USER ACCEPTANCE OF ONLINE TRAVEL AGENTS AGENT FOR MILLENIALS AND GEN Z

Muhammad Faikar Thaufan Lubis, Filda Rahmiati
| Abstract views: 239 | views: 116

Abstract

Pariwisata adalah salah satu sektor yang berkontribusi paling besar terhadap perekonomian suatu negara. Selain itu, ia berkontribusi paling besar bagi pembangunan berkelanjutan seperti di Indonesia. Salah satu pemain pariwisata adalah agen perjalanan online yang melayani kebutuhan wisatawan sebelum bepergian. Karena itu, penting bagi agen perjalanan untuk memenuhi kebutuhan wisatawan. Tujuan dari penelitian ini adalah untuk menentukan penerimaan pengguna terhadap agen perjalanan online di Gen Z dan Millennials. Penelitian ini dilakukan untuk mempelajari model Unified Theory Acceptance dan Use of Technology 2 (UTAUT2). Populasi dari penelitian ini adalah semua orang yang pernah membeli tiket dan / atau memesan akomodasi di Agen Perjalanan Online menggunakan purposive sampling non-probabilitas. Penelitian ini mengumpulkan data dengan menyebarkan kuesioner elektronik (e-kuesioner). 200 responden memenuhi kriteria dalam penelitian ini. Untuk menganalisis data, Partial Least Square - Structural Equation Model (PLS-SEM) dianalisis menggunakan SmartPLS 3.2.8. Hasil penelitian ini menunjukkan bahwa Pengaruh Sosial, Motivasi Hedonik, dan Kebiasaan berpengaruh signifikan terhadap Behavioral Intention. Behavioral Intention juga memiliki pengaruh signifikan terhadap Use Behavior. Dalam efek moderasi, hanya Umur yang dapat memoderasi Pengaruh Sosial pada Niat Perilaku. Dengan demikian, direkomendasikan untuk penelitian selanjutnya untuk menggunakan model UTAUT2 yang lengkap dan menambahkan variabel Perceived Security. Di sisi lain, Pegipegi harus menambahkan lebih banyak layanan pada bisnis utama mereka.

 

Tourism is one of the sectors that contribute the most to a country's economy. Moreover, it contributes most to sustainable development such as in Indonesia. One of tourism players is an online travel agency that caters to the needs of tourists before travelling. Therefore, it is important for travel agents to meet the needs of tourists. The purpose of this study was to determine user acceptance of online travel agents in Gen Z and Millennials. This research carried out to study Unified Theory Acceptance and Use of Technology 2 (UTAUT2) model. The population of this study is everyone who ever purchased ticket and/or booking accommodation on Online Travel Agent using non-probability purposive sampling. This research collected the data by spreading electronic questionnaire (e-questionnaire). 200 respondents met criteria in this research. To analyze the data, Partial Least Square – Structural Equation Model (PLS-SEM) analyzed using SmartPLS 3.2.8. The result of this research indicated that Social Influence, Hedonic Motivation, and Habit has significant influence on Behavioral Intention. Behavioral Intention also has significant influence on Use Behavior. In moderating effect, only Age can moderate Social Influence on Behavioral Intention. Thus, it is recommended for next research to use the complete of UTAUT2 model and add Perceived Security variable. On the other hand, Pegipegi should add more services on their main business.

Keywords

UTAUT2; Online Travel Agent; Technology Acceptance; Behavioural Intention; Use Behavior

Full Text:

PDF

References

Auliya, N. (2018). Application of the Unified Theory of Acceptance and Use of Technology 2 Model to the Interest and Behavior of E-Ticket Use in Yogyakarta.

Betz, C. L. (2019). Generations X, Y, and Z. Journal of Pediatric Nursing, 44, A7–A8. https://doi.org/10.1016/j.pedn.2018.12.013

Chin, W. W. (2000). Frequently Asked Questions – Partial Least Squares & PLS-Graph. Retrieved December 14, 2019, from http://disc-nt.cba.uh.edu/chin/plsfaq.htm

Creswell, J. W. (2014). Research Design : Qualitative, Quantitative, and Mixed Methods Approaches (4th Edition). Callifornia: SAGE Publications, Inc.

Dimock, M. (2019). Defining generations: Where Millennials end and Generation Z begins. Retrieved December 15, 2019, from Pew Research Center website:

https://www.pewresearch.org/fact-tank/2019/01/17/where-millennials-end-and-generation-z-begins/

Garson, G. D. (2016). Partial Least Squares: Regression & Structural Equation Models. In G. David Garson and Statistical Associates Publishing. North Carolina: Stastical Associates Publishing.

Ghozali, I., & Latan, H. (2015). Partial Least Squares Concepts, Techniques and Applications using the SmartPLS 3.0 Program (Edition 2). Semarang: Publisher Agency - Undip.

Goswami, A., & Dutta, S. (2016). Gender differences in schizophrenia: A literature review. Journal of Business and Management, 3(4), 51–59. https://doi.org/10.3109.10401239109148015

Gupta, A., & Dogra, N. (2017). Tourist adoption of mapping apps: A UTAUT2 perspective of smart travellers. Tourism and Hospitality Management, 23(2), 145–161. https://doi.org/10.20867/thm.23.2.6

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

Hew, J.-J., Lee, V.-H., Ooi, K.-B., & Wei, J. (2015). What catalyses mobile apps usage intention: An empirical analysis. Industrial Management & Data Systems, 115(7), 1269–1291. https://doi.org/https://doi.org/10.1108/IMDS-01-2015-0028

Hikmah, A. F., Kusyanti, A., & Perdanakusuma, A. R. (2018). Analysis of Factors Affecting ABC Messenger User Behavior in Receiving Information at XYZ Institution by Using The Unified Theory of Acceptance and Use of Technology (UTAUT). 2 (4), 1372–1381.

