ArticlePDF Available

Understanding motivations to use online streaming services: Integrating the technology acceptance model (TAM) and the uses and gratifications theory (UGT)

Authors:

Abstract and Figures

Purpose: The outbreak of the Coronavirus (COVID-19) pandemic and its preventative social distancing measures have led to a dramatic increase in subscriptions to paid streaming services. Online users are increasingly accessing live broadcasts as well as recorded video content and digital music services through Internet and mobile devices. In this context, this study explores the individuals’ uses and gratifications from online streaming technologies during COVID-19. Design/Methodology/Approach: This research has adapted key measures from the ‘Technology Acceptance Model’ (TAM) and from the ‘Uses and Gratifications Theory’ (UGT) to better understand the individuals’ intentions to use online streaming technologies. A structural equations partial least squares’ (SEM-PLS 3) confirmatory composite approach was used to analyze the gathered data. Findings: The individuals’ perceived usefulness and ease of use of online streaming services were significant antecedents of their intentions to use the mentioned technologies. Moreover, this study suggests that the research participants sought emotional gratifications from online streaming technologies, as they allowed them to distract themselves into a better mood, and to relax in their leisure time. Evidently, they were using them to satisfy their needs for information and entertainment. Research implications: This study contributes to the academic literature by generating new knowledge about the individuals´ perceptions, motivations, and intentions to use online streaming technologies to watch recorded movies, series, and live broadcasts. Practical implications: The findings imply that there is scope for the providers of online streaming services to improve their customer-centric marketing by refining the quality and content of their recorded programs, and through regular interactions with subscribers and personalized recommender systems. Originality/Value: This study integrates the TAM and UGT frameworks to better understand the effects of the users’ perceptions, ritualized and instrumental motivations on their intentions to continue watching movies, series and broadcasts through online streaming technologies, during COVID-19.
Content may be subject to copyright.
Understanding motivations to use
online streaming services:
integrating the technology
acceptance model (TAM) and the
uses and gratications theory (UGT)
Comprendiendo las motivaciones
para usar los servicios de streaming
en línea: Integrando el modelo de
aceptaci
on de la tecnología y la
teoría de usos y graticaciones
Mark Anthony Camilleri
Department of Corporate Communication, Faculty of Media and Knowledge Sciences,
University of Malta, Msida, Malta and The Business School,
The University of Edinburgh, Edinburgh, UK, and
Loredana Falzon
University of Malta, Msida, Malta
Abstract
Purpose The outbreak of the Coronavirus (COVID-19) pandemic and its preventative social distancing
measures have led to a dramatic increase in subscriptions to paid streaming services. Online users are
increasingly accessing live broadcasts, as well as recorded video content and digital music services through
internet and mobiledevices. In this context,this study aims to explorethe individualsuses and gratications
from online streaming technologies during COVID-19.
Design/methodology/approach This research has adapted key measures from the technology
acceptance model(TAM) and from the uses and gratications theory(UGT) to better understand the
individualsintentions to use online streaming technologies. A structural equations partial least squares
conrmatory composite approach was used toanalyze the gathered data.
© Mark Anthony Camilleri and Loredana Falzon. Published in Spanish Journal of Marketing ESIC.
Published by Emerald Publishing Limited. This article is published under the Creative Commons
Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative
works of this article (for both commercial and non-commercial purposes), subject to full attribution to
the original publication and authors. The full terms of this licence maybe seen at http://
creativecommons.org/licences/by/4.0/legalcode.
The authors thank the editor and his reviewers for their constructive remarks and suggestions.
Online
streaming
services
Received 25 April2020
Accepted 12 November2020
Spanish Journal of Marketing -
ESIC
Emerald Publishing Limited
2444-9709
DOI 10.1108/SJME-04-2020-0074
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/2444-9709.htm
Findings The individualsperceived usefulness and ease of use of online streaming services were
signicant antecedents of their intentions to use the mentioned technologies. Moreover, this study suggests
that the research participants sought emotional gratications from online streaming technologies, as they
allowed them to distract themselves into a better mood and to relax in their leisure time. Evidently, they were
using them to satisfy their needs for information and entertainment.
Research limitations/implications This study contributes to the academic literature by generating
new knowledge about the individualsperceptions, motivations and intentions to use online streaming
technologies to watch recorded movies, series and live broadcasts.
Practical implications The ndings imply that there is scope for the providers of online streaming
services to improve their customer-centric marketing by rening the quality and content of their recorded
programs and throughregular interactions with subscribers andpersonalized recommender systems.
Originality/value This study integrates the TAM and UGT frameworks to better understand the effects
of the usersperceptions, ritualized and instrumental motivations on their intentions to continue watching
movies, series and broadcasts through online streaming technologies, during COVID-19.
Keywords Uses and gratications theory, TAM, Technology acceptance model, COVID-19, UGT,
Online streaming, Broadcast media, SEM-PLS, Streaming video, COVID-19
Paper type Research paper
Resumen
Prop
osito El distanciamiento social durante la pandemia del coronavirus (COVID-19) ha llevado a un
aumento dram
atico en las suscripciones a los servicios de transmisi
on de pago. Los usuarios en línea acceden
cada vez m
as a transmisiones en vivo, así como a contenido de video grabado y servicios de música digital. En
este contexto, este estudio explora los usos y las graticaciones buscadas por las personas con las tecnologías
de transmisi
on en línea durante la COVID-19.
Diseño/Metodología/Enfoque En la operacionalizaci
on de las variables se utilizaron las medidas del
Modelo de Aceptaci
on de Tecnología(TAM) y la Teoría de Usos y Graticaciones(UGT). Adem
as, se
utiliz
o SEM-PLS 3 para analizar los datos recopilados de las encuestas.
Hallazgos La utilidad percibida y la facilidad de uso de los servicios de transmisi
on en línea son
antecedentes signicativos de la intenci
on de utilizarlos. Adem
as, las personas buscan graticaciones
emocionales de tales tecnologías, ya que les permiten distraerse, estar de mejor humor y relajarse en su tiempo
libre. Adem
as, las utilizan para obtener informaci
on y entretenimiento.
Implicaciones te
oricas Este estudio contribuye a la literatura académica generando nuevos
conocimientos sobre las percepciones, motivaciones e intenciones de los individuos de utilizar tecnologías de
transmisi
on en línea para ver películas grabadas, series y transmisiones en vivo.
Implicaciones pr
acticas Los hallazgos implican que hay margen para que los proveedores de servicios
de transmisi
on en línea mejoren su marketing centrado en el cliente reforzando la calidad y el contenido de sus
programas grabados y la publicidad intermitente.
Originalidad/Valor Este estudio integra las teorías TAM y UGT para comprender mejor el creciente
uso de las tecnologías de transmisi
on para ver películas grabadas, seriesy transmisiones en vivo.
Palabras clave Online streaming, Modelo de aceptaci
on tecnol
ogica (TAM),
Teoría de usos y graticaciones (UGT), COVID-19
Tipo de papel Trabajo de investigaci
on
1. Introduction
Relevant academic literature suggests that new media technologies are changing the way
how individuals consume television (Tefertiller, 2018;Aldea and Vidales, 2012;Hirsjärvi
and Tayie, 2011). Today, several media companies are offering video streaming services
that feature high-quality, original content that can be accessed through digital and mobile
technologies (Kostyrka-Allchorne et al., 2017;Groshek and Krongard, 2016). Video
streaming technologies have disrupted the way how individuals consume broadcast media.
Consumers are shifting from linear formats such as real-time television (TV) services that
SJME
are accessible through satellite/or cable and subscribing to online streaming services
(Spilker et al., 2020;Sørensen, 2016;Flavi
an and Gurrea, 2007). Online users are accessing
broadcast services through the home internet and/or via mobile devices (Lim et al., 2015;
Simpson and Greeneld, 2012). This is particularly conspicuous among the youngest
demographics, who are increasingly subscribing to online TV channels and video streaming
services (Panda and Pandey, 2017).
One cannot generalize that all young individuals would follow similar consumption
patterns. Therefore, media and entertainment businesses may consider other variables
when they explore their viewersproles and their consumption behaviors. For instance,
online streaming companies such as Amazon Prime Video, Apple TV, Disneyþ, HBO, Hulu,
Netix and Roku are continuously investing in new programs, as they are operating in an
increasingly competitive environment (WSJ, 2019;Jenner, 2016). Hence, their subscribers can
access a library of movies, series, shows and sports programs, etc. Very often, these media
companies are also using mobile applications (apps) and integrating personalized
recommender systems to enhance their customersexperiences. This way, they improve
their brand equity and service quality to retain existent consumers and attract new ones.
This research explores the consumersperceptions toward online streaming technologies
and sheds light on their motivations to use them. It presumes that individuals seek
emotional and instrumental gratications from watching recorded videos and/or live
broadcasts through digital and mobile devices. Therefore, this contribution builds on the
technology acceptance model (TAM) (Scherer et al., 2019;Munoz-Leiva et al.,2017;Rauniar
et al.,2014;Wallace and Sheetz, 2014; Davis et al., 1989; Davis, 1989) and on the uses and
gratications theory (UGT) (Kaur et al.,2020;Dhir et al., 2017a,2017b;Joo and Sang, 2013;
Smock et al.,2011;Stafford et al.,2004;Katz et al.,1973) to investigate the consumersease of
use and usefulness of these technologies, as well as their ritualized and instrumental
motivations that would ultimately have a positive and signicant effect on their behavioral
intentions to use them. Hence, this study relied on TAMs and UGTs key measures to
capture the data for this empirical investigation. These two theoretical frameworks were
purposely chosen as they comprise valid and reliable measures that were frequently tried
and tested in academia, in various contexts.
Specically, the underlying research questions are: what are the individualsmotivations
for watching online streaming through their digital and mobile devices? Are the streaming
technologies useful andeasy to use? Are they willing to continue using them to watch online
TV channels or recorded video content? To the best of our knowledge, there are no other
studies that have integrated TAMsand UGTs key constructs to shed light on the
individualsmotivations for ritualized use and instrumental use of online streaming
technologies, and to reveal their perceived usefulness and ease of use. Therefore, this
research addresses this gap in academic knowledge. In sum, this contribution suggests that
the individualsmotivations to use online streaming technologies to watch live TV channels
and/or recorded videos would have a positive and signicant effect on their acceptance of
these technologies, and on their intentions to continue using them.
This article is structured as follows: the following section provides a critical review of
key theories that were drawn from relevant marketing and technology literature. It presents
the conceptual framework and formulates the hypotheses for this research. Afterward, the
methodology section describes the method that was used to gather the data from the
respondents. It sheds light on the measures that were used in this quantitative study. Hence,
the results section features an analysis and interpretation of the ndings. In conclusion, this
contribution outlines its theoretical and its practical implications. The authors identify their
research limitations and outline their future research avenues to academia.
