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Utilitarian motivations to engage with travel websites: An interactive technology adoption model
By Mark Anthony Camilleri, University of Malta, Malta; University of Edinburgh, United Kingdom and
Northwestern University, United States of America.
AND
Metin Kozak, Kadir Has University, Turkey.
Suggested Citation: Camilleri, M.A. & Kozak, M. (2022). Utilitarian motivations to engage with travel websites:
An interactive technology adoption model. Journal of Services Marketing,
https://doi.org/10.1108/JSM-12-2021-0477
This is a prepublication version.
Purpose: This study aims to investigate perceptions about interactive travel websites. The researchers hypothesize
that engaging content, the quality of information and source credibility has a significant effect on the consumers’
utilitarian motivations to continue using them in the future.
Design/methodology/approach: A structured survey questionnaire was used to gather data from 1,287 online users,
who were members of two popular social media groups. The methodology relied on a partial least squares (PLS)
approach to analyze the causal relationships within an extended information adoption model.
Findings: The findings reveal that the research participants perceive the utility of interactive travel websites and
are willing to continue using them, particularly the responsive ones. The research participants suggest that these
sites are easy-to-use, capture their attention, and offer them useful information on various tourism services. The
results also indicate that they appreciate their source credibility (in terms of their trustworthiness and expertise of
their curators) as well as their quality content.
Research limitations/Implications: This study integrates key measures from the information adoption model
(IAM) with a perceived interactivity construct, to better understand the individuals’ acceptance and use of interactive
websites.
Practical implications: This research implies that service businesses ought to have engaging websites that respond
to consumer queries, in a timely manner. Hence, they should offer a seamless experience to their visitors to
encourage loyal behaviors and revisit intentions to their online domains.
Originality: To the best of our knowledge, there are no other studies that incorporated an interactive engagement
construct with key constructs from IAM and from the technology acceptance model (TAM). This contribution
underlines the importance of measuring the individuals’ perceptions about the engagement capabilities of interactive
media when investigating information and/or technology adoption.
Keywords: information quality; source credibility; interactive engagement; information adoption model;
technology acceptance model; consumer experience.
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1. Introduction
Previous research sought to identify the factors affecting the consumers’ perceptions about the
service quality of websites (Donthu et al., 2021; Klaus and Zaichkowsky, 2020; Zeithaml et al., 2002), in
terms of the attractiveness and appeal of their designs (Li et al., 2017), functionality (Rosenmayer et al.,
2018) and/or degree of user friendliness (Liu et al., 2013). Very often, the contributing authors shed light
on the websites’ reliability, safety or security, as well as on their responsiveness, as customers expect
websites to deliver an appropriate level of personalized electronic services (Camilleri, 2021; Nguyen et
al., 2018; Valtakoski, 2019). Online users are continuously evaluating the attributes and features of
electronic commerce websites (Klaus and Zaichkowsky, 2020; Zaki, 2019), before committing themselves
to a purchase decision.
Many commentators suggest that corporate websites can offer high levels of customer services
during and after sales transactions, as they are a useful tool to compare prices, to purchase services, and to
communicate with the service providers (e.g. to request refunds or to voice complaints). These service
technologies are equipped with consumer-centered, self-service applications (Lee et al., 2020; Wilkinson
et al., 2021). Very often, these technologies may direct their visitors to frequently-answered-questions
(FAQs), so that they can search for answers for themselves. Some of them are also offering Live Chat
services that may be operated by human agents and/or through artificially intelligent (AI)
chatbots/dialogue systems (Adam et al., 2021; Camilleri & Troise, 2022; Thomaz et al., 2020; Tsai, et al.,
2021). The latter software can respond to consumers’ queries in real time, via social media networks
(SNSs) including Facebook Messenger or WhatsApp, among others (Smutny and Schreiberova, 2020).
Therefore, consumers may be expected to use electronic service technologies including interactive
websites and/or AI-operated assistants, to resolve their service issues (Adam et al., 2021; Crolic et al.,
2021; Pantano and Pizzi, 2020).
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Arguably, there is scope for businesses to use service technologies, especially when and if they
experience a sudden influx in customer issues, during popular times of the day and in specific periods of
the year. Recently, service businesses were expected to deal with unprecedented changes in their marketing
environment (Kabadayi et al., 2020; Rosenbaum and Russell-Bennett, 2020). The outbreak of the
Coronavirus (COVID-19) pandemic has disrupted the travel itineraries of millions of consumers. Many
tourism businesses received higher volumes of telephone calls and/or online inquiries through different
digital media. During COVID-19, customers changed their bookings, cancelled their itineraries and/or
submitted refund requests to service providers. Such contingent situations have inevitably led to
inconvenience, extreme waiting times and inefficient service quality.
Previous studies investigated the online users’ perceptions toward a wide array of service
technologies (Donthu et al., 2021; Kabadayi et al., 2020; Klaus and Zaichkowsky, 2020; Rosenmayer et
al., 2018). Frequently, they employed the electronic service quality (e-SQ or e-SERVQUAL), electronic
retail quality (eTailQ), transaction process-based approaches to evaluate service quality (eTransQual), net
quality (NETQual), perceived electronic service quality (PeSQ), site quality (SITEQUAL) and website
quality (webQual), among other research models. Most of these conceptual models, including e-
SERVQUAL’s key constructs were utilized to examine the consumers’ satisfaction levels with electronic
websites. One may argue that the websites’ designs, ease of use, reliability, security and responsiveness,
among other factors, can be associated with key theoretical underpinnings related to the perceived
interactivity construct (McMillan and Hwang, 2002).
