Imagination Versus Telepresence: Consumer Patronage Intention Toward Peer-to-Peer Accommodations in Photo-Enhanced Imaginative Conditions and Virtual Reality Contexts

Abstract

The use of information and communication technology, such as virtual reality (VR) and photo-enhanced imaginative condition (PIC), in the online previews of peer-to-peer accommodations at the pre-reservation stage has become a common phenomenon. However, previous research has not systematically compared the impact of these two preview modes on accommodation reservations or the psychological mechanism and moderators of the impact. We combined duality theories and the technology-enabled engagement process model to establish that a VR/PIC preview enhances consumers’ appraisal and their intention to patronize P2P accommodations through cognitive and affective engagement. Furthermore, the VR/PIC preview’s effect on patronage intention was found to be influenced by the motivation for consumer reservation: consumers form a positive appraisal when the target accommodation type (comfortable vs. economical) matches the preview mode (PIC vs. VR). Finally, the message appeal emphasis (informational vs. emotional) of advertising was found to moderate the effect of the VR/PIC preview.

Keywords

virtual reality photo-enhanced imaginative condition peer-to-peer accommodation consumer engagement

Introduction

The substantial development of information and communication technology has given rise to the sharing economy (Chen & Wang, 2019), in which peer-to-peer (P2P) accommodation is a growing worldwide business (Garau-Vadell et al., 2019; Nieto García et al., 2020; Tussyadiah & Pesonen, 2016; Wang & Li, 2021; Zhang et al., 2021). For example, the P2P accommodation industry in China accounted for more than $3 billion USD for the online reservation transactions completed in 2019 (Trustdata, 2020). P2P accommodation refers to a room-sharing business in the cyber marketplace in which hosts (either professional or nonprofessional) provide guidance and accommodation to their guests and receive rent for their short-term stays booked through an online platform (Karlsson et al., 2017; Xu et al., 2022; Yang et al., 2022).

As a platform-mediated transaction (Yang et al., 2022), the online booking of P2P accommodations involves higher uncertainty and perceived risk because of information asymmetry and intangibility (Park & Tussyadiah, 2020). A guest cannot easily evaluate the outcome of an online accommodation transaction because P2P accommodations are unstandardized and vary in their property quality and host service quality (Huang et al., 2020; Yan & Gong, 2022). However, visual previews have emerged as an effective method to solve uncertainty and facilitate booking decisions by using cutting-edge technologies with high-value propositions, which can enhance the preview experience (Guttentag, 2010; Xu et al., 2022); in particular, virtual reality (VR) and photo-enhanced imaginative condition (PIC) technologies have been increasingly applied to online previews. The VR preview approach has become a new favorite for online booking services such as Sheraton because it improves individuals’ ability to view the accommodation with authenticity and in detail; this decreases the perceived risk in the reservation of accommodations (Flavián et al., 2019). Furthermore, the PIC preview approach has been increasingly adopted for online reservations (e.g., www.ctrip.com). It provides users with static photos of high aesthetic value and quality through changes in the technical attributes of the original photos (de Araujo et al., 2014).

Studies have extensively examined the contribution of the VR preview mode to tourism performance in terms of technological features, perceived experience, value, and technology acceptance (Flavián et al., 2019; Kim, Lee, & Jung, 2020); however, few have focused on the application of VR previews, especially when compared to other cutting-edge technologies, such as PIC. Because of the differences in their technical features, these two types of preview modes have different visual communication foci. In the VR preview, the consumer enters a 3-D panoramic interface by clicking a link. Through embodiment, they feel as if they are walking inside a real accommodation and viewing its details (Bogicevic et al., 2021; Flavián et al., 2019). In contrast, PIC preview provides the user with several induced images in a window, that is, beautifying and selectively presenting positive content and thereby stimulating the consumer to form an ideal image of the accommodation (Lourenção et al., 2020; Slevitch et al., 2022).

These differences in visual communications may cause differential consumer perceptions, promoting different information processing mechanisms in decision-making. Previous studies have neglected the role of information processing in consumers’ online booking decision processes. Moreover, when engaging in the online digital service process, consumers are likely to have different perceptions through cognitive and affective engagement, depending on the discrepant technological features and value performance of online previews; ultimately, this can result in a behavioral response (Heller et al., 2021). Thus, the difference in the visual perception presented by VR and PIC may trigger psychological engagements that affect the evaluation and reservation of P2P accommodations. We examined the following research questions:

RQ1. How does a VR or PIC preview influence consumer engagement in the pre-reservation experience of P2P accommodations through visual communication?

RQ2. Does consumer engagement of technology-driven previews (VR and PIC) in the pre-reservation stage influence consumer patronage intention for P2P accommodations? How does it affect their cognitive decision-making process?

RQ3. Is there any moderator or boundary condition for this operating mechanism when the VR or PIC preview mode caters to different types of P2P accommodations and advertising strategies?

To address these questions, we conducted two experiments with participants recruited from China and stimuli selected from the Kaolahome platform. This Australia-based platform provides overseas P2P accommodations for outbound Chinese tourists, which can be accessed through online reservations using VR and PIC preview modes. Since 2012, China has been the world’s fourth-largest tourism market in terms of the number of tourists (Lin et al., 2019); in 2019, the number of Chinese outbound tourists traveling to main destinations such as Australia was 155 million, and outbound tourism consumption totaled $133.8 billion (CTA, 2020a). Indeed, the number of Chinese tourists to Australia has experienced the fastest growth (Balli & Tsui, 2016). Therefore, we selected Kaolahome as the stimuli source to obtain a broad sample of Chinese tourists; this provided a context broadly representative of Chinese tourists’ outbound travel and P2P accommodation reservation patterns.

After clarifying the research questions and context, we built a P2P accommodation reservation theoretical model using visual communication (VR/PIC preview mode) and consumer engagement borrowed from the technology-enabled engagement process (TEEP) framework. This model also incorporates duality models (dual system and dual process models) into information processing to explore the possible impact of VR versus PIC preview on consumer patronage intention toward P2P accommodation (Kang, 2020; Zeng et al., 2020). Moreover, it explored the potential moderator of VR and PIC technologies that affect consumer engagement and booking decisions regarding message appeal emphasis (emotional vs. informational); this can lead to competing or parallel relationships between consumer engagement dimensions in different booking situations (Batra & Ahtola, 1991; Xiang et al., 2019). Finally, we examined the dynamic appraisal process of consumer engagement in P2P accommodation booking decisions under different boundary conditions of consumer needs (comfortable vs. economical; Lee et al., 2012).

Literature Review

The Expanded TEEP Framework

Technology is a service enabler, whereas consumer engagement is often the core factor in predicting a successful service. Therefore, when examining the effectiveness of new technologies in overcoming service intangibility, technology should likely be redefined in terms of both customers and services to better understand value co-creation in a service-centric context (Hilken et al., 2017). We incorporated the TEEP framework, a multi-stage conceptual framework derived from immersive technology automation services, into the research model (Heller et al., 2021). TEEP divides a consumer’s engagement process into five stages: Stage 1, interactive qualities; Stage 2, perception of technologies; Stage 3, psychological engagement; Stage 4, realization of value; and Stage 5, behavioral engagement.

Based on the TEEP framework, we introduced two types of preview modes that differ in visual features and information fit-to-task (interactive qualities; Stage 1). We then integrated duality theories (Stage 2) to explore the differentiated effect of the two preview modes on consumer engagement (Stage 3). Subsequently, we employed a cognitive appraisal process (Stage 4) that combines booking tasks to analyze the impact of the two types of preview modes on consumer behavioral responses (Stage 5). Finally, we proposed an expanded TEEP framework of visual preview modes → duality models adoption → psychological engagement → realization of value → behavioral engagement to organize the research model.

