1. bookVolume 11 (2021): Issue 1 (December 2021)
Journal Details
License
Format
Journal
eISSN
2182-4924
First Published
30 Apr 2016
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3 times per year
Languages
English
access type Open Access

The Role of Micro-Influencers in the Consumer Decision-Making Process in the Hospitality Field

Published Online: 30 Dec 2021
Volume & Issue: Volume 11 (2021) - Issue 1 (December 2021)
Page range: 102 - 112
Received: 15 Sep 2020
Accepted: 31 May 2021
Journal Details
License
Format
Journal
eISSN
2182-4924
First Published
30 Apr 2016
Publication timeframe
3 times per year
Languages
English
Abstract

The aim of this research is to understand the role played by social media influencers in consumers’ decision-making processes concerning hotels. To achieve this general objective, the following specific aims were defined: (1) to understand the profile of the micro-influencers that share user generated content (UGC) about hotels and the main networks within which they operate; to this end, a study was made by means of interviews to ascertain the profiles of 16 unpaid micro-influencers who share content about Portuguese hotels, and (2) to adopt the information acceptance model (IACM) put forward by Erkan and Evans (2016), to examine the influence of electronic word of mouth (eWOM) in social media on cosumer's behaviour intention in hotel industry, based on the profile of 166 consumers who follow these micro-influencers. Findings suggest that micro-influencers play a significant role in terms of influencing consumer purchase decision-making in the hospitality area; about 79% of surveyed consumers who follow micro-influencers’ content feel their choice is influenced and consider that the contents shared enable consumers to form an idea of what their stay will be like, due to some of the micro-influencers’ characteristics. The adoption of the IACM model demonstrates that the credibility of eWOM information positively affects the usefulness of the information. However, the quality of eWOM information, needs of eWOM information, and attitudes toward eWOM have a medium effect on the usefulness of eWOM information, but also in the attitudes toward eWOM and usefulness of eWOM in the adoption of eWOM information. The followers’ behavioural intentions are strongly explained by their attitudes toward eWOM information and adoption of eWOM information.

Keywords

Introduction

The development of technology and the Internet has changed consumers’ decision-making processes, the way they make their purchases, and how they interact and communicate with other people. These days, consumers use social networks and the Internet to share their experiences and opinions, to find information about products or services, and to make purchases online (Katawetawaraks & Wang, 2011).

Due to the continuous sharing of information, experiences, and comments, social networks have become a marketing tool for companies (influence marketing) and a means to support consumer decision making. They have also enabled the emergence of people who share their experiences and opinions on certain products and services, known as influencers, as they are able to influence consumers in their decision-making processes (Roelens et al., 2016).

Influencers’ shared online content, principally on hotels and destinations, has positively affected purchase decisions in the hotel and tourism sector, as when consumers intend to make a trip, they normally use digital media to search for ideas or information about the destination or the hotel. Shared multimedia content, such as photos and videos, helps the consumer to imagine the hotel or destination and overcomes the intangibility of online shopping (Terttunen, 2017; Xu & Pratt, 2018).

The role of micro-influencers in consumer decision-making processes is still a recent and little-studied topic, especially in the hotel sector. As yet there are few references in the literature and research related to this theme, so a study on this topic will fill a gap in this area of information and will provide a basis for study and data, paving the way for new research. It is thus crucial to study the profile of some of these micro-influencers to understand the characteristics and factors that contribute to their ability to influence consumers’ choice of hotel; it is also vital to study the profile of the consumers who follow these micro-influencers.

Social Media Network Influencers

In the Internet age, the emergence of new information technologies and social networking applications such as Instagram, Facebook, Twitter, Skype, and blogs, have brought innovation to the way in which people communicate, and have empowered social networks, which are visited more and more often by today's users (Liu et al., 2015).

Social networks have become an integral part of people's day-to-day lives. Social networks thus constitute an ensemble of applications that enable people to share their content, opinions, and experiences, and also allow access to entertainment and news (Faria & Elliot 2012; Ngai et al., 2015; Khan et al., 2017).

