Interactive engagement through travel and tourism social media groups: A social facilitation theory perspective

Abstract

This research investigates perceptions about online content attractiveness, interactive engagement and real time conversation capabilities through travel and tourism social media groups. The study hypothesizes that these factors affect the social media subscribers’ attitudes toward the destinations’ social media groups, their intentions to revisit them, and could even influence their social facilitation behaviors. The data was gathered from 923 Facebook (Meta) subscribers who were members of travel and tourism groups. A partial least squares (PLS) approach was used to reveal the validity and reliability of the chosen constructs. The findings suggest that Facebook subscribers were drawn to those groups that featured aesthetically pleasing content and to the ones that facilitated their engagement. This contribution implies that today's marketers ought to embrace digital transformation processes that are disrupting social network services (SNSs). Content curators are expected to continuously present appealing content in their social media posts, to interact with their followers in a timely manner, and to encourage positive social facilitation behaviors through online and offline channels.

Full text

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Interactive engagement through travel and tourism social media groups: A
social facilitation theory perspective
By Mark Anthony Camilleri
1
2
and Metin Kozak
3
Suggested citation: Camilleri, M.A. & Kozak, M. (2022). Interactive engagement through travel and tourism social media groups:
A social facilitation theory perspective. Technology in Society, https://doi.org/10.1016/j.techsoc.2022.102098
This is a prepublication version.
Highlights
• Social network services enable synchronous communications, concurrent engagement and facilitate real-time
conversations.
• This research explores the content attractiveness and interactive capabilities of social media groups.
• A composite-based structural equations modelling approach confirms the reliability and validity of this study.
• Interactive social media groups affect the subscribers’ intentions to revisit them as well as their social
facilitation behaviors.
Abstract
This research investigates perceptions about online content attractiveness, interactive engagement and real
time conversation capabilities through travel and tourism social media groups. The study hypothesizes that
these factors affect the social media subscribers’ attitudes toward the destinations’ social media groups,
their intentions to revisit them, and could even influence their social facilitation behaviors. The data was
gathered from 923 Facebook (Meta) subscribers who were members of travel and tourism groups. A partial
least squares (PLS) approach was used to reveal the validity and reliability of the chosen constructs. The
findings suggest that Facebook subscribers were drawn to those groups that featured aesthetically pleasing
content and to the ones that facilitated their engagement. This contribution implies that today's marketers
ought to embrace digital transformation processes that are disrupting social network services (SNSs).
Content curators are expected to continuously present appealing content in their social media posts, to
interact with their followers in a timely manner, and to encourage positive social facilitation behaviors
through online and offline channels.
Keywords: online content, social media, interactive engagement, social facilitation, real-time conversation, content attractiveness.
1
Department of Corporate Communication, Faculty of Media and Knowledge Sciences, University of Malta, Malta. Email:
mark.a.camilleri@um.edu.mt | https://orcid.org/0000-0003-1288-4256
2
The Business School, University of Edinburgh, Scotland.
3
Department of Advertising, School of Communication, Kadir Has University, Istanbul, Turkey.

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1. Introduction
Online users including businesses and organizations are increasingly subscribing to
different social networks services (SNSs), including Facebook, YouTube, Instagram, Twitter and
LinkedIn, among others. They are creating social media pages and groups to reach larger
audiences. SNSs allow them to raise awareness about products, services and causes. They enable
them to share online content including textual information, images, videos and hyperlink ([1],[2],
[3]).
At the same time, they can use them to engage in two-way conversations with their
followers, who may be consumers and prospects. Therefore, social media subscribers are expected
to dedicate their time to look after their account, to disseminate promotional content and to respond
to online users in a timely manner ([4],[5],[6]). The utilization of SNSs has radically influenced
the style of online communications and has altered the relationships among marketplace
stakeholders, between the businesses and their consumers as well as among customers and
prospects.
For instance, tourism marketers disseminate information about their travel services as well
as on their destinations’ attractions. They may usually feature a good selection of high-resolution
images and videos through the Internet ([7],[8],[9]). Very often, they are including testimonials
about tourist experiences ([10]). In many cases, online users are accessing and reading consumer
reviews and ratings before choosing which places to visit, to stay or to eat ([11]).
The information that is presented in SNSs can lure social media subscribers to engage in
online and offline word-of-mouth publicity with other individuals ([12],[13]). Moreover, the
attractiveness and appeal of interactive communications can have an impact on the individuals’
attitudes towards destinations and on their intentions to visit destinations ([14],[15],[16].

