Re-thinking the Role of Information in Diffusion Theory


Re-thinking the Role of Information in Diffusion Theory:
An Historical Analysis with an Empirical Test


        The 1930-1960 period, during which much of communication theory began to
develop, was a time of "rediscovery" of the group - the idea that the group
serves as the interface between the individual and society.  In the case of
diffusion theory, this rediscovery engendered a "dominant paradigm" focusing on
group processes, interpersonal communication, and influence - informed by a
spurt in empirical research and several new conceptual leaps - that shaped and
was itself influenced by researchers whose funding base and interests were
practical and applied.  Diffusion generalizations spawned in the 1950s have
guided not only 4,000 subsequent empirical studies, but have also had a profound
effect on the activities of communication strategists.
One of the key generalizations that emerged is that different channels of
communication play key roles at different points in the adoption process.  Mass
media play their key role in bringing about initial awareness and knowledge of
new ideas and practices, while interpersonal sources are relied upon when
deciding whether or not to adopt.  The idea of these discrete functions for
communication channels has found its way into the mainstream literature on how
to use communication effectively to bring about social change.  In a review,
Chaffee (1979) noted that this discrete function idea constitutes one of the
most enduring generalizations derived from research on human communication.
In hindsight, however, while it is clear how researchers were led to the
conclusions they drew at the time, examination of the origins of the
generalizations suggests that this generalization, and especially its practical
interpretation, does not now, and to some extent never did match the actual
diffusion process.   The major premise of this paper is that the generalizations
concerning the role of information in the diffusion process were shaped and to
some extent distorted by a preoccupation with the rediscovery of the group, and
a research emphasis on finding the most influential communication channels
rather than exploring how the overall patterns of information source use might
affect the process.  This was combined with a methodological approach that was
inadequate to measure the synergistic contributions of multiple information
sources to the diffusion process.  This paper has three main purposes:
1.      Explore the basis of the original generalizations in the context of the time
in which they developed, and demonstrate how conceptual preoccupations and
methodologies led to conclusions that failed to adequately explain the role of
communication;
2.      Offer four propositions that could form the basis for revised generalizations
concerning the role of information in the diffusion process;
3.      Provide a preliminary empirical test of the propositions, using a
longitudinal dataset of the adoption of computers over a 15-year period.

Diffusion Theory

Diffusion theory is one of the most commonly-used theories in the social
sciences, education, health and marketing, and is standard fare in most
communication theory or communication strategy and planning courses.  While
interest in this theoretical area peaked in the late 1950s and 1960s and then
declined, it has had a resurgence of sorts due to the current great interest in
new communication technologies and how they might affect society.
        "Diffusion" is concerned with the spread of ideas from originating sources to
ultimate users.  Research concerns have focused on the speed at which an
innovation spreads and the factors that facilitate or inhibit this spread.
Perhaps the most significant finding is that a significant time lag exists
between the introduction of an innovation into a social system and its
acceptance by most members of that social system.  The time required varies from
system to system and among innovations in the same system, but usually a period
of years or decades is required for fairly complete diffusion.  An S-shaped
diffusion curve has been found for the majority of innovations studied.
        What has been termed the "classic" diffusion model was developed by a small
group of rural sociologists in the early 1950s who became part of a North
Central states subcommittee that synthesized and published the results.  In
1954, the original draft was integrated by George M. Beal and Joe M. Bohlen of
Iowa State University as a flannel board presentation entitled "The Diffusion
Process" (North Central Regional Publication No. 1, 1962).
        The classic diffusion model included five stages of the adoption process -
awareness, interest, evaluation, trial and adoption - and suggested that there
were discrete functions for different information channels at different stages.
Everett Rogers later re-named the stages, and added a "confirmation" stage
following adoption in 1971 (Rogers with Shoemaker, 1971) and a "re-invention"
stage between adoption and confirmation in his 1983 and 1995 books (Rogers,
1983, 1995).
The classic 1954 diffusion model also included the idea that individual
differences cause people to adopt innovations at different time periods and
utilize varying amounts and sources of information.  Five categories of adopters
were conceptualized: innovators (first 2.5%), early adopters (next 13.5%), early
majority (next 34%), late majority (next 34%) and late adopters or laggards
(last 16%).
The 1954 Bohlen and Beal flannel board presentation also noted that there were
different types of innovations, and that their characteristics affect the
adoption process.  It distinguished between changes in materials and equipment,
changes in improved practices, and an "innovation" requiring new use patterns.
Later, these characteristics were re-worked to include Linton's (1936) approach
including "compatibility" of the innovation (see Lionberger, 1952, p. 140).  By
the time North Central Regional Extension Publication No. 13 was issued in
October, 1961, factors included compatibility, divisibility, complexity, and
visibility (North Central Regional Extension Publication No. 13, 1961).  By
1962, "relative advantage" had been added to the list (Subcommittee for the
Study of Diffusion of Farm Practices, 1962).

Origins of Generalizations about the Role of Information in Diffusion


        The generalizations concerning the role of information in the diffusion process
arose from a focus by rural sociologists on a practical problem: how to
encourage farmers to adopt new agricultural technologies such as antibiotics,
fertilizers, herbicides and other improved practices.  Beginning in the early
1940s, Bryce Ryan and Neal Gross (1943, 1950) had conducted what would become
the seminal study of how Iowa farmers adopted hybrid seed corn.   Setting the
stage for what would come later, they took a structural functionalist approach
that borrowed from earlier sociological diffusion research (Chapin, 1928;
Bowers, 1938), but moved analysis from an aggregated to an individual level.
They believed that social factors, and not just the economists' "invisible hand"
played a key role in social change.  As society modernized, they reasoned that
different individuals would be affected at different points in time, and that
this would be reflected in differential adoption rates of new practices.  In
their study, they set forth: (1) the "S" shape of the rate of adoption of an
innovation over time; (2) the characteristics of the various adoption
categories; and (3) the relative importance of different communication channels
at various stages in the innovation decision process.  Ryan designed the study
to examine "social factors in economic decisions" (Rogers, 1995).  Results
showed that farmers tended to name salesmen (who were often other farmers) as
their first source of information about hybrid seed corn, and friends or
neighbors as the channel used when they made their decision to adopt.  Ryan and
Gross concluded that interpersonal channels were very important in the diffusion
process.
Herbert Lionberger (1952, 1960) also took a functionalist approach, building on
Linton's (1936) idea that cultural differences between regions affect adoption.
His research (1951: 28) focused attention on the use of both mass media and
personal sources of information by both low resource and high resource farmers.
By 1951, Lionberger had concluded that  "personal sources" (friends,
agricultural agents)  are more convincing than "impersonal" ones (reading,
radio).  He reached this conclusion because the use of personal sources (experts
and neighbors) correlated more highly with use of an index of technological
practices than did impersonal sources (newspapers, magazines, radio).
Eugene Wilkening took a psychological approach, suggesting that different
individual perceptions of an innovation lead to different uses of information
sources.  His research  (1953) began to link the use of information sources to
stages of the adoption process.  In a study of Wisconsin dairy farmers,
Wilkening explored Ryan and Gross's idea that the sources of information farmers
used for "initial" knowledge might be different than "those they use for
understanding how it can be made more effective after it is adopted" (Wilkening,
1956: 361).  He divided information-seeking into three categories: (1)
awareness: hearing about the change; (2) decision-making: information that helps
decide whether or not to try it out; (3) action: instructions on how to put the
change into effect.   Although Ryan and Gross had found that salesmen were the
first source of information about hybrid seed corn, Wilkening hypothesized that
mass media, including magazines, newspapers and radio programs, would be the
most frequently mentioned first source.  Building on the work of Lionberger and
his own studies in North Carolina, he noted that both low-income and high-income
farmers tended to use mass media sources.  Therefore, he predicted that these
sources would be used to create awareness.  It should be noted that an important
difference between Wilkening's approach and Ryan and Gross was that Wilkening
did not ask about any particular innovation.  Instead, he asked where farmers
got information about "new ideas in farming."  This tends to produce important
differences in responses.  For example, contemporary studies asking general
audiences where they get their "news" tends to lead to a response of television,
while asking about some particular news event yields responses such as
newspapers, magazines, friends, etc.  Wilkening's results were in accord with
his expectations.  Mass media were often named as an initial source (63% of
cases), while "other farmers" were mentioned as the source that helped them
decide (47% of cases, compared to only 4% for mass media).
A. Lee Coleman and C. Paul Marsh (1955) were concerned with communication
aspects of the diffusion process.  They were interested in understanding
differences between communities (high adoption, low adoption), groups, and
individuals so they could tailor communication messages for maximum
effectiveness.
        In 1951, a subcommittee representing rural sociologists from North Central
states working on farm diffusion was created with Eugene Wilkening from the
University of Wisconsin as co-chair along with Neal Gross from Iowa State
University.  Other members were Lee Coleman, Kentucky; Charles Hoffer, Michigan
State; and Harold Pedersen, South Dakota.  Herbert Lionberger was added by 1952
(Lionberger, 1952: 141).  By 1954, the subcommittee added Joe Bohlen, Iowa
State, as chair, replacing Gross, Paul Miller, Michigan State replacing Hoffer,
and Robert Dimit, South Dakota State.  Harold Pedersen also left the committee
(Subcommittee for the Study of Diffusion of Farm Practices, 1955).  Bohlen and
an Iowa State colleague, George Beal, played a key role in the development of
the generalizations linking information seeking to stages of the adoption
process.
        Bohlen and Beal accepted the structural functionalist approach of Ryan and
Gross.  One of their major contributions was to add a conceptual basis for the
stages of the adoption process.  The work of Mead (1950) and Dewey (1910) was
used to suggest that there are general stages of inquiry people go through when
solving problems.  Bohlen and Beal adapted these stages specifically for
innovations.  They also were concerned with peer influence, small group
dynamics, and social psychology.  Their research on community action and
community leadership also influenced them to focus on how interpersonal
influence brings about change.
It is important to note that although they were presented as "generalizations,"
and built on the previous work by Lionberger, Wilkening and Ryan and Gross,
Bohlen and Beal's stage-based generalizations had not yet been subjected to
empirical test across the five stages of the adoption process developed by the
subcommittee.  Bohlen and Beal first presented the generalizations as part of a
flannel board presentation to Iowa State University Extension in 1954. In 1955,
they presented them to the National Project on Agricultural Communications at
Michigan State University.  In 1958, a major presentation to leading corporate
marketing executives took place.   Over the next few years, they would repeat
their presentation to more than 800 audiences of groups often numbering 400 or
more (Chang, 1998:23; Rogers, 1975: 11).
        The generalizations were first published in 1955 as North Central Regional
Publication No. 1 (Subcommittee for the Study of Diffusion of Farm Practices,
1955).  The report credited members of the subcommittee as accepting full
responsibility for the report.  In its first four years, more than 80,000 copies
of the report were sold (North Central Regional Extension Publication No. 13,
1961), a phenomenal success for a research publication.  A shortened version
produced by Iowa State University Extension distributed even more copies.  The
Subcommittee also published a bibliography of 110 relevant research publications
(North Central Rural Sociology Committee, 1959).  Rogers (1975) noted that the
members of this subcommittee constituted an "invisible college" that played an
important role in shaping both the theoretical paradigm and methodological
approaches used in diffusion studies.
For several reasons, relatively few of the thousands of diffusion studies dealt
with generalizations about information-seeking.  Most diffusion studies did not
focus on information seeking at all.  Instead, they were concerned with patterns
of adoption, socio-economic characteristics (age, education, social status, farm
size) and innovation-specific factors. Rogers with Shoemaker (1971) provide an
appendix classifying diffusion studies by the generalizations they tested.
Generalizations concerning the role of information in the diffusion process
developed by the rural sociologists were of two basic types.  First were
generalizations having to do with the overall use of information sources. In
1961, Bohlen and the other members of the subcommittee argued that "the typical
innovator not only receives more different types of information about new
practices, but also is likely to receive information sooner and from more
technically accurate sources" (North Central Regional Extension Publication No.
13, 1961: 8).  Rogers (1962) formalized the generalization: "Earlier adopters
utilize a greater number of different information sources than do later
adopters" (p. 313).  This generalization had been supported by a number of
earlier studies.
The second type of generalizations were new, and grew out of the flannel board
presentation of Bohlen and Beal.  They take a discrete function approach to
information source use.  Two key generalizations - one dealing with the role of
mass media at different stages of the adoption process, and the other with
interpersonal communication with friends and neighbors - emerged from the first
published work of the Subcommittee.  The generalizations suggested that
information channels have discrete functions. According to the Subcommittee for
the study of Diffusion of Farm Practices (1955):
 "It is at the awareness stage that the mass media devices have their greatest
impact. The evidence is that for the majority, mass media become less important
as sources of information after the individual has become aware of the ideas (p.
4)."  Later, it observes: (p. 5):  "the data available indicate that as people
are evaluating an idea for their own use, they usually consult with neighbors
and friends whose opinions they respect _. The reasons for the apparent lack of
importance of mass media and salesmen at this and later stages of the adoption
process are: (a) the information they provided through these channels is too
general; (b) the potential adopters mistrust some mass media information because
they feel that the information is tempered by the business interests of those
who are in control of them."