In terms of social media network influencers (SMNIs), there are different types that differ in terms of functionality and scope. Social networking sites allow users to create a personal profile and connect with other people by inviting colleagues and friends and by sending private or public messages. Users can choose what to share on their personal profiles, from objective data such as name, age, gender, and profession to subjective information like thoughts, opinions, likes, and dislikes. These personal profiles could also include photos, videos, links, and audio files (Kaplan & Haenlein, 2010). It is also important to reveal that in this new reality, the concept of prosumer is born to refer to how consumers have become more influential thanks to their ability to share their consumer experiences quickly, easily, and openly with an increasing number of people (Fine et al., 2017). Because content generated on social networks (Facebook, Instagram, Twitter, Snapchat, Pinterest) and review platforms (TripAdvisor, Holiday Check) derive from content posted by its members, they become ‘co-creators’ or ‘producer-consumers’ (i.e., prosumers; Fine et al., 2017). Members of a community, while generating content (co-creators), also support their decisions as consumers in the content generated by others, thus fully assuming the role of prosumer.

Influencers are people who share their knowledge, experiences, and opinions about certain products and services and aim to lead their followers to adopt a certain behaviour or attitude by posting content on social networks or blogs (Roelens et al., 2016). Senft (2008) noted that influencers can be characterized as ‘micro-celebrities’. They are a new approach of online performance that involves people expanding their recognition by using technologies like social platforms, blogs, and videos (Senft, 2008).

Increased adherence to social networks has led to the emergence of two new concepts: digital marketing and influence marketing. Both use digital media and electronic word of mouth (eWOM), which consists of word of mouth being propagated electronically through digital media, social networks, and social interactions to attract potential new customers (Li et al., 2011).

According to Lin et al. (2018), influencers interact directly with their followers, who consider them individuals with whom they can identify and respected, well-informed, and connected individuals. Influencers use eWOM in the form of videos, photos, text, or audio to share their experiences and content.

Trammell and Keshelashvili (2005) stated that influencers are often described as holding strong opinions and being reliable and frequently sought after by their peers for advice, whether online or offline (Freberg et al., 2011). In addition, De Veirman et al. (2017) explained that they are considered trendsetters in one or more niches and that they exert particular influence on people with whom they share specific interests (Uzunoglu & Kip, 2014). This influence takes place through sharing of eWOM, Uer Generated Content (UGC), or both, which in most cases consists of narration of their personal lives, lifestyles, and consumption choices by means of text and images (Abidin, 2015).

Of the various existing social networks, those most often used by influencers currently are undoubtedly Instagram and Facebook. However, regarding micro-influencers, it is also important to mention blogs, as most hotel and travel micro-influencers usually post to a blog to support their shares on social networks (Neiva, 2018).

However, the literature acknowledges the interest in studying the effects produced by different types of SMNIs (De Veirman et al., 2017), in particular, micro-influencers; that is, those who have a smaller number of followers (Casaló et al., 2020). Indeed, there is increasing debate about the value of influencers with smaller audiences. Arguments in favour of this type of influencer include their ability to provide focused communication, because they have a smaller, more loyal, and more devoted audience; and the high level of confidence inspired in their followers, considering that they create an empathic relationship and greater proximity and develop feelings of trust and need to follow their posts and their ability to generate greater levels of involvement when compared to larger scale influencers. In addition, micro-influencers are not usually driven by monetary reward, unlike larger scale influencers, which makes them more reliable, truthful, and accessible in the eyes of their audience (Gretzel, 2018; Lin et al., 2018; Neves & Liljeblad, 2017).

Online Consumer Behaviour: Information Acceptance Model

Consumer behaviour is the process via which the consumer selects, buys, uses, or benefits from a product, service, or experience to satisfy a need or desire. In the study of consumer behaviour, the aim is to understand the entire decision-making process and the reasons that led the consumer to decide to buy a certain product or service (Swarbrooke & Horner, 1999).

Online purchases of products or services are principally motivated by convenience, the amount of information and products available, and time and cost efficiency. However, this process can be affected by the intangible nature of the product, the risk associated with the information source, the product, the payment method, and the processing of personal data. Therefore, the online purchase process implies not only using technology, but also having confidence in the product one is buying and the seller one buys from (Katawetawaraks & Wang, 2011).

