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技术采用生命周期

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技术采用生命周期(Technology Adoption LifeCycle)

技术采用生命周期概述[1]

  技术采用生命周期(Technology Adoption LifeCycle),如图一所示,为1957年Iowa State College为分析玉米种子采购行为所提出。起先,该概念的提出并未获得许多回响,一直要等到1962年Everett Rogers出版《创新的扩散》(Diffusion of Innovations)一书后[2],才逐渐获得学研界的重视。

  技术采用生命周期为一钟形曲线(Bell Curve),该曲线将消费者采用新技术的过程分成五个阶段,分别包括创新者、早期采用者、早期大众、晚期大众与落后者。上述五个阶段的占整体使用人数比例分别为2.5%、13.5%、34%、34%与16% 。根据Roger的研究,上述五个不同阶段的使用者具不同特色,包括:

  • 创新者(innovators)2.5% - venturesome, educated, multiple info sources, greater propensity to take risk (冒险家)
  • 早期采用者(early adopters)13.5% - social leaders, popular, educated (意见领袖)
  • 早期大众(early majority)34% - deliberate, many informal social contacts (深思熟虑者)
  • 晚期大众(late majority)34% - skeptical, traditional, lower socio-economic status (传统百姓)
  • 落后者(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 early majority - more conservative but open to new ideas, active in community and influence to neighbours.

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

4.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.

技术生命周期与产品生命周期之相异点[1]

  表一、技术生命周期与产品生命周期之相异点

相似点周期曲线均为钟形曲线
差异点1.产品生命周期包含4阶段,技术采用生命周期为5阶段曲线

2.技术采用生命周期将每一阶段均有量化指标,其中2.5%、13.5%与34%即为关键数字
3.技术采用生命周期除强调每一阶段发展策略外,亦强调横跨不同阶段(介面议题)所需考量之策略议题。

参考文献

  1. 1.0 1.1 David.技术采用生命周期及死亡之井对新产品行销启示.科技产业资讯室
  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.