The Analysıs of Technology Acceptance Model (Tam) on Consumer Loyalty of Travelokapay Payment Systems in Travelokaeats Servıces

Hardy Gardian, Indra Kusumawardhana, Nabilah Fadiyah Sari, Faranita Mustikasari

Abstract


The massive technology development introduce non cash payment method using mobile phone, namely mobile payment. It changes consumer behaviour in conduct transaction and specifically induced by COVID 19 pandemic situation, whereas consumer minimize cash transaction. In Indonesian online travel provider, there are various brands available, and Travelokapay in TravelokaEats application considered as the new player in the market. Consumer may not easily adopt a new technology, because of various factors. This study aims to determine the effect of perceived of ease of use and usefulness on consumer attitudes which influence consumer interest in continuing to use the TravelokaPay payment system on the TravelokaEats service. It uses Technology Acceptance Model (TAM) which recognized as the familiar approach for new technology adoption. Data gathered from 158 respondents reside in Jakarta, Indonesia with purposive sampling technique. Analysis is conducted using Partial Least Square Structural Equation Modelling (PLS SEM). The results demonstrate that perceived ease of use significantly affect perceived usefulness, consumer attitude and continutaion intention. While perceived usefulness significantly affect only to consumer attitude.


Keywords


Technology Acceptance Model (TAM); Ease of Use; Usefulness; Customer Attitude; Continuance Intention

Full Text:

PDF

References


fungsi-utama/sistem-pembayaran/ritel/elektronifikasi/default.aspx

BankIndonesia. (2014). Peraturan Bank Indonesia.

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370.

Bobbitt, L. a. (2001). Integrating Attitudinal Theories to Understand and Predict Use of Technology-Based Self-Service: The Internet as an Illustration. International Journal of Service Industry Management, 12, 423-450.

Chen, J. J., & Adams, C. (2005). User acceptance of mobile payments: A theoretical model for mobile payments. Proceedings of the International Conference on Electronic Business, Hong Kong, China, 5.

Dahlberg, T., Mallat, N., Ondrus, J., & Zmijewska, A. (2008). In Past, present and future of mobile payments research: a literature review (pp. pp. 165-181.). Electronic Commerce Research and Applications, Vol. 7 No. 2.

Daud, N. M., Kassim, N., Said, W., & Noor, M. (2011). Determining critical success factors of mobile banking adoption in Malaysia. Australian Journal of Basic and Applied Sciences, 5(9):252-265.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

Donner, J., & Tellez, A. (2008). Mobile banking and economic development: linking adoption, impact, and use. Asian Journal of Communication, 3-15.

Dumbura, A., & Özkoç, E. E. (2021). Examining Technology Acceptance in Least-Developed Countries: The Case of ZESA. 6.

Emma Slade, M. W. (2013). Extending UTAUT2 To Explore Consumer Adoption Of Mobile Payments. Extending UTAUT2 To Explore Consumer Adoption Of Mobile Payments, 3-20.

Fareena Sultan, A. J. (2009). Factors Influencing Consumer Acceptance of Mobile Marketing: A Two-Country Study of Youth Markets. Factors Influencing Consumer Acceptance of Mobile Marketing: A Two-Country Study of Youth Markets, 5.

Gefen, D. K. (2003). Trust, Inexperience and experience with online stores. The importance of tam and IEEE Transactions on Engineering Management, 50, 307–321.

Ghezzi, A. R. (2010). Mobile payment applications: offer state of the art in the Italian market. Info 12. Mobile payment applications: offer state of the art in the Italian market. Info 12, 3-22.

Hair, J. F., Black, B., Black, W., Babin, B., & Anderson, R. (2014). Multivariate data analysis. Exploratory data analysis in business and economics. Pearson Education Limited.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (1998). Multivariate Data Analysis. Prentice-Hall International, Inc.

Hanafizadeh, P., Behboudi, M., Koshksaray, A., & Tabar, M. (2012). Mobile-banking adoption by Iranian bank clients. Telemat Informatics, 31: 62-78.