VR and PIC Accommodation Previews

Visualization has become a primary tool for assisting consumers in making online booking decisions (Slevitch et al., 2022). P2P accommodation platforms should present tangible evidence among their service components through visual cues provided by computing media, that is, accommodation content, to reduce the intangibility and uncertainty of e-service space (Suh & Lee, 2005). PIC and VR preview modes are effective visualization technologies that convey the image of remote P2P accommodation to consumers through visual communication channels (Flavián et al., 2019).

VR is “a computer-generated 3D environment that simulates intricate real-life situations and contexts, allowing people to immerse, navigate, and interact” (Wei et al., 2019, p. 283). VR provides users with physical immersion and psychological presence in the virtual environment (Fan et al., 2022). From a technological perspective, VR can be divided into two types: (1) immersive VR (wearable devices, e.g., head-mounted displays), and (2) nonimmersive VR, which is typically implemented on personal computers or mobile device screens and speakers (Errichiello et al., 2019). From a simulated environment perspective, VR can be divided into two types: (1) computer-simulated VR, which is a code-based setting created by experts in software development, and (2) 360-degree real panorama VR, derived from 360-degree panorama technologies to create immersive videos and pictures of real scenes (Fan et al., 2022). Nevertheless, regarding effects on consumer learning or hotel visiting intention, immersive VR headsets may not perform better than 360-degree tours onscreen (McLean & Barhorst, 2022).

Compared to traditional 2-D or 3-D preview modes, VR provides enhanced, detailed visual information by extending media richness and providing multisensory support (e.g., visual and proprioceptive; Flavián et al., 2019; Israel et al., 2019). High-quality 3-D images (or 360-degree realistic panoramic images) are the basis for the interactive function of a VR preview, allowing users to freely control the elements and intensity of information in a mediated environment with a self-centered view to research and inspect the details of P2P accommodation (Brivio et al., 2021). By creating a telepresence and sensory experience (Alyahya & McLean, 2022; Ying et al., 2022), VR makes the intangibility of booking services tangible (Bogicevic et al., 2019). These features of VR visualization are pronounced by visual communication (Suh & Lee, 2005), allowing consumers to gain objective comprehension of realistic images and function settings of target reservations, which conditions consumers to form semantic perceptual judgments about the preview content (Kang, 2020).

As an enhancement technique, PIC is defined as a direct operation from image pixels (de Araujo et al., 2014). Owing to changes in lighting, position, and other factors in the practical image-acquisition process, it is difficult to obtain high-quality images, which can impede consumers’ ability to judge a product’s quality. Hence, the PIC preview approach has been widely used in marketing because it enhances the image quality and contrast between represented objects and improves the relevant visual perception features by highlighting the most significant elements (Wang et al., 2011).

For visualization, PIC provides an induced destination image adjusted by marketers: first, PIC enhances the visual aesthetics of pictures, such as increasing saturation; second, PIC selectively presents accommodation content (Lourenção et al., 2020). For example, marketers can use photos edited by PIC to optimize accommodation advantages (e.g., modern design style) and conceal negative aspects (e.g., poor sanitary conditions). Because of the enhancements of the visual servicescape’s aesthetic value and attractiveness allowed by PIC, consumers imagine a positive journey that facilitates an emotional response of pleasure, excitement, and joy, potentially reducing their booking risk. Thus, the visual core of PIC in a P2P accommodation preview is its ability to enhance aesthetic impressions or symbolic associations (e.g., personal beliefs) by providing attractive visual information (Kusumasondjaja & Tjiptono, 2019).

Combining Crilly et al.’s (2004) expanded framework of communication in the visual domain (Baek & Michael Ok, 2017; Homburg et al., 2015), we proposed a framework for the visual communication process of P2P accommodation previews (see Figure 1).

Consumer Engagement

Consumer engagement is an important research topic associated with consumer behavior, especially in virtual and interactive environments (Claffey & Brady, 2019). The meaning of consumer engagement in a technology-mediated experience is similar to user engagement, which is “the quality of an experience characterized by the user’s cognitive, temporal, affective, and behavioral investment when interacting in a virtual environment” (O’Brien et al., 2018, p. 29). Tourism and hospitality research has explored the relationship between consumer engagement and perceived service experience. Consumer motivation, authentic perception, attachment, involvement, interactivity, and other factors regarding tourist objects may stimulate consumer engagement (Bryce et al., 2015; Rather et al., 2019; Romero, 2018) and encourage co-created value, trust, and loyalty (Rather et al., 2019), leading to patronage intention (Organ et al., 2015).

Adopting visual communication technologies can stimulate consumer engagement in online communities or consumption processes (Claffey & Brady, 2019). Specifically, the interactivity and authenticity of VR technology may affect consumer behavior through cognitive engagement (e.g., telepresence, immersion, perceived usefulness, perceived ease of use; Flavián et al., 2019; Israel et al., 2019; Kim, Lee, & Preis, 2020), and affective engagement (e.g., positive emotion and hedonic experience; Flavián et al., 2019; Willems et al., 2019). Nonetheless, PIC technology can provide optimized images (de Araujo et al., 2014) that generate a positive impression through high-quality visual cues, ultimately promoting an individual’s behavioral engagement in the virtual world, such as liking and forwarding (Vilnai-Yavetz & Tifferet, 2015). Thus, we drew on marketing-related research (Claffey & Brady, 2019) to view consumer engagement in technology-based online destination offerings as a multidimensional concept with cognitive, affective, and behavioral aspects (Harrigan et al., 2018).

Appraisal

Social psychology literature has shown that appraisal has cognitive and affective dimensions (Batra & Ahtola, 1991; Lee et al., 2012). Cognitive appraisal is the utilitarian aspect of attitude that involves the means-ends about the expectation of consequences (e.g., goal achievement), whereas affective appraisal is the hedonic aspect of attitude that evaluates an individual’s feelings, emotions, and gut reactions to an attractive object (Kempf, 1999; Lee et al., 2012). In online reservation contexts, consumer booking decisions typically rely more on cognitive appraisal to reduce booking risk (Kim, Lee, & Jung, 2020). Moreover, consumer reservation behaviors are at the pre-purchase stage of the customer journey, meaning that consumers have not yet truly experienced P2P accommodation services, and there may be no apparent emotional response due to a service experience (McLean & Barhorst, 2022). Therefore, we followed previous research and used only cognitive appraisal in its research model (Claffey & Brady, 2017, 2019).

Regarding cognitive appraisal, the applied technology will more likely produce a positive cognitive appraisal when it matches the individual motivation or can help the individual achieve task goals (Lee & Chen, 2011; Li et al., 2017). When consumer needs are satisfied, consumers typically form a positive evaluation of the environment or the object; when their needs are not satisfied, the evaluation is likely negative (Kim, Lee, & Preis, 2020). Cognitive appraisal has been used to mediate consumers’ psychological and behavioral responses to certain stimuli (Lee & Chen, 2011; Lee et al., 2012). Specifically, consumer expectations, such as hedonic, utilitarian, and integrative needs, affect the cognitive appraisal of their psychological engagement. In turn, cognitive appraisal leads to behavioral outcomes or necessary emotional formation conditions (Claffey & Brady, 2017, 2019).

