Virtual campus tours as strategic marketing communication: The role of personal innovativeness

Authors

  • Kurnadi Gularso Universitas Bunda Mulia
  • Henilia Yulita Universitas Multimedia Nusantara
  • Michael Christian Universitas Bunda Mulia
  • Sajjad Hussain NUST Business School Islamabad

DOI:

https://doi.org/10.56587/bemi.v4i1.151

Keywords:

virtual campus tours, behavioral intention, perceived ease of use, perceived enjoyment, personal innovativeness in technology

Abstract

Background: Virtual campus tours (VCTs) have emerged as an important digital marketing communication tool in higher education, enabling universities to engage prospective students through immersive and accessible virtual experiences. However, empirical evidence regarding the factors influencing prospective students’ intention to use VCTs remains limited.

Purpose: This study examines the effects of Personal Innovativeness in Information Technology (PIIT), Perceived Ease of Use (PEOU), and Perceived Enjoyment (PE) on prospective students’ Behavioral Intention (BI) to use VCTs.

Method: A quantitative study was conducted using an online survey involving 108 prospective undergraduate students in Greater Jakarta, Indonesia. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS. 

Findings: The results reveal that PIIT has a significant positive effect on PEOU. Furthermore, PEOU positively influences both PE and BI, while PE has a strong positive effect on BI. In addition, PE partially mediates the relationship between PEOU and BI. These findings suggest that designing VCTs that are both easy to use and enjoyable can effectively enhance prospective students’ intention to adopt virtual campus tours.

References

Al-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A., & Habibi, A. (2023). Extending the Technology Acceptance Model (TAM) to Predict University Students’ Intentions to Use Metaverse-Based Learning Platforms. Education and Information Technologies, 28(11), 15381–15413. https://doi.org/10.1007/s10639-023-11816-3

Alshammari, S. H., & Alshammari, M. H. (2024). Modelling the effects of perceived system quality and personal innovativeness on the intention to use metaverse: a structural equation modelling approach. PeerJ Computer Science, 10(e2331), 1–22. https://doi.org/10.7717/peerj-cs.2331

Alyoussef, I. Y. (2021a). E-Learning acceptance: The role of task–technology fit as sustainability in higher education. Sustainability, 13(11), 6450.. https://doi.org/10.3390/su13116450

Alyoussef, I. Y. (2021b). Massive open online course (MOOCs) acceptance: The role of task-technology fit (TTF) for higher education sustainability. Sustainability, 13(13), 7374.. https://doi.org/10.3390/su13137374

Alyoussef, I. Y. (2023). Acceptance of e-learning in higher education: The role of task-technology fit with the information systems success model. Heliyon, 9(3). https://doi.org/10.1016/j.heliyon.2023.e13751

Bapat, G. S., Mahale, P., Kumar, A., & Srinivasan, R. (2021). The Impact of Television Advertisements on Student Decision-Making Process for College Admission: An exploratory study in India. Asia Pacific Journal of Health Management, 16(4), 266–273. https://doi.org/10.24083/apjhm.v16i4.1299

Cabero-Almenara, J., Llorente-Cejudo, C., Palacios-Rodríguez, A., & Gallego-Pérez, Ó. (2023). Degree of acceptance of virtual reality by health sciences students. International Journal of Environmental Research and Public Health, 20(8), 5571. https://doi.org/10.3390/ijerph20085571

Chahal, J., & Rani, N. (2022). Exploring the acceptance for e-learning among higher education students in India: combining technology acceptance model with external variables. Journal of Computing in Higher Education, 34(3), 844–867. https://doi.org/10.1007/s12528-022-09327-0

Chang, S., & Suh, J. (2025). The Impact of Digital Storytelling on Presence, Immersion, Enjoyment, and Continued Usage Intention in VR-Based Museum Exhibitions. In Sensors, 25(9), 2914. https://doi.org/10.3390/s25092914

Chen, L., Wu, X., Liu, Y., Hu, Z., Chen, X., & Zhang, Z. (2025). Integrating TAM–ISSM–SOR framework to explore how virtual tourism experience influences tourists’ travel intention. Scientific Reports, 15(1), 38826. https://doi.org/10.1038/s41598-025-24793-z

