DOES EMOTION MATTER? GEN Z’S AUGMENTED REALITY INTENTION IN TOURISM
DOI:
https://doi.org/10.35631/JTHEM.1144014Keywords:
Augmented Reality, Perceived Enjoyment, Phygital Tourism, Self-Efficacy, Technology Acceptance ModelAbstract
Digital transformation is changing how tourists search for destinations, and one of the most compelling tools is Augmented Reality (AR), which combines the physical with the digital to form the immersion of phygital tourism experiences. However, even with significant technological improvements, AR in tourism has not been widely adopted, and it can be assumed that the current models fail to include the essential emotional aspects that can affect the behaviour of users. Thus, using Technology Acceptance Model as the theoretical foundation, this study incorporates perceived enjoyment as an intermediate emotional factor between cognitive (usefulness and ease of use) and psychological (self-efficacy) antecedents to intention of tourists in using AR. A questionnaire was used to collect data from Generation Z travellers and analysed using Partial Least Squares Structural Equation Modelling. The results indicate that enjoyment is a major facilitator of perceived usefulness, confidence, ease of use, and behavioural intention.
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Alam, S. S., Masukujjaman, M., Susmit, S., Susmit, S., & Aziz, H. A. (2022). Augmented reality adoption intention among travel and tour operators in Malaysia: Mediation effect of value alignment. Journal of Tourism Futures, 10 (2), 185-204. https://doi.org/10.1108/JTF-03-2021-0072
Alsomali, S. (2023). Exploring academics’ perspectives related to the adoption of Augmented Reality applications within an e-learning environment in Higher Education institutions: The role of AR self-efficacy, innovation resistance, perceived AR fatigue and technology involve. Proceedings of the International Conference on Modern Research in Education Teaching and Learning, 1(1), 33–45. https://doi.org/10.33422/icmetl.v1i1.40
Arghashi, V., & Yuksel, C. A. (2021). Interactivity, Inspiration, and Perceived Usefulness! How retailers’ AR-apps improve consumer engagement through flow. Journal of Retailing and Consumer Services, 64, 102756. https://doi.org/10.1016/j.jretconser.2021.102756
Bahri-Ammari, N., Soliman, M., & Salah, O. B. (2022). The impact of employer brand on job seekers’ attitudes and intentions: the moderating role of value congruence and social media. Corporate Reputation Review. https://doi.org/10.1057/s41299-022-00154-8
Bary, M. N. A. (2017). Robust regression diagnostic for detecting and solving multicollinearity and outlier problems: Applied study by using financial data. Applied Mathematical Sciences, 11, 601–622. https://doi.org/10.12988/ams.2017.7253
Bretos, M. A., Ibáñez-Sánchez, S., & Orús, C. (2023). Applying virtual reality and augmented reality to the tourism experience: a comparative literature review. Spanish Journal of Marketing - ESIC, 28(3), 287–309. https://doi.org/10.1108/sjme-03-2023-0052
Bridgwater, M. A., Klaunig, M. J., Petti, E., Pitts, S. C., Rouhakhtar, P. R., Ered, A., ... & Schiffman, J. (2023). The influence of psychotic-like experiences on intent to seek treatment: Findings from a multi-site community survey of mental health experiences. Schizophrenia research, 260, 30-36. https://doi.org/10.1016/j.schres.2023.07.028
Bujang, M. A., Omar, E. D., Foo, D. H. P., & Hon, Y. K. (2024). Sample size determination for conducting a pilot study to assess reliability of a questionnaire. Restorative dentistry & endodontics, 49(1). https://doi.org/10.5395/rde.2024.49.e3
Cherry, K. (2020). The pros and cons of longitudinal research. https://www.verywellmind.com/what-is-longitudinal-research-2795335
Chin, W. W. (2010). How to write up and report PLS analyses. In V. Esposito Vinzi, W. W. Chin, J. Henseler & H. Wang (Eds.), Handbook of partial least squares: Concepts, methods and applications in marketing and related fields (pp. 655-690). Springer. https://doi.org/10.1007/978-3-540-32827-8_29
