Exploring the Relationship between Host Self-Description and Consumer Purchase Behavior Using a Self-Presentation Strategy

Abstract

Information on short-term rental platforms plays an important role in consumer purchase behavior. However, information asymmetry between host and guest has been identified as a problem in sharing economy contexts. In this paper, to fill this gap, the authors develop six hypotheses about the focal impacts of self-presentation strategy and the moderating effects of third-party certification. Based on data from Airbnb, the authors first examine how the tactics of self-presentation strategy influence consumer purchase behavior. The results show that different self-presentation tactics affect consumer purchase behavior differently. The authors also found that the third-party certification level weakens the influence of self-presentation strategy interactions on consumer purchase behavior.

1. Introduction

In recent decades, there has been a dramatic increase in the number of enterprises in the sharing economy. As a main form of the sharing economy, shared accommodation, which refers to the sharing of redundant accommodation [1,2] assets with others as a form of short-term rental use, plays a pivotal role. Similar to the traditional sharing economy, shared accommodation emphasizes reciprocity [3,4]: hosts can make a profit by renting out vacant properties while at the same time providing more accommodation options for tourists. Simultaneously, online peer-to-peer(P2P) platforms such as Airbnb, Xiaozhu, Tujia, and others have brought about unprecedented opportunities for shared accommodation, allowing hosts to conveniently and quickly list a property (e.g., a house or a room) for short-term rentals and enabling potential guests to search for accommodation information, which is in line with the reciprocal mechanism of the sharing economy.

Indeed, research in the field of shared accommodation platforms has been conducted on a variety of topics, including trust and reputation [5,6], user behavior and preferences [7,8,9], economic impacts, regulatory and legal issues [10], and social and cultural impacts [11,12]. These areas of research provide valuable insights into the functioning, dynamics, and consequences of shared accommodation platforms. They help us better understand how these platforms affect users, hosts, communities, and the broader economy. In this paper, we also focus on user behavior and preferences.

In contrast to hotels which provide professional, conventional, and efficient services, sharing accommodation emphasizes more personalization [13,14] and unique accommodation interiors and atmospheres [15] and involves interaction between the host and guests [16,17,18]. Guests browse the sharing accommodation’s information [19] mainly through the online accommodation platform and then make decisions according to their preferences. However, due to online shopping’s lack of tactile, olfactory, and taste sensations, serious information asymmetry [20] between hosts and guests can arise, which can significantly hinder hosts’ sense of control. Social information processing theory [21] further points out that due to the lack of nonverbal cues (such as facial expressions, body language, and the social environment) in computer-mediated communication, communication and presentation in electronic media requires a greater level of disclosure of self-information. Therefore, the effective disclosure of information compensates for the shortcomings of online P2P platform information asymmetry. Self-descriptions on online shared accommodation platforms can reveal more details about a host’s personal characteristics, such as detailed information on their personality and hobbies [7,22,23] (not just information on the number of listings) [6]. Therefore, host self-presentation and providing effective host information can affect consumer purchase behavior.

Therefore, it would be valuable to use a more effective strategy that mixes host self-information to enhance consumer participation. Our study aims to solve two problems. The first problem is how to analyze the information presentation strategy on P2P platforms that influence existing consumer purchase behavior. Second, the paper analyzes how the third-party certification of the superhost moderates the influence of the information presentation strategy on consumer purchase behavior. For this paper, we applied a self-presentation strategy [24] that includes five techiques to extract information from host self-descriptions and determine how each strategy is effective in enhancing consumer behavior. Regression analysis on datasets with explanatory variables proved the validity of the dependent variables. Furthermore, the paper hypothesizes that superhosts, as the third-party certification party, weaken the influence of self-presentation strategies on consumer purchase behavior.

This paper makes several contributions to the literature. Firstly, we propose a novel approach that combines information from the host’s self-descriptions to enhance consumer participation, offering a fresh perspective on improving consumer behavior in P2P platforms. Secondly, this study addresses two important research problems: analyzing the influence of information presentation strategies on consumer purchase behavior and investigating the moderating effect of third-party certification by superhosts. By exploring these factors, this study contributes to a deeper understanding of the dynamics between information presentation, consumer behavior, and third-party endorsements in the context of P2P platforms. Thirdly, this study introduces a self-presentation strategy consisting of five distinct techniques to extract information from host self-descriptions. These strategies provide a comprehensive framework for understanding how each tactic effectively influences consumer behavior. This contribution adds value to the existing literature on self-presentation and consumer decision-making in online platforms. Lastly, this study validates hypotheses through regression analysis using datasets that include relevant explanatory variables. This empirical evidence strengthens the credibility of findings and enhances the practical implications of this research. Overall, the novelty of this study lies in its unique approach, addressing important research problems, introducing a comprehensive self-presentation strategy, and providing empirical validation. These contributions will help to advance knowledge in the field and offer valuable insights for both academia and industry.

The rest of the paper is organized as follows: Section 2 discusses consumer purchase behavior on P2P platforms, self-presentation strategies, and host self-description and develops hypotheses. Section 3 describes the data collection, variable measurements, and variable analysis. Section 4 describes and discusses the results derived from the regression models. Section 5 discusses theoretical and managerial implications. Section 6 discusses the study’s limitations and directions for future research.

