Chapter 6 : Development of the Problem-Structuring Approach

Chapter 6 : Development of the Problem-Structuring Approach

6.1 Introduction Before embarking upon the detail of the problem-structuring approach, it is useful to

draw together several of the important issues noted thus far. In particular, these relate to

the general problem which emerge from the sustainability discourse, the characteristics of

complex problems, and some of the more significant approaches to dealing with problem

complexity.

In Chapter 2, it was argued that two distinct philosophical positions have emerged

relating to sustainability: one, referred to in this dissertation as “sustainability”, is the

monist view that humanity is a part of nature, with no special privileges or moral

standing above other species. The other, referred to here as the “sustainable

development” position, is the dualist, anthropocentric view that mankind has some

special moral privilege but that it is in our interests to look after other species and

ecosystems. The other key point to emerge from the consideration of sustainability is

that, as recent awareness of these issues emerged over the last 30 years or so, many have

been found to be global in nature, often with great size and immense complexity. The

problems of sustainability are often cross-cultural, encompass great diversity of beliefs

and values, and result widely differing worldviews. Modern institutions struggle to deal

with the problems of sustainability, creating a scepticism in the eyes of many stakeholders

as to the capacity of the “expert” to effectively resolve the issues. Hence, a starting point

for a problem-structuring approach should be to establish a philosophical framework,

which, at the minimum, allows representation of the broadest range of philosophical

approaches encountered. In addition, it should provide a forum where critique is

encouraged and facilitated. Ideally, this should not be prescriptive in terms of ontology,

epistemology, or axiology – rather it should provide a framework in which ontological,

epistemological, and axiological issues can be identified, discussed, and resolved.

In Chapter 3, a new taxonomy was proposed for describing complex problems and a new

class of problem, the Type 3 problem, was identified. Type 3 problems are generally

difficult to resolve because of conflicting beliefs and values, substantial differences in

worldviews, a willingness among stakeholders to take advantage of disparate power

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Chapter 6 – Development of the Problem-Structuring Approach…

situations in coercive environments, and a tendency among some stakeholders to disrupt

the decision-making process. This type of problem is often encountered in the context

of the sustainability discourse. Often, the apparent irreconcilable position of

stakeholders causes resolution of the issue to come to a standstill. For convenience, the

characteristics of the Type 3 problem, which were identified in Chapter 3, are

summarised here:

• despite what is often an immense mass of information, there is a sense that the

problem cannot be adequately described. It is not so much that there is

incomplete information, rather the difficulty is to organise the information so as

to give clarity to the problem definition;

• the problem is characterised by uncertainty, which derives both from the

indeterministic, systemic nature of the problem itself, and from the social

interaction of the domain of interests;

• there is lack of agreement over the relevance or importance of both qualitative

and quantitative parameters, resulting from conflicting objectives, or differences

in values and beliefs. The disparate worldviews of stakeholder groups give rise to

different interpretations of the nature of the problem and why it exists, so there

may be lack of clarity regarding the problem boundaries;

• the reductionist approach does not work. There are two main reasons for this.

First, because beliefs and values are at the heart of Type 3 problems, attempts at

reductionism, which is fundamentally an analytical approach, do not give notions

of beliefs, rights, and values adequate consideration in representation of the

problem information. And, in its simple application, the reductionist approach

does not recognise the interrelationship between problem elements. Type 3

problems generally have highly complex interrelationships between various

aspects of the problem, some of which are difficult to even identify, let alone

resolve – they are often better thought of as “systems”. A symptom of this

phenomenon is that what appears to be a rational determination of a solution to

one part of the problem turns out to be nothing more than a manifestation of

another part;

• unlike the complex problems confronted by science, where the goal is to

understand and “to know”, resolution of Type 3 problems is focused entirely on

delivering a good outcome, that is, a practical result, not merely the advancement

of understanding and knowledge;

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• related to the preceding point, solutions will generally be judged according to

whether they are good or bad, rather than whether they are true or false;

• Type 3 problems are often unique. There may be similar situations which can

inform the decision-maker but there are usually differences, which are substantive

enough to preclude the application of pre-existing solutions. Often, there is no

clear test for the soundness of potential solutions and problem complexity

prevents modelling of consequences. In addition, actions taken to resolve

aspects of the problem often have unexpected consequences;

• there are often substantial constraints limiting time available for analysis. Thus

judgement is required to determine when to decide to stop analysis and make a

decision;

• there is limited or no scope for trial-and-error: solutions are usually so large and

complex in themselves that they need to be made to work. For example, once a

dam or a mine is built, it is not easily moved!

In addition to the need for a robust, philosophical framework, noted above, there were

three important conclusions that emerged from this consideration of the characteristics

of Type 3 problems. First, the problem situation is usually similar to some form of

complex system, so a “systems” approach is more likely to be effective than the

traditional reductionist, engineering approach. Second, problem complexity is so great

that, in many circumstances, it will be beyond the cognitive capacity of the human mind

to conceive of it in its entirety. A problem-structuring approach, which facilitates the

organisation of the problem information in such a way that it is readily received by

human cognitive processes, would be expected to result in more successful engagement

by the domain of interests. And third, Type 3 problems are qualitatively different to

problems of Types 1 and 2. The complexity of Type 3 problems is largely due to

conflicts in beliefs, values, interests, desires, worldviews, power relationships etc. In

addition to traditional analytical problem-solving techniques, critical theory, ethics, and

reason are required to come to terms with this type of problem. These are the important

issues which will be considered as the problem-structuring approach is developed in this

chapter.

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6.2 Problem-structuring approaches – background Problem-structuring, in its broadest sense, is engagement with the problem so as to seek

a greater understanding of the problem situation and to determine a way forward in its

resolution. According to Rosenhead and Mingers (2001), formalisation of problem-

structuring as a sub-discipline of operational research came about in response to the

recognition that traditional operational research approaches to so-called “wicked”

problems (the precursor to the Type 3 problem explicated here) were ineffectual. This

led to the development of a variety of approaches, which attempted to improve our

understanding of ill-structured problems. Rosenhead and Mingers further note that the

traditional operational research paradigm has a number of deficiencies: it focuses

overwhelmingly on the analysis of data; it seeks to reduce the problem to a single

objective and to optimise a solution around that objective, thus trading off multiple

objectives; and it assumes a hierarchical decision-making domain which “scientises” and

depoliticises the decision-making process.

The problem-structuring techniques developed in response to these objections, such as

Eden’s and Ackerman’s Strategic Options Development and Analysis (SODA) (Eden

(1989), Eden and Ackermann (2004)), Checkland’s Soft Systems Methodology (SSM)

(Checkland (1985)), Friend’s and Hickling’s Strategic Choice (Friend (1989)), seek to be

non-optimising, attempt to represent problems on various dimensions in order to

recognise the influence of people on the problem situation. They include consideration

of uncertainty and they attempt to integrate hard and soft information, through the

incorporation of social judgements.

Rosenhead (1996) argues that this more recent problem-structuring paradigm identifies

an alternative means to formalise decision analysis techniques and hierarchical processes

to represent relationships between problem system constituents. However, the position

taken here is that problem-structuring is an important step by which problem information is

examined and criticised in order apply established analytical techniques more effectively. That is to say,

combining the critical aspects of this type of problem-structuring approach with the more

orthodox analytical approaches (such as MCDA), which are sometimes seen as problem-

structuring approaches in themselves (see Chapter 8 section 8.4.5) can move beyond this

and significantly extend the understanding of the problem. Hence, the position taken in

this dissertation is that problem-structuring is an important step in coming to terms with

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and understanding Type 3 problems. Thus, problem-structuring can be a valuable means

to critically analyse problem information, using this to inform development of objectives

and values hierarchies, for use in formalised, analytical approaches.

One branch of the decision sciences which has given attention to the challenge of

structuring these highly complex problems is multiple criteria decision analysis (MCDA)

(Belton and Stewart (2002a)). (The field is also referred to as multiple criteria decision-

making (MCDM), or sometimes just decision analysis). The common features of this

family of approaches are that they recognise various sources of uncertainty (from

incomplete information, linguistic imprecision, natural variability, differences in

preferences and values and so on (Morgan and Henrion (1990a), Morgan and Henrion

(1990b)). Also, there is acknowledgement of the existence of multiple, conflicting

objectives which require trade-offs; and that, generally, there are many stakeholders, all of

whom may formulate the problem somewhat differently in consideration of objectives

and options available. Furthermore, these methods generally attempt to recognise that

trade-offs and value judgements are personal; that risks, costs, and benefits may not be

shared equally by all stakeholders; and that this may lead to substantial disagreement and

disharmony within the domain of interests. The principal aim of all MCDA techniques is

to attempt to establish a rational process whereby the problem can be attacked. In so

doing, multiple, conflicting criteria can be taken into account and a process can be

established, which is transparent and as simple as the complexity of the situation will

allow (von Winterfeldt and Edwards (1986), Belton and Stewart (2002b)).

Although there are different ways of representing the process of problem resolution (for

example, see Morgan and Henrion (1990b) p42, Beinat (1997) p6, Belton and Stewart

(2002a) p6), practices common to MCDM techniques have five fundamental steps.

These are summarised in Table 6.1 (overleaf).

It is the second of these steps, problem-structuring, that is of particular interest here, because

of its importance in interpreting the complex issues of the Type 3 problem in such a way

that structured MCDM techniques can be effectively utilised. A further reason for

focusing on problem-structuring is that the philosophical framework which underlies the

MCDM approach to problem resolution, generally is not explicit82 (Chapter 3, section

82 The work of Ulrich (1983), and Midgley (2000) are an exception to this.

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3.7). In an attempt to determine what the underlying philosophical principles might be,

typically, focus has been on retrospective consideration of issues, inferring the underlying

philosophical and cognitive assumptions which underpin the approach, sometimes

unconsciously. There appears to have been little done by way of developing problem-

structuring approaches which start with a fundamental philosophical framework and then

attempt to take into account the cognitive limitations of the human mind and the

heuristics which people naturally use to discover information about the problem

situation, to inform their judgement, and to make decisions in uncertainty. As noted

above, one of the main aims of MCDM techniques is to establish an open, transparent

process for problem resolution, hence, it is important that the underlying philosophical

principles are made clear to the participants.

STEP PURPOSE 1 Identification of the problem and

associated issues.

Recognition of the problem situation, identification of the domain of interests and the issues and challenges which need to be addressed for the problem to be resolved.

2 Problem-structuring.

Identification of the stakeholders, beliefs, values, system and subsystem boundaries. Qualitative consideration of the characteristics of the problem system, identifying and clearly stating key issues, uncertainties and constraints which influence problem resolution.

3 Development of a suitable model to provide adequate representation of the problem situation.

Quantitative representation of the problem situation, values, and preferences. Identification of quantitative attributes, and identification of options for consideration.

4 Utilisation of the model to illuminate thinking, develop and evaluate options, and negotiate potential ways forward.

Use model output to stimulate thinking regarding the consequences of particular options, in particular the critique of intuitive approaches to problem resolution and to build a comprehensive, robust understanding of the problem situation.

5 Development and implementation of an action plan.

Develop a robust way forward, together with insights and results of the analysis documented and incorporated into a plan of action which takes into account model assumptions and uncertainties.

Table 6.1 – Problem solution approach using multi-criteria decision analysis

Thus, there are two aims in developing the problem-structuring approach in this

dissertation. First, the approach developed here is put together from first principles.

From the philosophical principles of sustainable engineering practice proposed in

Chapter 4, a problem-structuring approach is developed which aligns with established theory as to how

human cognitive processes are thought to function and which reflects the dynamic, systems nature of the


Type 3 problem. The assertion made here is that, by clearly stating the practical

philosophical principles of the approach and aligning the approach with human cognitive

processes, there is a much greater opportunity for engagement across the breadth and

diversity of belief, values, and cognitive capacity represented within the domain of

interests. This will result in clearer insight into the options available to ultimately resolve

the problem situation. Second, is to propose a means by which a critical discourse can

take place around problem information, so as to facilitate the construction of a values

hierarchy (sometimes called an objectives hierarchy), which, itself, is an important step in

building an MCDM model.