The Elaboration and Testing of the Generalizations
        The importance and relative newness of the discrete function generalizations
can be seen by examining the overall pattern of diffusion studies up until that
time.  Table 1 divides key diffusion studies along two dimensions.  On the
left-hand side are studies that examine the first type of generalization --
general information-seeking both for general topics (Quadrant 1) and for
specific innovations (Quadrant 2). Such studies considered both mass media and
interpersonal channels to be important, but did not consider the possibility
that the use of channels might change as an individual moved from one adoption
stage to another.  Studies on the right-hand side of the figure focus on the
discrete function, explicitly considering information seeking by stage of the
adoption process.  Those in Quadrant 3 are for innovations in general, while
those in Quadrant 4 are for specific innovations.  The studies are arranged in
each quadrant by date.  Note that when the two generalizations were put forward
in 1954, only Ryan and Gross's original 1943 corn hybrid seed study was found in
Quadrant 4, and the only other study examining information-seeking by stages was
Wilkening's 1953 study in Quadrant 3.
 Table 1: Subcommittee Rural Diffusion Studies
Sorted by General versus Specific Innovations
And Information-Seeking in General or by Stages
Quadrant 1
Diffusion studies of general information-seeking for general innovations
USDA Vermont Study (1947)
Lionberger (1951)
Coleman and Marsh (1955)
Lionberger (1955; 1957); Lionberger and
        Coughenour, 1957)
Dickerson (1955)
Fliegel (1956)
van den Ban (1957)
Lionberger and Campbell (1971)
Yancey (1982)

Quadrant 3
Diffusion studies examining information-seeking by adoption stages
For general innovations
Wilkening (1953; 1956), 636 Wisconsin farmers
Lionberger and Chang (1981) 396 Taiwan
        Farmers
Quadrant 2
Diffusion studies examining general
Information seeking
for specific innovations
Wilson and Trotter (1933)
Bowers (1938)
Wilkening (1950; 1952)
Abell (1951)
Marsh and Coleman (1954)
Dimit (1954)
Lionberger (1955)
Campbell (1959)
Rogers and Burdge (1962)
Lee (1967)

Quadrant 4
Diffusion studies examining information-seeking by adoption stages
For specific innovations
Ryan and Gross (1943, 1950)
Beal and Rogers (1957); Rogers and Beal (1958)
Coleman, Katz, and Menzel (1957; 1959; 1966)
Copp, Sill and Brown (1958); Sill (1958)
Beal and Rogers (1960)
Rogers and Pitzer (1960)
Rogers and Burdge (1961)
Rahim (1961)
Deutschmann and Fals-Borda (1962)
Mason (1962, 1963)
Rogers and Leuthold (1962)
Lionberger (1963)
Rogers (1964); Rogers and Meynen (1965)
Mason (1964)
Singh and Jha (1965); Jha and Singh (1966)
Jain (1965)
Sawhney (1967)
Rogers with Svenning (1969)

        In the first two studies designed to test the generalizations, Rogers and Beal
(1958) argued logically that they should be supported:
"Most new farming practices are developed through research. The impersonal mass
media devices of newspapers, farm papers and magazines, radio, television, and
commercial publications all attempt to rapidly communicate these research
findings to the farmers.  Thus it would seem reasonable that the majority of
farmers, especially the early adopters, would become aware of new farming
practices through the impersonal mass media sources.
However, an understanding of the social relations of most farmers and the mental
processes involved at the information and application stages would suggest that
personal sources may play the more important role at the information and
application stages." (Rogers and Beal, 1958: 330)
Researchers at Columbia University
The 1954-1957 time period was one of significant conceptual creativity, research
and dissemination for the rural sociologists.  However, that same time period
was also of great importance for another group of researchers who shared the
rural sociologists' concerns about the practical effects of mass media and
interpersonal communication channels.  Because this other group was using the
same general paradigm emphasizing the importance of influence and groups in the
communication process, it is important to examine the origins of their work, as
well as how the two groups eventually merged.  Paul Lazarsfeld, Bernard
Berelson, and Hazel Gaudet published The People's Choice in 1948, a book
concerning the role of mass media and interpersonal channels in the 1940
presidential election.  The book was widely heralded as indicating the
importance of interpersonal communication channels and "opinion leaders" in
influencing voters.  By 1955, when Bohlen's subcommittee was first publishing
its generalizations, Elihu Katz and Paul Lazarsfeld were publishing Personal
Influence, which contained an extensive review of research on the use of mass
communication and interpersonal channels to influence audiences.   The book
emphasized the "re-discovery" of the importance of social groups in
communication and persuasion, and represented a declaration of victory over mass
communication theorists who had viewed audiences as "atomistic" individuals who
could be directly persuaded by mass media.  The book launched the "two-step
flow" theory of communication which postulated that mass media influence
traveled through opinion leaders who interpreted their content to audiences that
used the information to decide how to vote.  In a conclusion very similar to
that of the rural sociologists, they found that interpersonal sources are the
key to persuading individuals to change.  That is, information channels have
discrete functions in changing human behavior.  Katz and Lazarsfeld based their
work on a number of small group research studies including the industrial
(Hawthorne studies from 1924 through the 1930s emphasizing social relations as a
key factor in industrial output - (Roethlisberger and Dickson, 1941)), military
(The American Soldier studies showing the willingness of U.S. troops to fight in
World War II was dependent upon informal group processes - (Stouffer, 1949;
Shil, 1950)), and urban (The Yankee City studies showing the key role social
cliques play in placing groups socially - (Warner and Lunt, 1941)) studies that
re-emphasized the importance of groups in the persuasion and communication
process.
        Katz and Lazarsfeld (1955:3) concluded:
        "The 'rediscovery' of the primary group is an accepted term now, referring to
the belated recognition that researchers in many fields have given to the
importance of informal, interpersonal relations within situations formerly
conceptualized as strictly formal and atomistic.  It is 'rediscovery' in the
sense that the primary group was dealt with so explicitly (though descriptively
and apart from any institutional context) in the work of pioneering American
sociologists and social psychologists and then was systematically overlooked by
empirical social research until its several dramatic 'rediscoveries'" (Katz and
Lazarsfeld, 1955: 3).

