Virtual front and educational impact: Virtual reality effects in war tourism

Popescu, Delia et al. Article Virtual front and educational impact: Virtual reality effects in war tourism Amfiteatru Economic Provided in Cooperation with: The Bucharest University of Economic Studies Suggested Citation: Popescu, Delia et al. (2024) : Virtual front and educational impact: Virtual reality effects in war tourism, Amfiteatru Economic, ISSN 2247-9104, The Bucharest University of Economic Studies, Bucharest, Vol. 26, Iss. Special Issue No. 18, pp. 1160-1176, https://doi.org/10.24818/EA/2024/S18/1160 This Version is available at: https://hdl.handle.net/10419/318605 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ AE Virtual Front and Educational Impact: Virtual Reality Effects in War Tourism 1160 Amfiteatru Economic VIRTUAL FRONT AND EDUCATIONAL IMPACT: VIRTUAL REALITY EFFECTS IN WAR TOURISM Delia Popescu1 * , Ionuț-Andrei Militaru2, Daniel Bulin3,4 , Valentin Niță5, Iuliana Pop6and Cristina Ioana Balint (Curutiu)7 1)2)3)6) Bucharest University of Economic Studies, Romania 4) Institute for World Economy, Bucharest, Romania 5) Alexandru Ioan Cuza University of Iaşi, Romania 7) Babeș-Bolyai University, Cluj-Napoca, Romania Please cite this article as: Popescu, D., Militaru, I.A., Bulin, D., Niță, V, Pop, I. and Balint (Curutiu), C.I., 2024. Virtual Front and Educational Impact: Virtual Reality Effects in War Tourism. Amfiteatru Economic, 26(Special Issue No. 18), pp. 1160-1176. DOI: https://doi.org/10.24818/EA/2024/S18/1160 Article History Received:22 August 2024 Revised: 19 September 2024 Accepted: 11 October 2024 Abstract To better understand the factors influencing technological adoption and the benefits it offers for education, this study looks at the use of Virtual Reality (VR) in war tourism. To comprehend how social influence, effort expectations, performance expectancy, and facilitating conditions influence tourists' educational benefits and ` intentions to use VR, this study utilises the Unified Theory of Acceptance and Use of Technology (UTAUT). Using confirmatory factor analysis and structural equation modelling, we investigated 495 survey responses. The study shows that the UTAUT` factors have a strong influence on both behavioural intentions and the usefulness of educational services, especially those factors that emphasise social acceptance, ease of use, perceived value, and the need for infrastructure and support. It can be seen that the benefits significantly mediate UTAUT constructs and behavioural intentions to adopt VR. Therefore, travellers are more inclined to adopt and use virtual reality (VR) in war tourism if they perceive that it offers significant educational benefits. Implications for management include marketing promotion, userfriendly design, and the need to invest in quality VR educational content. Keywords: Virtual Reality, war tourism, educational benefits, technology acceptance, Unified Theory of acceptance and use of technology, structural equation modelling JEL Classification: L15, L83, M16, M31, Q20, Q55 * Corresponding author: Delia Popescu – e-mail: [email protected] This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2024 The Author(s). New Trends in Sustainable Business and Consumption AE Vol. 26 • Special Issue No 18 • November 2024 1161 Introduction Virtual reality (VR) has become a ground-breaking technology that is being used in various industries, including travel. The growing interest in the potential of virtual reality to enhance educational experiences has increased the demand for studies in specific situations, such as war tourism. War tourism is a specialised area of the tourism industry that involves visiting historical battlefields and sites associated with war, providing a rare opportunity to learn and view conflict. Nevertheless, little is known about the use of VR in this industry, particularly in terms of its potential for education and the elements that influence traveller acceptance. Numerous research studies, particularly applying theoretical frameworks such as the Unified Theory of Acceptance and Usage of