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entific and technological discoveries will be made
in the future).
Finally, the very process by which such pro-
jections are developed is often difficult to trace
—i.e., we seldom have an adequate “audit trail”
describing how relevant parameters are identified
and how these parameters are related to each an-
other. Without some form of traceability, we have
little possibility for scientific control over results.
How, then, can the task of developing complex
scenarios and future projections be put on a sound
methodological basis?
With this question in mind, a research pro-
gram was initiated at FOI (the Swedish Defence
Research Agency) in the early 1990s that was
aimed at developing a methodological framework
for creating models of systems and processes that
cannot be meaningfully quantified. We began by
attempting to develop an extended form of what
is called typology analysis (Bailey, 1969). Initially,
we thought we were doing something new. How-
ever, we subsequently learned that extended ty-
pology analysis was invented as early as the 1940s
by Professor Fritz Zwicky at the California Insti-
tute of Technology in Pasadena. He called it the
morphological approach.
The term morphology derives from the an-
cient Greek word morphe, which means shape or
form. The general definition of morphology is
“the study of form or pattern,” i.e., the shape and
arrangement of parts of an object, and how these
Abstract
General morphological analysis (GMA) is a
method for systematically structuring and ana-
lyzing the total set of relationships contained in
multi-dimensional, non-quantifiable problem
complexes. During the past 15 years, GMA has
been extended, computerized and applied to long-
term strategy management and organizational
structuring. It is especially useful for developing
scenario models and mapping alternative futures.
This article outlines the fundamentals of the mor-
phological approach and describes its use in a
number of case studies in scenario development
and futures projections done for Swedish govern-
ment authorities and NGOs.
1. Introduction and Methodological
Background
Developing scenarios and modeling alterna-
tive futures (“future projections”) presents us with
a number of difficult methodological problems.
Firstly, many of the factors involved are not mean-
ingfully quantifiable, since they contain strong
social, political, and cognitive dimensions. Sec-
ondly, the uncertainties inherent in such problem
complexes are in principle non-reducible and of-
ten cannot be fully described or delineated. This
includes both so-called agonistic uncertainty
(conscious, reflective actions among competing
actors) and non-specified uncertainty (for in-
stance, uncertainties concerning what types of sci-
Tom Ritchey, a former research director for the Institution for Technology Foresight and Assessment at the
Swedish Defense Research Agency: Lyckselevägen 35, 16267 Vällingby, Sweden. E-mail ritchey@swemorph.com.
Modeling Alternative Futures with General
Morphological Analysis
By Tom Ritchey
World Future Review Spring 2011 83
“morphological approach” from the 1940s until
his death in 1974.
More recently, morphological analysis has
been applied by a number of researchers in the
United States and Europe in the fields of policy
analysis and futures studies (e.g., Rhyne 1981,
1995; Coyle 1995, 1996). In 1995, advanced com-
puter support for GMA was developed at FOI
(Ritchey, 2003a). This has made it possible to cre-
ate non-quantified inference models, which sig-
nificantly extend GMA’s functionality and areas
of application (Ritchey 1997–2011). Since then,
more than 100 projects have been carried out us-
ing computer-aided GMA, for structuring com-
plex policy and planning issues, developing sce-
nario and strategy laboratories, and analyzing
organizational and stakeholder structures.
2. General Morphological Analysis
Essentially, GMA is a method for identifying
and investigating the total set of possible relation-
ships or “configurations” contained in a given
problem complex. This is accomplished by going
through a number of iterative phases which rep-
resent cycles of analysis and synthesis—the basic
method for developing (scientific) models
(Ritchey, 1991).
The method begins by identifying and defin-
ing the most important dimensions (or parame-
ters) of the problem complex to be investigated,
and assigning each dimension a range of relevant
values or conditions. This is done mainly in nat-
ural language, although abstract labels and scales
can be utilized to specify the set of elements de-
fining the discrete value range of a parameter.
A morphological field is constructed by set-
ting the parameters against each other in order to
create an n-dimensional configuration space (Fig-
ure 1). A particular configuration (the darkened
cells in the matrix) within this space contains one
”value” from each of the parameters, and thus
marks out a particular state of, or possible formal
solution to, the problem complex.
conform to create a whole, or Gestalt. The “ob-
jects” in question can be physical (e.g., an organ-
ism or an ecology), social/organizational (e.g., a
corporation or a defense structure), or mental
(e.g., linguistic forms or any system of ideas).
