Communication Theory/Diffusion of Innovations
Origins of the diffusion paradigmEdit
According to Rogers (1995), the study of the diffusion of innovations (DOI) can be traced back to the investigations of French sociologist Gabriel Tarde (p. 52). Tarde attempted to explain why some innovations are adopted and spread throughout a society, while others are ignored. At the beginning of the twentieth century, Tarde was witness to the development of many new inventions, many of which led to social and cultural change. In his book The Laws of Imitation (1903), Tarde introduced the S-shaped curve and opinion leadership, focusing on the role of socioeconomic status (for example, a cosmopolitan individual is more likely to adopt new products). Even though he did not specify and clarify key diffusion concepts, his insights affected the development of many social scientific disciplines such as geography, economics, and anthropology. Sociologist F. Stuart Chapin, for example, studied longitudinal growth patterns in various social institutions, and found that S-shaped curves best described the adoption of phenomena such as the commission form of city government (Lowery & Defleur, 1995, p. 118).
The basic research paradigm for the diffusion of innovationsEdit
The fundamental research paradigm for the diffusion of innovations can be traced to the Iowa study of hybrid seed corn. Bryce Ryan and Neal C. Gross (1943) investigated the diffusion of hybrid seed corn among Iowa farmers. According to Lowery and DeFleur (1995), the background of rural sociology should first be understood before one can discuss how and why the hybrid seed corn study was conducted. The Morrill Act helped “the states establish educational institutions that would be of special benefit to rural youth” (p. 120). Federal funds and other financial supports were given to these land-grant institutions in order to increase the development of the nation’s agricultural industry (p. 120). After World War II, rural sociologists changed their research focus on human problems among farmers because new agricultural technology such as new pesticides, new farm machine, and hybrid seed corn appeared. But in spite of these developments, some farmers ignored or resisted these new innovations. Rural sociologists at land-grant universities in the Midwestern United States such as Iowa State, Michigan State, and Ohio State Universities, performed many diffusion studies to find out the causes of adoption of innovations. One of these efforts was the hybrid seed corn study conducted by Ryan and Gross (1943). These researchers attempted to explain why some farmers adopted the hybrid seed corn, while others did not.
Bryce Ryan and Neal C. GrossEdit
Bryce Ryan earned a Ph. D in sociology at Harvard University. During his doctoral studies, Ryan was required to take interdisciplinary courses in economics, anthropology, and social psychology. This intellectual background helped him conduct the diffusion studies. In 1938, Ryan became a professor at Iowa State University which is known for its agricultural focus. At that time, Iowa State administrators were worried about the slow rate at which the hybrid seed corn was being adopted. Despite the fact that the use of this new innovation could lead to an increase in quality and production, an advantageous adoption by Iowa Farmers was slow. Ryan proposed the study of the diffusion of the hybrid seed corn and received funding from Iowa Agricultural Experiment Station, Iowa State University’s research and development organization. Contrary to previous research, which employed anthropological style approaches using qualitative methods, Ryan employed a quantitative survey method in his study. According to Rogers (1996), Ryan was encouraged to use this quantitative method by “professors in the Department of Statistics, such as Paul G. Homemeyer, Ray J. Jessen, and Snedecor” (p. 415).
When Ryan arrived at Iowa State University, Neal C. Gross was a graduate student who was soon assigned as Ryan’s research assistant. Ryan asked him to conduct interviews with Iowa farmers through survey research. Gross gathered the data from the Iowa communities of Jefferson and Grand Junction. Rogers (1996) mentioned that “by coincidence, these communities were located within 30 miles of where he grew up on a farm” (p. 415). It is also interesting to note that Rogers earned a Ph. D. in sociology and statistics at Iowa State University in 1957.