Technology (UTAUT), have looked at the acceptance and use of technology in the travel and tourism sector. The UTAUT developed by Venkatesh et al. (2003) identifies the key variables that influence users' intentions and behaviour in relation to new technologies. Holsapple & Wu (2007) analysed the entertainment-oriented technologies from the perspective of user acceptance of virtual world technologies, while Goel et al. (2011) proposed and tested a model to predict users' intentions to return to a virtual world. Veasna et al. (2013) examines the relationships between four constructs - credibility, image, attachment, and satisfaction – as antecedents of destination satisfaction. Kaushik et al. (2015) extend the utility of the technology acceptance model (TAM) by analysing additional antecedent beliefs to predict tourists' attitudes towards self-service technologies (SSTs). Huang et al. (2016) integrated the technology acceptance model (TAM) and self-determination theory in their study to understand how tourists use a 3D virtual world. Tan et al. (2017) proposed an integrated framework of Mobile Technology Acceptance Model with personal factors (mobile selfefficacy, technological self-efficacy) and interactivity theory to understand consumers' intention to use mobile social media advertising to receive tourism-related advertisements. Oncioiu & Priescu (2022) emphasise the importance of the authenticity of VR content and its influence on the perception and emotions of tourists. They show that authentic travel experiences presented in VR can significantly influence the travel intentions of potential tourists by providing them with a realistic and engaging perspective on destinations. Other authors also support the positive effects of using immersive virtual reality in education (Liu et al., 2020). Although virtual reality (VR) is widely used in various fields, its application in war tourism has been little explored, despite the fact that immersive experiences can significantly increase visitor engagement and education. The focus of this research was on how social influence, effort expectancy, performance expectancy, and facilitating conditions can influence tourists' intentions to adopt VR. These factors were identified as key determinants of user acceptance of new technologies. However, comparatively little attention has been paid to their relative impact on VR adoption in the context of war tourism, particularly in relation to its educational benefits. This study specifically aims to identify the ways in which VR acceptance in war tourism is mediated by educational benefits in relation to the key constructs postulated by UTAUT. AE Virtual Front and Educational Impact: Virtual Reality Effects in War Tourism 1162 Amfiteatru Economic 1. Literature Review 1.1. Virtual Reality and Unified Theory of acceptance and use of technology (UTAUT) in war tourism Although the acceptance of virtual experiences depends on travellers' attitudes and limitations, virtual reality (VR) offers potential applications for planning, management, entertainment, education, accessibility, and heritage preservation in tourism (Guttentag, 2010). The UTAUT theory (Unified Theory of Acceptance and Use of Technology), which was developed to understand the social factors, effort, and performance expectations, and facilitating conditions that influence the acceptance and use of technologies, has been adapted and contextualised for war tourism in this article. Social factors such as peer pressure and the opinions of those around you play a major role in whether visitors will use virtual reality (VR) in war tourism. Studies show that the way people perceive social norms and their social identity influences their intention to use online community services (Song & Kim, 2006). The sense of community among museum visitors increases both their enjoyment and the likelihood that they will return. This implies that the effects of conflict tourism could be comparable (Jung et al., 2016). People are more willing to use VR when they have social connections and interactions, as this makes the technology more enjoyable (Lee et al., 2019). According to Vishwakarma et al. (2020), one of the main reasons individuals try virtual reality (VR) in tourism is to acquire validation from friends and family. Thus, social factors therefore have a significant impact on travellers' decision to adopt virtual reality for war tourism. Tourists' interest in using virtual reality (VR) for war tourism is positively influenced by effort expectation or perceived ease of use. According to research results, behavioural intentions to adopt virtual reality are highly influenced by the perceived ease of use (Vishwakarma et al., 2020). If VR applications are simple to use, users are more likely to interact with them (Rauscher et al., 2020). In the Lake District National Park, user-friendly VR applications led to higher adoption rates (Dieck et al., 2018). During the pandemic, perceived ease of use was a significant predictor of VR adoption (Schiopu et al., 2021). In addition, perceived immersion, interest, enjoyment, and ease of use significantly influence the intention to use VR for travel planning (Disztinger et al., 2017). In conflict areas such as Ukraine, ease of use increases the intention to adopt VR (Hornoiu et al., 2023). Therefore, the expectation of effort is a very important factor for the adoption of VR for war tourism. Performance expectations, or how useful and effective VR appears to be, have a big impact on visitors' attitudes towards the use of VR in war tourism. If people perceive VR as helpful and immersive, their attitude becomes more positive, leading to higher acceptance rates (Rejón-Guardia et al., 2020). The effect can be observed in theme parks (Wei et al., 2019) and museums (Jung et al., 2016). The authentic previews of virtual reality have the power to influence hotel bookings (McLean & Barhorst, 2021) and improve visitors' perceptions of cultural heritage sites (Park et al., 2018). Overall, the positive perception of the use of VR in tourism is characterised by its perceived utility and captivating qualities (Tussyadiah et al., 2018). People are therefore more inclined to accept virtual reality in war tourism if it fulfils these performance expectations. New Trends in Sustainable Business and Consumption AE Vol. 26 • Special Issue No 18 • November 2024 1163 Facilitation conditions, such as technical support and resource availability, are essential for the adoption of VR (Oncioiu and Priescu, 2022). Strong facilitation conditions increase perceived usefulness and ease of use (Disztinger et al., 2017). Interactivity and technical support are important to create a memorable VR experience and encourage adoption (Leung et al., 2022). In war tourism, facilitation conditions have a significant impact on perceived value and adoption intentions (Vishwakarma et al., 2020). Based on the above research, we have formulated the first four research hypotheses (H1- H4): H1. Social influence factors have a significant influence on visitors' intention to adopt and use virtual reality in the context of war tourism; H2. Effort Expectation of effort or perceived ease of using virtual reality in war tourism is positively associated with visitors' intention to adopt this technology; H3. Performance expectation or perceived usefulness and effectiveness usefulness of using virtual reality in war tourism positively influences visitors' attitude towards using this technology; H4. Facilitating conditions have a positive influence on tourists' intention to use VR in war tourism. 1.2. Social Influence, Effort Expectation, Performance Expectation, Facilitation Conditions (UTAUT variables) and Educational Benefits of Using VR in War Tourism Research shows that the educational impact of virtual reality (VR) in the context of war tourism is significantly enhanced by social influence, performance expectations, effort expectations and facilitation conditions. Social factors, including institutional support or social interactions in virtual reality (VR), have been shown to increase learning outcomes and participation (Kang et al., 2012; Chiao et al., 2018; Ying et al., 2021; Guttentag, 2010). Expectation of effort