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Today, a number of tourism businesses and destination marketing organizations (DMOs)
are benefiting from the digital transformation of social media. SNSs are connecting social media
subscribers (that may include prospective tourists) to interactive websites and to other links that
display promotional content and information on various destinations ([17]). They promote tourist
attractions, points of interest as well as their amenities. The real time conversation capabilities of
the digital media can encourage online users to engage with other online users in public domains
([18],[19]). They could even motivate them to travel and to book their itineraries and hotel
accommodation ([20],[21]).
A relevant review from the marketing literature suggests that there are a number of studies
that investigated the individuals’ perceptions on the use of interactive websites like social media.
Many researchers reported that online users are experiencing their dynamic engagement facilities
([22],[23],[24],[25]).
SNSs facilitate instantaneous multi-directional flows of information. They enable
interactive communications that are conspicuous with a continuous exchange of information,
immediacy, responsiveness and user control functions such as participation and timely feedback
([26],[27]). DMOs and destination marketers are using these media to respond to online users to
assist them in their queries, in real-time. They are also utilizing social media to engage in online
conversations with prospective tourists and to encourage their followers to share their user-
generated content.
Past research explored the online users’ perceptions and attitudes on the use of social media
for destination marketing ([14],[15]). In many cases, commentators reported that SNSs enable
synchronous communications, concurrent engagement and facilitate real-time conversations that
are central to the concept of interactivity ([28],[29],[30]), and can affect the individuals’ attitudes

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([31],[32]) and intentions to use them ([33],[34],[35],[36]). Some academic authors sought to
understand their impact on the individuals’ intentions and behaviors, including on their word-of
mouth activities ([33],[34],[37]).
In this light, the researchers put forward a research model that hypothesizes that the
attractiveness of the online content ([38]) and the interactive capabilities of social media groups
([30]) can have significant effects on the individuals’ attitudes
([39]), intentions to use them ([31])
and social facilitation behaviors
([40]). This study differentiates itself from previous theoretical
underpinnings. To the best of the authors’ knowledge, there are no other studies in academia that
have integrated the same measures that were used in this research.
Notwithstanding, for the time being, there are limited studies in academia that shed light
on the antecedents of social facilitation behaviors through interactive channels or via offline
settings. Therefore, this research addresses this gap in the literature. This contribution clarifies that
SNSs that can ultimately foster positive social facilitation behaviors. It adds value to the relevant
academic literature that is focused on interactive social media content. In sum, it postulates that
social media communications compel subscribers to engage with appealing content (by using a
number of emojis to indicate their reactions and/or by cross posting) as well as with other
individuals including group administrators and other followers, who are involved in online
conversations.
2. The conceptual framework and the formulation of hypotheses
The theory of reasoned action (TRA), the theory of planned behavior (TPB) and the
technology acceptance model (TAM), among others, have often been used in different contexts to

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explore the individuals’ intentional behaviors to use various tourism technologies ([34],[35],[41];
[42]). Generally, these theoretical underpinnings suggest that the persons’ beliefs are linked
to their actions. For instance, the theory of reasoned action posits that the individuals’ positive
attitudes as well as the subjective norms and the influences from society, would have an effect on
their intentions and motivations to engage in certain behaviors ([43]).
Various studies that relied on TPB or TRA reported that the persons’ attitudes and
subjective norms are significant antecedents of behavioral intentions to visit destinations
([44],[45]). In a similar vein, TAM, also postulates that the individuals’ intentions are influenced
by their attitudes.
2.1 Attitudes and intentions
According to TRA, TAM and TPB, the individuals’ attitudes are a precursor of their behavioral
intentions ([46],[47],[48]). Their attitudes are considered as learned predispositions as persons tend
to respond in favorable or unfavorable ways towards given objects. Whilst, positive attitudes can
trigger intentional behaviors, negative attitudes could lead individuals to avoid certain activities.
Previous research in tourism also reported that the individuals’ attitudes may have a positive effect
on their intentions to travel ([36]), including during COVID-19 times ([49]).
A recent study reported that the online users’ attitudes toward SNSs and social media
advertisements predicted their purchase intentions ([50], [51]). Customers may usually have
positive attitudes toward co-creating content about their experiences in hotels, through social
media [52]. These authors confirmed that their favorable attitudes anticipated their intentions to
engage in co-creation behaviors in social media. Other contributions suggested that the
individuals’ attitudes were found to have a positive influence on their behavioral intentions to

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engage with blogs [53] or electronic government services [54] and/or to share information on SNSs
[55]. This study hypothesizes:
H1: The online users’ attitudes toward online content can affect their intentions to revisit
social media groups.
2.2 Social facilitation
Individuals may hold either positive or negative attitudes toward interactive websites like
SNSs. Hence, it is very likely that they communicate with others about their online browsing
experiences. They may use offline and/or online channels, including social media and review
websites to voice their opinions. Related research reported that the individuals’ attitudes towards
online information is one of the determinants for engaging in electronic word-of-mouth (eWOM)
through social media ([39],[56],[57].
Previous consumers’ transaction experiences and word-of-mouth activities can have an
effect on prospective customers’ trust and attitudes toward a given review website, thereby they
may increase or decrease their chances of revisiting it again in the future [31]. Although individuals
may hold favorable attitudes towards the businesses’ communications through social media, they
may still decide to refrain from making reference to them (with family or friends) or to spread
positive word of mouth publicity about them.
Individuals may be facilitated to communicate about businesses or on other issues, in the
presence of others ([40],[58]). On the other hand, they may feel inhibited by the same audience
([59]). These arguments are synonymous with the social facilitation phenomenon that is
conspicuous in social networks. In plain words, individuals may be intrigued to use emojis in social

