Effective airbnb advertising during COVID-19 pandemic: Message format and hypothetical distance

Abstract

Airbnb hosts encounter difficulty in choosing an approach to advertising during unprecedented times caused by the COVID-19 pandemic. This study explores effective Airbnb advertising messages with a particular focus on hypothetical distance based on construal level theory. A 2 (message format: abstract vs. concrete) × 2 (hypothetical distance: low vs. high likelihood of travel) between-subject experiment was conducted. Data collection was conducted in the US during the early phase of the COVID-19 pandemic. The findings revealed that the ‘abstract’ message results in a higher intention to stay when hypothetical distance is ‘low’, whereas the ‘concrete’ message results in a higher intention to stay when hypothetical distance is ‘high’. In addition, the mediating role of message relevance in the relationship between message format and intention to stay was also found. These findings provide meaningful theoretical contributions and have practical implications for tourism and hospitality research.

Keywords

Construal level theory hypothetical distance airbnb advertising message format message relevance intention to stay

Introduction

Composing advertising messages is a critical task for advertisers, who strive to stimulate consumer purchase decisions. As targeted advertising messages can produce substantial impacts on consumers’ brand attitudes, brand choices, and intentions to purchase (Martins, Costa, Oliveira, Gonçalves, & Branco, 2019), many researchers have paid increasing attention to message composition (Sung et al., 2020; Wang & Lehto, 2020). Advertising messages were often created based on psychological theories to better stimulate consumers’ purchase desires. For example, based on regulatory focus theory, advertising messages highlighted either a prevention-focused message (i.e. focusing on the negative consequences of not using the advertised product) or promotion-focused message (i.e. focusing on the positive consequences of using the advertised product) (Sung et al., 2020). Based on construal level theory (CLT), advertising messages also emphasised either an abstract message (i.e. high construal level, focusing on the primary and core attributes of the advertised product) or concrete message (i.e. low construal level, focusing on secondary and surface attributes of the advertised product) (Wang & Lehto, 2020).

Meanwhile, with the enormous success of Airbnb, internal competition on the platform to attract prospective consumers has intensified, resulting in increasing pressure on hosts to advertise their properties effectively through targeted property descriptions and photos, along with review management (Cheng & Jin, 2019). Furthermore, Airbnb hosts encounter difficulty in choosing an approach to advertising during unprecedented times caused by the COVID-19 pandemic (Chen et al., 2022). Despite this important phenomenon, few studies have examined how Airbnb hosts’ targeted advertising messages drive consumer decisions (Liu & Mattila, 2017). Thus, this study fills a research gap by exploring the effectiveness of Airbnb advertising messages by applying construal level theory (CLT) to examine the intervened effect of message format and hypothetical distance.

CLT is a theory in social psychology that explains the relationship between psychological distance and the degree to which people's thinking is abstract or concrete (Chen, 2020; Choi et al., 2019). According to CLT, greater psychological distance is associated with high-level construal, that is, with abstract and decontextualised phenomena, events, or objects, whereas shorter psychological distance is associated with low-level construal, that is, with concrete and contextualised phenomena, events, or objects (Alper, 2020; Kim et al., 2016). Identifying differences in construal levels and message format is important in advertising, because psychological distance constitutes a mental representation of events and objects at different levels, which affects consumers’ reactions to advertising (Alper, 2020; Kim et al., 2016).

Psychological distance has four dimensions: temporal (near vs. distant in time), spatial (near vs. distant in space), social (near vs. distant human relationships), and hypothetical (high vs. low likelihood of occurrence). In hypothetical distance, a high likelihood of occurrence means that a situation is certain to occur, and a low likelihood of occurrence means that it is uncertain whether a situation will occur. These two terms (high vs. low, certain vs. uncertain) are used interchangeably in this study. Taking hypothetical distance as an example, the more certain it is that a person will take a vacation (e.g. the planned holiday is definite, and the flight and Airbnb rental have been paid for), the closer he or she feels to the vacation psychologically and the more concrete the event becomes. Hence, high hypothetical distance is closely associated with low-level construal and concrete identification with the event, reflected in behaviour such as information searching and planning. In contrast, the less likely it is that the vacation will happen (e.g. browsing flight and Airbnb rental options with no definite holiday plan), the more psychologically distant it feels and the more abstract the event seems. Hence, low hypothetical distance is closely associated with high-level construal and abstract identification such as daydreaming. Hypothetical distance is considered one of the core factors fostering consumer purchase decisions, especially when there is a sudden change in travel plans due to personal reasons or external factors such as natural disaster, global crisis, or recession (Liberman et al., 2007). Such unexpected situations often cause individuals to postpone or cancel their travel (Rittichainuwat et al., 2018).

Meanwhile, firms and marketers need to continue to advertise to keep customers interested in their products to ensure post-crisis business recovery (Kang et al., 2020). Gangadharbatla (2021) and Vafainia (2020) contended that marketing strategies should be changed during global crisis such as COVID-19 pandemic. However, to the best of our knowledge, no attempt has been made to examine how hypothetical distance, which reflects likelihood and tourists’ confidence of traveling, influences the effectiveness of advertising in tourism and hospitality contexts. Furthermore, hospitality businesses may experience difficulty in choosing an advertising approach during the COVID-19 pandemic, because it is unclear which type of advertising will appeal and which message formats will be most effective (Im et al., 2021). Airbnb was placed in an especially challenging situation, as it needed to maintain its consumer base against the hotel industry and to deal with the COVID-19 pandemic despite variations in hypothetical distance. Due to underlying concerns about infection, consumers tend to prefer hotels, which have well-equipped quarantine systems, over Airbnb accommodations (Jiang & Wen, 2020). It became critical for Airbnb to develop effective advertising that appealed to consumers. Thus, it is academically meaningful to investigate the interaction effect of message formats and hypothetical distance on consumer behavioural intention in Airbnb advertising.

Therefore, this study aims to explore effective Airbnb advertising messages during COVID-19 pandemic. The specific objectives are 1) to examine whether abstract (vs. concrete) messages are associated with a higher level of intention to stay at an Airbnb property when hypothetical distance is low (vs. high) and 2) to investigate whether message relevance mediates the impact of message format on intention to stay. This study makes a number of academic contributions and has several practical implications. It broadens the Airbnb literature from a marketing perspective. It also provides an in-depth understanding of how effective message design drives consumer response by applying hypothetical distance, one of the four dimensions of CLT. Thus, this study uncovers a new theoretical approach to consumers’ decision-making process in response to Airbnb advertising during the COVID-19 pandemic. Finally, it has meaningful implications for Airbnb and Airbnb hosts during the COVID-19 pandemic.

