Diffusion of Innovations is a theory that seeks to explain how, why, and at what rate new ideas and technology spread through cultures. Everett Rogers, a professor of rural sociology, popularized the theory in his 1962 book Diffusion of Innovations. He said diffusion is the process by which an innovation is communicated through certain channels over time among the members of a social system. The origins of the diffusion of innovations theory are varied and span multiple disciplines.
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The concept was first studied by the French sociologist Gabriel Tarde (1890) and by German and Austrian anthropologists such as Friedrich Ratzel and Leo Frobenius.[1] Its basic epidemiological or internal-influence form was formulated by H. Earl Pemberton,[2] who provided examples of institutional diffusion such as postage stamps and compulsory school laws.
In 1962 Everett Rogers, a professor of rural sociology published Diffusion of Innovations. In the book, Rogers synthesized research from over 508 diffusion studies and produced a theory for the adoption of innovations among individuals and organizations.
The book proposed 4 main elements that influence the spread of a new idea: the innovation, communication channels, time, and a social system. That is, diffusion is the process by which an innovation is communicated through certain channels over time among the members of a social system. Individuals progress through 5 stages: knowledge, persuasion, decision, implementation, and confirmation. If the innovation is adopted, it spreads via various communication channels. During communication, the idea is rarely evaluated from a scientific standpoint; rather, subjective perceptions of the innovation influence diffusion. The process occurs over time. Finally, social systems determine diffusion, norms on diffusion, roles of opinion leaders and change agents, types of innovation decisions, and innovation consequences. To use Rogers’ model in health requires us to assume that the innovation in classical diffusion theory is equivalent to scientific research findings in the context of practice, an assumption that has not been rigorously tested.[3]
The origins of the diffusion of innovations theory are varied and span across multiple disciplines. Rogers identifies six main traditions that impacted diffusion research: anthropology, early sociology, rural sociology, education, industrial, and medical sociology. The diffusion of innovation theory has been largely influenced by the work of rural sociologists.[4]
Elements
The key elements in diffusion research are:
Element | Definition |
---|---|
Innovation | Rogers defines an innovation as "an idea, practice, or object that is perceived as new by an individual or other unit of adoption".[5] |
Communication channels | A communication channel is "the means by which messages get from one individual to another".[6] |
Time | "The innovation-decision period is the length of time required to pass through the innovation-decision process".[7] "Rate of adoption is the relative speed with which an innovation is adopted by members of a social system".[8] |
Social system | "A social system is defined as a set of interrelated units that are engaged in joint problem solving to accomplish a common goal".[9] |
Decisions
Two factors determine what type a particular decision is :
- Whether the decision is made freely and implemented voluntarily,
- Who makes the decision.
Based on these considerations, three types of innovation-decisions have been identified within diffusion of innovations.
Type | Definition |
---|---|
Optional Innovation-Decision | This decision is made by an individual who is in some way distinguished from others in a social system. |
Collective Innovation-Decision | This decision is made collectively by all individuals of a social system. |
Authority Innovation-Decision | This decision is made for the entire social system by few individuals in positions of influence or power. |
Mechanism
Diffusion of an innovation occurs through a five–step process. This process is a type of decision-making. It occurs through a series of communication channels over a period of time among the members of a similar social system. Ryan and Gross first indicated the identification of adoption as a process in 1943 (Rogers 1962, p. 79). Rogers categorizes the five stages (steps) as: awareness, interest, evaluation, trial, and adoption. An individual might reject an innovation at any time during or after the adoption process. In later editions of the Diffusion of Innovations Rogers changes the terminology of the five stages to: knowledge, persuasion, decision, implementation, and confirmation. However the descriptions of the categories have remained similar throughout the editions.
Stage | Definition |
---|---|
Knowledge | In this stage the individual is first exposed to an innovation but lacks information about the innovation. During this stage of the process the individual has not been inspired to find more information about the innovation. |
Persuasion | In this stage the individual is interested in the innovation and actively seeks information/detail about the innovation. |
Decision | In this stage the individual takes the concept of the change and weighs the advantages/disadvantages of using the innovation and decides whether to adopt or reject the innovation. Due to the individualistic nature of this stage Rogers notes that it is the most difficult stage to acquire empirical evidence (Rogers 1964, p. 83). |
Implementation | In this stage the individual employs the innovation to a varying degree depending on the situation. During this stage the individual determines the usefulness of the innovation and may search for further information about it. |
Confirmation | Although the name of this stage may be misleading, in this stage the individual finalises his/her decision to continue using the innovation and may end up using it to its fullest potential. |
Rates of adoption
The rate of adoption is defined as the relative speed with which members of a social system adopt an innovation. It is usually measured by the length of time required for a certain percentage of the members of a social system to adopt an innovation (Rogers 1962, p. 134). The rates of adoption for innovations are determined by an individual’s adopter category. In general, individuals who first adopt an innovation require a shorter adoption period (adoption process) than late adopters.