A number of colleagues elaborated on the engagement capabilities of various technologies,
including of social media networks (Lin and Chang, 2018; Vrontis et al., 2021), review websites (Liu et
al., 2022), crowdfunding platforms (Camilleri and Bresciani, 2022), AI chatbots (Camilleri & Triose,
2022), augmented and virtual reality devices (Park and Yoo, 2020; Serravalle et al., 2019), metaverse
applications (Gursoy et al., 2022), et cetera. In many cases, they clarified that these digital technologies
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enable two-way communications as they facilitate person-to-person and/or person-to-machine
communications, as opposed to traditional, one-way broadcast channels like linear TV, radio or print
media, that do not offer responsive messages to their consumers. Conversely, most websites (particularly
ecommerce websites) are increasingly offering interactive elements like personalization and customization
options that are integrated in search engines, online consumer reviews, FAQs as well as concurrent live
chat facilities, among other widgets. Therefore, consumers will probably hold perceptions about the
functionalities and interactivity features of certain websites (including travel websites), in terms of their
appealing content, ease-of-use (or user control) and degree of responsiveness (in a timely manner).
1.1 Research questions
Service marketing researchers have frequently explored the customer-brand engagement through
different digital media. In many cases, they sought to clarify whether online interactions led to increased
purchases and/or to positive reviews and ratings (Kim et al., 2020; Kumar, 2013). A number of studies
indicated that online consumer-brand engagement or interactive engagement increases customer
satisfaction, trust, commitment, loyalty and profitability, among other positive outcomes (Ashley and
Tuten, 2015; Brodie, et al., 2013; Tsai et al., 2021). Most contributions suggest that consumers perceive
the usefulness of interactive websites, and thus may be willing to revisit them again in the future (Bravo
et al. 2021; Camilleri, 2019; Oliveira et al., 2020).
This research integrates measures from Davis et al.’s (1989) technology adoption model (TAM),
namely, perceived usefulness and behavioral intentions with one of McMillan and Hwang’s (2002)
perceived interactivity construct, they referred to as an ‘engaging’ construct; with information quality and
source credibility from Sussman and Siegal’s (2003) information adoption model (IAM) or from Petty and
Cacioppo’s (1986) elaboration likelihood model (ELM). In sum, it presumes that the websites’ engaging
attributes and features (Kim et al., 2020; McMillan and Hwang, 2002), as well as the quality and credibility
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of their online content (Cheung et al., 2008; Filieri and McLeay, 2014; Leong et al., 2019; Newell and
Goldsmith, 2001; Wang and Scheinbaum, 2018), can have a positive and significant effect on the
customers’ motivations to use them (Camilleri, 2022; Davis et al., 1989). Moreover, the researchers
hypothesize that the online users’ perceptions about the usefulness of these interactive service technologies
would predict their intentions to continue using them in the future. The underlying research questions
(RQs) of this study are: (i) “Which factors are influencing the online users’ perceptions about the utility
of interactive travel websites”, and (ii) “"How and in what ways do interactive travel websites affect the
consumers’ intentions to use these sites?”
This contribution differentiates itself from previous research. It puts forward an integrative
information adoption – technology acceptance model that comprises key factors that were drawn from
IAM (Camilleri, 2022; Filieri and McLeay, 2014; Salehi-Esfahani et al., 2016; Shu and Scott, 2013;
Sussman and Siegal, 2003; Tseng and Wang, 2016), TAM (Ayeh, 2015; Bhattacherjee and Sanford, 2006;
Chen, et al., 2007; Davis et al., 1989; Go, Kang and Suh, 2020) as well as from an (interactive) engagement
construct (Calder et al., 2009; Chattaraman, Kwon, et al., 2019; Lin and Chang, 2018; Park and Yoo,
2020).
Although these measures have been used by a number of researchers in service marketing,
information management and technology adoption; to date, there is no other study that examines the effects
of ‘information quality’, ‘source credibility’ and (interactive) ‘engagement’ constructs (as exogenous
factors) on TAM’s ‘perceived usefulness’ and ‘intentions’ to continue using interactive website
technologies. This study addresses this knowledge gap in the academic literature. Unlike previous
research, this contribution raises awareness on the importance of measuring the individuals’ perceptions
about the engaging capabilities of interactive technologies when investigating their utilitarian motivations
to use them (through information/technology adoption models).
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The following section features a critical review of the relevant literature. The readers are introduced
to the conceptual framework and to the research hypotheses of this empirical study. Hence, the
methodology section sheds light on the method that was used to capture and analyze primary data.
Subsequently, the results section presents the findings from the structural equations modeling partial least
squares (SEM-PLS) confirmatory composite analysis approach. In conclusion, this article puts forward
implications to academia and practitioners. It identifies its research limitations and outlines plausible
research avenues to academia.
2. Conceptual framework and hypotheses development
Relevant theoretical underpinnings suggest that individuals tend to reflect on the quality of the
persuasive messages they receive. They would probably synthesize their arguments, before making
decisions and prior to committing themselves to certain behaviors (Bhattacherjee and Sanford, 2006; Shu
and Scott, 2013). This argumentation is consistent with Petty et al.’s (1983) ELM. Previous research
reported that the quality of online content can have a significant impact on the individuals’ intentions to
visit a website or to make a purchase (Chen and Chang, 2018; Erkan and Evans, 2016; Gupta and Harris
2010; Park, et al., 2007). Debatably, individuals would pursue ELM’s central route, if they consider the
quality of the argument in a message or communication, in terms of its understandability, accuracy,
relevance, timeliness and completeness (Allison, et al., 2017; Cheung, et al., 2008; Park and Lee, 2008).
