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From Agriculture to Technology: How a 1956 Study Reveals a Surprising Truth About Innovation Adoption?
The progress of science and technology has always been an important driving force for the development of human society. In 1966, George M. Beale and Joe M. Bolen published a landmark study that not only changed the understanding of agricultural technology but also provided a sociological model for the adoption of various innovative products. This model is called the "technology adoption life cycle," and it describes how people adopt new products based on different social and psychological characteristics.
The process of technology adoption is often illustrated by the classic normal distribution curve or "bell curve".
According to the model, the first users to emerge are called "innovators," followed closely by "early adopters." Then came the "early majority," the "late majority," and finally the group known as the "laggards" or "the fearful." For example, a phobe might only use a cloud service when it becomes the only option, but not have the in-depth technical knowledge to operate the service.
The model's initial groupings were based on observations from agricultural research and described the demographic and psychographic characteristics of each adopter group.
According to a 1956 study, innovators had larger farms, were more educated, had more wealth, and were more adventurous, while early adopters were generally younger and more educated and tended to become community leaders. The early majority are relatively conservative but still open to new ideas and are influential in community activities; the late majority are older and less educated, more conservative, and have less social activities; while the lagging behind are usually more conservative and have poor economic conditions. Poorer, oldest and least educated.
Over time, this model has been applied to different areas of technology adoption, especially in policy innovation in the late 20th century.
Application and evolution of the model
The evolution of the model has spawned a series of applicable models, which have expanded the concept of technology adoption to a variety of specific areas. In his famous book "Crossing the Chasm", Geoffrey Moore changed the original life cycle model. He proposed that for constantly changing innovative technologies, there is a gap between innovators and early adopters.
For such technology, the adoption process is often not linear, but has a diverse look.
In the field of educational technology, Lindy McKeown also provides a similar model, using the metaphor of a pencil to describe the adoption of ICT in education. The normalization process theory proposed by medical sociologist Carl May shows how technology is embedded and integrated in medical and other organizations.
Social Impact of Technology Adoption
Together, these models point out that technology adoption is not just a technical process but is deeply embedded in the fabric of society. People's adoption behavior is often influenced by their peers and is sensitive to the popularity of a particular behavior. If friends or colleagues in the community are using a certain technology, an individual's willingness to use it will increase accordingly.
In many format-dependent technologies, people are willing to follow the usage behavior of those around them.
This phenomenon is called the "peer effect" and plays an important catalytic role in the acceptance and popularization of new technologies. By setting adoption thresholds for users, such models can predict the acceptance and expansion of a technology in a specific community.
Summary and future
This 1956 study not only established a model, but also continues to provide inspiration in today's technological context. It prompts us to think about how the adoption of technology is actually a social process. With the rapid advancement of technology, we are faced with new challenges and opportunities, which naturally raises the question: How should individuals and society shape their technology adoption behavior in this ever-changing technological environment?
