Abstract
As the tourism industry faces growing competition and digital transformation in the post-pandemic era, virtual reality has emerged as a creative marketing strategy. However, investing in virtual reality may be costly. Evaluating what type of products can generate higher returns through virtual reality is critical. Our study explored the moderating effect of product complexity on the relationship between virtual reality characteristics and behavioral intention. Our results indicated that the relationship between telepresence and consumer trust is stronger for a complex tourism product than a simple product. Firms with limited resources should invest in virtual reality to market complex products.
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1 Introduction
The rapid development of tourism has challenged the tourism operators to be more efficient and effective to remain competitive, and they are turning to creative marketing strategies. One example is the metaverse. The architecture of the metaverse enables the linkage between the physical and virtual worlds, and virtual reality (VR) is regarded as the main interaction interface to achieve immersive user experience [1].
While traditional media platforms (paper brochures and video clips) have been sufficient for marketing standard products (e.g., 3-night accommodation in a three-star hotel), more complex tourism products (e.g., a 3-night cruise package) can leverage the immersive and interactive characteristics of VR for marketing. However, the metaverse can be an expensive technological investment. Therefore, it is crucial to understand the effect of VR based on product type and to strategically allocate resources to maximize returns. A recent review on virtual reality in tourism indicated that research has not sufficiently investigated fully immersive VR, compared to non-immersive and semi-immersive VR [2]. Questions related to the benefits of fully immersive VR, a costlier system compared to semi- and non-immersive VR, remain unanswered [3]. Our study intends to fill this research void and also assist tourism organizations with allocating internal resources when making decisions on metaverse investments.
2 Literature Review and Theoretical Framework
VR technology replicates an environment, real or imagined, and simulates a user’s physical presence to allow users to interact with the environment [4, 5]. “A VR experience can be described by its capacity to provide physical immersion and psychological presence” [6]. A higher level of immersion provides more extensive sensory information to users, which results in a stronger sense of presence in the virtual space. These characteristics of VR can serve as a powerful tool to improve product discovery and selection experience [7, 8] and facilitate immersive, engaging, social, and entertaining experiences [9,10,11]. Many past studies on VR in the tourism industry have addressed the simulation type, social interaction, prior visitation, and experience type as moderators of the effect of VR on cognitive/affective response and behavioral intention [12]. To the best of our knowledge, there has been no study on product complexity and our study is the first to explore the interaction effect of product complexity.
2.1 Media Richness and Telepresence
Media richness theory classifies the richness of a medium based on four criteria: feedback, multiple cues, language variety, and personal focus [13]. Face-to-face interactions are considered the richest medium, capable of reduce equivocality and uncertainty in information processing [14]. VR simulates real-world environments and is considered a rich medium that is comparable with face-to-face interactions [15]. Telepresence is the sense of presence in a virtual environment [16], which can enhance consumers’ perception about service offerings [17]. Trust, or the belief that a trusted party (e.g., a travel agency) will fulfill its commitments in an exchange relationship [18] is crucial especially when the transactions involve a certain level of risk, such as purchasing tourism products online [19]. Experiencing a richer medium through an embodied virtual representation provides users with a more realistic and vivid service officering, which enhances users’ trust in the service providers [17]. Therefore, we hypothesize:
H1: Media richness positively enhances consumer trust.
H2: Telepresence positively enhances consumer trust.
2.2 Product Complexity
The complexity of a tourism product is a function of the number of elements that a tourism product is composed of and the internal relationships among these elements. More cognitive resources from consumers are required when more complex products are offered owing to higher levels of ambiguity and uncertainty. Because of the high level of media richness and telepresence in VR, customers can receive more types of informational cues to understand and build trust in a complex product. Therefore, the effects of media richness and telepresence on consumer trust are stronger for complex products than for simple products. As a result, we propose:
H3: Product complexity moderates the relationship between media richness and consumer trust.
H4: Product complexity moderates the relationship between telepresence and consumer trust.
2.3 Purchase Intention
After comprehending the product information, consumers form a positive, neutral, or negative attitude that affects their actions [20]. Because marketing through VR increases consumer trust in the company and subsequently affects purchase intention, we propose:
H5: Consumer trust positively affects purchase intention.
3 Methodology
We conducted a survey-based experiment to test our hypotheses, and selected a leisure farm as a complex tourism product and a 3-star hotel as a simple tourism product. The leisure farm offered more product elements (room, breakfast, leisure activities, and farm experience) than the hotel (room and breakfast). We inspected both locations in-person and crafted the virtual environments to scale in the Unity engine. Please refer to the video capture of the leisure farm at https://youtu.be/T_2S48ptycM and the virtual hotel at https://youtu.be/CsKA3Ku627A for the virtual environments built. The experiment was conducted on campus in three universities in Taiwan where we set up the experiment in a lab setting. The recruitment of participants was announced on social media sites and open to general public. The participants include students, faculty and staff members of the universities, as well as the residents living nearby the universities. The participants were randomly assigned to experience either the leisure farm or the hotel by using an HTC Vive VR set. Participants were then asked to complete a survey after the experiment. The data collection period was from July 17 to August 14, 2022. A total of 207 participants were recruited; 103 participants experienced the virtual leisure farm, and the other 104 participants visited the virtual hotel.
4 Data Analysis
We used SmartPLS 4.0 for partial least squares structural equation modeling to conduct the data analysis. The factor loadings of the measurements were all greater than 0.681. The Cronbach’s alpha coefficient (all greater than 0.848), composite reliability (all greater than 0.853), and average variance extracted (all greater than 0.593) met the requirements of reliability and convergent validity. The heterotrait–monotrait (HTMT) ratios were all below 0.764 except telepresence (0.882) and exhibited satisfactory discriminant validity. Telepresence is related to media richness. Therefore, an HTMT ratio of 0.882 (below 0.9) was acceptable. The significance of the path coefficients was evaluated using bootstrapping. The results supported H1, H4, and H5 (Fig. 1). The model explained 46.8% and 27.2% of the variance in consumer trust and purchase intention, respectively.
5 Discussion and Conclusion
Our results revealed that media richness has a positive effect on consumer trust, regardless of product complexity. Telepresence does not have a positive effect on consumer trust when the product is simple but exhibits a positive effect on consumer trust when the product is complex. Our results suggest that tourism operators should strategically allocate resources when developing VR content in metaverse as it can be an expensive technological investment, depending on the level of detail and interaction in the virtual environment. Specifically, the sense of presence through VR enhances consumer trust and hence purchase intention only when the tourism product is complex. Therefore, when developing VR content in metaverse, resources should be prioritized for complex tourism products.
In our future studies, we will extend the proposed model by comparing VR with video as a marketing tool. We expect that the participants will experience a higher level of media richness and telepresence when exploring tourism products through VR than video clips. However, when promoting a simple product, the effect of VR and video may be similar on consumer trust and purchase intention, and a video clip may be sufficient. When promoting a complex product, VR may promote telepresence more than video and hence enhance consumer trust and purchase intention. Although the metaverse is gaining traction, not all products are suitable for VR. More research on the metaverse should be conducted to understand how VR affects consumer behavior.
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Chan, CH., Wong, K.Y., Lui, TW. (2023). Marketing Tourism Products in Virtual Reality: Moderating Effect of Product Complexity. In: Ferrer-Rosell, B., Massimo, D., Berezina, K. (eds) Information and Communication Technologies in Tourism 2023. ENTER 2023. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-031-25752-0_34
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