The meaning of the term “value” in the decision-making context is most important in the

consideration of Type 3 problems. As discussed in Chapter 2 (section 2.4.2.2), there is

an important distinction between intrinsic value, the notion that something is of value in

and of itself, and extrinsic value, the concept that value is derived purely instrumentally

(Attfield (1987)). Furthermore, the ranking of the two types of intrinsic value (the object

kind and the moral kind) are fundamentally different problems: the ranking of objective

intrinsic values requires axiological judgements and the ranking of intrinsic values of moral

standing requires moral judgements.

One of the challenges taken up by MCDM is to identify ways in which quantitative

representations can be constructed as a proxy for the axiological and moral judgements,

which decision-makers must reach in identifying a solution to the type of problem which

includes issues of one or other form of intrinsic value. Determining extrinsic value of an

object or thing requires knowledge of its instrumental value to some other object or

thing. The judgements relating to extrinsic value can be ranked qualitatively (for

example, a eucalypt tree has a greater extrinsic value to a termite than a pine tree) and

quantitatively (for example, the price of teak sawlogs is greater than the price of eucalypt

sawlogs). The Type 3 problems of the sustainability discourse will often have issues of

intrinsic and extrinsic value entangled. Hence, in order to identify potential solutions to

these problems, the problem-solving approach must attempt to not only distinguish

between methods of quantitative valuation (direct, indirect, or proxy), which focus largely

on extrinsic value but must also identify the axiological and moral judgements required to

deal with issues of intrinsic value. Often, MCDM techniques do not clearly distinguish

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between intrinsic and extrinsic value and, hence, do not adequately present a decision-

maker a rich enough representation of the decision-making challenge.

The problem-structuring technique developed here, because of its critical approach, helps

distinguish between intrinsic values, extrinsic values, and preferences through the discourse which emerges

from undertaking the problem-structuring exercise itself. This approach does not result in a values

or objectives hierarchy directly but attempts to make clear issues of intrinsic value,

extrinsic value, and preference, so that when the values or objectives hierarchy is

constructed, these issues will be properly dealt with.

In Chapter 4, it was argued that the engineering discipline, although progressing in the

technological sense, is locked in a dated philosophical paradigm. Engineering is still

largely positivist and does not reflect the substantial development of the philosophy of

science of the last 70 years. Furthermore, it was argued that engineering might be more

successful in its attempts to resolve the highly complex, Type 3 problems of the

sustainability discourse if it were to take a more critical approach, based on clearly stated

philosophical principles. The problem-structuring approach developed here uses these

principles as its philosophical foundation, in particular, arguing that in the case of

problems of the sustainability discourse, the engineer cannot adopt a position of

detached objectivity. Rather, it must be recognised that the characteristics of Type 3

problems require that the engineer must be engaged as part of the system; as a “system

component”. Information is then structured using principles derived from general

systems theory, as discussed in Chapter 3, and cognitive theory, discussed in Chapter 5.

6.3 Development of the problem-structuring approach 6.3.1 Overview The approach presented here is developed on three levels. The first of these is a

philosophical framework which allows consideration of a wide range of philosophical

beliefs and ideas. The focus is on ontology and epistemology in order to provide a

forum for axiological, semantic, and methodological issues to be explored and

considered. No distinctly philosophical defence of these positions is presented, rather

they are matters of belief and premise – generally they cannot be proved or refuted; they

are simply presented as the starting point from which the discourse can unfold.

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The second level contains a set of observations and theoretical propositions in relation to

Type 3 complex problems in two key areas. The first of these relates to the “systems”

nature that appears to be present in many of the situations encountered. And the second

relates to the nature and limitations of human cognition, and the use of a descriptive

theory of the way in which humans form judgements and make decisions under

uncertainty. This forms the basis for representing the problem in such a way as to

simplify the issues but not to discard the richness of information which is fundamental to

the description of the problem. Of key importance here is to be able to represent the

problem information without cognitive overload and to be able to quickly retrieve

information to explore new and different relationships. This requires considerable

flexibility to accommodate a wide range of cognitive abilities and preferences regarding

the way in which the human mind represents, considers, stores and accesses information.

The third level is the problem-structuring approach itself, in particular, the development

of some innovative tools and devices, with which to organise problem information in a

way which is consistent with the philosophical approach of the first level and the system

structure and cognitive constraints of the second.

There are a number of aspects of this approach which need to be noted at the outset. Of

particular importance is the underlying ontology and epistemology which encourage

critique. This will be described in detail shortly. Second, the approach to human

cognition used here is largely based on two important theories; first is Kelly’s theory of

personal constructs; and second is Beach and Connolly’s image theory. Such approaches

have been referred as naturalistic (or sometimes “second-generation behavioural”)

approaches to cognition, in that they attempt to describe the way in which humans

actually think and recognise that human cognition functions under significant constraints

as it attempts to come to terms with an immensely complex environment. Naturalistic

theories have not had the same impact as the two waves of behavioural cognitive

psychology (described in Chapter 5), which have given rise to the field of behavioural

economics, for example. However, the naturalistic theories, in particular, image theory,

have had a subtle but significant influence in both business management and public

administration. Indeed, many so-called “strategic management approaches” are entirely

consistent with the image theory paradigm. The reason that both personal constructs

theory and image theory have been used here as cornerstones of the cognitive framework

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for the problem-structuring approach is simply that it was considered desirable to have a

cognitive framework which is descriptive of the way in which people actually think. This

was considered preferable to normative cognitive approaches which attempt to explain

the differences between observed behaviour and expected so-called “rational behaviour”.

The point is simply that where the intention is to structure a problem in such a way as to

be able to engage as wide a range of interests as possible, it would seem that a good

approach would be to frame the approach around the way in which people naturally tend

to think, form judgements and make decisions.

And third, it is important to note that this is a problem-structuring approach and as such the

intent is to organise aspects of the problem (information, issues, beliefs, values, opinions,

questions, etc) across a range of dimensions, so that stakeholders may be more readily

engaged and can achieve greater commitment to problem resolution. This approach is

not intended to be or to become a problem-solving methodology – it is not merely a new set of

problem-solving tools and techniques. Rather, it should be seen as the first step in

coming to terms with the Type 3 problem, seeking to understand the problem better and

to illuminate problem information, so that the most appropriate analytical tools, such as

the family of multi-criteria decision analysis approaches, might then be applied with

greater insight and wisdom.

Albert Einstein (1954) observed that theories can be derived in two ways: constructive or

principled. Constructive theories are those which are derived from repeated observation

of phenomena allowing intuitive derivation of a framework of laws which explains the

phenomena and enables prediction. Principled theories are those which start from a

particular set of premises and which are logically derived to explain and predict observed

phenomena. The problem-structuring approach presented here has been derived using

both these avenues. The philosophical foundations are principle-derived; the cognitive

psychology and approach itself are constructive.

6.3.2 Level 1 – Philosophical framework In Chapter 4, six critical, practical philosophical principles were developed for

engagement in the highly complex Type 3 problem found in the sustainability discourse.

These are repeated here for ease of reference:

P1. There is a physical world which consists of mind-independent things;

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P2. There is a mental or psychological world which is an emergent, human

phenomenon, with which the human mind represents its perceptions of the

physical world;

P3. In a physical sense, there is an infinitely complex parade of events and

phenomena located in space and time – this is “the way the world is”;

P4. The world is fundamentally indeterministic in nature and its individual parts can

only be understood in relation to the whole, that is, in the context of the

“system”;

P5. Although it is beyond the capacity of the human mind to understand completely

and to describe adequately the way the world is, the human mind forms linguistic

and other representations based on perception and thought which attempt to

arrive at some “true” (but incomplete) understanding of the way the world is;

P6. “Truth”, a human phenomenon, may be considered from two perspectives. One

is an objective “fact of the matter” which relates to physical phenomena and

objective representations of the real world and these representations can be

determined to be either true or false. The other is a subjective representation of

socially-determined phenomena and the truth or falsity of these representations is

determined linguistically, according to generally accepted and verified beliefs and

values. In both cases, the appropriate position to take is to acknowledge them as

being true (or false) subject to the ever-present possibility of error and the

context in which their truth (or falsity) is determined. Both correspondence and

coherence approaches to truth each have their place but only as criteria for

determining truth.

6.3.2.1 Critique of established engineering practice in the context of these principles In Chapter 4 it was argued that to date, engineering practice has been largely

instrumentalist, in that it uses science as an instrument to model the real world and to

predict its behaviour. In addition, the scientific paradigm which most engineering

follows is positivist and mechanistic. Hence, the prevailing engineering approach to

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solving problems has been largely reductionist in its nature, aiming to break problems

down into their constituent parts, identifying solutions to these parts and then

synthesising a solution to the whole problem, by integrating the solutions to the parts. In

the last 50 years or so, systems analysis techniques have been utilised successfully, but

nonetheless, these are still based largely on the positivist, mechanistic, instrumentalist

worldview.

If this sketch of modern engineering practice is considered in relation to the six

principles noted above, it is clear that the strongest influence is principle P1: engineering

practice generally focuses on identifying quantitative model, which represent real world

things and phenomena. The complexity referred to in P5 is represented in the

uncertainty of quantitative modelling and the constraints placed on utilisation of model

output (for example, noting that models should only be used in certain circumstances or

applying safety factors to take into account differences between model behaviour and

observed real-world behaviour). Consideration of principles P2 and P5 suggests that

modern engineering practice typically gives little acknowledgement or credence to beliefs

and values which are consistent with the post-normal scientific paradigm. The concept

of “system” embodied in P4, whilst acknowledged in approaches such as systems

analysis, is compromised in the positivist concept of the independent, detached observer.

The extensive reliance of engineering practice on the simplifying assumptions contained

within reductionist analysis further conflicts with this principle. Criteria for determining

truth (P6) are largely correspondence-theoretical, typically structuring criteria for truth

according to whether or not model output corresponds to the observed behaviour of the

real world phenomena that it represents. Coherence-based approaches to truth are

mainly limited to establishing the coherence of quantitative models in relation to current

scientific theory and generally do not take into account issues of moral interests, rights,

beliefs, and values.

A conceptual representation of this is shown in Figure 6.1. That is, modern engineering

practice uses a problem-structuring approach with principle P1 at its centre, and with the

other philosophical principles being peripheral at best and having limited influence on

problem-structure.

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P1

P5

P2

P3

P6

P4

Figure 6.1 – Conceptual representation of traditional philosophical paradigm of engineering practice.

P1

P5

P2

P3

P6

P4

P1

P5

P2

P3

P6

P4

Figure 6.1 – Conceptual representation of traditional philosophical paradigm of engineering practice.

The manifestation of this paradigm in problem-structuring is a heavy technological

emphasis, with the engineer disconnected from most aspects of the problem, other than

through a determination to resolve technological issues. This often leads to seeing

aspects of the problem outside this representation as being interference and obstruction,

rather than parts of the problem which need to be taken into account. There are three

serious, fundamental deficiencies with his approach. First, the positivist, mechanistic

model which derives from the reductionist approach is inconsistent with the systems

approach required by P4. Hence, engineers often do not recognise their significant

influence in engagement with the full domain of interests (and often this influence

evokes a hostile response from other stakeholders.). Second, it does not give due

consideration to the social dimensions of the problem, which emerge when the domain

of interests’ widely differing beliefs, values systems, and interests are taken into account.

And third, the issues to which coherence-based approaches to the determination of truth

are most appropriate are often seen as being barriers external to the problem, rather than

part of it. Hence, often these are marginalised or excluded from consideration

altogether.

6.3.3 A new approach to structuring type 3 problems An alternative way to utilise these principles is to recognise their “connectedness” and

interdependency, as shown simply in Figure 6.2 (overleaf).

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P5

P4

P2P3

P1

P6

Figure 6.2 – Conceptual representation of the proposed philosophical paradigm of engineering practice.

P5

P4

P2P3

P1

P6

P5

P4

P2P3

P1

P6

Figure 6.2 – Conceptual representation of the proposed philosophical paradigm of engineering practice.