The Iowa Study of Hybrid Seed Corn: The Adoption of InnovationEdit
As noted above, the hybrid seed corn had many advantages compared to traditional seed, such as the hybrid seed's vigor and resistance to drought and disease. However, there were some barriers to prevent Iowa farmers from adopting the hybrid seed corn. One problem was that the hybrid seed corn could not reproduce (p. 122). This meant that the hybrid seed was relatively expensive for Iowa farmers, especially at the time of the Depression. Therefore, it is reasonable to assume that, despite the economic profit that the hybrid seed corn brought, its high price made a adoption among Iowa farmers remain slow.
According to Lowery and DeFleur (1995), Ryan and Gross sought to explain how the hybrid seed corn came to attention and which of two channels (i.e., mass communication and interpersonal communication with peers) led farmers to adopt the new innovation. They found that each channel has different functions. Mass communication functioned as the source of initial information, while interpersonal networks functioned as the influence over the farmers’ decisions to adopt (p. 125). One of the most important findings in this study is that “the adoption of innovation depends on some combination of well-established interpersonal ties and habitual exposure to mass communication” (p. 127). Ryan and Gross also found that the rate of adoption of hybrid seed corn followed an S-shaped curve, and that there were four different types of adopters. According to Rogers (1995), Ryan and Gross also made a contribution by identifying the five major stages in the adoption process, which were awareness, interest, evaluation, trial, and adoption. After Ryan and Gross’s hybrid corn study, about 5,000 papers about diffusion were published in 1994 (Rogers, 1995).
Medical innovation: Diffusion of a medical drug among doctorsEdit
According to Rogers (1996), diffusion theory became more widely accepted after James S. Coleman, Elihu Katz, and Herbert Menzel conducted a study on the diffusion of tetracycline, a new medical drug, in 1966. The Pfizer drug company invented this successful new drug and wanted to investigate the effectiveness of their tetracycline advertisements, which were placed in medical journals. The company asked three professors at Columbia University to find out how physicians adopted the new innovation and how mass communication influenced this adoption process. They conducted a survey to gather accurate and reliable data. Different with previous diffusion research that relied on respondents’ recall of how they adopted new technology, this study gathered data both from physicians' responses and pharmacies' prescription. In addition to this, Coleman et al. (1966) asked their respondents to list their interpersonal connections in order to investigate the effect of interpersonal network links with the new drug adoption. The result shows that the percentage of adoption of the new drug followed an S-shaped curve, but that the rate of tetracycline adoption was faster than the rate of other innovations adoption. The researchers also found that doctors who are cosmopolite were likely to adopt the new drug. One of the most important findings was that doctors who had more interpersonal networks adopted the new medical drug more quickly than those that did not. This meant that interpersonal communication channels with peers had a strong influence on the adoption process. Rogers (1996) noted that this Columbia University study is “one of the most influential diffusion studies in showing that the diffusion of an innovation is essentially a social process that occurs through interpersonal networks” (p. 419). In fact, Rogers (1996) mentioned that even though the study of Ryan and Gross became a milestone in diffusion paradigm, they did not measure the interpersonal network links among farmers. In this case, the Columbia University Drug Study made a contribution to identify the importance of social networks in the diffusion process.
Everett M. RogersEdit
Rogers was born in Carroll, Iowa in 1931. He earned his B.A., M.A., and Ph.D. degrees from Iowa State University. For two years during the Korean War, he served in the U.S. Air Force. Interestingly, in 1966, he worked on some family planning communication projects in Korea.
One interesting thing worthy mentioning is that Rogers’ father was a farmer who resisted adopting the hybrid seed corn (Singhal, 2005, p. 287). Due to the drought in Iowa in 1936, the Rogers’ farm withered, which made Rogers personally involved in the diffusion research. In the 1950's, Iowa State University was a perfect place for studying the diffusion of innovations, as the school's program focused on a rural sociology, agriculture, and statistics. The experience there led Rogers to dive into the research about why some innovations are adopted while others are ignored. Employed by Michigan State University in 1962, Rogers obtained opportunity to study diffusion in developing countries of Asia, Latin America, and Africa. Meanwhile, he published the book, Diffusion of Innovations, which earned him his academic reputation. Rogers’ comprehensive insights in the book helped to expand diffusion theory. The book has become the standard textbook on diffusion theory and it creats applications of diffusion theory in such fields as geography, economics, psychology, political science, and, as previously mentioned, communication. Rogers retired from University of New Mexico in 2004 because he was suffering from kidney disease. He died on October 21, 2005.
