Análisis de los Sistemas

A study by Ryan and Gross (1943) was pivotal in establishing the theory of innovation diffusion. The researchers used funding from the Iowa Agriculture Experimental Station to study the dissemination of hybrid corn among growers. This quantitative study found the adoption process began with a small number of farmers who adopted hybrid corn soon after its release. When neighbouring farmers saw the results of this innovation, they quickly adopted the new strains of corn; thus a strategy of targeting influential farmers hastened the innovation process, facilitating greater productivity (Strang & Soule 1998).

By 1954, Rogers (1962) was part of another research team at the Experimental Station to study factors that militated against adoption of innovative farming practices. The insights gained from this research were crystallised from a plethora of research over the next half-century as Rogers explored factors affecting the adoption or rejection of innovative techniques. This culminated in the theory of innovation diffusion distilled in several versions of Rogers’ opus Diffusion of Innovation (Rogers 2003). Rogers (2003)

defined diffusion as ‘the process by which an innovation is communicated through certain channels over time among the members of social system’ (p. 5). The key elements in diffusion research are innovation, types of communication channels, time or rate of adoption, and the social system which frames the innovation decision process (Rogers 2003). The Diffusion of Innovation model includes five major characteristics:

• relative advantage: the degree to which it is perceived to be better than that

superseded;

• compatibility: consistency with exacting values, past experience, and needs; • complexity: difficulty of understanding;

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• trialability: the degree to which it can be experimented on a no-limit basis;

and

• observability: the visibility of its results(Rogers 1962).

The innovation diffusion process, Rogers found, occurs in stages before and after the decision category. These stages assist investigators to understand factors and events in the diffusion process (see Figure 3.1).

Source Rogers 2003, p.170

Figure 3.1: Stages in the innovation-decision process

Rogers’s five stages of Diffusion Decision Process:

1. Knowledge: availability or perception of sufficient knowledge of the

innovation and its issues and outcomes to proceed;

2. Persuasion: when individuals seek reassurance from the innovator regarding

issues they raise;

3. Decision: based on existing knowledge, past experience and the information

from the innovator, an individual will accept or reject the innovation;

4. Implementation: when accepted, the individual harbours concerns regarding

the innovation, balanced by enthusiasm based on the innovator’s claims; and 5. Confirmation: when the adopter does not require further encouragement, and

on balance, accepts the innovation.

Adopter Categories, Rogers (2003) categorised the adopters into five groups, dependent on their engagement with innovation over time (Figure 3.2).

Figure 3.2: Adopter categories over time, against ma

1. Innovators: individuals can accept the risk and adopt the innovation when it

appears. These may be

in their social milieu and represent about 2.5 per cent of adopters;

2. Early adopters: those in the vanguard of adopters who can make an earlier

decision than the majority. These early adopters are educated and knowledgeable regarding trends and represent about 13.5 per cent of the adopters;

3. Early majority: these people tend to conservatism

adoption, although they have a relatively high social status; some 34 per cent of the adopters;

4. Late majority: somewhat sceptical, these adopters seek out the innovation after

the average population; also about one third (34%) of ad

5. Laggards: or last adopters represent the remainder who accept the technology due

to social or commercial pressure. They represent about 16 per cent of adopters. The models from i

including IS research, organisational change, customer loyalty programs and marketing products (Redmond 2003, Woodside & Biemans 2005, Tseng 2008, Lee & Liu 2008). However, innovation diffusion theory is routinely used in empirical studies by IS scholars to provide a structure for testing technology adoption variables (Moore & Benbasat 1991, Beatty, Shim & Jones 2001

Kraemer 2006, Troshani & Doolin 2007). Others have integrated

Source Rogers 2003, p.281

: Adopter categories over time, against market share

: individuals can accept the risk and adopt the innovation when it appears. These may be trendsetters in retail or ICT industries who are influential

in their social milieu and represent about 2.5 per cent of adopters;

those in the vanguard of adopters who can make an earlier decision than the majority. These early adopters are educated and knowledgeable regarding trends and represent about 13.5 per cent of the adopters;

: these people tend to conservatism regarding the value of adoption, although they have a relatively high social status; some 34 per cent of

: somewhat sceptical, these adopters seek out the innovation after the average population; also about one third (34%) of adopters; and

: or last adopters represent the remainder who accept the technology due to social or commercial pressure. They represent about 16 per cent of adopters. The models from innovation diffusion theory are used across many disciplines, ding IS research, organisational change, customer loyalty programs and marketing products (Redmond 2003, Woodside & Biemans 2005, Tseng 2008, Lee & Liu 2008). However, innovation diffusion theory is routinely used in empirical studies by IS vide a structure for testing technology adoption variables (Moore &

Beatty, Shim & Jones 2001, Marez & Verleye 2004, Troshani & Doolin 2007). Others have integrated DOI into

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rket share

: individuals can accept the risk and adopt the innovation when it in retail or ICT industries who are influential in their social milieu and represent about 2.5 per cent of adopters;

those in the vanguard of adopters who can make an earlier decision than the majority. These early adopters are educated and knowledgeable regarding trends and represent about 13.5 per cent of the adopters;

regarding the value of adoption, although they have a relatively high social status; some 34 per cent of

: somewhat sceptical, these adopters seek out the innovation after opters; and

: or last adopters represent the remainder who accept the technology due to social or commercial pressure. They represent about 16 per cent of adopters.

nnovation diffusion theory are used across many disciplines, ding IS research, organisational change, customer loyalty programs and marketing products (Redmond 2003, Woodside & Biemans 2005, Tseng 2008, Lee & Liu 2008). However, innovation diffusion theory is routinely used in empirical studies by IS vide a structure for testing technology adoption variables (Moore & ,Zhu, Dong, Xu & DOI into the adoption

55 models (Venkatesh et al. 2003). However, DOI theory does not provide a reasoned argument for action.