From Wikipedia, the free encyclopedia
The
diffusion of innovations according to Rogers. With successive groups of
consumers adopting the new technology (shown in blue), its market share (yellow) will eventually reach the saturation level. The blue curve is broken into sections of adopters.
Diffusion of innovations is a
theory that seeks to explain how, why, and at what rate new
ideas and
technology spread.
Everett Rogers, a professor of
communication studies, popularized the theory in his book
Diffusion of Innovations; the book was first published in 1962, and is now in its fifth edition (2003). Rogers argues that diffusion is the process by which an
innovation
is communicated over time among the participants in a social system.
The origins of the diffusion of innovations theory are varied and span
multiple disciplines.
Rogers proposes that four main elements influence the spread of a new idea: the innovation itself,
communication channels, time, and a social system. This process relies heavily on
human capital.
The innovation must be widely adopted in order to self-sustain. Within
the rate of adoption, there is a point at which an innovation reaches
critical mass.
The categories of adopters are innovators,
early adopters, early majority, late majority, and laggards.
Diffusion manifests itself in different ways and is highly subject to
the type of adopters and innovation-decision process. The criterion for
the adopter categorization is innovativeness, defined as the degree to
which an individual adopts a new idea.
History
The
concept of diffusion was first studied by the French
sociologist Gabriel Tarde in late 19th century and by German and Austrian
anthropologists and
geographers such as
Friedrich Ratzel and
Leo Frobenius. The study of diffusion of innovations took off in the subfield of
rural sociology
in the midwestern United States in the 1920s and 1930s. Agriculture
technology was advancing rapidly, and researchers started to examine how
independent farmers were adopting hybrid seeds, equipment, and
techniques.
A study of the adoption of hybrid corn seed in Iowa by Ryan and Gross
(1943) solidified the prior work on diffusion into a distinct paradigm
that would be cited consistently in the future. Since its start in rural sociology, Diffusion of Innovations has been applied to numerous contexts, including
medical sociology,
communications,
marketing,
development studies,
health promotion,
organizational studies,
knowledge management,
conservation biology and
complexity studies, with a particularly large impact on the use of medicines, medical techniques, and health communications. In organizational studies, its basic epidemiological or internal-influence form was formulated by H. Earl Pemberton, who provided examples of institutional diffusion such as postage stamps and standardized school ethics codes.
In 1962,
Everett Rogers, a professor of rural sociology, published his seminal work:
Diffusion of Innovations. Rogers synthesized research from over 508 diffusion studies across the fields that initially influenced the theory:
anthropology, early sociology,
rural sociology,
education,
industrial sociology and
medical sociology. Using his synthesis, Rogers produced a theory of the adoption of innovations among individuals and organizations.
Diffusion of Innovations
and Rogers' later books are among the most often cited in diffusion
research. His methodologies are closely followed in recent diffusion
research, even as the field has expanded into, and been influenced by,
other methodological disciplines such as
social network analysis and communication.
Elements
The key elements in diffusion research are:
Element
|
Definition
|
Innovation
|
Innovation is a broad category, relative to the current knowledge of
the analyzed unit. Any idea, practice, or object that is perceived as
new by an individual or other unit of adoption could be considered an
innovation available for study.
|
Adopters
|
Adopters are the minimal unit of analysis. In most studies, adopters
are individuals, but can also be organizations (businesses, schools,
hospitals, etc.), clusters within social networks, or countries.
|
Communication channels
|
Diffusion, by definition, takes place among people or organizations.
Communication channels allow the transfer of information from one unit
to the other. Communication patterns or capabilities must be established between parties as a minimum for diffusion to occur.
|
Time
|
The passage of time is necessary for innovations to be adopted; they
are rarely adopted instantaneously. In fact, in the Ryan and Gross
(1943) study on hybrid corn adoption, adoption occurred over more than
ten years, and most farmers only dedicated a fraction on their fields to
the new corn in the first years after adoption.
|
Social system
|
The social system is the combination of external influences (mass
media, surfactants, organizational or governmental mandates) and
internal influences (strong and weak social relationships, distance from opinion leaders). There are many roles in a social system, and their combination represents the total influences on a potential adopter.
|
Characteristics of innovations
Studies
have explored many characteristics of innovations. Meta-reviews have
identified several characteristics that are common among most studies. These are in line with the characteristics that Rogers initially cited in his reviews.
