chennai, India.

Setyowati, D. (2018). Tren Baru Pembayaran Kode QR yang Menyimpan Masalah. Retrieved from https://katadata.co.id/berita/2018/09/11/tren-baru-pembayaran-kode-qr-yang-menyimpan-masalah

Sharma, S. K. (2017). Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling. Information Systems Frontiers, pp. 1–13. https://doi.org/10.1007/s10796-017-9775-x

Sharma, S. K., Govindaluri, S. M., Al-Muharrami, S., & Tarhini, A. (2017). A multi-analytical model for mobile banking adoption: a developing country perspective. Review of International Business and Strategy, 27(1), 133–148. https://doi.org/10.1108/RIBS-11-2016-0074

Shin, D., Jung, J., & Chang, B. (2012). The pychocology behind QR Codes: User experience perspective. Computers in Human Behavior, 8.

Singh, S., & Srivastava, R. K. (2018). Predicting the intention to use mobile banking in India. International Journal of Bank Marketing, 36(2), 357–378.

Surekha, A., Rubesh Anand, P. M., & Indu, I. (2015). E-payment transactions using encrypted QR Codes. International Journal of Applied Engineering Research.

Suryanto, V. (2019). Top up bermasalah, begini penjelasan pihak Go-Pay. Retrieved from https://keuangan.kontan.co.id/news/top-up-bermasalah-begini-penjelasan-pihak-go-pay

Tan, E., & Lau, J. L. (2016). Young Consumers Behavioural intention to adopt mobile banking among the millennial generation. International Journal of Bank Marketing, 17(3), 18–31. https://doi.org/10.1108/YC-07-2015-00537

Tsuma, C. K., Osang, F. B., & Abinwi, N. (2015). Reviewing Information Systems Usage and Performance Models. International Journal of Computer Science and Information Technologies, 6(1), 476–484. https://doi.org/10.1.1.668.8794

Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425–478.

Venkatesh, Viswanath, & Zhang, X. (2010). Unified theory of acceptance and use of technology: U.S. vs. China. Journal of Global Information Technology Management, 13(1), 5–27. https://doi.org/10.1080/1097198X.2010.10856507




DOI: http://dx.doi.org/10.33603/jibm.v3i2.2635

Refbacks

  • There are currently no refbacks.


Jurnal Inspirasi Bisnis dan Manajemen is published by Lembaga Penelitian Universitas Swadaya Gunung Jati. This work is licensed under a Creative Commons Attribution-Sharealike 4.0.

View My Stats
execute(); ?>