Considering the principles arranged in this way enables a fundamentally different

approach to structuring problems to be devised. Representation of the physical world is

no longer at the centre of the problem-structure. Rather, all principles are given equal

emphasis. A problem-structure which arises from this thinking might be described in

these terms. Of key importance is the “system” nature of the world, that is, the problem

situation is represented as an open subsystem. The psychological influences in creating

the problem-structure are also recognised as being key determinants of the approach and,

ultimately, the methodology by which a potential problem solution is identified. This

approach also recognises the importance of locating events both in space and in time.

The additional emphasis on the time dimension means that historical perspectives can be

utilised to contextualise the current problem-structure and to inform the domain of

interests on different perspectives of the problem. The complex nature of the problem

and the location of the problem within the holistic system suggest that a systems

approach to both problem-structuring and problem solution might be fruitful.

The recognition that problem complexity can never be completely and adequately

understood, due to human cognitive limitations suggests that the characteristics of

human cognition should be taken into consideration, as part of the problem-structuring

methodology. Using both correspondence and coherence criteria for the determination

of truth, both in structuring the problem and identifying possible courses towards

solution, significantly increases the potential for engagement with the domain of

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interests, because many worldviews can be represented and incorporated into the

problem-structure. Recognition of the ever-present possibility of error and that attempts

to arrive at a complete understanding of the problem can never be completely successful

due to the problem complexity and system indeterminacy suggest that a precautionary

approach should be adopted. This is particularly important in situations where potential

problems solutions may have major, intractable impact. Importantly, the engineer is no

longer seen to be an independent, detached observer but is engaged in the problem itself,

as a system element: the engineer is now a part of the problem.

In summary, such an approach as this places emphasis on two specific issues. First, is

the importance of representing the problem as a system, composed of system elements

and subsystems, contained within a holistic, systemic universe. And second, is the need

to take into account the functioning of human cognition. Of particular importance are the

way in which representations of the physical world are thought to be formed; the means

by which complexity is dealt with and judgements are formed (particularly in relation to

future events and uncertainty); and the way in which problems are contextualised in

relation to the spatial and temporal dimensions of the real world. This leads to the

second level of the problem-structuring approach (which will be developed in the next

section), namely utilising systems theory and a systems approach as the functional

structure for the representation of Type 3 problems. In addition, theoretical approaches

to human cognition, judgement, and decision-making are utilised to better engage the

domain of interests, thus enabling them to more clearly contextualise the problem within

their spatial and temporal frames of reference.

6.3.4 Level 2 – Systems and cognitive framework for structuring type 3 problems

As note above, at the second level, there are two theoretical building blocks used to

develop the problem-structuring approach. System theory is used as the paradigm for

describing and engaging with the problem itself. And a framework, built on

psychological theory, is developed to relate to the way in which human cognition

functions, in particular, regarding judgement, choice, and decision-making in uncertainty.

Two important theories are Kelly’s theory of personal constructs (Chapter 5, section

5.3.2) and Beach and Connolly’s image theory (Chapter 5, section 5.3.4). In order to

represent the system itself and the relationships between system elements and

subsystems, and to contextualise problem information in the three spatial dimensions,

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cognitive maps are used. Then, to represent the problem temporally, and to facilitate

identification of uncertainty, inconsistencies, and gaps in knowledge, storytelling,

scenario analysis, and narrative (Chapter 5, sections 5.3.5 and 5.3.6) are utilised.

6.3.4.1 System theory and the systems approach As noted in Chapter 3, many complex problems can be considered to be complex social

systems. von Bertalanffy (1950) was highly influential in the development of a systems

approach, with his general system theory. He noted that general system theory is not

simply a system of differential equations used as approximations to describe an

ontologically mechanistic world, rather it represents a means to attack a newly identified

class of problem, not found in exact science. Later, von Bertalanffy (1972) proposed a

distinction between what he referred to as “real systems” (those which exist independent

of the observer) and “conceptual systems” (products of human thought such as

mathematics, music, and logic). Together with his concept of “abstracted systems”, by

which the system concept corresponds with reality, von Bertalanffy developed what he

referred to as a “systems ontology” and a “systems epistemology”, differing significantly

from the logical positivist approach83. Von Bertalanffy also noted the potential of

adopting a systems approach to problems relating to values, referring to the emergence

of “two cultures” of science and humanities, previously observed by Snow (1959).

Utilising general system theory as the paradigm for structuring Type 3 complex problems

provides the means to move the paradigm of engineering practice away from the logical positivist approach

to the critical approach, which has evolved in both the natural and social sciences since the

1930s. Such a step is consistent with the philosophical principles established in Level 1.

Operational research has seen a number of systems approaches in dealing with problem

complexity, particularly those relating to complex social problems. Multi-methodology

approaches, such as “total systems intervention” or “system of system methodologies”,

(Flood and Jackson (1991a), Flood and Jackson (1991b)) are representative of

approaches which aimed to bring a range of interventions, selecting those which appear

to be most effective for different parts of the problem. These have been useful but have

also been criticised as lacking sufficient epistemological depth and uncompromising

rigour in their pragmatic acceptance of particular methodological interventions (see

Mingers (1992), Brocklesby and Cummings (1996), Ulrich (2001)). Other ways such as

83 These three system types are coherent with Popper’s three worlds.

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integrating “hard” and “soft” systems analysis techniques have also been attempted.

However, these appear to suffer from the same lack of philosophical depth and would be

expected to be only partly useful, because they do not rigorously provide the means to

take into account the issues of moral accountability, values, beliefs, and rights of those

with moral interests. Thus, they lack the means to make the practitioner’s value

judgements clear in determining system boundaries.

The challenge in many of the complex problems of the sustainability discourse is that any

model of the system needs to represent not only its physical characteristics, but also

issues of morals, ethics, values, beliefs and the interests of both human and non-human

constituents. Generally, this requires moving beyond the simplistic but widely embraced

“triple bottom-line” approach to which sustainable development resorts in order to

accommodate these issues. Rather, the problems of the sustainability discourse present

unique challenges, which can best be approached by integrating “hard”, “soft”, social,

and natural systems methodologies, recognising that the traditional analytical and

strategic methodologies cannot be completely satisfactory, because they do not

adequately take into account the issues of moral accountability, values, and so on, as

noted above. Ulrich developed a critical systems methodology (Ulrich (2001), Ulrich

(2003)), which proposes the conduct of a critical, rational, argumentative discourse,

recognising the importance of a civil society, in which many voices can be heard and the

validity of their claims tested. Ulrich argues for an emancipatory orientation, aimed at

removing coercion and power imbalances and a reflective professional practice which has

an open mind towards new approaches and complementary techniques. In addition, he

stresses the importance of establishing system boundaries and of the critique of the

judgements as to where these boundaries lie.

However, none of these approaches explores the dynamic nature of systems and their

response to disturbances. An established way of modelling and characterising systems

analytically (for example, in engineering practice) is to develop a mathematical model of

the system, apply a disturbance to both the model and to the system and the to compare

the response of the model with the observed response of the real-world system. If both

responses are the same, the model is accepted as a satisfactory representation of the real

system, at least within the range of assumptions under which the model is built and

tested. A key assertion here is that qualitative exploration of the response of the Type 3

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problem to a hypothetical disturbance can be a valuable means to gain insights to the

problem and to its systemic nature. Such insights can then be used to further inform the

way in which the problem information might be structured.

Hence, this approach is to structure the problem, using the system metaphor, and then to

explore qualitatively how such a system might respond to a hypothetical disturbance

across a range of problem dimensions, which are representative of the nature of the

problem. In particular, emphasis is placed on qualitative and intuitive exploration of the

problem, with the intention being that the approach should be enquiring, discursive, and

critical, with emphasis on values, beliefs, and issues of moral standing and accountability,

because these important considerations are generally discarded in the traditional,

reductionist engineering approach. The purpose is to encourage the qualitative and

intuitive engagement of human cognitive processes by structuring the problem

information in such a way that it can be readily accessed as needed for future analysis.

Also, importantly, the aim is to facilitate understanding and thereby to encourage the

inclusion of as wide a representation of the domain of interests as possible.

Once the problem is structured in this way, it is anticipated that rigorous analytical,

quantitative methodologies can be more productively employed, ultimately to identify a

“solution space” for the problem. In many problem situations, it is anticipated that these

analyses can be applied iteratively, thus gaining further insight into the nature of the

problem. In order to consider the response of the system to the hypothetical

disturbance, assumptions need to be framed regarding system boundaries. That is not to

say that the system metaphor used here is one of a closed system, rather it is a bounded,

open system. The process of boundary critique, identified by Ulrich and Midgley, is

important in order to determine what interests are to be “swept in”, or included in

consideration of the problem.

Drawing upon the above points, a set of systems principles are proposed upon which the

problem-structuring approach is based:

S1. A system consists of complex, interacting elements;

S2. In many systems, there is a hierarchy of order, which includes subsystems;

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S3. The system responds as a whole, the changes to individual elements (or

subsystems) being dependent on all the others;

S4. A small change in one part of the system may cause significant change to the

state of the total system;

S5. Dynamic mechanisms exist within the system, which determine the way in which

it responds to disturbances;

Furthermore, in the case of the social systems found in Type 3 problems, these additional

principles apply:

S6. System and subsystem boundaries can be identified through rigorous critique;

S7. An emancipatory orientation should be used to remove the effects of coercion

and power imbalances;

S8. Insight into dynamic system response can be gained through the conduct of a

critical, rational, argumentative discourse.

This outlines the systems paradigm upon which the problem-structuring approach is

based. The next question to consider is the way in which representations of the problem

can be formed, so that problem complexity can be dealt with adequately within the

limitations of human cognition.

The approach taken to this challenge is to model the system according to, what are

understood to be, the important human cognitive processes used in forming judgements,

making choices, and reaching decisions in uncertainty. One of the significant challenges

in structuring Type 3 problems in a way which moves beyond the traditional, reductionist

engineering approach, is to organise problem information in such a way that it can be

dealt with within the constraints of human cognition. At the same time, the approach

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must protect against loss of important information and should work towards a greater

richness in the description of the problem.

6.3.4.2 The application of cognitive theory The issues of human cognitive psychology, which are drawn upon to develop the

approach, were identified in Chapter 5 (sections 5.3.2 to 5.3.6) and are repeated again

here for convenience. They are:

C1. Humans form mental representations of things and phenomena which they

encounter in World One. These appear to consist of some form of dynamic

system of depictions, non-visual patterns, and linguistic representations, which

can be stored, recalled, processed, correlated, and evaluated. These

representations, or “images”, form the substance of our World Two knowings

and are used to construct World Three propositional knowledge;

C2. The human mind can only retain about five or six units of concentration in short-

term memory at any one time, but has a very great capacity to retain information

in long-term memory and recall this to short-term memory as required;

C3. Fundamental to the way in which humans construct their conceptions of reality is

the “dichotomous construct”, in which three representations are needed: two of

these represent opposing poles of a similarity, against which the third

representation is contrasted. People then make use of a “scalar” to represent the

magnitude of the contrast;

C4. When confronted with situations where there is considerable uncertainty, humans

form judgements, make choices, and reach decisions using processes, which can

be adequately described using the “image theory” model. Of particular

importance here are the three types of image utilised by the decision-maker. The

“value image” helps the decision-maker frame the problem in the context of their

beliefs and values and what they believe is right. The “trajectory image” sets an

agenda or set of goals. And the “strategic image” is an image of plans to guide

behaviour and to create impressions of what the future will be like. Image theory

is well suited to problem situations which have strong intuitive, axiological issues

because of the way in which values are embedded in the decision-making process

itself through, the representations contained in the value image;

C5. Humans attempt to relate spatially to things and phenomena in the real world,

using various forms of cognitive map. The schematic structures of cognitive

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maps provide a means to combine both intuitive and analytical information and

thought, depicting these in a single, physical, visual representation. Such maps

become holistic representations of the entire system under consideration. They

need not be specifically isomorphic, but represent an important mechanism by

which information is contextualised and structured. This is to facilitate the

reaching of decisions, both for short-term, instantaneous decision-making and

long-term, contemplative deliberation;

C6. Whilst cognitive maps provide the means for humans to spatially orientate

problem information, there appears to be an additional cognitive process to

contextualise problem information in the temporal dimension. The use of

narrative is an important cognitive and social device to integrate temporal and

spatial representations of problem information. The use of narrative is also

thought to be an important cognitive device for reconciling apparent

inconsistencies and deficiencies in knowledge regarding the problem;

C7. Taken together, the cognitive map and the narrative allow physical representation

of cognitive processes in all four real-world dimensions and provide a means to

reconcile inconsistencies and identify gaps in our knowledge. Thus we come to

understand better the various aspects of problem complexity.

