Innovation diffusion model

Rogers developed the innovation diffusion model to explain how an innovation diffuses through a society [Geoghegan, 1994; Walton and Vukovic, 2003; Kiljander, 2004; Rogers, 2003]. The innovation diffusion model has been used extensively to explain the acceptance or rejection of IT innovations in an organisation or society [Urbaczewski et al., 2002].

According to Rogers [2003:36]. ‘An innovation is an idea, a practice, or object that is perceived as new by an individual or another unit of adoption’. ‘Diffusion is the process by which an innovation is communicated through certain channels over time among the members of a social system’ [Rogers, 2003:35]. The rate of adoption is determined by the characteristics of an innovation, which are as follows: [Rogers, 2003]:

• Relative advantage described as ‘the degree to which an innovation is perceived as better than the idea it supersedes’ [Rogers, 2003:15].

• Compatibility refers to the ‘degree to which an innovation is perceived as being consistent with the existing values, past experiences, and needs of potential adopters’ [Rogers, 2003:15].

• Complexity is ‘the degree to which an innovation is perceived as difficult to understand and use’ [Rogers, 2003:16].

• Trialability refers to ‘the degree to which an innovation may be experimented with on a limited basis’ [Rogers, 2003:16].

A model for representing the motivational and cultural factors that influence mobile phone usage variety 66 • Observability refers to ‘the degree to which the results of an innovation are visible to others’

[Rogers, 2003:16].

Rogers’ adoption/innovation curve divides adopters of innovations into five categories [Rogers, 2003], as depicted in Figure 4.3. Innovation distribution Innovators 2.5 Laggards 16 Early Adopters 13.5 Late Majority 34 Early Majority 34 0 5 10 15 20 25 30 35 40 Innovators Early Adopters

Early Majority Late Majority Laggards

Figure 4.3: Expressing Rogers’ adopter groups as a percentage of the population

Each adopter group in the model represents a unique psychographic profile based on the idea that some individuals are more open to adoption than others are. The categories can be described as follows [Geoghegan, 1994; Walton and Vukovic, 2003; Kiljander, 2004; Rogers, 2003]:

• Innovators: These are the ‘techies’, the experimenters who have technology as a central interest in their lives and pursue new technology as soon as it appears, no matter what its function is. They get acquainted with the details of all the new hardware and software, finding pleasure in mastering the intricacies of the technology. Their interest lies more with the technology itself than with its application to problems. Innovators make up approximately 2.5 per cent of the population.

• Early adopters: They are the ‘visionaries’ who blend an interest in technology with a concern for significant professional problems and tasks. They are mostly not technologists but exploit the new capability. They find it easy to imagine, understand and appreciate new technologies for their potential to bring about major improvements and achieve a competitive advantage. They provide seed funding for entrepreneurs since they are risk-takers, not averse to occasional failure, who often favour a tightly focused project orientation in their work. Early adopters make up approximately 13.5 per cent of the adopter population.

A model for representing the motivational and cultural factors that influence mobile phone usage variety 67 • Early majority: They are the ‘pragmatists’. Although fairly comfortable with technology in

general, their focus is on concrete professional problems rather than on the tools (technological or otherwise) that might be used to address them. They are driven by a strong sense of practicality and thus adopt a ‘wait-and-see’ attitude toward new applications of technology, i.e. they like to wait and see how other people are doing before they buy in themselves. They require concrete references and examples of success before adopting. They avoid abrupt change, being more attuned to evolutionary modification of existing processes and methods. The early majority want to see compelling value in an innovation before adopting it. They make up approximately 34%, which is the first half of the mainstream.

• Late majority: They are the conservatives or ‘sceptics’. They share the attitude of the early majority, though being less comfortable with technology. They will wait until something has become an established standard, and they prefer buying from large, well-established companies. By definition, they accept innovation only when the change has already become well established among the majority. The late majority make up approximately 34%, which is the latter half of the mainstream.

• Laggards: They are the most likely never to adopt at all. They are not interested in new technology and they generally buy technology products only when these are buried inside other products. Laggards make up the last approximately 16 per cent of the potential adopter population.

A successful innovation will be adopted in this order, beginning with the innovators, followed by the early adopters, the early and late majority, and perchance the laggards. A new technology is best focused on innovative adopters since they do not insist that the technology should have a track record, as they value a product on the basis of the latest technology built into it [Leung et al., 2003].

The mainstream of pragmatists and sceptics makeup the bulk of all technology infrastructure purchasers and represent about 68 per cent of the total population [Geoghegan, 1994; Rogers, 2003]. They adopt innovations only after a proven track record of useful productivity improvement [Leung et al., 2003]. The laggards are price-sensitive conservatives who are pessimistic about their ability to gain any value from technology investments. Although they are demanding consumers who delight in challenging the hype of high-tech marketing, they are still potential customers [Geoghegan, 1994]. The early and late markets (innovators, early adopters and laggards) each make up about 16 per cent of the market [Geoghegan, 1994; Rogers, 2003].

Ling [2001] notes the following problems with Rogers’s model:

• The model assumes that users behave in a rational way by weighing positive and negative factors. This does not acknowledge the influence of broader social processes.

• The model assumes the ideal Gaussian adoption curve, which is rarely achieved in reality.

• The model stops with the adoption of the innovation and does not consider ex post facto analyses of adoptions. This may not be a problem from the marketing and sales perspective, but in HCI and sociology research, both the adoption and rejection of innovations are of interest.

A model for representing the motivational and cultural factors that influence mobile phone usage variety 68 Other models that deal with technology diffusions are the Bass diffusion model [Ali-Vehmas and Luukkainen, 2005], the product life cycle by Levitt and the Positioning model by Trout and Reis [[12Manage Rigor and Relevance, 2006]. According to all these models, the number of success factors are limited [Ali-Vehmas and Luukkainen, 2005]. The fact that there are a limited number of factors determining the success of technology adoption makes it more feasible to model technology adoption.

The Rogers Innovation Diffusion Model focuses only on adoption and therefore it cannot be used to represent usage directly. However, the innovation diffusion model has implications for mobile phone usage since it describes customer segmentation. Furthermore, mobile phone adoption is becoming more widespread having implications for usage variety (as will be discussed in section 4.4).

4.3 FACTORS THAT INFLUENCE MOBILE PHONE