Online
streaming
services
2. The technology acceptance of online streaming services
Individuals are increasingly consuming the broadcast media through digital and mobile
technologies. Very often, they are watchingTV channels, movies, series, shows, etc. through
online streaming services that are readily available through ubiquitous technologies,
including smartphones or tablets. eMarketer (2019) reported that 70.1% surfed the internet
while watching their favorite movies and shows. Moreover, according to the latest
Global Web Index Trend Report, the individuals who were between 1624 years, spent
7 ¾ h per day online or on their smartphones or tablets. The individuals from this
demographic segment devoted over 2.5 h a day to social networking and were watching
more than an hour of online TV per day (GWI, 2019). The individuals hailing from the 2534
age segment have switched from linear TV to online streaming to watch live TV and/or
recorded videos. They subscribed to online services through digital and high-speed mobile
devices, including smartphones and tablets to stream live channels and recorded video
content from anywhere, at any time (eMarketer, 2019;GWI, 2019). Evidently, they were
accessing online streaming through virtual private networks to watch TV programs,
movies, entertainment, sporting events and the like (GWI, 2019). Hence, media and
entertainment businesses are continuously investing on the programming of new content,
including those produced in-house to satisfy their online subscribers. In this light, this study
explores the individualsperceptions toward online streaming technologies and their
motivations to use them to watch recorded videos and/or live broadcasts. The researchers
relied on TAMs(Nagy, 2018;Munoz-Leiva et al., 2017;Cha, 2013;Davis, 1989) and UGTs
key constructs (Kaur et al., 2020; Dhir et al., 2017a, 2017b) to capture the data from their
respondents.
2.1 The perceived usefulness and ease of use of the technology
TAM has often been used by various researchers to explore the individualsperceptions
toward the use of different technologies. The model comprises core constructs that measure
the usersmotivations to engage with a certain technology, namely, their perceived ease of
use,”“perceived usefulnessand attitudes.The outcome variables are the behavioral
intentions and technology usage (Scherer et al.,2019). Therefore, TAM seeks to explain why
people decide to accept or reject a technology (Davis, 1989;Lee et al.,2010). The individuals
perceived usefulness and their perceived ease of use are considered as key variables that
directly or indirectly explain the mentioned outcomes (Maranguni
c and Grani
c, 2015;
Rauniar et al., 2014). Davis (1989) dened the perceived ease of use as the degree to which a
person believes that using a particular system would be free from effort. The perceived
usefulness is the degree to which a person believes that using a particular system would
enhance his or her job performance (Davis, 1989). In other words, this construct determines
whether individuals would perceive the technology to be useful for what they want to do.
Various researchers reported that there is a positive relationship between the
perceived ease of use and the perceived usefulness (Nagy, 2018;Munoz-Leiva et al., 2017;
Niehaves and Plattfaut, 2014;Wallace and Sheetz, 2014;Joo and Sang, 2013;Liu et al.,
2010;Park, 2010;Davis et al., 1989). Relevant research on the topic of this study reported
that the perceived advantages of online streaming media were also inuenced by the
perceived ease of use of the technology (Tefertiller, 2020;Yang and Lee, 2018;Cha, 2013).
Previously, Rogers (2003) contended that individuals would use certain innovations if
they believe that they provide advantages over extant technologies. These theoretical
underpinning indicated that individuals may be intrigued to use certain technologies
(including online streaming services) if they are easy to use. Conversely, if the
SJME
technologies are complex, complicated or difcult to use, they would not perceive their
usefulness. Hence, this research hypothesizes:
H1. The individualsperceived ease of use of the online streaming technologies will
have a positive and signicant effect on their perceived usefulness.
The individualsperceived ease of use and their perceived usefulness of the technologies
precede their intentions to use them (Venkatesh et al.,2003;Venkatesh, 2000). Other studies
indicated that both the individualsperceived ease of use and their perceived usefulness of
certain technologies were found to have a positive and signicant effect on their intention to
use them (Joo and Sang, 2013;Jung et al., 2011;Venkatesh, 2000). Yang and Lees (2018)
study reported that the individualsperceived usefulness of streaming media devices was
positively associated with their behavioral intention to use them. This argumentation leads
to the following hypotheses:
H2. The individualsperceived ease of use of online streaming technologies will have a
positive and signicant effect on their intentions to use them.
H2a. The individuals perceived usefulness of online streaming technologies is mediating
the relationship between perceived ease of use and intention to use them.
H3. The individualsperceived usefulness of online streaming technologies will have a
positive and signicant effect on their intentions to use them.
TAM has been adapted and expanded by various scholars (Venkatesh and Davis, 2000;
Venkatesh, 2000). Many researchers argued that this model has limited predictive power
and its parsimony is one of its key constraint (Venkatesh et al.,2003;Venkatesh, 2000).
Benbasat and Barki (2007) held that TAM ignores the social processes of information
systems. Other researchers, including Legris et al. (2003) recommended that additional
variables from the innovation model ought to be integrated into TAM. Venkatesh and Davis
(2000) extended the original TAM model. They sought to clarify the notions of perceived
usefulness and usage intentions in terms of social inuences and cognitive instrumental
processes. Their revised model was referred to as TAM2. Afterward, Venkatesh et al. (2003)
rened TAM as they included new constructs, including facilitating conditions, social
inuences, as well as demographic variables in their unied theory of acceptance and use of
technology (or UTAUT). Eventually, Venkatesh and Bala (2008) proposed TAM3. This
model incorporated the effects of trust and perceived risk in the context of e-commerce
technologies. However, these TAM constructs appeared to be more applicable to using
technology for utilitarian motives rather than for hedonic purposes or intrinsic motivations
(Camilleri, 2019;Nikou and Economides, 2017;Vijayasarathy, 2004;Venkatesh, 2000).
2.2 The uses and gratications of the technology
The individualstechnology acceptance is inuenced by their extrinsic motivations,
including their perceived usefulness (Joo et al.,2018; Davis et al., 1989; Venkatesh and Davis,
2000). However, TAM did not include a construct that measured the individualsintrinsic
motivations. Hence, Venkatesh et al. (2012) extended the UTAUT as they included hedonic
motivation (along with price value), in addition to Venkatesh et al.s (2003) constructs. The
authors contended that many individuals seek intrinsic gratications when they use
certain technologies. The usersnon-utilitarian gratications, including enjoyment and
entertainment, can inuence their behavioral intentions to continue using technologies, such
as mobile devices (Camilleri and Camilleri, 2019;Nikou and Economides, 2017).
Online
streaming
services
UGT assumes that individuals use media technologies to enhance their gratications.
This theory is positivistic in its approach and holds heuristic value (Katz et al.,1973). It
seeks to explain why and how individuals are intrigued to use innovative technologies to
satisfy their specic needs and wants (Dhir et al., 2017a; Chen, 2011;Katz et al., 1973). Thus,
UGT has been widely used to explore the uses of various media, and to better understand
the consumersmotivations for using them. Of course, individuals would have different
motivations for using identical media, and may also exhibit divergent levels of
gratications.
In the past, UGT was considered as an extension of the needs and motivations theory
(Ray et al.,2019;Nikou, and Economides, 2017;Katz et al.,1973). Its measures were often
used to explore the individualsintentions to watch specic programs on television (Stafford
et al.,2004;Harwood, 1999) or to investigate their engagement with digital media, including
internet technologies (Kaur et al.,2020;Shao, 2009;Flavi
an and Gurrea, 2008) and social
media (Dhir et al., 2017a; Mäntymäki and Riemer, 2014;Smock et al.,2011). For example,
Sanz-Blas et al. (2019),aswellasMäntymäki and Islam (2016) have used UGT to shed light
on the adverse effects of social media on teenagers. Other researchers relied on this model to
examine the individualsgratications from mobile instant messaging (Kaur et al.,2020),
food delivery apps (Ray et al.,2019) and digital photo sharing with other social media
subscribers (Malik et al., 2016), among other contemporary topics.
Various studies suggested that individuals are using technologies for different reasons,
including to satisfy their own social and psychological needs (Dhir et al., 2016). Online users
use digital media technologies to access information or to share it with their followers
(Troise and Camilleri, 2020). Others use technologies to buy products (Talwar et al.,2020;
Kaur et al.,2020;Ray et al.,2019) or for entertainment purposes (Kuoppamäki et al., 2017;
Dhir and Torsheim, 2016). Alternately, they use them to communicate, build relationships or
seek affection (Malik et al., 2016;Leung,2015, 2013;Whiting and Williams, 2013).
Some researchers have focused on instant messaging (Ku et al., 2013;Lo and Leung,
2009), on blogging (Hollenbaugh, 2011;Shao, 2009) and on the creation of user generated
content (Herrero and San Martín, 2017;Ye et al., 2011;Van Dijck, 2009). Very often, their
studies shed light on how and why individuals hailing from various demographics and
backgrounds in society (in terms of different genders, age groups and educational levels)
were using these technologies. For instance, individuals may use their mobile devices to
access content (instrumentality) when they are out and about (mobility). Mobile technologies
provide immediate access to a wide array of online information including written content,
images and videos (e.g. via YouTube) (Khan, 2017). Smartphones and tablets allow their
users to entertain themselves by playing games and/or to socialize with other individuals
through social media (Calvo-Porral and Otero-Prada, 2020;Camilleri, 2020;Hajarian et al.,
2020;Calvo-Porral and Nieto-Mengotti, 2019;Dolan et al.,2019;Balakrishnan and Raj, 2012).
Individuals are increasingly subscribing to social media as they offer them different
gratications (Dolan et al.,2019;Dhir et al., 2017a;Khan, 2017).
Relevant theoretical underpinnings indicated that the internet provides three types of
gratications, including content gratication, process gratication and social gratication (Li
et al., 2017;Stafford et al., 2004). Individuals can use the internet to search for specic
information. In the meantime, they may enjoy the browsing process during their online
searches (Perks and Turner, 2019;Huang, 2008). Alternately, they may use the internet for
socializing purposes, as it enables them to connect with family, friends and acquaintances.
Several empirical studies have examined the internetspositive(gratications) and its negative
outcomes. For example, LaRose and Eastin (2004) relied on Banduras (1991) social-cognitive
approach to investigate the internet usersself-efcacy and their self-disparagement.
SJME
Other research investigated the individualsgratications from social networking
services (SNS) including Facebook, Instagram, Twitter and Linkedin, as well as blogs and
review websites (Bevan-Dye, 2020;Capriotti et al.,2020;Belanche et al.,2019;Sanz-Blas et al.,
2019;Leung, 2013;Park et al., 2009). Many authors have used UGT to explore the
gratications of social media subscribers as more individuals are becoming devoted,
engaged and highly motivated to upload content in specic SNS services (Rios Marques
et al.,2020;Malik et al.,2016). They are also listening to music and watching videos (Khan,
2017;Krause et al., 2014), sharing links (Baek et al.,2011), participating in groups (Karnik
et al., 2013;Park et al.,2009), sharing news (Lee and Ma, 2012) and photos (Malik et al.,2016)
through social media.