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media, or to share comments if there are a number of other online followers who are also engaging
with the social media page and its posts ([33]).
Relevant theoretical underpinnings reported that social facilitation in service interactions
([60]) and in interactive websites ([61]) can encourage individuals to engage in conversations with
others. In sum, the term ‘social facilitation’ suggests that individuals would act differently in the
presence of others ([62]). The cocreation of online content is a good example of interactions among
customers, service firms and technology, that is usually triggered by positive social facilitation
([52]). Therefore, a responsive audience in social media may attract online users who are willing
to share their experiences with others [63]. This leads to the following hypothesis:
H2: The online users’ attitudes toward online content can affect their social facilitation
behaviors.
2.3 Content attractiveness
The design, structure and layout of online content may attract or detract the attention of
individuals ([64], [65]). Online users simply decide to switch to other domains if the content does
not appeal to them ([66]). For instance, the posts that are disseminated through social media may
link subscribers to specific websites with legible content that is easy-to-read and comprehend.
These sites may use appropriate fonts and high-contrast buttons
that feature clear calls-to-action.
These features are meant to enhance the online visitors’ experiences.
This research postulates that the attractiveness of social media posts refers to the degree to
which one perceives that their content is visually or aesthetically appealing ([38]). Such posts may
elicit positive emotions and may be considered as socially desirable in terms of source

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attractiveness and credibility, thereby resulting in a high number of followers ([67]). This
argumentation is also synonymous with theoretical underpinnings relating to electronic service
quality (eSERVQUAL) ([68]) and/or to electronic retail quality (eTailQ) ([38],[69]), among
others.
The administrators of social media groups and/or their influencers may decide to create
and disseminate informative updates to lure online followers to like posts, to engage in online
conversations, or to share them through their profile ([70],[71]). Source attractiveness can possibly
generate considerable attention from the part of the audience, who may be willing to like and
accept the communicators’ messages ([72]), in the presence of other online users ([33],[40]). This
leads to the following hypothesis:
H3: The attractiveness of online content can affect the individuals’ social facilitation
behaviors.
Different individuals will probably hold varying attitudes and perceptions on the attributes
of attractive websites, including images, animations and video clips, that can be shared via social
media posts. To date, a few studies relating to the service dominant logic, have explored the effects
of attractive content that is featured in social media groups on their subscribers’ attitudes and
re/visit intentions ([33]). The usefulness of their information can influence their positive attitudes
toward online content and can also lead them to purchase travel services ([73]). Previous research
indicated that the content that is disseminated through social media by subscribers (i.e. user
generated content) and by marketers (i.e. firm created content) were found to positively impact
brand attitudes and purchase intentions across different brands ([50],[51]). The attractiveness of

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online content including their images and videos may entice online users to revisit them again in
the future ([38],[67]). This leads to the following hypotheses:
H4: The attractiveness of online content can affect the individuals’ attitudes toward online
content.
H5: The attractiveness of online content can affect the individuals’ intentions to revisit
social media group.
2.4 Real-time conversation
Many academic authors have presented different definitions about the interactivity of
websites ([30], [74]). In this case, interactivity refers to the SNSs’ features that enable two-way
communications, more specifically, to their real-time conversation capabilities among two or more
individuals ([21]). This line of reasoning is related to the degree to which online users feel in
control to communicate synchronously and reciprocally with one another through interactive
media ([75],[76]). The online users’ engagement may not be regular and consistent across various
digital networks ([77]). They may appreciate different aspects of social media, including their
responsiveness, timely feedback and the time required for information retrieval. In fact, interactive
websites like SNSs offer simultaneous, synchronous, and a continuous exchange of information.
They are responsive to their visitors’ needs; hence they may find them useful and helpful ([77]).
Online users may be interested in SNSs as they allow them to engage in interactive
communications with other individuals ([43]). A number of studies have shown that there is a
positive psychological outcome from using SNSs ([78],[79]). Subscribers may be intrigued to join
online conversations that are featured in social media groups because they attracted by their
informative and/or entertaining content. This argumentation leads to the following hypothesis:

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H6: The attractiveness of online content can affect the individuals’ real-time conversations
in social media.
Some interactive posts can trigger positive reactions including two-way communications
from social media users ([80], [81]). The ‘social support’ and the ‘sense of community’ are two of
the main factors that can lead to member satisfaction with regard to their interactive engagement
through SNSs ([82],[83]). Individuals can access information through the Internet or via social
media and use it in their interactive conversations. They may be facilitated to share online content,
because of specific social settings ([72]). A responsive audience in social media may encourage
online users to communicate with others [63]. Conversely, the presence of a passive audience
could inhibit individuals from sharing their comments or reviews [62]. This leads to the following
hypothesis:
H7: The individuals’ real-time conversations in social media can affect their social
facilitation behaviors.
The online users’ satisfaction with SNSs and their fulfilment experiences may motivate
them to continue using their technologies ([80]). Many academic researchers reported that the real-
time conversation capabilities of social media can have a positive effect on their users’ attitudes
([84]). Their two-way communications’ attributes may result in significant effects on the
individuals’ intentions to revisit them again in future ([84],[85]). This leads to the following
hypotheses:
H8: The individuals’ real-time conversation in social media can affect their attitudes
toward online content.

