Diffusing Innovations

From the study of the spread of a hybrid corn seed among U.S. Midwestern farmers to the examination of the adoption of computer centers among the urban poor in South Africa; from the investigation of how cellphones were massively adopted in the U.S. to the study of the diffusion of family planning practices in developing countries; researchers from a variety of disciplines have been studying the process through which innovations spread in a social system. In these studies, an innovation is understood broadly as an idea, a practice, a service, or a technology, that is perceived as new (a novelty) among members of a community, an organization, or a social system. (Rogers 1962, 2003)

Drawing on rational theories from economics, sociology, and communication, a whole research tradition emerged with the name of Diffusion of Innovations (DoI). Its goal has been to understand diffusion as a communication process “by which an innovation is communicated through certain channels over time among the members of a social system” (Rogers, 2003, 6). This process is dynamic, linear, and involves four major components: the innovation, communication channels, time (including innovation-decision process, adopter’s degree of innovativeness, and rate of adoption), and the social system. Some of the main questions that DoI researchers have tried to answer are: How are innovations diffused in a social system? What are the characteristics of the individuals and communication channels involved in the diffusion process? Why do some innovations spread rapidly and others slowly?

The Diffusion of Innovations (DoI) Model

The DoI model is rational and systemic, and involves a series of stages that unfold over a specific period of time. The model includes multiple variables, steps, and four major components that have been studied and empirically tested by researchers and practitioners from a variety of fields.


The first component of the model is the innovation itself. That is, “an idea, practice, or object that is perceived as new by an individual or other unit of adoption.(…) If the idea seems new to the individual, it is an innovation” (Rogers 2013, 11)

According to how innovations are perceived by people they are adopted with rapid or slower rates. Rogers (1962; 1971; 1983; 1995, 2003) has identified five different innovation characteristics:

  1. Relative advantage (how an individual perceives an innovation as better than the idea it supersedes);
  2. Compatibility (how an innovation is consistent with norms, values, and needs of adopters);
  3. Complexity (how an innovation is perceived as difficult to use and understand);
  4. Trialability (how an innovation can be experimented and tried on the installment); and
  5. Observability (how the results of an innovation are visible to others) (Rogers 2003).

Communication Channels
The second component of the model is the communication channels. According to Rogers, a “communication channel is the means by which messages get from one individual to another” (2003, 17). Communication channels allow individuals to create and share information with each other. Although originally these channels included only mass media and interpersonal communication, in recent years DoI researchers have also started to include the internet, cellphones and other information communication technologies (Rogers et al. 2009).

Given their wide reach and big audience, mass media channels are the most efficient means to create awereness-kwoledge about the existence of an innovation. However, they are not the most influential in the decision to adopt or reject an innovation. Interpersonal channels “are more effective in persuading an individual to adopt a new idea, especially if the interpersonal channel links two or more individuals who are near-peers” (Rogers, 2003, 18).

Although homophily among individuals makes communication more effective, in the process of diffusion of innovations, there is always at least some degree of heterophony. As Rogers explained, “ideally, they would be homophilous on all other variables (education, social status, and the like) even though they are heterophilous regarding the innovation.”(19) The emphasis on interpersonal communication has opened opportunities for doing network analysis of the social and peer relationships among the individuals participating in the DoI process (Valente 1995, 2006).


Time is the third component of the DoI model and is the most complex one. It involves three different dimensions that have been analyzed according to particular variables and stages. According to the DoI theory, a population adopts innovations in a time sequence, following a multi-step diffusion process (Rogers & Scott, 1997; Dearing, 2008).

The first dimension is the innovation-decision process. In this process an individual or an organization goes through five different steps:

  1. knowledge (an individual becomes aware of an innovation and has some idea of how it functions);
  2. persuasion (forms a favorable or unfavorable attitude toward the innovation),
  3. decision (engages in activities that lead to a choice to adopt or reject the innovation),
  4. implementation (puts an innovation into use), and
  5. confirmation (evaluates the results of an innovation- decision already made).