Remarkably, in 1955, despite the fact that their research concerned very similar
theory and research interests, neither of these two groups had noted or cited
each other. (An article by Coleman and Marsh, 1955, had cited Lazarsfeld and
Berelson, but only as an example of communication research.  The similarities to
the work of rural sociologists were not noted).   Thus, the initial
generalizations made by both groups were developed independently.  Although the
two groups discovered each other a year later, the generalizations that had
developed in each area were not changed immediately in any substantial way.
Rather, the discovery of each other led mainly to the citing of each other's
work as an indicator of the importance of their overall topical area.
        Common themes in both areas included:
1.      A focus on influence - how media and interpersonal sources lead to changes in
adoption and voting behavior;
2.      A concern with both mass media and interpersonal channels, with a primary
role for influence placed with interpersonal channels and social groups;
3.      A focus in the original research on practical recommendations that could be
derived from the research, rather than on building rigorous theory;
4.      An approach examining communication behavior and decision-making over
extended time periods.
The emphasis of the Columbia group on practical outcomes and interpersonal
communication is evident in the introduction Katz and Lazarsfeld wrote in their
1955 book:
"Our purpose, of course, is to try to point the way for the planning of research
on the transmission of mass persuasion via the mass media - and particularly,
for the incorporation of a concern with interpersonal relations into the design
of such research.  By attempting to specify exactly which elements of
person-to-person interaction might be relevant for mass media effectiveness, and
by exploring what social science knows about the workings of these elements, we
shall contribute, perhaps, to a more complex - yet more realistic - formulation
of a "model" for the study of mass persuasion campaigns" (p. 44).
Everett Rogers, who in 1954 became a graduate student of George Beal at Iowa
State, wrote in 1975 (Rogers, 1975) that he "stumbled across" an educational
diffusion study by Paul Mort, Columbia University, while leafing through a
journal in the waiting room of a professor's office.  He also found a medical
diffusion study conducted by Coleman, Katz and Menzel. In 1956, he got a small
grant to attend a conference in New York that was also attended by Columbia
researchers James Coleman, Elihu Katz and Herbert Menzel.  As a result of the
meeting, Rogers said he "became convinced that a general diffusion process
occurred for many types of innovations" (p. 12).
While Rogers' attendance at the New York conference solidified his own thinking,
researchers from both groups had already begun to notice one another. Menzel and
Katz (1955-56) cited Wilkening, Lionberger and Marsh and Coleman - all key farm
diffusion studies - as being relevant.  In 1956 Wilkening (1956) also cited a
number of Columbia studies in the same way.
The mutual discovery led to new material in the literature of both areas, and a
1960 article by Katz weaving together the strands of research from rural
sociology, small group research, education, medical sociology, industry and
other areas.  Although the Beal and Rogers diffusion article in 1957 (Beal and
Rogers, 1957) makes no mention of Katz or the Columbia researchers, by 1958
(Rogers and Beal, 1958) they were mentioned.  A 1958 synthesis of work presented
to corporate marketers discusses contributions of both the rural sociologists
and the Columbia researchers (Foundation for Research on Human Behavior, 1959).
By 1959, the rural sociologists began including Katz and Lazarsfeld's work in
their bibliographies.  Table 2 shows the cross-citations of the two schools of
research.   Although we have examined much of the published diffusion
literature, the gap between actual conceptual or field work and publication
makes it difficult in some cases to know exactly when some of the integration
occurred.
In 1960, in separate works, both Lionberger and Katz sought to link the
generalizations that had been developed by the two groups of researchers.  Katz,
specifically with respect to the generalizations about the role of information
in the process of making either political or agricultural decisions, noted that
a "convergence has already revealed a list of parallel findings which strengthen
theory in both [areas]. . . In both urban and rural settings personal influence
appears to be more effective in gaining acceptance for change than are the mass
media or other types of influence" (Katz, 1960, p. 439).  The work of Lionberger
and Wilkening is cited alongside Katz and Lazarsfeld.  From that time on,
studies from both areas of research have routinely cited one another.  Many of
the Columbia studies are now listed in diffusion bibliographies (see Rogers and
Shoemaker, 1971; Rogers, 1983; 1995).

Table 1: Chronological Comparisons of Cross-Citations Between
Rural Sociologist Subcommittee and Columbia University Researchers
Key Research: Subcommittee on Farmer Adoption:
Citations of Columbia researchers
Key Research: Bureau of Applied Research, Columbia University:
Citations of Subcommittee Research
1943: Ryan and Gross seminal study of the diffusion of hybrid seed corn
1948: Lazarsfeld, Berelson and Gaudet: The People's Choice;  no mention of rural
farm research
1962: Gross expansion of the 1943 study to 10 innovations makes no mention of
Columbia researchers.
1952: Lionberger review of literature; no mention of Columbia research;
1952: Wilkening North Carolina Bulletin 98 study; no mention of Columbia
empirical studies

1954: Bohlen and Beal give their first flannel board presentation including the
new discrete generalizations

1955 (November): Subcommittee publishes generalizations and initial
bibliography; no mention of Columbia work
1955: Coleman and Marsh cite Lazarsfeld and Berelson, but only as examples of
recent communication research.  They made no parallels with the work of rural
sociologists.
1955: Katz and Lazarsfeld publish Personal Influence; no mention of rural farm
research or Subcommittee
1956: Wilkening Social Forces journal article cites 1948 People's Choice book;

1956: Everett Rogers attends conference in New York and meets Columbia group.
1955-56: Menzel and Katz drug diffusion article explicitly cites Wilkening,
Lionberger and Marsh and Coleman studies, and concludes that "these studies are
excellent representatives of a research tradition of the greatest importance for
students of communication."
1957: Beal and Rogers (1957) article testing generalizations; no mention of
Columbia group
1957: Katz explicitly cites Ryan and Gross, and Marsh and Coleman in this 2-step
flow article
1957: Coleman, Katz and Menzel (1957) medical diffusion study:  no mention of
rural sociology studies, but this study focuses on group influences on doctors
1958: Rogers and Beal (1958) article testing generalizations cites both the
Columbia 1948 and 1955 books in support of importance of social groups
1958: Foundation for Research on Human Behavior includes a synthesis of research
from both the rural sociologists and Columbia researchers.

1959: 2nd Edition of Subcommittee Bibliography cites 1955 Personal Influence
book and Kurt Lewin

1960: Lionberger book on diffusion has citations of 1948, 1955, and Coleman,
Katz and Menzel medical study; plus other studies that form the base for the
Columbia research; he integrates Columbia studies in discussions of influence
and social status.
1960: Beal and Rogers Ag Experiment Station Report No. 26 mentions 1948 book
1960: Katz publishes review of literature explicitly including farm diffusion
studies as part of "rediscovery" of importance of social groups, and attempts to
integrate generalizations from the two areas.
1962: Rogers first book explicitly integrates Columbia University work into
diffusion studies
1961: Katz compares Ryan and Gross hybrid seed corn study with the Coleman, Katz
and Menzel medical study and uses both to develop joint generalizations

                In his 1979 review, Chaffee (1979: 1) recognized how powerful and long-lasting
the generalizations had become in the field of human communication.
"One of the most durable policy generalizations derived from research on human
communication is that interpersonal influence is more efficacious than mass
communication in bringing about social change.  Campaigns, corporations, and
even countries are advised that mass media, while perhaps necessary to achieve
economies of scale, are inferior to real, personal contact as a means of
persuading people to change their behavior. Of course, no one sophisticated in
the research literature would make such a sweeping statement unhedged by
limitations, exceptions and caveats. But in transliteration from academic
reviews to the more streamlined advice that circulates in communication planning
circles, the image of powerful interpersonal processes comes through with
unmistakable clarity."

What becomes clear is that the newly-designed generalizations were guided by the
paradigm of the importance of personal communication with a focus on influence.
Chaffee, in his 1979 critique of the generalizations, argued that both diffusion
and the two-step flow researchers were led to conclusions that supported their
interpersonal paradigm.  Chaffee found that although the 1940 Lazarsfeld,
Berelson and Gaudet (1948) study was considered a classic reinforcing the
importance of interpersonal communication, in fact:
 "the original data_ reveal that the media - even in that pre-television era -
were judged more powerful by most voters.  A slight majority cited either radio
(38%) or newspapers (23%) as the most important single source in making their
voting decisions_ About one-half of those who changed their voting intentions
during the campaign cited something learned from either the newspaper or radio
as the main source of change.  On the other hand, less than half mentioned any
personal contact as an influential source, and less than one-fourth considered
an interpersonal source as the most important one" (Chaffee, 1979, p. 8;
Chaffee, 1982, p. 66).  Chaffee's conclusion:  "Apparently the emphasis on
interpersonal influence emanating from the Erie County study was due more to the
contrast between these figures and the researchers' expectations for far more
dramatic evidence of media impact" (p. 9).
(While Chaffee's conclusion here about expectations is probably correct, it
should be noted that media use was assessed for every respondent, while
interpersonal source use was volunteered by respondents.  This would tend to
understate interpersonal mentions).
Similarly, for both diffusion and two-step flow theorists, Chaffee criticized an
approach that sought to find the "most influential" communication channel.
"Just as frequency of use is not a valid criterion for inferring higher
credibility or preference for a channel, neither is recalled influence a valid
criterion for concluding that one channel is capable of achieving stronger
effects than another.  _ wise utilizers of information rarely rely on mass media
alone; they do well to check with experts, compare notes with peers, and
otherwise attempt to validate media content for themselves before acting upon
it" (Chaffee, 1979, p.9).