The first to use the term morphology as an
explicitly defined scientific method would seem
to be J.W. von Goethe (1749-1832), especially in
his “comparative morphology” in botany. Today,
morphology is associated with a number of sci-
entific disciplines where formal structure, and not
necessarily quantity, is a central issue, e.g., lin-
guistics, geology, and zoology.
Zwicky proposed a generalized form of mor-
phology, which today goes under the name of
General Morphological Analysis (GMA):
Attention has been called to the fact
that the term morphology has long been
used in many fields of science to desig-
nate research on structural interrela-
tions—for instance in anatomy, geology,
botany and biology. ... I have proposed
to generalize and systematize the con-
cept of morphological research and in-
clude not only the study of the shapes of
geometrical, geological, biological, and
generally material structures, but also to
study the more abstract structural inter-
relations among phenomena, concepts,
and ideas, whatever their character
might be. (Zwicky, 1966, p. 34)
Zwicky developed GMA as a method for
structuring and investigating the total set of rela-
tionships contained in multi-dimensional, non-
quantifiable, problem complexes (Zwicky 1966,
1969). He applied the method to such diverse
fields as the classification of astrophysical objects,
the development of jet and rocket propulsion sys-
tems, and the legal aspects of space travel and col-
onization. He founded the Society for Morpho-
logica l Resear c h and ch ampi oned th e
84 World Future Review Spring 2011
is examined, a judgment is made as to whether—
or to what extent—the pair can coexist, i.e., rep-
resent a consistent relationship. Note that there is
no reference here to direction or causality, but
only to mutual consistency. Using this technique,
a typical morphological field can be reduced by
90% (or even 99%) depending on the problem
structure.
There are two principal types of inconsisten-
cies involved here: purely logical contradictions
(i.e., those based on the nature of the concepts in-
volved); and empirical constraints (i.e., relation-
ships judged to be highly improbable or implau-
sible on empirical grounds). Normative constraints
can also be applied, although these must be used
with great care, and clearly designated as such.
This technique of using pair-wise consistency
assessments between conditions, in order to weed
out inconsistent configurations, is made possible
by a principle dimension inherent in morpholog-
ical fields, or in any discrete configuration space.
While the number of configurations in such a
space grows exponentially with each new param-
eter, the number of pair-wise relationships be-
tween parameter conditions grows only in pro-
portion to the triangular number series—a
quadratic polynomial.
Naturally, there are also practical limits
reached with quadratic growth. The point, how-
ever, is that a morphological field involving as
The point is to examine all of the configura-
tions in the field, in order to establish which of
them are possible, viable, practical, interesting,
etc., and which are not. In doing this, we mark
out in the field a relevant solution space. The so-
lution space of a Zwickian morphological field
consists of the subset of all the configurations
which satisfy certain criteria. The primary crite-
rion is that of internal consistency.
Obviously, in fields containing more than a
handful of variables, it would be time-consuming
—if not impossible—to examine all of the config-
urations involved. For instance, a 6-parameter
field with 6 conditions under each parameter con-
tains more than 46,000 possible configurations.
Even this is a relatively small field compared to
some of the ones we have been studying. Thus the
next step in the analysis-synthesis process is to
examine the internal relationships between the
field parameters and “reduce” the field by weed-
ing out configurations which contain mutually
contradictory conditions. In this way, we create a
preliminary outcome or solution space within the
morphological field without having first to con-
sider all of the configurations as such.
This is achieved by a process of cross-consis-
tency assessment. All of the parameter values in
the morphological field are compared with one
another, pair-wise, in the manner of a cross-im-
pact matrix (Figure 2). As each pair of conditions
Figure 1: A 6-parameter morphological field. The darkened cells define one of
4800 possible (formal) configurations.
Parameter A Parameter B Parameter C Parameter D Parameter E Parameter F
Condition A1 Condition B1 Condition C1 Condition D1 Condition E1 Condition F1
Condition A2 Condition B2 Condition C2 Condition D2 Condition E2 Condition F2
Condition A3 Condition B3 Condition C3 Condition E3 Condition F3
Condition A4 Condition B4 Condition C4 Condition E4 Condition F4
Condition A5 Condition C5 Condition E5
Condition E6
World Future Review Spring 2011 85
tigation of boundary conditions, i.e. the limits and
extremes of different parameters within the prob-
lem space. The method also has definite advan-
tages for scientific communication and—nota-
bly—for group work.