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H9: The individuals’ real-time conversation in social media can affect their intentions to
revisit social media groups.
2.5 Engaging content
Interactive engagement involves an interchange of information and responsiveness
between two or more online users, that are not necessarily in real-time ([24],[74],[86]). The
individuals’ perceptions about the interactivity of websites can be based on their experiences with
their processes and features ([30]). The websites’ interactivity is related to their media richness
([77]). The authors went on to suggest that the individuals’ perceptions about the richness of
engaging content is an important antecedent of their perceived usefulness of information. For
example, promotional images and videos of tourist attractions can influence the consumers’
perceptions about destinations ([87],[88]).
Many companies, including travel and tourism businesses as well as DMOs are
increasingly using interactive websites as well as social media groups, as they help them raise
awareness about their services ([89]). Marketers create and share attractive content through the
digital media, to entertain their visitors, in different contexts ([88]). Hence, they often feature a
good selection of images and videos to entice prospective travelers to become familiar with their
tourism product or destinations ([90]). Their interactive content should load as quickly as possible.
Any delays in the responsiveness of content curators of even a couple of seconds would have a
negative effect on the site visitors’ likes, comments and shares in social media ([91]), and on their
likelihood to be affected by social facilitation. Conversely, online users may decide to switch to
an alternative domains or social media groups, if they perceive that the content is not engaging
enough for them ([74]). This leads to the following hypotheses:

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H10: Engaging content can affect the individuals’ real-time conversation in social media.
H11: Engaging content can affect the individuals’ social facilitation behaviors.
The engaging content is intended to provide a better online experience ([92]). The
individuals’ perceptions about engaging content are based on the unique characteristics of online
websites including SNSs, in terms of their functionalities, interface, and content. Consumers
voluntarily and intentionally engage in online relationships with businesses and brands through
social media ([93], [94]). On the other hand, marketers engage with consumers to facilitate
relational exchanges to shape consumer behaviors ([95]). An increased engagement with online
users through social media sites can have a positive effect on their attitudes as well as on their
intentions to use them again in the future ([29]). This leads to the following hypotheses:
H12: Engaging content can affect the individuals’ attitudes toward online content.
H13: Engaging content can affect the individuals’ intentions to revisit social media groups.
Figure 1 features a graphical illustration of the formulated hypotheses.

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Figure 1. The research model featuring the online users’ interactive engagement with social
media pages or groups
3 Methodology
A structured electronic questionnaire was disseminated through three Facebook (Meta)
groups that are focused on the marketing of tourist destinations. At the time of this research, there
were more than 174,000 subscribers who were following these groups. The targeted respondents

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were kindly requested to participate in an academic study that sought to investigate the interactive
features of social media groups. The online survey instrument adhered to the European General
Data Protection Regulation (GDPR) as the participants’ identities remained anonymous and
confidential.
The questionnaires’ items were presented in a such a way to minimize the effects of
common method bias ([96]). The survey was pilot tested with a small group of experienced
colleagues, to identify any possible weaknesses in the survey instrument. Although, the survey
relied on valid measures that were tried and tested in academia, the questions were adapted to the
target audiences who were interested in travel destinations.
The questionnaire featured 18 questions that were drawn from previous empirical studies
that were focused on the adoption of digital media in various contexts. The responses were coded
on a 5-point Likert scale, where 1 = strongly disagree and 5 = strongly agree. They have been used
by a number of authors who confirmed their reliability and validity values when they published
their findings in rigorous peer-reviewed journals.
Specifically, this research comprised the following constructs: ‘attractiveness of online
content’ ([38]), ‘real-time conversation’ ([30]), ‘engaging content’ ([30]), ‘attitudes towards online
information’ ([39],[56]), ‘intention to revisit social media groups’ ([31], [46]) and ‘social
facilitation’ ([40]). The measures their corresponding items are illustrated in Table 1. The survey
included two demographic variables, namely, age and gender that were placed in the latter part of
the survey.

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Table 1. The survey’s measures
Construct Items
Attractiveness of online
content
(Wolfinbarger and Gilly, 2003)
AOC1
AOC2
AOC3
The content of the travel destination’s social media
groups is visually appealing.
I like browsing through the images and videos of
travel destinations through social media groups.
I enjoy following the posts of travel destinations in
their social media
groups
.
Real-time conversation RTC1 The travel destinations’ social media groups enable
two
-
way communications.
(Mc Millan and Hwang, 2002)
RTC2 The travel destinations’ social media groups are
interactive.
RTC3 The travel destinations’ social media groups enable
interpersonal
communications
.
Engaging Content ENG1 The travel destinations’ social media groups offer a
variety of content.
(Mc Millan and Hwang, 2002)
ENG2 The travel destinations’ social media groups keep
my attention.
ENG3 The travel destinations’ social media groups
provide
immediate answers to my questions.
Attitudes toward online
information
ATT1 I check the travel destinations’ social media groups
before purchasing my itinerary.
ATT2 The travel destinations’ social media groups are
helpful for my decision
making.
(Erkan and Evans, 2016) ATT3 The travel destinations’ social media groups make
me confident about purchasing my tourism
products.
Intention to revisit social
media page
INT1 It is very likely that I will return to the travel
destinations’ social media groups, sometime in the
near future.
(Che et al., 2015; Ajzen, 1991) INT2 I look forward to revisiting the travel destinations’
social media groups.
Social facilitation
SF1 I bring up things I have seen on social media
groups
in conversations with many other people.
(Calder et al., 2009) SF2 I talk about the content that is featured in social
media groups.