Studies Supporting the Discrete Function Generalizations about the Role of
Information Across Stages.

The discrete function generalizations developed by Bohlen and Beal were
conceptually new, and at the time they found their way onto the flannel board
and into the first Subcommittee report, they had not been empirically tested.
The first two studies designed to test them were conducted by Beal, Bohlen and
Rogers in 1956 using 148 farm husbands and wives in central Iowa (Rogers and
Beal, 1958; Beal and Rogers, 1960; Beal and Rogers, 1957).  Both studies found
that mass media were the source of awareness for new fabrics, 2-4D herbicide
spray, and animal antibiotics, while friends and neighbors were most frequently
mentioned as the source of information at the "acceptance" or "persuasion" stage
of the process.  It was also noted that mass media and "cosmopolite" (expert,
non-local) sources played a more important role for innovators and early
adopters than for those who adopted later.
        By 1960, Lionberger (1960) counted two additional supportive studies (Copp,
Sill and Brown, 1958; and Lionberger, 1958).  In 1971, when the most exhaustive
list of studies to date was assembled by Rogers with Shoemaker (1971), a total
of 21 studies were cited in support of these generalizations.  However, when
duplication is removed (several studies report results of the same piece of
research), only 14 empirical studies remain.  Two additional studies were found
by Rogers with Shoemaker not to support the generalizations.
        In support of one of the most extreme implications of the discrete function
role of information sources, Rogers (1995) cites a key study by Sill (1958;
Copp, Sill and Brown, 1958) of dairy farmers in western Pennsylvania.  In that
study, the conclusion was that "if the probability of adoption were to be
maximized, communication channels must be used in an ideal time sequence,
progressing from mass media to interpersonal channels (Sill, 1958).  Copp, Sill
and Brown (1958: 70) found "a temporal sequence is involved in agricultural
communication in that messages are sent out through mass media directed to
awareness, then to groups, and finally to individuals.  A farmer upsetting this
sequence in any way prejudices progress at some point in the adoption process."
They concluded: "The greatest thrust out from the knowledge stage was provided
by the use of the mass media, while interpersonal channels were salient in
moving individuals out of the persuasion stage.  Using a communication channel
that was inappropriate to a given stage in the innovation-decision process (such
as an interpersonal channel at the knowledge stage) was associated with later
adoption of the new idea by an individual because such a channel use delayed
progress through the process."  (It should be noted here that Copp, Sill and
Brown (1958) classified "printed extension" information as a mass medium, while
Sill (1958) in his Ph.D. thesis using the same dataset classified "printed
extension" as a "Technician," not a mass medium.  The difference is important
since this was a frequently-mentioned source.  Since the use of sources such as
either printed extension materials or oral extension agents was highly
associated with later adoption, this is an important difference.)  This example
also demonstrates the interest of researchers in converting their findings into
specific recommendations for practitioners.
        Rogers with Shoemaker  conducted a comparative analysis of the role played by
mass media and cosmopolite-interpersonal channels by stages in the
innovation-decision process for 23 different innovations (mostly agricultural)
in the United States, Canada, India, Bangladesh, and Colombia. They concluded:
 "Mass media channels are of relatively greater importance at the knowledge
stage in both developing and developed countries, although there was a higher
level of mass media channel usage in the developed nations, as we would expect.
Mass media channels were used by 52 percent of the respondents in developed
nations at the persuasion stage, and 18 percent at the decision stage.  The
comparable figures for respondents in Third World nations were 29 percent and 6
percent.  This meta-research showed that cosmopolite-interpersonal channels were
especially important at the knowledge stage in developing nations" (Rogers,
1995: 196).

Studies Supporting Alternatives to the Discrete Function Approach

        There was evidence in the empirical studies suggesting that there might be
alternatives to the discrete function generalizations involving multiple media
use, and some studies - including the seminal Ryan and Gross study - did not
support the discrete function generalizations.   It should be emphasized that
the generalizations put forward by the Subcommittee did come with some caveats
concerning their application:
"Some studies, such as that of hybrid seed corn, indicate that salesmen are
important in creating awareness of new ideas which involve the use of commercial
products.  Neighbors and friends are important creators of awareness of new
ideas among the lower socio-economic groups" (Subcommittee for the Study of
Diffusion of Farm Practices, 1955: 4).
One source of ideas for an alternative approach to discrete functions came from
studies concerning the first type of generalizations - those predicting higher
use of information sources of all types by earlier adopters.  Those studies
found a significant relationship between high information seeking from many
different sources and adoption of specific innovations (Abell, 1951; Bowers,
1938; Dimit, 1954; Lionberger, 1955; Marsh and Coleman, 1954; USDA Vermont
Study, 1947; Wilkening, 1950; Wilson and Trotter, 1933).  Other studies found
high levels of general information seeking about general agricultural topics
rather than specific innovations also were associated with high levels of
adoption (Coleman and Marsh, 1955; Dickerson, 1955; Lionberger, 1951).  The high
reported use of all information sources suggested that multiple sources might be
operating at later stages of the process.
        Wilson and Trotter (1933), in reporting on farmers' adoption of improved
legumes and other practices in three Missouri counties, found that the more
exposure one reports to messages about legume practices from any source, the
greater the chances for adoption (Table 17, p. 32).  Lionberger (1951) found in
a study of low-income Missouri farmers that " _ compliance with each of the
approved practices is positively associated with the number of personal,
reading, and radio sources of information recognized by the households. This
indicates the desirability of a multiple approach to the problem of reaching
low-income farmers with educational materials."  Coleman and Marsh (1955) found
high adopters from a list of 21 innovations ranked higher in their use of every
single information source (pp. 98-99).  Coughenour (1960) also found a positive
correlation between the use of both institutionalized sources and print media
and adoption of an innovation.
        The discrete function generalizations suggested single information channels
were effective at different stages.  This led to methodological approaches that
precluded looking for multiple channels.  The desire to identify the single most
influential channel led to a methodology that permitted only one response per
stage.  For example, the typical question at the evaluation stage asked, "After
you had enough information to know quite a lot about [innovation], where or from
whom did you get the information that helped you decide whether or not to
actually try it out on your own farm?" (Rogers, 1957).  The approach assumed
that there was a single source of most influence since most often only one
response was permitted.  The same method was used across all stages, resulting
in a matrix with one information source named per stage.  When the 1957 and 1958
studies found that the one source named at the awareness and information stages
tended to be mass media, and friends and neighbors were named at the evaluation
stage, the generalizations were seen as being supported.  The possibility of
multiple channel use or interactions among media at a single stage could not be
considered.  This methodology was used in spite of the fact that some of the
researchers were well aware that more than one source of information was being
used at a stage.  Wilkening (1956:34) observed that:
 "The low percentages giving the mass media for help in decision making and in
the action stages of adopting changes does not mean that farmers do not obtain
some help from them.  The question elicits responses with respect to the most
usual source for the different types of information and not with respect to the
use of a source of information."
        Changing the methodological approach in studies in which information-seeking
behavior was examined across stages also changed the conclusions.  Copp, Sill
and Brown (1958) used a methodology that permitted farmers to mention more than
one source per stage. They found that farmers did name multiple sources (an
average of 1.6-2.0 for the awareness stage).    However,  it is difficult to
make precise comparisons since their case study approach did not specifically
ask farmers to name an information source or sources for each stage.  In
addition, for one of their three innovations, only 13% had moved beyond the
information stage of adoption, limiting possible generalizations about the
sequential use of various sources.    The researchers found that farmers
sometimes passed through a stage without indicating fresh sources of
information.  "In other words, earlier sources often possessed sufficient
momentum to carry the farm operator through a number of later stages" (Copp,
Sill and Brown, 1958: 149).
Coleman, Katz and Menzel (1966:56) used a methodology that focused on the order
of use of media and the purposes for which they were used.  While no attempt was
made to place the use of media across the five stages of the process, they
concluded: "the main point is that the decision to adopt gammanym (tetracycline)
was based on a variety of sources of information."
In one of the studies most strongly questioning the discrete function
generalizations, Mason (1962) assessed information source use independently of
the usual battery of adoption stage questions.  He used a series of scalable
items to determine a person's adoption stage and then attempted to match
patterns of information source use to persons at each stage. This approach
permitted multiple information source responses for each stage.  One finding was
that mass media use increased across stages. Lionberger found that mass media
(radio) was an important source of influence at both the early and late stages
in the adoption process, and that television was capable of activating viewers
to adopt.  However, despite the fact that this finding was reported along with a
summary of the classic diffusion articles, there was no change in the
generalizations as a result (Foundation for Research on Human Behavior, 1958).
Tichenor, Donohue and Olien (1980: 159) in a study of public knowledge of local
conflict-filled issues in two Minnesota regions found that newspapers were the
primary initial source of information named.  At a later time period, they found
that the use of interpersonal sources had increased, but the use of newspapers
had not declined. Both were about equal.
        These studies indicate that, given the opportunity, respondents do tend to name
a number of sources at each stage, and at least in some the number tends to
increase as one moves through the process.  In addition, a number of the studies
downplay the relative importance of finding a single important source.  Instead,
they emphasize the contribution of many sources.  Katz (1961:78), in a synthesis
of both agricultural and medical diffusion studies, concluded that "in fact, it
may be that the search for the 'most influential' medium is a fruitless one.  It
would seem that the focus should be the different uses of the media in varying
social and psychological circumstances."  In a more recent critique of the
Subcommittee's view, Chaffee (1979; p. 21) argued that "to think in terms of
competition between media and interpersonal channels is to misdirect one's
attention from the most important factors governing the flow of information."

