The Influence of Perceived Ease of Use and Perceived Usefulness on Switching Intention
DOI:
https://doi.org/10.32659/tsj.v10i2.439Keywords:
Online TravelaAgent, Perceived Easeoof Use, PerceivedoUsefulness, SwitchingoIntentionAbstract
Technology and the internet have brought substantial changes to the tourism industry, particularly through online travel agents (OTAs). One of the major challenges faced by OTA is the phenomenon of "switching intention," where consumers tend to move from one service provider to another. This behavior may result in customer loss and a decline in profits. The objective of this study is to analyze the influence of perceived ease of use and perceived usefulness on switching intention among OTA users. A quantitative research method was employed, using a descriptive and verification approach through an explanatory survey. Primary data were collected from 107 respondents who were Traveloka users. The data were analyzed using multiple linear regression. The findings reveal that both perceived ease of use and perceived usefulness hLS
References
Abolfathi, N., Santamaria, S., & Williams, C. (2021). How Does Firm Scope Depend on Customer Switching Costs? Evidence from Mobile Telecommunications Markets. Management Science, 68(1), 316–332. https://doi.org/10.1287/mnsc.2020.3913
Al-Banna, H., & Berakon, I. (2023). From bank to P2P lending: switching intention of SME’s: evidence from Indonesia. Journal of Financial Services Marketing, 29(2), 568–581. https://doi.org/10.1057/s41264-023-00225-9
Albort-Morant, G., Sanchís-Pedregosa, C., & Paredes, J. R. P. (2021b). Online banking adoption in Spanish cities and towns. Finding differences through TAM application. Economic Research-Ekonomska Istraživanja, 35(1), 854–872. https://doi.org/10.1080/1331677x.2021.1945477
Belmonte, Z. J. A., Prasetyo, Y. T., Cahigas, M. M. L., Nadlifatin, R., & Gumasing, M. J. J. (2024). Factors influencing the intention to use e-wallet among generation Z and millennials in the Philippines: An extended technology acceptance model (TAM) approach. Acta Psychologica, 250, 104526. https://doi.org/10.1016/j.actpsy.2024.104526
Billanes, J., & Enevoldsen, P. (2021). A critical analysis of ten influential factors to energy technology acceptance and adoption. Energy Reports, 7, 6899–6907. https://doi.org/10.1016/j.egyr.2021.09.118
Bujang, M. A., Sa’at, N., & Sidik, T. M. I. T. A. B. (2017). Determination of minimum sample size requirement for multiple linear regression and analysis of covariance based on experimental and non-experimental studies. Epidemiology Biostatistics and Public Health, 14(3), e12117-1-e12117-9. https://doi.org/10.2427/12117
Chang, Y. W., & Hsu, P. Y. (2019). An empirical investigation of organizations’ switching intention to cloud enterprise resource planning: a cost-benefit perspective. Information Development, 35(2), 290–302. https://doi.org/10.1177/0266666917743287
Chatterjee, N. D. S., & Karmakar, N. D. B. (2024). Exploring consumer choices in the metaverse: a new digital era. International Journal of Advanced Research in Science Communication and Technology, 487–492. https://doi.org/10.48175/ijarsct-19275
Cheng, S., Lee, S. J., & Choi, B. (2019). An empirical investigation of users’ voluntary switching intention for mobile personal cloud storage services based on the push-pull-mooring framework. Computers in Human Behavior, 92, 198–215. https://doi.org/10.1016/j.chb.2018.10.035
Dai, Q., & Cheng, K. (2022). What drives the adoption of agricultural Green production Technologies? an extension of TAM in agriculture. Sustainability, 14(21), 14457. https://doi.org/10.3390/su142114457
Davis, F. D. (1986). A Technology Acceptance Model For Empirically Testing New End-User Information Systems: Theory And Results. Sloan School of Management, MIT, 146(3652), 1648–1655. https://doi.org/10.1126/science.146.3652.1648
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/10.5962/bhl.title.33621
Fahmi, S., . N., Rohman, F., & . S. (2018). Factors Affecting Indonesian Consumers to Switch, Using Mobile Banking and Internet Banking Service. KnE Social Sciences, 3(10), 1236–1248. https://doi.org/10.18502/kss.v3i10.3465
Fahmi, S., Noermijati, Rohman, F., & Sunaryo. (2018). Factors affecting Indonesian consumers to switch, using mobile banking and internet banking service. KnE Social Sciences, 3(10). https://doi.org/10.18502/kss.v3i10.3465