Online users are engaging with other individuals through social media to fulll their
socio-cognitive needs or simply to express their feelings. They have different
motivations to use them, including for narcistic, socialization, recognition (status) and/
or for entertainment purposes. It goes without saying that individuals also seek
emotional gratications from traditional media, including television and cinemas (Li,
2017;Bartsch, 2012). They engage with different media to distract themselves into a
better mood (Zillmann, 2000). Lonsdale and North (2011) reported that adolescents tend
to regulate their moods by listening to music. Other authors went on to suggest that
media entertainment provide efcient stimuli to individuals to adjust their moods
(Smock et al., 2011;Park et al., 2009;Bumgarner, 2007;Knobloch, 2003)ortoescape
from emotional difculties (Greenwood and Long, 2011;Greenwood, 2008). Hence,
individuals use specic media to satisfy their needs for information and for
entertainment purposes (Lee et al., 2010;Quan-Haase and Young, 2010;Bumgarner,
2007). They may use media technologies, including mobile devices on a habitual basis
and/or when they have time to spare (Smock et al.,2011).
In this light, this research explores the effect of the individuals’“ritualized use
and of their instrumental useof online streaming technologies (Leung, 2015;Joo and
Sang, 2013;Cooper and Tang, 2009). This study has adapted Joo and Sangs (2013)
theoretical framework that they used to explore the usage of smartphone devices. In
this case, this empirical investigation is focused on the individualsconsumption
behaviors of online streaming technologies through digital and mobile devices. UGT
was used to explore the individualsmotivations toward online streaming services
that can be accessed through smart TVs, smartphones and tablets. This study
hypothesizes that:
H4. The individualsmotivations to use online streaming technologies for ritual
purposes, will have a positive and signicant effect on their intentions to use the
mentioned technologies.
H5. The individualsmotivation to use online streaming technologies for instrumental
purposes, will have a positive and signicant effect on their intention to use of the
mentioned technologies.
Our approach assumes that our respondents:
used smart TVs, smartphones and/or tablets;
were experienced with the use of these technologies (this helped them make
motivated choices); and
were using online streaming services to watch live broadcasts and/or recorded
videos. Figure 1 illustrates the hypothesized relationships of this research.
Online
streaming
services
3. Methodology
The data was gathered via an online survey questionnaire that was disseminated among higher
education students in a Southern European university. A stratied sampling approach was used
to select the survey sample. There were more than 10,000 students who were pursuing full time
and part time courses in this institution, who had voluntarily given their consent to receive
requests to participate in academic studies. The targeted research participants received an email
from the university registrar that comprised a hyperlink to this studys survey questionnaire.
There were 491 respondents who have completed their questionnaire.
This study complied with the research ethic policies of this institution and with the EUs
general data protection regulation. The research participants indicated the extent of their
agreement with the survey items in a ve-point Likert scale. The responses ranged from 1
strongly disagreeto 5 = strongly agreeand 3 signaled an indecision. In the latter part of the
questionnaire, the participants were expected to disclose their age by choosing one of ve age
groups. They indicated their gender that were coded by using the 1 or 0 dummy variable,
where 1 represented the women. The questionnaire was pilot tested among a small group of
postgraduate students (who were not included in the survey results) to reduce the plausibility
ofthecommonmethodbias,asperMacKenzie and Podsakoffs (2012) recommendations.
3.1 The measures
The survey instrument has adapted measuring items from Davis(1989) TAM and from
Katz et al. (1973) UGT. The participants were expected to indicate their level of agreement
on the survey items that explored their motivations and perceptions toward the use of online
streaming programs. The constructs included motivation for ritualized use,”“motivation
for instrumental use,”“perceived usefulness,”“perceived ease of useand intention to use
online streaming technologies.These constructs were tried and tested in several other
studies, and in other contexts (Tefertiller, 2020;Yang and Lee, 2018;Nagy, 2018;Munoz-
Leiva et al.,2017;Kaur, Dhir, Chen, Malibari and Almotairi, 2020;Dhir et al., 2017a,2017b;
Joo and Sang, 2013). The measuring items that were used in this study are presented in
Table 1.
Figure 1.
The conceptual
model and the
formulation of
hypotheses
H2/H2a H4
H1
H3 H5
Perceived Ease
of Use
Ritualized Use
Intention to Use
Perceived
Usefulness
Instrumental
Use
SJME
3.2 The demographic prole of the respondents
The participants provided their socio-demographic details about their gender,”“ageand
indicated the coursethat they were studying in the latter part of the survey questionnaire.
Their identity remained anonymous and their responses were kept condential. Only
aggregate information was used during the analysis of the data. More than two-thirds of the
respondents were women. The sample consisted of 339 women (69%) and 152 men (31%).
There were two individuals who did not indicate their gender. Most of the respondents
(n= 226, 46%) were between 18 and 21years of age. The second largest group (n= 114,
23%) were between 22 and 25 years old. The majority of respondents were pursuing courses
in the faculties of arts (14%), economics, management and accountancy (13%) and applied
sciences (12%). However, the sample included respondents from all areas of studies.
4. Results
4.1 Descriptive statistics
The respondents agreed with the survey items in the model, as the mean scores (M) were
above the mid-point of 3. The highest mean scores were reported for IU2 (M = 4.273), PU1
(M = 4.184) and PEoU (M = 4.167). Whilst INT2 reported the lowest mean score (M = 3.462).
The standard deviations (SD) ranged indicated that there was a narrow spread around the
mean. The values of the SD ranged from 0.696 (for IU2) to 1.112 (for INT1).
4.2 Conrmatory composite analysis
This study relied on a structural equation modeling (SEM) approach to explore the
measurement quality of this research model (Ringle et al.,2014). SEM-partial least squares
(PLS) 3 conrmatory composite analysisalgorithm revealed the results of the reective
measurement model (Hair et al.,2020).
Table 1.
The measuring items
Motivation for ritualized use
RU1 I watch online streaming services to break the routine
RU2 I watch online streaming services in my free time
RU3 Watching online streaming services is a form of entertainment
Motivation for instrumental use
IU1 I watch informative programs, including news and talk shows through online streaming services
IU2 I watch entertainment programs, including movies and series through online streaming services
IU3 I watch online streaming services as they offer advertising options, e.g. no advertising, limited
advertising or all advertising will be presented in free viewing mode
Perceived ease of use
PEOU1 It is an easy task for me to access the online streaming services of live or recorded programs
PEOU2 I nd it easy to access online streaming services through digital and mobile devices, including
smart TVs, smartphones and tablets
Perceived usefulness
PU1 The online streaming services allow me to view what I want in a faster way than traditional TV
subscriber services
PU2 The online streaming services enhance my experience of watching informative or entertainment
programs
PU3 I can watch online streaming services in any place I like if there is a good Wi-Fi or network connection
Intention to use
INT1 I will continue using digital and mobile devices, including smart TVs, smartphones and tablets
to watch online streaming
INT2 I shall spend more money on digital and mobile devices to access informative and entertainment
programs through online streaming services
Online
streaming
services
The values of the standardized loadings were higher than the recommended threshold of
0.7 (Hair et al., 2020) and had an associated t-statistic above 61.96. The composite reliability
values were between 0.821 and 0.929. The values of average variance extracted (AVE)
conrmed the constructsconvergent validities as it explained more than 50 % of the
variance of their items. In other words, the values for AVE were higher than 0.5 (Hair et al.,
2011). There was evidence of discriminant validity as the square root value of AVE was
greater than the correlation values among the latent variables (Fornell and Larcker, 1981).
This study also examined heterotrait-monotrait (HTMT) ratio of the correlations, thus it re-
conrmed the presence of discriminant validity across the constructs. The HTMT values
were lower than 0.9 (Henseler et al., 2015) as shown in Table 2.
4.3 Structural model assessment
The assessment criteria involved an examination of the collinearity among the constructs.
The results indicated that there were no collinearity issues as the variance ination factors
have exceeded the recommended threshold of 3.3 (Hair et al., 2020). The PLS algorithm
revealed the models predictive power, in terms of the coefcient of determination (R
2
) of the
endogenous latent variables. It also shed light on the effect (¾
2
) of each exogenous construct
on the endogenous constructs.
Afterward, a bootstrapping procedure was used to explore the statistical signicance
and relevance of the path coefcients. The signicance of the hypothesized path coefcients
in the inner model were evaluated by using a two-tailed t-test at the 5% level (Hair, Ringle
and Sarstedt, 2011). Table 3 presents the results of the hypotheses of this study. It tabulates
the ndings of the standardized beta coefcients (original sample and sample mean), the
condence intervals, ¾
2
,t-values and the signicance values (p). Table 4 features the results
of the mediating relationship.
H1: This study reported that there was a positive and signicant effect between the
individualsperceived ease of use and the perceived usefulness of the streaming
technologies, where
b
= 0.424, t= 10.086 and p<0.001. This result validates the TAM. The
Table 2.
A correlation
analysis and an
assessment of the
composite reliability,
convergent validity
and discriminant
validity
Outer
Construct Items Loadings CR AVE 1 2 3 4 5
1 Instrumental use IU1 0.831 0.821 0.607
IU2 0.822 0.779 0.442 0.737 0.402 0.609
IU3 0.676
2 Intention Int1 0.938 0.929 0.868 0.338 0.932 0.485 0.808 0.703
Int2 0.926
3 Perceived ease of use PEoU1 0.92 0.925 0.861 0.572 0.411 0.928 0.507 0.555
PEoU2 0.936
4 Perceived usefulness PU1 0.83 0.894 0.737 0.303 0.676 0.424 0.859 0.686
PU2 0.88
PU3 0.865
5 Ritualized use RU1 0.863 0.852 0.659 0.44 0.555 0.438 0.533 0.812
RU2 0.85
RU3 0.714
Notes: The discriminant validity was calculated by using the Fornell-Larcker criterion. The values of square
root of the AVE were presented in bold font. The AVEs for each construct were greater than the correlations
among the constructs. The shaded area features the results from the HTMT criterion (Henseler et al.,2015)
SJME
ndings suggest that the individuals who perceived the ease of use of these online
technologies will probably perceive their usefulness as well. H2 revealed that there was no
direct relationship between the individualsperceived ease of use of the streaming
technologies and their intention to use them. However, there was an indirect effect of
perceived usefulness on perceived ease of use intentions link. The mediating analysis
reported that there was full mediation from the perceived usefulness construct on this
relationship as
b
= 0.285, t= 7.396 and p<0.001. H3 indicated there was a positive and
direct relationship between the respondentsperceived usefulness of the streaming
technologies and their intentions to use them, where
b
= 0.509, t= 13.48 and p<0.001. H4:
The ndings suggest that the participantsmotivations for the ritualized use of the streaming
technologies (to watch entertaining programs such as movies and/or recorded TV series) was a
signicant antecedent of their intentions to use the mentioned technologies, where
b
= 0.236,
t= 5.678 and p<0.001. In conclusion, the ndings from H5 show that the students
instrumental motivations to use live streaming technologies (e.g. to watch the news and/or
informative programs) was not a signicant precursor of their intentions to use them.
The results indicated that there were signicant f
2
values between perceived usefulness
and intention f
2
= 0.360 and between perceived ease of use and perceived usefulness
(f
2
= 0.219). Figure 2 sheds light on the explanatory power of this research model. It
Table 3.