Literature review

Airbnb marketing strategies during the COVID-19 pandemic

The unprecedented COVID-19 pandemic has demonstrated the vulnerability of the tourism and hospitality sector, by threatening their operations, management, and revenues (Choi & Choi, 2021; Crick et al., 2021; Siow et al., 2021). Airbnb hosts have been substantially hit by a large drop in the number of bookings, and by the travel restrictions introduced under the government's coronavirus action plan (Chen et al., 2022; Dolnicar & Zare, 2020). Although tourism has gradually revived since then, consumers’ perceptions of the risks associated with travel and Airbnb remain high amidst the outbreak of new COVID-19 variants (Lee & Deale, 2021). Due to underlying concerns about infection, consumers often prefer to stay in hotels, which have well-equipped quarantine systems, rather than Airbnb accommodations, which often involve shared space (e.g. staying with Airbnb hosts) (Jiang & Wen, 2020). Lee and Deale (2021, p. 225) argued that consumers who plan to stay at an Airbnb perceive “higher social, physical, performance and convenience risk” during the COVID-19 pandemic. Indeed, consumers’ Airbnb consumption patterns have changed during the pandemic: they now show a higher willingness to pay for social distancing features, such as renting entire properties and properties with kitchen amenities (Hidalgo et al., 2021).

Thus, Airbnb has strived to develop crisis management strategies in response to the COVID-19 pandemic, to manage consumers’ risk perceptions of its products and services (Chen et al., 2022). The priority is to alleviate concerns about infection via surface contamination. Airbnb has accordingly highlighted its hygiene and sanitation measures in its advertising messages (Farmaki et al., 2020). Another strategy is to keep consumers informed about its new services to retain consumer awareness (Kang et al., 2020; Hidalgo et al., 2021). As work from home increased, Airbnb emphasised long-term stays beyond short-term rentals to target office workers. In addition, Airbnb promoted rentals as quarantine quarters for inbound tourists to attract long-term stay consumers (Gyódi, 2021). Firms and marketers must advertise to keep customers interested in their products and ensure crisis business recovery (Kang et al., 2020; Miguel et al., 2022). Thus, Airbnb hosts developed sophisticated advertising messages based on psychological theory to strategically appeal to consumers’ behavioural intention during the COVID-19 pandemic. Appendix 1 provides a range of studies on the Airbnb business during the COVID-19 pandemic.

Construal level theory, psychological distance, and message format

Psychological distance refers to egocentric distance perception, which is a mental distance concept that is formed and perceived by one's personal and subjective experience with respect to a particular phenomenon, event, or object (Liberman et al., 2007). CLT explains the relationship between psychological distance and the degree to which people's thinking is abstract or concrete (Chen, 2020; Choi et al., 2019). Construal level is classified as high or low (Liberman et al., 2007). High-level construal focuses on the abstract attributes of an object and tends to be primary, core, superordinate, coherent, decontextualized, and structured. In contrast, low-level construal focuses on concrete attributes and tends to be secondary, surface, subordinate, incoherent, contextualized, and unstructured (Trope & Liberman, 2010). By emphasizing different attributes, the effect of high and low construal levels on consumers’ judgment and decision can be influenced by their psychological distance (Chen, 2020; Choi et al., 2019). Researchers have postulated that psychological distance consists of temporal, spatial, social and hypothetical distance as shown in Table 1.

Table 1.

Psychological distances in construal level theory.

Type of distance	Definition	Example: A person who lives in New York is planning a holiday.
Temporal	Distance in time from an event or object in the near or distant future (low vs. high).	Low: A month away
Temporal		High: A year away
Spatial	Whether an event or object is physically near or distant (low vs. high).	Low: Florida, USA
Spatial		High: Auckland, New Zealand
Social	Psychological distance in social relationships; that is, how close or distant individuals feel to others (low vs. high).	Low: Friends, partners, and family
Social		High: Strangers
Hypothetical	Psychological distance created by the likelihood of occurrence (high vs. low).	Low (Uncertain): Flight and accommodation booking are cancelled due to national travel bans and suspension of flights. This trip is unlikely to be realised.
Hypothetical		High (Certain): Flight and accommodation purchased and confirmed. No urgent issues or national travel bans are anticipated. The person is highly likely to go on this trip.

Note: 1) Definitions are based on Trope and Liberman (2010); 2) Examples reflect relative concepts between near and far distances within a given dimension of psychological distance.

Temporal distance refers to the perception of psychological distance from an event or object in the near or distant future (Trope & Liberman, 2010). Spatial distance refers to the perception of whether an object or event is physically near or distant (Trope & Liberman, 2010). Social distance is the psychological distance that individuals perceive in their social relationships; that is, how distant or close they feel to other individuals (Chen, 2020). People tend to interpret this distance as shorter when they feel close to someone with whom they have a lot in common, but interpret it as greater when they feel less close to the person (Choi et al., 2019). Finally, hypothetical distance refers to the psychological distance created by the likelihood of occurrence. High hypothetical distance is associated with concrete attributes, while low hypothetical distance is associated with abstract attributes (Trope & Liberman, 2010).

Individuals’ perception of psychological distance can substantially influence their judgment on brand/product and purchase intentions (Choi et al., 2019; Wang & Lehto, 2020). The interaction effect of psychological distance and message format is evident in both commercial and public advertising. A number of studies have found that advertising that matches near temporal distance with a concrete message effectively appeals to prospective consumers and leads to higher purchase intentions and more positive attitudes towards the product and brand (Kim, Zhang, & Li, 2008; Kim et al., 2016; Trope & Liberman, 2010; Wang & Lehto, 2020). For example, Kim et al. (2008) found that the distant the temporal distance, the more sensitive it is to abstract product evaluations, whereas the near the temporal distance, the less sensitive it is to concrete product evaluations.

CLT has also been applied to advertise intangible products such as hotel services and tourism destinations. Consistent with the findings for tangible products, Kim et al. (2016) found that temporal and spatial distance significantly affected the preferred promotional message in the hotel industry. The participants preferred hotel websites that showed abstract information when the temporal and spatial distances were greater, but preferred concrete information when the distances were smaller. In addition, when the two factors—psychological distance and message format—were well matched, the participants showed favorable attitudes towards the hotel. Similarly, effective matching of temporal and spatial distances to message format has been shown to create more favorable attitudes towards tourism destinations (Wang & Lehto, 2020). These findings confirm that CLT applies not only to tangible products but also to intangible products such as services.

Hypothetical distance refers to the psychological distance created by the likelihood of occurrence (Trope & Liberman, 2010). Consistent with temporal, spatial, and social distances, several empirical studies have confirmed that a high (vs. low) likelihood of occurrence is associated with concrete (vs. abstract) messages (Bates et al., 2021; Duan et al., 2022; Youn & Cho, 2022). For example, Youn and Cho (2022) investigated the interaction effect of hypothetical distance (i.e. high vs. low chance of purchase) and the message format of luxury fashion brand advertising (i.e. concrete vs. abstract) on Gen Z consumers’ behavioural intentions. Concrete (vs. abstract) messages produced a higher level of e-word of mouth (WOM) among consumers through ad-brand congruency and trust in CSR advertising when their hypothetical distances were high (vs. low). Similar findings were obtained by Bates et al. (2021) in a study of charity advertising that aimed to trigger consumers’ intention to donate. Consumers’ donation intentions were high when an advertisement was associated with a concrete (vs. abstract) message and a high (vs. low) hypothetical distance. As a part of CLT, hypothetical distance has been increasingly applied in the marketing literature to explore consumer behaviours, such as social marketing (Duan et al., 2022). Synthesising CLT and previous studies’ empirical findings, we propose the following hypothesis (see, Figure 1).