As a process, the method demands that pa-
rameters, conditions, and the issues underlying
these be clearly defined. Poorly defined concepts
become immediately evident when they are cross-
referenced and assessed for internal consistency.
Like most methods dealing with complex social
and organizational systems, GMA requires strong,
experienced facilitation, an engaged group of sub-
ject specialists and a good deal of patience.
many as 100,000 formal configurations can re-
quire no more than few hundred pair-wise eval-
uations in order to create a solution space.
When this solution (or outcome) space is
synthesized, the resultant morphological field be-
comes an inference model, in which any param-
eter (or multiple parameters) can be selected as
“input,” and any others as “output.” Thus, with
dedicated computer support, the field can be
turned into a laboratory within which one can
designate initial conditions and examine alterna-
tive solutions.
GMA seeks to be integrative and to help dis-
cover new relationships or configurations. Impor-
tantly, it encourages the identification and inves-
Figure 2: The cross-consistency matrix for morphological field in Figure 1.
86 World Future Review Spring 2011
tional and international directives, technological
developments, shifting political ideologies, mar-
ket forces, and ethical concerns.
The purpose of the EPR study was to system-
atically formulate a range of future contextual en-
vironments by which to test alternative EPR strat-
egies. Two working groups of seven persons
each—a “strategic environment group” and a
“strategy development group”—performed the
modeling together with two morphologists. The
groups were composed of researchers from the
Swedish EPA and other relevant government au-
thorities, from two NGOs and from two private
companies involved in waste management and
recycling. Each group worked two days on their
respective fields, with a final one-day joint ses-
sion during which the strategic environment
model was merged with the strategy model.
Figure 3 is an EPR future projection field
consisting of eight parameters which represent
“external” factors that can influence or constraina
Swedish EPR system. The eight parameters gen-
erate 20,736 formal configurations. In contrast to
strategy fields, or fields representing system so-
lutions, scenario or future projection fields are of-
ten difficult to assess internally and reduce. This
is because it is risky to exclude relationships which
may seem improbable today, but which might
very well be the case in five, ten, or twenty years.
In such cases, it is better to work backwards,
so to speak: Select one or more parameters as driv-
ers, choose a number of configurations based on
varying these drivers, and then assess the chosen
configurations for internal consistency after-
wards. Repeat this process until the desired num-
ber of projections is achieved.
For the study in question, eight specific con-
figurations were chosen. Together, these covered
all of the parameter states in the scenario field
(“full field coverage”), and represented a broad
range of future EPR environments. The configu-
rations were then named and linked to the col-
umn at the far left—a scenario-name “place-
3. Scenario-Framework Models: Four
Examples
The four future projection models presented
here are:
• Scenarios and strategies for an extended-
producer responsibility system
• Future human actions affecting long-term
nuclear waste storage
• Nuclear sabotage threat scenarios
• Climate change scenarios
Please note: at the request of the clients in-
volved, some of the models presented here have
been truncated or generalized.
3.1 Scenarios and Strategies For an
Extended Producer Responsibility
System
Extended producer responsibility (EPR) im-
poses accountability over the entire life cycle of
products and packaging introduced on the mar-
ket. This means that firms which manufacture,
import and/or sell products and packaging, are
required to be financially or physically respon-
sible for such products after their useful life.
They must either take back spent products
and manage them through reuse, recycling, or us-
ing them in energy production, or they must del-
egate this responsibility to a third party, a so-
called producer responsibility organization
(PRO), which is paid by the producer for spent-
product management. In this way, EPR shifts re-
sponsibility for waste from government to private
industry, obliging producers, importers, and/or
sellers to internalize waste management costs in
their product prices (see Hanisch, 2000).
The long-term purpose of EPR is to encour-
age more environmentally friendly product de-
velopment—e.g., products that require fewer re-
sources, are easier to reuse/recycle, and which
contain fewer environmentally dangerous sub-
stances. The problem, then, is to develop flexible
EPR strategies for a future in which there is a good
deal of uncertainty concerning, for instance, na-
World Future Review Spring 2011 87
ish Government Report: SOU 2001:102 Resurs i
retur (Resources in return), 2001.
3.2 Future Human Actions Affecting
Long-Term Nuclear Waste Storage
As with many other countries that utilize nu-
clear power, Sweden has a program for maintain-
ing a long-term nuclear waste repository. Future
human actions (FHA) that can affect the safety of
such repositories need to be understood in order
to develop adequate strategies for their construc-
tion and future regulation—including knowledge
management. All of this involves questions con-
cerning the long-term evolution of society and
human behaviour.
