Baby boomers and the intention to use technology in travel planning
DOI:
https://doi.org/10.18089/tms.20260201Keywords:
Technology Acceptance, Travel Planning, Baby Boomer Generation, Generation Cohort TheoryAbstract
This research aimed to analyze the influence of the generational cohort on the intention to use technology in travel planning by the baby boomer generation, exploring important points for maintaining the usability of Information and Communication Technologies (ICT) in this age group. To achieve this objective, structural equation modeling (PLS-SEM) was used on a sample of 155 valid questionnaires from members of the baby boomer generation participating in elderly groups. The results suggest that the generational cohort is an important element to be considered in the intention to use technology in travel planning. Baby boomers are more resistant to adopting new technologies in travel planning, preferring ease and practicality over advanced technological features. In addition, personal innovation and financial cost are determinants for the adoption of technology by baby boomers, while personal influence is not relevant to boost the adoption of technology in tourism by this generation. This study contributes to broadening the debate about the acceptance and intention to use technologies by baby boomers in travel planning and also provides important indications for maintaining the use of ICTs in this age group.
References
Abou-Shouk, M. A., Zoair, N. I., & Abdelhakim, A. S. (2019, July). Exploring the factors predicting M-commerce applications' adoption in tourism and hospitality: evidence from travel agencies, hotels and archaeological sites. In 9th Advances in Hospitality and Tourism Marketing and Management Conference (pp. 132-147), Portsmouth.
Agag, G., & El-Masry, A. A. (2016). Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Computers in Human Behavior, 60, 97–111. https://doi.org/10.1016/j.chb.2016.02.038
Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204-215. https://doi.org/10.1287/isre.9.2.204
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888. https://doi.org/10.1037/0033-2909.84.5.888
Akel, G., & Armağan, E. (2021). Hedonic and utilitarian benefits as determinants of the application continuance intention in location-based applications: The mediating role of satisfaction. Multimedia Tools and Applications, 80(5), 7103-7124. https://doi.org/10.1007/s11042-020-10094-2
Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. International Journal of Information Management, 50, 28-44. https://doi.org/10.1016/j.ijinfomgt.2019.04.008
Alcántara-Pilar, J. M., Blanco-Encomienda, F. J., Armenski, T., & Del Barrio-García, S. (2018). The antecedent role of online satisfaction, perceived risk online, and perceived website usability on the affect towards travel destinations. Journal of Destination Marketing & Management, 9, 20–35. https://doi.org/10.1016/j.jdmm.2017.09.005
Arfi, W. B., Nasr, I. B., Khvatova, T., & Zaied, Y. B. (2021). Understanding acceptance of eHealthcare by IoT natives and IoT immigrants: An integrated model of UTAUT, perceived risk, and financial cost. Technological Forecasting and Social Change, 163, 120437. https://doi.org/10.1016/j.techfore.2020.120437
Bilan, Y., Tovmasyan, G., & Dallakyan, S. (2024). The Impact of Digital Technologies on Tourists' Travel Choices and Overall Experience. Journal of Tourism and Services, 15(29), 153-175. https://doi.org/10.29036/jots.v15i29.805
Box, S., & West, J. (2016). Economic and social benefits of Internet openness (OECD Digital Economy Papers, No. 257). OECD Publishing. https://doi.org/10.1787/5jlwqf2r97g5-en
Buhalis, D. (2020). Technology in tourism-from information communication technologies to eTourism and smart tourism towards ambient intelligence tourism: a perspective article. Tourism Review, 75(1), 267-272. https://doi.org/10.1108/TR-06-2019-0258
Burkett, M. G., & Recuero Virto, N. (2025). Exploring the Role of Innovation and Perceived Security in Contactless Technology Adoption: Evidence from Contactless Travel Services. Journal of Tourism and Services, 16(31), 220-244. https://doi.org/10.29036/e68ww460
Campo-Martínez, S., Garau-Vadell, J. B., & Martínez-Ruiz, M. P. (2010). Factors influencing repeat visits to a destination. The influence of group composition. Tourism Management, 31(6), 862–870. https://doi.org/10.1016/j.tourman.2009.08.013