2. Theoretical Background and Conceptual Framework

2.1. Consumer Purchase Behavior in Sharing Accommodation Platforms

The sharing economy, also known as collaborative consumption, places more emphasis on use than on possession. The internet, especially Web 2.0, has brought about many new ways of sharing and has facilitated large-scale forms of sharing. A sharing economy platform is an information–technology-based platform created by a third party that allows individuals to share products, services, and even knowledge and experience. The development of a sharing economy platform that promotes reciprocity promotes collaborative consumption as a result. Airbnb, as an important sharing accommodation platform, has become a hot issue in current research from the perspectives of, for example, guests, hosts, and companies.

Our study also focuses on the purchase behavior of consumers in the sharing economy. Although previous studies [25,26] have discussed these factors and their intended effect on enhancing consumers’ purchase behavior, very few studies have applied such strategies to information presentation on the platform and considered how it affects consumers’ purchase behavior. This study fills this gap in the literature by proposing a comprehensive framework of information that consists of five distinct strategies and discussing their impact on consumers’ purchase behavior.

Consumer purchase behavior is composed of a series of related activities which begins with requirements and ends with post-purchase behavior. To deeply examine the factors influencing consumer decision-making, it is necessary to familiarize ourselves with the decision-making process of consumer purchases and adopt the corresponding promotional means and strategies. The consumer purchase decision-making process includes five basic steps. The first step is to confirm demand. In the sharing economy, because of its own characteristics, consumers collect information when they decide to participate in the sharing model, the second step in the consumer’s purchasing decision-making process. Information is the basis of decision-making; before making a purchase decision, consumers collect relevant information, including housing and host information, through reviews, ratings, sales, and other information. Therefore, for the host, the provision of effective information for consumer decision-making has an important impact. The third step is to evaluate the product. The fourth and final steps are the decision to buy and post-purchase behavior. In the process of the sharing economy, when consumers choose a listing, they are influenced by various factors such as host attributes, product attributes, reputation, or guarantees [27,28]. In this study, more attention is paid to users’ information collection, that is, how to display self-information strategically from the perspective of the host to promote consumer buying behavior.

2.2. Host Self-Description

In the process of consumer purchase decisions, customers can collect information pertaining to four categories: business, personal, experience, and public information. Personal information is the most important type of information. While it is important for the host to emphasize the characteristics and uniqueness of the listing, it is also important for them to build a good personal impression to attract potential guests. Social networking sites (or sharing sites) such as online dating sites offer a variety of features that allow people to share their profiles (for example, online profiles) [29], emphasizing self-disclosure through social satisfaction [30]. On social networking sites, self-presentation and self-disclosure often provide an opportunity for users to present themselves as they truly are. For example, in the context of online dating, the pressure placed on an individual to emphasize their positive attributes may arise as a result of revealing their real personality to others in an intimate relationship [31].

Since hosts are targeted objects in the delivery of online transactions and offline services, they have a responsibility to build a good image. Longer self-descriptions can reduce information asymmetry and tend to be perceived as more trustworthy [5]. Furthermore, emotional and semantic topics in self-descriptions can provide more detailed information about the host, such as their occupation, personality, and values, which can also affect perceived trust. The number of words and topics included in the self-description has a positive effect on the perceived trust of guests. Similarly, the positive emotions expressed in the host’s self-description also helps to build up guests’ perceived trust. Therefore, it can be suggested that hosts adopting various strategies to display themselves on the platform through their personal profiles can attract more guests to participate in the sharing of economic consumption behavior. Hosts can introduce themselves on their profiles, apply effective self-presentation strategies in self-descriptions, and design a better self-description to reduce the cost of trust, thus obtaining more guests. The linguistic styles and types of semantic content [32,33,34] through which hosts describe themselves to help build guests’ perceived trust on Airbnb remain understudied.

2.3. Self-Presentation Strategy

To achieve one target, people always try to establish a favorable impression to influence the surrounding environment. To achieve this goal, people always start from their own impression, constantly adjusting and controlling the information presented to others, especially that about themselves. Goffman [35], in impression management (or self-expression) theory, saw people as actors on the stage of life and social behavior as participants’ self-expression, paving the way for a series of studies on self and self-expression in social psychology. Furthermore, Jones and Nisbett [36] introduced the concept of self-presentation into psychology as a basis for interpersonal processes.

Jones and Pittman [24] first proposed the concept in the 1980s and further conceptualized self-presentation strategies through induction and identification, finding five common self-presentation strategies in interpersonal interactions: ingratiation, self-promotion, intimidation, supplication, and exemplification. Dominick [37] further generalized and defined Jones’ and Pittman’s self-presentation strategies, applying them to the study of personal homepages in the early days of the internet. Dominick used five self-presentation strategies developed by Jones and Pittman [24] to categorize individual profiles and found that the most commonly used self-presentation strategies were “fawning”, followed by “competence”. This result is in line with the findings of the self-presentation strategy in face-to-face interaction. Subsequent computer media communication (CMC) studies similarly found that “ingratiation” and “self-promotion” are the main strategies for individual self-presentation [38,39]. Individuals present themselves through strategies regarding their online personal webpages, a situation that has been explored in the literature as a form of self-marketing [40,41].

Two strategies were identified from social media self-representation behaviors: honest self-representation and positive self-representation. On the one hand, the honest self-expression strategy emphasizes accuracy or authenticity, and on the other hand, positive self-expression strategies emphasize expectations. Jung [42] conducted an initial exploration of self-presentation strategies in social network services (SNSs) and discovered that the most commonly used self-presentation strategies in SNSs were “self-promotion”, followed by “supplication”, “exemplification”, and “ingratiation”. Although “intimidation” was shown to be less of a self-presentation tactic, it was more frequent in personal descriptive information. In addition, the supplication strategy, according to Jones [24], was rarely used.