The second dimension of time is related to the adopter’s innovativeness. That is, to the “degree to which an individual or other unit of adoption is relatively earlier in adopting new ideas than the other members of a system” (Rogers 2003, 22). According to the DoI model, individuals who adopt innovations in a social system can be categorized according to five different, and mutually exclusive, categories. They could be:

  1. innovators,
  2. early adopters,
  3. early majority,
  4. late majority, and
  5. laggards.

These categories are ideal types that are placed on an innovativeness continuum that expands through time. Each of them has specific characteristics that are related to socioeconomic status (e.g. early adopters have higher status), communication behavior (e.g. early adopters are highly interconnected), and personality traits (e.g. early adopters have greater empathy and intelligence) (Rogers, 1962; 1971; 1983; 1995, 2003). The adopter characteristics are generalizations that can be measured as variables. According to Rogers, they “provide a basis for audience segmentation strategies by diffusion agencies”(2003, 263) and facilitate researchers’ comparative analysis.

The third dimension of the time component is the rate of adoption. That is, the relative speed in which an innovation is adopted by individuals or units in a social system. The rate is measured using an innovation or a system as the unit of analysis. Usually it is measured by the length of time required for a number of the members of the system (a percentage) to adopt the innovation. According to Rogers (1962; 1971; 1983; 1995, 2003), most innovations have an S-shaped rate of adoption represented on the S- shaped cumulative curve of the number of adopters plotted over time. However, depending on the rate of adoption, the slope of the “S” can be steeper if it the innovation diffuses rapidly or less steep if it disseminates slowly. As Rogers explained, “at first, only a few individuals adopt the innovation in each time period (such as a year or a month, for example); these are the innovators. But soon the diffusion curve begins to climb, as more and more individuals adopt. Then the trajectory of the rate of adoption begins to level off, as fewer and fewer individuals remain who have not yet adopted. Finally, the s- shaped curve reaches its asymptote, and the diffusion process is finished” (2003, 23).

Social Systems

The social system is the fourth component of the DoI. According to Rogers, the system is “defined as a set of interrelated units that are engaged in joint problem solving to accomplish a common goal.” (2003, 24) Individuals, organizations or other kinds of groups can be considered units or members of a system. They have relationships and share a common goal that maintains the system together and creates its boundaries. In order to understand how the social system influence the process of diffusion, DoI researchers have analyzed the following issues: the characteristics of the social and communication structure, the effect of norms, the roles of opinion leaders and change agents, the types of innovation decisions, and the consequences of innovation. (Rogers 1962; 1971; 1983; 1995, 2003)

In the DoI model, the structure of the social system, and particularly its communication structure, affects the process of diffusion. While the social structure is understood as the formal “patterned social relationships” among the members of the system, the communication structure is more informal and consists of the “interpersonal networks linking a system’s members, determining who interacts with whom and under what circumstances” (Rogers 2003, 25). It is in the communication structure where communication flows happen.


  • Dearing, J. (2008) “Evolution of Diffusion and Dissemination Theory.” Journal of Public Health Management and Practice. Issue: Volume 14(2), March/April 2008, p 99–108
  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press. Rogers, E. M. (1995). Diffusion of innovations (4th ed.). New York: Free Press.
  • Rogers, E. M., & Scott, K. L. (1997, December 10). The diffusion of innovations model and outreach from the national network of libraries of medicine to Native American communities. [Draft]. National Network of Libraries of Medicine, Pacific Northwest Region, Seattle. Retrieved from http://nnlm.gov/archive/pnr/eval/rogers.html
  • Rogers, Singhal & Quinlan (2009) Diffusion of Innovations. In Don Stacks and Michael Salwen (Eds) . An integrated approach to communication theory and research. New York: Routledge.
  • Valente, T.W. (2006). Communication network analysis and the diffusion of innovations. In A. Singhal & J.W. Dearing, J.W. Communication of innovations: A journey with Ev
  • Rogers (pp. 61-82). Thousand Oaks, CA: Sage.
    Valente, T. W. (1995). Network models of the diffusion of innovations. Creskill, NJ: Hampton Press.

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