However, ELM also posits that the individuals’ attitudes towards information can be affected by
less rational judgements (Petty et al., 1983). This form of low elaborated communication is associated
with the peripheral route (Cheung et al., 2008; Petty and Cacioppo, 1986). Individuals may be influenced
by the volume of information or by the trustworthiness and expertise of the sources communicating the
messages (Bhattacherjee and Sanford, 2006; Sussman and Siegal, 2003). They may usually opt to pursue
the peripheral route’s low elaboration, as they may not be motivated to make cognitive efforts to evaluate
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the message, or simply because, for some reason, they are not capable of reflecting on its content (Petty
and Cacioppo, 1986). For instance, consumers can be influenced by subjective cues like brand image and
source attractiveness. These issues may hinder them from paying attention to the quality of the information
that is communicated to them (Filieri and McLeay, 2014).
The target audience may rely on heuristic inferences relating to source credibility, such as
endorsements or recommendations of other individuals, who may be likeable and/or knowledgeable in
their respective fields (Wang and Scheinbaum, 2018; Li, 2013; Bhattacherjee and Sanford, 2006). Thus,
individuals can be influenced by peripheral issues if they identify themselves with credible, trustworthy
sources or with experts. The assessment of information through ELM’s central and/or peripheral routes
does not necessarily imply that individuals will eventually reach different conclusions if they pursue a
wide array of evaluation methods or cues (Salehi-Esfahani et al., 2016; Sussman and Siegal, 2003).
Both routes can lead to persuasion and may even trigger immediate behaviors, such as purchasing
a product (Shu and Scott, 2013; Park et al., 2007). This reasoning is also reflected in other theories
including in IAM (Erkan and Evans, 2016; Filieri, 2015) and in the principles relating to technology
adoption models including TAM (Arghashi and Yuksel, 2022; Davis et al., 1989) and to psychological
theories like the Theory of Reasoned Action (Fishbein and Ajzen, 195) and the Theory of Planned
Behavior (Ajzen, 1991), among others.
The latter models suggest that the individuals’ intentions toward certain behaviors (or technologies)
is based on their perceptions, beliefs and evaluations. In a similar vein, IAM theorists argued that the
persons’ perceptions about the usefulness of information can predict their adoption (Bhattacherjee and
Sanford, 2006; Cheung et al., 2008; Sussman and Siegal, 2003). For instance, Cheung et al. (2008)
maintained that the information usefulness of word-of-mouth publicity within a virtual platform, can lead
individuals to make better buying decisions. Other authors pointed out that the online users’ perceptions
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on the usefulness of consumer reviews, would predict their intentions to continue relying on online content
(Erkan and Evans, 2016).
This argumentation is in line with the relevant literature that is focused on the impact of
communications on the individuals’ intentional behaviors, including consumer purchase decisions (Chen
and Chang, 2018). Subsequently, Erkan and Evans (2016) have built on Sussman and Siegal’s (2003) and
Cheung et al.’s (2008) frameworks as they included purchase intention as their endogenous construct in
their empirical model. Their study investigated the online users’ intentions to continue using review
websites. In sum, the researchers found that their respondents considered such recommender systems as
useful, helpful and informative. Similarly, individuals would be willing to revisit travel websites if they
consider them as useful to compare prices, to purchase itineraries, hotel accommodation, et cetera, and to
cancel their reservations, request changes in their bookings or to request refunds from the service provider.
This reasoning leads to the following hypothesis:
H1: The perceived usefulness of interactive travel websites significantly affects intentions to use them.
Presumably, individuals may be satisfied with good quality online content if it reflects their
expectations, and if it meets their requirements (Liu, et al., 2017; Rahimi and Kozak, 2017; Tsai et al.,
2021). Previous studies confirmed that the quality of websites is an antecedent for their adoption (Salehi-
Esfahani et al., 2016). Sussman and Siegel (2003) indicated that the quality of the emails’ content has a
significant effect on their usefulness. In other words, the individuals’ overall assessment about information
quality can also determine their confidence in online content (Kim and Niehm, 2009). Notwithstanding,
the information that is featured in websites, can raise awareness on the businesses’ services and products,
it could improve their image, and may also influence the consumers’ final purchase decisions (Chen and
Chang, 2018; Erkan and Evans, 2016).
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On the other hand, poor information quality is time consuming for consumers, and can have
negative effects on the businesses’ reputation. The use of low-quality content may result in detrimental
effects on the customers’ perceptions about brands (Gu et al., 2007). Customers will usually evaluate the
quality of information through indicators like the ease of accessibility and relevance of the content, or by
evaluating the richness of the data (Cheung et al., 2008; Islam and Rahman, 2017; Popovič et al., 2012).
Many authors suggested that individuals tend to assess the quality of the websites according to the
understandability, reliability and clarity of their content (Gu et al., 2007; Salehi-Esfahani et al., 2016).
Generally, they contended that consumers perceive them as useful if they believe that they feature high
quality content (Cheung et al., 2008; Sussman and Siegal, 2003). Hence, they may be intrigued to revisit
them again in the future (Arghashi and Yuksel, 2022; Salehi-Esfahani et al., 2016). This argumentation
leads to the following hypothesis:
H2: The quality of information of interactive travel websites significantly affects their perceived
usefulness.