Testing of the
hypotheses
Path coefficient
Confidence
t-
value pDecision
Original
Sample
Sample
Mean
Intervals Bias
corrected
f
square
H1 Perceived ease of use !
perceived usefulness
0.424 0.422 [0.345, 0.497] 0.219 10.086 0.000 Supported
H2 Perceived ease of use !
intention to use streaming
technologies
0.069 0.068 [0.009, 0.158] 0.006 1.695 0.091 Not
supported
H3 Perceived usefulness !
intention to use streaming
technologies
0.509 0.508 [0.434, 0.577] 0.360 13.480 0.000 Supported
H4 Ritualized use !intention to
use streaming technologies
0.236 0.235 [0.152, 0.322] 0.072 5.678 0.000 Supported
H5 Instrumental use !intention
to use streaming technologies
0.041 0.044 [0.037, 0.136] 0.002 0.940 0.348 Not
supported
Table 4.
Mediating effects
Path coefficient
Direct
effect
Indirect
effect
Total
effect
Confidence
Intervals
Bias
corrected
t-
value pDecision
H2 Perceived ease of use !
intention
0.069*
0.285 [0.162, 0.277] 7.396 0.000H2a Perceived ease of use !
perceived usefulness !
intention
0.216 Supported (full
mediation)
Notes: *The direct effect was not signicant, p= 0.091. The total effect (including the effect from the
mediating construct) was very signicant, where p<0.001
Online
streaming
services
illustrates the total effects, outer loadings and the coefcient of determination (R
2
) values of
the constructs. The studentsindicated that they were committed to continue using the
online streaming technologies (R
2
= 0.517) as they perceived its usefulness (R
2
= 0.179).
5. Conclusions
5.1 Theoretical implications
This contribution explored the individualsmotivations to use streaming technologies to
watch live broadcast programs and/or recorded content (Tefertiller,2020, 2018;Steiner and
Xu, 2018;Panda and Pandey, 2017;Sørensen, 2016;Groshek and Krongard, 2016). It
differentiated itself from other research, as it integrated valid measures that were drawn
from TAM (Nagy, 2018;Munoz-Leiva et al., 2017;Niehaves and Plattfaut, 2014;Cha, 2013;
Davis, 1989) and UGT (Steiner and Xu, 2018;Riddle et al.,2018;Joo and Sang, 2013;Bondad-
Brown et al., 2012;Katz et al.,1973).
The critical review of the relevant literature reported that both theories were widely used
(and cited) in academia to investigate the individualsbehavioral intentions to adopt new
technologies, in different contexts (Manis and Choi, 2019;Liu et al., 2010;Benbasat and
Barki, 2007). In essence, TAM suggests that the individualsperceptions about the ease of
use and the usefulness of certain technologies would predict their intentions to use them
again in the future (Scherer et al.,2019;Munoz-Leiva et al.,2017;Rauniar et al.,2014;Wallace
and Sheetz, 2014; Davis et al., 1989; Davis, 1989). Moreover, UGT assumes that individuals
seek to gratify their intrinsic and extrinsic needs through habitual consumptions of media
technologies (Kaur et al., 2020;Perks and Turner, 2019;Ray et al., 2019;Li et al.,2017;Joo
and Sang, 2013;Bartsch, 2012;Chen, 2011;Smock et al.,2011;Stafford et al.,2004;Katz et al.,
1973).
The ndings from this research indicated that the research participants perceived the
ease of use and the usefulness of the streaming technologies. The results conrmed that they
found it easy and straightforward to use their smart TVs, smartphones or tablets to access
online streaming services. The respondents believed that the streaming technologies
allowed them to view TV programs and/or recorded videos in a faster way than traditional
TV subscriber services or satellite TV. They perceived the usefulness of online TV and/or
Figure 2.
A graphical
illustration of the
results
SJME
video streaming services, as they enhanced their experience of watching informative and/or
entertainment programs, particularly when they used their mobile devices (Nikou and
Economides, 2017;Balakrishnan and Raj, 2012). Hence, the research participants were
committed to continue using their smart devices to access their favorite online programs
through streaming technologies. The regression analysis revealed that there were highly
signicant correlations between TAMs core constructs including the perceived ease of use
and the perceived usefulness of online streamingservices. Both of these constructs were also
signicant antecedents of the individualsintentions to continue using the mentioned
technologies.
The individualsritualized motivations to use the streaming technologies were found to
have a very signicant effect on their intention to use them. The respondents were using
online streaming technologies on a habitual basis, to break the routine. These ndings are
consistent with the relevant literature concerning UGT, where the researchers concluded
that many often, individuals consider the media technologies as a form of entertainment
(Dhir et al., 2017b;Li, 2017;Bartsch, 2012;Smock et al.,2011) as individuals. In this case, the
research participants sought emotional gratications from the streaming technologies.
Probably, they allowed them to relax in their free time. Other theoretical underpinnings
reported that individuals use certain technologies to distract themselves into a better mood
(Lonsdale and North, 2011; Park et al.,2009;Knobloch, 2003;Zillmann, 2000). Most of the
respondents indicated that they were using these technologies to satisfy their needs for
information and entertainment. These ndings are consistent with previous studies (Lee
et al.,2010;Quan-Haase and Young, 2010;Bumgarner, 2007).
The survey respondents revealed that they used online streaming technologies for
instrumental purposes to watch informative programs, including news and talk shows, as
well as entertainment programs, including movies and series through online streaming
services. Other researchers also reported that there were many instances where individuals
beneted of their smartphones and tabletsinstrumentality and mobility, as they enabled
them to access online content, including recorded videos, live streams and/or intermittent
marketing content,when they were out and about.
The participants indicated their agreement with the survey item about the advertising
options of online streaming services. This research suggests that they were aware that
subscribed users of online streaming technologies can limit or block intrusive and/or
repetitive advertisements they receive whilst using online streaming technologies (Belanche
et al.,2019). Previous studies also reported that online users were increasingly applying ad
blockers (Redondo and Aznar, 2018;Lim et al.,2015). The practitioners who are using digital
marketing platforms, including online streaming websites to promote their products and/or
services, ought to rene the quality and content of their customer centric marketing. Their
underlying objective is to engage their audiences with relevant, helpful information that
complements, rather than detracts from their overall online experience.
5.2 Practical implications
This research postulates that the respondents are consuming free-tier and/or paid streaming
services through different digital media including mobile devices such as smartphones and
tablets. It conrmed that online streaming technologies can improve the consumers
experiences of watching live broadcasts and/or recorded programs. The research
participants perceived their ease of use and their usefulness as they can be accessed in any
place, at any time, through decent Wi-Fi and/or network connections. The ndings are
consistent with the U&G theory as the participants indicated that the media technologies
were entertaining. Hence, they were committed to continue using them. They indicated that
Online
streaming
services
they would continue using them in the foreseeable future. On the other hand, this study
revealed that the respondentsinstrumental motivations to use online streaming services did
not predict their intentions to use them (even though these technologies allowed their
subscribers to limit or block online advertisements).
Most probably, the respondents were accessing on-demand streaming services in the
comfort of their home, rather than from mobile technologies, when they were out and about.
The reason for this behavior could be that they prefer watching online programs through
big screens as opposed to watching them through their mobile devicessmaller screens. The
latest TVs may offer quality, high resolution images and better sound than smartphones
and tablets. Thus, smart TVs (that are using Apple and/or Android systems, etc.) may be
considered more appropriate to watch recorded movies and/or TV series. It is very likely
that the participants would also perceive the ease of use and the usefulness of these
technologies for other purposes, including digital gaming, video conferencing, et cetera.
Recently, the unprecedented outbreak of the Coronavirus pandemic and its preventative
social distancing measures has led to a considerable increase in the use of digital media
(Camilleri, 2020). There was also a surge in the subscriptions to paid streaming services
(Marketwatch, 2020). As a result, more digital advertisements (ads) were featured in online
streaming services. They are usually presented to free tier consumers as skippable or non-
skippable streaming or static ads that appear before, during or after they access online
broadcasts and/or recorded programs. Alternately, online users may decide to subscribe to
the streaming services, if they want to block the marketing messages they receive
(Tefertiller, 2020;Kim et al., 2017). This way, they could have more control over their online
experience.
There are several media companies in the market that are offering competitive streaming
packages. Very often, they are producing new programs, including movies, series, et cetera.
Consumers may be intrigued to upgrade their services to benet of secure, reliable, low
latency streaminginfrastructures and to gain access to more exclusive content in an ad-free,
interactive environment. They may also appreciate if the service providers would increase
their engagement with them by using customer-centric recommender systems. Consumers
may be informed about their favorite programs through regular notications to their mobile
apps (if they subscribe to them). These alerts ought to be related to their personal
preferences. As a result, the consumers would continue entertaining themselves with online
streaming technologies as they perceive their instrumentality, ease of use and the usefulness
of their services.
6. Limitations and future research avenues
This research investigated the individualsattitudes and perceptions toward online streaming
of recorded movies, series or lives television programs, including news, entertainment shows,
quizzes, et cetera. This contribution did not specify whether they were accessing free or paid
online streaming. Therefore, further research can distinguish among different service providers
of online streaming, and those that are operating in different settings. This research was carried
out among university students, who were mostly young women. The respondents attended a
higher education institution from a Southern European context. The researchers decided not to
tweak the data to correct for age or gender imbalance.
Future studies may consider different constructs from other theoretical models to explore
the individualsacceptance and motivations to use online streaming technology. Although
there are many researchers who have appraised and used TAMs and UGTs measures,
others have indicated that their measures have inherent limitations, as reported within the
literature review section of this paper. Perhaps, further research may involve interpretative
SJME
studies to investigate the individualsin-depth opinions and beliefs on the latest
developments in broadcast media. Inductive studies can reveal other important factors
about the individualsconsumption behaviors, and may probably shed more light on why,
where, when and how they are using online streaming technologies. This way, service
providers of recorded video content and/or live broadcasts will be in a better position to
understand their audiencesexpectations.
References
Aldea, P.G. and Vidales, N.L., (2012), Television consumption trends among the digital generationin
Spain,International Journal of Iberian Studies, Vol. 25 No. 2, pp. 111-134.
Baek, K., Holton, A., Harp, D. and Yaschur, C. (2011), The links that bind: uncovering novel
motivations for linking on Facebook,Computers in Human Behavior, Vol. 27 No. 6,
pp. 2243-2248.
Balakrishnan, V. and Raj, R.G. (2012), Exploring the relationship between urbanized Malaysianyouth
and their mobile phones: a quantitative approach,Telematics and Informatics, Vol. 29 No. 3,
pp. 263-272.
Bandura, A. (1991), Social cognitive theory of self-regulation,Organizational Behavior and Human
Decision Processes, Vol. 50 No. 2, pp. 248-287.
Bartsch, A. (2012), Emotional gratication in entertainment experience. Why viewers of movies and
television series nd it rewarding to experience emotions,Media Psychology, Vol. 15 No. 3,
pp. 267-302.