Especially with the development of science and technology, human interaction is no longer limited to simple, real-time, face-to-face communication [43]; human interaction began with a variety of non-face-to-face, computer-mediated modes of communication [37,44]. In face-to-face interactions, people are limited and hindered in terms of their self-presentation. For example, when others see us for the first time, they tend to form assumptions; for example, people cannot effectively control spontaneous verbal or nonverbal responses. The web homepage, however, can solve these problems and be adapted for self-presentation with strategic complexity [45,46]. Therefore, the personal page of the host includes their name, age, region, interests, hobbies, and other personal information. The vast majority of online accommodation sharing sites encourage people to use their real names and other personal information and upload real photos as personal profile pictures.

The implementation of the self-presentation strategy is not that simple. There are many reasons for people to self-present in online shared accommodation platforms. First, to promote the smooth conduct of sharing behavior, hosts need to play a positive role in the sharing model. To attract more guests to participate in the process of sharing economic activities, self-presentation should provide more material or social rewards. Moreover, self-presentation is used for self-impression construction, which involves convincing guests that the host has the qualities or attributes mentioned so as to provide good accommodation.

With the development of online P2P platforms, the media of interactive communication affect the content, form, and goal of people’s self-presentation. Therefore, the stage of people’s self-presentation is also broadened, and hosts’ self-presentation should thus be strategic. Therefore, it is a challenge to determine the influence of each strategy that works on the behavior of guests. However, as far as we know, the current research on self-description focuses mainly on the level of vocabulary and phrases, while research on the more macro-level characteristics, such as the use of strategies, is still lacking. In this paper, the self-presentation strategy proposed by Jones and Pittman [24] in the 1980s is used to further conceptualize self-presentation. Jones and Pittman [24] found five common self-presentation strategies in interpersonal interactions: ingratiation, self-promotion, intimidation, supplication, and exemplification. Research studies such as the one conducted by Tussyadiah [47] have explored the self-presentation strategies hosts in the peer-to-peer accommodation sector use to effectively communicate with and attract potential consumers. Furthermore, another study [48] based on an analysis of 6074 Airbnb listings found that emphasizing social values through self-presentation strategies can indeed lead to an increase in sellers’ revenues. However, there are currently no available research studies that specifically apply Jones and Pittman’s self-presentation strategies to examine the association between host self-description and consumer purchasing behavior.

2.4. Hypothesis Development

2.4.1. Influence of Ingratiation Tactics on Consumer Purchase Behavior

Ingratiation is the most commonly used tactic for self-presentation. In using this strategy, individuals often employ tactics such as mentioning the positive attributes of others or conforming to their opinions in order to enhance their own personal qualities and appear more likable. The preference for shared accommodation over hotels stems from the desire for unique and personalized experiences [49,50]. It has been found that the use of ingratiation tactics significantly influences judgments of interpersonal attraction [24]. Moreover, research suggests that service employees who employ ingratiation tactics are positively associated with customers’ deep acting [51]. In the context of hosting, if hosts are able to offer distinctive experiences that include a variety of entertainment activities, they are more likely to attract a greater number of guests [52]. We hypothesize the following:

H1. 

The ingratiation tactic has a positive impact on consumer purchase behavior.

2.4.2. Influence of the Self-Promotion Tactic on Consumer Purchase Behavior

The goal of the self-promotion tactic is to make oneself appear competent to others. Using this tactic, people may elevate themselves either in general or in some particular way. A common feature of this strategy is related to topics such as competence, achievement, performance, and qualifications. Self-promotion is used to emphasize the favorable aspects of oneself or to enable one to appear competent [53]. On SNSs, self-promotion mainly depends on status updates, adding personal photos, and integrating self-descriptions, which have been shown to contribute to both subjective vitality and compulsion [40]. In the shared accommodation sector, hosts display their experience and ability to prove that they can provide qualified accommodation services [27,54]. Thus, this paper also hypothesizes the following:

H2. 

The self-promotion tactic has a positive impact on consumer purchase behavior.

2.4.3. Influence of the Intimidation Tactic on Consumer Purchase Behavior

In interpersonal communication, some people often create momentum at the beginning [55], a preemptive, so that others do not understand, thus controlling the impression of others. People who use this tactic form an impression that they are strong and unapproachable. Although “intimidation” is less used as a self-presentation tactic, it is more frequently found in host self-information. Research [56] suggests that grandiose narcissism is indeed associated with higher levels of intimidation. Individuals with Grandiose narcissism often display dominance, arrogance, and a need for power and control, which can lead to intimidating behavior. Research [57] highlights that the unique variance of antagonism is associated with increased tendencies to engage in blasting and intimidation behaviors while also displaying a reduced inclination towards offering apologies. Personality differences among hosts can indeed influence the use of threatening words or intimidating strategies. People with certain personality traits, such as those associated with antagonism or grandiose narcissism, may be inclined to use intimidating tactics in their interactions. While intimidation strategies may initially exert some control or influence, they can also have negative consequences. Using threatening words or intimidating behavior can create a hostile environment and repel potential customers or damage relationships. Thus, this paper hypothesizes the following:

H3. 

The intimidation tactic has a negative impact on consumer purchase behavior.