Erkan and Evans (2016) developed the information acceptance model (IACM) to examine the influence of eWOM on consumers’ purchase intentions. This is an attempt to develop a more robust model and includes (1) the information adoption model (IAM; Sussman & Siegal, 2003), which explains the influence of the characteristics of information (quality, credibility, and usefulness of information) on its adoption, alongside (2) related components of the theory of reasoned action (TRA) model by Fishbein and Ajzen (1975), regarding the attitude toward information, which represents the characteristics of the recipient. More specifically, it expresses consumer behaviour in relation to the information and its relationship to the purchase intention. In addition, this model also includes information needs as a characteristic of the recipient related to the information; it is considered an important determinant of the perception of the usefulness of the information and, consequently, of adoption of the information and purchase intention. Thus, this model is based on six variables around information: quality, credibility, need, attitudes, usefulness, and adoption. The IACM was validated through structural equation modelling. According to the IACM results, quality, credibility, usefulness and adoption of information, needs of information, and attitude toward information are the key factors of eWOM in social media that influence consumers’ purchase intentions.

IACM Adoption to eWOM Social Media about Hotels

In view of the literature review, the study of social media influencers (SMIs) in the hotel industry is still somewhat limited. The first aspect to point out is the fact that existing studies focus almost exclusively on bloggers, despite recognition of the interest in considering other social networks and other types of social media influencers (De Veirman et al., 2017). Studies exhibit a focus on fashion and lifestyle blogs; however, as the industry becomes more familiar with the use of influencers (Sudha & Sheena, 2017), the relevance of intensified research in the area of micro-influencers in the area of tourism and hospitality is being recognised, but applied to recently emerged social networks, including Instagram and Face-book (Abidin, 2015). Some authors have studied the areas of tourism (e.g., Magno & Cassia, 2018; Xu & Pratt, 2018) and culture (Magno, 2017). Similarly, Hsu et al. (2013) identified a positive relationship between confidence and purchase intention and Huang (2015) found that confidence has a similarly positive effect on attitudes toward the destination.

Content about hotels and destinations shared by influencers has helped overcome the intangibility of buying these products online. As travel and hotel stays are services, they cannot be seen, tested, or evaluated before use, and this can sometimes make the purchase decision difficult, as the risk of disappointment might be high. By means of shared videos and photos about hotels or destinations, consumers are able to view the service they are purchasing and gain a more authentic idea of it, in addition getting feedback from other people's experiences, be they positive or negative. Thus, content about hotels shared by influencers can positively affect consumer behaviour and purchase decisions (Ladhari & Michaud, 2015; Terttunen, 2017).

Because micro-influencers have a smaller and more dedicated audience, they create a more empathic and closer relationship with their followers, who therefore recognise them as being more authentic and reliable influencers, on whose opinions they can base their purchase decisions. Another factor that makes these influencers more authentic in the eyes of their followers is the fact that most are not paid for their posts. Furthermore, a close relationship also exists between influencer and consumer, allowing consumers to place more confidence in the feedback and content sharing of the influencer and leading them to want to buy that product or service (Casaló et al., 2020; Uzunoglu, 2014). According to some studies already undertaken, followers tend to give less credence to influencers who admit to receiving any type of monetary reward for their posts (as is the case with macro- and mega-influencers; Casaló et al., 2020; Gretzel, 2018; Neves & Liljeblad, 2017; Senecal & Nantel, 2004). Therefore, the following hypotheses can be formulated:

H1. Adoption of eWOM information about hotels is positively related to consumers’ purchase intention.

H2. Usefulness of eWOM information is positively related to adoption of eWOM information.

The specialisation of the micro-influencer, the type of content shared, the number of followers or the reach they have, and the relevance, quality, attractiveness, regularity, and originality of their posts are all factors that can positively affect the behaviour and purchase decisions of consumers when choosing a hotel. In addition to these factors, there are also the characteristics of the micro-influencers themselves, such as trust, credibility, proximity to and interaction with the consumer, authenticity, and friendliness; these also influence consumer behaviour and purchase decisions (Ferreira, 2018; Neiva, 2018). The literature places special emphasis on trust and credibility (e.g., Halvorsen et al., 2013; Huang, 2015; Magno & Cassia, 2018). Tan and Chang (2016) demonstrated the positive impact of the travel bloggers’ credibility on readers’ level of acceptance of their articles, as well as on their intention to visit the tourist destination in question and to recommend the shared information

Thus, if the micro-influencer has a close relationship with his or her followers, is authentic, and shares relevant, true, quality content with a degree of regularity and originality, he or she has a greater probability of positively influencing consumers in their purchase decisions in the case of hotels (Ferreira, 2018; Lin et al., 2018; Lisichkova & Othman, 2017; Magno, 2017; Neiva, 2018). As a result, the following hypotheses were proposed.