Belanche, D., Cenjor, I. and Pérez-Rueda, A. (2019), Instagram stories versus Facebook wall: an
advertising effectiveness analysis,Spanish Journal of Marketing ESIC, Vol. 23 No. 1,
pp. 69-94.
Benbasat, I. and Barki, H. (2007), Quo vadis, TAM?,Journal of the Association for Information
Systems, Vol. 8 No. 4, pp. 211-218.
Bevan-Dye, A.L. (2020), Antecedents of generation Y consumersusage frequency of online
consumer reviews,Spanish Journal of Marketing ESIC, Vol. 24 No. 2, doi: 10.1108/SJME-
12-2019-0102.
Bondad-Brown, B.A., Rice, R.E. and Pearce, K.E. (2012), Inuences on TV viewing and online
user-shared video use: demographics, generations, contextual age, media use, motivations,
and audience activity,Journal of Broadcasting and Electronic Media,Vol.56No.4,
pp. 471-493.
Bumgarner, B.A. (2007), You have been poked: exploring the uses and gratications of Facebook
among emerging adults,First Monday, Vol. 12 No. 11, available at: www.rstmonday.dk/ojs/
index.php/fm/article/view/2026
Calvo-Porral, C. and Nieto-Mengotti, M. (2019), The moderating inuence of involvement with ICTs in
mobile services,Spanish Journal of Marketing ESIC, Vol. 23 No. 1, pp. 25-43.
Calvo-Porral, C. and Otero-Prada, L. (2020), A prole of mobile service users in a mature market: from
uninvolved pragmatics to potential switchers,Spanish Journal of Marketing ESIC, doi:
10.1108/SJME-03-2020-0046.
Camilleri, M.A. (2019), The online usersperceptions toward electronic government services,Journal
of Information, Communication and Ethics in Society, Vol. 18 No. 2, pp. 221-235.
Camilleri, M.A. (2020), Strategic dialogic communication through digital media during COVID-19
crisis, in Camilleri, M.A. (Ed.), Strategic Corporate Communication in the Digital Age, Emerald,
Bingley.
Camilleri, M.A. and Camilleri, A.C. (2019), The studentsreadiness to engage with mobile learning
apps,Interactive Technology and Smart Education, Vol. 17 No. 1, pp. 28-38.
Online
streaming
services
Capriotti, P., Zeler, I. and Camilleri, M.A. (2020), Corporate communication through social networks:
the identication of the key dimensions for dialogic communication, in Camilleri, M.A. (Ed.),
Strategic Corporate Communication in the Digital Age, Emerald, Bingley.
Cha, J. (2013), Predictors of television and online video platform use: a coexistence model of old and
new video platforms,Telematics and Informatics, Vol. 30 No. 4, pp. 296-310.
Chen, G.M. (2011), Tweet this: a uses and gratications perspective on how active twitter use graties
a need to connect with others,Computers in Human Behavior, Vol. 27 No. 2,pp. 755-762.
Cooper, R. and Tang, T. (2009), Predicting audience exposure to television in todays media
environment: an empirical integration of active-audience and structural theories,Journal of
Broadcasting and Electronic Media, Vol. 53 No.3, pp. 400-418.
Davis, F.D. (1989), Perceived usefulness, perceived ease of use, and user acceptance of information
technology,MIS Quarterly, Vol. 13 No. 3, pp. 319-340.
Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1989), User acceptance of computer technology: a
comparison of two theoretical models,Management Science, Vol. 35 No. 8, pp. 982-1003.
Dhir, A. and Torsheim, T. (2016), Age and gender differences in photo tagging gratications,
Computers in Human Behavior, Vol. 63, pp. 630-638.
Dhir, A., Chen, S. and Nieminen, M. (2016), The effects of demographics, technology accessibility, and
unwillingness to communicate in predicting internet gratications and heavy internet use
among adolescents,Social Science Computer Review, Vol. 34 No. 3, pp. 278-297.
Dhir, A., Khalil, A., Lonka, K. and Tsai, C.C. (2017a), Do educational affordances and gratications
drive intensive Facebook use among adolescents?,Computers in Human Behavior, Vol. 68,
pp. 40-50.
Dhir, A., Chen, G.M. and Chen, S. (2017b), Why do we tag photographs on Facebook? Proposing a new
gratications scale,New Media and Society, Vol. 19 No. 4, pp. 502-521.
Dolan, R., Conduit, J., Frethey-Bentham, C., Fahy, J. and Goodman, S. (2019), Social media engagement
behavior: a framework for engaging customers through social media content,European Journal
of Marketing, Vol. 53 No. 10, pp. 2213-2243.
eMarketer (2019), Nearly half of TV viewers browse online while watching their favorite movies and
shows, eMarketer, available at: www.emarketer.com/content/nearly-half-of-tv-viewers-browse-
online-while-watching-their-favorite-movies-shows
Flavi
an, C. and Gurrea, R. (2007), Perceived substitutability between digital and physical channels: the
case of newspapers,Online Information Review, Vol. 31 No.6, pp. 793-813.
Flavi
an, C. and Gurrea, R. (2008), Reading newspapers on the internet: the inuence of web sites
attributes,Internet Research, Vol. 18 No. 1,pp. 26-45.
Fornell, C. and Larcker, D.F. (1981), Structural equation models with unobservable variables and
measurement error: algebra and statistics,Journal of Marketing Research, Vol. 18 No. 3,
pp. 382-388.
Greenwood, D.N. (2008), Television as escape from self: psychological predictors of media
involvement,Personality and Individual Differences, Vol. 44 No. 2, pp. 414-424.
Greenwood, D.N. and Long, C.R. (2011), Attachment, belongingness needs, and relationship status
predict imagined intimacy with media gures,Communication Research, Vol. 38 No. 2,
pp. 278-297.
Groshek, J. and Krongard, S. (2016), Netix and engage? Implications for streaming television on
political participation during the 2016 US presidential campaign,Social Sciences, Vol. 5 No. 4,
pp. 65-83.
GWI (2019), Digital versus traditional media consumption. Global web index trend report 2019,
Global Web Index, available at: www.globalwebindex.com/reports/traditional-vs-digital-media-
consumption
SJME
Hair, Jr J.F., Howard, M.C. and Nitzl, C. (2020), Assessing measurement model quality in PLS-SEM
using conrmatory composite analysis,Journal of Business Research, Vol. 109, pp. 101-110.
Hair, J.F., Ringle, C.M. and Sarstedt, M. (2011), PLS-SEM: Indeed a silver bullet,Journal of Marketing
Theory and Practice, Vol. 19 No. 2, pp. 139-152.
Hajarian, M., Camilleri, M.A., Díaz, P. and Aedo, I. (2020), A taxonomy of online marketing methods,
in Camilleri, M.A. (Ed.) Strategic Corporate Communication in the Digital Age, Emerald, Bingley.
Harwood, J. (1999), Age identication, social identity gratications, and television viewing,Journal of
Broadcasting and Electronic Media, Vol. 43 No.1, pp. 123-136.
Henseler, J., Ringle, C.M. and Sarstedt, M. (2015), A new criterion for assessing discriminant validity in
variance-based structural equation modeling,Journal of the Academy of Marketing Science,
Vol. 43 No. 1, pp. 115-135.
Herrero, Á. and San Martín, H. (2017), Explaining the adoption of social networks sites for sharing
user-generated content: a revision of the UTAUT2,Computers in Human Behavior, Vol. 71,
pp. 209-217.
Hirsjärvi, I. and Tayie, S. (2011), Children and new media: youth media participation. A case study of
Egypt and Finland,Comunicar, Vol. 19 No. 37, pp. 99-108.
Hollenbaugh, E.E. (2011), Motives for maintaining personal journal blogs,Cyberpsychology, Behavior,
and Social Networking, Vol. 14 Nos 1/2, pp. 13-20.
Huang, E. (2008), Use and gratication in e-consumers,Internet Research, Vol.18 No. 4, pp. 405-426.
Jenner, M. (2016), Is this TVIV? On Netix,New Media and Society, Vol. 18 No. 2, pp.257-273.
Joo, J. and Sang, Y. (2013), Exploring Koreanssmartphone usage: an integrated model of the
technology acceptance model and uses and gratications theory,Computers in Human
Behavior, Vol. 29 No. 6, pp.2512-2518.
Joo, Y.J., So, H.J. and Kim, N.H. (2018), Examination of relationships among studentsself-
determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs,
Computers and Education, Vol. 122, pp. 260-272.
Jung, J., Chan-Olmsted, S., Park, B. and Kim, Y. (2011), Factors affecting e-book reader awareness,
interest, and intention to use,New Media and Society, Vol. 14 No. 2, pp.204-224.
Karnik, M., Oakley, I., Venkatanathan, J., Spiliotopoulos, T. and and Nisi, V. (2013), Uses and
gratications of a Facebook media sharing group,In Proceedings of the 2013 Conference on
Computer Supported Cooperative Work. ACM, New York, NY, pp. 821-826.
Katz, E., Blumler, J.G. and Gurevitch, M. (1973), Uses and gratications research,Public Opinion
Quarterly, Vol. 37 No. 4, pp.509-523.
Kaur, P., Dhir, A., Chen, S., Malibari, A. and Almotairi, M. (2020), Why do people purchase virtual
goods? A uses and gratication (U&G) theory perspective,Telematics and Informatics, Vol. 53,
available at: www.sciencedirect.com/science/article/pii/S0736585320300356
Khan, M.L. (2017), Social media engagement: what motivates user participation and consumption on
YouTube?,Computers in Human Behavior, Vol. 66, pp. 236-247.
Kim, J., Nam, C. and Ryu, M.H. (2017), What do consumers prefer for music streaming services? A
comparative study between Korea and US,Telecommunications Policy, Vol. 41 No. 4,
pp. 263-272.
Knobloch, S. (2003), Mood adjustment via mass communication,Journal of Communication, Vol. 53
No. 2, pp. 233-250.
Kostyrka-Allchorne, K., Cooper, N.R. and Simpson, A. (2017), The relationship between television
exposure and childrens cognition and behaviour: a systematic review,Developmental Review,
Vol. 44, pp. 19-58.
Krause, A.E., North, A.C. and Heritage, B. (2014), The uses and gratications of using Facebook music
listening applications,Computers in Human Behavior, Vol. 39, pp. 71-77.
Online
streaming
services
Ku, Y.C., Chu, T.H. and Tseng, C.H. (2013), Gratications for using CMC technologies: a comparison
among SNS, IM, and e-mail,Computers in Human Behavior, Vol. 29 No.1, pp. 226-234.
Kuoppamäki, S.M., Taipale, S. and Wilska, T.A. (2017), The use of mobile technology for online
shopping and entertainment among older adults in Finland,Telematics and Informatics, Vol. 34
No. 4, pp. 110-117.
LaRose, R. and Eastin, M.S. (2004), A social cognitive theory of Internet uses and gratications: toward
a new model of media attendance,Journal of Broadcasting & Electronic Media, Vol. 48 No. 3,
pp. 358-377.