Christian, M., Nan, G., Dewantara, Y. F., Geng, B., Muzammil, O. M., & Gularso, K. (2025a). Imagination Over Intelligence? Assessing Determinants of Willingness to Accept AI-Based Tourism Advertising in the Chinese Digital Landscape. 2025 International Conference on Information Management and Technology (ICIMTech), 788–793. https://doi.org/10.1109/ICIMTech67074.2025.11265008

Christian, M., Pardede, R., Dewantara, Y. F., Nan, G., Geng, B., & Irlandra, F. (2025b). Impact of AI-Generated Tourism Ads on Consumer Intent in Indonesian Market Using PLS-SEM. 2025 4th International Conference on Creative Communication and Innovative Technology (ICCIT), 1–7. https://doi.org/10.1109/ICCIT65724.2025.11167619

Christian, M., Pardede, R., Yulita, H., Dewi, Y. K., Wibowo, S., & Sunarno, S. (2024). Anxiety-Related AI Configuration and AI Usage Behavior Among Lecturers: Gender’s Moderating Role. 2024 IEEE International Conference on Control & Automation, Electronics, Robotics, Internet of Things, and Artificial Intelligence (CERIA), 1–6. https://doi.org/10.1109/CERIA64726.2024.10914840

Daniel, M., Gottlieb, M., Wooten, D., Stojan, J., Haas, M. R. C., Bailey, J., Evans, S., Lee, D., Goldberg, C., Fernandez, J., Jassal, S. K., Rudolf, F., Guluma, K., Lander, L., Pott, E., Goldhaber, N. H., Thammasitboon, S., Uraiby, H., Grafton-Clarke, C., … Dolmans, D. (2022). Virtual interviewing for graduate medical education recruitment and selection: A BEME systematic review: BEME Guide No. 80. Medical Teacher, 44(12), 1313–1331. https://doi.org/10.1080/0142159X.2022.2130038

De Canio, F., Martinelli, E., Peruzzini, M., & Cavallaro, S. (2022). Experiencing a Food Production Site Using Wearable Devices: The Indirect Impact of Immersion and Presence in VR Tours. In Sustainability 14(5), 3064. https://doi.org/10.3390/su14053064

Deng, X., & Yu, Z. (2023). An extended hedonic motivation adoption model of TikTok in higher education. Education and Information Technologies, 28(10), 13595–13617. https://doi.org/10.1007/s10639-023-11749-x

Devisakti, A., & Muftahu, M. (2022). Digitalization in higher education: does personal innovativeness matter in digital learning? Interactive Technology and Smart Education, 20(2), 257–270. https://doi.org/10.1108/ITSE-10-2021-0182

Di Natale, A. F., Repetto, C., Costantini, G., Riva, G., Bricolo, E., & Villani, D. (2024). Learning in the Metaverse: Are University Students Willing to Learn in Immersive Virtual Reality? Cyberpsychology, Behavior, and Social Networking, 27(1), 28–36. https://doi.org/10.1089/cyber.2022.0395

Drew, Z. B., Setiawan, J., Fernando, E., Faza, A., Fianty, M. I., Winanti, W., & Murad, D. F. (2025). Interactive 360° Virtual Tour for Dark Tourism Promotion: A Digital Heritage Case Study of Makam Syekh Mubarok. 2025 8th International Conference on New Media Studies (CONMEDIA), 198–203. https://doi.org/10.1109/CONMEDIA67140.2025.11290285

Feng, J., Yu, B., Tan, W. H., Dai, Z., & Li, Z. (2025). Key factors influencing educational technology adoption in higher education: A systematic review. PLOS Digital Health, 4(4), e0000764. https://doi.org/10.1371/journal.pdig.0000764

Fussell, S. G., & Truong, D. (2022). Using virtual reality for dynamic learning: an extended technology acceptance model. Virtual Reality, 26(1), 249–267. https://doi.org/10.1007/s10055-021-00554-x

Granić, A. (2022). Educational Technology Adoption: A systematic review. Education and Information Technologies, 27(7), 9725–9744. https://doi.org/10.1007/s10639-022-10951-7

Hair, J., Hult, G. T. M., Ringle, C., Sarstedt, M., Danks, N., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A workbook. Springer Cham. https://doi.org/10.1007/978-3-030-80519-7