Ferreira, A., Silva, G. M., & Dias, Á. L. (2021). Determinants of continuance intention to use mobile self-scanning applications in retail. International Journal of Quality & Reliability Management, 40(2), 455–477. https://doi.org/10.1108/ijqrm-02-2021-0032
Franque, F. B., Oliveira, T., Tam, C., & De Oliveira Santini, F. (2020). A meta-analysis of the quantitative studies in continuance intention to use an information system. Internet Research, 31(1), 123–158. https://doi.org/10.1108/intr-03-2019-0103
Ghamry, S., & Shamma, H. M. (2020). Factors influencing customer switching behavior in Islamic banks: evidence from Kuwait. Journal of Islamic Marketing, 13(3), 688–716. https://doi.org/10.1108/jima-01-2020-0021
Huang, H., Liu, Y., & Lu, D. (2019). Proposing a model for evaluating market efficiency of OTAs: Theoretical approach. Tourism Economics, 26(6), 958–975. https://doi.org/10.1177/1354816619853114
Jhamb, D., Mittal, A., & Sharma, P. (2020). The Behavioural Consequences Of Perceived Service Quality: A Study Of The Indian Telecommunication Industry. Verslas Teorija Ir Praktika, 21(1), 360–372. https://doi.org/10.3846/btp.2020.11480
Kim, K., Seo, H., Yu, H., & Choi, J. (2017). A study on the factors affecting switching intention of public certificate storage?: focused on Smart Certificate(USIM). Journal of the Korea Society of IT Services, 16(1), 99–118. https://doi.org/10.9716/kits.2017.16.1.099
Li, P., & Varghese, M. M. (2023). Switching Intention and Intention to Use Personal Cloud Storage Services Among Chinese Undergraduates. Scholar: Human Sciences, 15(1), 171-181. https://doi.org/10.14456/shserj.2023.18
Lin, C., & Huang, H. (2022). Exploring users’ switching intention and behavior on social networking sites: Linear and nonlinear perspectives. Computer Standards & Interfaces, 83, 103660. https://doi.org/10.1016/j.csi.2022.103660
Liu, T., Lin, T. T., & Hsu, S. (2022). Continuance Usage Intention toward E-Payment during the COVID-19 Pandemic from the Financial Sustainable Development Perspective Using Perceived Usefulness and Electronic Word of Mouth as Mediators. Sustainability, 14(13), 7775. https://doi.org/10.3390/su14137775
Lv, X., Li, N., Xu, X., & Yang, Y. (2020). Understanding the emergence and development of online travel agencies: a dynamic evaluation and simulation approach. Internet Research, 30(6), 1783–1810. https://doi.org/10.1108/intr-11-2019-0464
Ma, J., Wang, P., Li, B., Wang, T., Pang, X. S., & Wang, D. (2024). Exploring User Adoption of ChatGPT: A Technology Acceptance Model Perspective. International Journal of Human–Computer Interaction, 41(2), 1431–1445. https://doi.org/10.1080/10447318.2024.2314358
Malik, S., Mahmood, S., & Rizwan, M. (2014). Examining Customer Switching Behavior in Cellular Industry. Journal of Public Administration and Governance, 4(2), 114. https://doi.org/10.5296/jpag.v4i2.5840
Malik, S., Mahmood, S., & Rizwan, M. (2014). Examining customer switching behavior in cellular industry. Journal of Public Administration and Governance, 4(2), 114. https://doi.org/10.5296/jpag.v4i2.5840
Mu, H., & Lee, Y. (2022). Will proximity mobile payments substitute traditional payments? Examining factors influencing customers’ switching intention during the COVID-19 pandemic. International Journal of Bank Marketing, 40(5), 1051–1070. https://doi.org/10.1108/ijbm-06-2021-0284
Ngau, C. M., Zins, A. H., & Rengasamy, D. (2023). Why do bank customers switch? A systematic literature review. International Journal of Bank Marketing, 41(6), 1308–1329. https://doi.org/10.1108/ijbm-10-2021-0475
Nugroho, A. P., & Hati, S. R. H. (2020). Determinants of repurchase intention and switching intention: analysis of online travel agent, Peer-To-Peer accommodation, and virtual hotel operator platforms. Market-Tržište, 32(1), 79–96. https://doi.org/10.22598/mt/2020.32.1.79
Prajapat, D. K., & R, K. (2024). Revolutionizing Tourism through Technology the Digital Transformation of Travel and Tourism. International Journal of Research Publication and Reviews, 5(2), 3643–3648. https://doi.org/10.55248/gengpi.5.0224.0626
Rahi, S., & Ghani, M. A. (2018). Investigating the role of e-service quality and brand image in internet banking acceptance context with structural equation modeling (SEM-PLS). http://www.esd-conference.com