Recall of Information Seeking Activity

        A final problem of the seminal studies for information seeking is that they are
based on recall of information over a long period of time.  The typical study
looking at information source use at different stages of the adoption process
began after many farmers had adopted, and asked respondents to reconstruct their
information-seeking behavior over time periods as long as 30 years (Deutschmann
and Fals-Borda, 1962) or even 50 years in the case of one of several innovations
studied by Lee (1967).  Ryan and Gross (1943, 1950), in one of the earliest and
most influential studies, found that most farmers learned about hybrid seed corn
in the period 1929-1931, yet did not adopt until 1936-1939.  The survey was
conducted in 1941, an average of 7 years after first knowledge and several years
more after adoption for most farmers. Could farmers accurately recall where they
first heard about hybrid seed corn after all those years?  Ryan and Gross looked
only at the first source of information, and most influential source.  They
report a residual category of "all others" which includes "unknown" of 9.1% for
original knowledge and 7.0% for most influential.  When five stages of the
process are examined, would this likely increase the difficulty of recall?
        Beal, Rogers and Bohlen (1957: 167), in justifying the validity of their
five-stage model of the adoption process, reported that "farmers seemed to have
little trouble recalling when they became aware of, tried, and adopted the
practice and their sources of information at each stage." They noted that their
data for the diffusion of 2,4-D and hog antibiotics contained "very few 'don't
know' answers."
        Other studies, however, do report some recall problems.  Wilkening (1956) asked
young Wisconsin farmers about their first source of information about new ideas
in farming, their source of information that "helps you decide," and their
source of information on "how much" or "when" to use the innovation.  He found:
"In obtaining responses to the questions used here there was some difficulty in
getting respondents to distinguish between the three different types of
information. This was particularly true for the second and third questions" (p.
363).  One difference between this study and Beal et al. was that Wilkening was
asking about a general topic - new ideas in farming - while Beal et al. were
asking about specific innovations.
        A second study (Lee, 1967) studied specific innovations, but also found that
both low and middle-income Missouri farmers said they had trouble remembering
sources of original information for some of the innovations.  For some
innovations, in fact, "I can't remember" was the most frequent answer given.
Dramatic differences were found between low-income respondents who were the
target of intensive Extension outreach efforts, and middle or low-income farm
groups that were not intervention targets.  Results ranged from a high of 44%
saying "I can't remember" or "I don't know" for non-intervention middle-class
dairy farmers to approximately 25% for middle class hog producers, low income
non-intervention dairy farmers, and low-income non-intervention hog producers.
For respondents in the intervention group, the "I can't remember" response was
only 4%.
        Rogers (1995: 122) offers this critique of the recall approach:
"One weakness of diffusion research is a dependence on recall data from
respondents as to their date of adoption of a new idea.  .. This hindsight
ability is not completely accurate for the typical respondent (Menzel 1957;
Coughenour, 1965).  It probably varies on the basis of the innovation's salience
to the individual, the length of time over which recall is requested, and on the
basis of individual differences in education, memory, and the like.
"Diffusion research designs consist mainly of correlational analyses of
cross-sectional data gathered in one-shot surveys of respondents (usually the
adopters and/or potential adopters of an innovation)...  If data about a
diffusion process are gathered at one point in time, the investigator can only
measure time through respondents' recall, and that is a rather weak reed on
which to base the measurement of such an important variable.
"More appropriate research designs for gathering data about the time dimension
are: (1) field experiments, (2) longitudinal panel studies, (3) use of archival
records, and (4) case studies of the innovation process with data from multiple
respondents (each of whom provides a validity check on the others' data)_.
Unfortunately, alternatives to the one-shot survey have not been widely used in
past diffusion research."
        An improved study design to reduce the threat to validity of the recall problem
would call for a longitudinal study, with farmers measured at multiple points as
they pass through the adoption process.  In this way, farmers would be recalling
source use over a much shorter time period, and patterns in their responses
would be evident over time.

Revised Propositions Concerning the Role of Information in the Diffusion Process

        Our first proposition concerns the overall pattern of use of information
sources as one moves through the adoption process:
Proposition  No. 1:

As one moves through the adoption process, information-seeking from all
available channels increases.

        Our basis for this proposition rests on three factors:
1.      Studies of the first type of generalizations consistently found that the
naming of many information sources is common, and that those who use multiple
sources tend to move through the adoption process more rapidly.
2.      Most studies permitting respondents to name more than one source per stage
find that they do.
3.      Mason's (1962, 1963, 1964) research found that naming mass media as a source
increased across stages rather than decreasing, and the reported use of all
sources increased across stages.
        This proposition would require a methodological approach which permits
respondents to name multiple sources of information at each stage of the
adoption process.

Access to Information with Relevant Content

        Because both the amount of information available about an innovation and the
mix of sources carrying that information change over time, it is important to
consider these changes when studying patterns of information source use. Also
important is individual access to relevant sources.  To some extent, attention
to these factors can help shed light on differences in information-seeking
behavior by innovators and laggards.  Two elements are involved here:
1.      Access to Information Sources;
2.      The Cycle of Media Content Relevant to the Innovation;

Access to Sources.  Farm access to general media such as general farm magazines,
radio, television, and newspapers has been found to be nearly universal by
studies in the Midwest (Lionberger, 1951; Wilkening, 1953, 1956) and the
Northeast (USDA Vermont Study, 1947).  In the South, far wider variations in
access to these media have been found (Coleman and Marsh, 1955; Yancey, 1982).
In other countries, access is often a much more important variable. Rogers and
Svenning (1969), for example, found that in rural Colombia few farmers had
access to printed or broadcast messages relevant to innovations at any stage of
the adoption process.
In the United States, access to specialized farm publications and services
distinguish large and small farmers.  The advent of controlled circulation farm
publications that are sent only to farmers with certain crops and a minimum
gross farm income has explicitly excluded smaller farmers.  In these cases,
small operators cannot receive these publications even if they are willing to
pay for them.  More significant are a variety of paid consulting and publication
services that tend to be used only by large operators.
The Cycle of Media Coverage.  Mass media tend to respond to news about
innovations in much the same way as they respond to other forms of news.  Often
there is scattered and uneven coverage at first, followed by a time of peak
coverage and intensive media interest. The innovation may become the "cover
story" of magazines. After a time, coverage tends to decline (Abbott, 1979).  In
a study of what they termed "the hoopla effect," Abbott and Eichmeier (1998)
found support for the idea that there is a regular pattern of media coverage of
technological innovations.  Abbott and Yarbrough (1989) found that the period of
maximum coverage about farm computers came earlier than the time when
significant adoption was occurring.  Tichenor, Donohue, and Olien (1980) found
that during the times of peak coverage, widespread awareness of news content
could be found at all educational levels of a community, and the gap between
those who know the most and those who know the least decreased.  However, both
before and after this peak in coverage, knowledge gaps would be expected to
increase between the two groups.
        This pattern of coverage would be expected to be reflected in increased
mentions of mass media at the peak times of coverage, and a decline in mentions
at other times.  Thus, it would be important to compare the time period or
periods when respondents were questioned with media content at those same
periods.
        Another important aspect of media or information cycles relates to what Rogers
(1995) terms the "pro-innovation" bias of many of the diffusion studies.
Technologies selected for diffusion studies are not random; in many cases they
are technologies that are the focus of interest and effort by industry,
government agencies, or some other interest groups.  Coleman, Katz and Menzel
(1966) who studied the introduction of tetracycline by a drug company, found
that drug salesmen were the most common first source of knowledge.  They
concluded:  "_the relative importance of different sources or channels of
communication about an innovation depends in part on what is available to the
audience of potential adopters.  For example, if a new idea is initially
promoted only by the commercial firm that sells it, it is unlikely that other
sources or channels will be very important, at least at the knowledge stage of
the innovation-decision process" (Rogers (1995), p. 192).
  This leads to our Proposition No. 2:

Information-seeking behavior is conditioned by the development and behavior of
message production and delivery systems.


Willingness to Use Sources

Beyond access, several other important factors shape the extent to which members
of an audience utilize information sources. Differential use of information
sources has often been explained in terms of personality variables, with
innovators much more eager to seek information and laggards clearly oriented to
the past (Rogers, 1983).  Scherer (1989) found that interest in using
information sources of all types was closely related to socio-economic status.
He explained this in terms of knowledge about how to control their information
environment.  Those who knew how to use information effectively use this ability
across information channels.   Rogers (1962:313) in his 1962 synthesis, put
forward the generalization that "earlier adopters utilize a greater number of
different information sources than do later adopters."  Rogers attributed this
to the fact that they have higher education, better abstract reasoning skills,
and more ability and willingness to take risks.
        Lionberger and Campbell (1971) found that when it comes to needing information,
farmers go to the persons who are expected to be most knowledgeable, whether or
not they are much like themselves.  This tendency was found at every stage of
the adoption process.
        Although audience characteristics play an important role, the characteristics
of the innovation itself may also influence channel use.
Jain (1965) in a study often cited in support of the original generalizations,
found that the type of source used depended on the innovation.  For hybrid seed
corn and a weed control chemical, farmers used neighbors and friends for
information.  But for a record-keeping system, they used cosmopolite sources.
An earlier study in Vermont found much the same thing.  For innovations first
mentioned by the interviewers, farmers tended to mention outside or cosmopolite
sources, but for innovations that the farmers themselves first mentioned, local
sources or "self" tended to be mentioned.