Potential adopters evaluate an innovation on its relative
advantage (the perceived efficiencies gained by the innovation relative
to current tools or procedures), its compatibility with the pre-existing
system, its complexity or difficulty to learn, its trialability or
testability, its potential for reinvention (using the tool for initially
unintended purposes), and its observed effects. These qualities
interact and are judged as a whole. For example, an innovation might be
extremely complex, reducing its likelihood to be adopted and diffused,
but it might be very compatible with a large advantage relative to
current tools. Even with this high learning curve, potential adopters
might adopt the innovation anyway.
Studies also identify other characteristics of innovations, but these are not as common as the ones that Rogers lists above.
The fuzziness of the boundaries of the innovation can impact its
adoption. Specifically, innovations with a small core and large
periphery are easier to adopt. Innovations that are less risky are easier to adopt as the potential loss from failed integration is lower.
Innovations that are disruptive to routine tasks, even when they bring a
large relative advantage, might not be adopted because of added
instability. Likewise, innovations that make tasks easier are likely to
be adopted.
Closely related to relative complexity, knowledge requirements are the
ability barrier to use presented by the difficulty to use the
innovation. Even when there are high knowledge requirements, support
from prior adopters or other sources can increase the chances for
adoption.
Characteristics of individual adopters
Like
innovations, adopters have been determined to have traits that affect
their likelihood to adopt an innovation. A bevy of individual
personality traits have been explored for their impacts on adoption, but
with little agreement.
Ability and motivation, which vary on situation unlike personality
traits, have a large impact on a potential adopter's likelihood to adopt
an innovation. Unsurprisingly, potential adopters who are motivated to
adopt an innovation are likely to make the adjustments needed to adopt
it.
Motivation can be impacted by the meaning that an innovation holds;
innovations can have symbolic value that encourage (or discourage)
adoption.
First proposed by Ryan and Gross (1943), the overall connectedness of a
potential adopter to the broad community represented by a city.
Potential adopters who frequent metropolitan areas are more likely to
adopt an innovation. Finally, potential adopters who have the power or
agency to create change, particularly in organizations, are more likely
to adopt an innovation than someone with less power over his choices.
Characteristics of organizations
Organizations
face more complex adoption possibilities because organizations are both
the aggregate of its individuals and its own system with a set of
procedures and norms.
Three organizational characteristics match well with the individual
characteristics above: tension for change (motivation and ability),
innovation-system fit (compatibility), and assessment of implications
(observability). Organizations can feel pressured by a tension for
change. If the organization's situation is untenable, it will be
motivated to adopt an innovation to change its fortunes. This tension
often plays out among its individual members. Innovations that match the
organization's pre-existing system require fewer coincidental changes
and are easy to assess and more likely to be adopted.
The wider environment of the organization, often an industry,
community, or economy, exerts pressures on the organization, too. Where
an innovation is diffusing through the organization's environment for
any reason, the organization is more likely to adopt it. Innovations that are intentionally spread, including by political mandate or directive, are also likely to diffuse quickly.
Process
Diffusion occurs through a five–step decision-making process. It
occurs through a series of communication channels over a period of time
among the members of a similar social system. Ryan and Gross first
identified adoption as a process in 1943.
Rogers' five stages (steps): awareness, interest, evaluation, trial,
and adoption are integral to this theory. An individual might reject an
innovation at any time during or after the adoption process. Abrahamson
examined this process critically by posing questions such as: How do
technically inefficient innovations diffuse and what impedes technically
efficient innovations from catching on? Abrahamson makes suggestions
for how organizational scientists can more comprehensively evaluate the
spread of innovations. In later editions of Diffusion of Innovation,
Rogers changes his terminology of the five stages to: knowledge,
persuasion, decision, implementation, and confirmation. However, the
descriptions of the categories have remained similar throughout the
editions.
