Dorothy Leonard-Barton, in K. M. Patton/Technological forecasting & Social Change 72 (2005) 1082 1093 1084 her Wellsprings of Knowledge 5, maintains that the process of introducing external streams
of knowledge into a company is just as important as managing information flows within the company.
and imports the knowledge that he or she develops into the decision-making process intuitively. Scanning processes are tools for systematizing the collection of early signals of change
and knowledge for an organization can begin in earnest. Researchers and analysts will need to examine carefully the clusters of abstracts
Only the Paranoid Survive, Doubleday, 1999.5 Dorothy Leonard-Barton, Wellsprings of Knowledge: Building and Sustaining the Sources of Innovation, Harvard Business school Press, Boston, 1995, p. 135.6 Eric D. Beinhocker, Sarah Kaplan, Tired of strategic planning?
and economic development (see for example the FOREN Guide 5) with a stronger emphasis on indigenous strengths and tapping local tacit knowledge.
10.1016/j. futures. 2010.11.003 the planning and emergence of knowledge-based clusters is informed often by a vision;
technological knowledge and/or the capabilities to innovate. This can be by means of grants, loans, fiscal incentives, consultancy support,
for example, knowledge clusters. An early example of this concept was the Finnish Governments knowledge cluster programme of the mid-1990s.
Here the aimwas tomobilise actors and networks by reference to the research focus of their activities rather than to the location inwhich these activities are carried out.
Knowledge cluster programmes allow a focus on areas of an economy in which there is potential for innovation
Cariola and Rolfo link this to an evolution from hierarchical organisational structures with tangible assets to network knowledge-based organisational forms as a backdrop to the formulation of innovation policy 36.
of shared knowledge and examination of alternative futures. Foresight activities are seen also increasingly as crucial functions in order to prepare for the future
The creation of new, especially shared knowledge is challenging, in particular, when the people participating in the foresight process typically have heterogeneous backgrounds,
Anticipation of intelligence (or knowledge) is a contribution to improve the knowledge base for the designing of policies.
and technology development by using the knowledge generated from roadmap activity. In the UK, the Development, Concept and Doctrine Centre (DCDC) a Directorate General of the Ministry of Defence (MOD) conducted a foresight process that produced as a key output a report‘‘the DCDC Global Strategic Trends Programme
Most of the projects we analysed have important informative functions in sense that they aim to provide new knowledge for better understanding of issues and of their future implications and challenges.
but mainly to draw conclusions on how foresight can be improved as an instrument contributing to knowledge creation for policy and decision-making in more general.
A knowledge-based perspective A. Eerola A i. Miles b a VTT Technical research Centre of Finland, Espoo, Finland b Manchester Institute of Innovation research, Manchester united Kingdom 1
Learning implies the production and reproduction of knowledge and this in turn implies that FTA necessarily involves knowledge management
whether this is formally acknowledged or more implicit. This knowledge management has to confront the challenges created by FTA's call for engagement across different disciplines, research traditions,
and professional activities and across potentially competing corporate, sectoral, and public interests. Futures 43 (2011) 265 278 A r T I C L E I N F O Article history:
and professional activities FTA then necessarily involves knowledge management (whether this be formal or implicit); and this knowledge management has to confront the challenges created by FTA's call for engagement across different
and across potentially competing corporate, sectoral, and public interests. This paper explores the consequences of this view of FTA
and how the roles of various FTA METHODS and tools are seen in terms of knowledge management. It goes on to discuss the implications that follow for FTA design,
The challenges of participatory knowledge management are seen to be particularly important ones to tackle. 2011 Published by Elsevier Ltd.*
10.1016/j. futures. 2010.11.005 2. FTA and knowledge management Talking about FTA in terms of‘‘knowledge''may seem to risk dealing in oxymorons.
so how can there be have knowledge about it unless we believe in divinely inspired prophets
deploying, using and fusing and, yes, even creating knowledge. The whole point of FTA is to better inform our decisions,
and this involves knowledge of historical and contemporary dynamics and developments, and what their implications may be for future circumstances.