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates. https://utstat.utoronto.ca/brunner/oldclass/378f16/readings/CohenPower.pdf
Cranmer, E. E., tom Dieck, M. C., & Fountoulaki, P. (2020). Exploring the value of augmented reality for tourism. Tourism Management Perspectives, 35, 100672. https://doi.org/10.1016/j.tmp.2020.100672
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/10.2307/249008
Deng, B., Xu, H., & Lei, Z. (2025). From phygital experience to virtual travel in cultural heritage destination: the role of tourist inspiration. Current Issues in Tourism, 1–22. https://doi.org/10.1080/13683500.2025.2466066
Diaz-Guzmán Verástegui, M., Medina-Quintero, J. M., & Ortiz-Rodriguez, F. (2025). Perceived usefulness and ease of use of e-government to generate trust and intention to use by citizens. Journal of technology management & innovation, 20(1), 49-60. http://dx.doi.org/10.4067/S0718-27242025000100049
Falk, R. F., & Miller, N. B. (1992). A primer for soft modelling. University of Akron Press. file:///C:/Users/Admin/Downloads/PrimerforSoftModeling.pdf
Fornell, C., & Cha, J. (1994). Partial least squares. In R. P. Bogozzi (Eds.), Advanced
methods in marketing research (pp. 52-78). Cambrige: Blackwell. https://www.scirp.org/reference/referencespapers?referenceid=685757
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://www.jstor.org/stable/pdf/3151312.pdf?casa_token=VB2ti2LeXkEAAAAA:5DArZlz26j-rKOLOFBy-ax8RcySVCssiQfWC9IHkr0yCOVNP6aN9pAXded75JBVvKj3mGzBz4zL_EI2tt-2tfLT85CyUNpEn681Eb6Sc9uNKIylcsw8
Franke, G. R., & Sarstedt, M. (2019). Heuristics versus statistics in discriminant validity testing: A comparison of four procedures. Internet Research, Forthcoming. https://www.researchgate.net/profile/Marko-Sarstedt/publication/322900910_Heuristics_versus_statistics_in_discriminant_validity_testing_A_comparison_of_four_procedures/links/5aa685b1aca27291845fe15b/Heuristics-versus-statistics-in-discriminant-validity-testing-A-comparison-of-four-procedures.pdf
Gatto, L., & Bundi, P. (2025). The use of quantitative text analysis in evaluations. In Artificial intelligence and evaluation: Emerging technologies and their implications for evaluation (pp. 144–167).
Gharibi, N., Rudsari, S. M. M., Ali, F., & Ryu, K. (2022). UNDERSTANDING XR TECHNOLOGY ACCEPTANCE BY PHYSICALLY DISABLED TOURISTS IN MUSEUMS. Tourism and Hospitality Management, 28(3), 661–682. https://doi.org/10.20867/thm.28.3.10
Golam Azam, M. (2022). In-depth case interview. In M. R. Islam, N. A. Khan & R. Baikady (Eds.), Principles of social research methodology (pp. 347–364). Springer. https://doi.org/10.1007/978-981-19-5441-2_24
Grasse, K. M., Kreminski, M., Wardrip-Fruin, N., Mateas, M., & Melcer, E. F. (2022). Using Self-Determination Theory to explore Enjoyment of Educational Interactive Narrative Games: A case study of Academical. Frontiers in Virtual Reality, 3. https://doi.org/10.3389/frvir.2022.847120
Hair, J. F., Jr., Celsi, W. M., Money, A. H., Samouel, P., & Page, M. J. (2015). Essentials of business research methods (2nd ed.). Routledge. https://www.researchgate.net/publication/311574685_The_Essentials_of_Business_Research_Methods
Hair, J. F., Jr., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on PLS-SEM. Sage Publications.
Hair, J. F., Jr., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on PLS-SEM. Sage Publications, Incorporated Hair, J. F., Jr., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014b). A primer on PLS-SEM. Sage Publications.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019a). 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
Hair, J. F., Sarstedt, M., & Ringle, C. M. (2019b). Rethinking some of the rethinking of partial least squares. European Journal of Marketing, 53(4), 566-584. https://doi.org/10.1108/EJM-10-2018-0665
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442–458. https://doi.org/10.1108/IMDS-04-2016-0130
Hair, J., Page, M., Brunsveld, N., Merkle, A., & Cleton, N. (2023). Essentials of business research methods (5th ed.). Routledge.