H3. Quality of eWOM micro-influencer information about hotels is positively related to usefulness of eWOM information.

H4. Credibility of eWOM information about hotels is positively related to usefulness of eWOM information.

The hotel and tourism sector, like others, has been subject to broad changes in consumer behaviour due to content shared by influencers about destinations, trips, or hotels. Nowadays, when consumers want to travel, they can search for ideas or information about the destination or the hotel on social networks, and are able to obtain not only the information they want quickly, practically, and reliably, but also comments (be they positive or negative), reports of lived experiences, and suggestions for their trip (Hernández-méndez et al., 2015; Xu & Pratt, 2018). ‘Consumers increasingly use online media to search for information, compare alternative products and services, and make decisions for activities such as travel planning and hotel selection’ (Cheng et al., 2017, p. 54). Concerning the IACM, the authors found that information needs were considered an important determinant of the usefulness of the information. As a result, the following hypothesis was proposed.

H5. Needs of eWOM information about hotels are positively related to usefulness of eWOM information.

According to Terttunen (2017) and Gretzel (2018), content on hotels shared by micro-influencers in the form of photographs or videos enables consumers to imagine and visualise the service they are buying, helps them to overcome the intangibility of buying this type of online product, and makes the consumer aware of other people's experiences. These two connected factors can influence consumers’ purchase decisions when it comes to choosing a hotel. Moreover, the model proposed integrates the variable attitude toward the use of eWOM information, similar to studies on purchasing behaviours: TRA (Fishbein & Ajzen, 1975), theory of planned behaviour (Ajzen, 1991) and TAM (Davis et al., 1992), technology acceptance model. Based on these relationships with intention and purchase, Erkan and Evans (2016) postulated and validated the relationship between attitude toward information and purchase intention for eWOM. Therefore, the attitude of social media users toward eWOM information can have a positive effect on the adoption of such information and on consumers’ behaviour intentions. Thus, the following hypotheses are proposed:

H6. Attitude toward eWOM information is positively related to usefulness of eWOM information.

H7. Attitude toward eWOM information is positively related to adoption of eWOM information.

H8. Attitude toward eWOM information about hotels is positively related to consumers’ behaviour intention.

Hence, this research adopts the IACM to help explain online consumer behaviour intentions in the context of the influence on eWOM of the micro-influencers or micro-celebrities in social media on consumers’ purchase intention in a hospitality context.

Method

The research methodology used in this research was divided into two sections; the first section was oriented by qualitative-intensive research via interviews with micro-influencers and micro-celebrities, who share content about Portuguese hotels. This was done to study the relationship between these and the consumer, the type of content shared, and the main social media networks for sharing that content, thus providing a more in-depth understanding.

The second section is quantitative-extensive research, using surveys of consumers who follow micro-influencers’ and micro-celebrities’ content about hotels, with the participants’ perspective to examine the relation between micro-influencers and consumers. The IACM was adopted to test the model in a different context, in this case in the tourism and hotels, as suggested by Erkan and Evans (2016). The main objective is to examine the relationships between the following variables: information quality, information credibility, needs of information, attitude toward information, information usefulness, information adoption, and behavioural intention.

Sample and Data Collection

To select the micro-influencers and micro-celebrities for these interviews, searches were carried out on the Google search engine and on Instagram, using the following Key Words: Portuguese travel blog, Portuguese micro-influencers, #hotelportugal, #digitalinfluencer, #hotelinfluencer, and #portugalinfluencer. After the search phase, micro-influencers and micro-celebrities were selected on the basis of two criteria: They must have posts about hotels in Portugal and they must be considered micro-celebrities or micro-influencers, to fit the definition of micro-influencers according to Gretzel (2018), Lin et al. (2018), and Senft (2008) on Facebook and Instagram. This resulted in 16 interviews.

The interview guide is divided into four groups of questions on (1) the profile of the relationship between the micro-influencer and social networks, (2) the profile of the shared content, (3) the relationship with followers, and (4) the demographic profile. The qualitative data analysis conducted used manual methods, based on the research objectives.