Chen, C.-F., & Chen, P.-C. (2011). Applying the TAM to travelers' usage intentions of GPS devices. Expert Systems with Applications, 38(5), 6217–6221. https://doi.org/10.1016/j.eswa.2010.11.047
Chen, H., Beaudoin, C. E., & Hong, T. (2017). Securing online privacy: An empirical test on Internet scam victimization, online privacy concerns, and privacy protection behaviors. Computers in Human Behavior, 70, 291-302. https://doi.org/10.1016/j.chb.2017.01.003
Chong, A. Y. L., Chan, F. T., & Ooi, K. B. (2012). Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia. Decision Support Systems, 53(1), 34-43. https://doi.org/10.1016/j.dss.2011.12.001
Chowdhury, S., Rodriguez-Espindola, O., Dey, P., & Budhwar, P. (2023). Blockchain technology adoption for managing risks in operations and supply chain management: Evidence from the UK. Annals of Operations Research, 327(1), 539–574. https://doi.org/10.1007/s10479-021-04487-1
Chung, C., Li, J., Chung, N., & Shin, S. (2024). The impact of smartphone usage on domestic travelers' existential authenticity and behavioral perception toward island destinations. A cross-country comparison of Hainan Island and Jeju Island. Journal of Destination Marketing & Management, 31, 100846. https://doi.org/10.1016/j.jdmm.2023.100846
Ciftci, O., Berezina, K., & Kang, M. (2021, January). Effect of personal innovativeness on technology adoption in hospitality and tourism: meta-analysis. In Information and Communication Technologies in Tourism 2021: Proceedings of the ENTER 2021 eTourism Conference, January 19–22, 2021 (pp. 162-174). Cham: Springer International Publishing.
Collado-Agudo, J., Herrero-Crespo, Á., & San Martín-Gutiérrez, H. (2023). The adoption of a smart destination model by tourism companies: An ecosystem approach. Journal of Destination Marketing & Management, 28, 100783. https://doi.org/10.1016/j.jdmm.2023.100783
Collins, P. R., & Waugh, R. F. (1998). Teachers' receptivity to a proposed system‐wide educational change. Journal of Educational Administration, 36(2), 183-199. https://doi.org/10.1108/09578239810204381
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
De Vos, J. (2019). Satisfaction-induced travel behaviour. Transportation Research Part F: Traffic Psychology and Behaviour, 63, 12–21. https://doi.org/10.1016/j.trf.2019.03.001
Domínguez Vila, T., & Darcy, S. (2025). Beyond technical website compliance: Identifying and assessing accessible tourism value chain information content on national tourism organisation websites. Tourism Management Perspectives, 55, 101332. https://doi.org/10.1016/j.tmp.2024.101332
Eisingerich, A. B., Marchand, A., Fritze, M. P., & Dong, L. (2019). Hook vs. hope: How to enhance customer engagement through gamification. International Journal of Research in Marketing, 36(2), 200-215. https://doi.org/10.1016/j.ijresmar.2019.02.003
Filieri, R., Lin, Z., Pino, G., Alguezaui, S., & Inversini, A. (2021). The role of visual cues in eWOM on consumers' behavioral intention and decisions. Journal of Business Research, 135, 663–675. https://doi.org/10.1016/j.jbusres.2021.06.055
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://doi.org/10.2307/3151312
Foroughi, B., Iranmanesh, M., & Hyun, S. S. (2019). Understanding the determinants of mobile banking continuance usage intention. Journal of Enterprise Information Management, 32(6), 1015-1033. https://doi.org/10.1108/JEIM-10-2018-0237
Gao, Y., Rasouli, S., Timmermans, H., & Wang, Y. (2018). Trip stage satisfaction of public transport users. A reference based model incorporating trip attributes, perceived service quality, psychological disposition and difference tolerance. Transportation Research Part A: Policy and Practice, 118, 759–775. https://doi.org/10.1016/j.tra.2018.10.029
Gärling, T. (2026). A conceptual analysis of the role of attitudes and values in car use reduction interventions. Transportation Research Part A: Policy and Practice. Advance online publication. https://doi.org/10.1016/j.tra.2026.104930
Goo, J., Huang, C. D., Yoo, C. W., & Koo, C. (2022). Smart tourism technologies' ambidexterity: balancing tourist's worries and novelty seeking for travel satisfaction. Information Systems Frontiers, 1-20. https://doi.org/10.1007/s10796-021-10233-6
Guerreiro, M., Pinto, P., Ramos, C. M., Matos, N., Golestaneh, H., Sequeira, B., Pereira, L. N., Agapito, D., Martins, R., & Wijkesjö, M. (2024). The online destination image as portrayed by the user-generated content on social media and its impact on tourists' engagement. Tourism & Management Studies, 20(4), 1-15. https://doi.org/10.18089/tms.20240401
Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123. https://doi.org/10.1504/IJMDA.2017.087624
Hameed, I., Akram, U., Khan, Y., Khan, N. R., & Hameed, I. (2024). Exploring consumer mobile payment innovations. An investigation into the relationship between coping theory factors, individual motivations, social influence and word of mouth. Journal of Retailing and Consumer Services, 77, 103687. https://doi.org/10.1016/j.jretconser.2023.103687
Han, S., & Yang, H. (2018). Understanding adoption of intelligent personal assistants: A parasocial relationship perspective. Industrial Management & Data Systems, 118(3), 618-636. https://doi.org/10.1108/IMDS-05-2017-0214
He, K., Ye, L., Li, F., Chang, H., Wang, A., Luo, S., & Zhang, J. (2022). Using cognition and risk to explain the intention-behavior gap on bioenergy production: Based on machine learning logistic regression method. Energy Economics, 108, 105885. https://doi.org/10.1016/j.eneco.2022.105885
Hew, J.-J., Leong, L.-Y., Tan, G. W.-H., Lee, V.-H., & Ooi, K.-B. (2018). Mobile social tourism shopping: A dual-stage analysis of a multi-mediation model. Tourism Management, 66, 121–139. https://doi.org/10.1016/j.tourman.2017.10.005
Hoque, R., & Sorwar, G. (2017). Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. International Journal of Medical Informatics, 101, 75-84. https://doi.org/10.1016/j.ijmedinf.2017.02.002
Huang, C. D., Goo, J., Nam, K., & Yoo, C. W. (2017). Smart tourism technologies in travel planning: The role of exploration and exploitation. Information & Management, 54(6), 757–770. https://doi.org/10.1016/j.im.2016.11.010
Hui, T. K., Wan, D., & Ho, A. (2007). Tourists' satisfaction, recommendation and revisiting Singapore. Tourism Management, 28(4), 965–975. https://doi.org/10.1016/j.tourman.2006.08.008
IBGE, 2022. População cresce, mas número de pessoas com menos de 30 anos cai 5,4% de 2012 a 2021. Retrieved on 12.01.2023 from https://agenciadenoticias.ibge.gov.br/agencia-noticias/2012-agencia-de-noticias/noticias/34438-populacao-cresce-mas-numero-de-pessoas-com-menos-de-30-anos-cai-5-4-de-2012-a-2021
Jászberényi, M., Ásványi, K., Csiszár, C., & Kökény, L. (2024). Demographic and social differences in autonomous vehicle technology acceptance in Hungary. Journal of Engineering and Technology Management, 72, 101813. https://doi.org/10.1016/j.jengtecman.2024.101813
Kang, Y. S., & Lee, H. (2010). Understanding the role of an IT artifact in online service continuance: An extended perspective of user satisfaction. Computers in Human Behavior, 26(3), 353–364. https://doi.org/10.1016/j.chb.2009.11.006
Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2) 183-213. https://doi.org/10.2307/249751
Kieanwatana, K., & Vongvit, R. (2024). Virtual reality in tourism: The impact of virtual experiences and destination image on the travel intention. Results in Engineering, 24, 103650. https://doi.org/10.1016/j.rineng.2024.103650
Kock, F., Berbekova, A., & Assaf, A. G. (2021). Understanding and managing the threat of common method bias: Detection, prevention and control. Tourism Management, 86, 104330. https://doi.org/10.1016/j.tourman.2021.104330
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration (ijec), 11(4), 1-10. https://doi.org/10.1007/978-3-319-64069-3_11
Kozak, M. (2001). Repeaters' behavior at two distinct destinations. Annals of Tourism Research, 28(3), 784–807. https://doi.org/10.1016/S0160-7383(00)00078-5
Lee, E., Chung, N., & Koo, C. (2023). Exploring touristic experiences on destination image modification. Tourism Management Perspectives, 47, 101114. https://doi.org/10.1016/j.tmp.2023.101114
Leibenstein, H. (1950). Bandwagon, snob, and Veblen effects in the theory of consumers' demand. The Quarterly Journal of Economics, 64(2), 183-207. https://doi.org/10.2307/1882692
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. https://doi.org/10.1016/j.im.2014.07.004
Li, X., Li, X. R., & Hudson, S. (2013). The application of generational theory to tourism consumer behavior. An American perspective. Tourism Management, 37, 147–164. https://doi.org/10.1016/j.tourman.2013.01.015
Lissitsa, S., Zychlinski, E., & Kagan, M. (2022). The Silent Generation vs Baby Boomers: Socio-demographic and psychological predictors of the "gray" digital inequalities. Computers in Human Behavior, 128, 107098. https://doi.org/10.1016/j.chb.2021.107098