Figure 1.

Proposed research model.

Hypothesis 1: There is an interaction effect between message format and hypothetical distance.

Hypothesis 1-1: An abstract message produces a higher level of intention to stay when the hypothetical distance is low (vs. high).

Hypothesis 1-2: A concrete message produces a higher level of intention to stay when the hypothetical distance is high (vs. low).

Message in airbnb advertising

Despite the dramatic growth of Airbnb, many potential consumers still feel that using it is risky and distrust Airbnb properties and hosts; thus, they hesitate to stay in Airbnb rentals (Yang et al., 2019). Distrust factors (e.g. perceived information quality, perceived privacy, and security) arouse consumers’ perceived risk, which affects their negative behavioural intention to stay at an Airbnb (Mao et al., 2020; Yang et al., 2019). Thus, effective advertising that portrays trustworthy, safe, and relaxing accommodation options is a critical way for Airbnb hosts to alleviate common concerns and attract consumers. As Airbnb (founded in 2008) has a much shorter business history than conventional hotels (Heo et al., 2019), it requires more effective advertising messages that evoke consumers’ cognition, affection, and awareness in advance of decision making. As such, scholars have shown growing interest in exploring the messages used in Airbnb advertising.

For example, Liu and Mattila (2017, p. 33) examined the impact of “belongingness appeal (i.e. feeling at home)” and “uniqueness appeal (i.e. atypical place to stay)” in Airbnb advertising on consumers’ behavioural intention, as moderated and mediated by a sense of power and self-brand connection. Their findings indicate that the interaction effect of a high sense of power and uniqueness appeal is associated with a high level of consumer behavioural intention, whereas the interaction effect of a low sense of power and belongingness appeal is associated with a high level of consumer behavioural intention. These findings suggest that the type of message appeal (e.g. belongingness vs. uniqueness) is crucial for online targeted advertising.

Wisker et al. (2019) revealed that emotional appeal is one factor of effective Airbnb advertising, resulting in purchase intention and word of mouth. They contended that Airbnb hosts should emphasise emotional appeal and creativity in advertising messages. Similarly, Koh et al. (2021, p. 103) investigated the impact of Airbnb listing titles on financial performance in seven Asian countries. They found that Airbnb listing titles could be categorised as ‘affective’, ‘social’, ‘cognitive’, ‘perceptual’, ‘drives’, ‘relativity’, ‘leisure’, ‘home’, ‘money’, and ‘religion’. Their findings further suggest the ‘dos and don'ts’ for listing titles in specific countries (e.g. “do use drive words’ but ‘don't use affective words” in South Korea).

In a similar vein, CLT in relation to individual psychological distance has been increasingly applied in the marketing and advertising literature (Chen, 2020). Some attempts have been made to examine consumers’ temporal and spatial distances on hotel websites and tourism destinations (Wang & Lehto, 2020); however, scholars have not investigated ‘hypothetical distance’ in the context of Airbnb. Individual hypothetical distance has substantially changed in the tourism and hospitality industry due to the COVID-19 pandemic. As many scholars have pointed out major obstacles to Airbnb use (e.g. distrust, safety, and security), it is theoretically meaningful to identify how the interaction effect of message format (abstract vs. concrete) and individual psychological distance (hypothetical distance: low vs. high), as mediated by message relevance, triggers the intention to stay at an Airbnb during the COVID-19 pandemic.

Meanwhile, message relevance refers to “the relevance of the message content to the target consumers’ current cognitive and/or affective needs’ (Varnali, 2014, p. 341)” This definition implies that relevance is the degree to which an individual feels it is important to pay attention to information about a specific object (O’Reilly et al., 2016; Srivastava, 2013). Zhao and Peterson (2017) extended this definition to the advertising media environment, including the relationship between the advertising message and consumer behaviour. Consumers tend to be interested in messages and information about the target (e.g. product/service) being advertised. Then, consumers form strong purchase intention through the information process when the message is relevant to them (Zhao & Peterson, 2017). This is referred to as a link to the individual consumer, when message format and message relevance form attitude and behavioural intention.

As message relevance is related to cognitive and/or affective needs and to the subjective experience of the relevance of the content, it is an important factor that influences consumer attitudes and behavioural responses to marketing communications such as advertising messages (Varnali, 2014). In other words, message relevance mediates advertising messages and consumer attitudes and behaviour. According to Petty and Cacioppo’s (1986) elaboration likelihood model, message relevance plays an important role in consumers’ information processing. The elaboration likelihood model is a dual-path model of information processing in which an individual takes either a central path or a peripheral path and the message is handled differently on each path. A key factor in the elaboration likelihood model is that customer attitudes and behaviour can vary depending on how the message is processed; that is, how important the consumer perceives it to be determines how much of the information in the message is processed, resulting in different consumer behaviour (Petty & Cacioppo, 1986). When consumers’ level of elaboration is high (i.e. paying more attention to the content of the advertising message), their emotions and the relevance of the message have a greater effect on behaviour (i.e. successful persuasion).

Lee and Rim (2017) argued that when message format is closely associated with message relevance, consumers process the information in messages more thoroughly (i.e. pay more attention). They also asserted that message relevance increases the individual's motivation to search for information related to the issue or product so that they can form attitudes and purchase behaviour towards advertised products. Dessart’s (2018) study of the effectiveness of storytelling advertisements showed that the message format used in advertising and message relevance significantly affect consumer attitudes and behaviour.

Krishnamurthy (2000) argued that message format influences message relevance, resulting in consumer engagement with advertised products/services. Similarly, Ducoffe and Curlo (2000) found that message relevance is a factor affecting consumers’ perceived value of advertising, attitude and purchase intention. Finally, Zhao and Peterson (2017) demonstrated the mediating role of message relevance in the relationship between psychological distance in a message and consumer response to public advertising. The study found that message relevance had a significant mediating effect on the relationship between temporal distance (e.g. near vs. distant) indicated in the message and message processing (e.g. systematic and heuristic processing), resulting in behavioural intentions towards antismoking advertising. In addition, message relevance mediated the relationship between message format (abstract vs. concrete) and behavioural intention in relation to hotel choice (Wan & Rucker, 2013). Synthesising the empirical findings, we propose the following hypothesis.

Hypothesis 2: Message relevance mediates the impact of the message format and hypothetical distance on intention to stay.