Five stages of the adoption process
Stage
|
Definition
|
Knowledge
|
The individual is first exposed to an innovation, but lacks
information about the innovation. During this stage the individual has
not yet been inspired to find out more information about the innovation.
|
Persuasion
|
The individual is interested in the innovation and actively seeks related information/details.
|
Decision
|
The individual takes the concept of the change and weighs the
advantages/disadvantages of using the innovation and decides whether to
adopt or reject the innovation. Due to the individualistic nature of
this stage, Rogers notes that it is the most difficult stage on which to
acquire empirical evidence.
|
Implementation
|
The individual employs the innovation to a varying degree depending
on the situation. During this stage the individual also determines the
usefulness of the innovation and may search for further information
about it.
|
Confirmation
|
The individual finalizes his/her decision to continue using the innovation. This stage is both intrapersonal (may cause cognitive dissonance) and interpersonal, confirmation the group has made the right decision.
|
Decisions
Two factors determine what type a particular decision is:
- Whether the decision is made freely and implemented voluntarily
- Who makes the decision.
Based on these considerations, three types of innovation-decisions have been identified.
Type
|
Definition
|
Optional Innovation-Decision
|
made by an individual who is in some way distinguished from others.
|
Collective Innovation-Decision
|
made collectively by all participants.
|
Authority Innovation-Decision
|
made for the entire social system by individuals in positions of influence or power.
|
Rate of adoption
The
rate of adoption is defined as the relative speed at which participants
adopt an innovation. Rate is usually measured by the length of time
required for a certain percentage of the members of a social system to
adopt an innovation.
The rates of adoption for innovations are determined by an individual’s
adopter category. In general, individuals who first adopt an innovation
require a shorter adoption period (adoption process) when compared to
late adopters.
Within the
adoption curve at some point the innovation reaches
critical mass. This is when the number of individual adopters ensures that the innovation is self-sustaining.
Adoption strategies
Rogers
outlines several strategies in order to help an innovation reach this
stage, including when an innovation adopted by a highly respected
individual within a
social network
and creating an instinctive desire for a specific innovation. Another
strategy includes injecting an innovation into a group of individuals
who would readily use said technology, as well as providing positive
reactions and benefits for early adopters.
Diffusion vs adoption
Adoption
is an individual process detailing the series of stages one undergoes
from first hearing about a product to finally adopting it. Diffusion
signifies a group phenomenon, which suggests how an innovation spreads.
Adopter categories
Rogers defines an adopter category as a classification of individuals within a
social system on the basis of innovativeness. In the book
Diffusion of Innovations,
Rogers suggests a total of five categories of adopters in order to
standardize the usage of adopter categories in diffusion research. The
adoption of an innovation follows an
S curve when plotted over a length of time. The categories of adopters are: innovators,
early adopters, early majority, late majority and laggards.
In addition to the gatekeepers and opinion leaders who exist within a
given community, change agents may come from outside the community.
Change agents bring innovations to new communities– first through the
gatekeepers, then through the opinion leaders, and so on through the
community.
Adopter category
|
Definition
|
Innovators
|
Innovators are willing to take risks, have the highest social
status, have financial liquidity, are social and have closest contact to
scientific sources and interaction with other innovators. Their risk
tolerance allows them to adopt technologies that may ultimately fail.
Financial resources help absorb these failures.
|
Early adopters
|
These individuals have the highest degree of opinion leadership
among the adopter categories. Early adopters have a higher social
status, financial liquidity, advanced education and are more socially
forward than late adopters. They are more discreet in adoption choices
than innovators. They use judicious choice of adoption to help them
maintain a central communication position.
|
Early Majority
|
They adopt an innovation after a varying degree of time that is
significantly longer than the innovators and early adopters. Early
Majority have above average social status, contact with early adopters
and seldom hold positions of opinion leadership in a system (Rogers 1962, p. 283)
|
Late Majority
|
They adopt an innovation after the average participant. These
individuals approach an innovation with a high degree of skepticism and
after the majority of society has adopted the innovation. Late Majority
are typically skeptical about an innovation, have below average social
status, little financial liquidity, in contact with others in late
majority and early majority and little opinion leadership.
|
Laggards
|
They are the last to adopt an innovation. Unlike some of the
previous categories, individuals in this category show little to no
opinion leadership. These individuals typically have an aversion to
change-agents. Laggards typically tend to be focused on "traditions",
lowest social status, lowest financial liquidity, oldest among adopters,
and in contact with only family and close friends.
|
Failed diffusion
Failed
diffusion does not mean that the technology was adopted by no one.
Rather, failed diffusion often refers to diffusion that does not reach
or approach 100% adoption due to its own weaknesses, competition from
other innovations, or simply a lack of awareness. From a social networks
perspective, a failed diffusion might be widely adopted within certain
clusters but fail to make an impact on more distantly related people.