is important because ease of use increases engagement and improves academic performance (Nguyen et al., 2019). High performance expectations also improve learning, empathy, and remembrance (Calvert and Abadia, 2020, Lignos and Korres, 2019). Effective facilitation conditions, including access to resources and support, further enhance the educational potential of VR (Nelson et al., 2019). Based on the above research results, we have formulated the following four research hypotheses (H5-H8): H5. Social influence factors have a significant influence on the educational benefits of using VR in war tourism; H6. Effort expectation (perceived ease) of using VR in war tourism is positively associated with educational benefits; H7. Performance expectation (perceived usefulness) of virtual reality in war tourism has a positive influence on educational benefits; H8. Facilitation conditions have a positive influence on the educational benefits of using VR in war tourism. 1.3. Perceived educational benefits and intention to use VR in tourism According to studies, virtual reality has significant educational benefits in a number of areas. According to Stavroulia (2019), it is an excellent tool for teacher preparation, while McGovern et al. (2020) have shown that it improves the communication skills of business students. According to Campos et al. (2022), virtual reality improves student understanding and the overall learning process. Virtual reality (VR) provides rich, interactive views of holiday destinations and creates a dynamic learning environment in tourism education (Zapatta-Moya and Astudillo-Rodriguez, 2023). VR can transform bad feelings into deeper AE Virtual Front and Educational Impact: Virtual Reality Effects in War Tourism 1164 Amfiteatru Economic awareness and learning, even in the context of “dark tourism” (Zheng et al., 2019). Furthermore, it is effective for hands-on learning on topics such as general tourism and climate change (Schott and Marshall, 2012; Schott, 2017). Perceived educational value is a powerful motivator, and people are more likely to adopt VR when they recognise its benefits and enjoy it (Vishwakarma et al., 2020, Rasul, 2021 and Shen et al., 2022). Social influence and the expectation of good performance are crucial, especially when the educational benefits are clear (Khalid et al., 2021). Taking the above studies into account, we have formulated 2 research hypotheses (H9- H10): H9. The perceived educational benefit has a significant influence on the intention to use VR in war tourism; H10. Perceived educational benefits mediate the relationships between the UTAUT variables and the intention to use VR in war tourism. In a study on mobile applications in tourism, age was found to moderate the effects of social influence and effort expectancy on behavioural intention. Younger users were more influenced by social factors, while older users placed more emphasis on the ease of use and perceived usefulness of the technology (Tan et al., 2017). Therefore, the last hypothesis was hypothesised: H11. Age moderates the relationships between SI, EE, PE, and intention to use VR in war tourism (BI). Based on the above hypotheses, we have proposed the following research model (Figure 1): . Bold lines are hypotheses. Orange dotted lines indicate the mediated role (H1a, b, c, d). Dashed lines indicate the moderated role (H11a, b, c). Figure no. 1. Proposed research framework Source: developed by authors 2. Methodology 2.1. Data collection To develop an initial list of measurement variables for our study, we first carefully reviewed previous research findings. These variables will help researchers understand the impact of Virtual Reality (VR) in war tourism and the benefits for education and learning. Our approach drew on previous research on foreign visitor behaviour, theories of human behaviour, and specific details on the use of virtual reality in war tourism (Vietnamese et al., 2019; Pyjas et al., 2022; Schiopu et al., 2022; Hornoiu et al., 2023). New Trends in Sustainable Business and Consumption AE Vol. 26 • Special Issue No 18 • November 2024 1165 Due