When do tourists prefer to continue using online travel agencies? An empirical study from Vietnam
-
DOIhttp://dx.doi.org/10.21511/im.20(4).2024.06
-
Article InfoVolume 20 2024, Issue #4, pp. 62-73
- 108 Views
-
17 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
Online travel agencies have profoundly influenced the travel industry by offering numerous essential advantages to both consumers and service providers. This paper aims to examine the factors that influence the intention to continue using online travel agencies in Vietnam, while also assessing the moderating effect of e-loyalty on the relationship between perceived usefulness and continuance intention. An integrated research framework was constructed using the Technology Acceptance Model as its foundational basis. The study utilized the Partial Least Squares Structural Equation Modeling approach to analyze the data. The survey data were obtained through an online survey administered to a valid sample of 301 Facebook users with prior experience using online travel agencies. Compared to conventional approaches such as telephone or mail surveys, utilizing Facebook for data collection offers a more cost-efficient alternative. This platform also enables researchers to reach a broad and diverse population of potential respondents, representing a wide range of demographics, geographic locations, and backgrounds. The results reveal that perceived compatibility, perceived ease of use, innovativeness, electronic word-of-mouth, and subjective norms all positively influenced perceived usefulness. Additionally, perceived usefulness is found to have a significant impact on the intention to continue using online travel agencies, while e-loyalty positively moderates the relationship between perceived usefulness and continuance intention to use online travel agencies. These findings extend the Technology Acceptance Model within the context of online travel agencies and provide practical insights for enhancing strategies among online travel agencies in Vietnam.
Acknowledgment
The author would like to thank the International University, Vietnam National University (VNU), HCMC, for providing research assistance.
- Keywords
-
JEL Classification (Paper profile tab)M10, M20, M31, Z33
-
References50
-
Tables4
-
Figures2
-
- Figure 1. Research model
- Figure 2. Structural model
-
- Table 1. Background information of participants
- Table 2. Measurement scale of variables
- Table 3. Discriminant validity and tests of differences between correlations
- Table 4. Structural model estimates
-
- Akdim, K., Casaló, L. V., & Flavián, C. (2022). The role of utilitarian and hedonic aspects in the continuance intention to use social mobile apps. Journal of Retailing and Consumer Services, 66, 102888.
- Alhalaybeh, A., & Althunibat, A. (2023). Measuring Acceptance of Adoption Metaverse in eLearning by Using TAM Model. In Proceedings of 2023 International Conference on Information Technology (ICIT) (pp. 361-366).
- Amoroso, D., & Lim, R. (2017). The mediating effects of habit on continuance intention. International Journal of Information Management, 37(6), 693-702.
- Ananadan, R., & Sipahimalani, R. (2017). Accelerating the growth of Southeast Asia’s Internet Economy.
- Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351-370.
- Carter, M., Wright, R., Thatcher, J. B., & Klein, R. (2014). Understanding online customers’ ties to merchants: the moderating influence of trust on the relationship between switching costs and e-loyalty. European Journal of Information Systems, 23(2), 185-204.
- Chang, T.-Z. (Donald), Kong, W. H., & Bahl, A. (2023). Personal values and travel social media use among Generation Z. Consumer Behavior in Tourism and Hospitality, 18(1), 49-65.
- Chen, Y., Liu, Y., Wu, L., & Li, X. (Robert). (2022). How Does Mobile Social Media Sharing Benefit Travel Experiences? Journal of Travel Research, 62(4), 841-858.
- Chuang, T. C., Liu, J. S., Lu, L. Y. Y., Tseng, F.-M., Lee, Y., & Chang, C.-T. (2017). The main paths of eTourism: trends of managing tourism through Internet. Asia Pacific Journal of Tourism Research, 22(2), 213-231.
- Claudy, M. C., Garcia, R., & O’Driscoll, A. (2015). Consumer resistance to innovation—a behavioral reasoning perspective. Journal of the Academy of Marketing Science, 43(4), 528-544.