Haowen, J., Vimalesvaran, S., Myint Kyaw, B., & Tudor Car, L. (2021). Virtual reality in medical students’ education: a scoping review protocol. BMJ Open, 11(5). https://doi.org/10.1136/bmjopen-2020-046986

Humida, T., Al Mamun, M. H., & Keikhosrokiani, P. (2022). Predicting behavioral intention to use e-learning system: A case-study in Begum Rokeya University, Rangpur, Bangladesh. Education and Information Technologies, 27(2), 2241–2265. https://doi.org/10.1007/s10639-021-10707-9

Iswari, N. M. S., & Afriliana, N. (2025). Enhancing Aspect-Based Sentiment Analysis in Tourism Reviews Through Hybrid Data Augmentation. Journal of Applied Data Sciences, 6(3). https://doi.org/10.47738/jads.v6i3.842

Jiang, J., & Fryer, L. K. (2024). The effect of virtual reality learning on students’ motivation: A scoping review. Journal of Computer Assisted Learning, 40(1), 360–373. https://doi.org/10.1111/jcal.12885

Jo, H., & Park, D.-H. (2023). Affordance, usefulness, enjoyment, and aesthetics in sustaining virtual reality engagement. Scientific Reports, 13(1), 15097. https://doi.org/10.1038/s41598-023-42113-1

Kang, D., & Park, M. J. (2023). Learner innovativeness, course interaction, and the use of a new educational technology system after the COVID-19 pandemic. The International Journal of Management Education, 21(3), 100824. https://doi.org/10.1016/j.ijme.2023.100824

Kim, E. J., Kim, J. J., & Han, S. H. (2021). Understanding student acceptance of online learning systems in higher education: Application of social psychology theories with consideration of user innovativeness. Sustainability, 13(2), 896. https://doi.org/10.3390/su13020896

Kisiołek, A., Karyy, O., & Нalkiv, L. (2021). The utilization of Internet marketing communication tools by higher education institutions (on the example of Poland and Ukraine). International Journal of Educational Management, 35(4), 754–767. https://doi.org/10.1108/IJEM-07-2020-0345

Koutromanos, G., Mikropoulos, A. T., Mavridis, D., & Christogiannis, C. (2024). The mobile augmented reality acceptance model for teachers and future teachers. Education and Information Technologies, 29(7), 7855–7893. https://doi.org/10.1007/s10639-023-12116-6

Lan, Y., Liu, S., Chen, H., & Xia, L. (2026). Configurational effects of personal innovativeness, self-efficacy, and perceived risk on AI adoption in media students. Scientific Reports, 16(1), 5681. https://doi.org/10.1038/s41598-026-36538-7

Lee, U.-K. (2022). Tourism using virtual reality: Media richness and information system successes. Sustainability, 14(7), 3975.. https://doi.org/10.3390/su14073975

Lei, M., Clemente, I. M., Liu, H., & Bell, J. (2022). The Acceptance of Telepresence Robots in Higher Education. International Journal of Social Robotics, 14(4), 1025–1042. https://doi.org/10.1007/s12369-021-00837-y

Li, J., Jin, M., & Chen, X. (2025). Understanding continued use of smart learning platforms: psychological wellbeing in an extended TAM-ISCM model. Frontiers in Psychology, 16. https://doi.org/10.3389/fpsyg.2025.1521174

Li, J., & Lv, C. (2024). Exploring user acceptance of online virtual reality exhibition technologies: A case study of Liangzhu Museum. PLOS ONE, 19(8), e0308267. https://doi.org/10.1371/journal.pone.0308267

Li, Y., Liang, J., Huang, J., Yang, M., Li, R., & Bai, H. (2022). Would You Accept Virtual Tourism? The Impact of COVID-19 Risk Perception on Technology Acceptance from a Comparative Perspective. In Sustainability 14(7), 12693. https://doi.org/10.3390/su141912693

Mailizar, M., Burg, D., & Maulina, S. (2021). Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model. Education and Information Technologies, 26(6), 7057–7077. https://doi.org/10.1007/s10639-021-10557-5

Mallek, F., Mazhar, T., Shah, S. F. A., Ghadi, Y. Y., & Hamam, H. (2024). A review on cultivating effective learning: synthesizing educational theories and virtual reality for enhanced educational experiences. PeerJ Computer Science, 10(e2000), 1–41. https://doi.org/10.7717/peerj-cs.2000