Within the rate of adoption there is a point at which an innovation reaches critical mass. This is a point in time within the adoption curve that enough individuals have adopted an innovation in order that the continued adoption of the innovation is self-sustaining. In describing how an innovation reaches critical mass, Rogers outlines several strategies in order to help an innovation reach this stage. These strategies are: have an innovation adopted by a highly respected individual within a social network, creating an instinctive desire for a specific innovation. Inject an innovation into a group of individuals who would readily use an innovation, and provide positive reactions and benefits for early adopters of an innovation.
Rogers’ 5 Factors
Rogers defines several intrinsic characteristics of innovations that influence an individual’s decision to adopt or reject an innovation.
Factor | Definition |
---|---|
Relative Advantage | How improved an innovation is over the previous generation. |
Compatibility | The level of compatibility that an innovation has to be assimilated into an individual’s life. |
Complexity or Simplicity | If the innovation is too difficult to use an individual will not likely adopt it. |
Trialability | How easily an innovation may be experimented with as it is being adopted. If a user has a hard time using and trying an innovation this individual will be less likely to adopt it. |
Observability | The extent that an innovation is visible to others. An innovation that is more visible will drive communication among the individual’s peers and personal networks and will in turn create more positive or negative reactions. |
Adopter categories
Rogers defines an adopter category as a classification of individuals within a social system on the basis of innovativeness. In the book Diffusion of Innovations, Rogers suggests a total of five categories of adopters in order to standardize the usage of adopter categories in diffusion research. The adoption of an innovation follows an S curve when plotted over a length of time.[10] The categories of adopters are: innovators, early adopters, early majority, late majority, and laggards (Rogers 1962, p. 150)
Adopter category | Definition |
---|---|
Innovators | Innovators are the first individuals to adopt an innovation. Innovators are willing to take risks, youngest in age, have the highest social class, have great financial lucidity, very social and have closest contact to scientific sources and interaction with other innovators. Risk tolerance has them adopting technologies which may ultimately fail. Financial resources help absorb these failures. (Rogers 1962 5th ed, p. 282) |
Early Adopters | This is the second fastest category of individuals who adopt an innovation. These individuals have the highest degree of opinion leadership among the other adopter categories. Early adopters are typically younger in age, have a higher social status, have more financial lucidity, advanced education, and are more socially forward than late adopters. More discrete in adoption choices than innovators. Realize judicious choice of adoption will help them maintain central communication position (Rogers 1962 5th ed, p. 283). |
Early Majority | Individuals in this category adopt an innovation after a varying degree of time. This time of adoption is significantly longer than the innovators and early adopters. Early Majority tend to be slower in the adoption process, have above average social status, contact with early adopters, and seldom hold positions of opinion leadership in a system (Rogers 1962 5th ed, p. 283) |
Late Majority | Individuals in this category will adopt an innovation after the average member of the society. These individuals approach an innovation with a high degree of skepticism and after the majority of society has adopted the innovation. Late Majority are typically skeptical about an innovation, have below average social status, very little financial lucidity, in contact with others in late majority and early majority, very little opinion leadership. |
Laggards | Individuals in this category are the last to adopt an innovation. Unlike some of the previous categories, individuals in this category show little to no opinion leadership. These individuals typically have an aversion to change-agents and tend to be advanced in age. Laggards typically tend to be focused on “traditions”, likely to have lowest social status, lowest financial fluidity, be oldest of all other adopters, in contact with only family and close friends, very little to no opinion leadership. |
Sample Case Study: Diffusion that Failed
Rogers, in his "Diffusion of Innovation" writings, discussed a situation in Peru that involved the implementation of water boiling to obtain higher health and wellness levels of the individuals living within the village of Los Molinas. The residents of the village have no knowledge of the link between proper sanitation and reduced levels of illness. The campaign was working with the villagers to try and teach them how to boil their water to make it healthier for consumption, as well as to burn their garbage, install working latrines, and report cases of illness to proper agencies. In Los Molinas, a stigma is linked to boiled water as being something that only the "sick" or "unwell" consume, and thus, the idea of healthy residents boiling their water prior to consumption was frowned upon, and those who did so wouldn't be accepted by their society. Thus, the two-year campaign to help bring more sanitary ways of living to this village was considered to be largely unsuccessful. Much of the reason for the lack of success is because the social norms and standards of acceptance into society greatly outweighed the idea of taking on this new innovation, even at the sake of the health, well-being, and greater levels of education to the villagers. This failure better exemplified the importance of the roles of the interpersonal communication channels that are involved in such a health-related campaign for social change.