- Cui, F., Lin, D., & Qu, H. (2018). The impact of perceived security and consumer innovativeness on e-loyalty in online travel shopping. Journal of Travel & Tourism Marketing, 35(6), 819-834.
- Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340.
- Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research.
- Fishbein, M., & Ajzen, I. (1973). Attribution of responsibility: A theoretical note. Journal of Experimental Social Psychology, 9(2), 148-153.
- Hansen, J. M., Saridakis, G., & Benson, V. (2018). Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers’ use of social media for transactions. Computers in Human Behavior, 80, 197-206.
- Hao, J.-X., Yu, Y., Law, R., & Fong, D. K. C. (2015). A genetic algorithm-based learning approach to understand customer satisfaction with OTA websites. Tourism Management, 48, 231-241.
- Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? Journal of Interactive Marketing, 18(1), 38-52.
- Hermawan, D. (2022). The effects of web quality, perceived benefits, security and data privacy on behavioral intention and e-WOM of online travel agencies. International Journal of Data and Network Science, 6(3), 1005-1012.
- Ho, J. C., Wu, C.-G., Lee, C.-S., & Pham, T.-T. T. (2020). Factors affecting the behavioral intention to adopt mobile banking: An international comparison. Technology in Society, 63, 101360.
- Jackson, J. D., Yi, M. Y., & Park, J. S. (2013). An empirical test of three mediation models for the relationship between personal innovativeness and user acceptance of technology. Information & Management, 50(4), 154-161.
- Jeon, M. M., & Jeong, M. (2017). Customers’ perceived website service quality and its effects on e-loyalty. International Journal of Contemporary Hospitality Management, 29(1), 438-457.
- Jermsittiparsert, K., Wongsuwan, N., & Akkaya, B. (2023). Subjective Norms and Behavioural Intention of E-Banking Adoption: Mediating Role of Perceived Usefulness. In Akkaya, B. & Tabak, A. (Eds.), Two Faces of Digital Transformation (pp. 177-193). Emerald Publishing Limited.
- Kotler, P., Armstrong, G., Harris, L. C., & He, H. (2019). Principles of Marketing. Pearson UK.
- Kumar, V., & Ayodeji, O. G. (2021). E-retail factors for customer activation and retention: An empirical study from Indian e-commerce customers. Journal of Retailing and Consumer Services, 59, 102399.
- Li, H., & Liu, Y. (2014). Understanding post-adoption behaviors of e-service users in the context of online travel services. Information & Management, 51(8), 1043-1052.
- Lim, W., Munikrishnan, U. T., Leong, C.-M., Hiew, L.-C., Leong, M.-W., & Yang, L. (2024). Do you want a secure e-wallet? Understanding the role of risk and security in e-wallet continuance intention. Information & Computer Security, 32(3), 304-321.
- Ling, L., Dong, Y., Guo, X., & Liang, L. (2015). Availability management of hotel rooms under cooperation with online travel agencies. International Journal of Hospitality Management, 50, 145-152.
- Lu, J., Mao, Z., Wang, M., & Hu, L. (2015). Goodbye maps, hello apps? Exploring the influential determinants of travel app adoption. Current Issues in Tourism, 18(11), 1059-1079.
- Matubatuba, R., & De Meyer-Heydenrych, C. F. (2022). Moving towards smart mobility: Factors influencing the intention of consumers to adopt the bus rapid transit (BRT) system. Cogent Business & Management, 9(1), 2089393.
- Mehra, A., Paul, J., & Kaurav, R. P. S. (2021). Determinants of mobile apps adoption among young adults: theoretical extension and analysis. Journal of Marketing Communications, 27(5), 481-509.
- Mou, J., Shin, D.-H., & Cohen, J. (2017). Understanding trust and perceived usefulness in the consumer acceptance of an e-service: a longitudinal investigation. Behaviour & Information Technology, 36(2), 125-139.