Lo, W. H., & Cheng, K. L. B. (2020). Does virtual reality attract visitors? The mediating effect of presence on consumer response in virtual reality tourism advertising. Information Technology & Tourism, 22(4), 537-562. https://doi.org/10.1007/s40558-020-00190-2
Lu, J., Liu, C., Yu, C. S., & Wang, K. (2008). Determinants of accepting wireless mobile data services in China. Information & Management, 45(1), 52-64. https://doi.org/10.1016/j.im.2007.11.002
Lu, J., Yao, J. E., & Yu, C. S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245-268. https://doi.org/10.1016/j.jsis.2005.07.003
Luarn, P., & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873-891. https://doi.org/10.1016/j.chb.2004.03.003
Lyons, S. T., Duxbury, L., & Higgins, C. (2007). An empirical assessment of generational differences in basic human values. Psychological Reports, 101(2), 339-352. https://doi.org/10.2466/pr0.101.2.339-352
Magsamen-Conrad, K., & Dillon, J. M. (2020). Mobile technology adoption across the lifespan: A mixed methods investigation to clarify adoption stages, and the influence of diffusion attributes. Computers in Human Behavior, 112, 106456. https://doi.org/10.1016/j.chb.2020.106456
Min, S., So, K. K. F., & Jeong, M. (2019). Consumer adoption of the Uber mobile application: Insights from diffusion of innovation theory and technology acceptance model. Journal of Travel & Tourism Marketing, 36(7), 770-783. https://doi.org/10.1080/10548408.2018.1507866
Moqbel, M., Bartelt, V., Al-Suqri, M., & Al-Maskari, A. (2017). Does privacy matter to millennials? The case for personal cloud. Journal of Information Privacy and Security, 13(1), 17-33. https://doi.org/10.1080/15536548.2016.1243854
Morris, M. G., & Venkatesh, V. (2000). Age differences in technology adoption decisions: Implications for a changing work force. Personnel Psychology, 53(2), 375-403. https://doi.org/10.1108/JOCM-12-2024-0767
Moschis, G. P. (1994). Marketing strategies for the mature market. Greenwood Publishing Group.
Mun, Y. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management, 43(3), 350-363. https://doi.org/10.1016/j.im.2013.02.006
Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2018). The moderating role of device type and age of users on the intention to use mobile shopping applications. Technology in Society, 53, 79-90. https://doi.org/10.1016/j.techsoc.2018.01.003
Nicolau, J. L., Rodríguez-Sánchez, C., & Ruiz-Moreno, F. (2024). A motivation-based study to explain accommodation choice of senior tourists: Hotel or Airbnb. International Journal of Hospitality Management, 123, 103911. https://doi.org/10.1016/j.ijhm.2024.103911
Oghuma, A. P., Libaque-Saenz, C. F., Wong, S. F., & Chang, Y. (2016). An expectation-confirmation model of continuance intention to use mobile instant messaging. Telematics and Informatics, 33(1), 34-47. https://doi.org/10.1016/j.tele.2015.05.006
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469. https://doi.org/10.2307/3150499
Orden-Mejía, M., Carvache-Franco, M., Huertas, A., Carvache-Franco, O., & Carvache-Franco, W. (2025). Analysing how AI-powered chatbots influence destination decisions. PLOS ONE, 20(3), e0319463. https://doi.org/10.1371/journal.pone.0319463
Pereira, T., Limberger, P. F., & Ardigó, C. M. (2021). The moderating effect of the need for interaction with a service employee on purchase intention in chatbots. Telematics and Informatics Reports, 1, 100003. https://doi.org/10.1016/j.teler.2022.100003
Phaosathianphan, N., & Leelasantitham, A. (2021). An intelligent travel technology assessment model for destination impacts of tourist adoption. Tourism Management Perspectives, 40, 100882. https://doi.org/10.1016/j.tmp.2021.100882
Polites, G. L., & Karahanna, E. (2012). Shackled to the status quo: The inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS Quarterly, 21-42. https://doi.org/10.2307/41410404
Porter, C. E., & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59(9), 999-1007. https://doi.org/10.1016/j.jbusres.2006.06.003
Qiu, L., Li, X., & Choi, S.-h. (2024). Exploring the influence of short video platforms on tourist attitudes and travel intention. A social–technical perspective. Journal of Destination Marketing & Management, 31, 100826. https://doi.org/10.1016/j.jdmm.2023.100826
Quester, P., Neal, C., Pettigrew, S., Grimmer, M. R., Davis, T., & Hawkins, D. (2007). Consumer behaviour: Implications for Marketing Strategy. McGraw-Hill.