Heterophily and communication channels
Lazarsfeld and Merton first called attention to the principles of homophily and its opposite, heterophily.[11] Using their definition, Rogers defines homophily as "the degree to which pairs of individuals who interact are similar in certain attributes, such as beliefs, education, social status, and the like".[11] When given the choice, individuals usually choose to interact with someone similar to him or herself.[12] Furthermore, homophilous individuals engage in more effective communication because their similarities lead to greater knowledge gain as well as attitude or behavior change.[12] However, most participants in the diffusion of innovations are heterophilous, meaning they speak different languages, so to speak.[12] The problem is that diffusion requires a certain degree of heterophily; if two individuals are identical, no diffusion occurs because no new information can be exchanged.[12] Therefore, an ideal situation would involve two individuals who are homophilous in every way, except in knowledge of the innovation.[12]
Opinion leaders within a social system
Throughout the diffusion process there is evidence that not all individuals exert an equal amount of influence over all individuals. In this sense there are Opinion Leaders, leaders who are influential in spreading either positive or negative information about an innovation. Rogers relies on the ideas of Katz & Lazarsfeld and the two-step flow theory in developing his ideas on the influence of Opinion Leaders in the diffusion process [13] Opinion Leaders have the most influence during the evaluation stage of the innovation-decision process and late adopters (Rogers 1964, p. 219). In addition opinion leaders have a set of characteristics that set them apart from their followers and other individuals. Opinion Leaders typically have greater exposure to the mass media, more cosmopolitan, greater contact with change agents, more social experience and exposure, higher socioeconomic status, and are more innovative.
Research was done in the early 1950s at the University of Chicago attempting to assess the cost-effectiveness of broadcast advertising on the diffusion of new products and services.[14] The findings were that opinion leadership tended to be organized into a hierarchy within a society, with each level in the hierarchy having most influence over other members in the same level, and on those in the next level below it. The lowest levels were generally larger in numbers, and tended to coincide with various demographic attributes that might be targeted by mass advertising. However, it found that direct word of mouth and example were far more influential than broadcast messages, which were only effective if they reinforced the direct influences. This led to the conclusion that advertising was best targeted, if possible, on those next in line to adopt, and not on those not yet reached by the chain of influence. It can be a waste of money to market to those not yet ready to buy.
Other research relating the concept to public choice theory finds that the hierarchy of influence for innovations need not, and likely does not, coincide with hierarchies of official, political, or economic status.[15] Elites are often not innovators, and innovations may have to be introduced by outsiders and propagated up a hierarchy to the top decision makers.
Organizations
Innovations are often adopted by organizations through two types of innovation-decisions: collective innovation decisions and authority innovation decisions. The collective innovation decision occurs when the adoption of an innovation has been made by a consensus among the members of an organization. The authority-innovation decision occurs when the adoption of an innovation has been made by very few individuals with high positions of power within an organization (Rogers 2005, p. 403). Unlike the optional innovation decision process, these innovation-decision processes only occur within an organization or hierarchical group. Within the innovation decision process in an organization there are certain individuals termed "champions" who stand behind an innovation and break through any opposition that the innovation may have caused. The champion within the diffusion of innovation theory plays a very similar role as to the champion used within the efficiency business model Six Sigma. The innovation process within an organization contains five stages that are slightly similar to the innovation-decision process that individuals undertake. These stages are: agenda-setting, matching, redefining/restructuring, clarifying, routinizing.
Policy Diffusion
The theories of diffusion have spread beyond the original applied fields. In the case of political science and administration, policy diffusion focuses on how institutional innovations are adopted by other institutions, at the local, state or country level. An alternative term is 'policy transfer' where the focus is more on the agents of diffusion such as in the work of Diane Stone.
The first interests with regards to policy diffusion were focused in the variation over time (Berry & Berry 1990 [1] or [2], state lottery adoption) but more recently the interest has shifted towards mechanisms (emulation, learning, coercion, as in Simmons & Elkins 2004 doi:10.1017/S0003055404001078 or Gilardi 2010 doi:10.1111/j.1540-5907.2010.00452.x) or in channels of diffusion (as in Jordana, Levi-Faur and Fernández-i-Marín doi:10.1177/0010414011407466, where the authors find that the creation of regulatory agencies is transmitted by country and sector channels).