2.4.4. Influence of the Supplication Tactic on Consumer Purchase Behavior

The supplication tactic involves showing others your weakness and dependence on others, intending to elicit sympathy from others, and then obtaining help from others. At the same time, this tactic is also a trick that some people use to gain trust, sympathy, and other material help; it is used to demonstrate helplessness and thus attract others to help. Vulnerable narcissism is associated with increased supplication [56]. Individuals with vulnerable narcissism may exhibit a more submissive and self-effacing attitude, seeking validation and reassurance from others through excessive compliance and deference. To build favorable images with consumers, 31.8% of modern corporations’ websites use the supplication tactic [58]. Some hosts employ the supplication tactic as a self-presentation strategy to attract more guests and encourage their purchase behavior. By portraying themselves as vulnerable or in need of support, these hosts aim to elicit sympathy and empathy from potential guests. Therefore, this paper hypothesizes the following:

H4. 

The supplication tactic has a positive impact on consumer purchase behavior.

2.4.5. Influence of the Exemplification Tactic on Consumer Purchase Behavior

The exemplification tactic aims to give others the impression of integrity and noble conduct and thus make others feel good about one another and foster a sense of trust. Research [59] has shown that the strategy of exemplification plays a significant role in directly explaining purchase behavior. This finding is particularly significant as it provides a fresh perspective on the behavior of the players involved in purchasing virtual items. Moreover, the exemplification tactic can also play a role in shaping consumers’ social norms and sense of identity. By projecting stories of social responsibility, organizations can enhance consumer attitudes by presenting themselves as virtuous and morally worthy [60]. By presenting positive examples, demonstrating desirable outcomes, and creating a sense of identification, the host can effectively persuade consumers to make purchasing decisions in their favor [61]. Therefore, this paper hypothesizes the following:

H5. 

The exemplification tactic has a positive impact on consumer purchase behavior.

2.5. Moderation Effect of Third-Party Certification

Asymmetric information can cause a lack of accurate information for both buyers and sellers prior to making purchase decisions, which can affect their willingness to engage in trade. When consumers are unable to discern the true quality of a product, they rely on other indicators or signals, such as seller status, experience, and ability; this is known as signal theory [62,63]. Signal theory posits that signals can convey information from the party with more information to the party with less information, thereby reducing the problem of information asymmetry faced by communicators [64]. In new consumer models like shared accommodation, which involve online transactions and offline experiences, the information asymmetry between host service quality and customer needs highlights the importance of trust signals in forming consumer purchase decisions. Platforms like Airbnb describe superhosts as experienced individuals who provide unforgettable travel experiences for their guests. Empirical research has shown that hosts with the superhost badge receive more reviews and higher ratings [54], making guests more likely to book rooms attached to a host with the superhost badge. Therefore, certified hosts are more likely to receive greater bookings in comparison to other hosts.

Considering the difference in self-presentation tactics and superhost badge influence on user behavior, the effect of self-presentation is expected to change with the change in the type of host badge. If a host on the online platform has a superhost badge, then the guest will value their badges more when making decisions and ignore the content of their self-presentation. Conversely, if the host does not have a superhost badge, then the guest can make a decision only by carefully reading the host’s self-description. Therefore, assuming that when a host receives a superhost badge, it weakens the role of the self-presentation strategy when users make decisions, Hypotheses 6A to 6E are proposed. The conceptual framework of the present study is shown in Figure 1.

H6A. 

Third-party certification weakens the relationship between the ingratiation tactic of self-presentation and consumer purchase behavior.

H6B. 

Third-party certification weakens the relationship between the self-promotion tactic of self-presentation and consumer purchase behavior.

H6C. 

Third-party certification weakens the relationship between the intimidation tactic of self-presentation and consumer purchase behavior.

H6D. 

Third-party certification weakens the relationship between the supplication tactic of the self-presentation and consumer purchase behavior.

H6E. 

Third-party certification weakens the relationship between the exemplification tactic of self-presentation and consumer purchase behavior.

3. Materials and Methods

3.1. Data Collection

Airbnb, as a fairly new short-term rental platform, has revolutionized the public’s perception of traditional hotel accommodations. As the community platform continues to grow, it offers millions of unique options, including villas, apartments, castles, treehouses, and more, for travelers around the world. At the same time, the platform also allows hosts with idle resources to rent out a property, which improves the utilization rate of such idle resources to obtain maximum income. Inside Airbnb is a mission-driven project that provides data on http://insideairbnb.com (accessed on 20 May 2023). The listings in New York, USA, were selected as our dataset for the following reasons:

• It has a massive number of hosts to provide listings;
• As a worldwide city, the host self-descriptions of the respective listings are mainly in English;
• Hosts and guests in New York come from around the world, which weakens the influence of culture.

The sample data used in this study cover most of the host information, such as self-description, superhost badge, verification status, response time, and response rate and include listing information, such as price, reviews, and rating. The New York dataset contains a total of 39,881 listings. The data in the dataset were preprocessed as follows:

• Remove the data with empty text or those with a length of less than five words from the host’s self-description;
• Remove the data that pertain to confusing information provided by the platform;
• Remove the data that do not even pertain to empty text but are composed of punctuation that had no analytical meaning or value.

After the above three steps were carried out, 12,971 data records that were consistent with this study were obtained.

3.2. Measurement

3.2.1. Dependent Variable

In this study, host self-description is considered as the main research subject to examine its effects on guest behavior. In Section 2, the self-presentation strategy used in this paper was introduced. To measure the tactics involved, Linguistic Inquiry and Word Count (LIWC) was used to analyze host self-descriptions, as it is the gold standard with respect to software for analyzing word use. LIWC is used to analyze the language of others and can help people understand their thoughts, feelings, personality, and the ways in which they connect with others. Over 20,000 scientific articles involving the use of LIWC have already been published. Therefore, the reliability [65] and validity of LIWC analyses have been well established [66].