Research Hypotheses

Duality Models and the TEEP Framework

The dual system and process theories (i.e., duality theories) show that individuals have two different ways of thinking and have been widely used to explain consumer decision-making processes (Mugg, 2016). Considering that the duality theories accompany each consumer decision-making stage, duality models have been applied to persuasion and attitude change (elaboration likelihood model [ELM] and heuristic-systematic model [HSM]), judgment and decision-making (experimental-analytic model [EAM]), and consumption behavior (reflective–impulsive model [RIM]; Samson & Voyer, 2012). Different duality models share some common attributes (Mugg, 2016): first, system 1 (S1) is a fast and automatic process without accurate details and context related to an individual’s implicit attitude (Wilson et al., 2000); second, system 2 (S2) develops slowly and thoughtfully, following logic, social norms, and abstract thinking. Previous research indicates that S1 is suitable for hedonic experience activities, whereas S2 hinders this process and prompts individuals to focus on utilitarian values (Chen & Chancellor, 2019; Mugg, 2016).

When focusing on online accommodation reservations, with the visual communication process (Figure 1), consumers form an aesthetic impression, symbolic association, or functional interpretation of a P2P accommodation preview via the different visual characteristics of VR/PIC (Baek & Michael Ok, 2017). However, duality theories suggest that aesthetic impressions and symbolic associations can be used as peripheral information-processing cues that stimulate S1 processes (Chang et al., 2020). Moreover, based on more detailed and authentic information (Meng & Choi, 2019), functional interpretation may provide direct and persuasive evidence for reservations, motivating consumers to use S2 to process the information (Carvajal-Trujillo et al., 2021). Further, this dual system of processing, inspired by visual communication features, is accompanied by subsequent cognitive, affective, and behavioral engagement (Kim, Lee, & Jung, 2020; Samson & Voyer, 2012).

Based on the above analysis, we integrated duality models into multiple stages of the expanded TEEP framework (Figure 2) to explore how consumers trigger the corresponding information-processing mechanism by receiving previews with different visual features, influencing consumers’ psychological engagement (the persuasion and attitude change stage, ELM), the realization of value (the judgment and decision-making stage, EAM), and promoting behavioral engagement (the reservation behavior stage, RIM).

In addition to visual previews (VR or PIC), we also incorporated other key accommodation booking factors in the research model (Kong et al., 2019; Park et al., 2019). Considering that both visual cues and textual descriptions are provided for online accommodation reservations in the persuasion and attitude change stage, we also focused on the moderating role of message appeal emphasis (informational vs. emotional) from the perspective of dual-model HSM (Xiang et al., 2019).

In the judgment and decision-making stages, we focused on the role of consumer booking motivations in consumer appraisal (Chang et al., 2020). By integrating the information content factor price with booking motivations, we set two boundary conditions (consumer need for comfortable or economical P2P accommodations) to explore the influence of psychological engagement on booking decisions under selected dual systems (i.e., EAM). The proposed relationships among the expanded TEEP framework, duality theories, and research model are shown in Figure 3.

Persuasion and Attitude Change Stage: VR/PIC Preview and Consumer Engagement

In the first step of the persuasion and attitude change stage, consumers generate an intuitive evaluation based on the quality and characteristics of the received information from visual previews, which compels them to adopt a specific type of persuasion mechanism. ELM is a classical duality model that reflects persuasion and attitude changes (Samson & Voyer, 2012), in which the central or peripheral routes stimulate the evolution of individual attitudes (Macinnis et al., 2002). VR provides realistic, rich, interactive visual information that allows consumers to seek detailed information on accommodation during the pre-reservation stage, thus prompting them to form a functional interpretation of preview content and adopt the central route to evaluate accommodation performance (Chang et al., 2020; Meng & Choi, 2019). The information provided by the PIC preview is abstract and focuses on aesthetic perceptions or symbolic associations; these emotional and heuristic cues are more likely to inspire peripheral processes (e.g., emotions and experiences) in consumers (Macinnis et al., 2002).

Visual cues from physical accommodation environments trigger cognitive engagement when processing VR accommodation information (Suh & Lee, 2005). Consumers can think about content through the central route and test the relevance and availability of detailed evidence to realize their target, associated costs, and return rates to form judgments about an accommodation (Bhattacherjee & Sanford, 2006). However, the concise and highly aesthetic information provided by PIC previews typically induces consumers to adopt the peripheral route, focusing on the expected self-satisfaction obtained through accommodation. Therefore, they are likely to experience enjoyment and hedonic pleasure, which lead to an affective engagement process. Thus, we proposed the following hypotheses:

H1: Consumers prefer to trigger cognitive engagement when they experience VR accommodation previews.

H2: Consumers prefer to trigger affective engagement when they experience PIC accommodation previews.

Moderator: Accommodation description—Message appeal emphasis

During the persuasion and attitude change stage, consumers’ adoption of information-processing routes can be influenced by an emphasis on message appeal (Petty et al., 1983; Xiang et al., 2019). Informational (logical) and emotional (pathos) aspects are two of the main appeals used in business information persuasion (Kulkarni et al., 2020; Xiang et al., 2019). Informational appeal emphasizes product attributes and functions, whereas emotional appeal emphasizes products’ emotional resonance and pleasure.

The message appeal of accommodations provides cues to consumers about different types of information, thus leading them to mobilize cognitive resources to process emotions and valence, ultimately improving consumer decision-making. For example, when an accommodation’s message appeal emphasizes logical attributes (e.g., facilities, transportation, sanitation), consumers will typically evoke attention to valence, which triggers S2 (Xiang et al., 2019). Conversely, when an accommodation’s message appeal emphasizes the emotional atmosphere, consumers pay attention to the warmth attributes of the accommodation that evokes emotion, thereby triggering S1 (Xiang et al., 2019). Therefore, message appeal emphasis allows consumers to generate an auxiliary impression in addition to previewing the content (Zhang, Hanks, et al., 2019).

Consequent to the above analysis, for message appeal emphasis, consumers may also trigger the HSM to process information. Unlike ELM’s single cognitive route, HSM emphasizes that consumers can be persuaded by both heuristic and systematic routes simultaneously and that these two routes have a parallel relationship (Samson & Voyer, 2012). This means that when the advertising message emphasizes information, the effect of the VR preview on cognitive engagement is likely to be enhanced (explained by the ELM). However, for the PIC preview, in addition to affective engagement, informational appeal activates cognitive engagement (explained by the HSM). When the message emphasizes emotion, the PIC preview’s effect on emotional engagement is likely augmented (explained by the ELM). However, for VR previews, in addition to cognitive engagement, emotional appeal activates affective engagement (explained by the HSM). Thus, we proposed the following hypotheses:

H3: Message appeal emphasis moderates the relationship between accommodation preview modes and consumer engagement.

(a) For the PIC preview, relative to no emphasis, an informational message enhances consumer cognitive engagement but has no effect on affective engagement, whereas an emotional message enhances consumer affective engagement but has no effect on cognitive engagement.

(b) For the VR preview, relative to no emphasis, an emotional message enhances consumer affective engagement but has no effect on cognitive engagement, whereas an informational message enhances consumer cognitive engagement but has no effect on affective engagement.

Judgment and Decision-Making Stage: Consumer Engagement and Appraisal

Boundary condition: Motivation—Consumer needs for accommodations

In the judgment and decision-making stages, the appraisal process depends on the consistency between consumers’ perceived values and their original motivations (Buhalis et al., 2019; Willems et al., 2019). Considering that consumer engagement is a central factor in forming perceived value, we further explored how the matching effect between consumer engagement and booking motivations affects the appraisal process.