This leads to our Proposition No. 3:

For economically-rational innovations, individuals who are habitually high
information seekers will adopt earlier and will use information from all sources
more.


Information-Seeking Behavior After Adoption
        One problem in studying information-seeking after adoption of an innovation is
that the question originally asked of respondents at this stage was ambiguous.
Beal and Rogers (1960) asked:  "After you once tried (antibiotics or 2,4-D weed
spray) on your farm, how did you decide whether or not to continue using and
actually adopt it?"  A more appropriate wording for this stage might have been:
"Where or from whom did you get information about the innovation after you
adopted it?"  This would parallel how questions at other stages were asked.  The
answer most commonly received by Beal and Rogers was that the farmer looked at
the results of a trial and decided to continue based upon his own evaluation.
Bohlen and Beal (1957) reported that in more than 90 percent of their studies,
individual satisfaction with the idea was the most important factor in its
continued use.  Jain (1965), using the same approach as Beal and Rogers, got the
same answer.  An answer of "self" was difficult to compare with
information-seeking responses at other stages, and as a result, the entire stage
was often dropped from either the questionnaire or the analysis.
        Beal and Rogers' (1957) companion study of adoption of new fabrics by
housewives dropped analysis of the adoption stage.  Neither Rogers nor
Deutschmann and Fals-Borda included this stage in their Colombian studies
(Deutschmann and Fals-Borda, 1962; Rogers, 1964; Rogers and Meynen, 1965; Rogers
with Svenning, 1969).  Mason (1963) did look at the communication behavior of
farmers after adoption of an innovation.  He found that in general, use of all
sources increases as one moved across stages.  However, there was an exception
for high influentials after adoption, when use of mass media declined.
        Recently, interest in what happens after adoption has increased.  Rogers (1995)
now refers to the adoption stage as a time of re-invention (adaptation of the
innovation by the adopter) and confirmation (seeking reinforcement for the
adoption decision).  Rogers explains post-adoption information behavior
partially in terms of a need to reduce dissonance.  Cognitive dissonance
research (Festinger, 1957) found that the highest levels of information seeking
often occurred immediately following adoption, but he explained this as arising
from a need to justify the adoption decision rather than a need to gather
information about how to use the innovation.
Another possibility is that for computers and other general innovations that can
do many things, questions about how to use or apply them become more salient
after adoption.  Books, manuals, dealers and other sources would be useful in
answering these questions. Thus, some innovations may be associated with very
high levels of information-seeking following adoption.  Rogers implies this when
he points out that "re-invention" is very likely for computers.  Our proposition
No. 1 already predicted a high level of information-seeking at the adoption
stage.  But in the special case of computers and other complex innovations, a
unique proposition seems to be in order.  While computers are an obvious example
of an innovation with high post-adoption information seeking, we argue that many
other innovations such as hybrid seed corn and minimum tillage agriculture
probably follow the same pattern.  In agriculture, for example, the adoption of
hybrid seed corn was not a simple process, but involved consideration of changes
in fertilizer, chemicals, planting densities, and storage issues.  Thus,
adoption of hybrid seed corn led to a significant increase in the need for
information.  Organic and minimum tillage agriculture are also complex
innovations to implement.
        This leads to our Proposition No. 4:

For innovations that are evolving internally or that are becoming more
integrated with other practices, information seeking continues at a high level
after adoption.

Using Information-Seeking Scores to Predict Behavioral Change
        Proposition No. 1 predicts a positive correlation between one's stage in the
adoption process and the total number of information sources being sought.  One
way of interpreting this finding is that as a person becomes more and more
actively interested in an innovation, he or she is likely to seek out more and
more information about it.  Thus, at the awareness stage, one would expect a low
level of information-seeking activity from any source.  At the information or
knowledge stage, more sources or more intensive use of existing sources would be
expected.  At the evaluation, persuasion or decision stages, when a respondent
says he or she is seriously considering adoption, one would expect a very high
level of information-seeking.  Finally, a case has been made that after adoption
of a computer or similar device, the rate of information-seeking would be
expected to remain high.
        Operationally, this means that if one were to follow information-seeking
behavior of potential adopters over time, one would expect that those who
exhibit little or no change in information-seeking would remain at their current
adoption stage, and that those who raise their levels of information-seeking
would move forward in the process by one or more stages.  If our approach is
correct, we would anticipate that a reduction in information-seeking activity
should be associated with a backward movement in adoption.  That is, a person at
Time 1 who said he or she is seriously evaluating adoption of an innovation
might move backward to the knowledge stage at Time 2. The original diffusion
model did not anticipate this type of movement. One interpretation, and the one
adopted here, is that while the traditional diffusion approach  would require
either a static condition or movement to adoption or rejection, in fact there is
some "temporary suspension" of thinking about an innovation, which might mean
that the person continues to read about an innovation, but is not now seriously
considering it.  A second possibility is that these changes might be due to
random error.  However, if the information-seeking activity would also decline
as a person reports backward movement, this would indicate not only that the
error is not random, but would demonstrate the close relationship between
information-seeking activity and stage in the adoption process.  This leads to
the fourth proposition:
An increase in one's information-seeking behavior tends to be associated with a
forward movement to a more advanced adoption stage, while a decrease in one's
information-seeking is associated with a backward movement.

The Longitudinal Dataset
Data for the preliminary test of the propositions is taken from a longitudinal
study of computer adoption by Iowa farmers initiated by J. Paul Yarbrough at
Iowa State University in 1982, and continued by Clifford Scherer and Eric
Abbott.  The research was funded by the Iowa State University Agricultural and
Home Economics Experiment Station.  The study consisted of an initial panel of
1,000 randomly-selected farmers surveyed by mail in 1982, and then re-surveyed
in 1984 and 1987; a second panel of 1,000 randomly-selected farmers surveyed by
mail in 1984 and again in 1988; a third random sample of 1,000 surveyed in 1989;
and a fourth random sample of 1,000 surveyed in 1997.  The mail surveys used the
Dillman (1978) Total Design Method, and resulted in return rates of between 65%
and 75% (except for 1997, which had a return rate of 44%).  By 1987 when the
first panel had responded three times, it contained 303 farmers.  The second
panel, which responded for the second time in 1988, contained 440 farmers.
Each time the farmers were surveyed, they were asked two questions that are
crucial for this analysis.  First, they were asked to indicate where they were
with respect to adoption of a computer.  Following a classification similar to
that developed by the original subcommittee, farmers were asked to indicate if
they had given "little thought (awareness)" to computers, had sought
"information" about computers (but not yet making any decision), were actively
"deciding (evaluating)" whether or not to adopt, had actually "adopted," or had
"rejected."   Since the research began at a time when very few farmers had
adopted, the problem of having to recall information from long ago was
minimized.  In addition, since these same farmers were surveyed repeatedly, it
was possible to chart their adoption progress over a period of time.  This
avoids the problems with "one-shot" diffusion studies mentioned by Rogers.
The second variable was a series of questions concerning computer information
seeking.   Farmers were asked: "Within the past year, how often have you used
the following sources to obtain information about computers?"  There were 11
choices, which included both mass media and interpersonal sources.
Items were:
1.      reading about them in magazines or newspapers;
2.      reading books or computer manuals;
3.      writing or telephoning for information from computer manufacturers or
dealers;
4.      visiting a computer dealer;
5.      attending a computer exhibit or fair;
6.      taking a computer short-course or workshop from a computer dealer, college or
other organization;
7.      attended an Extension meeting where part of the program was about computers;

1.      talked with Extension staff about computers;

1.      Talked with college or high school teachers about computers;

1.      Talked about computers with other farmers who are using them;

1.      Talked about computers with non-farm users.


For each item, respondents could indicate "never" (0), "once" (1), "twice" (2),
"three times" (3), "four or more times" (4).  A score was then calculated by
adding all computer information-seeking items, yielding a possible range of from
0 to 44.  Unlike the early diffusion studies, the use of all information sources
was assessed, and then compared to the respondent's adoption stage.
Test of Proposition No.1

As one moves through the adoption process, information-seeking from all
available channels increases.