ELM suggests that the individuals’ stance about information quality can help them form their
perceptions on a wide variety of topics (Petty and Cacioppo, 1986). However, it also presumes that the
credibility of information sources could also influence the individuals’ attitudes, particularly, if they are
considered as dependable and reliable (Bhattacherjee and Sanford, 2006; Tseng and Wang, 2016).
Individuals are usually influenced by the sources’ attractiveness, likeability, as well as by their credentials
(Cheung et al., 2008). The sources’ expertise and their trustworthiness are considered as key dimensions
of source credibility (Ayeh, 2015; Dou et al., 2012; Hussain et al., 2017; Lowry et al., 2014; Newell and
Goldsmith, 2001).
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Whilst the source trustworthiness construct is used to measure the levels of trust on the
communicators’ content; source expertise is utilized to measure the recipients’ perceptions about the
content curators’ competences to convey correct information (Ismagilova et al., 2020; Filieri et al., 2018;
Lock and Seele, 2017). The information that is disseminated by communication experts is assumed to be
reliable and credible, when compared to other content that is transmitted by unprofessional sources. Source
experts are perceived as knowledgeable and skilled by the receivers of information (Bhattacherjee and
Sanford, 2006; Ismagilova et al., 2020). If online users believe that the sources of information are credible
in terms of their trustworthiness and expertise, they will probably perceive that their content is helpful to
them (Salehi-Esfahani et al., 2016). Thus, source credibility can have a positive influence on the
individuals’ perceptions about the usefulness of information. This argumentation leads to the following
hypothesis:
H3: The source credibility of interactive travel websites significantly affects their perceived usefulness.
Chen et al. (2007) argued that the richness of the media is an important antecedent of information
usefulness. Thus, interactive websites can be characterized as high or low in terms of “media richness”,
depending on their ability to facilitate shared meanings that are based on the immediacy of feedback,
multiple cues, language varieties and personal foci (Capriotti et al., 2021). The Internet offers great
potential for interactive engagement (Camilleri and Kozak, 2022). It influences the online users’
perceptions toward companies and their products (Baggio and Del Chiappa, 2014). For example, it can
affect the consumers’ perceived images of travel destinations (Cao and Yang, 2016; Choi et al., 2007).
Interactive websites that offer simultaneous, synchronous, and a continuous exchange of information, are
responsive to their visitors’ needs, hence online users would find them useful before planning their travel
itineraries (Bastida and Huan, 2014; Camilleri, 2018; Camilleri and Camilleri, 2022; Chen et al., 2007).
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Many service companies including travel and tourism businesses are increasingly using interactive
websites as they help them raise awareness about their services (Hadjielias et al., 2022; Rather and
Camilleri, 2019). Ultimately, it is in their interest to create attractive websites, to entertain their visitors
(Cao and Yang, 2016). Hence, they can feature a good selection of appealing images and videos to entice
prospective travelers to visit destinations. This way, they familiarize them with their tourism products
(Salehi-Esfahani et al. 2016; Choi et al., 2007).
Generally, the tourism businesses use the interactive media to share useful information on the
attributes and features about their services and to display their prices. Therefore, their corporate websites
must capture the attention of online users. They have to be easy-to-use and should offer a variety of content
that provide immediate answers to consumers and prospects (EU, 2020; Park and Jang, 2014; McMillan
and Hwang, 2002). This leads to the following hypothesis:
H4: Engaging travel websites significantly affect their perceived usefulness.
Figure 1 depicts the research hypotheses of this contribution. This study explores the direct effects
between perceived usefulness and intentions to use interactive travel websites, and between information
quality, source credibility and interactive engagement on perceived usefulness. At the same time, it sheds
light on the indirect effects of all constructs on intentions to use interactive technologies.
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Figure 1. A research model that explores the individuals’ motivations to engage with interactive
travel websites
3. Methodology
The empirical data was collected through an online survey questionnaire that was disseminated
through two popular social media groups in June 2021. These groups were focused on consumer
experiences with service providers (including those that used travel, tourism and hospitality websites).
They had more than 60,000 subscribers. A link directed the targeted research participants to the survey
questionnaire. The group members were kindly invited to participate in an academic study that investigated
their perceptions about (interactive) travel websites. They were reassured that their identity would not be
revealed, as only aggregate data was analyzed in this research. After two weeks, there were 1,287
respondents who submitted their completed questionnaires.
The survey instrument integrated measures that were drawn from ELM/IAM (Camilleri, 2022;
Wang and Scheinbaum, 2018; Filieri and McLeay, 2014; Cheung et al., 2008; Sussman and Siegal, 2003),
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TAM (Camilleri 2018; Camilleri and Falzon, 2020; Cheung et al., 2008; Erkan and Evans, 2016) and from
relevant literature relating to interactive engagement (Kim et al., 2020; McMillan and Hwang, 2002).
Table 1 features a list of measures that were utilized in this study and provides a short definition for them
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Table 1 The measuring constructs and their corresponding items that were used in this research
Construct Definition Code Item Sources
Information
quality
This construct refers to the individuals'
perceptions about the quality of the
online content in terms of its
understandability, completeness,
timeliness and accuracy.
IQ1 The information in the travel websites is easy to understand. Elaboration Likelihood Model’s
Central Route (Camilleri, 2022;
Cheung et al., 2008; Filieri and McLeay,
2014).
IQ2 The information in the travel websites is complete.