Networks that are over-connected might suffer from a rigidity that
prevents the changes an innovation might bring, as well.
Sometimes, some innovations also fail as a result of lack of local involvement and community participation.
For example, Rogers discussed a situation in Peru involving the
implementation of boiling drinking water to improve health and wellness
levels in the village of Los Molinas. The residents had no knowledge of
the link between sanitation and illness. The campaign worked with the
villagers to try to teach them to boil water, burn their garbage,
install latrines and report cases of illness to local health agencies.
In Los Molinas, a stigma was linked to boiled water as something that
only the "unwell" consumed, and thus, the idea of healthy residents
boiling water prior to consumption was frowned upon. The two-year
educational campaign was considered to be largely unsuccessful. This
failure exemplified the importance of the roles of the communication
channels that are involved in such a campaign for social change. An
examination of diffusion in
El Salvador
determined that there can be more than one social network at play as
innovations are communicated. One network carries information and the
other carries influence. While people might hear of an innovation's
uses, in Rogers' Los Molinas sanitation case, a network of influence and
status prevented adoption.
Heterophily and communication channels
Lazarsfeld and Merton first called attention to the principles of
homophily and its opposite,
heterophily.
Using their definition, Rogers defines homophily as "the degree to
which pairs of individuals who interact are similar in certain
attributes, such as beliefs, education, social status, and the like".
When given the choice, individuals usually choose to interact with
someone similar to themselves. Homophilous individuals engage in more
effective communication because their similarities lead to greater
knowledge gain as well as attitude or behavior change. As a result,
homophilous people tend to promote diffusion among each other.
However, diffusion requires a certain degree of heterophily to
introduce new ideas into a relationship; if two individuals are
identical, no diffusion occurs because there is no new information to
exchange. Therefore, an ideal situation would involve potential adopters
who are homophilous in every way, except in knowledge of the
innovation.
Promotion of healthy behavior provides an example of the balance
required of homophily and heterophily. People tend to be close to others
of similar health status.
As a result, people with unhealthy behaviors like smoking and obesity
are less likely to encounter information and behaviors that encourage
good health. This presents a critical challenge for health
communications, as ties between heterophilous people are relatively
weaker, harder to create, and harder to maintain.
Developing heterophilous ties to unhealthy communities can increase the
effectiveness of the diffusion of good health behaviors. Once one
previously homophilous tie adopts the behavior or innovation, the other
members of that group are more likely to adopt it, too.
The role of social systems
Opinion leaders
Not all individuals exert an equal amount of influence over others. In this sense
opinion leaders
are influential in spreading either positive or negative information
about an innovation. Rogers relies on the ideas of Katz & Lazarsfeld
and the
two-step flow theory in developing his ideas on the influence of opinion leaders.
Opinion leaders have the most influence during the evaluation stage of the innovation-decision process and on late adopters.
In addition opinion leaders typically have greater exposure to the mass
media, more cosmopolitan, greater contact with change agents, more
social experience and exposure, higher socioeconomic status, and are
more innovative than others.
Research was done in the early 1950s at the University of Chicago
attempting to assess the cost-effectiveness of broadcast advertising on
the diffusion of new products and services.
The findings were that opinion leadership tended to be organized into a
hierarchy within a society, with each level in the hierarchy having
most influence over other members in the same level, and on those in the
next level below it. The lowest levels were generally larger in numbers
and tended to coincide with various demographic attributes that might
be targeted by mass advertising. However, it found that direct word of
mouth and example were far more influential than broadcast messages,
which were only effective if they reinforced the direct influences. This
led to the conclusion that advertising was best targeted, if possible,
on those next in line to adopt, and not on those not yet reached by the
chain of influence.
Research on
actor-network theory (ANT)
also identifies a significant overlap between the ANT concepts and the
diffusion of innovation which examine the characteristics of innovation
and its context among various interested parties within a social system
to assemble a network or system which implements innovation.
Other research relating the concept to
public choice theory
finds that the hierarchy of influence for innovations need not, and
likely does not, coincide with hierarchies of official, political, or
economic status.
Elites are often not innovators, and innovations may have to be
introduced by outsiders and propagated up a hierarchy to the top
decision makers.