For this reason, the Swedish Nuclear Fuel and
Waste Management Company commissioned a
study to develop an initial conceptual framework
(1) to consider what factors to take into account
holder.” This is done for practical reasons, in order
to keep track of specific configurations of inter-
est. (When such a placeholder is employed to de-
fine specific configurations, we call the field spec-
ified. When no such placeholder is present, then
the field is open.)
(Note: On the computer, morphological field
configurations are color-coded. For instance, se-
lected input conditions are rendered in red, and
output conditions in blue. In the figures below,
red is represented by grey, and blue is represented
by black.)
The eight alternative future EPR environ-
ments were later linked onto a strategy space, in
order to establish which what types of strategy al-
ternatives would be most effective and/or flexible
for different ranges of alternative futures (Figure
4).
The project was reported in the official Swed-
Figure 3: An eight-parameter scenario field with a scenario “placeholder”
parameter (at far left) showing list of scenario configurations defined in the
study. One configuration—Current Policies (Negative trend)—is selected (grey).
88 World Future Review Spring 2011
man anxiety to technology, were judged to be im-
portant: e.g., values, mood, social wealth/stratifi-
cation, knowledge, intent, motive, geographic
conditions and technology. One of the central
questions posed was under what circumstances
knowledge of the repositor y could be lost by
society, and what the possible consequences of
this would be.
Figures 5 and 6 show two configurations ob-
tained from one of the models developed. This
model concerned societal knowledge of and rea-
sons for intruding into the repositories.
3.3 Nuclear Sabotage Threat Scenarios
The Swedish Nuclear Power Inspectorate
(SKI) is the regulatory authority for nuclear ac-
tivities in Sweden. Its responsibilities include nu-
clear safety and security issues, including physi-
cal protection against theft of nuclear material and
concerning long-term nuclear waste storage, and
(2) to develop a selection of representa tive sce-
narios for illustrative consequence analysis. The
work began with a series of GMA workshops in
which experts representing a wide range of tech-
nical, historical, social, and information-based
competencies took part.
These workshops had the dual purpose of
identifying framework conditions that describe
feasible societal contexts for future human ac-
tions, and also providing a forum for structured
discussions among various competencies needed
to create “smart teams.” The initial discussions at
the workshop concerned factors that can influ-
ence future human actions directed towards the
repository site (consciously or unconsciously) and
what might trigger an action that affects reposi-
tory safety.
Factors of widely differing natures, from hu-
Figure 4: Linked fields. The scenario placeholder parameter is imposed on the
strategy field. One scenario is selected (grey), with one of its possible strategy
configurations shown (black).
World Future Review Spring 2011 89
sabotage of nuclear facilities. Since the middle of
the 1970s, SKI has applied the concept of Design
Basis Threat (DBT), i.e., a profile of the type, com-
position, and capabilities of an adversary.
The DBT has repeatedly been reviewed and
revised over the years. However, in light of the
terrorist attacks in New York City and Washing-
ton, D.C., in September 2001, the DBT needed to
Figure 6: Example of positive long-term social stagnation and
lost knowledge of repository.
Figure 5: Example of positive long-term social development resulting in deposits
being retrieved as resources.
90 World Future Review Spring 2011
The highlighted configuration shows a threat
scenario which describes a small group of aggres-
sors without the support of an insider. The group
has a high level of knowledge both about the tar-
geted facility and the weapons and explosives it em-
ploys. The purpose of the attack is to sabotage
equipment in vital areas and/or to compromise re-
actor safety systems and possibly cause radiologi-
cal releases. Depending on the effectiveness of
safety systems and physical protection measures,
the potential consequence would either be no ra-
diological consequences or limited emissions.
3.4 Climate-Change Conflict
Scenarios
The series of climate change conflict models
were developed for an EU-financed project called
Climate Tools, carried out by the Swedish Defence
Research Agency (FOI). The study was directed
be revised once again, to properly take into ac-
count the experience gained from 9/11. For this
purpose, SKI decided to employ GMA as a well-
structured method within which both the process
and the results would be transparent, traceable,
and clearly documented.
The task was to develop a series of morpho-
logical models that described the total problem
complex within which alternative scenarios could
be formulated, developed, tested, and evaluated.
The work was carried out in four two-day work-
shops during the first half of 2002.
