The technology adoption cycle is a sociological model that describes the adoption or acceptance of new products or innovations, according to the demographic and psychological characteristics of the adopter group defined. The adoption process over time is usually described as a normal classical distribution or "bell curve". The model shows that the first group of people using a new product is called an "innovator", followed by an "early user". Next comes the initial majority and the final majority , and the last group that finally adopts the product is called "phobics." Phobics use the cloud without knowing what they are doing.
The demographic and psychological (or "psychographic") profiles of each adoption group were initially determined by the Northern Central Rural Sociology Committee, the Subcommittee on the Study of the Diffusion of Agricultural Practice, by Beal and Bohlen agricultural researchers in 1957. This report summarizes categories as:
- innovators - have larger, more educated, more prosperous and more risk-oriented farms
- early users - younger, more educated, tend to be community leaders, less prosperous
- the early majority - more conservative but open to new ideas, active in the community and influencing neighbors
- the final majority - older, less educated, quite conservative and less socially active
- slow - very conservative, has small farms and capital, the oldest and the least educated
This model was later adapted for many areas of technology adoption by the end of the 20th century.
Video Technology adoption life cycle
Adaptation of model
This model has spawned a variety of adaptations that expand the concept or apply it to a particular interest domain.
In his book Crossing the Chasm , Geoffrey Moore suggests variations from the original life cycle. He suggested that for discontinuous innovations, which can lead to Foster's disruption based on s-curves, there is a gap or gap between the first two adopter groups (early innovators/adopters), and the vertical market.
Disturbances such as those used today are Clayton M. Christensen varieties. This disorder is not curve based.
In educational technology, Lindy McKeown has provided a similar model (pencil metaphor) that describes the absorption of ICT in education. In medical sociology, Carl May has proposed a theory of normalization processes that demonstrate how technology becomes embedded and integrated in health care and other types of organizations.
Wenger, White and Smith, in their book Digital Habitat: Stewarding Technology for the Community , talks about technology servants: people with sufficient understanding of available technology and the technological needs of a community to serve the community through technology adoption process.
Rayna and Striukova (2009) propose that the choice of early market segments is critical to cross the gap, since adoption in this segment could lead to cascade adoption in other segments. This initial market segment, at the same time, contains most of the visionaries, small enough to be adopted from within the segment and from other segments and reasonably connected with other segments. If this is the case, adoption in the first segment will further decrease to adjacent segments, thus triggering adoption by the mass market.
Maps Technology adoption life cycle
Example
One way to model product adoption is to understand that people's behavior is influenced by their peers and how widely they think of specific actions. For many technology-dependent formats, people have a non-zero payment for adopting the same technology with their closest friends or colleagues. If two users alike adopt product A, they may get the result a Ã, & gt; Ã, 0; if they adopt product B, they get b Ã, & gt; Ã, 0. But if someone adopts A and the other adopts B, they both get the result of 0.
Thresholds can be set for each user to adopt a product. Say that the vertex v in the graph has a neighbor d: then v will adopt product A if the fraction of its neighboring p is greater than or equal to some threshold. For example, if threshold v is 2/3, and only one of its two neighbors adopts product A, then v will not adopt A. Using this model, we can determine deterministically the adoption of the product on the sample network.
History
The technology adoption cycle is a sociological model that is an extension of the previous model called the diffusion process, originally published in 1957 by Joe M. Bohlen, George M. Beal and Everett M. Rogers at Iowa State University and which was originally issued only for applications for agriculture and home economics. build on previous research conducted there by Neal C. Gross and Bryce Ryan. Their initial goal was to track the pattern of purchasing hybrid corn seeds by farmers.
Beal, Rogers and Bohlen jointly developed a model called the diffusion process and then, Everett Rogers generalized its use in his much-touted 1962 book Diffusion of Innovation (now in the fifth edition ), illustrates how new ideas and technologies are spread across cultures. Others have since used models to illustrate how innovations spread across countries in the US.
See also
- Bass diffusion model
- Diffusion (business)
- Hype cycle
- Lazy user model
- Matches people and technology models
- Technology acceptance model
- Technology life cycle
- Variant Rule
Note
Source of the article : Wikipedia
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