Consequences of adoption
There are both positive and negative outcomes when an individual or organization chooses to adopt a particular innovation. Rogers states that this is an area that needs further research because of the biased positive attitude that is associated with the adoption of a new innovation (Rogers 2005, p. 470). In the Diffusion of Innovation, Rogers lists three categories for consequences: desirable vs. undesirable, direct vs. indirect, and anticipated vs. unanticipated.
In her article, "Integrating Models of Diffusion of Innovations," Barbara Wejnert details two categories for consequences: public vs. private and benefits vs. costs.
Public vs. Private
Public consequences refer to the impact of an innovation on those other than the actor, while private consequences refer to the impact on the actor itself.[16] Public consequences usually involve collective actors, such as countries, states, organizations, or social movements.[16] The results are usually concerned with issues of societal well-being.[16] Private consequences usually involve individuals or small collective entities, such as a community.[16] The innovations are usually concerned with the improvement of quality of life or the reform of organizational or social structures.[16]
Benefits vs. Costs
The benefits of an innovation obviously refer to the positive consequences, while the costs refer to the negative.[17] Costs may be monetary or nonmonetary, direct or indirect.[17] Direct costs are usually related to financial uncertainty and the economic state of the actor.[17] Indirect costs are more difficult to identify.[17] An example would be the need to buy a new kind of fertilizer to use innovative seeds.[17] Indirect costs may also be social, such as social conflict caused by innovation [17]
Mathematical treatment
The diffusion of an innovation typically follows an S shaped curve which often resembles a logistic function.
International Institute for Applied Systems Analysis (IIASA)
Several papers on the relationship between technology and the economy have been written by researchers at the International Institute for Applied Systems Analysis (IIASA). The pertinent papers deal with energy substitution and the role of work in the economy as well as with the long economic cycle. Using the logistic function, these researchers were able to provide new insight into market penetration, saturation and forecasting the diffusion of various innovations, infrastructures and energy source substitutions.[18] Cesare Marchetti published on Kondretiev waves and on diffusion of innovations.[19]
A mathematical discussion of diffusion and substition models can be found in th Grübler (1990).[20]
Diffusion data
Diffusion curves for radio, television, VCR, cable, flush toilet, clothes washer, refrigerator, home ownership, air conditioning, dishwasher, electrified households, telephone, cordless phone, cellular phone, per capita airline miles, personal computer and the Internet are available from link on footnote.[21]
Diffusion curves for infrastructures (canals, railroads, highways, pipelines, airlines) and replacement of sailing ships by steam, then steam by diesel and replacement of steam locomotives by diesel are available from a link on the footnote.[20]
Criticism
Much of the evidence for the diffusion of innovations gathered by Rogers comes from agricultural methods and medical practice.
Various computer models have been developed in order to simulate the diffusion of innovations. Veneris[22] [23] developed a systems dynamics computer model which takes into account various diffusion patterns modeled via differential equations.
There are a number of criticisms of the model which make it less than useful for managers. First, technologies are not static. There is continual innovation in order to attract new adopters all along the S-curve. The S-curve does not just 'happen'. Instead, the s-curve can be seen as being made up of a series of 'bell curves' of different sections of a population adopting different versions of a generic innovation.
Rogers has placed the contributions and criticisms of diffusion research into four categories: pro-innovation bias, individual-blame bias, recall problem, and issues of equality.[24]
One of the cons of the Diffusion of Innovation approach is that the communication process involved is a one-way flow of information. The sender of the message has a goal to persuade the receiver, and there is little to no dialogue. The person implementing the change controls the direction and outcome of the campaign. In some cases, this is the best approach, but other cases require a more participatory approach.
Electronic communication social networks
Prior to the introduction of the Internet, it was argued that social networks had a crucial role in the diffusion of innovation particularly Tacit knowledge in the book The IRG Solution - hierarchical incompetence and how to overcome it. The book argued that the widespread adoption of computer networks of individuals would lead to the much better diffusion of innovations, and with greater understanding of their possible shortcomings, and the identification of needed innovations that would not have otherwise occurred - the Relevance paradox.
See also
- Lateral diffusion
- Central media
- Collaborative innovation network
- Critical mass (sociodynamics)
- Delphi technique
- Hierarchical incompetence
- hierarchical organization
- Information Revolution
- Information Routing Group
- Interlock diagram
- Interlock research
- lateral communication
- lateral media
- Lazy User Model
- Opinion leadership
- Pro-innovation bias
- Relevance paradox
- Tacit knowledge
- The Wisdom of Crowds
- Public Choice Theory
References
Diane Stone ‘Transfer Agents and Global Networks in the ‘Transnationalisation’ of Policy’, Journal of European Public Policy, 11(3) 2004: 545-66.