Indonesia Statistics Bureau (2019). Domestic Tourist Statistic 2018. Retrieved from https://www.bps.go.id/publication/2019/07/02/5249c2b645e21291b51dfc1a/statistik-wisatawan-nusantara-2018.html

Jaradat, M.-I. R. M., & Al Rababaa, M. S. (2013). Assessing Key Factor that Influence on the Acceptance of Mobile Commerce Based on Modified UTAUT. International Journal of Business and Management, 8(23), 102–112.

https://doi.org/10.5539/ijbm.v8n23p102

Kamal, R. M., & Azis, E. (2015). Adoption of Internet Technology by Indonesian MSME Consumers to Shop Online (Study on the site Tokopedia.com 2015). 2 (3), 2451–2458.

Liu, Y. C., & Huang, Y. M. (2015). Using the UTAUT model to examine the acceptance behavior of synchronous collaboration to support peer translation. JALT CALL Journal, 11(1), 77–91.

Malau, Y. (2016). Analysis of Rail Ticket System Acceptance at PT. KAI using the UTAUT model. Paradigm, XVIII (2), 102-112.

Marhaeni, G. A. M. M. (2014). Analysis of the Behavior of Using Instant Messaging Applications using the Unified Theory of Acceptance and Use of Technology 2 Model in Bandung. E-Proceeding of Management, 1 (3), 42–56.

Melisa, & Indrawati. (2016). Analysis of Customer Acceptance of Online Travel Agent Technology using UTAUT2 Model (A Case Studt on E-Commerce Traveloka in Indonesia). Sustainable Collaboration in Business, Technology, Information and Innovation, 7(2012), 115–120.

Morgan, A. R. (2013). Factors Influencing Student Use of Online Homework Management Systems. Research Gate Annual Edition, 3, 98–112.

Nofadhila, A., Prasetio, A., & Sofyan, E. (2018). The Consumer Acceptance of Traveloka Mobile App Affects Behavioral Intention: Analyzing 7 Factors of Modified UTAUT2 (Study Case in Indonesia). E-Proceeding of Management, 5(1), 874.

Pertiwi, N. W. D. M. Y., & Ariyanto, D. (2017). Penerapan Model UTAUT2 untuk Menjelaskan Minat dan Perilaku Penggunaan Mobile Banking di Kota Denpasar. E-Jurnal Akuntansi Universitas Udayana, 18(2), 1369–1397. https://doi.org/10.1017/CBO9781107415324.004

PJII. (2018). Penetration & Profile of Indonesian Internet User Behavior. In Apjii. Retrieved from www.apjii.or.id

Putra, M. A. A. (2018). Evaluation of Use of Bank Mandiri E-Money Electronic Money Products Using the UTAUT 2 Model (Case Study: Ciputat District) (Vol. 2). Syarif Hidayatullah State Islamic University Jakarta.

Ramdhani, A. B., Rachmawati, I., Sidiq, F., & Prabowo, A. (2017). Effect of Adoption of Telkomsel Cash Electronic Money Service Technology Using the Utaut Approach2 The Effect of Adoption Technology Electronic Money Services Telkomsel Cash Using Utaut2. E-Proceeding of Management, 4 (1), 53–61.

Rema, Y. O. L., & Setyohadi, D. B. (2016). Factors affecting the acceptance of mobile banking case studies: BRI Bajawa Branch. Information Technology Research Seminar, 114-122.

Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Retrieved from http://www.smartpls.com

Sandjojo, N. (2011). Path Analysis Method and its Application. Jakarta: Pustaka Sinar Harapan.

Sarwono, J., & Narimawati, U. (2015). Make a Thesis, Thesis, and Dissertation with Partial Least Square (PLS SEM). Yogyakarta: ANDI Publisher.

Sugiyono (2017). Quantitative, Qualitative, and R&D Research Methods. Bandung: Alfabeta.

Suryadinata, A. S., Ariyanti, M., & Sumrahadi. (2017). Positioning Analysis of Online Ticket Reservation Sites Based on Consumer Perceptions in Indonesia in 2016 (Study on Traveloka Sites, Tickets, Tiket2, Pegipegi, and Nusatrip). E-Proceeding of Management, 4 (2), 1188–1195.

Tak, P., & Panwar, S. (2017). Using UTAUT 2 model to predict mobile app based shopping: evidences from India. Journal of Indian Business Research, 9(3), 248–264. https://doi.org/10.1108/JIBR-11-2016-0132

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.

We Are Social. (2019). Digital 2019: Indonesia. Global Digital Insights, 77. https://doi.org/https://datareportal.com/reports/digital-2019-indonesia.

Yu, C.-S. (2012). Factors Affecting Individuals to Adopt Mobile Banking: Empirical Evidence from the UTAUT Model. Journal of Electronic Commerce Research, 13, 104–121.

Copyright (c) 2020 Jurnal Muara Ilmu Ekonomi dan Bisnis
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Refbacks

  • There are currently no refbacks.