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The response rate represented around 5% of the targeted research participants as there were
nine hundred thirty-one (931) responses after two weeks since the dissemination of the electronic
survey instrument through Google Forms. The researchers discarded 8 questionnaires that had
several missing values. As a result, this empirical study is based on nine hundred twenty-three
(923) responses. The frequency table reported that there were five hundred twenty-seven females
(n=527) and three hundred ninety-six males (n=396) who took part in this research. The
respondents were categorized into five (5) age groups (18-28; 29-39; 40-50; 51-61 and over 62
years of age). In sum, the largest group of respondents were between 29 and 39 years of age
(n=439), followed by those between 40 and 50 years of age (n=221).
4 Data analysis
4.1 Descriptive statistics
The researchers evaluated the mean (M) scores and the standard deviations (SD). The
findings indicated that the research participants agreed with the survey’s items, as evidenced by
their high attitudinal scores that were above three (3). The highest mean (M) scores were reported
for ENG3 (M=3.94), AOC3 (M=3.89) and SF2 (M=3.83). RTC2 recorded the lowest mean score
(M=3.15). The standard deviation (SD) values suggested that there were low variances in the
participants’ responses. SD varied from 0.650 (for ATT3) to 0.993 (for ENG3). Table 2 features
the descriptive statistics, as well as the results of the outer loadings, construct reliability and
validity of this research model.

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Table 2. An assessment of outer loadings, construct reliability and validity
Items Mean SD Outer
Loadings Alpha rho_A CR AVE 1 2 3 4 5 6
1
Attractiveness of
online content
AOC1 3.74
0.844
0.89
0.863 0.865 0.917 0.786 0.886 AOC2 3.532
0.877
0.901
AOC3 3.896
0.714
0.867
2
Attitudes toward
online content
ATT1 3.792
0.828
0.849
0.856 0.857 0.912 0.777 0.849 0.881 ATT2 3.74
0.78
0.923
ATT3 3.688
0.65
0.871
3 Engaging content
ENG1 3.844
0.869
0.916
0.893 0.894 0.934 0.824 0.82 0.83 0.908 ENG2 3.728
0.784
0.917
ENG3 3.948
0.993
0.89
4 Intention to revisit
social media page
INT1
3.676
0.973
0.929
0.785 0.819 0.902 0.821 0.81 0.8 0.865 0.906
INT2
3.636
0.805
0.882
5 Real-time
conversation
RTC1 3.532
0.749
0.891
0.803 0.86 0.881 0.712 0.751 0.778 0.749 0.721 0.844 RTC2 3.156
0.666
0.896
RTC3 3.532
0.499
0.734
6 Social facilitation SF1 3.728
0.907
0.937
0.854 0.855 0.932 0.872 0.754 0.797 0.807 0.809 0.692 0.934
SF2 3.832
0.874
0.931
Note: The discriminant validity was calculated by using the Fornell-Larcker criterion. The square roots of AVE (in bold) were greater than the correlations that were
featured in the same column.

2
4.2 The composite-based analysis of the structured model
A partial least squares (PLS) confirmatory composite analysis was used to assess the
validity and reliability of the measures and to evaluate the quality of this structured model
([97]). The PLS algorithm shed light on the results of standardized loadings. It confirmed that the
constructs were reliable. Alpha, Rho_A and composite reliability values were higher than the
recommended threshold of 0.7. The findings also reported the convergent validity of the
constructs. The average variance extracted (AVE) values were well above the 0.5 benchmark. In
addition, the results indicated appropriate discriminant validity values. The square root value of
AVE was greater than the correlation values among the other variables in the same columns ([98]).
The findings confirmed that there were no collinearity issues in this proposed research model as
the variance inflation factors (VIFs) did not exceed 3.3. PLS illustrated the model’s coefficients of
determination (R
2
).
A bootstrapping procedure reported the statistical significance of the hypothesized
relationships. It reaffirmed the relevance of the path coefficients that were present in this model.
Table 3 features the results from the original sample, the confidence intervals, t-statistics
and the significance values (p). Table 4 provides a summary of the accepted/rejected hypotheses.