6.3.4.3 Integration of the systems approach and cognitive theory Using concepts drawn from both systems and cognitive theory, the problem-structuring

approach developed here qualitatively represents the Type 3 problem as a bounded, open

system. To facilitate analysis of the response of the system to disturbances, system

boundaries are proposed and subjected to critique, through engagement of a wide

representation from the domain of interests.

6.3.4.3.1 Identifying and structuring problem information

There are two major challenges in organising information relating to Type 3 problems.

First is that the problems are of such complexity, that a large amount of information is

required to characterise them. And second, is that there is usually an overwhelming

amount of information available regarding the problem, which will be considered to be

of differing degrees of importance, depending on the perspective of the various members

of the domain of interests. Human cognitive limitations make it difficult for individuals

to come to terms with both the breadth and depth of problem information. The solution

proposed here to this issue is to identify ways in which various problem dimensions may

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be identified, and then to categorise and sort information according to whichever

dimension it is most closely associated. One way to achieve this is to identify aspects of

the problem which exhibit particular similarities (Verma (1998)), representing these as

problem dimensions84. In addition, elements of problem information are examined to

determine what relationships might exit between them, both within and between

problem dimensions. In some cases, these relationships will be relatively simple but in

others, subsystems within the problem system boundary must be identified and

represented.

As information is identified which is anticipated to be influential on system behaviour, it

may be mapped, so as to represent important relationships across the various problem

dimensions. The way in which this mapping takes place will be described in the detail of

the problem-structuring devices developed in Level 3. The important point to note here

is that the mapping process should align with the cognitive processes which take place to

identify and to evaluate problem information. Three elements of cognitive psychology

are important in preparing these cognitive maps. First, information must be organised in

representations which come most easily to those involved in the mapping process. That

is, the representations should be depictions, linguistic descriptions, non-visual patterns,

or a combination of all of these – the determinant should be the ease with which these

are identified and recorded for future use. Second, wherever possible, problem

information should be represented in groups of five to eight units of concentration, so

that the part of the problem under consideration can be focused on by participants as a

single, integrated piece of information. And third, by exploring the relationships between

system elements (as grouped into their units of concentration of five to eight pieces), the

richness of problem information can be identified and recorded, using dichotomous

constructs, as suggested by personal construct theory.

6.3.4.3.2 Application of system theory

Once an initial characterisation of the Type 3 problem has been formulated and the

relationships between important aspect of the problem have been identified, an initial

image of the system can be described. This process is as follows:

84 Verma notes that similarities are fundamental to the way in which people understand things. There are

three types of similarity: structural similarity; functional similarity; and teleological similarity. An example might demonstrate the distinction. Sugar and saccharin are both sweet, so they are functionally similar. However, they are different chemical compounds, so they are structurally dissimilar. They are also teleologically dissimilar because they were not intended to be sweet, they just happen to be so.

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i. Describing the initial system state – This is referred to as the “As-Is” system state

– that is, an initial description of the system, which identifies the key relationships and

the dynamics of the system’s elements and its subsystems. There is an implication

that the “As-Is” system state is in stable equilibrium, however, this need not be the

case. As part of this initial system characterisation, an initial description of the various

“value images” represented in the domain of interests can be described. This is a

comprehensive description of the moral and ethical issues contained in the problem

description, contextualised in terms of the initial system model. This is an important

step in identifying the moral issues represented in the domain of interests and is

essential in order to undertake a substantive boundary critique.

An important characteristic of systems, identified by von Bertalanffy, is the nature of the

system’s response to some disturbance. The system responds as a whole, determined by

the interrelationships both within and between subsystems and system elements. Such

responses can be exponential. Hence, the next step in structuring the problem is to

consider what qualitative response the system might exhibit to some hypothetical

disturbance.

ii. Defining a plausible, hypothetical system disturbance – Such a hypothetical

disturbance is prepared using a similar approach to the characterisation of the system

itself – that is, establishing a plausible system disturbance and developing a rich

description of the disturbance, using the construct approach briefly outlined above.

This will be discussed in further detail in the Level 3 description (section 6.3.5.2).

Once the hypothetical disturbance has been imagined, the response of the system model

to this disturbance can be explored.

iii. Qualitative exploration of system response – Representatives from the domain

of interests are encouraged to discuss their views of the likely outcome, as the system

responds to the hypothetical disturbance. It is important to note that this is primarily

an intuitive, qualitative, discussion involving stakeholders. Ultimately, the aim is to

identify issues which subsequently can be explored, using established analytical and

quantitative techniques. Using the initial description of the “As-Is” system, various

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scenarios can be explored as plausible responses to the hypothetical disturbance.

Scenario analysis is a technique which has been developed in large government and

commercial enterprises (for example, Royal Dutch Shell) and will be covered in

greater depth, as Level 3 of the problem-structuring approach is developed further in

the next section. The various scenarios representing the system model response to

the hypothetical disturbance are considered by the representatives from the domain of

interests. Then, one plausible scenario is identified as being the “Likely Future”

response of the system to the hypothetical disturbance.

iv. Exploration of alternative “Desirable Futures” – In the same way as the initial

“As-Is” system was developed, the “Likely Future” scenario-set is also represented in

a set of multidimensional cognitive maps, together with any other depictions and

textual material which may have been developed to enhance the richness of the

system model. Now the model description can be explored further by the

representatives of the domain of interests. An alternative system response, capable of

achieving the “Desirable Future” can be considered. This uses the existing analysis,

exploring changes which might be made to the “As-Is” system model (and by

implication to the real-world things and phenomena represented by the system

model), so that it becomes capable of delivering the “Desirable Future” response.

Up to this point, it is expected that, for practical reasons, the problem-structuring would

have been undertaken by a relatively small group of representatives from the domain of

interests. Normally, these people will be chosen because of their knowledge, expertise,

or specific interest in the problem situation under consideration. In order for the broad

engagement of the wider community to take place, the problem needs to be more readily

accessible. In other words, the process sketched up to this point is relatively complex

and would be unlikely to appeal to many in the community. The way in which this issue

is addressed is through the development of a set of word-rich narratives, which concisely

but comprehensively describe the problem from the range of perspectives likely to be

encountered in the broader community. The important point here is that the problem

must be described using a set of agreed information. This information may be interpreted

differently, depending on perspectives represented in the domain of interest. Narratives

developed from this set of agreed problem information, must then be able to be

deconstructed later (as might be done by a naïve, informed reader), to reveal the

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information, even though it may be coloured by the perspective, beliefs, and values of

the narrative writer. That is to say, such narratives rigorously prepared will carry

conscious or unconscious bias, due to the perspective of the narrative writer, but the

deconstructed content of the narrative will contain all of the agreed problem

information. Indeed, the way in which the final quality of the set of narratives is assured

is by objective deconstruction of each narrative in order to ensure that all problem

information agreed by the original representatives of the domain of interests is present.

v. Engaging the broader community – the narratives are used as the principal

means of communicating the issues to the community. Broad-based community

critique of the problem system, as represented in the set of narratives is encouraged

through activities such as seminars, public meetings, and workshops of interested

community representatives. During this process, specific narratives are selected the

set prepared using the process described above, according to interests of the particular

audience. Discussion and evaluation by the audience further elicits values and

preferences, which can be captured and built into the problem structure. After each

such community engagement session, narratives can be revised and further developed,

provided there is time and resource available to rigorously critique the resultant

revision against the original agreed set of problem information. The information

elicited through this additional debate and discussion facilitates the construction of

the values hierarchy to be used as part of the formal application of decision-analysis

techniques.

Having outlined the way in which the theoretical components have been integrated into

the problem-structuring approach, the third level will now be developed. This level

contains the devices and tools which have been created to give substance to the

theoretical approach just discussed.

6.3.5 Level 3 – Tools and devices for structuring type 3 problems This section describes a number of devices which have been developed and assembled

into an integrated approach, in order to structure the information which characterises the

Type 3 problem. It is consistent with the underlying philosophical principles of Level 1

and the integrated framework of systems theory and cognitive theory developed in Level

2. The aim is for these to facilitate representation of the problem information using the

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system paradigm and structuring the information in a way which relates isomorphically to

human cognitive processes.

Many Type 3 complex problems of sustainability can be thought of as complex “socio-

eco-systems”, often with technologically-based subsystems, which often are the main

focus of analysis. Examples of these types of systems are development of sustainable

solutions to complex problems such as water, transportation, energy infrastructure, and

large resource developments (for example, mines and oil-and-gas projects), and so on.

That is, they are comprised of complex, interacting social and ecological system elements

which respond as a whole and which contain complex interrelationships between system

elements. Often, the subsystem (such as the water supply, the mine, the transportation

system, etc) can be well defined in a technological sense but the interactions with the

social and ecological system elements are complex and poorly understood. Frequently,

there are diverse and even irreconcilable worldviews and philosophical positions among

stakeholders and, because of the complexity of both the issues and of the information

available, there are cognitive limits to the extent to which the problem can be described

and comprehended. Hence, it is argued here that if the problem structure is isomorphic

with or mimics human cognitive processes, there is a greater likelihood of a wider

constituency being able to engage with and understand the issues contained within the

problem.

This approach differs from established engineering practice, in that it is deliberately non-

reductionist – information is not discarded, rather it is arranged and stored in a way to

identify relationships between various aspects of the problem, so that they can be readily

recalled for later consideration. In comparing the established, reductionist engineering

approach with the systems approach developed here, on one hand, the reductionist

approach attempts to focus on critical issues relating to the problem, discarding those

things which are considered to be unimportant or marginal. On the other, the systems

approach treats all problem information as potentially useful and attempts to identify

important relationships which exist within the system. However, information and

relationships which, at the time, are not considered to be important are not discarded;

they are kept for future reference. This might be likened to identifying landmarks (Fiol

and Huff (1992), Chown et al. (1995)) in a piece of scenery – certain aspects stand out

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and may be considered to be more important than others in some contexts but no

information is lost.

To achieve this, problem information needs to be organised in such a way that

relationships between elements can be readily identified, so that the systems nature of the

problem situation becomes clear. To avoid to avoid losing clarity as the complexity and

richness as the model development proceeds, problem information can be arranged in

dimensions or layers, so that important information and relationships can be stored for

later reference. This also facilitates representation of problem information in a way

whereby relevant aspects of the problem can be accessed readily by the various

representatives from the domain of interests. Thus, the problem-structuring process

consists of five steps (see also Figure 6.3 overleaf):

1. System representation.

2. Definition of hypothetical system disturbances.

3. Imagine plausible system responses.

4. Multi-dimensional critique.

5. Critical discourse.

Because of the relative complexity of the modelling process, it would be expected that

the first four of these steps would be manageable only with a relatively small working

group of participants representative of the entire domain of interests. It is important to

select these participants, based on their interest in the issue, the extent to which they

represent the domain of interests (or at lease one part of it), their knowledge of the issue,

so that a balanced, diverse representation of the entire domain of interests is achieved.

Arguably, this is the most challenging aspect of the problem-structuring approach

because of its susceptibility to bias (both conscious and unconscious), and the need to

have potentially irreconcilable and confrontational positions represented on the working

group. Indeed, many projects become unviable because of the differences among

participants over representation or power within of the domain of interests. (Experience

in the case study suggests that this also can be manifested in people deciding not to

participate because they believe their work will not be valued or influential).