Electronic communication social networks
Prior
to the introduction of the Internet, it was argued that social networks
had a crucial role in the diffusion of innovation particularly
tacit knowledge in the book
The IRG Solution – hierarchical incompetence and how to overcome it.
The book argued that the widespread adoption of computer networks of
individuals would lead to much better diffusion of innovations, with
greater understanding of their possible shortcomings and the
identification of needed innovations that would not have otherwise
occurred. The social model proposed by Ryan and Gross
is expanded by Valente who uses social networks as a basis for adopter
categorization instead of solely relying on the system-level analysis
used by Ryan and Gross. Valente also looks at an individual's personal
network, which is a different application than the organizational
perspective espoused by many other scholars.
Recent research by Wear shows, that particularly in regional and
rural areas, significantly more innovation takes place in communities
which have stronger inter-personal networks.
Organizations
Innovations
are often adopted by organizations through two types of
innovation-decisions: collective innovation decisions and authority
innovation decisions. The collective decision occurs when adoption is by
consensus. The authority decision occurs by adoption among very few
individuals with high positions of power within an organization.
Unlike the optional innovation decision process, these decision
processes only occur within an organization or hierarchical group.
Within an organization certain individuals are termed "champions" who
stand behind an innovation and break through opposition. The champion
plays a very similar role as the champion used within the efficiency
business model
Six Sigma.
The process contains five stages that are slightly similar to the
innovation-decision process that individuals undertake. These stages
are:
agenda-setting, matching, redefining/restructuring, clarifying and routinizing.
Extensions of the theory
Policy
Diffusion
of Innovations has been applied beyond its original domains.
In the case of political science and administration, policy diffusion
focuses on how institutional innovations are adopted by other
institutions, at the local, state, or country level. An alternative term
is 'policy transfer' where the focus is more on the agents of diffusion
and the diffusion of policy knowledge, such as in the work of
Diane Stone.
Specifically, policy transfer can be defined as "knowledge about how
policies administrative arrangements, institutions, and ideas in one
political setting (past or present) is used in the development of
policies, administrative arrangements, institutions, and ideas in
another political setting".
The first interests with regards to policy diffusion were focused in time variation or state lottery adoption, but more recently interest has shifted towards mechanisms (emulation, learning and coercion) or in channels of diffusion where researchers find that
regulatory agency
creation is transmitted by country and sector channels. At the local
level, examining popular city-level policies make it easy to find
patterns in diffusion through measuring public awareness.
At the international level, economic policies have been thought to
transfer among countries according to local politicians' learning of
successes and failures elsewhere and outside mandates made by global
financial organizations.
As a group of countries succeed with a set of policies, others follow,
as exemplified by the deregulation and liberalization across the
developing world after the successes of the
Asian Tigers.
The reintroduction of regulations in the early 2000s also shows this
learning process, which would fit under the stages of knowledge and
decision, can be seen as lessons learned by following China's successful
growth.
Technology
Peres,
Muller and Mahajan suggested that diffusion is "the process of the
market penetration of new products and services that is driven by social
influences, which include all interdependencies among consumers that
affect various market players with or without their explicit knowledge".
Eveland evaluated diffusion from a phenomenological view,
stating, "Technology is information, and exists only to the degree that
people can put it into practice and use it to achieve values".
Diffusion of existing technologies has been measured using "S
curves". These technologies include radio, television, VCR, cable, flush
toilet, clothes washer, refrigerator, home ownership, air conditioning,
dishwasher, electrified households, telephone, cordless phone, cellular
phone, per capita airline miles, personal computer and the Internet.
These data can act as a predictor for future innovations.
Diffusion curves for
infrastructure reveal contrasts in the diffusion process of personal technologies versus infrastructure.
Consequences of adoption
Both
positive and negative outcomes are possible when an individual or
organization chooses to adopt a particular innovation. Rogers states
that this area needs further research because of the biased positive
attitude that is associated with innovation.
Rogers lists three categories for consequences: desirable vs.
undesirable, direct vs. indirect, and anticipated vs. unanticipated.
In contrast Wejnert details two categories: public vs. private and benefits vs. costs.
Public versus private
Public
consequences comprise the impact of an innovation on those other than
the actor, while private consequences refer to the impact on the actor.