IQ3 The information in the travel websites is timely.
IQ4 The information in the travel websites is correct.
Source
credibility
This construct refers to the
individuals' perceptions about the
sources’ credentials in terms of the
trustworthiness of their online content
and expertise in curating their
information.
SC1 I trust the content that is featured in the travel websites.
Elaboration Likelihood Model’s
Peripheral Route (Camilleri, 2022;
Newell and Goldsmith, 2001; Wang and
Scheinbaum, 2018).
SC2 The content that is featured in the travel websites is truthful.
SC3 The travel business has a great amount of experience in the
curation of online content.
SC4 The travel business is skilled in developing online content.
Interactive
engagement
This construct refers to the
individuals' perceptions about the
engagement capabilities of interactive
websites, in terms of appealing
content, ease-of-use and their degree
of responsiveness.
ENG1 The travel websites offer a variety of content.
Perceived Interactivity - Engaging
Construct (Camilleri & Kozak, 2022;
McMillan and Hwang, 2002).
ENG2 The travel websites keep my attention.
ENG3 It is easy to use the travel websites.
ENG4 The travel websites provide immediate answers to my
questions.
Perceived
usefulness
This construct refers to the
individuals' beliefs about the
utilitarian value of (interactive)
technologies.
PU1 The travel websites are useful. Technology Acceptance Models -
TAM, TAM2 and TAM3 (Camilleri &
Falzon, 2020; Davis et al., 1989; Erkan
and Evans, 2016).
PU2 The travel websites are informative.
PU3 The travel websites are helpful.
Intentions to
use the
technology
This construct refers to the
individuals’ willingness to perform
specified behaviors (like using
interactive technologies).
INT1 Most probably, I will return to the travel websites, sometime in
the near future.
Technology Acceptance Models -
TAM, TAM2, TAM3 (Camilleri and
Camilleri, 2022; Davis et al., 1989;
Erkan and Evans, 2016) and Theory of
Planned Behavior (Ajzen, 1991),
among others.
INT2 I will continue using the travel websites in future.
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The respondents were expected to indicate the extent of their agreement with the survey’s
measuring constructs in a five-point Likert scale. Their responses ranged from 1 “strongly disagree” to 5
= “strongly agree”, and 3 signaled an indecision. In the latter part of the questionnaire, the participants
revealed their demographic information, as they disclosed their gender and age. They also indicated their
frequency of usage of travel websites.
The measuring items were presented in a such a way to reduce the plausibility of common method
bias. The survey instrument considered the effects of the chosen participants’ response styles, the
proximity of related or unrelated constructs. The items’ wording was kept simple and straightforward,
according to MacKenzie and Podsakoff’s (2012) recommendations. The method bias was reduced by pilot
testing the questionnaire with a small group of experienced colleagues, to identify any possible weaknesses
in the survey instrument.
4. Results
More than half of the respondents were females. The sample consisted of 731 females (56.8%) and
555 males (43.2%). Most of the respondents (n=465, 36.1%) were between 30 and 39 years of age. The
second largest group (n=354, 27.5%) comprised individuals who were between 40 and 49 years old. The
findings indicated that most of the research participants frequently browsed through interactive travel
websites in the past. Table 2 provides a descriptive profile of the research participants.
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Table 2. The profile of the research participants
Variable
Range N
Variable Range N
Gender
Female 731
Usage of travel websites
Yes 1268
Male 555
No 19
Missing
1
Missing 0
Total
1287
Total 1287
Age
18-29 291
Frequency of usage of travel websites
Never 15
30-39 465
1-2 times a year 445
40-49 354
3-5 times a year 567
50-59 124
1-2 times a month 162
Over 60
53
More than 3 times in a month
98
Missing
0
Missing 0
Total
1287
Total
1287
The respondents have mostly agreed with the survey items in the model, as the mean scores (M)
were above the mid-point of 3. Whilst the perceived usefulness - PU3 construct reported the highest score
(M=4.114), information quality - IQ1 registered the lowest mean score (M=3.4). The standard deviations
(SD) indicated that there was a narrow spread around the mean. The values of SD ranged from 0.51 that
represented intention to use the technology - INT1, to 1.091, that was noted for information quality – IQ1.
4.1 Confirmatory composite analysis
This study relied on a structural equation modelling partial least squares (SEM-PLS) approach to
explore the measurement quality of a reflective measurement model (Ringle et al., 2014). SEM-PLS’
algorithm revealed that the results of the outer loadings were higher than 0.6. Cronbach’s alpha, rho_A
and the composite reliability values were well above 0.7. The constructs that were used in this study
reported acceptable convergent validities as their average variance extracted (AVE) values were higher
than 0.5 (Hair et al., 2012). There was evidence of discriminant validity, as the square root value of AVE
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was higher than the correlation values among the latent variables (Fornell and Larcker, 1981). This study
also presented the results of the heterotrait-monotrait (HTMT) as reported in the shaded area of Table 3.
Again, the correlations re-confirmed the presence of discriminant validity, where the values were lower
than 0.85 (Henseler et al., 2015).