Methodology

Pilot study

Methods

Experiment design and procedure

To test the proposed hypotheses, a 2 (message format: abstract vs. concrete) x 2 (hypothetical distance: low vs. high) between-subjects experiment was conducted (Pilot Study). Amazon Mechanical Turk was used to recruit 300 participants during the early phase of COVID-19 pandemic (i.e. mid-January 2020). Although scholars have pointed out that data from online panels can be marred by irresponsible behaviours, such as speeding and cheating (Smith, Roster, Golden, & Albaum, 2016), data obtained from MTurk have shown better quality than data obtained from other professional online panel platforms in terms of completion rate and passing manipulation checks (Zhang & Gearhart, 2020). Due to its reliability and convenience, MTurk has been widely used in academia (Zhang & Gearhart, 2020). The participants were randomly assigned into one of the four conditions. Three selection criteria were applied to participant selection: 1) US residents; 2) hotel stay experience in the past 12 months; and 3) Airbnb usage in the past 12 months. 46 cases were excluded because they provided incorrect answers to two attention check questions: 1) “Please choose ‘strongly disagree’ below”; and 2) “According to the survey scenario, where do you plan to travel?” Thus, the final sample consisted of 254 cases. More than half of the participants were male (n = 168, 66.4%) and married (n = 155, 61.3%). The largest age group was 30–39 (n = 129, 51.0%), followed by 20–29 (n = 63, 24.9%), 40–49 (n = 34, 13.4%), 50–59 (n = 17, 6.7%), and 60 or above (n = 10, 4.0%). In addition, more than half of the participants had a bachelor's degree (n = 149, 58.9%).

Upon their agreement to participate in the study, all of the participants were asked to imagine that they planned to travel to Paris, France. Information about a particular Airbnb property was then given as a search result. Paris was chosen as a study setting because it is one of the most popular Airbnb host destinations, with the largest number of Airbnb property listings (Heo et al., 2019). By manipulating a) the hypothetical distance of the travel scenario and b) the message format of the Airbnb property listing, four stimuli were created (Condition 1 = low hypothetical distance and abstract message, Condition 2 = high hypothetical distance and abstract message, Condition 3 = low hypothetical distance and concrete message, and Condition 4 = high hypothetical distance and concrete message).

Hypothetical distance was manipulated with two versions of a travel scenario (likelihood of occurrence: low vs. high). In the low hypothetical distance condition, the participants were given the following information: “Trip to Paris: flight booking and purchase not completed! Assume that you and your friends are considering spending a summer holiday in Paris, a global centre of art, culture, and gastronomy. However, the flight couldn't be booked and purchased due to personal and external factors. This trip is unlikely to be realised!” The participants in the high hypothetical distance condition were given the following information: “Trip to Paris: flight booking and purchase completed! Assume that you and your friends are planning to spend a summer holiday in Paris, a global centre of art, culture, and gastronomy. The flight is booked and paid for. You are highly likely to go on this trip!” The participants in both conditions were given the same Airbnb information: “In Paris, you will stay with Airbnb, renting an entire apartment for six nights. Your preferred location is the 18th arrondissement of Paris, known as Montmartre. As the average price in this district is USD229 per night, you browse the Airbnb listings between USD200 and USD300.” As the scenarios describe the travel period, ticketing status, and possibility of travel, the respondents would have recognised the likelihood of travelling and staying at an Airbnb during the COVID-19 pandemic.

Two versions of the Airbnb posting (abstract vs. concrete) were created by manipulating the photos and property description (see, Figure 2). The two photos in the concrete condition provided more detailed information about the property space than the two photos in the abstract condition. The textual description in the concrete condition also contained more detailed information about the property size, location, and facilities than the abstract condition. All of the participants were asked to read the Airbnb property information carefully and then fill out a post-experiment questionnaire.

Figure 2.

Experimental stimuli in pilot study

Measures

The post-experiment questionnaire had three sections: 1) two manipulation check questions, 2) measures for message relevance, intention to stay, and two covariates, and 3) socio-demographic information (age, gender, marital status, education, and income). The manipulation of hypothetical distance was checked with one item: “While taking this survey, I believe that my chance to travel to Paris is… (1 = very low, 7 = very high).” One item was adopted from Kim et al. (2016) to check the manipulation of the message format: “The information of this Airbnb property is… (1 = very abstract, 7 = very concrete).” Message relevance was measured with four items (α = .860) adopted and revised from Jensen et al. (2012): “The information about this Airbnb property is meaningful to me.”; “The information about this Airbnb property is appropriate for me.”; “The information about this Airbnb property is useful to me.”; and “The information about this Airbnb property is valuable to me.” Three items (α = .875) adapted and revised from Han and Yoon (2015) were used to measure intention to stay at the Airbnb property: “I am planning to stay at this Airbnb property when traveling.”; “I intend to stay at this Airbnb property when traveling.”; and “I will make an effort to stay at this Airbnb property when traveling.” Message relevance and intention to stay were measured with 7-point Likert scale (1 = strongly disagree, 7 = strongly agree).

In addition, perceived realism and destination familiarity were measured as covariates. Previous studies have found that perceived realism influences message evaluation (Cho et al., 2014) and booking intention (Sparks & Browning, 2011). Three items (α = .804) adopted from Sparks and Browning (2011) were used to measure perceived realism (1 = strongly disagree, 7 = strongly agree): “I think this Airbnb post is realistic.”; “I could imagine seeing this Airbnb post in the real world.”; and “For the purpose of this survey, I was able to imagine using Airbnb to book a room.” Tourism studies have shown that tourists’ level of familiarity with a destination positively influences travel intentions and decision-making in the destination (Horng et al., 2012; Milman & Pizam, 1995). Three items (α = .920) were adopted and refined from Horng et al. (2012) to measure destination familiarity (1 = not at all, 7 = extremely): “How familiar are you with Paris?”; “How experienced are you with Paris?”; and “How knowledgeable are you about Paris?”

Results

Manipulation check

The manipulation check for hypothetical distance (t = −11.70, p <.01) showed that the participants in the high condition perceived their chance of travelling to Paris to be higher (M = 6.25, SD = 1.11) than those in the low condition (M = 3.91, SD = 1.97). For the message format manipulation (t = −3.43, p <.01), the participants in the concrete condition (M = 5.72, SD = 1.19) felt that the information about the Airbnb property was more concrete than those in the abstract condition did (M = 5.12, SD = 1.57). Thus, the manipulations were successful.

Interaction effect of hypothetical distance and message format

A two-way ANCOVA on message relevance was conducted (see Table 2). The main effect of message format was statistically significant at the.05 level. An independent samples t-test (t = −3.82, p < .01) showed that the participants in the concrete condition (M = 5.79, SD = .78) considered the information to be more relevant to them than those in the abstract condition did (M = 5.32, SD = 1.17). However, the main effect of hypothetical distance and the interaction effect of hypothetical distance and message format were not significant. A two-way ANCOVA on intention to stay was also conducted. However, the main effects and interaction effect of hypothetical distance and message format were not significant. Two covariates, perceived realism and destination familiarity, had significant effects on both message relevance and intention to stay.

Table 2.

ANCOVA results for message relevance and intention to stay (pilot study).