According to cognition and motivation theory, consumer needs reflect individual consumers’ motivations and preferences in information processing (Xiang et al., 2019). Consumer needs for P2P accommodation have been divided into two categories—economical and comfortable reservations—distinguished by extrinsic motivation (i.e., motivating consumers to pursue instrumental value) versus intrinsic motivation (i.e., motivating consumers to focus on pleasure in the task; Chung et al., 2018; Ketter, 2019). Economical accommodation focuses on functional performance to satisfy utilitarian needs, whereas comfortable accommodation highlights experience value to meet hedonic needs. In the duality theories, consumer judgment and decision-making may be affected by experimental or analytical thinking modes (Samson & Voyer, 2012). The experimental thinking mode of processing information tends to utilize what is automatically or easily retrievable from memory by relying on impressions and intuitions. The analytical thinking mode relies on logical evaluation, calculation, and comparison of evidence.

Consumers are relatively concerned about the functional value of P2P accommodation when they wish to reserve an economical accommodation. During this process, consumers are more inclined to obtain detailed, authentic, high-quality information about accommodations through cognitive engagement (Slevitch et al., 2022) while utilizing analytical thinking to logically evaluate the evidence and weigh the costs and benefits of making reservations. Therefore, VR previews are more suitable than PIC previews because VR stimulates consumers to participate in cognitive engagement, consistent with their utility booking goals, and then make an analytical appraisal. Thus, we proposed the following hypothesis:

H4: Cognitive engagement will positively influence appraisal when consumers need economical accommodations.

When consumers desire comfortable accommodations, they have more hedonistic and idealistic needs. The PIC preview mode is more visually aesthetic and symbolically valuable (Lourenção et al., 2020), which may lead consumers to engage in experiential thinking because of heuristic cues (e.g., aesthetics, design, intuition) and make decisions related to impressions and intuitions (Samson & Voyer, 2012). Consequently, PIC previews may be more suitable in this situation for triggering affective engagement, which will be consistent with consumers’ hedonic booking goals, leading to positive consumer appraisal. Thus, we proposed the following hypothesis:

H5: Affective engagement will positively influence appraisal when consumers need comfortable accommodations.

Reservation Behavior Stage: Appraisal and Patronage Intention

As an organism’s response, cognitive appraisal will mediate environmental stimulation and organism behaviors, including consumer behaviors (Kim, Lee, & Jung, 2020). In the reservation behavior stage, individuals are more likely to apply the RIM for consideration (Samson & Voyer, 2012). In the reservation of an economical accommodation, consumers obtain accommodation information through cognitive engagement and then match it with their functional expectation to form a cognitive evaluation judgment. RIM states that, during the evaluation, consumers compare their appraisal with other alternatives, reflect on their past booking experience, and rationally decide whether to proceed with the reservation (Samson & Voyer, 2012). In the reservation of comfortable accommodation, consumers generate an overall perception of the accommodation (e.g., first impression and affective clusters) through affective engagement (Samson & Voyer, 2012). According to RIM, consumers impulsively form the intention to move forward when their appraisal is consistent with their affective expectations of an ideal accommodation. Therefore, the appraisal process is fluent when information processing matches reservation targets, leading to positive behavioral intentions. Thus, we proposed the following hypothesis:

H6: Appraisal will positively influence patronage intention toward the accommodation.

Research Design

We explored how different P2P accommodation preview modes influence consumer decision-making processes and further determined the boundary conditions of this operating mechanism. We tested these hypotheses using two studies. The first step of Study 1 verified that in the persuasion and attitude change stage, the visual characteristics of the VR/PIC preview drove cognitive (affective) engagement (H1 and H2). In Step 2, in the judgment and decision-making stage, consumers matched the engagement process with their original reservation motivations (economical vs. comfortable) and reviewed P2P accommodation (H4 and H5) thereafter. In Step 3, the reservation behavior stage and consumer appraisal lead to consumer patronage intention toward P2P accommodation (H6). Based on Study 1, Study 2 further explored the effect of message emphasis (informational vs. emotional) on how consumers allocate cognitive resources in the persuasion and attitude change stage (H3).

Analysis of Population Characteristics

We compared the demographic profile of the sample in geographical distribution, gender, age, income, and educational level with the background characteristics of Chinese outbound tourists. The results are shown in the Supplemental Appendix. First, the geographical distribution of participants showed a regional eastern–central–western decline, which is consistent with the distribution characteristics of Chinese outbound tourists and with GDP (CAT, 2018). Second, participants showed gender balance (56.7% male), youthfulness (M_study1 = 27.84; M_study2 = 29.64), and relatively high income and educational levels, consistent with the background characteristics of Chinese outbound tourists (CTA, 2020a, 2020b).

Moreover, the demographic profile implied an excellent basis for further analysis of our study. First, participants’ good educational background and income meant they had a certain personal innovativeness (M_study1 = 5.21, SD = 0.99; M_study2 = 5.34, SD = 0.83) and could accept the VR and PIC reservation modes. Second, the demographic profile allowed us to analyze the findings in relation to geographic distribution. Table 1 reflects the regional characteristics of the sample, showing that participants from the eastern region had a higher level of individual innovativeness than those from the central and western regions. In addition, participants in the eastern region reported a higher level of patronage intention in the PIC condition than in the VR condition; however, the opposite was true for participants in the center and west.

Table 1.

Sample Test of Region.

	Study 1			Study 2
	Eastern	Central	Western	Eastern	Central	Western
Cognitive engagement
VR	5.72 (0.40)	5.50 (0.44)	5.67 (0.56)	5.80 (0.60)	5.85 (0.51)	5.72 (0.60)
PIC	5.41 (0.70)	5.25 (0.62)	4.96 (0.54)	5.36 (0.54)	4.92 (0.60)	4.62 (0.51)
Static photo	4.80 (0.58)	4.90 (0.65)	4.50 (0.56)	—	—	—
Affective engagement
VR	5.56 (0.62)	5.44 (0.51)	5.41 (0.63)	5.22 (0.56)	5.20 (0.62)	5.28 (0.61)
PIC	5.88 (0.55)	5.77 (0.49)	5.58 (0.59)	5.91 (0.52)	5.66 (0.54)	5.39 (0.52)
Static photo	4.92 (0.66)	4.47 (0.68)	4.66 (0.59)	—	—	—
Cognitive appraisal
VR	5.80 (0.49)	5.80 (0.40)	5.79 (0.59)	5.84 (0.49)	5.72 (0.56)	5.84 (0.52)
PIC	5.75 (0.54)	5.75 (0.57)	5.53 (0.51)	5.79 (0.53)	5.55 (0.64)	5.17 (0.57)
Static photo	5.20 (0.58)	5.23 (0.98)	4.97 (0.42)	—	—	—
Patronage intention
VR	5.82 (0.41)	5.80 (0.37)	5.73 (0.45)	5.96 (0.44)	5.93 (0.32)	5.92 (0.35)
PIC	5.92 (0.43)	5.61 (0.43)	5.42 (0.21)	6.16 (0.37)	5.38 (0.40)	5.05 (0.51)
Static photo	5.02 (0.54)	4.98 (0.45)	4.98 (0.28)	—	—	—
Consumer innovativeness
VR	5.45 (0.65)	5.16 (0.69)	5.23 (0.60)	5.57 (0.67)	5.15 (0.75)	5.18 (0.56)
PIC	5.48 (0.61)	5.10 (0.70)	4.80 (0.67)	5.56 (0.61)	5.05 (0.65)	4.71 (0.73)
Static photo	5.32 (0.67)	4.74 (0.64)	4.50 (0.65)	—	—	—

Note. The numbers in brackets are the standard deviations of the variables. The eastern region includes participants whose IP addresses were Beijing, Shanghai, Jiangsu, Zhejiang, Shandong, Fujian, Liaoning, Hainan, Guangdong, Hebei, and Tianjin; the central region includes Henan, Shanxi, Jiangxi, Anhui, Inner Mongolia, Heilongjiang, Jilin, Hunan, and Hubei; the western region includes Xinjiang, Shaanxi, Gansu, Qinghai, Sichuan, Yunnan, Chongqing, Guangxi, Ningxia, and Tibet.