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Table 3. The descriptive statistics as well as the construct reliability and validity values
Construct Items Mean Deviation
Loadings Alpha rho_A CR AVE 1 2 3 4 5
1
Interactive
engagement
ENG1 3.725 0.922 0.778
0.808 0.815 0.872 0.63 0.794 0.927 0.703 0.771 0.721
ENG2 3.7 0.9 0.812
ENG3 3.8 0.843 0.826
ENG4 4 0.707 0.756
2
Information
quality
IQ1 3.4 1.091 0.857
0.867 0.878 0.909 0.715 0.757 0.845 0.492 0.634 0.508
IQ2 3.65 1.014 0.84
IQ3 4.075 0.685 0.806
IQ4 3.975 1.012 0.877
3
Intentions
to use the
technology
INT1 4.2 0.51 0.811
0.691 0.780 0.861 0.757 0.574 0.415 0.870 0.63 1.12
INT2 4.025 0.724 0.925
4
Perceived
usefulness
PU1 4.071 1.034 0.935
0.954 0.955 0.97 0.916 0.697 0.584 0.530 0.957 0.642 PU2 4.2 0.9 0.976
PU3 4.114 0.848 0.96
5
Source
credibility
SC1 4.025 0.689 0.788
0.773 0.774 0.855 0.598 0.580 0.423 0.832 0.555 0.773
SC2 3.775 0.851 0.828
SC3 3.375 0.886 0.803
SC4 3.625 0.827 0.655
Note: The discriminant validity was confirmed through Fornell-Larcker’s criterion and the HTMT procedure. The values of the square root of the AVEs (in bold) for each
construct were greater than the correlations among the constructs in their respective columns. The shaded area features the results from the HTMT procedure. The
discriminant validity was reconfirmed where the values were less than 0.85 (Henseler et al., 2015)
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4.2 Structural Model Assessment
The assessment criteria involved an examination of the collinearity among the constructs. SEM
PLS algorithm indicated that there were no collinearity issues as the variance inflation factors (VIFs) were
lower than 3.3 (Kock, 2015). The model’s predictive power indicated the coefficients of determination
(R2) and the effects (f2) of the exogenous factors on the endogenous constructs. The findings from this
research model reported that the constructs that were used in this study predicted 52.9% of the participants’
perceived usefulness and 28.1% of their intentions to continue using interactive travel websites.
Perceived usefulness had the highest effect on intentions to use the technology, where f2=0.391.
There were other effects between interactive engagement-perceived usefulness (f2=0.152), source
credibility-perceived usefulness (f2=0.075) and information quality-perceived usefulness (f2=0.02). Figure
2 depicts the explanatory power of this research model. It illustrates the total effects, outer loadings and
the coefficient of determination (R2) values of the constructs.
Figure 2. Factors affecting the individuals’ motivations to engage with interactive travel websites
20
The results from the bootstrapping procedure were used to explore the hypothesized path
coefficients. With regards to H1, this research reported that the perceived usefulness of travel websites
strongly and significantly predicted the individuals’ intentions to use them (β=0.53, t=14.017, p<0.001).
This finding is consistent with other studies relating to TAM. H2 suggests that the quality of information
was reported to be a significant antecedent of the respondents’ perceived usefulness (β=0.141, t=2.819,
p<.01). H3 indicated that source credibility was positively and significantly predicting their perceptions
about the perceived usefulness of the mentioned technologies (β=0.231, t=3.999, p<0.001. Moreover, H4
confirmed that interactive engagement was a very significant precursor for the respondents’ perceptions
about the usefulness of the websites (β=0.456, t=6.729, p<0.001). Table 4 presents the results of the
hypotheses of this study. It tabulates the findings of the standardized beta coefficients (original sample),
the standard deviations, the confidence intervals, t statistics and the significance values. Table 5 features
the indirect effects within this research model.
21
Table 4. The investigation of the hypotheses
Path Coefficient
Original
Sample
(O)
Standard
Deviation
(STDEV)
Confidence
Intervals Bias
Corrected
T statistics
(|O/STDEV|)
P Values
Decision
2.50%
97.50%
H1 Perceived usefulness -> Intentions to use
the
technology
0.530***
0.038 0.448 0.597 14.017 0.000 Supported
H2 Information quality -> Perceived usefulness 0.141***
0.050 0.049 0.243 2.819 0.005 Supported
H3 Source credibility -> Perceived usefulness 0.231***
0.058 0.124 0.349 3.999 0.000 Supported
H4 Interactive engagement -> Perceived
usefulness
0.456***
0.068 0.295 0.564 6.729 0.000 Supported
***Critical Values P<0.01, T>1.96
22
Table 5. The indirect effects
Path Coefficient Indirect Effects
Original
Sample
(O)
Standard
Deviation
(STDEV)
Confidence
Intervals Bias
Corrected
T statistics
(|O/STDEV|) P Values
2.50%
97.50%
Information quality -> Intentions to use the
technology
0.075*** 0.028 0.028 0.136 2.673 0.008
Source credibility -> Intentions to use the technology 0.122*** 0.033 0.059 0.190 3.693 0.000
Interactive engagement -> Intentions to use the
technology
0.242*** 0.040 0.170 0.320 5.992 0.000
***Critical Values P<0.01, T>1.96
23
4.3 Discussion
This study sought to identify the most significant factors that are affecting the online users’
perceptions about the usefulness of interactive websites. It also investigated whether they were willing to
continue utilizing these service technologies in the future. The statistical results reported that the research
hypotheses were all confirmed. The ‘perceived usefulness’ - ‘intentions to use the technology’ link was
the most significant in this research model. This is consistent with previous findings (Salehi-Esfahani et
al., 2016; Erkan and Evans, 2016; Shu and Scott, 2013), as perceived usefulness of information/technology
can be a significant antecedent of revisiting interactive websites (Arghashi and Yuksel, 2022), writing
positive reviews (Cheung et al., 2008; Filieri & McLeay, 2014) or may even induce online users to lay
down their credit card to make a purchase (Chen and Chang, 2018).