Three of the random samples of Iowa farmers (1982, 1989 and 1997) were used for
this test so that information-seeking could be examined at several different
time periods.   The two variables, stage of the adoption process and computer
information-seeking, were compared for each time period.
Results, Table 3, show that Proposition No. 1 is supported in every time period.
In each case, total computer information-seeking increases as one moves through
the stages of the process, and is highest for those who have adopted a computer.
Table 3: Total computer information-seeking behavior
By computer adoption progress: 1982, 1989, 1997 Iowa random samples

Adoption Progress Scale
1982
1989
1997
"Little thought"
  4.5
  4.6
  4.3
"Rejected" or "Discontinued"
  4.7
  5.4
  2.9
"Obtained Information"
  9.5
10.1
  8.0
"Deciding or Decided to get a computer"
14.8
13.5
11.9
"Adopted a computer"
18.2
19.1
12.9
F linear test
273.6  (p<.000)
386.1 (p<.000)
105.4 (p<.000)
F deviation from linear
7.2 (p<.001)
6.8 (p<.001)
3.0 (p<.05)
Correlation
 .57 (p<.000)
.62 (p<.000)
.53 (p<.000)

These results have very high F values on a linear test, indicating a highly
significant increase for every year.  Deviation scores are also significant, but
at a much lower level, indicating that the increases are not perfectly linear.
Nevertheless, there remains a high correlation in each group between computer
information-seeking and the stage of the process.
A more rigorous test of the proposition would divide computer
information-seeking in the three time periods by whether or not the sources
were:
1.      Impersonal media  (articles or books)
2.      Expert sources (extension staff, dealers, teachers, etc.)
3.      Friends or neighbors
For this test, the 11 items used to construct the overall computer
information-seeking score were divided into the three categories.  Only one -
computer fairs - was eliminated, since a fair could mean contact with friends,
experts, or media sources. The others were grouped as follows:
1.      Impersonal media:
y       Read articles in magazines or books;
y       Read books about computers (or computer manuals)
4.      Expert sources:
y       Written or telephoned for information from computer manufacturers or dealers;
y       Visited a computer dealer;
y       Taken a computer short course or workshop from a computer dealer, college or
other organization;
y       Attended an Extension meeting where part of the program was about computers;
y       Talked with Extension staff about computers;
y       Talked with college or high school teachers about computers.
11.     Friends and neighbors:
y       Talked about computers with other farmers who are using them;
y       Talked about computers with non-farm users.

Scores have been standardized across categories.  Results indicate strong
support for the proposition.   Use of sources increases significantly for every
type of information across each of the three time periods.  Analysis of variance
tests for linearity show highly significant results for all columns of the
table.  Deviation from linearity scores are much lower, but indicate that
relationships are not perfectly linear in several cases, especially for experts
in 1982 and 1989.  Use jumps rather suddenly rather than increasing in a linear
fashion.  High and significant correlations exist for every column of the table.
The original generalizations would suggest that the use of mass media would
decline as one becomes more serious about adoption, and that the use of friends
and neighbors and expert sources would increase.  Results, Table 4, show that
information-seeking scores for all three categories increases as one moves
across the adoption process.  This supports Proposition No. 1 for all
information sources.
Table 4
Mean Computer Information-Seeking by Source
for 1982, 1989, and 1997 Iowa Random Samples


1982
1989
1997

Media
Experts
Friends
Media
Experts
Friends
Media
Experts
Friends
Little Thought
2.5
  .5
1.2
1.9
  .4
1.4
1.5
  .6
1.6
Rejected
2.3
  .8
1.2
1.8
  .7
1.7
  .9
  .3
1.3
Know-ledge
4.2
1.8
2.8
3.3
1.9
3.0
2.6
1.0
3.2
Decision
5.4
4.6
3.5
4.0
3.2
4.1
3.6
2.8
3.9
Adoption
6.8
6.7
3.8
5.6
6.1
4.5
4.0
3.2
3.8
F Linear test
147.3*
262.5*
95.1*
219.8*
330.0*
191.6*
67.6*
66.4*
56.6*
F Deviation from linear test
    4.9*
  14.0*
  2.0
    7.3*
  35.8*
    2.5
  2.4
  1.8
  2.7*
Correlation
.46*
.56*
.39*
.52*
.59*
.49*
.44*
.44*
.41*


The reported use of a number of information sources does not indicate the value
that might be placed on any one source, or the synergistic effect that might be
brought about by the use of multiple sources.  However, it is strongly
suggestive of the fact that printed or impersonal media sources do not lose
their importance as one moves through the adoption process.





Proposition No. 2
Information-seeking behavior is conditioned by the development and behavior of
message-production and delivery systems.

This proposition deals with the message-production and delivery systems.    In
the tables testing Proposition No. 1, three different time periods are shown.  A
re-examination of the tables shows that the computer information-seeking scores
decline across time for all types of sources.   The availability of relevant
media coverage could be expected to influence media use.  Agenda setting theory,
for example, has found a strong relationship between the amount of material in
the press on a given topic and the public's ranking of the topic as being
important or not important.   The main emphasis of the current research was not
on patterns of media coverage.  However, during the initial period of computer
diffusion, from 1978-1986, we conducted a content analysis of coverage of farm
computers by farm magazines and the Des Moines Register.  The results show a
peak in coverage in 1983-84, which was a period of optimism about the future of
farm computers.  Two years later, the farm economy was in recession, and a
number of new farm computer magazines went out of business.  Figure 1 shows the
pattern.



  [--- WMF  Graphic Goes Here  ---]




















 Media coverage patterns would indicate that the greatest likely use of
information about farm computers would have occurred in the 1983-1984 peak, and
would have declined somewhat thereafter.  Unfortunately, a complete dataset
showing what media provided after 1986 is not available.  However,  we can look
at media use patterns by farmers during this time period using the panel that
was surveyed in 1982, 1984, and 1987.  Since these are the same individuals, we
can control to an extent for differences across groups.  In general, panel
studies show an increase in scores over time as less willing or able individuals
cease responding.  However, as Table 5 shows, in this case the data support our
proposition, especially for the mass media coverage.  The 1984 group - matching
the height of the media hoopla about farm computers - in general shows the
highest computer information-seeking scores for media and experts, but not
friends/neighbors.  The analysis of variance test for linearity is not
significant, but the significant quadratic test for a curvilinear relationship
confirms that the 1984 year is higher (this is what we predicted).  By 1987,
when the farm depression hit and media coverage of farm computers declined,
information-seeking scores declined for the knowledge, decision and adoption
stages for almost all categories (the one exception again was the decision stage
for friends).  The tests for experts and friends are not as clear (but the
proposition deals mainly with mass media).  Use of experts is significant in
both linear and quadratic tests, indicating that use of experts overall
increased across time, and their use in 1984 was also highest.  For friends,
results show a linear trend, indicating a steady increase in interpersonal
communication over time.    Tichenor, Donohue and Olien (1980) have found a
close relationship between media coverage levels and interpersonal discussion
and learning.  Media tend to stimulate discussion.
Table 5: Trends in computer information-seeking
Iowa Panel No. 1: 1982, 1984, 1987

Year
F value
Source
1982
1984
1987
Linear
Quadratic
Media
3.0
3.4
3.1
  1.53 n.s.
  4.01 (p<.05)
Experts
1.2
2.3
2.0
23.7 (p<.000)
16.8 (p<.000)
Friends
1.6
2.3
2.5
34.6 (p<.000)
  2.0 n.s.


Proposition No. 3
For economically-rational innovations, individuals who are habitually high
information seekers will adopt earlier and will use information from all sources
more.

        Since this proposition is not in conflict with the body of findings from
previous diffusion studies, no test of it is provided here.  Existing diffusion
literature has consistently found that those with high education seek out more
information and adopt earlier.  Part of the reason why information-seeking
scores tend to decline over time is that innovators and early adopters tend to
be well-educated, and thus are adept at seeking information from many different
sources.
Proposition No. 4
For innovations that are evolving internally or that are becoming more
integrated with other practices, information-seeking continues at a high level
after adoption.

Our longitudinal study was of the adoption of computers, and results support the
proposition.  Information-seeking scores found among adopters in Tables 3, 4 and
5 were consistently the highest of any group across all types of
information-seeking.  This includes information-seeking from media sources,
experts and friends/neighbors.   The tendency of adopters to seek computer
information is not limited to recent adopters.  In fact, our 1997 dataset shows
that those who adopted computers before 1990 have computer information-seeking
scores (15.3) that are slightly higher than  those who adopted in 1990 or later
(13.1).  Rogers explained information-seeking following adoption as being due in
part to dissonance, with information-seeking occurring to allow the purchaser to
justify the decision.  However, long-term information-seeking patterns such as
those shown in our data would be difficult to explain using dissonance theory.
The pattern shown here suggests information-seeking for answers to questions
about how to use the machine effectively and master new applications.
Because it is possible that computers form a special case, this proposition
should be tested with a number of different types of evolving innovations.   As
mentioned earlier, it is our position that high post-adoption
information-seeking would be found for many innovations.

Proposition No. 5

An increase in one's information-seeking behavior tends to be associated with a
forward movement to a more advanced adoption stage, while a decrease in one's
information-seeking is associated with a backward movement.


        The focus of interest for testing this proposition is on the change across time
between an individual's adoption stage and his or her information-seeking score.
To test this, paired comparisons between the status of respondents at one point
in time with another were made.  For the first panel, two time periods could be
compared - the change between 1982-1984, and between 1984-1987.  For the second
panel, one time period, 1984-1988, could be compared.  This yielded two paired
comparisons of 303 each for the first panel, and 440 for the second, for a total
of 1044 comparisons.
        Each comparison could fit into one of three categories:
1)      No change: the respondent might not have changed adoption stages between the
two time periods. For example, a respondent who said he was at the information
stage at time 1 and was still there at time 2 would be classified as no change;
2)      Forward Progress: the respondent has moved forward, for example from the
awareness stage to information, evaluation or adoption; or from evaluation to
adoption;
3)      Backward Progress: the respondent has moved backward, for example from
evaluation back to information.
Based on their categories, respondents were then placed in cells in a matrix.
For each cell, the mean computer information-seeking score was calculated, as
well as the change in score from time 1 to time 2.  The results are shown in
Table 6 below.
Table 6:
Change in Information Behavior
By Change in Adoption Stage

Before




After

Aware
Information
Evaluation
Adoption

Aware
5.3
0.14
6.0
-1.64

10.5
-8.99


9.7
-7.21

Information
6.8
0.06
8.3
-2.44



Evaluation
13.7
2.51
14.8
-1.91


Adoption
16.9
4.36
19.5
-3.33

N=1044 paired comparisons
Pooled Iowa Panels: 1982-1984; 1984-1987; 1984-1988
Top Number in each cell is the mean computer information-seeking score
Bottom Number in each cell is the change in computer-information-seeking between
Before and After.

