Route Of Acceptance (2012 Watch Online Free)
Billie Kjergaard
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.
El distanciamiento social durante la pandemia del coronavirus (COVID-19) ha llevado a un aumento dramtico en las suscripciones a los servicios de transmisin de pago. Los usuarios en lnea acceden cada vez ms a transmisiones en vivo, as como a contenido de video grabado y servicios de msica digital. En este contexto, este estudio explora los usos y las gratificaciones buscadas por las personas con las tecnologas de transmisin en lnea durante la COVID-19.
La utilidad percibida y la facilidad de uso de los servicios de transmisin en lnea son antecedentes significativos de la intencin de utilizarlos. Adems, las personas buscan gratificaciones emocionales de tales tecnologas, ya que les permiten distraerse, estar de mejor humor y relajarse en su tiempo libre. Adems, las utilizan para obtener informacin y entretenimiento.
Este estudio contribuye a la literatura acadmica generando nuevos conocimientos sobre las percepciones, motivaciones e intenciones de los individuos de utilizar tecnologas de transmisin en lnea para ver pelculas grabadas, series y transmisiones en vivo.
Los hallazgos implican que hay margen para que los proveedores de servicios de transmisin en lnea mejoren su marketing centrado en el cliente reforzando la calidad y el contenido de sus programas grabados y la publicidad intermitente.
Relevant academic literature suggests that new media technologies are changing the way how individuals consume television (Tefertiller, 2018; Aldea and Vidales, 2012; Hirsjrvi 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 are accessible through satellite/or cable and subscribing to online streaming services (Spilker et al., 2020; Srensen, 2016; Flavin and Gurrea, 2007). Online users are accessing broadcast services through the home internet and/or via mobile devices (Lim et al., 2015; Simpson and Greenfield, 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).
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 findings. 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.
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 influences and cognitive instrumental processes. Their revised model was referred to as TAM2. Afterward, Venkatesh et al. (2003) refined TAM as they included new constructs, including facilitating conditions, social influences, as well as demographic variables in their unified 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).
Online users are engaging with other individuals through social media to fulfill 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 gratifications 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 efficient stimuli to individuals to adjust their moods (Smock et al., 2011; Park et al., 2009; Bumgarner, 2007; Knobloch, 2003) or to escape from emotional difficulties (Greenwood and Long, 2011; Greenwood, 2008). Hence, individuals use specific 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).
Afterward, a bootstrapping procedure was used to explore the statistical significance and relevance of the path coefficients. The significance of the hypothesized path coefficients 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 findings of the standardized beta coefficients (original sample and sample mean), the confidence intervals, ƒ2, t-values and the significance values (p). Table 4 features the results of the mediating relationship.
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 refine 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.
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 benefit of secure, reliable, low latency streaming infrastructures 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 notifications 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.
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)
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