Overview of the diffusion of innovationsEdit
According to Rogers (1996), diffusion refers to “the process by which an innovation is communicated through certain channels over time among the members of a social system. An Innovation is an idea, practice or object perceived as new by an individual or other unit of adoption. The diffusion of innovations involves both mass media and interpersonal communication channels” (p. 409). That is, by sharing communication channels such as interpersonal communication or mass communication people can get information of an innovation and perceive its innovation as useful. Lasswell (1948) presented a well-known model of communication that is analyzed as five parts, S-M-C-R-E (e.g., sender-message-channel-receiver-effect). Rogers (1995) mentioned, “this S-M-C-R-E communication model corresponds closely to the elements of diffusion” (p. 19). Specifically, (1) sender can be inventors or opinion leaders, (2) message can be a new idea or product, (3) channels can be interpersonal or mass communication, (4) receivers can be members of a social system, and finally (5) the effects can be individual’s adoption or social change. In the diffusion theory, ‘Time’ variable is a very important factor. According to Rogers (1995), time variable is involved in diffusion in (1) the innovation-decision process; (2) innovativeness; (3) an innovation’s rate of adoption.
Most innovations have an S-shaped rate of adoption. Diffusion research has attempted to explain the variables that influence how and why users and audience adopt a new information medium, such as the Internet. According to evolution of media technology, interpersonal influences are important even though in the past the individual is usually the unit of analysis. Also, critical mass becomes an important factor in adopting new media because new media are interactive tools and thus are required by many users to gain efficiency. That is, the more people use, the more people get benefits. In this sense, diffusion theory not only can apply to practical things, but also can be related to digital divide.
There are five different types of adopters in the diffusion process, according to Innovativeness: “(1) Innovators (venturesome), (2) Early Adopters (respectable), (3) Early Majority (Deliberate), (4) Late Majority (skeptical), and (5) Laggards (traditional)” (Rogers, 1995, pp. 183–185). Rogers defined this term as “the degree to which an individual is relatively earlier in adopting new ideas than other members of his social system” (Rogers, 1995, p. 40). Figure 1 shows the relationships between types of adopters divided by innovativeness and their place on the adoption curve. Also, these categories follow a standard deviation curve which is bell-shaped.
Source by www2.gsu.edu/~wwwitr/docs/diffusion/
Figure 2 shows that an innovation would spread through society over various periods of time in a S-shaped curve. However, as noted above, different types of innovations (e.g., the rate of tetracycline adoption is faster than that of the hybrid seed corn) can have their own different rates in diffusion.
Figure 2. Shapes of curves of diffusions for innovations
Source by: www.mitsue.co.jp/english/case/concept/02.html
When it comes to the process of innovation-decisions, Rogers (1995) mentioned that there are five stages.
- Knowledge + or – (selective exposure or awareness of news)
- Attitudes + or – (people have positive or negative attitude toward innovations)
- Adoption (Decision): people decide to adopt the innovation
- Implementation (regular or standard practice)
- Confirmation (comparing and evaluating)
Rogers introduced perceived characteristics of innovations that consist of (1) relative advantage (2) compatibility (3) complexity (4) triability (5) observability. Based on these five criteria, individuals perceive an innovation as new or useful and decide to adopt it. For example, Rogers (1995) defined relative advantage as “the degree to which an innovation is perceived as better than the idea it supersedes” (p. 15).” New media such as the mp3 will displace conventional media such as CDs or tapes when people perceive new media as advantageous (e.g., low cost or means to be cool). When an individual decides to adopt new media or switch old media with new media, the perceived characteristics of innovations play an important role in reducing some uncertainty about the innovations.