Source	Type III Sum of Squares	df	Mean Square	F
Message Relevance (R² = .439)
Intercept	17.555	1	17.555	29.31**
Covariates
Perceived realism	94.139	1	94.139	157.15**
Destination familiarity	3.096	1	3.096	5.17*
Test Effects
Hypothetical distance (HD)	.509	1	.509	.85
Message format (MF)	2.800	1	2.800	4.67*
HD*MF	.348	1	.348	.58
Error	148.560	248	.599
Total	8105.938	254
Intention to Stay (R² = .384)
Intercept	6.115	1	6.115	6.80*
Covariates
Perceived realism	108.966	1	108.966	121.19**
Destination familiarity	13.303	1	13.303	14.80**
Test Effects
Hypothetical distance (HD)	1.146	1	1.146	1.28
Message format (MF)	.541	1	.541	.60
HD*MF	.015	1	.015	.02
Error	222.978	248	.899
Total	7790.778	254

Note. *p <.05; **p <.01.

Implications for a follow-up study

The lack of support for the hypotheses in Pilot Study raised three major issues about the research design and stimuli development. First, the length of description was substantially different in the abstract (40 words) and concrete conditions (132 words). The participants may have been influenced by not only the type of message format but also by the length of the message. Second, the amount of information, particularly in the abstract conditions, might not have been sufficient to make judgments about the message relevance. Third, compounding effects (e.g. attractiveness) associated with the different photos used in abstract and concrete conditions might have influenced the results. The photos in the two conditions showed different aspects and facilities of the property. Previous studies found that participants’ perceptions of the visual appeal of the photos varied when evaluating online information (Harris & Goode, 2010; Mehraliyev et al., 2021). To address these issues, a follow-up study was designed that used property descriptions of similar length and with similar amounts of information in the abstract and concrete conditions. To eliminate the potential effects of the photos, the same photos were used in the abstract and concrete conditions in Study 1.

Study 1

Methods

Experiment design and procedure

To resolve the methodological issues identified in Pilot Study and eliminate potential compounding effects, a follow-up experiment was designed. In Study 1, a 2 (message format: abstract vs. concrete) x 2 (hypothetical distance: low vs. high) between-subjects experiment was conducted. Using the same selection criteria as in Pilot Study, 300 participants who did not participate in Pilot Study were recruited from Amazon Mechanical Turk in lat|e January 2020, and randomly assigned to one of the four conditions. 47 participants who provided incorrect answers to the two attention check questions were excluded. The final sample consisted of 253 cases. There were more male (60.8%) than female (39.2%) participants. About half of the participants were married (51.6%), and most were in the 20–29 (48.8%) age group, followed by 30–39 (36.8%), 40–49 (7.6%), and 50–59 (5.2%). In addition, more than half of the participants had bachelor's degree (56.6%).

Following the same procedure as Pilot Study, the participants were asked to imagine that they were planning to travel to Paris, France and a particular Airbnb property posting was given as a search result. By manipulating hypothetical distance and message format, four stimuli were created. The same manipulation for travel scenarios (low vs. high) was used. However, the manipulation of the message format was substantially changed (see Figure 3). First, the same photos were displayed in the abstract and concrete conditions. Compared to Pilot Study, more information about the property was provided and the textual descriptions were of similar length: 317 words in the abstract condition and 315 words in the concrete condition. All of the participants were asked to read the given Airbnb property information carefully and to fill out a post-experiment questionnaire.

Figure 3.

Experimental stimuli in study 1

Measures

The manipulation check questions and measures used in Study 1 were the same as those used in Pilot Study. The reliability of message relevance, intention to stay, perceived realism, and destination familiarity was acceptable (α = .726 -.898).

Results

Manipulation check

The manipulation check question for hypothetical distance (t = −8.56, p <.01) showed that the participants in the high condition thought that their chance of travelling to Paris was higher (M = 6.27, SD = .94) than those in the low condition (M = 4.62, SD = 1.95). The manipulation check of message format (t = −2.05, p <.05) found that the participants in the concrete condition (M = 5.72, SD = 1.18) felt that the information about the focal Airbnb property was more concrete than those in the abstract condition did (M = 5.43, SD = 1.08).

Interaction effect on message relevance and intention to stay

A two-way ANCOVA on message relevance was conducted (see Table 3). Two covariates, perceived realism and destination familiarity, were included. The results revealed that the main effect of hypothetical distance was significant (F(1, 247) = 4.72, p <.05). More importantly, the interaction between hypothetical distance and message format was significant (F(1, 247) = 10.89, p <.01). These results supported H1. Figure 4 illustrates the interaction. In the low condition, the message was perceived as less relevant when the property information was presented in a concrete format (M = 5.36, SD = 1.03) than when it was presented in an abstract format (M = 5.70, SD = .80; t = 2.07, p <.05). In the high condition, the focal message was perceived as more relevant when the property information was presented in a concrete format (M = 5.99, SD = .70) than when it was presented in an abstract format (M = 5.64, SD = .83; t = −2.60, p <.01). These results supported H1-1 and H1-2. The effects of both covariates, perceived realism (F(1, 247) = 151.56, p <.01) and perceived attractiveness (F(1, 246) = 19.55, p < 01), were all significant.

Figure 4.

Interaction effect of hypothetical distance and message format on message relevance.

Table 3.

ANCOVA results for message relevance and intention to stay (study 1).

Source	Type III Sum of Squares	df	Mean Square	F
Message Relevance (R² = .465)
Intercept	8.598	1	8.598	20.68**
Covariates
Perceived realism	63.002	1	63.002	151.558**
Destination familiarity	8.126	1	8.126	19.55*
Test Effects
Hypothetical distance (HD)	1.964	1	1.964	4.72*
Message format (MF)	.113	1	.113	.27
HD*MF	4.525	1	4.525	10.89**
Error	102.677	247	.416
Total	8322.563	253
Intention to Stay (R² = .436)
Intercept	7.228	1	7.228	15.61**
Covariates
Perceived realism	55.883	1	55.883	33.43**
Destination familiarity	15.482	1	15.482	33.43**
Test Effects
Hypothetical distance (HD)	4.041	1	4.041	8.73**
Message format (MF)	.607	1	.607	1.31
HD*MF	.348	1	.348	.75
Error	114.396	247	.446
Total	7953.667	253

Note. *p <.05; **p <.01.

The results of a two-way ANCOVA on intention to stay also found a significant main effect of hypothetical distance (F(1, 247) = 8.73, p <.01). The participants in the high conditions (M = 5.72, SD = .83) were more willing to stay in the given Airbnb accommodation than those in the low condition (M = 5.35, SD = .93). The main effect of message format and the interaction effect were not statistically significant. The effects of the two covariates, perceived realism (F(1, 247) = 33.43, p <.01) and destination familiarity (F(1, 247) = 33.43, p < 01), were significant.