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Dimension 5Dimension 4

1. System representation:

2. Define hypothetical disturbances:

3. Imagine plausible system responses:

4. Multi-dimensional critique:

Dimension 7 Dimension 6 Dimension 8…

Dimension 1 Dimension 3Dimension 2

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5. Critical discourse: Engagement with Domain of Interests

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Figure 6.3 – Concept map of the problem-structuring process








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Figure 6.3 – Concept map of the problem-structuring process Each of these steps will now be described in greater detail.

6.3.5.1 Step 1. System representation – boundary definition and trilemma system mapping

The problem is initially described in such a way that system boundaries can be identified,

“landmark” system elements can be recognised, and subsystems can be defined. The

challenge here is to retain as much information as possible about the definition of the

problem and to organise it in a way, which does not overload cognitive function but

allows quick recall of information for further consideration. Important in structuring the

problem information as a system is the “trilemma”, a cognitive mapping device for

representing problem information as a set of cognitive constructs, consistent with Kelly’s

theory of personal constructs. Boundary critique and the development of an initial

“value image” as part of the “As-Is” initial system state system are key parts of the first

step.

There are three important considerations in representing the problem as a system:

• establishing the context of the problem using a comprehensive narrative to

provide background context to participants in the problem-structuring exercise.

In many cases, this narrative will be historical in nature, because many Type 3

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problems are identified as a consequence of their having been recognised for a

long time but attempts to solve them have not been successful;

• establishing system boundaries and undertaking “boundary critique” to determine

what aspects of the problem should be “swept in”, what should be excluded, and

what should be considered to be at the margin between that which is included

and that which is not. It is important that the process for undertaking boundary

critique is rigorous. Reference is made here to an extensive line of work on this,

developed in the area of operational research;

• identifying “landmark” system elements and subsystems which are expected to

have the most influence on system response and behaviour. This takes place at

the same time as the boundary critique

Each of these will now be considered more closely.

6.3.5.1.1 Development of a contextual narrative

This initial step is to acquaint those interested in the problem with the various issues

which have contributed to the emergence of the problem situation. Because most Type

3 problems emerge over a fairly long period of time, the narrative tends to be historical

and should focus on key aspects of the problem, which are thought to be the major

contributors to complexity and problem irreconcilability. This narrative should be brief

but cover thoroughly the major influences on the problem. The narrative presented in

the case study in Chapter 7 gives both a chronological perspective of the way in which

the problem has developed and also gives some insight into the way in which the system

has responded to various disturbances. Generally, the narrative will be prepared by one

person but should be subject to critique to ensure that it is factually accurate and to

identify and to make transparent the implicit and explicit values and beliefs of the author.

6.3.5.1.2 Boundary definition and critique

The first step in defining the system boundary is a concise but embracing statement of

the problem. For example, “the challenge of providing a sustainable water system for a

major metropolis” (which is the broad theme of the case study developed in Chapter 7).

This stimulates many questions (for example, does the problem relate only to provision

of potable water? Is sewerage included? What constraints are there in terms of

infrastructure development – such as capital cost, environmental issues, health and so

on? What political obstacles might exist? What technologies are available? How far

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beyond the metropolis does the impact of the water system extend? What institutional

barriers may need to be considered? What moral interests need to be recognised and

taken into account?) These questions naturally lead to consideration of system

boundaries. With Type 3 complex problems, boundary definition is usually unclear and

judgement needs to be used as to what should be included and excluded from

consideration and the extent to which certain problem aspects and interests may be

marginalised. The approach adopted here follows a line of thought which originated in

Churchman (1970) and Ulrich (1987), and was further developed by Midgley (1992),

Ulrich (2001), Yolles (2001), Ulrich (2003), Midgley (2003), Midgley and Reynolds (2004),

Ulrich (2006). (The detail of the approach appears in the case study example – see

Chapter 7, section 7.3.5.)

This considers boundary definition to take place through a discursive process of dialogue

between members of the domain of interests, taking into consideration not only the

technical judgement of experts but also giving due weight to the ethical consideration of

the interests which should be represented in the problem (see Figure 6.4).

SystemSystemSystemSystem

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Figure 6.4 – Determining system boundaries – boundary critique. In practice, this is achieved by identifying experts, knowledgeable in the issues proposed

for inclusion in the problem system, together with representatives from interest groups

which are identified as taking a particular interest in the problem. These could be

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community groups, NGOs, or vocal individuals. Type 3 problems are usually of such a

magnitude and prominent position in the community that normally both experts and

interest groups are identified readily. The challenge for the steering group is to ensure

that all interests in the problem are represented and that participation does not favour

one group over another.

The important point to note is that for Type 3 problems, this is an ethical discourse not

simply definition of a system boundary in its physical sense. For example, in undertaking

boundary critique for a metropolitan water system, ethical considerations regarding

marginalisation of interests of small population groups well away from the metropolitan

area but within a water catchment requires careful consideration. Similarly, depending on

the intrinsic valuation established during the boundary critique process, non-human

moral interests, such as those of threatened species or ecosystems will be either included

(if a sustainability position is adopted) or possibly excluded (should a sustainable

development position be taken). In practical terms, the way in which this boundary

critique takes place is through a process of engagement with representatives from the

entire domain of interests. Irrespective of the actual determination of system boundaries,

if the process if followed rigorously, both implicit and explicit valuations will become

transparent both to the participants in the analysis and to those who may not be directly

involved.

6.3.5.1.3 Representing system elements

The approach taken here is that the system can be represented in sets of about five to

eight system elements or subsystems. As many sets as required to fully represent the

problem information can be prepared, with relationships being identified between system

elements both within and among these sets, provided that the data sets can be readily

stored and recalled for consideration. As noted above, the device used to represent

system elements is the “trilemma”, a cognitive mapping device coherent with Kelly’s

personal construct theory. This is consistent with principle C2, allowing the mind to

focus on a small number of specific aspects of the problem at one time, while quickly

being able to recall other information for consideration.

The term “trilemma”, representing a situation of three conflicting choices or pathways is

by no means new but it has been given popular currency recently, particularly in

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economics and in corporate strategic planning. Rodrik (2000) refers to the work done by

Obstfeld and Taylor in relation to Mundell’s and Fleming’s work in the 1950s on

exchange rates, capital movement, and monetary policy. Rodrik presents the trilemma in

its original interpretation: it is impossible to satisfy all three constraints at once – in order

to achieve two outcomes, the third must be sacrificed. However, Royal Dutch/Shell, in

their long-range strategic planning process developed the trilemma concept somewhat

differently – they considered a trilemma of three major forces in tension and considered

what the outcomes might be if one or other of the forces were to become dominant (van

der Veer (2005)). In this process they conceived of “Utopias” – desirable, but practically

unachievable future states – at each vertex of the triangle. This enabled them to explore

scenarios on a “two-win, one-loss” basis. The Royal Dutch/Shell trilemma approach is a

powerful means of exploring hypothetical futures. However it suffers two notable

deficiencies: first, it is highly reductionist, attempting to characterise an enormously

complex system as a single trilemma representing the interaction between just three

forces; and second, there is no reason why future states necessarily need be utopic –

when a particular force dominates, the outcome at a triangle vertex can conceivably be

either desirable or undesirable – either a utopia or a “dystopia”. To address the first of

these deficiencies, the approach taken here is to further develop the concept of the

trilemma, not as a system, but rather as a system element. And to address the second, the

relationship between the three forces is explored so as to identify both utopic and dystopic

responses to the hypothetical disturbance and a plausible outcome which is reflective of

some balance between the two (see Figures 6.5 and 6.6 opposite). (It should be noted

that this approach contains a simplifying assumption: it assumes that the three forces

represented in the trilemma are independent and that linear combinations of the forces do

not give rise to more extreme positions than those represented at the vertices of the

triangle in which a single force dominates. Furthermore, it does not take into account

relationships that might exist between trilemmas. It would be expected that these

assumptions be considered during the critique process and used to develop relationships

in approaches such as MCDA which attempt to represent the relationships of

“preferential independence”, whereby a preference for an issue represented by one

trilemma can be expressed independently of how one might feel about other issues

represented by other trilemmas)

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Major influences or forces which are acting in opposing directions are identified.

Most complex problems will have no more than 20 to 40 major influences.• most problems can be represented

by 4 to 8 trilemmas

Major influences or forces which are acting in opposing directions are identified.

Most complex problems will have no more than 20 to 40 major influences.• most problems can be represented

by 4 to 8 trilemmas

Figure 6.5 – Constructing a trilemma: identifying opposing forces

It should be noted that neither Rodrik’s work nor the Royal Dutch/Shell approach make

specific reference to psychological theory. However, using the trilemma as a device to

represent system elements aligns well with Kelly’s personal construct theory (principle

C3) – holding one force constant and exploring the effect of varying the other two is

analogous to Kelly’s concept of the dichotomous construct. It also gives a sense of the

strength of the relationship between the force which is held constant and the other two,

analogous to the scalar representation in Kelly’s theory.

They are then refined by holding one force constantand exploring the effect of varying the other two.

Utopia Dystopia

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DystopiaPlausibleoutcome

PlausibleoutcomeUtopia

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“Plausible Outcomes” are imagined based on each force being dominant

They are initially identifiedby assuming one force is dominant and imagining a plausible set of outcomes

• Utopias are an “ideal”outcome when a force prevails

• Dystopias are the “nightmare” outcome

Figure 6.6 – Constructing a trilemma: identifying utopias, dystopias and plausible outcomes


Utopia Dystopia

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Figure 6.6 – Constructing a trilemma: identifying utopias, dystopias and plausible outcomes

Using trilemmas to characterise a system

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The process for developing the system map using trilemmas as the means for

representing system elements is this:

• identify the forces at play in the system – usually these can be thought of as

“force-pairs” which are represented as dichotomous constructs and these

correspond to aspects of the problem which are in tension. One way to identify

the dichotomies is through the well-established practice of brainstorming

(Brazzard (1989), Bryson and Ackermann (2004)). In some cases, the nature of

the dichotomies will be apparent from the problem itself; in others, they are

constructed just by taking one problem feature and considering its opposite. (See

example in Figure 6.7.) Note that in the example, in some instances, the

dichotomous constructs represented are not forces but symptoms representing

behaviours in response to the forces. This suggests that there is potential to

develop the trilemma device at two levels in terms of means and ends. On one

hand, the trilemma might be thought of as the means by which the system’s

response can be evaluated. On the other, the system states represented at the

vertices of the trilemma indicate the end, that it, a plausible system response.

Figure 6.7 – Brainstorm dichotomous constructs and identify underlying force pairs.

Health Risk ↔ Recycling

Change Acceptance ↔ Change Aversion

High Rainfall ↔ Low Rainfall Enabling Technology ↔ Politics

Public Ownership ↔ Private Ownership

Community Concern ↔ Technological Influence

Greenfield ↔ BrownfieldFree Market ↔ Monopoly

Political Self-Interest ↔ Community Concern

Centralised ↔ Decentralised

Regulation ↔ Monopoly

Media Influence ↔ Politics

Vested Interests ↔ Community Engagement

Opinion Leaders ↔ Community EngagementOpinion Leaders ↔ Politics

Free-market Capitalism ↔ Big Government

Vested Interests ↔ Community Interests

Economics ↔ Environmental Concern

Legal Activism ↔ Politics

Legal Activism ↔ Corporate Governance

Population Growth ↔ Population DeclineHigh Energy Cost ↔ Low Energy Cost

Identify the dichotomies…

Political Self-Interest ↔Technological Influence

Figure 6.7 – Brainstorm dichotomous constructs and identify underlying force pairs.