        First, we examine the characteristics of individuals in the first group - who
have not changed their adoption status.  These respondents are found in the band
of cells from top left to bottom right of the table.  These are individuals who
were in the awareness stage "before" and are still there "after," the
Information stage before and after, etc.   The mean computer information-seeking
scores show the same trend that we saw in our earlier analysis of the random
samples - as one moves from awareness through information, evaluation and to
adoption, computer information-seeking scores climb.  The second figure, in
boldface, shows the change in scores.  Note that the scores become slightly
negative across time.  One reason for this slight negative trend was shown when
testing Proposition 2.  As mass media coverage declines somewhat over time, use
of sources declines.
        The second group, those who have made forward progress are shown in the dark
box at the bottom left of the table.  For example, those who were only aware
"before" and are now at the information stage "after" are shown in the box at
the top of the darkened area.  Figures are also shown for movement to evaluation
and adoption from lower "before" stages.  Note that once again, mean computer
information-seeking scores rise as one moves to more advanced adoption process
levels.  More importantly, the change score is positive, and becomes more
positive as one moves through information to evaluation and then to adoption.
        The third group, those who have moved backward through the process, are shown
in the dotted area at the top right of the table.  These individuals now report
that they are at an earlier stage of the adoption process than they were when
first measured.  Note that the change score for individuals in this group is
negative, and for those moving from adoption and evaluation to a lower stage, it
is very negative.
        These results offer strong preliminary support for our proposition.  Changes in
information-seeking behavior are closely associated with actual changes in
adoption progress.  And the changes may be positive or negative.

         Conclusions

        There have been several previous critiques of the diffusion theory
generalizations dealing with the role of information in the adoption process,
including Chaffee's 1979 paper and critiques by diffusion scholars themselves.
This paper goes beyond these earlier critiques in two important respects.
First, it develops four new propositions designed specifically to redirect
attention to important areas of information-seeking that have not been
adequately investigated by diffusion researchers.  Second, it tests the
propositions using a longitudinal dataset designed especially to measure
multiple channel information-seeking and adoption behavior over time.

Four New Propositions

Multiple Sources
        By presenting information-seeking as an additive process rather than a discrete
process, our approach attempts to redefine the paradigm about the role of
information-seeking in the diffusion process.  Once an additive approach is
followed, research can begin on synergistic ways in which adopters use
information sources simultaneously.  Both the Columbia researchers and the
members of the subcommittee were interested in the roles of different media
channels (impersonal vs. personal), but this emphasis on a discrete approach
(that mass media inform and friends persuade) obscured the ways in which people
use many media sources for similar purposes.
        The additive approach conceptualizes the initial source as a product of the
pattern of use of information sources by adopters.  Whatever channel is
customarily available that carries new information will be used.  In the classic
hybrid seed corn study (Ryan and Gross, 1943), it was salesmen.  In the Columbia
researchers' medical innovation study (Coleman, Katz and Menzel, 1966) it was
drug detail men.  In Sill (1958), it was Extension - an agency that was
dedicated to reaching farmers with new information on specific innovations.
Similarly, where mass media are widely available and carry relevant content,
they are often named as the initial source (Beal and Rogers, 1957, Rogers and
Beal, 1958).  Where mass media are not widely available, as in many developing
countries, interpersonal sources are found to be the key initial source (Rogers
and Svenning, 1969; Deutschman and Fals-Borda, 1962).
        Once there is interest in an innovation, which is likely to be caused by both
available information and a cognitive realization that an innovation might be
useful, there is a dramatic acceleration of information-seeking from all sources
perceived to have useful information.  Chaffee (1979) suggested that information
consumers typically cross-check sources to verify and validate information.
Tichenor, Donohue and Olien (1980) find that when information saturation occurs
in communities about a relevant local topic, considerable learning takes place
among all socio-economic levels, and there is a significant relationship between
interpersonal communication and learning from newspapers and other media.
Chaffee and Choe's (1980)  study of voting behavior shows that campaign deciders
wake up to the fact that it is time to pay attention to the campaign about a
month or two before the election, and begin to use both interpersonal and mass
media sources. Pre-campaign deciders, on the other hand, attend to multiple
information channels almost from the beginning and continue to use them
throughout the campaign.
        How audiences utilize multiple information sources to make sense of what an
innovation offers, how they evaluate what is a credible source and what is not,
and how the totality of information is used to reach a decision would be a
productive new area for diffusion research.  In the area of computers, computer
magazines that offer detailed information and comparative performance trials
might be considered more valuable in the decision process than the fact that a
neighbor or friend happens to be using a computer, although surely potential
adopters would check both.  Kosicki's (1990)  notion that people's history with
information channels leads to development of framing strategies that guide
subsequent source use and evaluation is an example of where this research might
lead.
Shifts in Mass Media and Interpersonal Content
        The idea that there is a constantly-shifting pool of information and media
about an innovation - with a hoopla period or waves of coverage - suggests that
much more attention should be paid to the patterns of provision of information
across time.  Rather than being viewed as a constant, with differential use
being attributed to personality factors (innovators versus laggards), seeing the
information system as dynamic refocuses attention on what was available at any
given point in time, and what audiences were stimulated to talk about.  Early
adopters tend to adopt during hoopla periods when there are many different
sources of information available and considerable interpersonal discussion.  Is
it surprising that evidence shows that they use them?  Laggards, coming later,
find information channels carry less information. At the same time, as more and
more people have adopted, it is more likely that laggards will encounter someone
who has adopted or knows about the innovation.  This would explain why laggards
tend to use such interpersonal sources.
        The discussion here is not intended to suggest that all differences can be
accounted for by change in the types of information available.  We agree with
the strong evidence frequently cited in diffusion literature showing that
education is a powerful force shaping patterns of attention and use of
information sources.  Our assertion is only that information channel content is
dynamic and should be studied along with education and other factors.
Information-Seeking Following Adoption

        Diffusion researchers have already begun to focus on the adoption and
post-adoption stages of the process (adoption, re-invention, confirmation - see
Rogers, 1995).  Our contribution here is to suggest that for innovations that
are evolving internally or complex, information-seeking is likely to continue at
a high level for some time.   Our computer data show that information-seeking
levels remain high for up to 20 years following adoption --higher than any other
stage of the adoption process.  This is a long-term area of information use that
needs to be studied further.  Although Rogers' (1995) notion that dissonance
theory might explain some of the information-seeking that goes on following
adoption, our evidence indicates that there must be much more going on than
that.   Rogers (1995) development of the "re-invention" and "confirmation"
stages represents an important step in studying post-adoption behavior.
        Many innovations, such as taking a long-term drug for a heart or bone density
condition, organic farming, or changing to low-fat cooking, are actually complex
in their ramifications and probably stimulate long-term information-seeking
behavior.   Although more study is needed, we expect that computers are not
unique in high information-seeking after adoption.

Forward and Backward Progress
        The proposition concerning forward and backward adoption progress of people
over time, and the close relationship between patterns of innovation
information-seeking and changes in adoption stage, suggest that
information-seeking can to some extent be taken as a barometer of adoption
progress.   When levels increase, forward progress is likely (although rejection
is also possible).  When they decline, suspension of interest or even
discontinuance may occur.  The pattern strongly supports the notion that
adoption is related not to the use of any one type of information source (e.g.
interpersonal) but to use of the whole spectrum of information sources.
        Backward progress illustrates the need for study of the dynamic process by
which people are activated to consider adoption and then lose their interest.
Although not shown in the figure presented, we found that "rejection" is a
dynamic phenomenon - today's rejecter may be tomorrow's adopter.  Rejection,
which in some few cases actually is the result of a carefully considered
decision, is more often a statement of not wanting to think about an innovation.
That is why information-seeking scores associated with rejection are so similar
to the "little thought" group scores.
        Instead of a one-way linear process, we now see the adoption process as
potentially containing a number of periods of interest followed by periods of
inactivity, initial rejection followed by information-seeking followed by yet
another rejection, or adoption followed by discontinuance.  Changes in
individual circumstances, such as receiving a substantial tax refund, may set in
motion information-seeking and adoption behavior that had been inactive for some
time.

A Revised Methodological Approach and Longitudinal Study

        The second contribution of our research has been to go beyond criticism of the
original generalizations, and to develop and test a methodology for the
alternative propositions.  Characteristics  of the revised methodology include:
y       A combination of panel and random sample surveys taken over the period of
diffusion of the innovation;
y       Questions that document both the adoption progress stage and innovation
information-seeking at every survey point.
The approach addresses a number of criticisms that Rogers (1995) has made of
existing diffusion datasets, including the problems of recall over long periods
of time and reliance on one-shot surveys.  It also measures post-adoption
information-seeking behavior, up to 20 years after the innovation was adopted.
        Our dataset is somewhat unique, in that it began when computers first became
commonly available and has now continued through the innovator (2.5%), early
adopter (13.5%) and early majority (34%) stages using both panel and random
samples.  Panel data have permitted us to examine specific changes in individual
behavior over time, while the random samples have provided estimates of overall
adoption progress and information-seeking at regular points in time.  Such
datasets are needed to move diffusion research beyond its current level.

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