The research uses a quantitative approach, which included data collection through web surveys, with a questionnaire specifically created for the purposes of this study. It analyses the connection of consumers to social networks, whether or not they are followers of micro-influencers who share content about Portuguese hotels and whether or not they are influenced in their decision making when choosing a hotel owing to a post made by a micro-influencer.

The questionnaire is divided into four groups of questions on (1) profile of the relationship with social networks, (2) hotels and online decision making, (3) hotels and profile of travel frequency, and finally (4) demographic profile. Nonprobabilistic and convenience sampling was used, as the objects of study of these surveys are simply individuals who follow micro-influencers with shares on Portuguese hotels and participate in their social networks. In total, 166 responses were obtained.

Figure 1

The research IACM model adoption.

Source: Adapted from Erkan and Evans (2016) IACM.

Data Analysis and Procedure

Descriptive statistics were used to describe the research results by variables. The qualitative data analysis conducted used manual methods, based on the research objectives.

Concerning the research model and hypotheses, the structural equation model (path analysis) was created to test the hypotheses and explain the relationships between the variables under study. A set of adjustment indexes—χ2/gl, comparative fit index (CFI), goodness-of-fit index (GFI), and root mean square error of approximation (RMSEA)—were used to test its validity.

Simple correlational analysis was also performed between the variables as a means of ascertaining the types of correlations that existed. The Spearman correlation test was used, as it was considered the most appropriate, taking the ordinal variables into account (Hair et al., 2010; Maroco, 2010).

Results and Discussion
Results of the Interviews with Micro-Influencers

Regarding the interviews, the profile of the sample of micro-influencers shows that 80% are female. All respondents say they use Facebook and Instagram as their networks for sharing, and 75% also use a blog as a support network. There is a wide range of ages, with two between 28 and 31 years old, and the rest between 36 and over 46. Regarding academic qualifications, 80% of respondents have a postgraduate qualification and 20% are graduates, and in terms of profession, they all have other jobs in addition to being micro-influencers, which leads us to believe that they undertake this activity as a hobby and not as a profession. Most of the interviewees have been engaged in micro-influencing activities for a number of years, with activity times varying between 11 months and 5 years. As for collaboration with agencies or partners, none of the interviewees in question works with influencer agencies.

Regarding content sharing, most of the respondents share at least once a week, with only one micro-influencer stating that they share only once a fortnight. All share content about hotels, and some also share about lifestyle, fashion, food, and technology.

According to the interviewees, their shared contents represent real experiences, and they choose the hotels they share on a completely personal basis, using criteria such as the quality of the experience, the quality/price ratio, good accessibility for people with reduced mobility, and hotels that value concepts that differ from the norm.

Regarding the influence they exert, the interviewees state that they feel they influence their followers with their posts on choice of hotel. In their view, some of the characteristics that they deem most important for their followers to follow them are the naturalness of their feed and posts, the regularity with which they share, the quality of the content, their availability to help and give tips, and genuineness. Some of these characteristics had already been studied by Ferreira (2018) and Neiva (2018), and among others were judged to be determining characteristics for influencing consumer behaviour in online choice and purchase of stays in hotels.

As for the impact that sharing visual content and sharing experiences has on the number of views and likes, all agreed that these two aspects do indeed have this effect. This is mainly because, in their view, images combined with positive feedback are very valuable and have great appeal for their readers. The platforms that provide greater visibility and a greater degree of influence are blogs and Instagram.

The fact that the interviewees feel that their posts of content about hotels influence their followers in their choice and purchase allows us to understand the profile of micro-influencers that share UGC about hotels, but also the main characteristics and platforms that contribute most to influence consumer behaviour in online hotel choice.

Results of the Survey Applied to Followers of Micro-Influencers on Social Networks

In the case of the surveys, the majority of respondents are women (about 72%), and with regard to age, about 46% of the sample are between 18 and 24 years old. This substantiates what Rebelo (2017) claimed, in that this age group is the target audience of choice for influencers, as they are younger and more connected to technology and social networks. A total of 96% of respondents visit social networks several times a day, and are on more than three social networks, with Facebook, Instagram, and LinkedIn being the most mentioned.