Health Risk ↔ Recycling



















Political Self-Interest ↔Technological InfluenceHealth Risk ↔ Recycling



















Political Self-Interest ↔Technological Influence

• identify force-pairs which might be able to be arranged as true trilemmas. A “true

trilemma” is one where the three forces exist independently but interact and have

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a natural tendency oppose one another (this step is intended to strengthen the

simplifying assumption noted earlier);

• in turn, hold each force constant and imagine and describe a utopia and dystopia

which would prevail if the remaining force-pair under consideration were to

prevail (this is analogous to the personal construct as hypothesised by Kelly

(1955));

• characterise the “As-Is” system by developing the sets or maps of five to eight

trilemmas and identifying the relationships that might exist between the

trilemmas themselves. Some system elements may be found to contain greater

complexity than can be represented in several trilemmas and these should be

treated as subsystems being mapped at a greater level of detail. As these

relationships are developed, they can be used to assist in constructing objectives

hierarchies in MCDA;

• engage with the group of representatives from the domain of interests to critique

the system model, with particular emphasis on understanding element

relationships. This includes undertaking the discourse necessary to establish and

criticise system boundaries. It is important to note that development of the

system model requires a substantial understanding of the problem-structuring

process itself. It consists of a set of cognitive maps representing problem

information as trilemmas and with some of the relationships which exist between

trilemmas also identified. Similar maps of subsystems might also have to be

developed. Hence, for the critique of the system model to be valuable, at this

early stage, it needs to be confined to project team members who are well-versed

in the methodology. Typically, this group of people would be expected to be the

facilitators who will ultimately lead the broader critique of the system model in

the wider community.

One means of establishing the sets of trilemmas representing the total system is to

consider the various dimensions of the problem, so that pieces of information can be

grouped according to their similarity and criticised. For example, van der Heijden (1996),

in his approach to scenario analysis, identifies such structural issues as information,

resources, cultural, legislation, political, financial, technology, ecology, physics, policy,

thresholds, power distribution, territorial, regulation, agreements, and demography.

These are also encountered in other approaches to corporate strategic planning and

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sometimes referred to as “environmental scanning” (see, for example, Kotler (1991),

Macmillan and Tampoe (2000)). In some instances, this deliberation will need to be

made iteratively, as a problem dimensions are descriptors of system response and insight

will emerge from considering the system response to disturbances. Developing the

model in this way recognises that the problem is a dynamic system. One powerful aspect

of the approach is that the richness of the model develops as the response of the system to the

disturbance is tested repeatedly.

Experience in the case study suggests that even very complex systems can be

comprehensively represented by considering thirty to forty force-pairs and that these can

then be represented in five to eight trilemmas. Important aspects of the problem can be

considered in further depth when represented as subsystems.

The sets of trilemmas can then be explored, both as individual system elements, and also

in the way in which they interrelate to represent the total system. Trilemmas identified at

a high-level may be further investigated as subsystems and explored in more depth if this

is useful in forming a more comprehensive representation of the problem situation.

This approach of qualitatively representing a complex socio-eco-system has a number of

benefits:

• it allows representation of a large amount of information using relatively simple

schema – this meets challenge of having only five to eight units of concentration,

so the mind can keep focused, consistent with principle C2;

• the trilemma device is consistent with dichotomous constructs (principle C3);

• each trilemma is effectively “self-bounded” – description of any situation in

relation to the three trilemma forces will be contained within the triangle, thus

facilitating boundary critique of the system as a whole;

• by engaging a wide range of stakeholder perspectives in identifying the forces and

creating the trilemmas, there is both engagement of stakeholders and the creation

of a common language to describe the problem;

• it is relatively straightforward to identify utopic/dystopic positions by holding

one force constant and exploring the effect of varying the other two (principle

C3).

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6.3.5.2 Step 2. Definition of hypothetical system disturbances This step identifies one or more hypothetical disturbances to be applied to the system in

order to allow qualitative exploration of the way in which the system might respond.

Issues to consider in defining such a disturbance are these:

• Whether the origin of the disturbance should be external or internal to the

system. In the initial analysis, only one disturbance is considered. Whether the

hypothetical disturbance should be internal or external should be determined by

the most likely risk: is it some external shock to the system (for example, in the

case study in Chapter 7, a metropolitan water system, permanent climate change

was considered); or is it some internal disturbance (for example, collapse of

critical infrastructure, such as a major dam might be plausible);

• for reasons of practicality, the type of disturbance will probably be either a step

change or a ramp change in external conditions85;

• the hypothetical disturbance should be relate to some major aspect of uncertainty,

which might be expected to have a significant impact on the system stability;

• trilemma analysis can be helpful in conceiving system disturbances;

• a simple disturbance will be more easily analysed than a complex one.

Once the disturbance has been determined, it should be described clearly and concisely

in words. It is important that the description of the system disturbance is simple and

readily understood.

6.3.5.3 Step 3. Imagine plausible system responses – scenario analysis In this step, plausible responses of the “As-Is” system to the hypothetical disturbances

are considered. At this stage, the system response is explored qualitatively, identifying

areas where quantitative analysis might be useful. At least two future system states are

considered in this step. On one hand, is the likely response of the “As-Is” system to the

disturbance; on the other is a desirable response to the disturbance. In the first instance, the

most likely response of the “As-Is” system is explored, assuming that no structural

change is made to the “As-Is” system as a direct consequence of the disturbance itself.

In the second case, consideration is given to what structural changes to the “As-Is”

system would be required for it to be able to respond and to deliver the “Desirable

85 Systems analysis theory of mathematically defined systems can treat many different types of disturbance

but the qualitative approaches being used here suggest some practical limitation on the type of disturbance considered.

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Future” response. In the case study in Chapter 7, only these two scenarios were

considered. However, depending on the nature of the problem and the time horizon

under consideration, further scenarios may be required to populate the range of

uncertainty in the problem. This is considered when preparing for the “scenario

analysis” (see below). The “As-Is” system is described using a combination of cognitive

maps, depictions, symbols, diagrams, and words to capture the richness of the qualitative

analysis86.

Then a different trajectory is imagined for the system towards a “Desirable Future”,

identifying differences in strategic image required for the “Desirable Future” to become

achievable. As with the “As-Is” system description, a rich representation of the

“Desirable Future” system state is captured using cognitive maps, depictions, diagrams,

symbols and words.

To explore the potential effects of the hypothetical disturbance, a well-established

technique (or, rather, family of techniques), which has evolved over the last 50 years or

so (Miller and Waller (2003)), called “scenario analysis” is used87. To determine which

specific technique to use, it is useful to consider what the ultimate objective of the

scenario analysis is (whether it is explorative or descriptive); the process to be used

(whether it is to be intuitive or analytical); and the content (whether it is to be simple or

complex) (van Notten et al. (2003)). (Olson (1994), Godet (2000), Krueger et al. (2001),

Raskin and Banuri (2002), and Swart et al. (2004)) provide examples of the application of

scenario analysis to inform strategy, using scenario analysis in relation to complex social

problems, and integrating the approach into consideration of the complex problems of

sustainability.)

The general process for scenario analysis can be described thus:

86 For example, in a typical working group, notes might be recorded on flip chart paper, complemented by

graphs, sketches, diagrams, and even photographs. Together these can be used to convey important information from the analysis to others working on the project.

87 Scenario analysis originated as part of the Manhattan project when modelling was done to determine the strategic effects of the atomic bomb and, after the war, was extended into strategic thinking as the Cold War commenced. A number of consulting firms introduced the technique to large corporations and over the next twenty years it became well accepted as a tool for corporate strategic planning. In the 1970s, when the first oil shock occurred, Royal Dutch/Shell extended the concept to look out over much greater time-frames, modelling the impact of variables such as oil prices and energy supply/demand as part of their strategic analysis.

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• Define the time horizon over which the response of the system to the

hypothetical disturbance will be considered. As noted above, with most Type 3

problems, 10 to 50 years is not uncommon. As the timeframe lengthens, the

range of uncertainty increases and each scenario-set requires the development of

a larger number of scenarios to consider in order to cover the range of

uncertainty. (See Figure 6.8) The consideration of uncertainty is an important

issue in determining both the nature and number of scenarios explored.

Uncertainty in relation to Type 3 problems can derive from a number of sources:

it may be due to incomplete information, natural variability, differences in the

way in which the problem is described or characterised, or it may arise from

differences in preference and values (Morgan and Henrion (1990a)).

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Figure 6.8 – Developing scenarios to span the range of uncertainty

Scenario analysis

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Figure 6.8 – Developing scenarios to span the range of uncertainty • Representation of the domain of interests. It is important that all interests be

represented in the analysis, so that the ultimate scenario-sets have access to all

perspectives which need to be taken into account. The issues relating to

uncertainty noted in the previous point are also likely to influence the selection of

this representation.

• Identify those issues which are “knowable”. Extrapolate from past trends

and attempt to ascribe the uncertainty related to each. Where possible, attempt

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to identify qualitative relationships between system elements and the way in

which these will respond to the disturbances.

• Define the boundary scenario themes. This may be simply putting all positive

responses into one scenario and all negative ones into another – the essential

point is to attempt to conceive of boundary scenarios for the range of

uncertainty. It is important to note is that the uncertainty dealt with here is of a

“structural” nature and is characteristic of the system. That is, future events are

not particularly influenced by past events and multiple interpretations are possible

both to explain and to predict behaviour of the system. Identification of the

boundary scenario themes (and, indeed, those in between – as depicted in Figure

6.8) is intended to appeal to our capacity for intuitive thought (as discussed

Chapter 5, section 5.2.1). That is, it is intended to stimulate recognition of

patterns in the system and consideration of how they might develop (van der

Heijden (1996)).

• Cover the range of uncertainty by developing additional scenarios as necessary

to fill the future landscape.

• Analyse for plausibility and internal consistency. Once initial scenarios have

been drafted they should be refined and tested for internal consistency and to

assure that any irrationality is identified and noted. Whereas the definition and

development of scenarios is largely intuitive, the consideration of their plausibility

and internal consistency is analytical. However, where beliefs and values are

involved, inevitably there will be irreconcilable differences identified. Skilled

facilitators are needed to mediate in these discussions to ensure that imbalances

in power are considered and that coercive elements within the domain of

interests are restrained from having undue influence. The starting requirement is

that the working group is structured in such a way (both in terms of hierarchy

and representation) that power imbalances are minimised. This can be

challenging indeed where political or commercial interests dominate the

structuring of the working group.

• Seek opportunities to strengthen scenarios. Note where gathering objective

information would fill gaps in knowledge regarding the problem.

• Convert scenarios into “storyboards”. Using cognitive maps, symbols, and

depictions, to develop representations of each scenario-set, drawing these

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together with a number of narratives prepared from different stakeholder

perspectives. In some cases, facilitators might be required to prepare initial

narratives as a starting point for critique and discussion. This is explored in

terms of the case study in Chapter 7.

• Explore opportunities to develop quantitative models. Note areas where

quantitative modelling (for example, economic modelling, values preference

modelling, etc) might be used to gain further insight into the scenario-sets.

• Test the final scenario-sets. Ensure that all participants in the analysis have

had the opportunity to critically examine the scenarios and to contribute to

additions or changes.

The principal advantages of this approach relative to the alternative quantitative

forecasting approaches are these:

• it extends consideration of uncertainty beyond the limitations of quantitative

forecasting approaches by taking into account the structural uncertainty in the

problem situation. These derive from incomplete information, linguistic

differences in problem description, and differences in preferences and values

(Morgan and Henrion (1990a), van der Heijden (1996)). As noted in Chapter 5,

significant psychological biases appear which may result in either under-

estimating or over-estimating probabilities, particularly where intuitive judgement

is involved. That is not to say that quantitative methods for representing

uncertainty should be excluded. Rather, it is suggested that the construction of a

set of scenarios to span a range of problem uncertainty allows insight into the

problem to be developed beyond that represented by purely quantitative

methods. This is particularly so in areas where there is no basis for assignment of

probabilities;

• presentation of a number of scenarios, using storyboard techniques, is a good

way to engage stakeholders by avoiding often complex analytical approaches;

• constructing a number of stories from different stakeholder perspectives allows

representation and engagement of a diverse range of stakeholder views and

values;

• it allows deconstruction of highly complex future environments into a number of

simpler and more readily understood parts. (It should be noted that this is not

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necessarily reductionist, rather it allows system elements and subsystems to be

explored and their interrelationships examined.);

• a number of variables may be changed simultaneously. This may be complex in

formal analytical methodologies;

• because initial definition of the starting point for scenarios is largely subjective,

the beliefs, values, and biases of participants become embedded in the scenarios.