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Table 3. Testing of the Hypotheses
Path Coefficient Original Sample CI Bias
Corrected t-value p Decision
Sample Mean [2.5%,97.5%]
H1 Attitudes toward online content -> Intention to revisit social media group 0.232 0.231 [0.163, 0.294] 7.154 0.000 Supported***
H2 Attitudes toward online content -> Social facilitation 0.068 0.068
[0.001, 0.143]
1.898 0.058 Not Supported.
H3 Attractiveness of online content -> Social facilitation 0.341 0.341
[0.292, 0.399]
11.6 0.000 Supported***
H4 Attractiveness of online content -> Attitudes toward online content 0.464 0.463
[0.396, 0.539]
12.42 0.000 Supported***
H5 Attractiveness of online content -> Intention to revisit social media group 0.164 0.166
[0.104, 0.220]
5.464 0.000 Supported***
H6 Attractiveness of online content -> Real-time conversation 0.517 0.517
[0.444, 0.583]
14.51 0.000 Supported***
H7 Real-time conversation -> Social facilitation 0.059 0.058
[0.013, 0.105]
2.455 0.014 Supported *
H8 Real-time conversation -> Attitudes toward online content 0.144 0.145
[0.101, 0.189]
6.333 0.000 Supported***
H9 Real-time conversation -> Intention to revisit social media group 0.034 0.033
[
-
0.014, 0.086]
1.329 0.184 Not Supported.
H10 Engaging content -> Real-time conversation 0.324 0.324
[0.258, 0.394]
9.172 0.000 Supported***
H11 Engaging content -> Social facilitation 0.429 0.43
[0.334, 0.509]
9.813 0.000 Supported***
H12 Engaging content -> Attitudes toward online content 0.331 0.332
[0.266, 0.393]
10.52 0.000 Supported***
H13 Engaging content -> Intention to revisit social media group 0.516 0.516
[0.466, 0.562]
21.33 0.000 Supported***
Note
: Critical values are
:
t < 1.96; ***
p
< 0.0
0
1, ** p < 0.01, * p < 0.05.

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Table 4. A summary of accepted/rejected hypotheses
H1 Attitudes toward online content -> Intention to revisit social media page Supported***
H2 Attitudes toward online content -> Social facilitation Not Supported.
H3 Attractiveness of online content -> Social facilitation Supported***
H4 Attractiveness of online content -> Attitudes toward online content Supported***
H5 Attractiveness of online content -> Intention to revisit social media page Supported***
H6 Attractiveness of online content -> Real-time conversation Supported***
H7 Real-time conversation -> Social facilitation Supported *
H8 Real-time conversation -> Attitudes toward online content Supported***
H9 Real-time conversation -> Intention to revisit social media page Not Supported.
H10 Engaging content -> Real-time conversation Supported***
H11 Engaging content -> Social facilitation Supported***
H12 Engaging content -> Attitudes toward online content Supported***
H13 Engaging content -> Intention to revisit social media page Supported***
Note: Critical values are: *** p < 0.001, ** p < 0.01, * p < 0.05.

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4.3
Discussion of the results
Generally speaking, the results provide sufficient empirical evidence to support the
majority of hypotheses. H1: This study suggests that the individuals’ attitudes toward online
content have a highly significant effect on their intention to revisit the social media groups (
β
=
0.232, p < 0.001, t = 7.154). H2: The findings indicate that their attitudes towards online content
have a negligible effect on social facilitation (
β
= 0.068, p < 0.1, t = 1.898). H3: The empirical
evidence confirms a strong direct effect between content attractiveness and social facilitation (
β
=
0.341, p < 0.001, t = 11.6). H4: The results confirm that there is a highly significant effect between
the attractiveness of online content and attitudes toward online content (
β
= 0.464, p < 0.001, t =
12.42). H5: The attractiveness of online content is also a precursor of the participants’ intentions
to revisit the social media page (
β
= 0.164, p < 0.001, t = 5.464). H6: Furthermore, this study
reports that the attractiveness of online content has a very high effect on the individuals’ real-time
conversations through social media (
β
= 0.517, p < 0.001, t = 14.51).
H7: Unlike what was proposed in the literature review, the results suggest that there is a
weak relationship between real-time conversations and social facilitation (
β
= 0.059, p < 0.05, t=
2.455). On the other hand, the findings provide sufficient evidence to empirically justify H8,
meaning that real-time conversations are a significant precursor of the respondents’ attitudes
toward online content (
β
= 0.144, p < 0.001, t = 6.333). The empirical evidence is insufficient to
support H9 as there is no significant effect between real-time conversation and the online users’
intentions to revisit the social media page. H10: However, the findings indicate that there are
highly significant relationships between engaging content and real-time conversation (
β
= 0.324,
p < 0.001, t = 9.172); H11: between engaging content and social facilitation (
β
= 0.429, p < 0.001,

6
t = 9.813); and H12: between engaging content and attitudes toward online content (
β
= 0.331, p
< 0.001, t = 10.52). H13: Interestingly, the results confirm that engaging content is a highly
significant antecedent of the online users’ intentions to revisit the social media page (
β
= 0.516, p
< 0.001, t = 21.33).
The research participants’ intentions to revisit social media page has the highest level of
explanatory power (where R
2
= 0.794) in this research model. The results suggest that while their
attitudes toward online content (R
2
= 0.774) as well as their dispositions for social facilitation (R
2
= 0.711) have substantial explanatory power, the findings indicate that real-time conversations
have a moderate level of explanatory (R
2
= 0.647). Figure 2 illustrates the total effects and the
coefficients of determination (R
2
) values. Table 5 sheds light on the results of the mediation
analyses. Table 6 features a summary of results of the indirect effects within our research model