Public consequences usually involve collective actors, such as
countries, states, organizations or social movements. The results are
usually concerned with issues of societal well-being. Private
consequences usually involve individuals or small collective entities,
such as a community. The innovations are usually concerned with the
improvement of quality of life or the reform of organizational or social
structures.
Benefits versus costs
Benefits
of an innovation obviously are the positive consequences, while the
costs are the negative. Costs may be monetary or nonmonetary, direct or
indirect. Direct costs are usually related to financial uncertainty and
the economic state of the actor. Indirect costs are more difficult to
identify. An example would be the need to buy a new kind of pesticide to
use innovative seeds. Indirect costs may also be social, such as social
conflict caused by innovation.
Marketers are particularly interested in the diffusion process as it
determines the success or failure of a new product. It is quite
important for a marketer to understand the diffusion process so as to
ensure proper management of the spread of a new product or service.
Mathematical treatment
The diffusion of an innovation typically follows an S shaped curve which often resembles a
logistic function.
Mathematical programming models such as the
S-D model apply the diffusion of innovations theory to real data problems. In addition to that,
agent-based models follow a more intuitive process by designing individual-level rules to model diffusion of ideas and innovations.
Complex systems models
Complex network
models can also be used to investigate the spread of innovations among
individuals connected to each other by a network of peer-to-peer
influences, such as in a physical community or neighborhood.
Such models represent a system of individuals as
nodes in a network (or
graph).
The interactions that link these individuals are represented by the
edges of the network and can be based on the probability or strength of
social connections. In the dynamics of such models, each node is
assigned a current state, indicating whether or not the individual has
adopted the innovation, and model equations describe the evolution of
these states over time.
In threshold models,
the uptake of technologies is determined by the balance of two factors:
the (perceived) usefulness (sometimes called utility) of the innovation
to the individual as well as barriers to adoption, such as cost. The
multiple parameters that influence decisions to adopt, both individual
and socially motivated, can be represented by such models as a series of
nodes and connections that represent real relationships. Borrowing from
social network analysis, each node is an innovator, an adopter, or a
potential adopter. Potential adopters have a threshold, which is a
fraction of his neighbors who adopt the innovation that must be reached
before he will adopt. Over time, each potential adopter views his
neighbors and decides whether he should adopt based on the technologies
they are using. When the effect of each individual node is analyzed
along with its influence over the entire network, the expected level of
adoption was seen to depend on the number of initial adopters and the
network's structure and properties. Two factors emerge as important to
successful spread of the innovation: the number of connections of nodes
with their neighbors and the presence of a high degree of common
connections in the network (quantified by the
clustering coefficient). These models are particularly good at showing the impact of opinion leaders relative to others.
Computer models
are often used to investigate this balance between the social aspects
of diffusion and perceived intrinsic benefit to the individuals.
Criticism
Because
there are more than four thousand articles across many disciplines
published on Diffusion of Innovations, with a vast majority written
after Rogers created a systematic theory, there have been few widely
adopted changes to the theory.
Although each study applies the theory in slightly different ways, this
lack of cohesion has left the theory stagnant and difficult to apply
with consistency to new problems.
Diffusion is difficult to quantify because humans and human
networks are complex. It is extremely difficult, if not impossible, to
measure what exactly causes adoption of an innovation.
This is important, particularly in healthcare. Those encouraging
adoption of health behaviors or new medical technologies need to be
aware of the many forces acting on an individual and his or her decision
to adopt a new behavior or technology. Diffusion theories can never
account for all variables, and therefore might miss critical predictors
of adoption. This variety of variables has also led to inconsistent results in research, reducing heuristic value.
Rogers placed the contributions and criticisms of diffusion
research into four categories: pro-innovation bias, individual-blame
bias, recall problem, and issues of equality. The pro-innovation bias,
in particular, implies that all innovation is positive and that all
innovations should be adopted.
Cultural traditions and beliefs can be consumed by another culture's
through diffusion, which can impose significant costs on a group of
people.
The one-way information flow, from sender to receiver, is another
weakness of this theory. The message sender has a goal to persuade the
receiver, and there is little to no reverse flow. The person
implementing the change controls the direction and outcome of the
campaign. In some cases, this is the best approach, but other cases
require a more participatory approach.
In complex environments where the adopter is receiving information from
many sources and is returning feedback to the sender, a one-way model
is insufficient and multiple communication flows need to be examined.