to technological developments, online surveys are now a popular method to collect information from various audiences, especially in the field of hospitality and tourism research (Kim et al., 2020). When subjected to rigorous testing, such as cognitive testing and pilot surveys, these online surveys ensure high-quality data by achieving content validity and reliability (Heale and Twycross, 2015). For this study, we used Google Forms for data collection. We focused on people who attended the Romanian Tourism Fair 2023 and are interested in hospitality and tourism. From 9 November 2023 to 29 December 2023, we collected 495 responses. Participants rated their answers on a Likert scale from 1 (“strongly disagree”) to 7 (“strongly agree”). Our questionnaire was based on studies of international tourist behaviour, theories of human behaviour, and war tourism. In particular, we used concepts such as Social Influence (SI), Effort Expectancy (EE), Performance Expectancy (PE), Facilitating Conditions (FC), and Behavioural Intention to Use VR (BI) by Oncioiu (2022). For Social Influence (SI), we included three questions based on the recommendations of Venkatesh et al. (2003) and Guo and Barnes (2009). Effort Expectancy (EE) was measured with statements such as “Using VR while travelling seemed relatively easy” and “VR creates the intention to use the system to escape from everyday life.” the Performance Expectancy (PE) category comprised four questions. Behavioural Intention (BI) to use VR in war tourism was assessed with three items from Glasman and Albarracín (2006). The educational benefit of using VR in war tourism was based on a model by Zheng et al. (2019) and comprised seven questions. First, we used confirmatory factor analysis to clearly identify the factors and variables in our study, which helped us to reduce overlap and error between indicators (Yoon and Uysal, 2005). We then used confirmatory factor analysis to create a measurement model and tested the latent structural model on this basis (Kline, 2005). The pre-testing procedure of the questionnaire was conducted on a sample of 12 students. The results showed that the questions were correctly formulated and well understood by the participants. The pre-testing allowed for the identification of ambiguities or issues with clarity, but the positive feedback obtained confirmed the appropriateness of the questions in relation to the research objectives. Thus, the relevance and accuracy of the questionnaire were validated prior to its application to the extended sample. 2.2. Respondent profile In our study, most of the respondents were females, accounting for 57.58% (285 respondents), while the proportion of males was 42.42% (210 respondents). There were 294 people in the 15–25 age group, which is 59.39% of the total population. The next largest age groups were 26-35 years old (14.14%; 70 people), 36-45 years old (11.31%; 56 people) and 46-60 years old (11.11%; 55 people). The age group over 60 made up the smallest percentage (20 people). About half of the respondents (48.08% or 238 people) had completed high school. This was followed by those (42.83%, 212 people) who had completed their undergraduate studies. A smaller number had post-graduate education (7.68%, 38 people), and very few had only completed secondary education (1.41%, 7 people). In terms of monthly income, the largest group earned more than 4000 RON, namely 25.86% (128 people). This was followed by those who earned between 2001 and 3000 RON (20.61%, 102 people) and between 3001 and 4000 RON (15.96%, 79 people). A AE Virtual Front and Educational Impact: Virtual Reality Effects in War Tourism 1166 Amfiteatru Economic significant proportion earned between 500 and 1000 RON (13.54%, 67 people) and less than 500 RON (12.32%, 61 people). The smallest group earned between 1001 and 2000 RON and represented 11.72% (58 people). We used SmartPLS 4.1.0.2 (Ringle et al., 2024) to perform a confirmatory factor analysis of the model to test its reliability and validity. 