Diane Stone ‘Non-Governmental Policy Transfer: The Strategies of Independent Policy Institutes’, Governance: An International Journal of Policy and Administration, 13 (1) 2000: 45-70.
Diane Stone ‘Learning Lessons and Transferring Policy Across Time, Space and Disciplines’, Politics, 19 (1) 1999: 51-59.
Notations
- Rogers, Everett M. (1962). Diffusion of Innovations. Glencoe: Free Press. ISBN 0612628434. http://books.google.com/?id=zw0-AAAAIAAJ.
- Rogers, Everett M. (1983). Diffusion of Innovations. New York: Free Press. ISBN 978-0-02-926650-2
- Wejnert, Barbara (2002). "Integrating Models of Diffusion of Innovations: A Conceptual Framework". Annual Review of Sociology (Annual Reviews) 28: 297–306. doi:10.1146/annurev.soc.28.110601.141051. JSTOR 3069244.
Notes
- ^ see the article on Trans-cultural diffusion or Roland Burrage Dixon (1928): The Building of Cultures.
- ^ Pemberton, H. E. (1936) 'The Curve of Culture Diffusion Rate', American Sociological Review, 1 (4): 547-556.
- ^ "A Guide to Knowledge Translation Theory"[dead link]
- ^ Ryan (1943), see above.
- ^ (Rogers, 1983. p. 11)
- ^ (Rogers, 1983. p. 17)
- ^ (Rogers 1983, p. 21)
- ^ (Rogers, 1983. p. 21, 23)
- ^ (Rogers, 1983. p. 24)
- ^ J. C. Fisher and R. H. Pry , "A Simple Substitution Model of Technological Change", Technological Forecasting & Social Change, vol. 3, no. 1 (1971)
- ^ a b (Rogers, 1983. p. 18)
- ^ a b c d e (Rogers, 1983. p. 19)
- ^ Katz, Elihu & Lazarsfeld, Paul (1955). Personal influence: The part played by people in the flow of mass communications, Glencoe: Free Press
- ^ Bell, W.E. (1963), "Consumer Innovators: A Unique Market for Newness," in Toward Scientific Marketing, ed. Stephen A. Greyser, Chicago: American Marketing Association, 90-93.
- ^ Economic policy making in evolutionary perspective, by Ulrich Witt, Max-Planck-Institute for Research into Economic Systems.
- ^ a b c d e (Wejnert, "Integrating Models of Diffusion of Innovations," p. 299)
- ^ a b c d e f (Wejnert, "Integrating Models of Diffusion of Innovations," p. 301)
- ^ Ayres, Robert (1989). Technological Transformations and Long Waves. http://www.iiasa.ac.at/Admin/PUB/Documents/RR-89-001.pdf
- ^ [|Marchetti, Cesare] (1996). Pervasive Long Waves: Is Society Cyclotymic. http://www.agci.org/dB/PDFs/03S2_CMarchetti_Cyclotymic.pdf
- ^ a b Grübler, Arnulf (1990). The Rise and Fall of Infrastructures: Dynamics of Evolution and Technological Change in Transport. Heidelberg and New York: Physica-Verlag. pp. 12–25. http://www.iiasa.ac.at/Admin/PUB/Documents/XB-90-704.pdf
- ^ Moore, Stephen; Simon, Julian (Dec. 15, 1999). The Greatest Century That Ever Was: 25 Miraculous Trends of the last 100 Years, The Cato Institute: Policy Analysis, No. 364. http://www.cato.org/pubs/pas/pa364.pdf
- ^ Veneris, Yannis (1984). The Informational Revolution, Cybernetics and Urban Modelling, PhD Thesis. University of Newcastle upon Tyne, UK.
- ^ Veneris, Yannis (1990). "Modeling the transition from the Industrial to the Informational Revolution". Environment and Planning A 22 (3): 399-416. doi:10.1068/a220399.
- ^ Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.
External links
- The Diffusion Simulation Game, about adopting an innovation in education.
- The Pencil Metaphor on diffusion of innovation particularly ICT in education.
- Diffusion of Innovations, by Jon Roland, summarizing ideas in the field.
- [3], Diffusion of Innovations,Strategy and Innovations. The D.S.I Framework by Francisco Rodrigues Gomes, Academia.edu share research.