Study 1

Method

Accommodation stimuli

In Study 1, we conducted a 3 (preview mode: VR vs. PIC vs. control) × 2 (boundary condition: economical vs. comfortable) between-subjects design experiment. We selected two accommodations from Kaolahome (https://www.kaolahome.com/) as stimuli (determined by Pretest 1; see the Supplemental Appendix). Kaolahome, a P2P accommodation platform headquartered in Melbourne, Australia, provides booking services for Chinese people traveling and living abroad and is committed to building a P2P accommodation flagship brand. We chose this platform for two reasons: (1) it provides all three types of preview modes simultaneously: 360-degree VR, PIC, and ordinary photos; and (2) as an overseas start-up platform that serves Chinese tourists, using Kaolahome helps us avoid the confounding effect of consumers’ previous brand knowledge on the results.

Stimuli design

We provided a booking interface with a P2P accommodation preview (VR vs. PIC vs. control), a description of facilities (economical vs. comfortable), and a price tag (high vs. low) to simulate the booking situation. This approach was confirmed in a previous study (Bresciani et al., 2021). We chose economical and comfortable accommodations to manipulate consumer accommodation needs (boundary condition). Research has demonstrated that the price and scope of services (or facilities) are the main differences between economical and upscale hotels (Brotherton, 2004; Jang et al., 2021; Luo et al., 2021). Thus, the price and service of P2P accommodations in the stimuli design followed the division of accommodation levels from Fu et al. (2020) and Meituan.com (the second-largest OTA in China) to ensure authenticity and accuracy. Under the comfortable reservation condition, the accommodation booking price was 2,000 RMB (approximately 410 AUD; at a high level), a private villa with a swimming pool providing luxurious facilities. Under the economical reservation condition, the accommodation booking price was 700 RMB (approximately 135 AUD; at the low or medium level), a downtown apartment with basic facilities.

Manipulation of preview modes

Under each economical and comfortable accommodation condition, participants were randomly assigned to three groups. In the VR group, participants could access the VR preview by clicking the link and exploring the 360-degree VR panorama by clicking, zooming, and rotating, thus viewing all details. In the PIC group, the sharpness and contrast were adjusted for all accommodation photos to make them more aesthetically pleasing. In the ordinary photo group, all photos depicted the original appearance of the accommodation and were not processed using any type of technology (All stimuli were determined by Pretest 1; see the Supplemental Appendix).

Main experiment

Participants and procedures

We recruited potential participants for our study and conducted an online experiment in December 2020 using a well-established platform, Credamo (https://www.credamo.com). We chose this platform for two reasons: (1) Credamo is an effective platform that manages the supply and demand of assignments for participants, and (2) Credamo, with a sample database of 2.8 million Chinese individuals, is found to be demographically diverse (Huang & Sengupta, 2020).

We included a total of 316 participants in Study 1. We first used three screening items adapted from a similar study conducted by Bogicevic et al. (2019) to choose relevant individuals to ensure the validity and reliability of the results. Only participants who met the following requirements were able to complete the task: they (1) were 18 years or older, (2) had reserved accommodations in the past, and (3) had never experienced cybersickness after spending time in virtual environments. We randomly assigned them to one of two boundary conditions (economical vs. comfortable) and used the three preview modes (VR vs. PIC vs. control) as independent variables. We asked participants to imagine that they would soon embark on a vacation in another country; thus, they would need to book a P2P accommodation in Kaolahome. Thereafter, by group, they previewed accommodations in one of three preview modes. After excluding incomplete information and overly quick responses, 293 valid responses were recruited (57.7% male, average age = 27.84, see the Supplemental Appendix for more information). The sample size was larger than the suggested size of 216 from G*Power, a medium effect size (i.e., .25) at 80% power with six groups (Luo et al., 2023).

Measurements

After the preview, participants completed a questionnaire. To measure consumer engagement (including cognitive engagement [CE] and affective engagement [AE]), we adapted a seven-item consumer engagement scale (Hollebeek et al., 2014). We adapted a four-item cognitive appraisal scale to measure appraisal (AP; Lee et al., 2012). We measured the dependent variable, patronage intention (PI), using a three-item scale (Kukar-Kinney & Walters, 2003). We set up customer innovativeness (four-item scale) and personal involvement inventory (four-item scale) as covariates (Bogicevic et al., 2019). All items used a seven-point Likert-type scale. We used a one-item scale to measure brand familiarity to avoid consumer brand preferences affecting the results (Thomas & Jewell, 2019). Finally, we used several items to measure the demographic variables and evaluate the participants. Table 2 presents descriptive statistics and Cronbach’s α for all variables.

Table 2.

Study 1: Descriptive Statistics, Correlation, and Average Variance Extracted (AVE).

Variable	CE	AE	AP	PI	CI	PII
1. Cognitive engagement (CE)	.804
2. Affective engagement (AE)	.554**	.814
3. Appraisal (AP)	.694**	.587**	.782
4. Patronage intention (PI)	.633**	.550**	.672**	.880
5. Customer innovativeness (CI)	.512**	.375**	.408**	.442**	.802
6. Personal involvement inventory (PII)	.470**	.390**	.527**	.427**	.387**	.722
Composite reliability	.846	.887	.863	.912	.878	.814
Cronbach’s alpha (α)	.726	.828	.788	.855	.693	.813
AVE	0.647	0.662	0.611	0.775	0.643	0.522
Mean	5.25	5.35	5.56	5.53	5.21	5.11
Standard deviation	0.92	0.97	0.78	1.02	0.99	0.53

Note. N = 293.

p < .01.

Results and Discussion

Manipulation checks

We tested manipulations of the preview mode through perceived interactivity and aesthetics. We combined all six groups to form VR, PIC, and control groups. A one-way ANOVA revealed that the perceived interactivity differed across the three preview modes (F [2, 290] = 24.16, p < .001). Specifically, the VR preview (M = 5.84) was perceived to be more interactive than the PIC preview (M = 5.04, p < .001) and control preview (M = 4.68, p < .01). In addition, one-way ANOVA revealed that perceived aesthetics differed across the three preview modes (F [2, 290] = 27.37, p < .001). Specifically, the PIC preview (M = 5.75) was perceived to be more aesthetic than the VR preview (M = 5.21, p < .001) and the control preview (M = 4.83, p < .01). These results supported the proposed ranking of the three preview modes based on their degrees of interactivity and aesthetics.

We tested the manipulation of boundary conditions with one item, namely, “Please rate the extent to which the accommodation is comfortable (economical),” using a seven-point Likert scale. We combined the six groups to create economical and comfortable groups. The results of one-way ANOVA revealed that the perceived economics of accommodation differed across the three preview modes (F [1, 291] = 53.447, p < .001). Specifically, the economical group (M = 4.32) was perceived as more economical than the comfortable group (M = 5.57, p < .001). These results supported the proposed ranking of the two boundary conditions concerning their degree of economical feeling.