The tactic of ingratiation involves influencing others with certain strategic behaviors (e.g., elevating others and conforming to others’ opinions) to increase the attractiveness of one’s own personal qualities and make oneself seem likeable. Studies have shown that the ingratiation tactic can be effective in affecting others’ behavior. Compared with traditional hotels, people who opt for shared accommodation prefer rich and unique experiences, so hosts can implement the ingratiation tactic by meeting the needs of guests. Entertainment, which is one dimension of experience identified by Pine [67], is proven to have an appreciable effect on both consumer satisfaction and trust [68]. Therefore, it is necessary to use this strategy to attract guests by showing them the entertainment options that they have or can provide. Entertainment, as one of the reasons why customers choose to share accommodation, is also consistent with the ingratiation tactic. Thus, the language features we extracted in LIWC included game, fun, play, and party to express the host’s behavior of pleasing the guest.

The self-promotion tactic involves communicating one’s abilities and accomplishments to achieve a goal [69]. People usually think that a longer and more detailed description can be effective. Construal-level theory [58] was used to investigate self-promotion in P2P trading, which affirms that it has a positive effect on seller revenues [48]. In the shared accommodation sector, hosts tend to present themselves using longer and more detailed descriptions in their self-descriptions to prove their ability to provide a quality service. In LIWC, topic diversity was extracted to describe self-promotion tactics.

Exemplification. The exemplifier typically presents themselves as honest, disciplined, charitable, and self-abnegating. Hosts using exemplification tactics to build the impression of authenticity can improve guests’ trust. Authenticity can be applied in many ways, including various meanings. Airbnb guests usually choose shared accommodation because they hope to obtain a real experience that is generated through social contact with local culture. In this respect, authenticity involves how comfortable the home is and how much personality the environment has. In LIWC, when people display their own information, the true meaning is expressed more directly rather than in an evasive way. In this study, authenticity was measured by algorithms derived from various LIWC variables based on previous empirical research.

The supplication tactic involves receiving special treatment from others or appearing helpless so that others will help you. A vulnerable narcissist may strategically act weak to gain favor and sympathy (pleading). In shared accommodation, supplication can give the impression that the host is nonaggressive and vulnerable, thereby building a sense of safety among consumers. However, the more common method simply requires the consumer and host to work with organizations, thereby improving consumer attitudes by stimulating expressions of sympathy or enhancing self-worth [70]. In LIWC, words such as lack/want are extracted to describe the supplication tactic.

Intimidation typically involves threats, anger, and underlying displeasure and is usually not used on a daily basis. Intimidators are able to control their relations with others when they have enough power to defend against aggressive threats [24]. In commercial activities, intimidation tactics are not used infrequently for threatening purposes, particularly for consumers. Some hosts focus their efforts on inducing fear by using threatening lexis in their self-description, suggesting that consumers have limited options when they provide a superior product or service. In LIWC, anger emotions were extracted to describe the intimidation tactic.

3.2.2. Explanatory Variable

Purchase behavior is influenced by host information, listing information, and so on. However, the number of orders is not provided by the Airbnb platform. Thus, researchers often use the number of reviews instead. However, this methodology is flawed as not all consumers comment; therefore, we combined the number of reviews with the rate of reviews. Inside Airbnb’s analysis suggests that it would be reasonable to use 50% as the review rate because it sits almost exactly between 72% and 30.5%. Accordingly, the present paper describes consumer purchase behavior as the number of reviews divided by the review rate (50%).

3.2.3. Controlling Variables

In this study, six controlling variables are considered: rating score, response rate, price, accommodation, personal photo, and identity verification. Rating score refers to the average review score given by guests. Response rate refers to the rate of a host responding to his guests. Price is one of the key factors for consumers in the P2P market [71]. Therefore, it is not surprising that prices and pricing strategies are particularly relevant to Airbnb. Accommodation refers to the number of listings that can accommodate passengers. Personal photo refers to whether the host has provided a personal photo, which has been found to have a positive effect on the price of the listing and the probability of one choosing to stay there [72]. Therefore, providing personal photos is treated as 1; otherwise, it is treated as 0. Identity verification refers to whether the host’s identification has been verified by the platform. Therefore, verified identity is treated as 1; otherwise, it is 0.

Third-party certification on Airbnb is auto-endowed by the platform in the form of a superhost badge. A host with a superhost badge is treated as 1; otherwise, it is 0. The descriptions and measurements of all variables are shown in

Table 1. Descriptions and measurements of variables.

Variable Type	Variable	Measures
Dependent variable	Review number	Ln(review number)
Independent variable	Ingratiation	$\frac{\mathrm{Number} \mathrm{of} \mathrm{words} \mathrm{expressing} \mathrm{ingratiation}}{\mathrm{number} \mathrm{of} \mathrm{words} \mathrm{of} \mathrm{host} \mathrm{self-description}}$
	Self-promotion	Topic number extracted by the meaning extraction method (MEM)
	Exemplification	Numbers are standardized scores ranging from 1 to 99.
	Supplication	$\frac{\mathrm{Number} \mathrm{of} \mathrm{words} \mathrm{expressing} \mathrm{supplication}}{\mathrm{number} \mathrm{of} \mathrm{words} \mathrm{of} \mathrm{host} \mathrm{self-description}}$
	Intimidation	$\frac{\mathrm{Number} \mathrm{of} \mathrm{words} \mathrm{expressing} \mathrm{intimidation}}{\mathrm{number} \mathrm{of} \mathrm{words} \mathrm{of} \mathrm{host} \mathrm{self-description}}$
Moderating variable	Third-party certification	Endowed superhost badge is 1 and 0 otherwise
Controlling variable	Rating score	From 0 to 5
	Response rate	From 0 to 100%
	Price	Price per night in dollars
	Personal photo	Provision of a personal photo is 1 and 0 otherwise
	Identity verification	Through identity verification is 1 and 0 otherwise
	Accommodates	Number of people an accommodation can hold

, which provides a comprehensive overview of the variables used in this study, including their variable type, variable name, and the measurement of variables.

