Pavlik & Bridges (2013, p.11) note that Rogers's research delineated five stages in the process of adoption of an innovation which is: (1) knowledge, (2) persuasion, (3) decision, (4) implementation, and (5) confirmation. According to them:
In the knowledge stage, an innovation becomes known, but there is insufficient information.
In the persuasion stage, potential users become interested in the innovation and seek more information. In the decision stage, the innovation is evaluated with advantages or disadvantages listed that help to adopt or reject it. If the innovation is adopted, the implementation stage involves a trial of the innovation in which the overall usefulness of the innovation and whether it should be used on a larger scale are assessed. Finally, the confirmation stage involves the adoption of the innovation to its fullest potential (Pavlik &
Bridges, 2013, p.11).
The theory also considers that for any innovation to be adopted, certain factors are to be considered.
Pavlik and Bridges (2013, p.11) posit that the rate of adoption of an innovation is influenced basically by at least five factors, including (1) the perceived relative advantage of the innovation, (2) compatibility, (3) complexity or simplicity, (4) trialability, and (5) observability. Certain personal characteristics also influence innovation adoption; demographic indicators such as sex, age and educational and social backgrounds become key markers. In the social or cultural organization, however, Rogers stated there are various levels at which different people react to and adopt change.
People chose to adopt technology at various stages. A person's decision to adopt or reject an innovation is often determined by the innovation itself (Rogers, 2003).
The pattern by which an innovation spreads through a social system has been well documented and follows a classic S-shaped curve of adoption over time (Davenport, et al., 2002). There are five distinct categories of adopters according to the theory and the approximate percentage of individuals included in each category is described, based on the degree of their “innovativeness”. This includes innovators, early adopters, early majority, late majority, and laggards. These classifications according to Rogers (1995) can be used to understand the process by which information technology has become part of the journalistic profession. Also (Rogers, 1995; Li, 2003), listed three sets of variables in the diffusion process; ‘technology ownership, adopters' characteristics, and innovation attributes, and each has enduring impacts on the adoption of new technologies.
There are recent innovation diffusion studies that focused on the adoption of product technologies, for instance, the mobile phone (Roach, 2009); mobile gaming (Kleijnen et al., 2004); Internet as a communication channel (Lin and Yu, 2006) and; mobile Internet service (Pedersen, 2005). There seem to be few studies that concentrate on the adoption of the new media, especially in the broadcast newsroom (Fischer 2011; Shin & Shin, 2010; Cheung, Chiu & Lee, 2010). Thus, this study will conceptualize new media use in broadcast newsrooms to be an innovation, which distinguishes it from other media communications.
Criticism of Diffusion of Innovation Theory
Research has shown that many factors which might affect the diffusion of the innovation process.
Surendra (2001) used diffusion of innovations theory to examine the use of Web technology among college professors and administrators. The theory was used to provide a background against which social media adoption by journalists was studied. D'arcy (2012) in her study of social media use among TV journalists used the diffusion of innovations theory to hypothesize potential relationships between age, educational level, experience and social media use. Her preliminary findings showed that age and educational level did influence social media use. Journalists aged 29 and below tended to use social media more than those 39 years and above.
This shows that with this theory, the adoption of a new idea does not just happen within a twinkle of an eye. It moves from one step to the other. First of all, users must be aware of the innovation as well as the need for an innovation. From this awareness level, they make up their minds on whether to adopt the innovation or not. If they make up their minds towards the positive direction, they would proceed to test the innovation to ascertain its effectiveness. Satisfaction from this initial usage leads to the continuation and adoption of that innovation. This implies that for converging new media technologies to be adopted in the broadcast media terrain, media practitioners must, first of all, identify the existing vacuum in their practices which could be enhanced by the media technologies before the adoption takes place. Rogers identified some clear steps in the adoption process: first, people have to become aware of innovations; a small group of early adopters will try it out; the early adopters share their successes with opinion leaders who try the innovation themselves. He also observes that: the early adopter will then share their success with opinion followers, who ultimately try it out and that the late adopters finally get with the program when almost everybody else has adopted the innovation. For instance, think about how people in our society have adopted the use of cell phones or personal computers. There will probably be some early adopters, some opinion leaders and some late adopters in our society with regard to those new technologies. One may, probably, be an early adopter of one kind of innovation, but a late adopter in another.
Also, adopters must be aware of these technological innovations with regards to how they function before they can utilize them for optimum performance. From this theory, it is clear that the media practitioners are expected to be aware of the existence of a particular technology as well as how it operates before they decide to adopt it in their operations. Failure to do this could lead to inappropriate handling of the technology. In such a situation, the development which the technology is expected to bring would no longer be achieved. From this awareness level, they move over to the next level, which is test-running. If the technology affects a significant and appreciable change in their system, it
becomes part of their system. Therefore, it important that media outfit makes available the technologies facilitating the adoption of new media for use by media practitioners.