This research sheds light on the factors that are influencing the acceptance and use of interactive
websites, namely, information quality, source credibility as well as their engagement capabilities. A highly
significant effect was found between interactive engagement and perceived usefulness. Evidently, the
individuals' perceptions about the attributes of interactive websites including their ease of use, appealing
content that captures the attention of online users, and their responsive capabilities, were influencing their
utilitarian motivations to use them.
Moreover, the study also suggests that ‘information quality’ and ‘source credibility’ were found
to be significant antecedents for the respondents’ ‘perceived usefulness’ of interactive websites. These
findings are congruent with past studies, particularly those that are focused on ELM/IAM (Chen and
Chang, 2018; Cao and Yang, 2016; Choi et al., 2007; Erkan and Evans, 2016; Park and Lee 2008; Park et
al., 2007; Salehi-Esfahani et al., 2016; Shu and Scott, 2013). Similar results were also reported in previous
research, where other colleagues found that the individuals’ processing of information could involve
elements of central (e.g. information quality) and/or peripheral routes (like source credibility) (see Cao
24
and Yang, 2016; Choi et al., 2007; Petty and Cacioppo, 1986; Petty et al., 1983; Salehi-Esfahani et al.,
2016; Shu and Scott, 2013; Sussman and Siegal, 2003).
ELM researchers noted that individuals may be influenced by subjective signals or heuristic
inferences like source attractiveness and brand image. Very often, they contended that individuals may be
affected by large volumes of information including by consumer testimonials, as well as by online reviews
and recommendations, among other cues (Filieri and McLeay, 2014; Salehi-Esfahani et al., 2016). In this
case, the research participants were affected by ELM’s peripheral issues relating to source credibility.
They indicated in their responses that the websites were curated by skilled and experienced professionals.
In addition, the findings from SEM-PLS reported that source credibility had stronger effects than
information quality on the perceived usefulness of interactive travel websites. Nevertheless, the results
confirmed that to a certain extent, the research participants felt that their online content was satisfying their
needs for information, in terms of its completeness, timeliness and accuracy, as they were willing to revisit
them again, in the future (according to the direct and indirect effects that were reported in Tables 4 and 5).
5.1 Theoretical contribution
Previous studies reported that interactive websites ought to be accessible, appealing, convenient,
functional, secure and responsive to their users (Crolic et al., 2021; Hoyer et al., 2020; Kabadayi et al.,
2020; Klaus and Zaichkowsky, 2020; Rosenmayer et al., 2018; Sheehan et al., 2020; Valtakoski, 2019).
Online service providers are expected to deliver a personalized customer service experience and to exceed
their consumers’ expectations at all times, to encourage repeat business and loyal behaviors (Li et al.,
2017; Tong et al., 2020; Zeithaml et al. 2002).
Many service marketing researchers have investigated the individuals’ perceptions about price
comparison sites, interactive websites, ecommerce / online marketplaces, electronic banking, and social
media, among other virtual domains (Donthu et al., 2021; Kabadayi et al., 2020; Klaus and Zaichkowsky,
25
2020; Rosenbaum and Russell-Bennett, 2020; Rosenmayer et al., 2018; Valtakoski, 2019; Zaki, 2019).
Very often, they relied on measures drawn from electronic service quality (e-SQ or e-SERVQUAL),
electronic retail quality (eTailQ), transaction process-based approaches for capturing service quality
(eTransQual), net quality (NETQual), perceived electronic service quality (PeSQ), site quality
(SITEQUAL) and website quality (webQual), among others.
Technology adoption researchers often adapted TAM measures, including perceived usefulness
and behavioral intentions constructs, among others, or relied on psychological theories like the Theory of
Reasoned Action (Fishbein and Ajzen, 195) and the Theory of Planned Behavior (Ajzen, 1991), among
others, to explore the individuals’ acceptance and use of different service technologies, in various contexts
(Park et al., 2007; Chen and Chang, 2018). Alternatively, they utilized IAM’s theoretical framework to
investigate the online users’ perceptions about the usefulness of information or online content. Very often
they examined the effects of information usefulness on information adoption (Erkan and Evans, 2016; Liu
et al., 2017).
A review of the relevant literature suggests that good quality content (in terms of its
understandability, completeness, timeliness and accuracy) as well as the sources’ credibility (with regard
to their trustworthiness and expertise) can increase the individuals' expectations regarding a business and
its products or services (Cheung et al., 2008; Li et al., 2017; Liu et al., 2017). ELM researchers suggest
that a high level of message elaboration (i.e., argument quality) as well as the peripheral cues like the
credibility of the sources and their appealing content, can have a positive impact on the individuals’
attitudes toward the conveyors of information (Allison et al., 2017; Chen and Chang, 2018; Petty et al.,
1983), could affect their intentions to (re)visit the businesses’ websites (Salehi-Esfahani et al., 2016), and
may even influence their purchase intentions (Chen and Chang, 2018; Erkan and Evans, 2016).