Han, S., Yoon, J.-H., & Kwon, J. (2021). Impact of experiential value of augmented reality: The context of heritage tourism. Sustainability, 13(8), 4147. https://doi.org/10.3390/su13084147
Hasmiana, H., & Syamsuddin, F. R. (2025). The influence of perceived ease of use on behavioral intention through perceived Usefulness as an intervening medium in Digital Payment DANA. JURNAL ECONOMIC RESOURCE, 7(2), 340–346. https://doi.org/10.57178/jer.v7i2.1122
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academic Mark Science, 43, 115–135. 10.1007/s11747-014-0403-8
Huang, Y., & Suo, L. (2024). Influence of the technology acceptance model on customer engagement. Human Behavior, Development and Society, 25(2), 39–49. https://doi.org/10.62370/hbds.v25i2.273288
Hussain, A., Zhiqiang, M., Li, M., Jameel, A., Kanwel, S., Ahmad, S., & Ge, B. (2025). The mediating effects of perceived usefulness and perceived ease of use on nurses’ intentions to adopt advanced technology. BMC Nursing, 24(1). https://doi.org/10.1186/s12912-024-02648-8
Janes, E., & Melendez‐Torres, G. J. (2025). A longitudinal analysis comparing the mental health of children by level of young carer status. Journal of Adolescence, 97(3), 713-731. https://doi.org/10.1002/jad.12448
Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of consumer research, 30(2), 199-218. https://www.jstor.org/stable/pdf/10.1086/376806.pdf
Jiang, C., Phoong, S. W., & Moghavvemi, S. (2025). Cultural odyssey in the metaverse: investigating the impact of virtual technologies on tourist reuse behavior and social sustainability. Humanities and Social Sciences Communications, 12(1). https://doi.org/10.1057/s41599-025-05132-z
Judijanto, L., Uhai, S., & Suri, I. (2024). The influence of business analytics and big data on predictive maintenance and asset management. The Eastasouth Journal of Information System and Computer Science, 1(03), 123-135. https://doi.org/10.58812/esiscs.v1i03
Khlaif Gharaibeh, M., Khlaif Gharaibeh, N., Ayoub Khan, M., Abdel karim Abu-ain, W., & Kasim Alqudah, M. (2021). Intention to Use Mobile Augmented Reality in the Tourism Sector. Computer Systems Science and Engineering, 37(2), 187–202. https://doi.org/10.32604/csse.2021.014902.
Kline, R. B. (2011). Principles and practice of structural equation modelling (3rd ed.). Guilford Press.
Legowo, D., Ismiyati, I., Kurniawan, D., & Sholikah, M. (2025). Enhancing sustainable service quality based on QR-codes: A case study at the archives unit of universitas negeri Semarang. Journal of Curriculum Indonesia, 8(2), 396-410. https://hipkinjateng.org/jurnal/index.php/jci/article/viewFile/152/153
Li, T., & Chen, Y. (2019). Will virtual reality be a double-edged sword? Exploring the moderation effects of the expected enjoyment of a destination on travel intention. Journal of Destination Marketing & Management, 12, 15–26. https://doi.org/10.1016/j.jdmm.2019.02.003
Li, X., Chen, C., Kang, X., & Kang, J. (2022). Research on relevant Dimensions of tourism Experience of Intangible Cultural Heritage Lantern Festival: Integrating generic learning outcomes with the Technology Acceptance Model. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.943277
Liang, L. J., & Elliot, S. (2021). A systematic review of augmented reality tourism research: What is now and what is next? Tourism and Hospitality Research, 21(1), 15–30. https://doi.org/10.1177/1467358420941913
Liao, Y., Wu, W., Le, T. Q., & Phung, T. T. T. (2022). The integration of the Technology Acceptance Model and Value-Based Adoption Model to study the adoption of E-Learning: The Moderating Role of E-WOM. Sustainability, 14(2), 815. https://doi.org/10.3390/su14020815
Mahmoud, A. B., Fuxman, L., Asaad, Y., & Solakis, K. (2024). Exploring new realms or losing touch? Assessing public beliefs about tourism in the metaverse–a big-data approach. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/ijchm-09-2023-1515
Mansoor, T., Malak, M. Z., Bint Wan Puteh, S. E., Aizuddin, A. N., & Banafa, N. S. (2024). Validating an instrument for measuring the awareness and challenges of nursing services accreditation from the healthcare providers in Yemen. Palestinian Medical and Pharmaceutical Journal, 10(4). https://doi.org/10.59049/2790-0231.10.4.2391
Mariani, M., & Baggio, R. (2021). Big data and analytics in hospitality and tourism: a systematic literature review. International Journal of Contemporary Hospitality Management, 34(1), 231–278. https://doi.org/10.1108/ijchm-03-2021-0301
Mohd Dzin, N. H., & Lay, Y. F. (2021). Validity and reliability of adapted self-efficacy scales in Malaysian context using PLS-SEM approach. Education Sciences, 11(11), 676. https://doi.org/10.3390/educsci11110676
Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a world-wide-web context. Information & management, 38(4), 217-230.