3. Results and Discussion 3.1. Measurement model In order to get a clear picture of how each indicator reflects its underlying concept, the links between the constructs and the corresponding variable indicators are presented in the measurement model. To evaluate the measurement model, the values of Cronbach α, composite reliability (CR) and the extracted mean variance (AVE) were checked. A value of 0.60 or higher is considered acceptable, which means that the model exhibits composite reliability (Bagozzi & Yi, 1988). Therefore, all elements of the model are reliable (Table 1). The second component of the measurement model, convergent validity, assesses whether a set of indicators represents one and the same underlying construct. A key measure of convergent validity is the Average Variance Extracted (AVE). The desirable limit value for AVE is 0.50 (Hair et al., 2010), which means that the construct explains on average 50% or more of the variance in its indicators. The constructs therefore have convergent validity (see Table 1). Table 1. Factor loadings, reliability, and convergent and discriminant validity Itemi BI EE FC EB PE SI ∆ Cronbach's alpha CR AVE (Outer Loadings) (rho_a) BI 0.920 0.920 0.862 BI 1 0.927 BI 2 0.931 BI 3 0.927 EE 0.656 0.898 0.900 0.831 EE 1 0.907 EE 2 0.931 EE 3 0.882 FC 0.708 0.730 0.910 0.910 0.847 FC 1 0.918 FC 2 0.935 FC 3 0.909 EB 0.679 0.643 0.817 0.957 0.958 0.794 EB 1 0.886 EB 2 0.922 EB 3 0.920 New Trends in Sustainable Business and Consumption AE Vol. 26 • Special Issue No 18 • November 2024 1167 Itemi BI EE FC EB PE SI ∆ Cronbach's alpha CR AVE (Outer Loadings) (rho_a) EB 4 0.887 EB 5 0.890 EB 6 0.882 EB 7 0.848 PE 0.806 0.827 0.849 0.751 0.847 0.852 0.685 PE 1 0.847 PE 2 0.788 PE 3 0.836 PE 4 0.839 SI 0.509 0.631 0.555 0.515 0.606 0.751 0.761 0.669 SI 1 0.808 SI 2 0.879 SI 3 0.763 Source: Developed by authors based on SmartPLS calculations The Heterotrait Monotrait (HTMT) Ratio method is used to assess the discriminant validity of a measurement model. The method is used to determine whether constructs that are supposed to be different from each other are actually different from each other. Benitez et al. (2020) point out that a threshold value of 0.85 or less for the HTMT ratio is the most conservative criterion to ensure that the constructs are distinguishable from each other. In our research, all HTMT values are below the threshold of 0.85 (see Table 1). 3.2. The structural model The structural model assesses the hypothesised relationships between latent variables (see Table 2) and is important to test the fit of the overall model and the significance of the proposed pathways, with t-value > 1.960 and p-value < 0.05 (Hair et al., 2014). The analysis revealed that Social Influence (SI) significantly affects Behavioural Intention (BI) with β=0.061, t=1.981, p<0.05. H1 is therefore confirmed. H2 examines whether behavioural Intention (BI) is significantly influenced by Effort Expectancy (EE). Our results show that H2 was confirmed (β=0.072, t=2.044, p<0.05). H3 investigates whether behavioural intention (BI) is significantly impacted by performance expectation (PE). The results show that PE has a significant influence on BI with a path coefficient (β) of 0.410 (t=10.352, p<0.05). H3 is thus confirmed. H4 investigates whether Facilitating Conditions (FC) significantly affect Behavioural Intention (BI) and our study shows that FC have a significant impact on BI (β=0.107, t=2.423, p<0.05). In this case, H4 is supported. In addition, the results show that Social Influence (SI) significantly impacts Educational Benefits (EB) (β=0.061, t=2.243, p<0.05). Therefore, H5 is validated. The analysis also demonstrates that Effort Expectancy (EE) has a significant influence on Educational Benefits (EB) (β=0.060, t=1.961, p<0.05), confirming hypothesis 6. The results show that AE Virtual Front and Educational Impact: Virtual Reality Effects in War Tourism 1174 Amfiteatru Economic Tourism Management Perspectives, 16, pp. 278-289. https://doi.org/10.1016/ j.tmp.2015.09.002. Khalid, B., Chaveesuk, S., and Chaiyasoonthorn, W., 2021. MOOCs adoption in higher education: a management perspective. Polish Journal of Management Studies. 