Ribeiro, H., Barbosa, B., Moreira, A. C., & Rodrigues, R. G. (2023). Determinants of churn in telecommunication services: a systematic literature review. Management Review Quarterly, 74(3), 1327–1364. https://doi.org/10.1007/s11301-023-00335-7
Rizal, H., Amin, H., Suddin, L., Sondoh, S. L., & Ku, C. J. (2020). Relationship Quality and E-Loyalty towards Online Travel Agency (OTA): Social Exchange Theory Perspective. Jurnal Pengurusan, 58, 39–51. https://doi.org/10.17576/pengurusan-2020-58-04
Saleh, S. S., Nat, M., & Aqel, M. (2022). Sustainable Adoption of E-Learning from the TAM Perspective. Sustainability, 14(6), 3690. https://doi.org/10.3390/su14063690
Sekaran, U., & Bougie, R. (2016). Research Methods for Business?: A Skill-Building (7th ed.). John Wiley & Sons Ltd. https://doi.org/10.13140/RG.2.1.1419.3126
Senanu, B., & Narteh, B. (2022). Banking sector reforms and customer switching intentions: evidence from the Ghanaian banking industry. Journal of Financial Services Marketing, 28(1), 15–29. https://doi.org/10.1057/s41264-021-00135-8
Sonmez, A., & Ozdamar, N. (2024). Examining the factors related to learners’ intention and usage continuity of online learning. Open Praxis, 16(2), 195–207. https://search.informit.org/doi/10.3316/informit.T2024041000013891399051007
Taherdoost, H. (2016). Sampling Methods in Research Methodology; How to Choose a Sampling Tech-nique for Research. In International Journal of Academic Research in Management (IJARM). https://hal.archives-ouvertes.fr/hal-02546796
Tang, J., Yang, F., & Yang, T. (2023). Perceived uncertainty and switching intention on e-commerce platforms: The moderating role of usage habit. Electronic Commerce Research and Applications, 61, 101302. https://doi.org/10.1016/j.elerap.2023.101302
Tsai, L. L. (2022). A deeper understanding of switching intention and the perceptions of non-subscribers. Information Technology and People, 36(2), 785–807. https://doi.org/10.1108/itp-04-2021-0255
Ukaegbu, O. C., & Fan, M. (2025). Examining the Influence of Personal eHealth Literacy on Continuance Intention towards Mobile Health Applications: A TAM-Based Approach. Health Policy and Technology, 101024. https://doi.org/10.1016/j.hlpt.2025.101024
Van Nguyen, A. T., Halibas, A. S., McClelland, R., & Thuan, N. H. (2023). Configurational analysis of conditions influencing customers’ channel switching intention in omnichannel retailing: a fuzzy-set analysis. Quality & Quantity, 58(1), 141–178. https://doi.org/10.1007/s11135-023-01633-8
Vlahovi?, O., Ra?enovi?, Z., Perovi?, D., Vuja?i?, V., & Davidovi?, K. (2024). Digital Transformation in Tourism: The Role of E-Booking Systems. Croatian Regional Development Journal. https://doi.org/10.2478/crdj-2024-0012
Wang, C., Ahmad, S. F., Ayassrah, A. Y. B. A., Awwad, E. M., Irshad, M., Ali, Y. A., Al-Razgan, M., Khan, Y., & Han, H. (2023). An empirical evaluation of technology acceptance model for Artificial Intelligence in E-commerce. Heliyon, 9(8), e18349. https://doi.org/10.1016/j.heliyon.2023.e18349
Wang, Y., & Lin, K. (2021). Understanding Continuance usage of mobile learning Applications: The moderating role of habit. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.736051
Winarko, Hilarius Bambang and Husna, Asmaul, The Consumer Behavior toward Online Travelling Agency (OTA): Evidence from Indonesia (March 18, 2020). International Journal of Tourism & Hospitality Reviews eISSN: 2395-7654, Vol 7, No 1, 2020, Available at SSRN: https://ssrn.com/abstract=3557089
Ye, D., Liu, F., Cho, D., & Jia, Z. (2022). Investigating switching intention of e-commerce live streaming users. Heliyon, 8(10), e11145. https://doi.org/10.1016/j.heliyon.2022.e11145
Zeng, Z., Li, S., Lian, J., Li, J., Chen, T., & Li, Y. (2021). Switching behavior in the adoption of a land information system in China: A perspective of the push–pull–mooring framework. Land Use Policy, 109, 105629. https://doi.org/10.1016/j.landusepol.2021.105629
Zhao, C., Noman, A. H. M., & Hassan, M. K. (2023). Bank’s service failures and bank customers’ switching behavior: does bank reputation matter? International Journal of Bank Marketing, 41(3), 550–571. https://doi.org/10.1108/ijbm-07-2022-0287
Downloads
Published
How to Cite
Issue
Section
Citation Check
License
Copyright (c) 2025 Gusti Ketut Oka Saputra, Oce Ridwanudin, Yeni Yuniawati

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
-
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
-
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.