4. Results and Discussion

4.1. Descriptions and Correlations

In our study, ordinary least squares (OLS) regression was applied to test Hypotheses H1 to H6. The above-listed variables were extracted from the dataset and are illustrated in

Table 2. Correlations, means, and standard deviations (SDs) (n = 12,791).

	Mean	SD	1	2	3	4	5	6	7	8	9	10	11	12	13
1. Exemplification	71.93929	32.6282	1
2. Intimidation	0.0179611	0.1946284	−0.046 ***	1
3. Ingratiation	2.080059	4.728654	−0.101 ***	0.021 **	1
4. Supplication	0.0347971	0.4229522	−0.016 *	−0.005	−0.017 *	1
5. Selfpromotion	0.4110386	0.147807	−0.248 ***	0.009	0.230 ***	−0.020 **	1
6. Responserate	0.947886	0.1622301	−0.019 **	0.021 **	−0.047 ***	−0.003	−0.030 ***	1
7. Superhost	0.4469549	0.4971977	0.022 **	0.038 ***	0	−0.020 **	−0.051 ***	0.212 ***	1
8. Personalphoto	0.9985146	0.038514	0.009	0.004	0.013	0.003	0.019 **	−0.005	0.018 **	1
9.Identity_verified	0.8832773	0.3211021	0.038 ***	0.01	0.002	−0.040 ***	0.003	0.033 ***	0.007	0.030 ***	1
10.Accommodation	3.285201	2.214346	−0.026 ***	0.013	−0.017 *	−0.028 ***	−0.001	0.051 ***	0.008	−0.004	0.004	1
11. Price	161.6416	202.3004	−0.022 **	−0.022 **	0.021 **	−0.024 ***	0.039 ***	0.018 **	0.006	0.007	0.026 ***	0.420 ***	1
12. Review_scores	4.738007	0.4343801	0.032 ***	0.001	0.008	−0.003	−0.024 ***	0.109 ***	0.259 ***	0.007	−0.012	−0.001	0.039 ***	1
13. ln_reviews	2.989741	1.640128	0.066 ***	−0.020 **	0.036 ***	0.020 **	−0.090 ***	0.081 ***	0.328 ***	0.028 ***	−0.047 ***	0.060 ***	−0.056 ***	0.146 ***	1

Note: * p < 0.05, ** p < 0.01, and *** p < 0.001.

. Although some inconsistent data in the above work have been deleted, the collected data have not been censored. We first checked for constant error variance (homoscedasticity) using White’s test [73] and the Breusch–Pagan test [74]. The results failed White’s test (${\chi }^2=77.15, p<0.01$) and passed the Breusch–Pagan test (${\chi }^2=1.24, p>0.01$). Then, the robust standard errors approach [73,75], as an additional regression analysis, was performed to remedy the problem of heteroscedasticity. In order to assess the presence of multicollinearity among the independent variables, we computed the variance inflation factors (VIFs). The results indicated that the presence of multicollinearity is not likely to be a concern, as all VIFs were found to be below the commonly recommended threshold of 10.

The results are shown in

Table 3. Results of regression with robust standard errors and OLS (n = 12,791).

Variable	Robust			OLS
	Coefficient	t Value	Sig.	Coefficient	t Value	Sig.	VIF
Main effects
Exemplification	0.003	5.78	0.000	0.003	6.04	0.000	1.91
Intimidation	0.089	0.63	0.532	0.089	0.76	0.449	2.95
Ingratiation	0.023	5.80	0.000	0.023	6.37	0.000	1.62
Supplication	0.133	4.12	0.000	0.133	3.63	0.000	1.33
Selfpromotion	−0.713	−5.68	0.000	−0.713	−5.75	0.000	1.85
Control variables
Responserate	0.101	1.14	0.256	0.101	1.19	0.235	1.06
Personalphoto	1.06	3.48	0.000	1.066	3.05	0.002	1.00
Identity_verified	−0.232	−5.78	0.000	−0.232	−5.52	0.000	1.01
Accommodation	0.076	7.70	0.000	0.076	11.31	0.000	1.22
Price	−0.000	−4.17	0.000	−0.000	−11.2	0.000	1.22
Review_scores	0.244	7.11	0.000	0.244	7.6	0.000	1.08
Moderating variable
Superhost	1.072	13.21	0.000	1.072	12.72	0.000	8.1
Moderating effects
Third-party certification × exemplification	−0.003	−3.67	0.000	−0.003	−3.58	0.000	7.26
Third-party certification × self-promotion	−0.089	−0.48	0.632	−0.089	−0.45	0.651	9.48
Third-party certification × intimidation	−0.606	−3.40	0.001	−0.606	−4.13	0.000	2.95
Third-party certification × ingratiation	−0.004	−0.80	0.424	−0.004	−0.76	0.449	1.84
Third-party certification × supplication	−0.138	−2.58	0.010	−0.138	−1.87	0.062	1.33
constant	0.292	0.81	0.418	0.292	0.74	0.459

, along with the OLS regression results. Both the t values and the significance levels of these path coefficients in these two models are significantly similar to those in the OLS model. Thus, the OLS results are reported in

Table 4. Results of OLS regression analysis for consumer purchase behavior (n = 12,791).