7
Figure 2. A graphical illustration of the results

8
Table 5. The Mediated Analyses
CI Bias Corrected
Path Coefficient Direct Indirect
1
Indirect
2
Indirect
3 p Interpretation Total
[2.5%, 97.5%] t-
value p
H3 Attractiveness of online content ->
Social facilitation
0.341 0.000
0.408 [0.356, 0.467] 13.829
0.000
H3a
Attractiveness of online content ->
Attitudes toward online content ->
Social facilitation
0.032 0.047 Partial mediation
H3b
Attractiveness of online content ->
Real-time conversation -> Social
facilitation
0.03 0.016 Partial mediation
H3c
Attractiveness of online content ->
Real-time conversation -> Attitudes
toward online content -> Social
facilitation
0.005 0.122 No mediation
H4 Attractiveness of online content ->
Attitudes
toward online content
0.464 0.000
0.539 [0.477, 0.603] 16.738
0.000
H4a
Attractiveness of online content ->
Real-time conversation -> Attitudes
toward online content
0.075 0.000 Partial mediation
H5
Attractiveness of online content ->
Intention to revisit social media
page
0.164 0.000
0.306 [0.251, 0.353] 11.894
0.000
H5a
Attractiveness of online content ->
Real-time conversation -> Intention
to revisit social media page
0.017 0.194 No mediation
H5b
Attractiveness of online content ->
Attitudes toward online content ->
Intention to revisit social media
page
0.108 0.000 Partial mediation
H5c
Attractiveness of online content ->
Real-time conversation -> Attitudes
toward online content -> Intention
to revisit social media page
0.017 0.000 Partial mediation

9
H7 Real-time conversation -> Social
facilitation
0.059 0.014
0.069 [0.021, 0.122] 2.626 0.009
H7a
Real-time conversation -> Attitudes
toward online content -> Social
facilitation
0.01 0.114 No mediation
H9 Real-time conversation -> Intention
to revisit social media page
0.034 0.184
0.067 [0.018, 0.111] 2.779 0.006
H9a
Real-time conversation -> Attitudes
toward online content -> Intention
to revisit social media page
0.033 0.000 Full mediation
H11 Engaging content -> Social
facilitation
0.429 0.000
0.474 [0.404, 0.532] 14.554
0.000
H11a Engaging content -> Real-time
conversation
-
> Social facilitation
0.019 0.018 Partial mediation
H11b
Engaging content -> Attitudes
toward online content -> Social
facilitation
0.023 0.069 No mediation
H11c
Engaging content -> Real-time
conversation -> Attitudes toward
online content
-
> Social facilitation
0.003 0.117 No mediation
H12 Engaging content -> Attitudes
toward online content
0.331 0.000
0.378 [0.304, 0.440] 11.121
0.000
H12a
Engaging content -> Real-time
conversation -> Attitudes toward
online content
0.047 0.000 Partial mediation
H13 Engaging content -> Intention to
revisit social media page
0.516 0.000
0.615 [0.564, 0.664] 24.189
0.000
H13a
Engaging content -> Real-time
conversation -> Intention to revisit
social media page
0.011 0.180 No mediation
H13b
Engaging content -> Attitudes
toward online content -> Intention
to revisit social media page
0.077 0.000 Partial mediation

10
H13c
Engaging content -> Real-time
conversation -> Attitudes toward
online content -> Intention to revisit
social media page
0.011 0.000 Partial mediation
Table 6. A summary of accepted/rejected hypotheses
H1 Attitudes toward online content -> Intention to revisit social media page Supported***
H2 Attitudes toward online content -> Social facilitation Not Supported.
H3 Attractiveness of online content -> Social facilitation Supported***
H4 Attractiveness of online content -> Attitudes toward online content Supported***
H5 Attractiveness of online content -> Intention to revisit social media page Supported***
H6 Attractiveness of online content -> Real-time conversation Supported***
H7 Real-time conversation -> Social facilitation Supported **
H8 Real-time conversation -> Attitudes toward online content Supported***
H9 Real-time conversation -> Intention to revisit social media page Not Supported.
H10 Engaging content -> Real-time conversation Supported***
H11 Engaging content -> Social facilitation Supported***
H12 Engaging content -> Attitudes toward online content Supported***
H13 Engaging content -> Intention to revisit social media page Supported***
Note: Critical values are: *** p < 0.001, ** p < 0.01, * p < 0.05.