Moshfeghyeganeh, S., & Hazari, Z. (2021). Effect of culture on women physicists’ career choice: A comparison of Muslim majority countries and the West. Physical Review Physics Education Research, 17(1), 010114. https://doi.org/10.1103/PhysRevPhysEducRes.17.010114
Musa, H. G., Fatmawati, I., Nuryakin, N., & Suyanto, M. (2024). Marketing research trends using technology acceptance model (TAM): a comprehensive review of researches (2002–2022). Cogent Business & Management, 11(1). https://doi.org/10.1080/23311975.2024.2329375
Neuhofer, B. (2024). Positive tourism experiences for human transformation: a Horizon 2050 paper. Tourism Review. https://doi.org/10.1108/tr-12-2023-0888
Ngala, N. E., Lapalelo, N. B., & Imran, T. (2025). Intrinsic motivation and employee performance improvement in educational organizations. Research Horizon, 5(4), 1437–1450. https://doi.org/10.54518/rh.5.4.2025.740
Nikou, S. A. (2024). Factors influencing student teachers’ intention to use mobile augmented reality in primary science teaching. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12481-w
Nunnally, J. C. (1967). Psychometric theory. McGraw-Hill.
Nunnally, J. C. (1978). An overview of psychological measurement. In B. B. Wolman (Ed.), Clinical diagnosis of mental disorders (pp. 97–146). Springer. https://doi.org/10.1007/978-1-4684-2490-4_4
Or, C. (2024). Thirty-Five Years of the Technology Acceptance Model: Insights from Meta-Analytic Structural Equation Modelling. The Open/Technology in Education Society and Scholarship Association Journal, 4(3), 1–26. https://doi.org/10.18357/otessaj.2024.4.3.66
Oyman, M., Bal, D., & Ozer, S. (2021). Extending the technology acceptance model to explain how perceived augmented reality affects consumers’ perceptions. Computers in Human Behavior, 128, 107127. https://doi.org/10.1016/j.chb.2021.107127
Papakostas, C., Troussas, C., Krouska, A., & Sgouropoulou, C. (2021). Measuring user experience, usability and interactivity of a personalized mobile augmented reality training system. Sensors, 21(11), 3888.
Pradhan, V., & Bhattacharya, S. (2018). The role of displeasure, worry and annoyance on pro-safety intention among young motorcyclists in Pune, India. Indian Journal of Transport Management. https://www.researchgate.net/profile/Vishal-Pradhan-3/publication/332321300_The_Role_of_Displeasure_Worry_and_Annoyance_on_Pro-safety_Intention_Among_Young_Motorcyclists_in_Pune_India/links/5cadd98292851ccd4ac0981a/The-Role-of-Displeasure-Worry-and-Annoyance-on-Pro-safety-Intention-Among-Young-Motorcyclists-in-Pune-India.pdf
Pratisto, E. H., Thompson, N., & Potdar, V. (2022). Immersive technologies for tourism: A systematic review. Journal of Hospitality and Tourism Technology, 24(2), 181–219. https://doi.org/10.1007/s40558-022-00228-7
Purwanto, A., & Sudargini, Y. (2021). Partial least squares structural squation modeling (PLS-SEM) analysis for social and management research: A literature review. Journal of Industrial Engineering & Management Research, 2(4), 114-123. https://doi.org/10.7777/jiemar.v2i4
Rese, A., Baier, D., Geyer-Schulz, A., & Schreiber, S. (2021). How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions. Technological Forecasting and Social Change, 124, 306-319.
Rosli, M. S., Saleh, N. S., Ali, A. M., Bakar, S. A., & Tahir, L. M. (2022). A Systematic Review of the Technology Acceptance Model for the Sustainability of Higher Education during the COVID-19 Pandemic and Identified Research Gaps. Sustainability, 14(18), 11389. https://doi.org/10.3390/su141811389
Salah, F. H., Bahri-Ammari, N., Soliman, M., Hassoumi, I., & Sharma, S. (2025). The nexus between augmented reality experiences and visitor behaviour in tourist destinations. Journal of Hospitality and Tourism Insights. https://doi.org/10.1108/jhti-07-2024-0726
Salam, K. N., Singkeruang, A. W. T. F., Husni, M. F., Baharuddin, B., & Dhita Pratiwi, A. R. (2024). Gen Z marketing strategies: Understanding consumer preferences and building sustainable relationships. Golden Ratio of Mapping Idea and Literature Format, 4(1), 53–77. https://doi.org/10.52970/grmilf.v4i1.351
Sarawak Tribune. (2025, October 13). Gen Zs turn to TikTok for travel inspiration. Sarawak Tribune. https://www.sarawaktribune.com/gen-zs-turn-to-tiktok-for-travel-inspiration/
Sekaran, U., & Bougie, R. (2019). Research methods for business: A skill-building approach (8th ed.). John Wiley & Sons, Inc.