and we can bring knowledge to bear on determining who these experts are, how valid their methods are,
Another sort of knowledge we can have is knowledge about the views that others have (or profess) about the nature of the current situation,
This sort of knowledge may be little more than a specialised form of opinion poll analysis: many Delphi studies do take this form,
Bell and Olick 2 reframe the discussion about‘‘knowledge of the future''by arguing that we posit the future
but also differences from, the ways in which we create knowledge about the past and present.‘
‘Knowing'the future is thought better of as knowing about future possibilities, rather than knowledge of the future.
and explication of knowledge surrogates, and their use to support decision-making. Posits are such‘knowledge surrogates,
'for Bell and Olick 2. We can have knowledge about the posts themselves. We can examine their plausibility and limits, their internal consistency and conformity with models and data,
the extent to which they are consistent with expert judgement, etc. Posits are based on knowledge of (or assumptions about) past and present,
and analysis of posits and their implications for action requires examination of this underlying knowledge base,
its limits and quality, and its use in the generation of posits. The idea of posits provides us with a label for specific sets of knowledge.
These are the sets of knowledge that are to do with the consequences that our models of situations
and systems imply, when we bring various assumptions to bear about how these situations and systems may evolve into the future.
Various tasks for knowledge management in respect of such‘‘knowledge surrogates''can be identified. Posits need to be created, explicated, communicated;
or at least with the decision-makers that the exercise is intended to inform the scope of knowledge management (KM) has to extend 1 The application of evolutionary theory within theology has led to notions of an‘‘evolving god''(or gods) too,
whose knowledge of the future may well be far less than omniscient, and whose acts of creation are undertaken for the purpose of learning.
It will require managing knowledge in a wider community albeit that the precise community in question may have been constructed partly by the exercise itself.
and structuring of this community is itself a task that requires knowledge. And this knowledge involves knowledge management too
concerning, for example, the methods of stakeholder mapping that are employed, the ways in which suggestions for participants and dissemination approaches are elicited. 3. Methods and tools So,
Practically any source of insight into the dynamics of science and technology (S&t) their production, communication, application can be utilised as knowledge inputs into FTA.
These all contribute to the knowledge base and methodological development of FTA 3 7. The result is a proliferation of tools.
the accumulation and integration of knowledge about different tools and approaches is very uneven. Many (probably the great majority of) FTA practitioners are familiar with only a limited number of these tools.
But huge knowledge gaps are apparent, often stemming from the fact that much FTA work is conducted under pressure to provide results to inform urgent decisions.
and thereby producing foresight knowledge (some of this will be posits, in Bell and Olick's terminology.
the (iv) translation and (v) interpretation of this knowledge to create understanding of its implications for the future of the organisation in question (further posits.
subtask (v). She portrays this as the conversion of translated knowledge into understanding. It uses of methods such as roadmapping and scenario development relevant to the particular organisation/stakeholder.
which is liable to impede the effective use of the knowledge and posits generated. There is a missing KM link, in effect,
in terms of knowledge and posits, we can interpret as follows. The first dimension reflects how far the method relies on eliciting, working with,
and synthesising expert knowledge, as opposed to mobilising and fostering interaction within stakeholder groups. The second dimension reflects how far the method involves formal analytic techniques such as statistical trend
Some combination of methods that span these dimensions is recommended as helping maximise the scope for FTA to draw on expert knowledge,
The two dimensions might be seen as reflecting the balance between knowledge from experts and knowledge within communities,
and of sources of specialised knowledge about the issues and actions in focus, than characterised many earlier futures studies.
a matter of participatory democracy as commonly understood though such FTA could be an important contributor to establishing more deliberative democracy in S&t policy areas that have on account of the expert knowledge associated with them historically been dominated by vested interests and technocratic elites.
Enlarging the available knowledge base. This can be seen as a reflection of the growing complexity of S&t decisions,
which is associated with such factors as the combination of multiple scientific and technological knowledge bases in many 7 Naisbitt 36,
and with large-scale use of new technological knowledge). Even technocratic FTA has to confront the likelihood that no single organisation will itself contain expertise on all of the matters that bear intimately on a specific set of S&t issues it will be necessary to go out to a wider set of communities.
The knowledge and mental models of practitioners and stakeholders may have to be brought into play in such cases.
Methods for identifying key sources of knowledge and eliciting information from them in a form that can be used readily,
These include issues that centrally involve the application of new knowledge as in the case of genomics (controversies over stem cells, use of genetic information, etc.;
the aim is embed to the knowledge that has been generated in the programme into theirownorganisations and practices.