Ifinedo, P. (2006). Acceptance and Continuance Intention of Web-based Learning Technologies (WLT) Use Among University Students in a Baltic Country. The Electronic Journal on Information Systems in Developing Countries, vol.23, no.6, pp.1-20.

Juhri, K. &. (2017). Kepercayaan dan penerimaan layanan mobile money t-cash di Bandung dengan pendekatan Technology Acceptance Model (TAM). Jurnal Pro Bisnis, 10(1), 36–51.

Kim, C., Mirusmonov, M., & Lee, I. (2010). An Empirical Examination of Factors Influencing the Intention to Use Mobile Payment. Computers in Human Behavior , 26(3):310-322.

Kim, C., Tao, W., Shin, N., & Kim, K.-S. (2010). An empirical study of customers’ perceptions of security and trust in e-payment systems. Electronic Commerce Research and Applications, Vol. 9 No. 1.

Kim, J.-H., & Lee, J.-E. R. (2011). The Facebook paths to happiness: Effects of the number of Facebook friends and self-presentation on subjective well-being. CyberPsychology, behavior, and social networking, 14(6), 359-364.

Kumar, V. R. (2017). Extending the TAM model: Intention of management students to use mobile banking: Evidence from India. . Global Business Review.

Leng, G. S. (2011). An exploration of social networking sites (SNS) adoption in Malaysia using technology acceptance model (TAM), theory of planned behavior (TPB) and intrinsic motivation. The Journal of Internet Banking and Commerce, 16(2), 1-27.

Leong, L.-Y., Hew, T.-S., Tan, G. W.-H., & Ooi, K.-B. (2013). Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. 3.

Li, J., Liu, J.-L., & Ji, H.-Y. (2014). Empirical Study of Influence Factors of Adaption Intention of Mobile Payment based on TAM Model in China. 15.

Li, J., Wang, J., Wangh, S., & Zhou, Y. (2019). Mobile Payment with Alipay: An application of extended technology acceptance model. 10.

Linda Alkire (n´ee Nasr), G. E. (2020). Patient experience in the digital age: An investigation into the effect of generational cohorts. Patient experience in the digital age: An investigation into the effect of generational cohorts, 4.

Liu, G. S. (2016). A study of factors affecting the intention to use mobile payment services in Vietnam.

Lwoga, E. T. (2017). User Acceptance of Mobile Payment: The Effects of User‐Centric Security, System Characteristics and Gender. The Electronic Journal of Information Systems in Developing Countries.

Mallat, N. (2007). Exploring consumer adoption of mobile payments–A qualitative study. The Journal of Strategic Information Systems.

Marumbwa, J., & Mutsikiwa, M. (2013). An analysis of the factors influencing consumers’ adoption of mobile money transfer services (MMTS) in Masvingo urban Zimbabwe. British Journal of Economics Management & Trade, 3(4):498-512.

Mathwick, C. M. (2002). The effect of dynamic retail experiences on experiential perceptions of value: an Internet and catalog comparison. Journal of retailing, 78(1), 51-60.

Meharia, P. (2012). Assurance on the reliability of mobile payment system and its effects on its’ use: An empirical examination. Accounting & Management Information Systems / Contabilitate Si Informatica De Gestiune, 11(1), 97-111.

Moore, G. C. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222.

Muk, A., & Chung, C. (2014). Applying the technology acceptance model in a two-country study of SMS advertising. 6.

Mulia, K. (2021). In the top flight: Everything you need to know about Traveloka. https://kr-asia.com/in-the-top-flight-everything-you-need-to-know-about-traveloka-part-1-of-2.

Mun, Y. P. (2017). Millennials’ perception on mobile payment services in Malaysia. Procedia Computer Science, 124, 397-404.

Musafak. (2012). Budaya Ekonomi Digital Kalangan Masyarakat Menengah Atas. 1.

Onsongo, E. K., & Schot, J. (2017). Inclusive Innovation and Rapid Sociotechnical Transitions: The Case of Mobile Money in Kenya.

Persico, D., Manca, S., & Pozzi, F. (2013). Adapting the Technology Acceptance Model to evaluate the innovative potential of e-learning systems. 9.