This contribution differentiates itself from previous research as the researchers adapted key
measures from ELM/IAM namely ‘information quality’ (Filieri and McLeay, 2014; Salehi-Esfahani et al.,
26
2016; Shu and Scott, 2013; Tseng and Wang, 2016) and ‘source credibility’ (Ayeh, 2015; Leong et al.,
2019; Wang and Scheinbaum, 2018) and integrated them with an ‘interactive engagement’ construct
(McMillan and Hwang, 2002), to better understand the individuals’ utilitarian motivations to use the
service businesses’ interactive websites. The researchers hypothesized that these three constructs were
plausible antecedents of TAM’s ‘perceived usefulness’ and ‘intentions to use the technology’. Specifically,
this research examines the direct effects of information quality, source credibility and interactive
engagement on the individuals’ perceived usefulness of interactive website, as well as their indirect effects
on their intentions to continue using these service technologies.
To the best of the researchers’ knowledge, there is no other research in academia that included an
interactive engagement construct in addition to ELM/IAM and TAM measures. This contribution
addresses this gap in the literature. The engagement construct was used to better understand the
respondents’ perceptions about the ease-of-use of interactive websites, to ascertain whether they are
captivating their users’ attention by offering a variety of content, and more importantly, to determine
whether they consider them as responsive technologies.
5.2 Managerial implications
This study sheds light on the travel websites’ interactive capabilities during an unprecedented crisis
situation, when businesses received higher volumes of inquiries through different channels (to change
bookings, cancel itineraries and/or submit refund requests). At the same time, it identified the most
significant factors that were affecting the respondents’ perceptions and motivations to continue using
interactive service technologies in the future.
In sum, this research confirmed that the respondents were evaluating the quality of information
that is featured in interactive websites. The findings reported they were well acquainted with the websites’
content (e.g. news feeds, product information, differentiated pricing options, images, video clips, and/or
27
web chat facilities). The researchers presumed that the respondents were well aware of the latest
developments. During COVID-19, a number of travel websites have eased their terms and conditions
relating to cancellations and refund policies (EU, 2020), to accommodate their customers. Online
businesses were expected to communicate with their customers and to clarify any changes in their service
delivery, in a timely manner.
The contribution clarified that online users were somehow influenced by the asynchronous content
that is featured in webpages. Therefore, service businesses ought to publish quality information to satisfy
their customers’ expectations. They may invest in service technologies like a frequently answered
questions widget in their websites to enhance their online customer services, and to support online users
during and after the sales transactions. Service businesses could integrate events’ calendars, maps, multi-
lingual accessibility options, online reviews and ratings, high resolution images and/or videos in their
interactive websites, to entertain their visitors (Cao and Yang, 2016; Bastida and Huan, 2014).
This research underlines the importance for service providers to consistently engage in concurrent,
online conversations with customers and prospects, in real-time (Buhalis and Sinarta 2019; Chattaraman
et al., 2019; Rihova et al., 2018; Harrigan et al., 2017). Recently, more researchers are raising awareness
on the provision of live chat facilities through interactive websites or via SNSs like WhatsApp or
Messenger (Camilleri & Troise, 2022). Services businesses are expected to respond to consumer queries,
and to address their concerns, as quickly as possible (McLean and Osei-Frimpong, 2019), in order to
minimize complaints.
AI chatbot technologies are increasingly enabling service businesses to handle numerous
interactions with online users, when compared to telephone conversations with human customer services
representatives (Adam et al., 2021; Hoyer et al., 2020; Luo et al., 2019; McLean and Osei-Frimpong,
2019; Van Pinxteren et al., 2019). The most advanced dialogue systems are equipped with features like
omnichannel messaging support, no code deployment, fallback options, as well as sentiment analysis.
28
These service technologies are designed to improve the consumers’ experiences by delivering automated
smart responses, in an efficient manner. Hence, online businesses will be in a better position to meet and
exceed their customers’ service expectations. Indeed, service businesses can leverage themselves with a
responsive website. These interactive technologies enable them to improve their positioning among
customers, and to generate positive word-of-mouth publicity.
5.3 Limitations and future research avenues
This study has included a perceived interactivity dimension, namely an ‘interactive engagement’
construct within an information adoption model. The findings revealed that the respondents believed that
the websites’ engaging content was a significant antecedent of their perceptions about the usefulness of
interactive websites. This study also reported that the interactive engagement construct indirectly affected
the individuals’ intentions to revisit them again.
In conclusion, the authors recommend that future researchers validate this study’s measures in
other contexts, to determine the effects of interactive engagement on information adoption and/or on the
acceptance and usage of online technologies. Further research is required to better understand which
attributes and features of interactive websites are appreciated by online users. Recent contributions suggest
that there are many benefits for service businesses to use conversational chatbots to respond to online
customer services. These interactive technologies can offer increased convenience to consumers and
prospects (Thomaz et al., 2020), improved operational efficiencies (Pantano and Pizzi, 2020), reduced
labor costs (Belanche et al., 2020), as well as time-saving opportunities for customers and service
providers (Adam et al., 2021).
Prospective empirical research may consider different constructs from other theoretical
frameworks to examine the individuals’ perceptions and/or attitudes toward interactive websites and their
service technologies. Academic researchers are increasingly relying on the expectancy theory/expectancy
29
violation theory (Crolic et al., 2021), the human computer interaction theory/human machine
communication theory (Wilkinson et al., 2021), the social presence theory (Tsai et al., 2021), and/or the
social response theory (Adam et al., 2021), among others, to investigate the customers’ engagement with
service technologies.
Notwithstanding, different methodologies and sampling frames could be used to capture and
analyze primary data. For instance, inductive studies may investigate the consumers’ in-depth opinions
and beliefs on this topic. Interpretative studies may reveal important insights on how to improve the
efficacy and/or the perceived usefulness of interactive service technologies.
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