Figure 7 shows one of the threat scenario
models developed in the study, containing seven
parameters. Originally generating over one mil-
lion formal configurations, it was reduced to
slightly more than 40,000. Note, that for reasons
of confidentiality, some of the variable conditions
have been modified or truncated in this example.
Figure 7: A nuclear sabotage scenario-framework model developed for the
Swedish Nuclear Power Inspectorate.
World Future Review Spring 2011 91
types of conflict that could arise out of this.
In Figures 8 and 9, a worst-case example was
selected involving a mean global temperature rise
of 6-8 degrees and a sea level rise of 70-80 centi-
meters. The time perspective was 50 years. Note
that in this model, the Baltic area manages fairly
well compared, for example, to southern Europe.
While the principal types of conflict that might
result are the same, their details differ in the dif-
ferent geo-political contexts.
at hypothesizing how different climate change
scenarios, involving both temperature and sea-
level increases, might affect different areas of the
world, and in which ways. The inputs for the
model are a set of futures projections involving
given temperature and sea level increases and spe-
cific geo-political areas influenced. The outputs
concern possible physical consequences, what
main sectors of society would be most affected,
subsequent societal consequences, and possible
Figure 8: Climate change conflict scenario model with worst case scenario
selected for Baltic Sea area.
Scenario
Global mean
temp change (C)
Sea level rise (cm)
Area influ-
enced (ex-
amples)
Conse-
quences for
area influ-
enced
Main sectors
influenced
Possible so-
cietal conse-
quences for
affected
area
Conflicts
that can be-
fall influ-
enced areas
Extreme
Case (A1F1)
Mean temp in-
crease: 6-8 C
Sea level rise:
70-80 cm
Baltic Sea
area Heavy drought Agriculture
Structural
changes in in-
ternational
competition
Civil war, inter-
nal conflicts
High temp
renewable
energy (B1)
Mean temp in-
crease: 5-6 C
Sea level rise:
50-60 cm
Middle
Europe
Desert
spreading Forestry
Increased re-
gional
divergence
Regional war/
conflicts over
land and wa-
ter areas
Mild rise re-
newable
energy (B2)
Mean temp in-
crease: 3-4 C
Sea level rise:
20-40 cm
Southern
Europe Flooding Energy
production
Mass immigra-
tion (“climate
refugees”)
Economic re-
source con-
flicts (includ-
ing fresh
water)
Kyoto +
Mean temp in-
crease: 1-2 C
Sea level rise:
10-20 cm
North Africa /
Sahel
Greatly in-
creased
precipitation
Transport
Mass emmi-
gration (“cli-
mate
refugees”)
Closed
borders
Tropical
Africa
Decreased wa-
ter supplies
Living envi-
ronment
(housing)
Brain drain Warlordism
Southeast
China
Increased heat
waves Fishery
Increased
spread of con-
tagions
(infection)
Increased in-
ternational
terrorism
Northeast
China
Warmer and
shorter
winters
Industrial
production
Increased
poverty Nothing
Arctic Region Tourism Extreme
protectionism
Russia Water supplies Financial
crises
USA Infrastructure “Failed state”
92 World Future Review Spring 2011
dimensional problems that include non-quanti-
fied dimensions, provides for a well-structured
discussion concerning such complex problems,
is well suited for working with groups of subject
matter specialists that represent different areas of
competence, produces an “audit trail” and docu-
mentation, and is well suited for developing sce-
nario and strategy laboratories.
As is the case with all modeling methods, the
output of a morphological analysis is no better than
the quality of its inputs. However, even here the mor-
4. Conclusions
General Morphological Analysis is based on
the fundamental scientific method of cycling be-
tween analysis and synthesis. For this reason, it
can be trusted as a useful, conceptual modeling
method for investigating problem complexes
which are not meaningfully quantifiable and
which cannot be treated by formal mathematical
methods and causal modeling.
Morphological Analysis, with dedicated
computer support systematically deals with multi-
Figure 9: Climate change conflict scenario model with worst case scenario
selected for Southern Europe.