Phonthanukitithaworn, C., Sellitto, C., & Fong, M. (2015). User Intentions to Adopt Mobile Payment Services: A Study of Early Adopters in Thailand. Journal of Internet Banking and Commerce, 20(1), 1–29.

Phonthanukitithaworn, C., Sellitto, C., & Fong, M. W. (2016). A comparative study of current and potential users of mobile payment services. SAGE Open, Vol. 6 No. 4.

PwC, R. (2019). It’s time for a consumer-centered metric: introducing ‘return on experience’. In Global Consumer Insights Survey.

Rasyid, R. A., Sunarya, E., & Ramdan, A. M. (2020). Analisis Minat Menggunakan Mobile Payment Dengan Pendekatan Technology Accpetance Model Pada Pengguna Link Aja Sukabumi. 11.

Schierz, P. S. (2010). “Understanding consumer acceptance of mobile payment services: an empirical analysis”. Electronic Commerce Research and Applications, Vol. 9 No. 3.

Shankar, A., & Datta, B. (2020). Factors Affecting Mobile Payment Adoption Intention: An Indian Perspective. 18.

Slade, E., Williams, M., & Dwivedi, Y. (2013). Mobile payment adoption: classification and review of the extant literature. The Marketing Review. 167-190.

Stanley Lemeshow, D. W. (1997). Besar Sampel dalam Penelitian Kesehatan (terjemahan). Gadjah Mada University Press, Yogyakarta.

Sugiyono. (2016). Metode penelitan kuantitatif, kualitatif dan R&D. In Alfabeta. Alfabeta.

Syafi’i, A., & Widijoko, G. (2016). Determinan Minat Individu Menggunakan Uang Elektronik: Pendekatan Modifikasi Technology Acceptance Model. 2.

Teng, P. K., Ling, T. J., & Seng, K. W. (2018). Understanding Customer Intention To Use Mobile Payment Services In Nanjing, China.

Thong, J. Y., Hong, S.-J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation confirmation model for information technology continuance. International Journal of Human-Computer Studies vol. 64, no.9, pp. 799-810.

Tobbin, P., & Kuwornu, J. (2011). Adoption of Mobile Money Transfer Technology: Structural Equation Modeling Approach. European Journal of Business and Management, 3: 59-78.

Tounekti, O., Martínez, A. R., & Gómez, A. S. (2019). Users supporting multiple (mobile) electronic payment systems in online purchases: An empirical study of their payment transaction preferences. 33.

Traveloka. (2018, Mei 18). Traveloka . From Traveloka : https://www.traveloka.com/id-id/restaurants

Venkatesh, V. &. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. In Management science (pp. 46, 186–204).

Vrontis, D., Thrassou, A., & Amirkhanpour, M. (2017). B2C Smart Retailing: A Consumer-Focused Valuebased Analysis Of Interactions And Synergies. In In Technological Forecasting & Social Change (pp. 45(2), 271-282.).

Wang, J.-H. W.-C. (2004). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. What drives mobile commerce? An empirical evaluation of the revised technology acceptance model, 5.

Watchravesringkan, K., Hodges, N., & Kim, Y.-H. (2010). Exploring consumers' adoption of highly technological fashion products: The role of extrinsic and intrinsic motivational factors. Journal of Fashion Marketing and Management, 14(2), 263 - 281.

Wong, C. C., & Hiew, P. L. (2005). Correlations between factors affecting the diffusion of mobile entertainment in Malaysia. In Proceedings of the 7th international conference on Electronic commerce, pp. 615-621.

Wong, W. H., & Mo, W. Y. (2019). A Study of Consumer Intention of Mobile Payment in Hong Kong, Based on Perceived Risk, Perceived Trust, Perceived Security and Technological Acceptance Model.

Yuan, S., Liu, Y., Yao, R., & Liu, J. (2016). An investigation of users' continuance intention towards mobile banking in China. Inf Dev 32:, 20-34.

Zhou, T. (2013). In An empirical examination of continuance intention of mobile payment services (pp. pp. 1085-1091.). Decision Support Systems, Vol. 54 No. 2.




DOI: https://doi.org/10.21776/ub.apmba.2022.010.03.8

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.