When asked whether they follow micro-influencers who share hotel content, 51% of respondents answered in the affirmative; that is, 84 of the respondents follow micro-influencers who share hotel-related content. Of these 84, around 79% feel that content shared by micro-influencers influences their decisions when choosing a hotel. Regarding use of accommodation, about 77% say they stay in a hotel once or twice a year and travel between one and four times a year (76%) for leisure reasons, as shown in Table 1.

Sample profile.

Item Frequency %
Gender
Male 47 28
Female 119 72

Age
18–24 76 46
25–31 25 15
32–45 32 19
> 55 33 20

Level of education
High school 39 23
University degree 86 52
Postgraduate qualification 41 25

Number of social networks used
1 10 6
2 37 22
> 3 119 72

Social network use
Several times a day 160 96
During the week 6 4

Follow influencers on hotels
Yes 84 51
No 82 49

Frequency of stays in a hotel
More than three times a month 1 1
Once a month 6 4
Every 2 months 10 6
Every 3 months 20 12
Twice a year 67 40
Once a year 62 37
Trips per year
Never 5 3
Once or twice 65 39
Three or four times 61 37
Five or six times 17 10
More than seven times 18 11

Reasons for travel
Work 9 5
Leisure 157 95
Measurement Model

A simple correlational analysis was also performed between the variables as a means of ascertaining the types of correlations that existed. The Spearman correlation test was used, as it was considered the most appropriate, taking the ordinal variables into account (Hair et al., 2010). The results of the correlations between the variables under study can be seen in Table 2. From these results, we can draw several conclusions.

Matrix of correlations between variables.

(AT) BI UF QL CD ND AT
Adoption of eWOM information (AD) 1.00
Behavioural intention (BI) .50** 1.00
Usefulness of eWOM information (UF) .14 .12 1.00
Quality of eWOM information (QL) .15 .29** .21* 1.00
Credibility of eWOM information (CD) .13 .07 .28** .19 1.00
Needs of eWOM information (ND) .25* .40** .17 .39** .20 1.00
Attitude toward eWOM information (AT) .50** .99** .12 .28** .08 .39** 1.00

Note: N = 88.

p < .05.

p < .001.

The usefulness of eWOM information is significantly correlated with the quality of information (rs = .21, p = .049) and credibility of eWOM information (rs = .28, p = .008). Adoption of eWOM information is positively and significantly correlated with behavioural intention (rs = .50, p < .001), needs of eWOM information (rs = .25, p = .021), and attitude toward eWOM information (rs = .50, p < .001).

The quality of eWOM information is significantly and positively correlated with behavioural intention (rs = .29, p = .007), usefulness of eWOM information (rs = .21, p = .049), needs of eWOM information (rs = .39, p < .001), and attitude toward eWOM information (rs = .28, p = .010).

The behavioural intention is positively and significantly correlated with adoption of eWOM information (rs = .50, p < .001), quality of eWOM information (rs = .29, p = .007), needs of eWOM information (rs = .40, p < .001), and attitude toward eWOM information (rs = .99, p < .001). The credibility of eWOM information has a positive and significant correlation with usefulness of eWOM information (rs = .28, p = .008).

Needs of eWOM information is positively and significantly correlated with adoption of eWOM information (rs = .25, p = .021), behavioural intention (rs = .40, p < .001), quality of eWOM information (rs =. 39, p < .001), and attitude toward eWOM information (rs = .39, p < .001).

Finally, the attitude toward eWOM information is significantly correlated with adoption of eWOM information (rs = .50, p < .001), behavioural intention (rs = .99, p < .001), quality of information eWOM information (rs = .28, p = .010), and need of eWOM information (rs = .39, p < .001).

Structural Equation Analysis: Testing Hypotheses

In the second phase of data analysis, the structural model was evaluated. The proposed conceptual model fits the data correctly. Table 3 shows the model results obtained concerning the seven hypothesised relationships between the variables in the study.

Results from the structural equations model (path analysis).