Unit of analysis on diffusion theoryEdit
Diffusion of innovation theory attempts to explain how an innovation is spread and why it is adopted at both the micro and macro levels of analysis. Rogers (1996) mentioned, “the individual is usually the unit of analysis, although in recent years a number of studies have been conducted in which an individual organization is the unit of analysis (Wildemuth, 1992; Zaltman, Duncan, & Holbek, 1973)” (p. 418). This characteristic of unit of analysis is due to research methods, such as utilizing a survey to study diffusion. Many studies have focused on individual decisions or adoption. In contrast, diffusion theory considers analysis at both the micro-individual and macro-social levels. This is because studies of diffusion include both an innovation at the micro level, as well as its influence, such as social change, at the macro level.
Rogers (1995) suggested that the four main elements in the diffusion of innovation process were innovation, communication channels, time, and social system. Individuals’ innovativeness, or psychological factors such as communication needs, are analyzed as micro-independent variables. At the macro-social level, this theory assumes that social systems, such as norms, can affect an individual’s adoption or use of an innovation. In terms of communication channels, diffusion of an innovation involves both interpersonal channels (micro) and mass communication channels (macro). By utilizing both mass and interpersonal communication channels, people can get information about an innovation and perceive its usefulness. Therefore, diffusion theory requires both micro-individual and macro-social analysis.
Several diffusion research streamsEdit
According to Rice & Webster (2002), ["research and models of the adoption, diffusion, and use of new communication media in organizational settings have arisen from several research streams -- diffusion of innovations, media choice, and implementation of information systems." According to the previous writer of this Wikibook,] we can classify diffusion research and models into three categories: (1) diffusion of innovations (e.g., Rogers, 1995), (2) media choice (e.g., Daft & Lengel, 1986), and (3) implementation of information systems (e.g., Saga & Zmud, 1994). [Unfortunately, one cannot generalize all diffusion research and models with an explanation of diffusion of new communication media.] Table 1 shows that each dependent variable, according to three primary streams of diffusion studies.
Table 1 (Needs to be cleaned up using piping!) The diffusion Of innovation The Media choice The Information system Dependent variable Media adoption Usage Choice Evaluation Acceptance User satisfaction Source by: Rice, R., & Webster, J. (2002). Adoption, diffusion and use of new media. In C. Lin and D. Atkin (Eds.), Communication Technology and Society.
That is, the ‘diffusion of innovations’ studies emphasize characteristics of an innovation and the role of communication channels in adopting the innovation, the ‘media choice’ studies focus on the interaction between individual characteristics and social influences in choosing some innovations, and the ‘implementation’ studies assume that the variables such as technology design or ease of use will affect media use (Rice & Webster, 2002, p. 192).
The diffusion tradition has classified people, in terms of demographics, in explaining the variables that influence the adoption of an innovation. For that reason, some scholars often criticize that this theory may not provide a causal explanation of why and how people adopt certain technologies. Nevertheless, when it comes to the use and choice of old and new media, diffusion theory will be suited for explaining why some people prefer to use the old media or new media, because this theory provides some conceptual guidance for understanding the adoption of some technologies or innovations. According to evolution of media technology, interpersonal influences or channels are important even though in the past the individual is usually the unit of analysis. Also, critical mass becomes an important factor in adopting new media because new media are interactive tools and thus are required to many users for getting efficiency. That is, the more people use, the more people get benefits. Markus (1987) proposed that the value of an interactive communication medium is associated with the number of other users. For example, in the case of the mp3, a social influence such as peer pressure that interacts with young generation needs to be cool or to gain status drives young people to adopt the mp3 as an innovation. Besides, when it comes to the emergence of interactive communication such as the new communication technologies, Rogers (1996) mentioned, “a critical mass occurs when the diffusion process becomes self-sustaining. After the critical mass point, individuals in a system perceive that “everybody else” has adopted the interactive innovation. With each successive adopter of an interactive innovation, the new idea becomes more valuable not only for each future adopter, but also for each previous adopter” (p. 418-419). When it comes to the future of diffusion theory, we expect that the popularity of diffusion research will increase because as in recent years, new communication technologies have increased and proliferated.