Moderated mediation model

The bootstrapping approach of Hayes (2018, Model 7, bias-corrected bootstrap = 5000) was used to analyze the moderated mediation model. The model specified the message format as the independent variable (X), hypothetical distance as the moderator (W), message relevance as the mediator (M), and intention to stay as the dependent variable (Y). Two covariates (perceived realism and destination familiarity) were included in the model. Consistent with the results of the ANCOVA, the interaction effect of hypothetical distance and message format was significant. As shown in Table 4, the bootstrapping results indicated that message relevance mediated the effect of message format on intention to stay both in low (indirect effect = -.12; 95% CI = -.2399 to -.0244) and high conditions (indirect effect = .08; 95% CI = .0095 to.2154). The concrete message had a negative indirect effect on intention to stay through message relevance when the hypothetical distance was low, whereas the concrete message had a positive indirect effect when the hypothetical distance was high. Thus, the results of Study 1 supported H2.

Table 4.

Conditional indirect effect of message format on intention to stay through message relevance.

Hypothetical distance	Effect	95% CI	Index	95% CI
Low (i.e. Uncertain)	−.1150*	−.2399 to −.0244	.1987	.0640 to.4036
High (i.e. Certain)	.0837*	.0095 to.2154	.1987	.0640 to.4036

* Significant conditional indirect effect, p <.05.

Discussion

This study explored effective Airbnb advertising messages from the perspective of psychological distance, particularly focusing on hypothetical distance. Specifically, the study examined the interaction effect of message format (abstract vs. concrete) and hypothetical distance (low vs. high) on travelers’ intention to stay with Airbnb. The findings suggest that a concrete message results in a higher level of intention to stay when high hypothetical distance is displayed, while an abstract message results in a higher level of intention to stay when low hypothetical distance is displayed. In addition, the mediating role of message relevance in the relationship between message format and intention to stay was investigated.

Theoretical contributions

This study makes several theoretical contributions. First, it broadens the Airbnb literature from a marketing perspective. The Airbnb literature has overlooked the importance of online marketing and advertising, although topics such as laws and regulations, the economic impact of Airbnb on hotel performance, and consumer motivation have been intensively investigated (Nieuwland & van Melik, 2020; So et al., 2018). This study aligns with that of Liu and Mattila (2017), who examined the interaction effect of advertising appeal (belongingness vs. uniqueness) and power (high vs. low) on consumer responses, such as purchase intention and click-through intention. However, this study makes an additional contribution to the Airbnb literature by exploring advertising message format (e.g. abstract vs. concrete) and individuals’ psychological distance, within the CLT framework from a marketing perspective.

Second, this study provides an in-depth understanding of how effective message design drives consumer response by applying hypothetical distance, one of the four dimensions of CLT. Along with message framing theory, CLT has often been used in targeted online advertising research (Kim et al., 2018; Park & Morton, 2015). However, the topics and methodological approaches have been limited. For example, most previous studies drawing on CLT have explored the role of temporal, spatial, and social distance in consumer behavioural responses, such as attitudes and purchase intentions towards products or brands (Kim et al., 2016; Kim et al., 2018; Teng & Chang, 2014). However, few empirical studies have considered the hypothetical distance associated with online advertising in the field of hospitality and tourism. This study's findings provide empirical evidence that hypothetical distance significantly influences consumer behavioural intention.

Third, this study provides a new theoretical approach for understanding consumers’ decision-making process in response to Airbnb advertising during the COVID-19 pandemic. To the best of our knowledge, it is the first attempt to empirically examine the roles of hypothetical distance (high vs. low) and message relevance in relation to message format (abstract vs. concrete) and intention to stay at an Airbnb. As hospitality products are different from tangible products, due to their intangibility, perishability, inseparability, and heterogeneity (Melissen et al., 2019), they require a different approach to marketing and promotion. Furthermore, the COVID-19 pandemic has transformed the way service enterprises operate and increased consumers’ risk perceptions, which directly affects purchasing decisions (Lee & Deale, 2021).

Overall, consumers perceive a higher risk of staying at an Airbnb than at a hotel, due to inconsistent hygiene standards and safety measures among Airbnb hosts (Farmaki et al., 2020; Lee & Deale, 2021). Our study explores the underlying consumer decision-making process of Airbnb advertising, based on hypothetical distance and message relevance. The findings indicate that the interaction effect of message format (abstract vs. concrete) and hypothetical distance (low vs. high) significantly affects intention to stay at an Airbnb, as mediated by message relevance. Petty and Cacioppo (1986) elaboration likelihood model also suggests that message relevance is important for consumers’ information processing.

Although Kim et al. (2016) and Wang and Lethto (2020) confirmed the interaction effect of temporal and spatial distances and message format on consumer attitudes towards a brand and destination, this study further examines the role of hypothetical distance, as reflected by CLT, and consumers’ underlying persuasion process (e.g. message relevance), as reflected by the elaboration likelihood model. That is, this research model combines CLT and the elaboration likelihood model to explain the consumer information process of Airbnb advertising and identifies consumer behavioural intention during the COVID-19 pandemic. Given the scarcity of empirical studies on hypothetical distance in Airbnb marketing, this study makes a strong theoretical contribution to the marketing and advertising literature.

Finally, this study demonstrates the underlying mechanism that links message format, psychological distance, and intention to stay with Airbnb by examining the mediating role of message relevance. The findings suggest that message format, acting through message relevance, stimulates consumers’ intention to stay at Airbnb accommodation. Consistent with the advertising literature (Varnali, 2014; Zhao & Peterson, 2017), the role of message relevance was confirmed in this study.

Practical implications

First, this study provides meaningful implications for Airbnb and its hosts during the COVID-19 pandemic. The COVID-19 pandemic has drastically reduced tourism demand and individual hypothetical distance due to travel restrictions. However, the rollout of vaccinations and ‘travel bubble’ arrangements have contributed to renewing tourism demand (Fusté-Forné & Michael, 2021). That is, the hypothetical distance (e.g. likelihood of travel and staying at an Airbnb) substantially varies across destinations worldwide. This study shows how effective Airbnb advertising can be developed based on CLT during the COVID-19 pandemic. In response to vaccination rates and travel guidelines, the Airbnb platform's marketing team can launch central marketing initiatives applicable to each region and destination.

For example, the full vaccination rate in European countries was 68.3% as of 4 January 2022 (European Centre for Disease Prevention and Control, n.d.), and no travel ban has been imposed in Spain, implying the high hypothetical distance of dominant inbound markets in other European countries. Thus, it will be effective for the Airbnb platform in Spain to promote its attractiveness and safety as a destination via a concrete message format. Similarly, individual Airbnb hosts should also highlight their unique selling point using a concrete message format. In contrast, France has tightened its travel restrictions for visitors from neighbouring countries. To maintain prospective consumers and keep them interested, Airbnb hosts in France should use an abstract message format. This study's findings will help Airbnb hosts establish effective short-term and long-term advertising strategies based on the likelihood of international and domestic travel resuming during the COVID-19 pandemic.

Second, personalised online marketing and advertising are applicable to other hospitality and tourism businesses. Consistent with the advertising literature (Kim et al., 2016; Wang & Lehto, 2020), this study's findings confirm the applicability of CLT to the service sector. Hotels, travel companies, and destination marketing organisations can provide prospective consumers with personalised information through face-to-face chats, virtual chats, social media, and official websites. Furthermore, when employees deal with visitor inquiries, applying this study's findings on the role of hypothetical distance will lead to more positive consumer behavioural responses.