Scenario
Global mean
temp change (C)
Sea level rise (cm)
Area influ-
enced (ex-
amples)
Conse-
quences for
area influ-
enced
Main sectors
influenced
Possible so-
cietal conse-
quences for
affected
area
Conflicts
that can be-
fall influ-
enced areas
Extreme
Case (A1F1)
Mean temp in-
crease: 6-8 C
Sea level rise:
70-80 cm
Baltic Sea
area Heavy drought Agriculture
Structural
changes in in-
ternational
competition
Civil war, inter-
nal conflicts
High temp
renewable
energy (B1)
Mean temp in-
crease: 5-6 C
Sea level rise:
50-60 cm
Middle
Europe
Desert
spreading Forestry
Increased re-
gional
divergence
Regional war/
conflicts over
land and wa-
ter areas
Mild rise re-
newable
energy (B2)
Mean temp in-
crease: 3-4 C
Sea level rise:
20-40 cm
Southern
Europe Flooding Energy
production
Mass immigra-
tion (“climate
refugees”)
Economic re-
source con-
flicts (includ-
ing fresh
water)
Kyoto +
Mean temp in-
crease: 1-2 C
Sea level rise:
10-20 cm
North Africa /
Sahel
Greatly in-
creased
precipitation
Transport
Mass emmi-
gration (“cli-
mate
refugees”)
Closed
borders
Tropical
Africa
Decreased wa-
ter supplies
Living envi-
ronment
(housing)
Brain drain Warlordism
Southeast
China
Increased heat
waves Fishery
Increased
spread of con-
tagions
(infection)
Increased in-
ternational
terrorism
Northeast
China
Warmer and
shorter
winters
Industrial
production
Increased
poverty Nothing
Arctic Region Tourism Extreme
protectionism
Russia Water supplies Financial
crises
USA Infrastructure “Failed state”
World Future Review Spring 2011 93
mission, Stockholm, December 2002. (Available for down-
load at: http://www.swemorph.com/downloads.html.)
Ritchey, T. (2004) “Strategic Decision Support using
Computerized Morphological Analysis.” Presented at the
9th International Command and Control Research and
Technology Symposium, Copenhagen, September 2004,
(Available for download at: http://www.swemorph.com/
downloads.html.)
Ritchey, T. (2005a) “Wicked Problems: Structuring
Social Messes with Morphological Analysis.” Adapted from
a lecture given at the Royal Institute of Technology in
Stockholm, 2004. (Available for download at: http://www.
swemorph.com/downloads.html.)
Ritchey, T. (2005b) “Futures Studies using Morpho-
logical Analysis.” Adapted from an article for the UN Uni-
versity Millennium Project Futures Research Methodology
series (Available for download at: http://www.swemorph.
com/downloads.html.)
Ritchey, T. (2006a) “Problem Structuring using
Computer-Aided Morphological Analysis.” Journal of the
Operational Research Society, Special Issue on Problem
Structuring Methods, (2006) 57, 792–801. (Available for
download in PDF for JORS subscribers at: http://www.
palgrave-journals.com/jors/journal/v57/n7/abs/2602177a.
html.)
Ritchey, T. (2006b) “Modeling Multi-Hazard Disaster
Reduction Strategies with Computer-Aided Morphologi-
cal Analysis.” Reprint from the Proceedings of the 3rd
International ISCRAM C onference, Newark, NJ, May
2006. (Available for download at: http://www.swemorph.
com/downloads.html.)
Ritchey, T. (In press): Wicked Problems/Social Messes:
Decision support Modelling with Morphological Analysis.
Hamburg: Springer.
SOU 2001:102 Resurs I retur (Resources in return),
2001. (Swedish Government Report on the development
of a Swedish EPR system.)
Zwicky, F. (1969) Discovery, Invention, Research
Through the Morphological Approach. Toronto: The Mac-
millan Company.
Zwicky, F., and A. Wilson (eds.) (1967) New Methods
of Thought and Procedure: Contributions to the Symposium
on Methodologies. Berlin: Springer.
phological approach has some advantages. It expressly
provides for a good deal of in-built “garbage detec-
tion,” since poorly defined parameters and incomplete
ranges of conditions are immediately revealed when
one begins the task of cross-consistency assessment.
These assessments simply cannot be made until the
morphological field is well defined and the working
group agrees on what these definitions mean.
References and Further Reading
Bailey, K. (1994) “Typologies and Taxonomies: An
Introduction to Classification Techniques.” Sage University
Papers. Sage Publications: Thousand Oaks.
Coyle, R. G., and G. R. McGlone (1995) “Projection
Scenarios for Southeast Asia and the Southwest Pacific.”
Futures 27(1), 65-79.
Coyle, R.G., and Y. C. Yong (1996) “A Scenario Pro-
jection for the South China Sea.” Futures 28 (3), 269-283.
Doty, D. H., & W. Glick (1994) “Typologies as a
Unique Form of Theory Building.” Academy of Manage-
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