Effect of preview mode

We conducted a one-way ANOVA to test H1 and H2. We combined all six groups to form the VR, PIC, and control groups. The results revealed that the effect of the VR preview mode was stronger for evoking cognitive consumer engagement (M_VR = 5.68 vs. M_PIC = 5.30 vs. M_control = 4.78, F [2,290] = 27.488, p < .001), which supported H1. In addition, the effect of the PIC preview mode was stronger for evoking affective consumer engagement (M_PIC = 5.80 vs. M_VR = 5.52 vs. M_control = 4.73, F [2,290] = 40.688, p < .001), which supported H2.

The structural models in two boundary conditions

We conducted a structural equation modeling (SEM) procedure using SmartPLS 3 to test the indirect effect of preview mode on patronage intention and the underlying mechanisms of consumer engagement and appraisal. We used two SEM models to verify H4, H5, and H6, derived from the two boundary conditions. We coded the independent variable in both models as a dummy variable. Specifically, we coded the VR preview as 1, the PIC preview as −1, and the control preview as 0.

For the economical accommodation condition (Figure 4, Model 1), when participants wanted to book an economical accommodation, VR preview had a significant effect on cognitive engagement (β = .291, p < .001), and cognitive engagement led to appraisal (β = .486, p < .001), thus supporting H1 and H4. This result revealed that cognitive engagement satisfied consumers’ cognitive needs for booking economical accommodation and that there was a matching effect. Finally, positive appraisal led to patronage intention (β = .641, p < .001), supporting H6. However, the preview mode had no significant effect on affective engagement, which meant that affective engagement did not fit consumers’ cognitive habits regarding the economical reservation. In addition, Model 1 explained 8.5% of the variance in cognitive engagement, 59.0% in appraisal, and 58.1% in patronage intention.

In the comfortable accommodation condition (Figure 4, Model 2), PIC preview had a significant effect on affective engagement (β = −.211, p < .01), thus leading to appraisal (β = .184, p < .05), which supported H1 and H5. This result confirmed that there was also a matching effect, such that affective engagement satisfied consumers’ cognitive need to book comfortable accommodations. Finally, positive appraisal led to patronage intention (β = .452, p < .001), thereby supporting H6. However, the PIC preview mode had no significant effect on cognitive engagement, which meant that cognitive engagement did not fit consumers’ cognitive habits of booking comfortable reservations. In addition, Model 2 explained 4.4% of the variance in affective engagement, 52.1% in appraisal, and 39.6% in patronage intention.

Study 2

Method

Accommodation stimuli

In Study 2, we conducted a 2 (preview mode: VR vs. PIC) × 3 (message appeal type: informational vs. emotional vs. control) between-subjects design. We chose one mid-level accommodation from Kaolahome, which had a kitchen, sitting room, bedroom, bathroom, and viewing balcony.

Considering that Study 1 supported the effects of preview modes on consumer engagement, Study 2 determined whether message appeal influenced the mechanism between the preview mode and consumer engagement. Thus, we supplied only two preview modes, the VR and PIC groups, which had the same forms as those described in Study 1.

For Study 2, we designed three message appeal types for each VR or PIC group to manipulate message appeal. In the informational appeal group, the title and description of the accommodation introduction page showed details of the specific functions in the form of lists, such as traffic conditions, layout, facilities, and services provided. In the emotional appeal group, the title and description on the introduction page described the accommodation’s romantic living experience and emphasized the emotional atmosphere. In the control group, only the VR or PIC preview of the accommodation was supplied (all stimuli were determined by Pretest 2; see the Supplemental Appendix).

Main experiment

Participants, procedures, and measurements

As in Study 1, we used the same online platform, Credamo, to recruit potential participants and conduct the online experiment in January 2021. There were 322 participants in the experiment; each employed the same screening items as in Study 1. We asked these participants to imagine they would soon take a vacation in another country; thus, they needed to book accommodation in Kaolahome. Thereafter, we randomly assigned them to either VR or PIC preview mode and used three message appeal types (information vs. emotional vs. control) as moderating conditions. The specific grouping is presented in the Supplemental Appendix. After reading the introduction page and experiencing accommodation previews, participants completed a questionnaire. After excluding invalid responses, 314 participants were identified (54.8% male, average age = 29.64, see the Supplemental Appendix for more information). We used the same contexts, variables, and items as those employed in Study 1, and Table 3 shows the descriptive statistics and Cronbach’s α for all the abovementioned variables.

Table 3.

Study 2: Descriptive Statistics, Correlation, and AVE.

Variable	CE	AE	AP	PI	CI	PII
1. Cognitive engagement (CE)	.807
2. Affective engagement (AE)	.397**	.809
3. Appraisal (AP)	.478**	.324**	.770
4. Patronage intention (PI)	.547**	.517**	.540**	.840
5. Customer innovativeness (CI)	.260**	.196**	.240**	.256**	.761
6. Personal involvement inventory (PII)	−.042	.056	−.022	−.073	.088	.815
Composite reliability	.849	.884	.852	.878	.845	.888
Cronbach’s alpha (α)	.732	.824	.768	.792	.757	.839
AVE	0.652	0.655	0.593	0.706	0.579	0.665
Mean	5.46	5.50	5.72	5.87	5.34	5.30
Standard deviation	0.86	0.84	0.73	0.75	0.83	1.01

Note. N = 314.

p < .01.

Results and Discussion

Manipulation checks

We used perceived interactivity and aesthetics to test the effects of manipulating the two preview modes. We combined the six groups of responses to form the VR and PIC groups. A one-way ANOVA revealed that the perceived interactivity differed across the two preview modes (F [1, 312] = 40.048, p < .001). Specifically, the VR preview (M = 5.92) was perceived as more interactive than the PIC preview (M = 5.09, p < .001). Moreover, one-way ANOVA revealed that perceived aesthetics differed between the two preview modes (F [1, 312] = 6.396, p < .05). Specifically, the PIC preview (M = 5.68) was perceived to be more aesthetically pleasing than the VR preview (M = 5.45, p < .001). These results supported the proposed ranking of the two preview modes regarding their degrees of interactivity and aesthetics.

We tested the message appeal manipulation using four items adapted from Williams and Drolet (2005). For informational appeal, there were two items: (1): “This advertisement made me focus on my thoughts about this accommodation,” and (2) “This advertisement is directed at making me think something about this accommodation.” The other two items used to test emotional appeal were (1): “This advertisement makes me focus on my feelings about this accommodation,” and (2) “This advertisement is directed at making me feel something about this accommodation.” We assessed all items using a seven-point Likert-type scale.

We combined all six groups to form the informational, emotional, and control groups. The results of the one-way ANOVA revealed that the perceived informational appeal differed across the three types of messages (F [2, 311] = 7.414, p < .005). Specifically, the informational appeal group (M = 5.79) was perceived to be more informational than both the emotional appeal group (M = 5.27, p < .001) and the control group (M = 5.43, p < .001). The results of the one-way ANOVA also revealed that the perceived emotional appeal differed across the three types of messages (F [2,311] = 13.329, p < .000). Specifically, the emotional appeal group (M = 5.83) was perceived to be more emotional than the informational (M = 5.09, p < .001) and control groups (M = 5.38, p < .001). These results supported the proposed ranking of the three message types based on the degree of affective message emphasis.