Independent variables Dependent variables B b t p R2
Quality of eWOM information Usefulness of eWOM Information .13 .14 1.24 .215 .183
Credibility of eWOM information .29 .30 2.74 .006
Needs of eWOM information .09 .11 0.98 .327
Attitudes toward eWOM information .01 .02 0.14 .886

Usefulness of eWOM information Adoption of eWOM Information .22 .17 1.77 .076 .048
Attitudes toward eWOM information .18 .46 4.90 < .001

Attitudes toward eWOM information Behavioural intention .98 .99 74.38 < .001 .988
Adoption of eWOM information .00 .00 0.30 .763

Goodness-of-fit indexes

χ2/gl .477
Goodness-of-Fit IndeX (GFI) .990
Normed Fit Index (NFI) .993
Comparative Fit Index (CFI) 1.000
Akaike's Information Criterion (AIC) 45.34
Root mean square error of approximation (RMSEA) .000

The credibility of eWOM information significantly explains the usefulness of eWOM information (B = .29, p < .001) and contributes to increasing it, thus validating Hypothesis H4. Analysis also shows that the attitudes toward eWOM contributes to a significant increase in adoption of eWOM information by 0.18 points (B = .18, p < .001), which allows us to validate Hypothesis H7. In addition, the link between the attitudes toward eWOM information has a direct effect on behavioural intention at 0.98 points (B = .98, p < .001), thus validating Hypothesis H8. On the other hand, the effect of the quality of eWOM information, credibility of eWOM information, needs of eWOM information, and attitudes toward eWOM explain only 18.3% (r2 = 0.183) of the usefulness of eWOM information, which means that they have a medium effect. Also, the attitudes toward eWOM and usefulness of eWOM information only contribute 4.8% (r2 = .048) to adoption of eWOM information.

Finally, the results revealed that behavioural intention is 98.8% explained (r2 = .988) by attitudes toward eWOM and adoption of eWOM information, which means that attitudes toward eWOM and adoption of eWOM information are the variables that best explain behavioural intention, thus validating Hypotheses H1 and H8.

Discussion and Implications

After analysing the results obtained, the objectives set at the beginning can be said to have been met, and it is also possible to state that micro-influencers already play a significant role regarding influence on consumer purchase decision making in the hotel area.

The answers obtained in the interviews carried out are in line with Neiva (2018), as the main platforms for sharing content used by micro-influencers are indeed Facebook, Instagram, and blogs. However, most hotel and travel micro-influencers in this research usually also have a blog to support their social sharing networks. As for the type of shared content, the choice of micro-influencers lies mainly in photographic content and text about their personal experiences. The choice of the hotel is grounded in a completely personal basis, using criteria such as the quality of the experience, the quality/price ratio, good accessibility for people with reduced mobility, and hotels that value concepts that differ from the norm. Regarding their influence on followers, the micro-influencers indicated that the naturalness of their feed and posts, the regularity with which they share, the quality of the content, their availability to help and give tips, and genuineness are determining characteristics for influencing consumer behaviour in online choice and purchase of stays in hotels, characteristics that had already been studied by Ferreira (2018) and Neiva (2018).

The results obtained in the surveys show that users turn to micro-influencers’ posts to help in their decision making, as they represent already lived experiences, on the basis of which they can form a reliable idea of what their stay will be like.

Considering the adoption of the IACM (Erkan & Evans, 2016), the results demonstrate that the credibility of eWOM information positively affects the usefulness of the information, and that the attitudes toward eWOM information about hotels have a significant effect in the adoption of eWOM information. Concerning behavioural intention, it was interesting to find that the followers’ behavioural intentions are explained by their attitudes toward eWOM information and adoption of eWOM information.

Concerning the medium effect of the quality of eWOM information, needs of eWOM information, and attitudes toward eWOM in the usefulness of eWOM information, but also in the attitudes toward eWOM and usefulness of eWOM in the adoption of eWOM information, this effect could be explained by the fact that, as Xu and Pratt (2018) indicated, hospitality is one of the sectors that has been most affected by differences in consumer behaviour regarding the sharing of content about hotels by influencers on social networks. This content overcomes the intangibility of the product in question and also allows consumers to have an idea of what their experience might be like, based on the experience of other consumers. Moreover, the characteristics of micro-influencers are determinants in the decision-making process, but having feedback from another person who is not paid to give it is also very important for consumers. It not only contributes to developing a close connection with the micro-influencer, but it also makes it easier for consumers to trust their opinions and prompts them to actually purchase a stay at that hotel (Casaló et al., 2020; Uzunoglu, 2014).