Lee, H., Kim, D., Ryu, J. and Lee, S. (2010), Acceptance and rejection of mobile TV among young
adults: a case of college students in South Korea,Telematics and Informatics, Vol. 28 No. 4,
pp. 239-250.
Lee, C.S. and Ma, L. (2012), News sharing in social media: the effect of gratications and prior
experience,Computers in Human Behavior, Vol. 28 No. 2, pp. 331-339.
Legris, P., Ingham, J. and Collerette, P. (2003), Why do people use information technology? A critical
review of the technology acceptance model,Information & Management, Vol. 40 No. 3,
pp. 191-204.
Leung, L. (2013), Generational differences in content generation in social media: the roles of the
gratications sought and of narcissism,Computers in Human Behavior, Vol. 29 No. 3,
pp. 997-1006.
Leung, L. (2015), Using tablet in solitude for stress reduction: an examination of desire for aloneness,
leisure boredom, tablet activities, and location of use,Computers in Human Behavior, Vol. 48,
pp. 382-391.
Li, S.C.S. (2017), Television media old and new: a niche analysis of OTT, IPTV, and digital cable in
Taiwan,Telematics and Informatics, Vol. 34 No.7, pp. 1024-1037.
Li, Q., Guo, X. and Bai, X. (2017), Weekdays or weekends: exploring the impacts of microblog posting
patterns on gratication and addiction,Information and Management, Vol. 54 No. 5,
pp. 613-624.
Lim, J.S., Ri, S.Y., Egan, B.D. and Biocca, F.A. (2015), The cross-platform synergies of digital video
advertising: implications for cross-media campaigns in television, internet and mobile TV,
Computers in Human Behavior, Vol. 48, pp. 463-472.
Liu, I.F., Chen, M.C., Sun, Y.S., Wible, D. and Kuo, C.H. (2010), Extending the TAM model to explore
the factors that affect intention to use an online learning community,Computers and Education,
Vol. 54 No. 2, pp. 600-610.
Lo, O.W.Y. and Leung, L. (2009), Effects of gratication-opportunities and gratications-obtained
on preferences of instant messaging and e-mail among college students,Telematics and
Informatics, Vol. 26 No.2, pp. 156-166.
Lonsdale, A.J. and North, A.C. (2011), Whydo we listen to music? A uses and gratications analysis,
British Journal of Psychology, Vol. 102 No. 1, pp. 108-134.
MacKenzie, S.B. and Podsakoff, P.M. (2012), Common method bias in marketing: causes, mechanisms,
and procedural remedies,Journal of Retailing, Vol. 88 No. 4, pp. 542-555.
Malik, A., Dhir, A. and Nieminen, M. (2016), Uses and gratications of digital photo sharing on
Facebook,Telematics and Informatics, Vol. 33 No. 1, pp. 129-138.
Manis, K.T. and Choi, D. (2019), The virtual reality hardware acceptance model (VR-HAM): extending
and individuating the technology acceptance model (TAM) for virtual reality hardware,Journal
of Business Research, Vol. 100, pp. 503-513.
Mäntymäki, M. and Riemer, K. (2014), Digital natives in social virtual worlds: a multi-method study of
gratications and social inuences in Habbo Hotel,International Journal of Information
Management, Vol. 34 No. 2, pp. 210-220.
SJME
Mäntymäki, M. and Islam, A.N. (2016), The Janus face of Facebook: positive and negative sides of
social networking site use,Computers in Human Behavior, Vol. 61, pp. 14-26.
Maranguni
c, N. and Grani
c, A. (2015), Technology acceptance model: a literature review from 1986 to
2013,Universal Access in the Information Society, Vol. 14 No. 1, pp. 81-95.
Marketwatch (2020), Netix pulled off a showstopper early in the pandemic, but will the sequel
deserve the price, available at: www.marketwatch.com/story/netix-in-the-age-of-covid-19-
streaming-pioneer-may-have-new-edge-on-competition-2020-04-07
Munoz-Leiva, F., Climent-Climent, S. and Liébana-Cabanillas, F. (2017), Determinants of intention to
use the mobile banking apps: an extension of the classic TAM model,Spanish Journal of
Marketing Esic, Vol. 21 No. 1, pp. 25-38.
Nagy, J.T. (2018), Evaluation of online video usage and learning satisfaction: an extension of the
technology acceptance model,International Review of Research in Open and Distributed
Learning, Vol. 19 No. 1, pp. 160-184.
Niehaves, B. and Plattfaut, R. (2014), Internet adoption by the elderly: employing is technology
acceptance theories for understanding the age-related digital divide,European Journal of
Information Systems, Vol. 23 No. 6, pp. 708-726.
Nikou, S.A. and Economides, A.A. (2017), Mobile-based assessment: integrating acceptance and
motivational factors into a combined model of self-determination theory and technology
acceptance,Computers in Human Behavior, Vol. 68, pp. 83-95.
Panda, S. and Pandey, S.C. (2017), Binge watching and college students: motivations and outcomes,
Young Consumers, Vol. 18 No. 4, pp. 425-438.
Park, N. (2010), Adoption and use of computer-based voice over internet protocol phone service:
toward an integrated model,Journal of Communication, Vol. 60 No. 1, pp. 40-72.
Park, N., Kee, K.F. and Valenzuela, S. (2009), Being immersed in social networking environment:
Facebook groups, uses and gratications, and social outcomes,Cyberpsychology and Behavior,
Vol. 12 No. 6, pp. 729-733.
Perks, L.G. and Turner, J.S. (2019), Podcasts and productivity: a qualitative uses and gratications
study,Mass Communication and Society, Vol. 22 No.1, pp. 96-116.
Quan-Haase, A. and Young, A.L. (2010), Uses and gratications of social media: a comparison of
Facebook and instant messaging,Bulletin of Science, Technology and Society, Vol. 30 No. 5,
pp. 350-361.
Rauniar, R., Rawski, G., Yang, J. and Johnson, B. (2014), Technology acceptance model (TAM) and
social media usage: an empirical study on Facebook,Journal of Enterprise Information
Management, Vol. 27 No. 1, pp. 6-30.
Ray, A., Dhir, A., Bala, P.K. and Kaur, P. (2019), Why do people use food delivery apps (FDA)? A uses
and gratication theory perspective,Journal of Retailing and Consumer Services, Vol. 51,
pp. 221-230.
Redondo, I. and Aznar, G. (2018), To use or not to use ad blockers? The roles of knowledge of ad
blockers and attitude toward online advertising,Telematics and Informatics, Vol. 35 No. 6,
pp. 1607-1616.
Riddle, K., Peebles, A., Davis, C., Xu, F. and Schroeder, E. (2018), The addictive potential of television
binge watching: comparing intentional and unintentional binges,Psychology of Popular Media
Culture, Vol. 7 No. 4, pp. 589-604.
Ringle, C.M., Wende, S. and Becker, J.M. (2014), SmartPLS 3, Hamburg: SmartPLS. Academy of
Management Review, 9, pp. 419-445.
Rios Marques, I., Casais, B. and Camilleri, M.A. (2020), The effect of macro celebrity and micro
inuencer endorsements on consumer-brand engagement on Instagram, in Camilleri, M.A. (Ed.)
Strategic Corporate Communication in the Digital Age, Emerald, Bingley.
Rogers, E.M. (2003), Diffusion of Innovations, (5th ed.), Simon and Schuster, New York, NY, USA.
Online
streaming
services
Sanz-Blas, S., Buzova, D. and Miquel-Romero, M.J. (2019), From Instagram overuse to instastress and
emotional fatigue: the mediation of addiction,Spanish Journal of Marketing ESIC, Vol. 23
No. 2, pp. 143-161.
Scherer, R., Siddiq, F. and Tondeur, J. (2019), The technology acceptance model (TAM): a meta-
analytic structural equation modeling approach to explaining teachersadoption of digital
technology in education,Computers and Education, Vol. 128, pp. 13-35.
Shao, G. (2009), Understanding the appeal of user-generated media: a uses and gratication
perspective,Internet Research, Vol. 19No. 1, pp. 7-25.
Simpson, W. and Greeneld, H. (2012), IPTV and Internet Video: Expanding the Reach of Television
Broadcasting, Routledge, Oxford.
Smock, A.D., Ellison, N.B., Lampe, C. and Wohn, D.Y. (2011), Facebook as a toolkit: a uses and
gratication approach to unbundling feature use,Computers in Human Behavior, Vol. 27 No. 6,
pp. 2322-2329.
Sørensen, I.E. (2016), The revival of live TV: liveness in a multiplatform context,Media, Culture and
Society, Vol. 38 No. 3, p. 381-399.
Spilker, H.S., Ask, K. and Hansen, M. (2020), The new practices and infrastructures of participation:
how the popularity of twitch. TV challenges old and new ideas about television viewing,
Information, Communication and Society, Vol. 23 No. 4, pp. 605-620.
Stafford, T.F., Stafford, M.R. and Schkade, L.L. (2004), Determining uses and gratications for the
internet,Decision Sciences, Vol. 35 No. 2, pp.259-288.
Steiner, E. and Xu, K. (2018), Binge-watching motivates change: uses and gratications of streaming
video viewers challenge traditional TV research,Convergence: The International Journal of
Research into New Media Technologies, Vol. 26 No. 1, pp. 82-101.
Talwar, S., Dhir, A., Kaur, P. and Mäntymäki, M. (2020), Barriers toward purchasing from online
travel agencies,International Journal of Hospitality Management, Vol. 89, doi: 10.1016/j.
ijhm.2020.102593.
Tefertiller, A. (2018), Media substitution in cable cord-cutting: the adoption of web-streaming
television,Journal of Broadcasting and Electronic Media, Vol. 62 No. 3,pp. 390-407.
Tefertiller, A. (2020), Cable cord-cutting and streaming adoption: advertising avoidance and
technology acceptance in television innovation,Telematics and Informatics, Vol. 51, doi:
10.1016/j.tele.2020.101416.
Troise, C. and Camilleri, M.A. (2020), The use of digital media for marketing, CSR communication and
stakeholder engagement, in Camilleri, M.A. (Ed.), Strategic Corporate Communication in the
Digital Age, Emerald, Bingley.
Van Dijck, J. (2009), Users like you? Theorizing agency in user-generated content,Media, Culture and
Society, Vol. 31 No. 1, pp. 41-58.
Venkatesh, V. (2000), Determinants of perceived ease of use: integrating control, intrinsic motivation,
and emotion into the technology acceptance model,Information Systems Research, Vol. 11
No. 4, pp. 342-365.
Venkatesh, V. and Bala, H. (2008), Technology acceptance model 3 and a research agenda on
interventions,Decision Sciences, Vol. 39 No. 2, pp. 273-315.
Venkatesh, V. and Davis, F.D. (2000), A theoreticalextension of the technology acceptance model: four
longitudinal eld studies,Management Science, Vol. 46 No. 2, pp. 186-204.
Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003), User acceptance of information
technology: toward a unied view,MIS Quarterly, Vol. 27 No. 3, pp. 425-478.