The moderating effect of message appeal

To test the moderating effect of message appeal, we first used a two-way ANOVA to compare the effects of informational and emotional information appeal with the control group in VR and PIC preview modes. For the VR preview mode, compared with the control group, the informational group led to more cognitive engagement (M_{informational} = 6.02 vs. M_control = 5.71, F [1,102] = 4.097, p < .05); the emotional group showed more affective engagement (M_emotional = 5.50 vs. M_control = 5.04, F [1,101] = 4.005, p < .05). For the PIC group, compared with the control group, the informational group led to more cognitive engagement (M_{informational} = 5.45 vs. M_control = 5.10, F [1,102] = 5.745, p < .05); the emotional group showed more affective engagement (M_emotional = 5.97 vs. M_control = 5.69, F [1,104] = 4.835, p < .05). These results partly supported H3, as shown in Table 4 and Figures 5 and 6.

Table 4.

Study 2: Results of Multi-Group Analysis on Informational and Emotional Messages.

Preview mode	Dependent variable	Informational appeal			Emotional appeal
		Path model	ANOVA		Path model	ANOVA
		Coefficient	Mean	p-Value	coefficient	Mean	p-Value
VR vs. control	Cognitive engagement	.197 *	6.02 (5.71)	.041	−.034^ns	5.65 (5.71)	.695
VR vs. control	Affective engagement	−.050^ns	5.04 (5.12)	.612	.197 *	5.50 (5.12)	.043
PIC vs. control	Cognitive engagement	.233 *	5.45 (5.10)	.025	−.138^ns	4.86 (5.10)	.135
	Affective engagement	−.060^ns	5.63 (5.69)	.619	.204 *	5.97 (5.69)	.023

Note. We report the mean value of the experimental group in each cell, the mean value of the control group in parentheses, and the coefficients (in bold) of the path model are in each cell. ns = nonsignificant.

p < .05.

To further understand the moderating effect of message appeal, we conducted an SEM using SmartPLS 3. Four SEM models were used to compare the effect of previews (VR and PIC) on consumer engagement under informational or emotional appeal situations with the control group to determine the moderating effect of message appeal. The results revealed that, under the informational appeal condition, compared to the control condition, both the VR (β = .197, p < .05) and the PIC (β = .233, p < .05) previews positively affected cognitive engagement. However, compared to the control condition, the PIC preview under the informational appeal condition did not lead to more affective engagement. The results also revealed that, under the emotional appeal condition, both the PIC (β = .204, p < .05) and the VR (β = .197, p < .05) previews positively influenced affective engagement. However, compared to the control condition, the VR preview under the emotional appeal condition did not lead to more cognitive engagement. Thus, H3a and H3b were both supported. The path coefficients of the four SEM models are listed in Table 4.

The structural models

To reveal the indirect effect of the preview mode on patronage intention and the underlying mechanisms of consumer engagement and appraisal without apparent reservation goals, we chose data from the VR and PIC groups to conduct the SEM procedure using SmartPLS 3. Specifically, for the preview mode, we coded the VR preview as 1 and the PIC preview as −1.

According to the SEM model results (see Figure 7), considering the lack of booking goals (accommodation type), VR and PIC previews significantly affected consumer engagement when participants wanted to book accommodation. In particular, the VR preview had a significant effect on cognitive engagement (β = .404, p < .001) and appraisal (β = .391, p < .001), supporting H1. In addition, the PIC preview had a significant effect on affective engagement (β = −.335, p < .001), and affective engagement led to appraisal (β = .165, p < .05), supporting H2. It was also revealed that for those lacking a booking goal, the path coefficients between consumer engagement and appraisal were lower than those in Study 1. Finally, positive appraisal led to patronage intention (β = .478, p < .001), supporting H6. This model explained 16.3% of the variance in cognitive engagement, 11.2% in affective engagement, 24.3% in appraisal, and 31.6% in patronage intention.

Discussion

Although both VR and PIC preview modes are used in P2P accommodation platforms, limited studies have investigated their influencing mechanisms. Combining the visual communication features of VR and PIC previews, we used the TEEP framework and duality models to examine the effect of VR/PIC previews on the patronage intention for P2P accommodation under Chinese tourist backgrounds. In Study 1, VR/PIC influenced consumers’ appraisal and patronage intention toward accommodations (via cognitive and affective engagement) under different reservation conditions. Specifically, the VR preview influenced consumers to trigger S2 to get more details about the concerned accommodation via cognitive engagement; this is consistent with the appraisal of consumers’ economical accommodation reservation motivation, resulting in a positive patronage intention. However, the PIC preview provided consumers with enhanced photos that displayed the accommodation’s high-quality environment, influencing consumers to trigger S1 and thereby producing more emotional resonance through affective engagement; this is consistent with the appraisal of consumers’ comfortable accommodation reservation motivation, resulting in a positive patronage intention.

Study 2 assessed the message appeal of an accommodation’s advertisements as a moderator (Xiang et al., 2019). When the message emphasized information, the VR preview mode strengthened cognitive engagement, and the PIC preview led to cognitive engagement among consumers. When the message emphasized emotion, the PIC preview strengthened affective engagement, and the VR preview also led to affective engagement among consumers. Considering the lack of apparent reservation goals, although the level of appraisal obtained by the preview mode was reduced, cognitive and affective engagement still met consumers’ specific needs (utilitarian or hedonic) to some extent. Thus, patronage intention was still influenced. These results indicated that VR and PIC had their own prospects and advantages in the context of consumer behavior in P2P accommodation reservations under different advertising message appeals.

Theoretical Implications

We provided several contributions to the literature. First, our study enriched the literature on P2P accommodation visualization. Previous studies had explored the effects of VR and static photo previews on booking intention based on differences in embodiment or interaction but paid little attention to visual communication (Bogicevic et al., 2021; Willems et al., 2019). We drew on and expanded Crilly et al.’s (2004) communication framework in the visual domain to frame the bridge between visual previews of VR/PIC and consumer cognitive and affective responses. The explanation of VR/PIC visual perceptions extended the findings of previous studies regarding online previews and psychological reactions (Bogicevic et al., 2019; Flavián et al., 2019).

More importantly, we constructed a theoretical model for the consumer booking decision process (Heller et al., 2021; Samson & Voyer, 2012). The application of duality theories further translated the differences in the visual perception of VR and PIC into differences in visual information processing. Moreover, the inclusion of the TEEP framework represented the thorough consideration of the complex process of consumers perceiving or adopting the online preview as an autonomous service technology. Moreover, this theoretical model responded to Kim, Lee, and Jung (2020) by classifying consumer responses during viewing previews into cognitive and affective dual pathways and conceptualizing them as consumer engagement. By adding duality models, this model clarified how VR and PIC contribute to appraisal and behavioral intention, respectively, through dual paths of engagement. Thus, our study expanded not only the automatic service literature but also the findings on tourism-related consumption behaviors.

Finally, by incorporating critical online booking factors, we further enriched its dual path theoretical model for understanding how consumers perceive visual preview stimuli. We revealed matching effects between information processing and visual perceptions by testing the boundary and moderating effects. Specifically, the finding of a consistent impact between booking motivations and visual perceptions on appraisal supported Claffey and Brady (2017, 2019) and delved into the dynamic realization of value during P2P accommodation reservations. Additionally, the joint effect between visual preview and message appeal revealed the dominance of visual information in decision-making (He et al., 2018), and the finding that message appeal emphasis could moderate the relationship between dual paths of information processing enriched the destination marketing literature from the view of advertising (Xiang et al., 2019).