Variable			OLS Regression Analysis
	Model 1		Model 2		Model 3		Model 4
	Coeff. (S.E., VIF)	t Value	Coeff. (S.E., VIF)	t Value	Coeff. (S.E., VIF)	t Value	Coeff. (S.E., VIF)	t Value
Control variables
host_response_rate	0.643 *** (7.28, 1.02)	7.28	0.066 *** (0.088, 1.02)	7.63	0.010 (0.089, 1.06)	1.11	0.010 (0.089, 1.06)	1.14
host_has_profile_pic	1.282 *** (3.47, 1.00)	3.47	0.031 *** (0.349, 1.00)	3.74	0.025 ** (0.311, 1.00)	3.44	0.025 *** (0.306, 1.00)	3.48
host_identity_verified	−0.234 *** (−5.27, 1.00)	−5.27	−0.047 *** (0.041, 1.01)	−5.75	−0.047 *** (0.040, 1.01)	−6.02	−0.045 *** (0.040, 1.01)	−5.78
Accommodation	0.074 *** (10.54, 1.22)	10.54	0.103 *** (0.010, 1.22)	7.68	0.103 *** (0.010, 1.22)	7.80	0.103 *** (0.010, 1.22)	7.70
Price	−0.000 *** (−10.94, 1.22)	−10.94	−0.103 *** (0.000, 1.22)	−4.23	−0.101 *** (0.000, 1.22)	−4.19	−0.102 *** (0.000, 1.22)	−4.17
review_scores_rating	0.540 *** (16.38, 1.01)	16.38	0.139 *** (0.028, 1.02)	18.54	0.066 *** (0.034, 1.08)	7.22	0.065 *** (0.034, 1.08)	7.11
Main effects
exemplification			0.048 *** (0.000, 1.08)	5.25	0.044 *** (0.000, 1.08)	5.07	0.071 *** (0.001, 1.91)	5.78
intimidation			−0.024 ** (0.075, 1.00)	−2.67	−0.034 *** (0.077, 1.01)	−3.76	0.011 (0.144, 2.95)	0.63
ingratiation			0.066 *** (0.003, 1.06)	7.44	0.061 *** (0.003, 1.06)	7.20	0.067 *** (0.004, 1.62)	5.80
supplication			0.019 ** (0.028, 1.00)	2.72	0.025 ** (0.028, 1.00)	3.43	0.034 *** (0.032, 1.33)	4.12
Selfpromotion			−0.083 *** (0.099, 1.12)	−9.31	−0.07 *** (0.094, 1.12)	−8.25	−0.064 *** (0.125, 1.85)	−5.68
Moderating variable
Third-party certification					0.306 *** (0.029, 1.12)	35.05	0.306 *** (0.029, 8.1)	35.11
Moderating effects
Third-party certification × exemplification							−0.042 *** (0.001, 7.26)	−3.67
Third-party certification × self-promotion							−0.005 (0.188, 9.48)	−0.48
Third-party certification × intimidation							−0.059 *** (0.178, 2.95)	−3.40
Third-party certification × ingratiation							−0.008 (0.006, 1.84)	−0.80
Third-party certification × supplication							−0.018 ** (0.054, 1.33)	−2.58
_cons	−1.358 *** (−3.34)	−3.34	−1.153 ** (0.382)	−3.02	0.440 (0.361)	1.22	0.292 (0.361)	0.81
Observations	12,791		12,791		12,791		1372
R-squared	0.04		0.055		0.139		0.141
ΔR2	-		0.015		0.84		0.02
F test	91.01		67.99 ***		160.42 ***		111.56 ***

Standardized regression coefficients are reported with standard errors in parentheses. Two-tailed tests were performed. ** p < 0.01, and *** p < 0.001. VIF = variance inflation factor.

. First, controlling variables were entered in Model 1. Then, five independent variables were added to Model 2. Model 3 added the moderating variable (superhost). Finally, in Model 4, the five interaction terms of the dependent and moderating variables were introduced.

4.2. Discussion

A significant and positive correlation between ingratiating tactics and consumer purchase behavior was observed (β = 0.066; p < 0.001) in Model 2, thus supporting hypothesis H1. H2 indicates a positive relationship between the self-promotion tactic and consumer purchase behavior. Unexpectedly, a significant and negative coefficient for the self-promotion tactic (β = −0.083; p < 0.001) was found in Model 2. Thus, hypothesis H2 can be rejected. A possible explanation for this could be that from the perspective of the host, too much information may make consumers unable to obtain key content. There is a concave relationship between the amount of information and consumer purchase behavior [7]. Hypothesis H3 was supported in Model 2 as the relationship between the intimidation tactic and consumer purchase behavior was shown to be negative and significant (β = −0.024; p < 0.01). Hypothesis H4 was supported in Model 2, in which the relationship between the supplication tactic and consumer purchase behavior was shown to be positive and significant (β = 0.019; p < 0.01). Hypothesis H5 was supported in Model 2, in which the relationship between the exemplification tactic and consumer purchase behavior was shown to be positive and significant (β = 0.048; p < 0.001). The addition of these five variables significantly increased the R² value of the consumer purchase behavior enhanced over the previous model (ΔR² = 0.015, p < 0.001).

Subsequently, as a moderating variable, third-party certification was added into Model 3, and the interaction term of third-party certification and self-presentation strategy was added into Model 4. While H6A predicts that third-party certification has a significant negative regulating effect on the positive correlation between the ingratiation tactic and consumer purchase behavior, the coefficient for the interaction term of the ingratiation tactic and third-party certification (β = −0.008; p > 0.05) was found in Model 4. Thus, H6A can be rejected.