Diffusion study and Two-Step Flow studyEdit
According to Lowery and Defleur (1995), since diffusion study emphasizes the role of interpersonal communications, the diffusion study by Ryan and Gross “parallels what was independently found by Lazarsfeld and his associates in the discovery of the two-step flow process in the very different setting of The People’s Choice” (p. 132). "The People’s Choice” showed that audiences are not powerless and passive. The study showed that interpersonal channels, such as opinion leaders, are more important than the mass media. Unlike magic bullet theory, both of these studies emphasized the role of the opinion leaders and interpersonal communication, such as face-to-face interactions influencing decision-making.
Alexander, P. J. (1994). Entry barriers, release behavior, and multiproduct firms in the music recording industry. Review of Industrial Organization, 9, 85-98.
Allen, D. (1983). New telecommunication services: Network externalities and critical mass. Telecommunications Policy, 12, 57-271.
Crane, D. (1972). Invisible colleges. Chicago, IL: University of Chicago Press.
Coleman, J. S., Katz, E., & Mentzel, H. (1966). Medical innovation: Diffusion of a medical drug among doctors. Indianapolis, MN: Bobbs-Merrill.
Daft, R. L., & Lengel, R. H. (1986). A proposed integration among organizational information requirements, media richness, and structural design. Management Science, 32, 554-571.
Deutschmann, P. J., & Fals Borda, O. (1962). Communication and adoption patterns in an Andean villege. San Jose, Costa Rice: Programa Intermericano de Information Popular.
Chapin, F.S. (1928). Cultural change. New York: Century Company.
Lasswell, H. D. (1948). The structure and function of communication in society. In L. Bryson (Ed.), The communication of ideas. New York: Harper & Co, 33-51.
Lowery, S.A., & DeFleur, M.L. (1995). Milestones in Mass Communication research. White Plains, NY: Longman Publishers USA.
Markus, M.L. (1987). Toward a “critical mass” theory of interactive media: Universal access, interdependence and diffusion. Communication Research, 14, 491-511.
Rogers, E.M. (1976). New product adoption and diffusion. Journal of Consumer Research, 2, 290–301.
Rogers, E.M. (1994). A history of communication study: A biographical approach. New York: Free Press.
Rogers, E.M. (1995). Diffusion of Innovations (4th ed.). New York: Free Press.
Rogers, E., & Singhal, A. (1996). Diffusion of innovations. In Salwen and Stacks, op. cit., (pp. 409-420).
Ryan & Gross (1943), “The Diffusion of Hybrid Seed Corn in Two Iowa Communities, ” Rural Sociology 8 (March): 15.
Saga, V. L., & Zmud, R. W. (1994). The nature and determinants of IT acceptance, routinization, and infusion. In L. Levine (Ed.), Diffusion, transfer and implementation of information technology (pp. 67-86). Amsterdam: North-Holland.
Singhal, A. (2005). Forum: the life and work of Everett Rogers- some personal reflections. Journal of Health Communication, 10, 4.
Tarde, G. (1903). The laws of imitiation, (E. C. Parsons, Trans.). New York: Holt.
Wildemuth, B. M. (1992). An empirically grounded model of the adoption of intellectual technologies. Journal of the American Society for Information Sciences, 43, 210-224.
Zaltman, G., Duncan, R., & Holbek, J. (1973). Innovations and organizations. New York: Wiley.