In conclusion, the development of technologies and social networks means that more and more micro-influencers are appearing. They are increasingly being seen by consumers and prosumers as models to follow and as reliable sources of information, as they have the ability to influence purchase decision making, particularly regarding hotels (Fine et al., 2017). Micro-influencers are already playing a relevant role in terms of influencing consumer decision making in the hotel sector.

The results obtained from this study reinforce the potential of a digital influencing marketing strategy in the hospitality field. Considering the characteristics of the hotel, it is essential to identify relevant key persons and endorse them to act as social influencers within specific segments of consumers. In addition, it is important to reinforce that micro-influencers are considered trendsetters in one or more niches and that they exert particular influence on people with whom they share specific interests

In the specific case of hotels, however, there are few unpaid micro-influencers. Most influencers in this area are macro- or mega-influencers; that is, they are remunerated for their services. This was one of the limitations of this study, together with the lack of studies and scientific articles that address the role of micro-influencers in the hotel industry and in consumer decision making. Nevertheless, it is possible to state that micro-influencers in the hotel area are an information tool that is still under development, although already important for the consumer to some extent.

Future research could develop the research model by adding more variables such as trust of eWOM information and involvement, or using the current one in the hotel context, but in an international perspective, considering that this research focused on a sample of Portuguese micro-influencers and Portuguese followers.

Finally, it is suggested that the relationship between micro-influencers and hotels be studied in both directions: how micro-influencers can work in partnership with hotels and vice versa, especially if it is an unpaid partnership, and also the relationship between hotel and consumer—how hotels can influence consumers’ purchase decision making. It might also be interesting to undertake a study on the advantages and disadvantages of working with paid and unpaid micro-influencers in the hotel context. In addition, this research focused on a sample of Portuguese micro-influencers and Portuguese followers, whereas an international comparison would have made it possible to take into account the influence of the tourist's behavioural intention as part of the proposed research model.

Figure 1

The research IACM model adoption.Source: Adapted from Erkan and Evans (2016) IACM.
The research IACM model adoption.Source: Adapted from Erkan and Evans (2016) IACM.

Matrix of correlations between variables.

(AT) BI UF QL CD ND AT
Adoption of eWOM information (AD) 1.00
Behavioural intention (BI) .50** 1.00
Usefulness of eWOM information (UF) .14 .12 1.00
Quality of eWOM information (QL) .15 .29** .21* 1.00
Credibility of eWOM information (CD) .13 .07 .28** .19 1.00
Needs of eWOM information (ND) .25* .40** .17 .39** .20 1.00
Attitude toward eWOM information (AT) .50** .99** .12 .28** .08 .39** 1.00

Results from the structural equations model (path analysis).

Independent variables Dependent variables B b t p R2
Quality of eWOM information Usefulness of eWOM Information .13 .14 1.24 .215 .183
Credibility of eWOM information .29 .30 2.74 .006
Needs of eWOM information .09 .11 0.98 .327
Attitudes toward eWOM information .01 .02 0.14 .886

Usefulness of eWOM information Adoption of eWOM Information .22 .17 1.77 .076 .048
Attitudes toward eWOM information .18 .46 4.90 < .001

Attitudes toward eWOM information Behavioural intention .98 .99 74.38 < .001 .988
Adoption of eWOM information .00 .00 0.30 .763

Goodness-of-fit indexes

χ2/gl .477
Goodness-of-Fit IndeX (GFI) .990
Normed Fit Index (NFI) .993
Comparative Fit Index (CFI) 1.000
Akaike's Information Criterion (AIC) 45.34
Root mean square error of approximation (RMSEA) .000

Sample profile.

Item Frequency %
Gender
Male 47 28
Female 119 72

Age
18–24 76 46
25–31 25 15
32–45 32 19
> 55 33 20

Level of education
High school 39 23
University degree 86 52
Postgraduate qualification 41 25

Number of social networks used
1 10 6
2 37 22
> 3 119 72

Social network use
Several times a day 160 96
During the week 6 4

Follow influencers on hotels
Yes 84 51
No 82 49

Frequency of stays in a hotel
More than three times a month 1 1
Once a month 6 4
Every 2 months 10 6
Every 3 months 20 12
Twice a year 67 40
Once a year 62 37
Trips per year
Never 5 3
Once or twice 65 39
Three or four times 61 37
Five or six times 17 10
More than seven times 18 11

Reasons for travel
Work 9 5
Leisure 157 95

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