This is by no means undesirable but care needs to be taken to identify these and

to retain their transparency as the scenarios are developed. These values-laden

scenarios are useful in developing complete narratives, which represent the

problem system from a range of different worldviews. Again, this is explored in

Chapter 7.

When undertaking scenario analysis, there are a number of important aspects to keep in

mind about the technique. With infrastructure projects, where there is large capital

expenditure or potentially significant social and environmental impact, the analysis looks

a long way into the future (usually from 10 to 50 years or more). Because of the inherent

uncertainty this implies, scenarios cannot be considered to be forecasts, as there is only a

relatively small likelihood of any one scenario actually coming true. Hence, scenarios

should not be thought of as being predictions. Rather, they should be considered to be

outcomes which could emerge from considering a set of plausible assumptions and

parameters in relation to the existing system state. The technique is at its most powerful

when a number of “story-lines” or narratives can be developed which are internally self-

consistent and can be contrasted with one another. The most extreme positions define

the boundary conditions and the intermediate scenarios propose situations which are

plausible outcomes. Consideration and evaluation of these allow strategic plans to be

developed in such a way as to allow greater flexibility in the way in which resources are

deployed (Science and Technology Policy Research Unit (2002)).

Because development of the scenarios is a mixture of both rational thought and intuition,

with disparate views and values, reaching consensus can be difficult or even impossible.

There needs to be a recognition of this difficulty and a commitment among participants

to follow a defensible process. This is required to arrive at a comprehensive range of

story-lines. Furthermore, it should be emphasised that this approach is to identify issues

and their interrelationships through a widely accessible structuring of problem

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information, the aim being to inform decision-makers about important issues. This issue

is by no means trivial – it requires skilled facilitation and a comprehensive understanding

of the entire problem-structuring approach and, preferably subsequent analytical

approaches such as MCDA.

It is not intended nor is it expected that the approach described here will lead directly to

solutions to the problem. Rather, issues will be identified which will need further

exploration and deeper analysis, using formalised analytical techniques such as preference

modelling, economic modelling, multi-criteria modelling, and so on. The value of the

approach developed in this dissertation is that it strengthens these techniques through

developing a problem structure which takes into account the dynamic nature of the

problem system to plausible, hypothetical disturbances. This allows greater confidence

to be established in parameters utilised in formalised modelling techniques and greater

insight into the broad range of hard, soft, and values-laden information. This approach

is expected to be of particular use in techniques such as MCDA which attempt to

develop comprehensive mathematical representations of incommensurate aspects of the

problem through development of mathematical functions representing values and

preferences and then to facilitate their comparison through techniques such as out

ranking methods.

In the problem-structuring approach developed here, the application of scenario analysis,

while adhering to the general principles outlined above, has been modified slightly as

shown in Figure 6.9 (overleaf). The specific steps used in this approach are;

• Start with the “As-Is” system, and consider qualitatively the way in which this

system might respond to the hypothetical disturbance (or disturbances)

conceived of in Step 2.

• Imagine a plausible future scenario-set, representing the response of the “As-Is”

system to the disturbance, assuming no fundamental change to the “As-Is”

system characteristics. This is called the “Likely Future” scenario-set.

• Imagine a second plausible scenario-set representing a “Desirable Future”, a

response to the disturbance which is desired but which the “As-Is” system is

incapable of delivering. Development of this scenario-sets requires critique of

the system elements, subsystems and their interrelationships to determine the

challenges in arriving at utopic positions.

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• Once the “Desirable Future” scenario-set has been conceived, it can be

compared with the “Likely Future” scenario-set across the problem dimensions.

This allows identification of issues across the breadth of the problem as

characterised by the “As-Is” system which need to be addressed if the “Desirable

Future” scenario-set is to become achievable.

What Strategies are needed to change the Trajectory?

• Describe these in terms of the problem dimensions

Characterise the “As Is”system…

• Establish and critique boundaries

• Describe the history and “Values” which shaped the system

• Identify the forces at work• Formulate and critique the Trilemmas

• Characterise the sub-system

Disturbance

Describe the two scenarios:• Words, diagrams, pictures, etc

Interpret the effect in terms of the Trilemmas

SystemSystem

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Figure 6.9 – The system model underlying the problem-structuring approach.








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Figure 6.9 – The system model underlying the problem-structuring approach.

This important step in the process is the starting point to identify options which will

be available finally to the decision-makers in formulating policy and designing

interventions to achieve desired real-world system responses. In identifying the

characteristics of the system that need to be changed, it is almost inevitable that

trade-offs will be required in different system elements or subsystems. In order for

these to be included in quantitative analyses in the latter stages of decision-making, it

is important that comprehensive documentation is developed. This should

comprehensively record the problem-structuring approach (including participants,

discussion notes, meeting minutes, depictions of the system model, narratives, and

conclusions). This document should be widely disseminated among the domain of

interests, so it can be referred to as policy formulation and decision-making takes

place to ensure that all aspects of the problem are properly addressed. Such a

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document can be instrumental in removing power imbalances, particularly if it is

disseminated through he media.

6.3.5.4 Step 4. Multi-dimensional critique – “straw proposal” cognitive maps and narratives

Now, critique of the system can be undertaken. The “Likely Future” and “Desirable

Future” scenario-sets are examined as outlined below, capturing these in several word-

rich narratives representative of the range of perspectives of the entire domain of

interests. By referring to the “As-Is”, “Likely Future” and “Desirable Future” trilemma

system maps, a comprehensive narrative or storyline can be prepared as a “straw-

proposal” for discussion and critique by stakeholders88. Groups of stakeholders with

expertise or interest in a particular problem dimension can be assembled to examine

relevant aspects of the problem, or “multi-dimensional” groups can consider

relationships between information across problem dimensions.

Multidimensional critique is important in two respects. First, it draws together and

considers critically the response of the system to the hypothetical disturbances; and

second, it summarises the interpretation of the system response from a range of

perspectives representative of the domain of interests. This combination of the

description of system response from a number of differing perspectives ultimately allows

a greater engagement by the domain of interests, because a range of values and belief

systems is represented. Cognitive mapping of “landmark” system elements facilitates the

identification of important aspects of the problem, together with relationships which can

be identified between them. This can take place across multiple problem dimensions.

This is the starting point for developing narratives which allow identification of and

reflection upon gaps in knowledge regarding the problem and system element

interrelationships. Also, the various values, beliefs, and interests of the representatives of

problem stakeholders emerge from the structure of the narratives, consistent with

principle C6.

The process for multidimensional critique is this:

88 “Straw-man proposal” or “straw proposal” is a term commonly used in business analysis as a starting

point proposal for developing business strategy. Anecdotally, its origin is an effigy of a man made of straw used in jousting practice. Hence, it is a proposal which is to be knocked down, picked up, reshaped, and knocked down again in order to shape and refine thinking.

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• a steering group prepares an initial draft of the “As-Is” and “Desirable Future”

system responses to the hypothetical disturbance. This is a set of draft cognitive

maps and a brief, “straw-proposal” narrative as a starting point for group

discussion.

• Small groups (with from four to eight members) are assembled representing

specific areas of expertise in particular problem dimensions or chosen as

representatives of various parts of the domain of interests. Using the straw-

proposal as a starting point, these groups develop narratives (together with

supporting information such as diagrams, pictures, symbols, etc), which are

descriptive of both the “As-Is” and “Desirable Future” system responses.

• As part of this process, each narrative is deconstructed to determine the extent to

which the original problem information is represented in the narrative. This is an

important step in controlling the quality of the problem-structuring process. It

should be noted that the intention is not to restrict or discourage values-laden

interpretation of problem information, rather it is to ensure that as much

problem information as possible is represented and interpreted in the narrative

context.

• Once the draft narratives have been completed by the working groups, they are

circulated for consideration and discussion to the full working group engaged in

structuring the problem.

• The full working group has the opportunity to contribute to and to criticise the

draft narratives, with an iterative process of review and re-work taking place until

there is consensus that the sets of narratives fairly represent the diverse view of

the working group regarding the problem structure. That is that they contain an

agreed set of problem information. Because the full working group has been selected to

represent the entire domain of interests, the resultant narratives would be

expected to contain a fair representation of the entire range interests present in

the problem.

(A cognitive mapping technique has been developed to facilitate recording information

from the system critique. This is based on utilising visual or word-based representations

of issues identified in the critique, highlighting major relationships (called “conjugation

points”), both within and between problem dimensions. This allows large amounts of

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information to be recorded about the problem and not lost through any tendency to

reductionism. This technique is outlined in Appendix 6.1.)

6.3.5.5 Step 5. Critical discourse – community engagement The final step in the problem-structuring process is to use the information prepared in

the preceding four steps to engage the broader community within the domain of interests

with the issues identified in the problem-structuring exercise. Depending on the nature

of the specific Type 3 problem under consideration, this may be as simple as identifying a

particular intervention (for example, based on technological requirements). On the other

hand, it may extend all the way through to extensive media engagement, utilising formal,

paid consulting resources to ensure engagement of all elements of the domain of

interests (as established in the boundary critique), with the explicit intention of

influencing policy direction. Typical avenues for community engagement include

participating in public meetings and forums, the sponsoring of specialised conferences to

consider the problem situation, testifying before formal hearings into the problem

situation, and engagement with mass media (including utilisation of professional public

relations resource). The difference between the approach taken here and typical public

consultation approaches is that representatives from the domain of interests are engaged

at the very first stages of problem definition. The community is presented with a

comprehensive, wide-ranging brief of information representing the full diversity of the

interests represented in the problem. Because this should take place well before a final

decision on solution to the problem is required, there is maximum opportunity for

engagement. This contrasts with more established community consultation approaches

which are often little more than presentation of a set of two or three options at the

conclusion of often secretive investigative and design work, which represents a single

powerful or influential worldview.

It is this last point which leads to a further important application of the problem-

structuring approach to be developed in the next section.

6.3.6 Retrospective critique Thus far, the approach has been prospective – the assumption is that a problem has been

recognised, that there is a determination that it be characterised and resolved, and that a

process is under way to resolve it (as outlined in Table 6.1). However, many Type 3

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problems are not new. Rather they have been either neglected or considered to be too

hard by successive groups of decision-makers. Ultimately, some crisis results in there

being no alternative but to take action. Often in these situations analytical work is done

in “crisis mode”, with a solution being identified with incomplete analysis and presented

to the domain of interests with little time for consultation or consideration. In these

circumstances the problem-structuring approach developed here can be utilised

retrospectively to critique potential solutions, which may have been forced to

implementation without adequate policy consideration. Representing the problem

structure as described here allows identification of important problem information,

which can be used as the basis for critique of other work on the problem system which

may have been already completed. This is explored as part of the case study in Chapter

7.

The approach developed here to review and critique existing policy or plans has been

developed in two strands. First, is a normative approach, whereby important system

information is determined through analysis of the trilemmas system maps and

multidimensional cognitive maps developed during the problem-structuring exercise.

This enables “landmark” features of the problem system to be identified across all the

problem dimensions which, together, form the system model. It is then a

straightforward task to review existing policy and planning documents against a checklist

of these landmark features to determine whether they have been adequately considered in

framing the policy or preparing a strategic plan. Second, is a more holistic, intuitive

approach: interrogating the narratives prepared during the problem-structuring exercise

and conducting a critique of the policy or strategic planning information, informed by the

worldviews and perspectives of the narrative writers. In the case study in Chapter 7,

both normative and holistic approaches are demonstrated in a review of a major, state

infrastructure planning process.

6.4 Research approach As noted in Chapter 1 (section 1.6.2), where the distinction was drawn between the

characteristics of quantitative and qualitative research, the research approach taken here

sits within the postpositivist and critical theorist positions, that is, it is based upon the

qualitative research paradigm.