Limitations and future research

Despite its academic contributions and practical implications, this study has several limitations. First, caution is required when interpreting the experimental data and study findings due to the limited sample size and data collection site. All of the participants were US residents and the online stimuli were limited to Paris, France. Like other empirical studies, generalization remains a limitation. Second, although the findings have implications for the tourism and hospitality industry during and after the COVID-19 pandemic, more sophisticated and diverse scenarios that consider tourist mobility and restrictions are required to identify tourists’ attitudes and purchase intentions in the post-COVID-19 era.

Footnotes

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Miju Choi

Youngjoon Choi

Appendix.

Airbnb business during the COVID-19 pandemic

References

Alper

(2020) Explaining the complex effect of construal level on moral and political attitudes. Current Directions in Psychological Science 29(2): 115–120.

Bates

Sherwani

Grijalva

(2021) Charitable giving in the context of unfamiliar organizations: the effectiveness of construal level theory in predicting donating intentions and antecedents. Southern Communication Journal 86(5): 472–486.

Benítez-Aurioles

(2021) How the peer-to-peer market for tourist accommodation has responded to COVID-19. International Journal of Tourism Cities 8(2): 379–392.

Boto-García

(2022) Heterogeneous price adjustments among airbnb hosts amid COVID-19: evidence from Barcelona. International Journal of Hospitality Management 102: 103169.

Braje

Pechurina

Bıçakcıoğlu-Peynirci

, et al. (2021). The changing determinants of tourists’ repurchase intention: The case of short-term rentals during the COVID-19 pandemic. International Journal of Contemporary Hospitality Management 34(1): 159–183.

Bresciani

Ferraris

Santoro

, et al. (2021) The seven lives of airbnb. The Role of Accommodation Types. Annals of Tourism Research 88: 103170.

Chen

Cheng

Edwards

, et al. (2022) COVID-19 pandemic exposes the vulnerability of the sharing economy: A novel accounting framework. Journal of Sustainable Tourism 30(5): 1141–1158.

Chen

(2020) Effects of psychological distance perception and psychological factors on pro-environmental behaviors in Taiwan: application of construal level theory. International Sociology 35(1): 70–89.

Cheng

Jin

(2019) What do airbnb users care about? An analysis of online review comments. International Journal of Hospitality Management 76: 58–70.

10.

Cho

Shen

Wilson

(2014) Perceived realism: dimensions and roles in narrative persuasion. Communication Research 41(6): 828–851.

11.

Choi

(2021) Employee perceptions of hotel CSR activities during the COVID-19 pandemic. International Journal of Contemporary Hospitality Management 33(10): 3355–3378.

12.

Choi

Yoon

Kim

, et al. (2019) Text versus pictures in advertising: Effects of psychological distance and product type. International Journal of Advertising 38(4): 528–543.

13.

Chuah

SHW

Sujanto

Sulistiawan

, et al. (2022) What is holding customers back? Assessing the moderating roles of personal and social norms on CSR’S routes to airbnb repurchase intention in the COVID 19, era. Journal of Hospitality and Tourism Management 50: 67–82.

14.

Crick

Chaudhry

(2021) Interfirm collaboration as a performance-enhancing survival strategy within the business models of ethnic minority-owned urban restaurants affected by COVID-19. International Journal of Entrepreneurial Behavior & Research. Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJEBR-04–2021–0279

15.

Dessart

(2018) Do ads that tell a story always perform better? The role of character identification and character type in storytelling ads. International Journal of Research in Marketing 35(2): 289–304.

16.

Dolnicar

Zare

(2020) COVID19 And airbnb–disrupting the disruptor. Annals of Tourism Research 83: 102961.

17.

Duan

Zwickle

Takahashi

(2022) Refining the application of construal level theory: egocentric and nonegocentric psychological distances in climate change visual communication. Environmental Communication 16(1): 92–107.

18.

Ducoffe

Curlo

(2000) Advertising value and advertising processing. Journal of Marketing Communications 6(4): 247–262.

19.

European Centre for Disease Prevention and Control. (n.d.). COVID-19 vaccine tracker. Retrieved April 2, 2022, from https://vaccinetracker.ecdc.europa.eu/public/extensions/COVID-19/vaccine-tracker.html#uptake-tab

20.

Farmaki

Miguel

Drotarova

, et al. (2020). Impacts of COVID-19 on peer-to-peer accommodation platforms: host perceptions and responses. International Journal of Hospitality Management, 91: 102663.

21.

Fusté-Forné

Michael

(2021). Limited tourism: Travel bubbles for a sustainable future. Journal of Sustainable Tourism, Ahead-of-print, https://doi.org/10.1080/09669582.2021.1954654

22.

Gangadharbatla

(2021) COVID-19 and advertising: the case for a paradigm shift. Journal of Current Issues & Research in Advertising 42(1): 1–18.

23.

Gyódi

(2021) Airbnb and hotels during COVID-19: Different strategies to survive. International Journal of Culture, Tourism and Hospitality Research 16(1): 168–192. https://doi.org/10.1108/IJCTHR-09-2020-0221

24.

Han

Yoon

(2015) Hotel customers’ environmentally responsible behavioral intention: impact of key constructs on decision in green consumerism. International Journal of Hospitality Management 45: 22–33.

25.

Harris

Goode

(2010) Online servicescapes, trust, and purchase intentions. Journal of Services Marketing 24(3): 230–243.

26.

Hayes

(2018) Partial, conditional, and moderated moderated mediation: quantification, inference, and interpretation. Communication Monographs 85(1): 4–40.

27.

Heo

Blal

Choi

(2019) What is happening in Paris? Airbnb, hotels, and the parisian market: A case study. Tourism Management 70: 78–88.

28.

Hidalgo

Riccaboni

Rungi

, et al. (2021) COVID-19, social distancing and guests’ preferences: impact on peer-to-peer accommodation pricing. Current Issues in Tourism 1–7. https://doi.org/10.1080/13683500.2021.1963215

29.

Horng

J-S

Liu

C-H

Chou

H-Y

, et al. (2012) Understanding the impact of culinary brand equity and destination familiarity on travel intentions. Tourism Management 33: 815–824.

30.

Kim

Miao

(2021) CEO Letters: hospitality corporate narratives during the COVID-19 pandemic. International Journal of Hospitality Management 92: 102701.

31.

Jang

Kim

(2022) Remedying airbnb COVID-19 disruption through tourism clusters and community resilience. Journal of Business Research 139: 529–542.

32.

Jang

Kim

, et al. (2021) Spatial and experimental analysis of peer-to-peer accommodation consumption during COVID-19. Journal of Destination Marketing & Management 20: 100563.

33.

Jensen

King

Carcioppolo

, et al. (2012) Why are tailored messages more effective? A multiple mediation analysis of a breast cancer screening intervention. Journal of Communication 62(5): 851–868.

34.