Venkatesh, V., Thong, J.Y. and Xu, X. (2012), Consumer acceptance and use of information technology:
extending the unied theory of acceptance and use of technology,MIS Quarterly, Vol. 36 No. 1,
pp. 157-178.
SJME
Vijayasarathy, L.R. (2004), Predicting consumer intentions to use on-line shopping: the case for an
augmented technology acceptance model,Information and Management, Vol. 41 No. 6,
pp. 747-762.
Wallace, L.G. and Sheetz, S.D. (2014), The adoption of software measures: a technology acceptance
model (TAM) perspective,Information and Management, Vol. 51 No. 2, pp. 249-259.
Whiting, A. and Williams, D. (2013), Why people use social media: a uses and gratications approach,
Qualitative Market Research: An International Journal, Vol. 16 No. 4, pp. 362-369.
WSJ (2019), The great streaming battle is here. No one is safe, available at: www.wsj.com/articles/the-
great-streaming-battle-is-here-no-one-is-safe-11573272000 (accessed 12 February 2020).
Yang, H. and Lee, H. (2018), Exploring user acceptance of streaming media devices: an extended
perspective of ow theory,Information Systems and e-Business Management, Vol. 16 No. 1,
pp. 1-27.
Ye, Q., Law, R., Gu, B. and Chen, W. (2011), The inuence of user-generated content on traveler
behavior: an empirical investigation on the effects of e-word-of-mouth to hotel online bookings,
Computers in Human Behavior, Vol. 27 No. 2, pp. 634-639.
Zillmann, D. (2000), Mood management in the context of selective exposure theory,Annals of the
International Communication Association, Vol. 23 No. 1, pp. 103-123.
Further reading
Dhir, A. and Tsai, C.C. (2017), Understanding the relationship between intensity and gratications of
Facebook use among adolescents and young adults,Telematics and Informatics, Vol. 34 No. 4,
pp. 350-364.
Ho, R. (2006), Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSS,
CRC Press, Boca Raton, FL.
Kline, P. (2014), An Easy Guide to Factor Analysis, Routledge, Oxford.
Leung, L. and Wei, R. (2000), More than just talk on the move: a use-and-gratication study of the
cellular phone,Journalism and Mass Communication Quarterly, Vol. 77No. 2, pp. 308-320.
Sundar, S.S. and Limperos, A.M. (2013), Uses and grats 2.0: new gratications for new media,Journal
of Broadcasting and Electronic Media, Vol. 57 No. 4, pp. 504-525.
Corresponding author
Mark Anthony Camilleri can be contacted at: mark.a.camilleri@um.edu.mt
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
Or contact us for further details: permissions@emeraldinsight.com
Online
streaming
services
... This study contributes to the recent stream of adoption studies developed in the context of other technologies that are currently in the process of implementation, such as artificial intelligence [61][62][63], e-wallets [64] or online streaming services [65]. In the context of VR acceptance in the context of sports, the initial TAM hypotheses have been verified in various studies [6,27,30,37,[66][67][68]. ...
... Further investigating the influence that a technology's perceived ease of use has on other constructs of the model, [90] affirms that innovative technology is likely to be accepted if it is perceived as easy to use, which creates a positive attitude in the consumer. The same hypothesis was formulated by previous researchers [32,62,65]. Therefore, the following hypothesis is proposed: ...
... However, the curiosity of spectators and the usage attitude are inferior compared to the extrinsic motivators. Putting this finding in the context of previous research [65,109], it becomes obvious that positive emotions, such as enjoyment or emotional gratification, are antecedents for explaining the intention to use in the context of digital services (either streaming or, as here, the usage of VR technology to spectate mega sports events). ...
Article
Digitalization has advanced to become an opportunity to spectate sports during the pandemic and its restrictions for traveling to competitions. The purpose of this study is to investigate the antecedents of using virtual reality technology for spectating mega sports events. Based on a literature review, the authors created a model of behavioral intention, built on the unified theory of acceptance and use of technology and technology acceptance model to examine the curiosity and self-construal of spectators. An online survey obtained empirical evidence from 339 sports enthusiasts. The research model was fitted using the partial least squares algorithm. The results show that all the antecedents significantly affected the intention to use a VR device to spectate mega sports events, which explains a significant variance. Surprisingly, influences arising from social norm predominated over those arising from curiosity and the hedonic exploration of VR (enjoyment, and experience). The social norm strongly influences a VR device’s perceived usefulness, implying that people believe using VR will enhance their position in society and that they will thus perceive the technology as being more beneficial. The novelty of this study arises from quantifying the importance of curiosity’s relationship to VR acceptance and pinpointing the relevance of self-construal for VR acceptance.
... Hence, there may be different reasons why they may not have positive attitudes towards technologies. Usually, people use technologies for utilitarian reasons (23,27,28,29] or for hedonistic purposes as they find them entertaining [30,31]. TAM's key constructs were often focused to determine the extent to which individuals believe that specific technologies could improve their job performance. ...
... A good number of researchers confirmed that their participants' attitudes toward education technologies were affecting their intentions to continue using them in the future [3]. These studies were also consistent with Ajzen's [31] theory of planned behavior (TPB), as attitudes toward the technology is one of the most important factors that determines the users' intentions to use them [3,7,11]. This argumentation leads to the following hypothesis: ...
Conference Paper
Full-text available
Students are increasingly utilizing mobile learning applications (m-learning apps) in various contexts. They can access their content from anywhere, anytime. This research explores the students' perceptions about learning technologies in a higher educational context. It integrates the Technology Acceptance Model's (TAM) constructs with "perceived enjoyment" to better understand their dispositions to engage with educational apps. The data was gathered through an online survey questionnaire among 317 research participants who were following full time university courses in a Southern European country. The findings suggest that the students were motivated to use learning apps. Their perceived usefulness, ease-of-use and enjoyment were having a significant effect on their intentions to continue using them in the future. This contribution implies that "perceived enjoyment" construct can be combined with TAM to shed more light on the users' intrinsic motivations to use mobile apps for educational purposes.
... Perceived ease of use affects behavioral intention to use video conferencing apps for learning Islamic knowledge. This finding adds to the research list which suggests that perceived ease of use can influence intention to use [39]- [42]. It is even the strongest one in this study. ...
Article
Full-text available
Seeking knowledge is obligatory for Muslims. Video conferencing apps help Muslims for learning Islamic knowledge. This study attempted to comprehend factors influencing intention to use video conferencing applications for learning Islamic knowledge by modifying Technology Acceptance Model (TAM). The data was gathered through a questionnaire from 85 respondents. Partial Least Square-Structural Equation Modeling (PLS-SEM) was used to evaluate the proposed model. The findings show that perceived usefulness, perceived ease of use, and religiosity all have a significant influence on behavioral intention to use video conferencing apps. Furthermore, religiosity significantly influences perceived usefulness. Facilitating condition also significantly influences perceived usefulness and perceived ease of use.
... Unlike regular television broadcast streams, streaming platforms can produce local content based on the preferences of consumers in the markets where they are located and are digital applications that can be completely shaped according to the wishes of the users and are among the best time-passing alternatives (Shon et al., 2021;Ramasoota and Kitikamdhorn, 2021;Silva and Lima, 2022). Streaming platforms, which are based on a subscriber-based system with alternative payment options, are designed to meet users' entertainment needs by removing geographical barriers (Camilleri and Falzon, 2020;Nagaraj et al., 2021). Streaming platforms, which make a difference in the industry by supporting local producers and content creators, also play an important role in marketing and advertising activities in the digital age, by integrating technological devices such as smartphones, smart televisions, computers, and tablets with internet infrastructure, allowing for intercultural interaction in the markets they participate in (Elkins, 2019;Wongkitrungrueng and Assarut, 2020;Taylor et al., 2021;Agrawal and Mittal, 2022). ...
Article
Full-text available
The purpose of this study is to determine which factors influence people's preferences for streaming platforms that frequently employ digital marketing techniques. Accordingly, the “number of subscribers, minimum and maximum monthly payment amount, the number of followers on Twitter, Instagram, Facebook and YouTube social media platforms, the PlayStore and AppStore application score, and the number of complaints on the Şikayetvar.com site” were weighted using the CRITIC method as determined within the main framework of "platform features" and "platform image”. This was followed by the analysis of the data belonging to “Netflix, BluTv, Exxen, Gain, Turkcell TV+, Tivibu, D-Smart, Bein Connect” platforms using the CODAS and PIV methods and comparison of the results. According to the study's findings, the "minimum monthly payment amount" criterion is the most effective criterion for consumers when selecting streaming platforms. Furthermore, in the overall evaluation of the analyses carried out, the "Netflix" platform was found to be more successful than other streaming platforms.
... and without commercials (Madnani et al.. 2020). and online streaming has become popular programmes/shows in order to provide their subscribers with access to a library that contains a wide range of content, such as movies, sports programs, series, shows, entertainment and among other things (Camilleri et al., 2020). However, in emerging economies, people are hesitant to spend money on OTT platforms because a substantial section of the population is low-income and prefers to watch free content available online. ...
Conference Paper
Full-text available
The entertainment industry is witnessing a tremendous change during the CovID-19 pandemic. OTT platforms have emerged as the significant driver of these changes. Collectively, students are considered to be a significant ingredient of the total Customers of OTT platforms. This study aims to understand the perceptions of college and university students towards using Over-the-Top (OTT) platforms. It is an attempt to test students' perceptions of demographic variables such as gender. age, location and educational qualifications. The data was analyzed through statistical tools/ techniques including Student's t-test and one-way ANOVA. The study is cross-sectional in nature and brings valuable insights to the OTT service providers regarding the intentions/preferences of students regarding the usage of OTT platforms.
... Additionally, perceived ease of use (PEU) is found to influence perceived usefulness (PU) which means that there is a positive outcome on continued use of Teams, since when technology is easy to use it means that the students believe it is useful to them, in agreement with other researchers who have found that PEU affects PE of the technology (Camilleri & Falzon, 2020;Chiu & Wang, 2008;Cicha et al., 2021). Regarding PEU and PU, the present research has also found positive effects on behavioral intensions using Teams, a result which is in line with other studies that stress that behavioral intention is affected by the PEU and PU of the technology (Pal & Vanijja, 2020;Park et al., 2009;Yoon, 2016). ...
Chapter
Since the outbreak of the COVID-19 pandemic, higher education has been confronted with several challenges leading to a new perspective of education and affecting the teaching and the learning processes. Higher education institutions in tourism studies have tried to adapt to these changes and have implemented online courses and Web conferencing technologies as the ideal learning environment during these unprecedented circumstances. This research investigates the acceptance, success, and overall evaluation of Web conferencing technologies in tourism higher education during the COVID-19 pandemic. More specifically, the Technology Acceptance Model (TAM), one of the most influential models worldwide, is used to measure the acceptance of Web conferencing technologies in tourism higher education. Additionally, the popular Information System Success Model (ISSM) is also used to the degree of the user’s satisfaction. For the purpose of this research Microsoft Teams is selected to be the Web conference platform. The findings of this empirical research indicated a positive and significant effect on tourism students’ acceptance, satisfaction, and intentions to continue using Web conferencing technologies in the future. Students have also recognized these digital platforms as effective learning environments facilitating the educational process and providing the quality of education during the difficult circumstances of the pandemic.