Maltais, L.-G., & Gosselin, L. (2022). Visiting central heating plant and mechanical rooms in buildings: A case study of virtual tours to foster students’ learning in a distance course. International Journal of Mechanical Engineering Education, 50(4), 1007–1024. https://doi.org/10.1177/03064190221105078

Marks, B., & Thomas, J. (2022). Adoption of virtual reality technology in higher education: An evaluation of five teaching semesters in a purpose-designed laboratory. Education and Information Technologies, 27(1), 1287–1305. https://doi.org/10.1007/s10639-021-10653-6

Peanchitlertkajorn, S., Reynolds, P. A., Chaisawas, M., Krungthong, Y., Boonkaew, B., & Sipiyaruk, K. (2024). The impact of an online gamified virtual tour on cognitive enhancement in dental practice management. Scientific Reports, 14(1), 26975. https://doi.org/10.1038/s41598-024-75128-3

Puiu, S., & Udriștioiu, M. T. (2024). The Behavioral Intention to Use Virtual Reality in Schools: A Technology Acceptance Model. In Behavioral Sciences 14(7). 615. https://doi.org/10.3390/bs14070615

Rojas-Sánchez, M. A., Palos-Sánchez, P. R., & Folgado-Fernández, J. A. (2023). Systematic literature review and bibliometric analysis on virtual reality and education. Education and Information Technologies, 28(1), 155–192. https://doi.org/10.1007/s10639-022-11167-5

Rosli, M. S., Saleh, N. S., Md. Ali, A., Abu Bakar, S., & Mohd Tahir, L. (2022). A Systematic Review of the Technology Acceptance Model for the Sustainability of Higher Education during the COVID-19 Pandemic and Identified Research Gaps. In Sustainability 14(8).11389. https://doi.org/10.3390/su141811389

Sakr, A., & Abdullah, T. (2024). Virtual, augmented reality and learning analytics impact on learners, and educators: A systematic review. Education and Information Technologies, 29(15), 19913–19962. https://doi.org/10.1007/s10639-024-12602-5

Shah, N. L., Miller, J. B., Bilal, M., & Shah, B. (2021). Smartphone Apps in Graduate Medical Education Virtual Recruitment During the COVID-19 Pandemic. Journal of Medical Systems, 45(3), 36. https://doi.org/10.1007/s10916-021-01720-z

Shen, S., Xu, K., Sotiriadis, M., & Wang, Y. (2022). Exploring the factors influencing the adoption and usage of Augmented Reality and Virtual Reality applications in tourism education within the context of COVID-19 pandemic. Journal of Hospitality, Leisure, Sport & Tourism Education, 30, 100373. https://doi.org/10.1016/j.jhlste.2022.100373

Stracke, C. M., Bothe, P., Adler, S., Heller, E. S., Deuchler, J., Pomino, J., & Wölfel, M. (2025). Immersive virtual reality in higher education: a systematic review of the scientific literature. Virtual Reality, 29(2), 64. https://doi.org/10.1007/s10055-025-01136-x

Yang, C., Yan, S., Wang, J., & Xue, Y. (2022). Flow Experiences and Virtual Tourism: The Role of Technological Acceptance and Technological Readiness. In Sustainability 14(9)5361. https://doi.org/10.3390/su14095361

Yang, H., Cai, M., Diao, Y., Liu, R., Liu, L., & Xiang, Q. (2023). How does interactive virtual reality enhance learning outcomes via emotional experiences? A structural equation modeling approach. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1081372

Downloads

Published

2026-07-19

How to Cite

Gularso, K., Yulita, H., Christian, M., & Hussain, S. (2026). Virtual campus tours as strategic marketing communication: The role of personal innovativeness. Bulletin of Educational Management and Innovation, 4(1), 237–255. https://doi.org/10.56587/bemi.v4i1.151

Issue

Vol. 4 No. 1 (2026): Bulletin of Educational Management and Innovation

Section

Articles

License

Copyright (c) 2026 Kurnadi Gularso, Henilia Yulita, Michael Christian, Sajjad Hussain

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors who publish in this journal agree to the following terms:

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) License that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).