As well as knowledge being widely distributed, so are power and action. Of course both are distributed unevenly: some actors have more access to sources of information
providing and working with relevant knowledge to build capabilities for better action. Since these decisions and actions involve many actors,
This is liable to gowell beyond the knowledge that can be gained from poring over a report, let alone just reading an executive summary.
butwill be carriers of this FTA knowledge into their own organisations, working to create decisions
and is also likely to increase the commitment to making use of the foresight knowledge).
The senior actorswill thus be primed to receive the detailed knowledge that is gained by the more junior actors.
Jaspers et al. 16 contrast two‘‘ideal types''technological knowledge management and participatory knowledge management (TKM and PKM, respectively.
develop and use knowledge, coming close to Boisot's idea of social learning cycle (17,18). Taking account of cultural factors, values and opinions,
Discussions of knowledge management, and efforts to plan relevant systems, may well focus on one or other of these polar types.
and deploying the knowledge and posits that they make available and that are generated during the FTA PROCESS.
and knowledge One of the most influential contributions to thinking about organisational learning and KM has been the model of the dynamics of shared knowledge creation developed by Nonaka and Takeuchi 19.
combination and internalisation) represent a knowledge cycle undertaken in the course of organisational learning. Two dimensions underlie the Nonaka and Takeuchi 19 account:
one is essentially ontological is known the knowledge at the individual level only, at the group level,
and the other is more epistemological is the knowledge tacit or explicit? In fact, a spiral of several successive cycles is needed usually for innovation
and FTA PROCESSES moving between so-called tacit and explicit knowledge. Interacting individuals share their knowledge, linking, presenting and discussing information and insights with each other.
This also enables them to internalise this knowledge through interpretations in specific contexts. This is highly reminiscent of
what takes place in FTA, even if the four knowledge conversion modes in the Nonaka model do not correspond precisely with the three steps of Horton and Weick,
or the five of Saritas. While there is great value in the distinction between tacit and explicit knowledge
a more practical distinction in the context of FTA would perhaps be the distinction between knowing individuals
and other such external manifestations and products of knowledge as suggested by Dawson 20. Dawson also reformulates the Nonaka framework accordingly (Fig. 1),
as representing movement between knowledge (which requires knowing agents, and is embodied thus human), and information (that can be codified
along with ideas about knowledge being contained''in things and knowledge flows happening (e g. in technology transfer), that it is hard to shift.
The critique of this terminology is mentioned here to highlight‘‘knowledge''as a property of knowing individuals.
This emphasis is highly relevant for FTA. Individual actors in FTA organise information in ways that are relevant to their purposes practical problems, conceptual challenges,()TD$FIG Knowledge Information Knowledge Socialisation:
Transfer of knowledge between people (through interaction rather than mediated through captured information) Externalisation: Capturing people's knowledge by rendering it as documents or structured processes Informationinternalisation:
Knowledge acquisition learning how to use models, formulae, equipment, methods etc. Combination: systematising and/or translating formalised concepts into new frameworks, procedures, etc.
Fig. 1. The knowledge cycle. Source: Dawson 20 after Nonka and Takeuchi 19.9 For a much fuller survey of the field,
though one with a high orientation to IT solutions, see Alavi and Leidner 38. A. Eerola,
I. Miles/Futures 43 (2011) 265 278 271 understanding themselves and their worlds, or whatever.
Codifying this knowledge (and posits) as written insights, sets of procedure, and the like, provides information resulting from the knowledge.
This information may be an account of the knowledge and/or posits, or may simply imply such an account (which an observer equipped with relevant knowledge will be able to reconstruct).
Different agents may interpret and organise the information in different ways, deriving different sorts of knowledge from it.
For example, a detailed account of a scenario represents a codification of posits, from which it is possible to reverse engineer at least some of the knowledge that informed the scenario work.
Good FTA practice will make it easy for later users of the work to assess the validity of its knowledge base
and the derivations that have been made from it. What then of concepts like‘‘knowledge transfer''?''Since knowledge is not a‘‘thing''out there,
it cannot simply be transferred like a document or technological artefact. People can gain knowledge from the act of interpreting, reading, reverse engineering texts and other artefacts;
and they can also gain knowledge by examining nature. Knowledge is deposited not simply in texts and machines,
or embedded in the natural world, for that matter. Knowledge is achieved through an interrogation of these things.