2.3.2 Technology Acceptance Model
Closely related to diffusion theory is the Technology Acceptance Model (TAM). The technology acceptance model is an extension of the diffusion of innovations theory. Originally conceived by Davis (1985) in his doctoral thesis in which he suggests that an individual user’s motivation to use a system is influenced by the system’s features and capabilities. Davis et al. (1989) suggest that perceived ease of use and perceived usefulness are beliefs about a new technology that influence an individual’s attitude toward and use of that technology. TAM is believed to have a relationship with the Theory of Reasoned Action (TRA). Wu, Tao and Yang (2008, p.925) stressed that “the purpose of TAM is to simplify TRA and provide a generalization model that possesses theoretical foundation and parsimony and the tools that a manager uses”. They further agree with Venkatesh, Morris, Davis, &
Davis (2003) that TAM allows users to weigh the introduction of new technology, and then predicts and explains the user's behaviour of accepting information technology. At the same time, the researcher can understand the external factors that affect researcher's internal faith, attitude and desire when using the technology.
Basically, TAM is designed to predict adoption of new technologies in the workplace, especially at the individual level. Key predictors include performance expectancy, or belief that the technology will improve job performance; effort expectancy, or ease of use of the technology; and social influence, or belief that "important others" sanction the technology. As is evident, the rational choice behaviour is assumed, though the response to social influence in the form of "compliance" suggests the pursuit of legitimacy. However, the impetus for compliance is instrumental rather than institutional; as individuals comply mostly because, they expect rewards from an “important other” (Venkatesh, et al., 2003).
The theory has been employed in several studies of communication and information technology.
Porter and Donthu (2006) employed TAM to explain how attitudes determine Internet usage. Their study revealed that factors such as age, education, income, and race influenced beliefs about the Internet and thus were determinants in how people used it. Porter and Donthu (2006) also looked at access barriers such as cost and how this affected perceptions regarding perceived usefulness and ease of use. Similarly, Nasri & Charfeddine (2012) studied the adoption of Facebook among 240 university students in Tunisia. Their study aimed to propose a conceptual framework to better understand the factors in Facebook adoption in Tunisia. The results confirmed a relationship between perceived ease
of use and perceived usefulness in the adoption of Facebook and revealed that attitudes, as well as social norms, were important factors in Facebook adoption.
Criticism of TAM
Technology Acceptance Model is based primarily on the Theory of Reasoned Action (TRA), proposed by Fishbein & Ajzen (1975), which postulates that beliefs influence attitude, which in turn shapes a behavioural intention to engage in a particular behaviour. The Theory of Planned Behavior (TPB) extends TRA by incorporating perceived behavioural control to account for situations where an individual lacks the control or resources necessary for carrying out the targeted behaviour, despite a positive attitude toward it (Ajzen 1991). The Technology Acceptance Model (TAM) shares with TRA the common thread that connects attitude to behavioural intention, but differs in its theorized determinants of attitude and behavioural intention. TAM is also specifically designed to address the determinants of end-user computing technology acceptance (Chau & Hu 2002).
The reason why TAM is generally valued and adopted by researchers is that it uses users' perception to infer Behavioral Intention (BI) directly, its method is simple and clear, but questions such as "which factors would influence users' perception" have not been discussed. Legris, Ingham, and Collerette (2003) suggested that other variables should be added to TAM so as to provide a complete model structure. Venkatesh and Davis (2000) therefore, proposed a new structure, TAM2, which extends forward, and they claimed that “social influence” and “cognitive instrumental” are the two main variables that influence users’ consciousness. However, TAM includes three dimensions, which are
“subjective norm”, “voluntariness” and “image”; while the new TAM2 includes four dimensions, which are “job relevance”, “output quality”, “result demonstrability” and “perceived ease of use”. This study is hinged on Technology Acceptance Model and takes cognizance of these dimensions in examining the use of new media technologies in broadcast newsrooms in South East, Nigeria.
Nordenson (2008) highlighted the impact of the information age on news production and consumption in the areas of openness, user-friendliness, and self-government. In a study that examined journalism‘s future in an era of unprecedented information abundance, Nordenson concluded that the Internet has altered the business model of media organizations. How the Nigeria media entrepreneur balances this reality, will shape the contour and terrain of new media adoption and media convergence in the country. Given this scenario, the complete adoption of new media technologies and expansion in social media use in media practice as practised in the United States, Britain, and other countries could help to deliver to the audience quality programming and editorial content that will foster development.
Embracing a new media model may well be the better option for media proprietors in Nigeria.
However, this requires a change of mindset and a determination to adjust to new ways of doing
broadcasting as a business. Quinn (2005) remarked that the success of multimedia journalism is dependent upon the readiness of journalists to change old habits and adopt new practices which challenge their ego, skill, innovation, creativity, and patience. Quinn‘s view touches at the heart of the imminent challenge facing the average Nigerian media practitioner who has to struggle to put behind old media practices, including ego and learn to give the readers and viewers a premier consideration in a converged media environment. This study will employ the applicability of TAM in explaining the perception of Nigerian broadcast practitioners concerning the usefulness of new media technologies in media practice.