Jiang

Wen

(2020) Effects of COVID-19 on hotel marketing and management: A perspective article. International Journal of Contemporary Hospitality Management 32(8): 2563–2573.

35.

Kang

Diao

Zanini

(2020) Business-to-business marketing responses to COVID-19 crisis: A business process perspective. Marketing Intelligence & Planning 39(3): 454–468.

36.

Kim

Sung

Lee

, et al. (2016) Are you on timeline or news feed? The roles of Facebook pages and construal level in increasing ad effectiveness. Computers in Human Behavior 57: 312–320.

37.

Kim

Yoo

Lee

(2018) The influence of self-concept on ad effectiveness: interaction between self-concept and construal levels on effectiveness of advertising. Journal of Marketing Communications 24(7): 734–745.

38.

Kim

Zhang

(2008) Effects of temporal and social distance on consumer evaluations. Journal of Consumer Research 35(4): 706–713.

39.

Kim

Sim

Chung

(2021) The effect of changes in airbnb host’s marketing strategy on listing performance in the COVID-19 pandemic. Journal of Intelligence and Information Systems 27(3): 1–27.

40.

Koh

Kim

Vaughan

(2021) How you name your airbnb’s title matters: Comparison of seven countries. Journal of Travel & Tourism Marketing 38(1): 93–106.

41.

Krishnamurthy

(2000) Deciphering the internet advertising puzzle. Marketing Management 9(3): 34–39.

42.

Lee

Rim

(2017) Consumer evaluation of cause-brand alliance in cause-related advertising: the role of brand familiarity and personal relevance. Business Management and Strategy 8(1): 103–122.

43.

Lee

Deale

(2021) Consumers’ perceptions of risks associated with the use of airbnb before and during the COVID-19 pandemic. International Hospitality Review 35(2): 225–239.

44.

Liberman

Trope

Wakslak

(2007) Construal level theory and consumer behavior. Journal of Consumer Psychology 17(2): 113–117.

45.

Liu

Mattila

(2017) Airbnb: online targeted advertising, sense of power, and consumer decisions. International Journal of Hospitality Management 60: 33–41.

46.

Mao

Jones

, et al. (2020) Sleeping in a stranger’s home: A trust formation model for airbnb. Journal of Hospitality and Tourism Management 42: 67–76.

47.

Martins

Costa

Oliveira

, et al. (2019) How smartphone advertising influences consumers’ purchase intention. Journal of Business Research 94: 378–387.

48.

Mehraliyev

Choi

King

(2021) Expert online review platforms: interactions between specialization, experience, and user power. Journal of Travel Research 60(2): 384–400.

49.

Melissen

Van der Rest

Josephi

, et al. (2019) Hospitality Experience. Noordhoff Uitgevers, The Netherlands: Routledge.

50.

Miguel

Pechurina

Kirkulak-Uludag

, et al. (2022) Short-term rental market crisis management during the COVID-19 pandemic: Stakeholders’ perspectives. International Journal of Hospitality Management 102: 103147.

51.

Milman

Pizam

(1995) The role of awareness and familiarity with a destination: the central Florida case. Journal of Travel Research 33(3): 21–27.

52.

Nieuwland

Van Melik

(2020) Regulating airbnb: How cities deal with perceived negative externalities of short-term rentals. Current Issues in Tourism 23(7): 811–825.

53.

O’Reilly

MacMillan

Mumuni

, et al. (2016) Extending our understanding of eWOM impact: the role of source credibility and message relevance. Journal of Internet Commerce 15(2): 77–96.

54.

Park

Morton

(2015) The role of regulatory focus, social distance, and involvement in anti-high-risk drinking advertising: A construal-level theory perspective. Journal of Advertising 44(4): 338–348.

55.

Petty

Cacioppo

(1986) The elaboration likelihood model of persuasion. In Communication and Persuasion. New York, NY: Springer, 1–24.

56.

Rittichainuwat

Nelson

Rahmafitria

(2018) Applying the perceived probability of risk and bias toward optimism: implications for travel decisions in the face of natural disasters. Tourism Management 66: 221–232.

57.

Siow

Lockstone-Binney

Fraser

, et al. (2021) Re-building students’ post-COVID-19 confidence in courses, curriculum and careers for tourism, hospitality, and events. Journal of Hospitality & Tourism Education 33(4): 270–287.

58.

Smith

Roster

Golden

, et al. (2016) A multi-group analysis of online survey respondent data quality: comparing a regular USA consumer panel to MTurk samples. Journal of Business Research 69(8): 3139–3148.

59.

KKF

Min

(2018) Motivations and constraints of airbnb consumers: findings from a mixed-methods approach. Tourism Management 67: 224–236.

60.

Sparks

Browning

(2011) The impact of online reviews on hotel booking intentions and perception of trust Tourism Management 32: 1310–1323.

61.

Srivastava

(2013) Media multitasking performance: role of message relevance and formatting cues in online environments. Computers in Human Behavior 29(3): 888–895.

62.

Sung

Tao

CWW

Slevitch

(2020) Restaurant chain’s corporate social responsibility messages on social networking sites: the role of social distance. International Journal of Hospitality Management 85: 102429.

63.

Teng

Chang

(2014) Effects of temporal distance and related strategies on enhancing customer participation intention for hotel eco-friendly programs. International Journal of Hospitality Management 40: 92–99.

64.

Trope

Liberman

(2010) Construal-level theory of psychological distance. Psychological Review 117(2): 440.

65.

Vafainia

(2020) Marketing in post COVID-19 era: A guide for marketing managers. Managing a Post-Covid19 Era 31: 31–35.

66.

Varnali

(2014) SMS Advertising: how message relevance is linked to the attitude toward the brand? Journal of Marketing Communications 20(5): 339–351.

67.

Wan

Rucker

(2013) Confidence and construal framing: when confidence increases versus decreases information processing. Journal of Consumer Research 39(5): 977–992.

68.

Wang

Lehto

(2020) The interplay of travelers’ psychological distance, language abstraction, and message appeal type in social media advertising. Journal of Travel Research 59(8): 1430–1446.

69.

Wisker

Kadirov

Bone

(2019) Modelling P2P airbnb online host advertising effectiveness: The role of emotional appeal information completeness creativity and social responsibility. International Journal of Culture. Tourism and Hospitality Research 13(4): 505–523.

70.

Yang

Lee

, et al. (2019) In airbnb we trust: understanding consumers’ trust-attachment building mechanisms in the sharing economy. International Journal of Hospitality Management 83: 198–209.

71.

Youn

Cho

(2022) CSR Ads matter to luxury fashion brands: A construal level approach to understand gen Z consumers’ eWOM on social media. Journal of Fashion Marketing and Management 26(3): 516–533.

72.

Zhang

Gearhart

(2020) Collecting online survey data: A comparison of data quality among a commercial panel & MTurk. Survey Practice 13(1): 1–10.

73.

Zhao

Peterson

(2017) Effects of temporal framing on response to antismoking messages: the mediating role of perceived relevance. Journal of Health Communication 22(1): 37–44.