Article
Using visualizations of danmaku and word cooccurrence analysis, the current research evaluates China's live-streaming travel industry by extracting live streamers' and customers' cocreated content to construct a framework of cocreation patterns on live-streaming platforms. The results indicate that streamers and viewers focus on the themes of "hotel amenities and services", "live-streaming commerce", "viewers' evaluations and comments", "business strategy of Ctrip", and "price of tourism and hospitality products". Cocreation behaviors on the Ctrip Live platform include the following: "question only", "answer only", and "Q&A". Six categories of cocreation patterns were also identified. Thus, this paper contributes to the literature on live-streaming travel commerce by providing theoretical insights and practical implications, specifically, for tourism enterprises' recovery following the COVID-19 pandemic.
Article
The current study attempts to measure the determinants of continuous intention of over-the-top (OTT) platforms. In the present context, stimulus–organism–response (S–O–R) model was applied to identify the determinants of continuous intentions. The data were collected from users of the existing OTT platforms. To test the proposed model, we applied the partial least square structural equation modeling (PLS-SEM) technique in accordance with the objective and hypotheses. The proposed model explains 45% of perceived value and 41% of continuance intentions, respectively. The results indicated that there are four significant relationships and one insignificant relationship. To explicitly state; perceived ease of use, perceived customization benefits, mobility has a favorable impact on perceived value, and perceived value significantly influences the continuous intention of OTT platform, and last, entertainment value was found to be insignificant with perceived value. This study provides varied clues to marketers to shape up customers behavior and to ensure the factors affecting decision regarding continuous intention of OTT platform. The current study proposes that continuous intentions can be framed by offering value.
Article
Purpose Most previous studies on new technologies and services have concentrated on their acceptance, seldom exploring in depth why users may choose not to accept technology or service and remain “non-users.” This study aims to understand free platform users' intention to switch to paid subscription platforms. Design/methodology/approach This study utilized push-pull-mooring (PPM) theory to investigate free OTT platform viewers' switching intentions toward paid OTT platforms. A research model was established and examined via a two-stage partial least square (PLS) method. A total of 446 free users were collected from Facebook and Line for data analysis. Findings Results show that perceived intrusiveness is the push factor and alternative attractiveness is the pull factor and that both have a positive impact on the switching intention of non-subscribers. Habit represents the mooring factor and negative affects switching intention. Perceived convenience and perceived enjoyment are shown to be two significant habitual antecedents. Furthermore, habit is revealed to moderate the effect of users' perceived advertisement intrusion and alternative attractiveness on switching intention to strengthen positive impact when the habit is strong. Originality/value This study is one of the pioneering studies to consider free-to-paid switching behavior on media services using PPM's structural equation model. Contrary to previous research, the study found that, in the context of the free-to-paid transition, highly accustomed users' perception of pull factors and push factors were strengthened, thus generating the tendency to switch platforms.
Chapter
Full-text available
The latest advances in digital technologies have changed the way companies communicate with their stakeholders. This chapter explores the businesses' usage of digital communication channels. It focuses on their utilization of social media for marketing and promotion of products, corporate social responsibility (CSR) practices and stakeholder engagement with financial stakeholders. An exploratory study was carried out on a sample of 167 Italian businesses. It investigated the companies' websites and their social media accounts. The findings suggest that the Italian businesses are using various social media networks for corporate communication purposes. This descriptive research shows that they are utilizing Facebook, LinkedIn and YouTube, among others, to communicate commercial information and to promote their business. Moreover, they are using Instagram and Twitter to raise awareness about their CSR initiatives. In conclusion, this chapter implies that marketers need to carefully coordinate the use of different digital tools to ensure that they reach their target audiences in an effective manner.
Chapter
Full-text available
Several brands are striving in their endeavors to find new ways to improve their consumer engagement through social media. They are using different tools including influencer marketing through social networking sites (SNSs). Therefore, this chapter addresses a gap in the academic literature as it distinguishes between two types of online influencers. The researchers investigate the effects of celebrity endorsers' and of micro influencers' posts on a brand's page in Instagram. They examine the number of followers, clicks, comments and likes that are generated following their influencer marketing. The results suggest that both influencers have generated varying levels and types of interactions. In sum, this exploratory study revealed that the chosen celebrity's posts attracted more followers to the brand's Instagram page, when compared to the micro influencer's publications. However, the latter has garnered more clicks, comments and likes, thereby increasing the consumer-brand engagement through social media. In conclusion, this contribution identifies future research avenues relating to influencer marketing.
Chapter
Full-text available
This chapter presents a systematic review of over thirty (30) types of online marketing methods. It describes different methods like email marketing, social network marketing, in-game marketing and augmented reality marketing, among other approaches. The researchers discuss that the rationale for using these online marketing strategies is to increase brand awareness, customer centric marketing and consumer loyalty. They shed light on various personalization methods including recommendation systems and user generated content in their taxonomy of online marketing terms. Hence, they explain how these online marketing methods are related to each other. The researchers contend that the boundaries between online marketing methods have not been clarified enough within the academic literature. Therefore, this chapter provides a better understanding of different online marketing methods. A review of the literature suggests that the 'oldest' online marketing methods including the email and the websites are still very relevant for today's corporate communication. In conclusion, the researchers put forward their recommendations for future research about contemporary online marketing methods.
Book
Full-text available
This authoritative book features a broad spectrum of theoretical and empirical contributions on topics relating to corporate communications in the digital age. It is a premier reference source and a valuable teaching resource for course instructors of advanced, undergraduate and post graduate courses in marketing and communications. It comprises fourteen engaging and timely chapters that appeal to today’s academic researchers including doctoral candidates, postdoctoral researchers, early career academics, as well as seasoned researchers. All chapters include an abstract, an introduction, the main body with headings and subheadings, conclusions and research implications. They were written in a critical and discursive manner to entice the curiosity of their readers. Chapter 1 provides a descriptive overview of different online technologies and presents the findings from a systematic review on corporate communication and digital media. Camilleri (2020a) implies that institutions and organizations ought to be credible and trustworthy in their interactive, dialogic communications during day-to-day operations as well as in crisis situations, if they want to reinforce their legitimacy in society. Chapter 2 clarifies the importance of trust and belonging in individual and organizational relationships. Allen, Sven, Marwan and Arslan (2020) suggest that trust nurtures social interactions that can ultimately lead to significant improvements in corporate communication and other benefits for organizations. Chapter 3 identifies key dimensions for dialogic communication through social media. Capriotti, Zeler and Camilleri (2020) put forward a conceptual framework that clarifies how organizations can enhance their dialogic communications through interactive technologies. Chapter 4 explores the marketing communications managers’ interactive engagement with the digital media. Camilleri and Isaias (2020) suggest that the pace of technological innovation, perceived usefulness, ease of use of online technologies as well as social influences are significant antecedents for the businesses’ engagement with the digital media. Chapter 5 explains that the Balanced Scorecard’s (BSC) performance management tools can be used to support corporate communications practitioners in their stakeholder engagement. Oliveira, Martins, Camilleri and Jayantilal (2020) imply that practitioners can use BSC’s metrics to align their communication technologies, including big data analytics, with organizational strategy and performance management, in the digital era. Chapter 6 focuses on UK universities’ corporate communications through Twitter. Mogaji, Watat, Olaleye and Ukpabi (2020) find that British universities are increasingly using this medium to attract new students, to retain academic employees and to promote their activities and events. Chapter 7 investigates the use of mobile learning (m-learning) technologies for corporate training. Butler, Camilleri, Creed and Zutshi (2020) shed light on key contextual factors that can have an effect on the successful delivery of continuous professional development of employees through mobile technologies. Chapter 8 evaluates the effects of influencer marketing on consumer-brand engagement on Instagram. Rios Marques, Casais and Camilleri (2020) identify two types of social media influencers. Chapter 9 explores in-store communications of large-scale retailers. Riboldazzi and Capriello (2020) use an omni-channel approach as they integrate traditional and digital media in their theoretical model for informative, in-store communications. Chapter 10 indicates that various corporations are utilizing different social media channels for different purposes. Troise and Camilleri (2020) contend that they are using them to promote their products or services and/or to convey commercial information to their stakeholders. Chapter 11 appraises the materiality of the corporations’ integrated disclosures of financial and non-financial performance. Rodríguez-Gutiérrez (2020) identifies the key determinants for the materiality of integrated reports. Chapter 12 describes various electronic marketing (emarketing) practices of micro, small and medium sized enterprises in India. Singh, Kumar and Kalia (2020) conclude that Indian owner-managers are not always engaging with their social media followers in a professional manner. Chapter 13 suggests that there is scope for small enterprises to use Web 2.0 technologies and associated social media applications for branding, advertising and corporate communication. Oni (2020) maintains that social media may be used as a marketing communications tool to attract customers and for internal communications with employees. Chapter 14 shed light on the online marketing tactics that are being used for corporate communication purposes. Hajarian, Camilleri, Diaz and Aedo (2020) outline different online channels including one-way and two-way communication technologies. Endorsements "Digital communications are increasingly central to the process of building trust, reputation and support. It's as true for companies selling products as it is for politicians canvasing for votes. This book provides a framework for understanding and using online media and will be required reading for serious students of communication". Dr. Charles J. Fombrun, Former Professor at New York University, NYU-Stern School, Founder & Chairman Emeritus, Reputation Institute/The RepTrak Company. “This book has addressed a current and relevant topic relating to an important aspect of digital transformation. Various chapters of this book provide valuable insights about a variety of issues relating to "Strategic Corporate Communication in the Digital Age". The book will be a useful resource for both academics and practitioners engaged in marketing- and communications-related activities. I am delighted to endorse this valuable resource”. Dr. Yogesh K. Dwivedi, Professor at the School of Management at Swansea University, UK and Editor-in-Chief of the International Journal of Information Management. “This title covers a range of relevant issues and trends related to strategic corporate communication in an increasingly digital era. For example, not only does it address communication from a social media, balanced scorecard, and stakeholder engagement perspective, but it also integrates relevant contemporary insights related to SMEs and COVID-19. This is a must-read for any corporate communications professional or researcher”. Dr. Linda Hollebeek, Associate Professor at Montpellier Business School, France and Tallinn University of Technology, Estonia. "Corporate communication is changing rapidly, and digital media represent a tremendous opportunity for companies of all sizes to better achieve their communication goals. This book provides important insights into relevant trends and charts critical ways in which digital media can be used to their full potential" Dr. Ulrike Gretzel, Director of Research at Netnografica and Senior Fellow at the Center for Public Relations, University of Southern California, USA. "This new book by Professor Mark Camilleri promises again valuable insights in corporate communication in the digital era with a special focus on Corporate Social Responsibility. The book sets a new standard in our thinking of responsibilities in our digital connected world". Professor Wim Elving, Hanze University of Applied Sciences, Groningen, The Netherlands.