技術採用生命周期

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技術採用生命周期(Technology Adoption LifeCycle)

目錄

技術採用生命周期概述[1]

  技術採用生命周期(Technology Adoption LifeCycle),如圖一所示,為1957年Iowa State College為分析玉米種子採購行為所提出。起先,該概念的提出並未獲得許多迴響,一直要等到1962年Everett Rogers出版《創新的擴散》(Diffusion of Innovations)一書後[2],才逐漸獲得學研界的重視。

  技術採用生命周期為一鐘形曲線(Bell Curve),該曲線將消費者採用新技術的過程分成五個階段,分別包括創新者、早期採用者、早期大眾、晚期大眾與落後者。上述五個階段的占整體使用人數比例分別為2.5%、13.5%、34%、34%與16% 。根據Roger的研究,上述五個不同階段的使用者具不同特色,包括:

  • 創新者(innovators)2.5% - venturesome, educated, multiple info sources, greater propensity to take risk (冒險家)
  • 早期採用者(early adopters)13.5% - social leaders, popular, educated (意見領袖
  • 早期大眾(early majority)34% - deliberate, many informal social contacts (深思熟慮者)
  • 晚期大眾(late majority)34% - skeptical, traditional, lower socio-economic status (傳統百姓)
  • 落後者(laggards)16% - neighbours and friends are main info sources, fear of debt(落伍者)

Technology adoption lifecycle

The technology adoption lifecycle is a sociological model developed by Joe M. Bohlen, George M. Beal and Everett M. Rogers at Iowa State College,[3] building on earlier research conducted there by Neal C. Gross and Bryce Ryan.[4][5][6] Their original purpose was to track the purchase patterns of hybrid seed corn by farmers.

Beal, Rogers and Bohlen together developed a technology diffusion model[7] and later Everett Rogers generalized the use of it in his widely acclaimed book, Diffusion of Innovations[8] (now in its fifth edition), describing how new ideas and technologies spread in different cultures. Others have since used the model to describe how innovations spread between states in the U.S.[9]

Image:DiffusionOfInnovation.png

A graph of Everett Rogers Technology Adoption Lifecycle model. Drawn in OmniGraffle and then trimmed in Apple Preview.

The technology adoption lifecycle model describes the adoption or acceptance of a new product or innovation, according to the demographic and psychological characteristics of defined adopter groups. The process of adoption over time is typically illustrated as a classical normal distribution or "bell curve." The model indicates that the first group of people to use a new product is called "innovators," followed by "early adopters." Next come the early and late majority, and the last group to eventually adopt a product are called "laggards."

The demographic and psychological (or "psychographic") profiles of each adoption group were originally specified by the North Central Rural Sociology Committee, Subcommittee for the Study of the Diffusion of Farm Practices (as cited by Beal and Bohlen in their study above).

The report summarised the categories as:

1.innovators - had larger farms, were more educated, more prosperous and more risk-oriented.

2.early adopters - younger, more educated, tended to be community leaders

3.early majority - more conservative but open to new ideas, active in community and influence to neighbours.

4.late majority - older, less educated, fairly conservative and less socially active.

5.laggards - very conservative, had small farms and capital, oldest and least educated.

Adaptations of the model

The model has spawned a range of adaptations that extend the concept or apply it to specific domains of interest. In this book, Crossing the Chasm, Geoffrey Moore proposes a variation of the original lifecycle. He suggests that for discontinuous or disruptive innovations, there is a gap or chasm between the first two adopter groups (innovators/early adopters), and the early majority. In Educational technology, Lindy McKeown has provided a similar model (a pencil metaphor[10]) describing the ICT uptake in education.

Examples

One way to model product adoption[11] is to understand that people's behaviors are influenced by their peers and how widespread they think a particular action is. For many format-dependent technologies, people have a non-zero payoff for adopting the same technology as their closest friends or colleagues. If two users both adopt product A, they might get a payoff a > 0; if they adopt product B, they get b > 0. But if one adopts A and the other adopts B, they both get a payoff of 0.

We can set a threshold for each user to adopt a product. Say that a node v in a graph has d neighbors: then v will adopt product A if a fraction p of its neighbors is greater than or equal to some threshold. For example, if v's threshold is 2/3, and only one of its two neighbors adopts product A, then v will not adopt A. Using this model, we can deterministically model product adoption on sample networks.

技術生命周期與產品生命周期之相異點[1]

  表一、技術生命周期與產品生命周期之相異點

相似點周期曲線均為鐘形曲線
差異點1.產品生命周期包含4階段,技術採用生命周期為5階段曲線

2.技術採用生命周期將每一階段均有量化指標,其中2.5%、13.5%與34%即為關鍵數字
3.技術採用生命周期除強調每一階段發展策略外,亦強調橫跨不同階段(介面議題)所需考量之策略議題。

參考文獻

  1. 1.0 1.1 David.技術採用生命周期及死亡之井對新產品行銷啟示.科技產業資訊室
  2. Diffusion of innovations
  3. Bohlen, Joe M.; Beal, George M. (May 1957), "The Diffusion Process", Special Report No. 18 (Agriculture Extension Service, Iowa State College) 1: 56–77.
  4. Gross, Neal C. (1942) The diffusion of a culture trait in two Iowa townships. M.S. Thesis, Iowa State College, Ames.
  5. Ryan, Bryce, and Neal C. Gross (1943) “The diffusion of hybrid seed corn in two Iowa communities.” Rural Sociology 8: 15-24. RS(E)
  6. Ryan, Bryce, and Neal C. Gross (1950) Acceptance and diffusion of hybrid corn seed in two Iowa communities. Research Bulletin 372, Agricultural Experiment Station, Ames, Iowa.
  7. Beal, George M., Everett M. Rogers, and Joe M. Bohlen (1957) "Validity of the concept of stages in the adoption process." Rural Sociology 22(2):166-168.
  8. Rogers, Everett M. (1962). Diffusion of Innovations, Glencoe: Free Press.
  9. Savage, Robert L. (1985). "Diffusion Research Traditions and the Spread of Policy Innovations in a Federal System" Publius 15 (Fall): 1-27.
  10. Pencil metaphor
  11. Von Ahn, Luis. (2008) Science of the Web lectures at Carnegie Mellon University.
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