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The realist ontology argued in Chapter 4 (principle P1, Chapter 4) clearly precludes a

constructivist approach and also rejects the naive realism of positivism, arguing not for a

mechanistic ontology, but rather, for a holistic, systems approach (principle P4). But

there is also a recognition that social, political, institutional, economic, ecological, and

technological history has shaped the way in which the problems of sustainability have

been dealt with and are expected to emerge in the 21st century. Hence, the approach

must position extend into the realm of critical theory. In this dissertation, a clear

distinction is drawn between the real-world things and phenomena of World One, and

our World Two and World Three representations of them. The discussion of

philosophical principles and cognitive psychology argued that limitations and flaws in our

representations of World One phenomena are primarily a result of human cognitive

constraints, rather than being an ontological feature of the universe. That is, they are

epistemological, rather than being ontological.

A important aim of this research is to develop models and devices which can contribute

to our capacity to develop our knowledge and understanding of the real world in which

we find ourselves. But in addition, there is a central intention of this work to influence

and change the way in which engineering is practised – that is, it is emancipatory in

nature, intending to free engineers from a dated paradigm. The widely held engineering

paradigm, which evolved in the first 200 years of engineering practice, has been

extensively criticised and a new set of principles to deal with the complexity and

challenges of sustainability in the 21st century has been proposed. Again, this places this

research within the domain of the critical theorist and emphasises the importance of

basing criticism on a practical representation of the problem. It also calls for a better,

more complete way of structuring Type 3 complex problems so as to improve our

understanding of them and, most importantly, to contribute to their solution. The

theoretical consideration of cognitive processes, particularly the importance of cognitive

mapping and narrative, identified these two processes as being primary means by which

humans place their experiences in both spatial and temporal context. In addition,

humans utilise narrative as an important cognitive mechanism to resolve inconsistencies

and to fill in gaps in our understanding. This further emphasises the importance and

influence of critical theory on this research. Turning to axiology, values and ethics are

considered to be intrinsic to the resolution of problems of the sustainability discourse. It

is argued here that engineering cannot be considered to be a values-free discipline. The

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ethical position of engineers in considering and taking into account the moral standing of

all interests in the Type 3 problem is a key feature of the approach being advocated here.

Furthermore, it is expected that engineers who embrace the change to the paradigm of

engineering practice proposed here will become active advocates of the need for such a

change.

The important point to draw from this discussion is that the research approach in this

thesis is primarily critical and qualitative, rather than quantitative in its nature. The

intention is to stimulate and advocate change in engineering practice, so that the

problems of sustainability can be resolved, not simply to further inform the decision-

making and policy formulation of others.

6.5 The case study The qualitative, critical research methodology discussed above is used as the foundation

for the case study in the following chapter. The problem-structuring devices developed

in Chapter 6 have been applied to a Type 3 problem relating to the water system of

Sydney, Australia, a large metropolis with some particularly challenging contemporary

issues regarding its water system. The approach taken was one of “action research”, with

the intention that the problem-structuring methodology be utilised, tested and criticised

to determine its robustness and its value in structuring the problem for greater

engagement of the community interests and as intervention to make a contribution to

resolution of the problem.

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Appendix 6.1 – Multi-Dimensional Conjugate Cognitive Mapping (MDCCM)

Cognitive mapping techniques are inherently reductionist – they attempt to represent

complex systems visually, so problems can be represented in pieces small enough for the

mind to be able to comprehend them effectively. Consequently, cognitive maps generally

suffer from one (or both) of two deficiencies: either they become so large and complex

that they defeat their purpose, or they oversimplify the situation, losing important

information. Bougon (1992) recognised this and created the concept of congregate

cognitive mapping. The technique described below builds on the approach initiated by

Bougon, significantly improving the way in which information is managed and presented.

Multi-Dimensional Conjugate cognitive Mapping (MDCCM) is a technique developed to

enhance the problem-structuring technique developed here which aims to simplify

representation of the problem without loss of information. It allows information to be

“conjugated” according to the similarities defined by Verma (1998), or by other

groupings which might be useful.

Building a MDCCM consists of the following steps:

• identifying all relevant aspects of the problem, describing these as words, phrases

or sentences (or diagrams, sketches, images, etc);

• these may then be grouped according to one or other of their similarities;

• “conjugation points”, which link groups are then added;

• additional problem dimensions possibly other similarities, issues, approaches etc

can be identified on transparent “layers” which can be added, either temporarily

or permanently, to facilitate decision-making or judgement.

The MDCCM can be prepared on paper, with transparent layers being added, or using

any one of a number of computer programs capable of displaying a mixture of text,

graphics and layers (or dimensions).

The technique has a number of advantages over other cognitive mapping approaches:

• it becomes practical to handle large amounts of data, particularly if computer

software is used;

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• dimensions can be added or removed as layers, depending on the level of

complexity to be represented and the degree of focus desired;

• all important, relevant information can be recorded and retrieved as needed;

• multiple perspectives and worldviews can be accommodated using different

dimensions. This can be a useful mechanism for finding differences, but more

importantly, the common ground where there are widely differing perspectives or

worldviews can be identified.

A partially populated MDCCM is represented below to demonstrate application of the

technique to the subject considered in this dissertation – see Figures 6.10 to 6.13.

Conjugate Cognitive Map

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Figure 6.10 – Conjugate cognitive map framework


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Figure 6.10 – Conjugate cognitive map framework As many aspects of the problem as possible are identified and represented on the map.

These are grouped into broad categories to give a visual representation of the problem

and principal conjugation points are identified and added to the map as shown in Figure

6.11.

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SustainabilityEconomic

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Figure 6.11 – Populating the map with issues and identifying important conjugation points – Issues dimension



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Figure 6.11 – Populating the map with issues and identifying important conjugation points – Issues dimension These may be layered also, depending on the type of problem being addressed.

Relationships are identified and further dimensions are added (Figures 6.12 and 6.13),

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Figure 6.13 –Identifying important cognitive relationships – Approaches dimension

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Figure 6.13 –Identifying important cognitive relationships – Approaches dimension representing different similarities or other aspects of the problem which are important.

As many layers as needed may be added to represent the required richness of information

– see Figure 6.14.


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BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping






Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Reductionism

Bucketand

Search-light

ExpectedUtility

Problems

Sustainability


Worldviews

Cognition

Philosophy


GameTheory




Structuring



ScenarioPlanning



SubjectiveExpected

UtilityPolicy

ManagementStyles

Engagementof Public

ValueElicitation

BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping






Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Reductionism

Bucketand

Search-light

ExpectedUtility

ProblemsProblems



Worldviews

Cognition



GameTheory




Structuring



ScenarioPlanning



SubjectiveExpected

UtilityPolicy

ManagementStyles

Engagementof Public

ValueElicitation

BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping






Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Reductionism

Bucketand

Search-light

ExpectedUtility


Worldviews

Cognition

Philosophy



Moral standing

Power

Dominance


Dominance

MedicalLegal

Leadingquestions

PowerPreferences

MoralstandingRisk

Acceptance



Neoconfucianism


ValuesBeliefs

Anarchism


Rationality



Aesthetic



Social Context



CognitionCognition




Moral standing

Power

Dominance


Dominance

MedicalLegal

Leadingquestions

PowerPreferences

MoralstandingRisk

Acceptance



Neoconfucianism


ValuesBeliefs

Anarchism


Rationality




EconomicSocial








Aesthetic




Worldviews

Cognition

Philosophy



RiskJudgment


Moral standing

Power

Dominance


Dominance

MedicalLegal

Leadingquestions

PowerPreferences

MoralstandingRisk

Acceptance



Neoconfucianism


ValuesBeliefs

Anarchism


Rationality

MoralsEpistemology

Politics


Beliefs

Behaviours

SolutionsAgreements




EconomicSocial






Social Context



CognitionCognition




RiskJudgment


Moral standing

Power

Dominance


Dominance

MedicalLegal

Leadingquestions

PowerPreferences

MoralstandingRisk

Acceptance



Neoconfucianism


ValuesBeliefs

Anarchism


Rationality

MoralsEpistemology

Politics


Beliefs

Behaviours

SolutionsAgreements



Aesthetic




Worldviews

Cognition

Philosophy



RiskJudgment


Moral standing

Power

Dominance


Dominance

MedicalLegal

Leadingquestions

PowerPreferences

MoralstandingRisk

Acceptance



Neoconfucianism


ValuesBeliefs

Anarchism


Rationality

MoralsEpistemology

Politics


Beliefs

Behaviours

SolutionsAgreements




EconomicSocial






Social Context



CognitionCognition




RiskJudgment


Moral standing

Power

Dominance


Dominance

MedicalLegal

Leadingquestions

PowerPreferences

MoralstandingRisk

Acceptance



Neoconfucianism


ValuesBeliefs

Anarchism


Rationality

MoralsEpistemology

Politics


Beliefs

Behaviours

SolutionsAgreements


Worldviews

Cognition

Philosophy



Moral standing

Power

Dominance


Dominance

MedicalLegal

Leadingquestions

PowerPreferences

MoralstandingRisk

Acceptance



Neoconfucianism


ValuesBeliefs

Anarchism


Rationality



Aesthetic



Social Context



CognitionCognition




Moral standing

Power

Dominance


Dominance

MedicalLegal

Leadingquestions

PowerPreferences

MoralstandingRisk

Acceptance



Neoconfucianism


ValuesBeliefs

Anarchism


Rationality




EconomicSocial






Sustainability

Problems


Worldviews

Cognition

Philosophy


GameTheory




Structuring


Decision-Making

ScenarioPlanning


Engagementof Public

ValueElicitation

BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping





Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Bucketand


Utility


Reductionism


SubjectiveExpected

Utility

Reductionism



Problems

Social Context



Cognition



GameTheory




Structuring


Decision-Making

ScenarioPlanning


Engagementof Public

ValueElicitation

BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping





Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Bucketand


Utility


Reductionism


SubjectiveExpected

Utility

Reductionism


Sustainability

Problems


Worldviews

Cognition

Philosophy


GameTheory




Structuring


Decision-Making

ScenarioPlanning


Engagementof Public

ValueElicitation

BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping





Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Bucketand


Utility


Reductionism


SubjectiveExpected

Utility

Reductionism



Problems

Social Context



Cognition



GameTheory




Structuring


Decision-Making

ScenarioPlanning


Engagementof Public

ValueElicitation

BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping





Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Bucketand


Utility


Reductionism


SubjectiveExpected

Utility

Reductionism


Problems

Sustainability


Worldviews

Cognition

Philosophy


GameTheory




Structuring



ScenarioPlanning



SubjectiveExpected

UtilityPolicy

ManagementStyles

Engagementof Public

ValueElicitation

BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping






Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Reductionism

Bucketand

Search-light

ExpectedUtility

ProblemsProblems



Worldviews

Cognition



GameTheory




Structuring



ScenarioPlanning



SubjectiveExpected

UtilityPolicy

ManagementStyles

Engagementof Public

ValueElicitation

BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping






Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Reductionism

Bucketand

Search-light

ExpectedUtility

Problems

Sustainability


Worldviews

Cognition

Philosophy


GameTheory




Structuring



ScenarioPlanning



SubjectiveExpected

UtilityPolicy

ManagementStyles

Engagementof Public

ValueElicitation

BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping






Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Reductionism

Bucketand

Search-light

ExpectedUtility

ProblemsProblems



Worldviews

Cognition



GameTheory




Structuring



ScenarioPlanning



SubjectiveExpected

UtilityPolicy

ManagementStyles

Engagementof Public

ValueElicitation

BoundedRationality

ProspectTheory

ImageTheory

CognitiveMapping






Anarchy


Language


Clocksand

Clouds

DifferentOntologies

Reductionism

Bucketand

Search-light

ExpectedUtility

Figure 6.14 – Add as many dimension as need to fully represent the problem issues and relationships. The information gathered in the critique is being used to inform decision-makers of what

other investigating work needs to be done to address the issues highlighted in the

structuring approach.

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Chapter 6 : Development of the Problem-Structuring Approach

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Transcript of Chapter 6 : Development of the Problem-Structuring Approach