23(1) nr. art. 31. https://doi.org/10.17512/pjms.2021.23.1.15. Kim, M., Lee, C., and Jung, T., 2020. Exploring Consumer Behavior in Virtual Reality Tourism Using an Extended Stimulus-Organism-Response Model. Journal of Travel Research, 59, pp. 69-89. https://doi.org/10.1177/0047287518818915. Kline, R. B., 2005. Principles and practice of structural equation modeling (2nd ed.). Guilford Press. Lee, J., Kim, J., and Choi, J., 2019. The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties. Telematics Informatics, 39, pp. 37-48. https://doi.org/10.1016/J.TELE.2018. 12.006. Leung, W., Cheung, M., Chang, M., Shi, S., Tse, S., and Yusrini, L., 2022. The role of virtual reality interactivity in building tourists’ memorable experiences and postadoption intentions in the COVID-19 era. Journal of Hospitality and Tourism Technology. 13 (3), https://doi.org/10.1108/jhtt-03-2021-0088. Lignos, I., and Korres, M., 2019. Virtual Reality Applications as an Innovative Educational Practice in Adult Education: A Case Study on Training Hellenic Air Force Pilots. Research Anthology on Adult Education and the Development of Lifelong Learners. https://doi.org/10.4018/978-1-5225-6255-9.CH012. Liu, R., Wang, L., Lei, J., Wang, Q., and Ren, Y., 2020. Effects of an immersive virtual reality‐based classroom on students’ learning performance in science lessons. British Journal of Educational Technology, 51(6), pp. 2034-2049. https://doi.org/10.1111/ bjet.13028. McGovern, E., Moreira, G., and Luna-Nevarez, C., 2020. An application of virtual reality in education: Can this technology enhance the quality of students’ learning experience? Journal of Education for Business, 95(7), pp. 490-496. https://doi.org/10.1080/ 08832323.2019.1703096. McLean, G., and Barhorst, J., 2021. Living the Experience Before You Go . . . but Did It Meet Expectations? The Role of Virtual Reality during Hotel Bookings. Journal of Travel Research, 61, pp. 1233-1251. https://doi.org/10.1177/00472875211028313. Nelson, K., Anggraini, E., and Schlüter, A., 2019. Virtual reality as a tool for environmental conservation and fundraising. PLoS ONE, 15. https://doi.org/10.1101/ 785014. Nguyen, V., Jung, K., Yoo, S., Kim, S., Park, S., and Currie, M., 2019. Civil War Battlefield Experience: Historical Event Simulation using Augmented Reality Technology. 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), pp. 294-2943. https://doi.org/10.1109/AIVR46125.2019.00068. Oncioiu, I., Priescu, I., 2022. The Use of Virtual Reality in Tourism Destinations as a Tool to Develop Tourist Behavior Perspective. Sustainability, 14(7), art. no. 4191. https://doi.org/10.3390/su14074191. New Trends in Sustainable Business and Consumption AE Vol. 26 • Special Issue No 18 • November 2024 1175 Park, H., Kim, J., Bang, S., and Woo, W., 2018. The Effect of Applying Film-induced Tourism to Virtual Reality Tours of Cultural Heritage Sites. 3rd Digital Heritage International Congress (DigitalHERITAGE) held jointly with 24th International Conference on Virtual Systems and Multimedia (VSMM 2018), pp. 1-4. https://doi.org/10.1109/DigitalHeritage.2018.8810089. Pyjas, G., Weinel, J., and Broadhead, M., 2022. Storytelling and VR: Inducing emotions through AI characters. Proceedings of EVA London 2022 (EVA 2022) https://doi.org/10.14236/ewic/eva2022.37. Rasul, T., 2021. Adoption intention of virtual reality in choosing travel destinations in the context of a developing economy. Tourism Recreation Research, 47, pp. 448-452. https://doi.org/10.1080/02508281.2021.1981073. Rauscher, M., Humpe, A., and Brehm, L., 2020. Virtual Reality in Tourism: Is it ‘Real’ Enough?. Academica Turistica, 13(2), pp. 127-138. https://doi.org/10.26493/2335- 4194.13.127-138. Rejón-Guardia, F., García-Sastre, M. A., Orfila-Sintes, F., and Garau-Vadell, J.B., 2020. Virtual Reality in Tourism: Centennials Acceptance. Tourism Analysis, 25(2-3), 335- 344. https://doi.org/10.3727/108354220X15758301241837. Ringle, C. M., Wende, S., and Becker, J.