Rahimizhian, S., Ozturen, A., & Ilkan, M. (2020). Emerging realm of 360-degree technology to promote tourism destination. Technology in Society, 63, 101411. https://doi.org/10.1016/j.techsoc.2020.101411
Ramlall, S., Hattingh, M., & Van Deventer, P. (2020, September). Baby Boomers' intention to use branch or digital banking channels in South Africa: An exploratory study. In Conference of the South African Institute of Computer Scientists and Information Technologists 2020 (pp. 74-84).
Recuero Virto, N., Aldas Manzano, J., García-Madariaga, J., & Blasco López, F. (2024). Unveiling the Instagram effect. Decoding factors influencing visiting intentions of superstar Spanish museums. Journal of Destination Marketing & Management, 33, 100881. https://doi.org/10.1016/j.jdmm.2024.100881
Reyes-Menendez, A., Saura, J. R., & Martinez-Navalon, J. G. (2019). The impact of e-WOM on hotels management reputation: exploring tripadvisor review credibility with the ELM model. Ieee Access, 7, 68868-68877. https://doi.org/10.1109/ACCESS.2019.2919030
Richards , G. (2025). Journeys in the network society: spiders, ants and archipelagos . Revista Brasileira De Pesquisa Em Turismo, 19, 3213 . https://doi.org/10.7784/rbtur.v19.3213
Roca, J. C., Chiu, C.-M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of Human-Computer Studies, 64(8), 683–696. https://doi.org/10.1016/j.ijhcs.2006.01.003
Soares, A. M., Casais, B., Calvo-Porral, C., & Oliveira, A. (2025). The' Insta' effect on the intention to visit a destination: a case for conspicuous consumption?. Tourism & Management Studies, 21(2), 1-11. https://doi.org/10.18089/tms.20250201
Sancho-Esper, F., Ostrovskaya, L., Rodriguez-Sanchez, C., & Campayo-Sanchez, F. (2023). Virtual reality in retirement communities: Technology acceptance and tourist destination recommendation. Journal of Vacation Marketing, 29(2), 275-290. https://doi.org/10.1177/13567667221080567
Santosa, A. D., Taufik, N., Prabowo, F. H. E., & Rahmawati, M. (2021). Continuance intention of baby boomer and X generation as new users of digital payment during COVID-19 pandemic using UTAUT2. Journal of Financial Services Marketing, 26(4), 259-273. https://doi.org/10.1057/s41264-021-00104-1
Schewe, C. D., & Meredith, G. (2004). Segmenting global markets by generational cohorts: Determining motivations by age. Journal of Consumer Behaviour: An International Research Review, 4(1), 51-63. https://doi.org/10.1002/cb.157
Seow, A. N., Foroughi, B., & Choong, Y. O. (2024). Tourists' satisfaction, experience, and revisit intention for wellness tourism. E word-of-mouth as the mediator. SAGE Open, 14(3), 21582440241274049. https://doi.org/10.1177/21582440241274049
Seyfi, S., Lee, C., Jo, Y., & Kim, M. J. (2025). Generational differences in adopting AI-generated travel advice: What drives trust and reduces resistance? Tourism Management Perspectives, 57, 101364. https://doi.org/10.1016/j.tmp.2025.101364
Shi, Y.-c., & Lee, U.-K. (2021). The impact of restaurant recommendation information and recommendation agent in the tourism website on the satisfaction, continuous usage, and destination visit intention. SAGE Open, 11(4), 21582440211046947. https://doi.org/10.1177/21582440211046947
Shin, H., & Baek, S. (2023). Unequal diffusion of innovation: Focusing on the digital divide in using smartphones for travel. Journal of Hospitality and Tourism Management, 55, 277–281. https://doi.org/10.1016/j.jhtm.2023.04.012
Sorcaru, I. A., Muntean, M.-C., Manea, L.-D., & Nistor, R. (2025). Voice assistants in the tourism customer journey: From knowledge and decision-making to ecotourism loyalty in family vacations. Journal of Innovation & Knowledge, 10(6), 100833. https://doi.org/10.1016/j.jik.2025.100833
Sun, H., Jing, P., Liu, Y., Wang, D., Ye, J., Du, W., Ma, H., Wang, C., & Zhang, S. (2025). How do older adults cross the digital divide and enjoy the benefits of ride-hailing services with the collision of the aging and digital society in China? Telematics and Informatics, 97, 102239. https://doi.org/10.1016/j.tele.2025.102239