Managerial Implications

Our study revealed important implications for technology adoption and experience design for P2P accommodation providers. First, the results suggest potential marketing strategies (i.e., VR and PIC) to overcome the “intangible” aspects and uncertainty associated with the online booking of P2P accommodation reservations. Hygienic conditions and environmental facilities of hotels or P2P accommodations are fundamental factors influencing consumer reservations, and aesthetics and comfortable designs are motivating factors. Thus, providing VR previews can satisfy a consumer’s needs for determining the real accommodation conditions at an economical level; however, a double-edged effect of VR technology, namely, its full range of real service environment display with the risk of exposing potential deficiencies, may lower consumer expectations (El-Said & Aziz, 2022). In the case of platforms or hosts targeting consumer comfort, a VR preview was found to be less effective than PIC in the presence of a gap between the real environment and consumer expectations.

Moreover, we proposed strategies for P2P accommodation platforms and hosts in their selection of online preview modes. P2P accommodation platforms may offer a hybrid preview service to hosts because platform vendors do not delineate clear positioning. Thus, it may be better to use VR and PIC to complement each other in parallel to maximize consumer patronage intention. Platforms and hosts with specific positioning may choose a preview mode consistent with their target consumers’ booking motivations to avoid the cognitive inconsistency inherent in the booking process.

Additionally, we blended advertising with preview modes to provide hybrid marketing suggestions for P2P accommodation platforms and hosts. The message appeal of advertising can be considered a stimulus and neutralizer for the effects of preview modes. For specific positioning (comfortable vs. economical) of P2P accommodation platforms and hosts, advertising messages that match the preview mode reinforce their characteristics. Nevertheless, different collocations can be used for comprehensive platforms and hosts to achieve improved results.

According to our study, platforms and hosts could combine technological approaches and demographic characteristics to cope with environmental uncertainty. Combined with the population test, economically developed areas can act as a “window” for new preview technologies and help overcome the disruptive impact of the COVID-19 pandemic. For platforms and hosts, a hybrid marketing strategy is more effective when adopting a regionally undifferentiated marketing strategy. When adopting a regionally differentiated marketing strategy, PIC is more conducive to the presentation of an accommodation than VR for participants in eastern China (with a more developed economy) because they value an aesthetic experience; for participants in central and western China, VR is more suitable than PIC. In addition, during crises such as the COVID-19 pandemic, when there are restrictions on travel and booking accommodations, complementary visual previews and textual advertising descriptions could be an effective marketing tool to reduce consumers’ perceived risk in both the cognitive and emotional dimensions.

Limitations and Future Research Suggestions

We had certain limitations that may provide directions for future research. First, online experiments are a limited tool for data collection because only those who use a computer or mobile phone and are registered on the panel are recruited for the study (Suess et al., 2020). Future research could use qualitative and quantitative data from multiple sources, such as interviews, online reviews, and surveys, to further triangulate the findings.

Second, we conducted online experiments in the Chinese context, which may limit the generalizability of the results. Because consumer innovativeness may affect VR and PIC experiences, future research can further compare the differences in the new technology experiences of participants from developed and developing regions with regard to the online booking of P2P accommodations; this will help obtain a more robust effect.

Third, we tested three types of online preview of P2P accommodations (VR vs. PIC vs. static photo) in a simulated environment. Future research could conduct field experiments to compare the actual use. Moreover, we used 360-degree real panorama VR as a preview mode of P2P accommodations because immersive VR headsets do not currently have a market for P2P accommodations. However, immersive VR headsets are used in the hotel sector, where online preview is more developed. Despite their availability, McLean and Barhorst (2022) demonstrated no difference between immersive VR headsets and 360-degree real panorama VR regarding consumer learning and hotel visit intentions. Future research can explore the possibility of immersive VR headset applications in the online preview of P2P accommodation and test whether there is a difference between immersive VR headsets and 360-degree panorama VR usage in the P2P accommodation sector.

Fourth, we distinguished only between economical and comfortable P2P accommodations and did not discuss their ownership forms, such as peer-hosted or third-party managed. These different operation systems may also influence consumer perceptions of pre-booking risk. Future work can compare the impact of online previews on consumer reservations of peer-hosted and third-party managed accommodations (including hotels).

COVID-19 Statement

Following Sorakunnas and Konu (2022), the authors declare that COVID-19 has not influenced the theoretical contribution or practical implications discussed. Although we conducted online experiments during the COVID-19 pandemic, the main findings may not have been affected; this is because we examined online preview modes and the online reservation behavior of P2P accommodation, which belong to the pre-purchase stage decision and take place in an online environment rather than in the field on a trip. In addition, the COVID-19 pandemic in China was substantially alleviated during the second half of 2020 to 2021 (https://covid19.who.int/region/wpro/country/cn), and the hypotheses were tested on the Chinese people whose access to travel remained unaffected by the COVID-19 pandemic. Thus, the consumer behavior of the participants in our study may not have been influenced by the pandemic. Nevertheless, to obtain robust conclusions (Ribeiro et al., 2022), it is necessary to collect post-pandemic data to confirm the research model’s validity and applicability.

Supplemental Material

sj-docx-1-jtr-10.1177_00472875221141879 – Supplemental material for Imagination Versus Telepresence: Consumer Patronage Intention Toward Peer-to-Peer Accommodations in Photo-Enhanced Imaginative Conditions and Virtual Reality Contexts

Supplemental material, sj-docx-1-jtr-10.1177_00472875221141879 for Imagination Versus Telepresence: Consumer Patronage Intention Toward Peer-to-Peer Accommodations in Photo-Enhanced Imaginative Conditions and Virtual Reality Contexts by Xiaojun Fan, Xinyu Jiang and Nianqi Deng in Journal of Travel Research

Footnotes

Acknowledgements

We are grateful to our handling editors (Dr. James Petrick, Dr. Geoffrey Crouch, and Dr. Nancy McGehee) and four anonymous reviewers for numerous valuable suggestions and insightful comments that helped to substantially improve the paper. All remaining errors are ours.

Author Contributions

Xiaojun Fan: Conceptualization, Resources, Funding acquisition. Xinyu Jiang: Conceptualization, Methodology, Data curation, Formal analysis, Software, Writing—Original draft preparation. Nianqi Deng: Conceptualization, Methodology, Supervision, Writing—Reviewing and Editing.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was partly supported by the National Natural Science Foundation of China (72272097) and Humanities and Social Sciences Youth Foundation, Ministry of Education of the People’s Republic of China (22YJC630017).

ORCID iD

Nianqi Deng

Supplemental Material

Appendix for this article is available online, or can be found in .

Author Biographies

Xiaojun Fan is a Professor at the School of Management, Shanghai University, PR China. His research interests include network marketing and marketing channel. His work has been published in Tourism Management, Journal of Travel Research, Journal of Business Ethics, European Journal of Operational Research, Transportation Research Part E: Logistics and Transportation Review, Annals of Operations Research, Journal of the Operational Research Society, Electronic Commerce Research and Applications, International Transactions in Operational Research, International Journal of Market Research, Asia Pacific Journal of Marketing and Logistics.

Xinyu Jiang is a PhD Student at the School of Management, Shanghai University, PR China. She focuses on intersection topics of marketing and tourism management. Her work has been published in Tourism Management, Journal of Travel Research, Information Technology and People, Entertainment Computing.

Nianqi Deng is an Assistant Professor at the School of Business Administration, Zhejiang University of Finance and Economics, PR China. His research interests include digital marketing, CnSR, as well as intersection topics of marketing, information systems management, and tourism. His work has been published in Journal of Business Ethics, Tourism Management, Journal of Travel Research, Annals of Operations Research, Information Technology and People, Journal of Research in Interactive Marketing, Marketing Intelligence and Planning, Journal of Retailing and Consumer Services, Transformations in Business and Economics, Telematics and Informatics.

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