-M., 2024. "SmartPLS 4." Bönningstedt: SmartPLS. https://www.smartpls.com. Schiopu, A., Hornoiu, R., Padurean, M., and Nica, A., 2021. Virus tinged? Exploring the facets of virtual reality use in tourism as a result of the COVID-19 pandemic. Telematics and Informatics, 60, art. no. 101575. https://doi.org/10.1016/ j.tele.2021.101575. Schiopu, A.F., Hornoiu, R.I., Padurean, M.A., and Nica, A., 2022. Constrained and virtually traveling? Exploring the effect of travel constraints on intention to use virtual reality in tourism, Technology in Society, 71. art. no.102091. https://doi.org/10.1016/ j.techsoc.2022.102091. Schott, C., and Marshall, S., 2021. Virtual reality for experiential education: a user experience exploration. Australasian Journal of Educational Technology, 37(1), pp. 96-110. https://doi.org/10.14742/ajet.5166. Schott, C., 2017. Virtual fieldtrips and climate change education for tourism students. Journal of Hospitality, Leisure, Sport and Tourism Education, 21, pp. 13-22. https://doi.org/10.1016/j.jhlste.2017.05.002. Shen, S., Xu, K., Sotiriadis, M., and 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 and tourism education, 30, art. no. 100373. https://doi.org/10.1016/ j.jhlste.2022.100373. Song, J., and Kim, Y., 2006. Social influence process in the acceptance of a virtual community service. Information Systems Frontiers, 8, pp. 241-252. https://doi.org/10.1007/s10796-006-8782-0. Stavroulia, K. E., Christofi, M., Baka, E., Michael-Grigoriou, D., Magnenat-Thalmann, N., and Lanitis, A., 2019. Assessing the emotional impact of virtual reality-based teacher training. The International Journal of Information and Learning Technology, 36(3), pp. 192-217. https://doi.org/10.1108/IJILT-11-2018-0127. AE Virtual Front and Educational Impact: Virtual Reality Effects in War Tourism 1176 Amfiteatru Economic Tan, G., Lee, V., Lin, B., and Ooi, K., 2017. Mobile applications in tourism: the future of the tourism industry? Industrial Management & Data Systems, 117(3), pp. 560-581. https://doi.org/10.1108/IMDS-12-2015-0490. Tussyadiah, I., Wang, D., Jung, T., and Dieck, M., 2018. Virtual reality, presence, and attitude change: Empirical evidence from tourism. Tourism Management. 66, pp. 140-154. https://doi.org/10.1016/J.TOURMAN.2017.12.003. Veasna, S., Wu, W. Y., and Huang, C. H., 2013. The impact of destination source credibility on destination satisfaction: The mediating effects of destination attachment and destination image. Tourism Management, 36, pp. 511-526. https://doi.org/10.1016/ j.tourman.2012.09.007. Venkatesh, V., Morris, M., Davis, G.B., Davis, and F.D., 2003. User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), pp. 425-478. Vishwakarma, P., Mukherjee, S., and Datta, B., 2020. Travelers’ intention to adopt virtual reality: A consumer value perspective. Journal of Destination Marketing and Management, 17, art. no. 100456. https://doi.org/10.1016/j.jdmm.2020.100456. Wei, W., Qi, R., and Zhang, L. (2019). Effects of virtual reality on theme park visitors' experience and behaviors: A presence perspective. Tourism Management. 71, pp. 282-293.https://doi.org/10.1016/J.TOURMAN.2018.10.024. Yang, C., Liu, C., and Wang, Y., 2022. The acceptance and use of smartphones among older adults: differences in UTAUT determinants before and after training. Library Hi Tech. 41(5). https://doi.org/10.1108/lht-12-2021-0432. Ying, T., Tang, J., Ye, S., Tan, X., and Wei, W., 2021. Virtual Reality in Destination Marketing: Telepresence, Social Presence, and Tourists’ Visit Intentions. Journal of Travel Research, 61(8), pp. 1738-1756. https://doi.org/10.1177/00472875211047273. Yoon, Y., and Uysal, M. 2005. An examination of the effects of motivation and satisfaction on destination loyalty: a structural model. Tourism Management, 26(1), pp. 45-56. https://doi.org/10.1016/j.tourman.2003.08.016. Zapatta, F., and Astudillo-Rodriguez, C., 2023. The Use of Virtual Reality in Tourism Education: Systematic Review. Training, Education, and Learning Sciences, 109(109). https://doi.org/10.54941/ahfe1003157. Zheng, C., Zhang, J., Qiu, M., Guo, Y. and Zhang, H., 2019. From mixed emotional experience to spiritual meaning: learning in dark tourism places, Tourism Geographies. 22(1) pp 105-126. https://doi.org/10.1080/14616688.2019.1618903.