- Murphy, H. C., & Chen, M.-M. (2014). Online Information Sources Used in Hotel Bookings: Examining Relevance and Recall. Journal of Travel Research, 55(4), 523-536.
- Nugroho, A., Siagian, H., Oktavio, A., & Tarigan, Z. J. H. (2023). The effect of e-WOM on customer satisfaction through ease of use, perceived usefulness and e-wallet payment. International Journal of Data and Network Science, 7(1), 153-162.
- Purani, K., Kumar, D. S., & Sahadev, S. (2019). e-Loyalty among millennials: Personal characteristics and social influences. Journal of Retailing and Consumer Services, 48, 215-223.
- Ray, A., Bala, P. K., & Rana, N. P. (2021). Exploring the drivers of customers’ brand attitudes of online travel agency services: A text-mining based approach. Journal of Business Research, 128, 391-404.
- Roy, G., Datta, B., Mukherjee, S., & Basu, R. (2021). Effect of eWOM stimuli and eWOM response on perceived service quality and online recommendation. Tourism Recreation Research, 46(4), 457-472.
- Schneider, D., & Harknett, K. (2019). What’s to Like? Facebook as a Tool for Survey Data Collection. Sociological Methods & Research, 51(1), 108-140.
- Setiawan, P., & Widanta, A. (2021). The effect of trust on travel agent online use: Application of the technology acceptance model. International Journal of Data and Network Science, 5(3), 173-182.
- Shanmugavel, N., & Micheal, M. (2022). Exploring the marketing related stimuli and personal innovativeness on the purchase intention of electric vehicles through Technology Acceptance Model. Cleaner Logistics and Supply Chain, 3, 100029.
- Singh, N., & Sinha, N. (2020). How perceived trust mediates merchant’s intention to use a mobile wallet technology. Journal of Retailing and Consumer Services, 52, 101894.
- Siu, N. Y. M., & Chang, L. M. K. (2015). A Study of Service Quality, Perceived Risk and Personal Innovativeness in Internet Banking. In Spotts, H. E. (Ed.), Revolution in Marketing: Market Driving Changes (pp. 78-83). Springer International Publishing.
- Sun, Y., Gonzalez-Jimenez, H., & Wang, S. (2021). Examining the relationships between e-WOM, consumer ethnocentrism and brand equity. Journal of Business Research, 130, 564-573.
- Tan, L., Ren, C., Zhan, Y., Chang, Y.-W., Chen, J., & Hsu, M.-C. (2024). Exploring consumers’ adoption and recommendation in smart retailing: a cognitive absorption perspective. Current Psychology, 43(26), 22560-22577.
- Thornton, G. (2019). TómtắtbáocáoKhảosátngànhDịchvụKháchsạnthườngniên, năm 2018 [Annual Hospitality Industry Survey Report Summary, 2018]. Việt Nam: Công ty TNHH Grant Thornton.
- Van Nuenen, T., & Scarles, C. (2021). Advancements in technology and digital media in tourism. Tourist Studies, 21(1), 119-132.
- Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204.
- Wang, S. C., Lii, Y. S., Sy, E., & Fang, K. T. (2008). A study on the continuous adoption intention model of information systems — cognitive process, emotional states, and belief bases. In Proceedings of 2008 International Conference on Service Systems and Service Management (pp. 1-7).
- Wang, Y., Wang, S., Wang, J., Wei, J., & Wang, C. (2020). An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model. Transportation, 47(1), 397-415.
- Wibowo, A., Saptono, A., Narmaditya, B. S., Effendi, M. S., Mukhtar, S., Suparno, & Shafiai, M. H. M. (2024). Using technology acceptance model to investigate digital business intention among Indonesian students. Cogent Business & Management, 11(1), 2314253.
- Zheng, J., & Li, S. (2020). What drives students’ intention to use tablet computers: An extended technology acceptance model. International Journal of Educational Research, 102, 101612.