Talukder, M. S., Sorwar, G., Bao, Y., Ahmed, J. U., & Palash, M. A. S. (2020). Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach. Technological Forecasting and Social Change, 150, 119793. https://doi.org/10.1016/j.techfore.2019.119793
Tung, V. W. S., & Ritchie, J. B. (2011). Exploring the essence of memorable tourism experiences. Annals of Tourism Research, 38(4), 1367-1386. https://doi.org/10.1016/j.annals.2011.03.009
Tussyadiah, I. P., Wang, D., Jung, T. H., & Tom Dieck, M. C. (2018). Virtual reality, presence, and attitude change: Empirical evidence from tourism. Tourism Management, 66, 140-154. https://doi.org/10.1016/j.tourman.2017.12.003
Twenge, J. M., Campbell, S. M., Hoffman, B. J., & Lance, C. E. (2010). Generational differences in work values: Leisure and extrinsic values increasing, social and intrinsic values decreasing. Journal of Management, 36(5), 1117-1142. https://doi.org/10.1177/0149206309352246
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178. https://doi.org/10.2307/41410412
Wamuyu, P. K. (2017). Bridging the digital divide among low-income urban communities: Leveraging use of Community Technology Centers. Telematics and Informatics, 34(8), 1709–1720. https://doi.org/10.1016/j.tele.2017.08.004
Wang, X., & Yu, X. (2024). Art students' technostress, perceived usefulness, satisfaction, and continuance intention to use mobile educational applications. SAGE Open, 14(2), 21582440241260206. https://doi.org/10.1177/21582440241260206
Wang, Y., Genc, E., & Peng, G. (2020). Aiming the mobile targets in a cross-cultural context: Effects of trust, privacy concerns, and attitude. International Journal of Human–Computer Interaction, 36(3), 227–238. https://doi.org/10.1080/10447318.2019.1625571
Weng, G. S., Zailani, S., Iranmanesh, M., & Hyun, S. S. (2017). Mobile taxi booking application service's continuance usage intention by users. Transportation Research Part D: Transport and Environment, 57, 207–216. https://doi.org/10.1016/j.trd.2017.07.023
Williams, K. C., & Page, R. A. (2011). Marketing to the generations. Journal of Behavioral Studies in Business, 3(1), 37-53.
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729. https://doi.org/10.1016/j.im.2004.07.001
Wu, X., & Lai, I. K. W. (2022). The use of 360-degree virtual tours to promote mountain walking tourism: Stimulus–organism–response model. Information Technology & Tourism, 24(1), 85-107. https://doi.org/10.1007/s40558-021-00218-1
Yan, C., Siddik, A. B., Akter, N., & Dong, Q. (2023). Factors influencing the adoption intention of using mobile financial service during the COVID-19 pandemic: The role of FinTech. Environmental Science and Pollution Research, 30(22), 61271-61289. https://doi.org/10.1007/s11356-021-17437-y
Yang, K., & Jolly, L. D. (2008). Age cohort analysis in adoption of mobile data services: gen Xers versus baby boomers. Journal of Consumer Marketing, 25(5), 272-280. https://doi.org/10.1108/07363760810890507
Yao, Y., Chen, J., & Chen, Y. (2025). Chinese senior travelers encounter with smart tourism: why are they falling into the travel digital divide? Journal of Hospitality and Tourism Management, 65, 101336. https://doi.org/10.1016/j.jhtm.2025.101336
Yuan, L., & Marzuki, A. (2024). What keeps historical theme park visitors coming? Research based on expectation confirmation theory. Frontiers in Psychology, 15, 1293638. https://doi.org/10.3389/fpsyg.2024.1293638
Zhang, T., Tao, D., Qu, X., Zhang, X., Lin, R., & Zhang, W. (2019). The roles of initial trust and perceived risk in public's acceptance of automated vehicles. Transportation Research Part C: Emerging Technologies, 98, 207-220. https://doi.org/10.1016/j.trc.2018.11.018
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