11
5.
Conclusions and implications
This study builds on previous academic knowledge on the acceptance and use of social
media groups. It relied on valid constructs that were drawn from TRA, TPB and TAM, as the
proposed research model comprised “attitudes toward technology” and “behavioral intentions”
constructs. However, it integrated them with perceived interactivity constructs, including “real-
time conversation” and “engaging” as well as with “content attractiveness” from eTailQ.
This empirical investigation clarifies that the content attractiveness of social media posts
as well as their engaging content and real-time conversation capabilities, can have significant
effects on social facilitation behaviors of individuals, and on their intentions to revisit social media
groups. The findings from this study reiterate the importance of continuously creating relevant
content that appeals to social media followers.
Previous research posited that online users should keep their followers engaged through
rich media ([77]). Other theoretical underpinnings reported that interactive websites, particularly
social media and video sharing platforms, can offer great potential to DMOs to promote tourism
and hospitality services ([88]). Internet domains can showcase a wide array of high-res images
and video clips to lure online users to book their travel itineraries to visit destinations ([90]). The
digital media and mobile applications (app) ought to be as functional and responsive as possible
([99]). They should load quickly without delays to reduce the likelihood of dissatisfied visitors,
who can easily switch to another website or app ([74]).
In this case, the results suggest that there are very significant effects between the online
users’ perceptions about engaging content and their intentional behaviors to check out the social
media pages (on a regular basis); and between their perceptions about engaging content and their
social facilitation dispositions to communicate about social media groups through online and

12
offline channels, in the presence of others. The respondents are appreciating the attractive content,
including images or videos, that are disseminated through the social media groups’ posts.
Moreover, the findings indicate that they hold positive perceptions about the co-creation of user
generated content. Evidently, the exchange of information as well as the responsiveness between
two or more online users was leading them to revisit the social media groups.
This study is consistent with the relevant literature that sought to explore the online users’
perceptions about the websites’ interactivity features ([30], [34]). Other researchers maintained
that real-time conversations had a positive effect on the online users’ attitudes toward engaging
websites ([84]). In this case, this argumentation holds for social media groups, as well.
This contribution underlines the importance of posting engaging content including
appealing images and videos through social media. It clearly indicates that interactive content as
well as the social networks’ real-time conversation capabilities can foster positive social
facilitation behaviors. Arguably, individuals are interested and intrigued to interact with other
online users through popular social media groups in the presence of other members. They are likely
to join in online discussions and conversations in prolific social media groups, particularly in those
that are regularly disseminating attractive content, and in those that facilitate interactive
engagement among their members.
The cocreation of user generated content in social media, blogs and review sites is driven
by online audiences. This study confirms that the relevance and attractiveness of social media
content can have a positive effect on triggering real-time conversations as well as on social
facilitation. This reasoning is consistent with the social facilitation theory ([33],[40],[60],[61]).
This research corroborates that while the presence of other individuals can increase the likelihood

13
of social engagement, a passive audience may inhibit them from sharing their comments about the
attractiveness of interactive content.
The findings of this research also yield plausible implications to practitioners. The
researchers indicate that social media subscribers are attracted by the online content that is being
posted by DMOs and travel marketers. Online users and prospective travelers are increasingly
browsing through interactive content including images and videos of travel destinations. The social
media groups are offering a variety of multimedia content that is appealing to online users. Very
often, they allow their followers to engage in two-way communications, as members can comment
on posts and may also interact with other online users, in real-time. This study suggests that the
research participants are visiting the social media groups as they considered them as helpful for
their decision making, prior to booking their travel itineraries. Apparently, they were intrigued to
revisit these groups and were likely to communicate about their content with other people through
offline and online channels, as it appealed to them and captured their attention.
Therefore, travel marketers ought to focus on publishing quality content. This increases
the chances of their engagement. Prospective travelers are attracted by multi-media features
including high-res images with zooming effects and video content; that are adapted for mobile
technologies, including tablets and smartphone devices. Travel marketers and DMOs ought to
curate their social media group(s) with appealing content to raise awareness about their tourism
products. It is in their interest to share relevant and attractive material to increase the number of
followers and their engagement. More importantly, they are expected to interact with online users,
in a timely manner, to turn them into brand advocates and to encourage social facilitation
behaviors.

14
In sum, this empirical research clarifies that the attractiveness of online content of social
media groups, including their images and videos of destinations, as well as their interactive and
real-time conversation capabilities are affecting their subscribers’ revisit intentions. They are also
influencing their social facilitation behaviors - in the presence of others. This study raises
awareness on the importance of sharing engaging content and of encouraging interactive
discussions among social media subscribers. The researchers contend that content creators can lure
individuals to visit and revisit their social media pages/groups to generate leads and conversions.
Arguably, the more engagement (e.g. through emojis and shares) and conversations (e.g.
comments), the greater the chances of captivating the attention of existing followers and of enticing
the curiosity of new ones. For the time being, the social facilitation paradigm is still relatively
under-explored in academia, particularly within the travel and tourism marketing literature.
Future researchers are encouraged replicate this study in different contexts. They may adapt
the measures that were used in this research, including engaging content, real time conversation
and social facilitation constructs, in addition to other popular constructs that are drawn from TRA,
TPB and TAM. They may include other constructs in their research models, including those
relating to psychological theories that can clarify their motivations to engage with other individuals
through such digital channels. Further research could focus on the demographic backgrounds of
their respondents to better understand who, why, when and where they are engaging with other
users through social media groups. Perhaps, there is scope for other studies to employ different
sampling frames and methodologies, including inductive ones, to explore this topic in more depth
and breadth.

15
Acknowledgements
This research was funded through the University of Malta’s academic work resources.
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