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The Secret of Technology Adoption: Why Do Some People Always Adopt New Technologies First?
In today's world where technology is developing at a rapid pace, why are some people able to become early adopters of new technologies? Behind this question lies a sociological model called the “technology adoption life cycle.” This model divides adopters according to the characteristics of user groups and describes the process by which new products or innovations are accepted. It not only involves the adoption of technology, but also maps the impact of social and cultural context on technological progress.
The technology adoption life cycle is often depicted as a classical normal distribution or "bell curve."
According to this model, the first group of people to use a new product are called “innovators,” followed by “early adopters.” Next are the “early majority” and “late majority”, and the last group is the “laggards” or “fearfuls”. Laggards are often those who adopt new technologies when they have no other choice. They usually have a relatively shallow understanding of technology and may even be completely dependent on technical support provided by others.
Psychology and characteristics of adopters
According to a 1956 description by some agricultural researchers, different categories of adopters have different psychological and social characteristics:
Innovators: have more human resources, higher education, and dare to take risks;
Early Adopters: Young, relatively well-educated, and often leaders in their communities;
Early Majority: more conservative, but open to new ideas and more active in community activities;
Late majority: older, less educated, less socially active;
Laggards: Conservative, with limited funding and technical knowledge.
This model was later widely used in various fields of technology adoption and further evolved into specific applications for different industries.
Adaptation and extension of the model
Furthermore, this model has also undergone many adaptations and extensions. For example, in his book Crossing the Chasm, Geoffrey Moore proposes a variation on the original life cycle. He believes that in some cases, especially for disruptive innovation, there is a "chasm" between innovators and early adopters, which makes the adoption of technology more complicated.
Like disruptive innovation, this process can lead to disruptive changes in the economy, which is exactly the "disruptive innovation" model proposed by Clayton M. Christensen.
In different fields, relevant scholars and experts have also put forward their own views. For example, in the field of educational technology, Lindy McKeown used the metaphor of a pencil to describe the application of information and communication technology in education. Carl May proposed the "normalization process theory" in medical sociology to explore how technology is integrated into the health care system.
Social influence and network effects
Research also shows that adopters’ behavior is influenced by the people around them, and their perceptions of a technology’s adoption behavior can also influence the final choice. In many format-dependent technologies, people have a non-zero payoff, meaning that their satisfaction increases if their friends or colleagues adopt the same technology.
For example, studies have shown that if two-thirds of a person's neighbors choose a certain product, their chances of adoption increase.
This model provides a way to deterministically model product adoption behavior in a sample network and reveals the underlying mechanism of adoption behavior in social networks.
Historical Background of Technology Adoption
The technology adoption life cycle model dates back to 1956 when it was first published by George M. Beal and Joe M. Bohlen. Subsequently, Everett M. Rogers' academic contribution further extended this model to areas beyond agriculture and systematized and popularized it in his 1962 book Diffusion of Innovations.
In today's era of rapid technological development, behind every adopter's choice are deep-seated social, cultural and personal psychological factors. Understanding these factors not only helps us better understand the process of technology adoption, but also allows us to reflect on our own attitudes toward new technologies: Will you be one of these innovators?