H6B predicts that the positive effect of the self-promotion tactic on consumer purchase behavior can be weakened by third-party certification. However, the coefficient for the interaction term of the self-promotion tactic and third-party certification (β = −0.005; p > 0.05) was found in Model 4. Thus, H6B can be rejected. A possible explanation for the rejection of H6A and H6B could be that regardless of whether or not the host has a superhost badge, guests care more about their service ability. A significant and negative coefficient for the intimidation tactic and consumer purchase behavior (β = −0.024; p < 0.01) was found in Model 2. A significant and negative coefficient for the interaction term of the intimidation tactic and third-party certification (β = −0.059; p < 0.001) was found in Model 4. This finding proves that third-party certification has a significant negative regulating impact on the negative effect between the intimidation tactic and consumer purchase behavior, thus supporting H6C.

A significant and positive coefficient for the supplication tactic and consumer purchase behavior (β = 0.019; p < 0.01) was found in Model 2. A significant and negative coefficient for the interaction term of the supplication tactic and third-party certification (β = −0.018; p < 0.01) was found in Model 4. This finding proves that third-party certification has a significant negative regulating impact on the negative effect between the supplication tactic and consumer purchase behavior, thus supporting H6D.

A significant and positive coefficient for the exemplification tactic and consumer purchase behavior (β = 0.048; p < 0.001) was found in Model 2. A significant and positive coefficient for the interaction term of the exemplification tactic and third-party certification (β = −0.042; p < 0.01) was found in Model 4. This finding proves that third-party certification has a significant negative regulating impact on the positive effect between the exemplification tactic and consumer purchase behavior, thus supporting H6E.

Many studies can support and explain our conclusions. According to common sense, adding the host self-description can help the guest understand the host better, thus alleviating information asymmetry between the guest and host. The superhost badge, as certified by a third party, is regarded by guests as a signal of accommodation quality and platform commitment [76]. Therefore, when a host is a certified superhost, customers may ignore the excellent host self-description on the website and trust the superhost badge given by the platform instead.

5. Conclusions

5.1. Theoretical Implications

In this paper, the role of self-presentation theory in host self-description on consumer behavior and the moderating role of third-party certification in self-presentation theory has been studied. The novelty of our paper lies in several aspects.

First, for the study, we employed big data analysis techniques. This research study involved the used of a big dataset (12,791) to mine and quantify the language content of self-description texts according to self-presentation tactics. Through leveraging big data techniques, we have provided a method for analyzing consumer purchase behavior. The inclusion of linguistic features such as emotion adds depth and richness to the analysis, setting it apart from previous studies that may not have explored text content in such detail.

Secondly, this study specifically focuses on the impact of self-description language. This research highlights the impact of linguistic features in self-description on self-presentation strategy, which in turn influences consumer purchase behavior. By examining how language content affects self-presentation tactics, this study sheds light on the crucial link between language and consumer behavior. This emphasis on language adds a unique perspective to the research and distinguishes it from studies that may have focused solely on other aspects of self-presentation or consumer behavior.

Lastly, this study also examines the role of superhosts as moderators in the relationship between self-description and consumer behavior. The research also examines the influence of superhosts (a form of third-party authentication) on the relationship between self-presentation strategies and consumer purchase behavior. By considering the role of superhosts as moderators, this research explores how the presence of a superhost badge impacts the effectiveness of self-presentation strategies, offering insights into the dynamics of shared accommodation platforms.

5.2. Practical Implications

Regarding hosts, our results can help them to improve their self-description ability, thus further improving their credibility and potentially increasing the number of orders they receive. Therefore, this paper asserts that the host should have a strategy to manage their presentation. For instance, when hosts write self-descriptions, they are advised to describe the amenities and services available or the local features, which highlights their ability to provide guests with a travel experience. At the same time, hosts should show guests their sense of morality. Because the accommodation is shared in the host’s home, guests are very concerned about their own safety, so a moral host is more attractive to guests.

In addition, hosts should avoid using threatening language. Although shared accommodation is characterized by a reciprocity mechanism, hosts also have the right to select guests; while the use of intimidation tactics safeguards their rights, it can also lead to customer withdrawal. In contrast, the host should use the strategy of supplication in moderation. Showing weakness to the guest makes the host look more sincere, which can arouse sympathy within the guest. While adequate information can form a full picture of the host, providing too much information can backfire [5]. Our work also finds that guests do not care about the host’s achievements but rather about their ability to provide services to guests.

For hosts who have not yet obtained a superhost badge, it is crucial to strategically describe yourself in order to attract more tenants to your home. This can be achieved by emphasizing professionalism and highlighting your charisma.

From the perspective of the platform, self-presentation can also help the manager of the platform. Sharing platform managers or designers could provide tips on using a self-presentation strategy to guide the host and advise them on which aspects should be mentioned and which should be omitted in their description.

6. Limitations and Future Research

Our study also has several limitations. First, the computer-aided text analysis method was used to describe the host’s self-description. However, this method has limited ability in word selection and matching. In the future, if there are better techniques of text analysis and extraction, they should be used. Second, in this study, superhosts were used as our moderators, but there are many factors, such as accommodation, websites, hosts, property, historical reviews, rental policies, and availability, that influence consumer behavior. Furthermore, there are other factors that may influence the relationship between self-presentation strategies and consumer behavior, which may open up more opportunities for future research.