Shamim, N., Gupta, S., & Shin, M. M. (2024). Evaluating user engagement via Metaverse environment through immersive experience for travel and tourism websites. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/ijchm-10-2023-1590
Sharma, P. N., Liengaard, B. D., Hair, J. F., Sarstedt, M., & Ringle, C. M. (2023). Predictive model assessment and selection in composite-based modeling using PLS-SEM: Extensions and guidelines for using CVPAT. European journal of marketing, 57(6), 1662-1677. https://doi.org/10.1108/EJM-08-2020-0636
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European journal of marketing, 53(11), 2322-2347. https://doi.org/10.1108/EJM-02-2019-0189
Song, B. L., Kaur, D., Subramaniam, M., Tee, P. K., Wong, L. C., & Zin, N. a. M. (2024). The adoption of mobile augmented reality in tourism industry: effects on customer engagement, intention to use and usage behaviour. Journal of Tourism and Services, 15(28), 235–252. https://doi.org/10.29036/jots.v15i28.679
Stankov, U., Gretzel, U., & Vujičić, M. D. (2025). AI-powered smartphones and phygital tourism experiences: implications and future research directions. Information Technology & Tourism. https://doi.org/10.1007/s40558-025-00317-3
Subhaktiyasa, P. G. (2024). PLS-SEM for multivariate analysis: A practical guide to educational research using SmartPLS. EduLine: Journal of Education and Learning Innovation, 4(3), 353-365. https://doi.org/10.35877/454RI.eduline2861
Sujit, K. S., & Rajesh, B. K. (2016). Determinants of discretionary investments: Evidence from Indian food industry. SAGE, 6(1), 1-16. https://doi.org/10.1177/2158244016636429
Sukmayasa, I. M., Soza-Parra, J., & Ettema, D. (2025). Determinants of travel mode access for adolescents in developing countries: A literature review. Transport Reviews, 45(2), 194-215. https://doi.org/10.1080/01441647.2024.2435309
Toh, S. Y., Lim, S. L., Kaur, R., & Too, C. T. (2025). Can the leadership sense of duty of Gen Z be bought? Evidence from Malaysian Gen Z students. Business Perspectives and Research, 13(2), 279-290. https://doi.org/110.1177/22785337221119589
Wei, W., Qi, J., & Zhang, L. (2022). Immersive technology: A meta-analysis of augmented/virtual reality applications and their impact on tourism experience. Tourism Management, 91, 104534. https://doi.org/10.1016/j.tourman.2022.104534
Yan, S., Eng, L. G., & Seong, L. C. (2024). Influencing factors of continuous intention to use e-learning system of undergraduates in Guangxi, China: The mediating role of perceived ease of use and perceived usefulness. SAGE Open, 14(4), 1-21. https://doi.org/10.1177/21582440241305231
Yin, C. Z. Y., Jung, T., tom Dieck, M. C., & Lee, M. Y. (2021). Mobile augmented reality heritage applications: Meeting the needs of heritage tourists. Sustainability, 13(5), 2523. https://doi.org/10.3390/su13052523
Yu, J., Kim, S., Hailu, T. B., Park, J., & Han, H. (2023). The effects of virtual reality (VR) and augmented reality (AR) on senior tourists’ experiential quality, perceived advantages, perceived enjoyment, and reuse intention. Current Issues in Tourism, 27(3), 464–478. https://doi.org/10.1080/13683500.2023.2165483
Zhang, K., Wang, J., Zhang, J., Wang, Y., & Zeng, Y. (2024). Exploring the impact of location-based augmented reality on tourists’ spatial behavior, experience, and intention through a field experiment. Tourism Management, 102, 104886. https://doi.org/10.1016/j.tourman.2024.104886
Zhuang, X., Hou, X., Feng, Z., Lin, Z., & Li, J. (2020). Subjective norms, attitudes, and intentions of AR technology use in tourism experience: the moderating effect of millennials. Leisure Studies, 40(3), 392–406. https://doi.org/10.1080/02614367.2020.1843692