Well-designed texts are particularly useful in how they have been designed for interrogation. Where the issues at hand are complex,
involving overlapping fields of expertise, ill-defined, and so on as is the case for many of the core topics that FTA addresses design of such texts can be very challenging.
This is one reason for the stress on stakeholder engagement. Mutual learning can be accomplished in the interaction between knowing agents.
Briefly put these agents engage in a process of comparison and modelling they can determine to what extent each is interpreting given material in the same way,
What is transferred is information about knowledge, rather than the knowledge itself. New knowledge and posits is constructed on the basis of this new information and past knowledge.
The agents in question may well make use of technological aids and texts notably whiteboards and flip-charts on which diagrams
The joint construction of knowledge by participants may result in a great deal of the key knowledge being shared within the team or workshop involved.
The idea that knowledge development takes place through a (typically clockwise) multi-cycle spiral movement through these different SECI cycle categories is a powerful heuristic for explicating FTA EXERCISES and activities.
to understanding and guiding the shared knowledge creation of key actors (industry, academia and policymakers) in the context of Nordic foresight activities 21,22.
When the FTA PROCESS involves a wide range of key actors in the case of the Nordic H2 energy foresight coming from several countries there are special challenges confronted in shared knowledge creation (even in agreeing upon which of Bell's‘‘posits''to explore
The SECI framework portrays the knowledge cycle of organisational learning as a dynamic interaction process.
The design and planning of the FTA can be interpreted as the preliminary‘‘S''phase of the knowledge cycle.
In the Nordic H2 energy foresight, the appropriation of the knowledge from the foresight process into various stakeholder organisations was seen as being accomplished through such activities as pilot projects
The complexity of FTA PROCESSES means that they can involve application of similar techniques for different purposes, at different points in the foresight knowledge cycle.
and necessarily internalising the knowledge and posits being developed in the foresight process, relating these to the interests and goals of their organisations.
The boundaries between the phases of the SECI knowledge cycle may thus be rather permeable.
We can even see some of the more ambitious FTA METHODS as themselves involving several or most of the knowledge conversion phases of the SECI spiral.
which knowledge is exchanged and posits developed and assessed. The various phases of knowledge A. Eerola,
I. Miles/Futures 43 (2011) 265 278 272 management in a scenario workshop are discussed in the next section,
in order to illustrate the relevance of thekmapproach even in the context of individual/specific FTA METHODS. 6. Scenario workshops as knowledge processes Scenario workshops typically feature a sequence of activities.
identify participants for the scenario workshop it is vital to include the right range of interests, knowledge and expertise,
and often gathers knowledge it may be undertaken with KM objectives firmly in mind, or this may be more implicit.
Delphi or other()TD$FIG Tacit knowledge Tacit knowledge Explicit knowledge Explicit knowledge Tacit knowledge Tacit knowledgee g d e l w o n k t i c i
l p x E e g d e l w o n k t i c i l p x E Field building Linking explicit knowledge Dialogue Learning by doing Socialization
on foresight process and results Conference papers Project website Fig. 2. Different foresight elements in a dynamic process of shared knowledge creation, a SECI perspective.
''often the two knowledge activities are hard to demarcate. We typically ask participants to brainstorm factors that are important under each of the STEEPV headings in turn,
and presenting their own disciplinary and practitioner knowledge. They have to work together to cluster ideas
The scenario framework can be a valuable tool for encouraging people from very different backgrounds to apply their knowledge in new ways.
A major task will be to move other parties through their own knowledge cycles, so that they can seriously incorporate the thinking of the workshop in their own decision-A. Eerola,
they will have much deeper knowledge of the underlying knowledge base, the assumptions and decisions that have gone into the posits,
Understanding the knowledge objectives of the FTA PROCESSES we are embarked upon, and ensuring that the design is conducive to achieving these objectives,
Here we have related methods in FTA to knowledge and knowledge management issues. Even a cursory examination of the KM literature will confirm several things.
Knowledge management can also draw on social networking and other tools to locate people with specific types of knowledge input.
Social learning and‘‘PKM''elements of FTA can be augmented by use of IT, though this may require careful design
and using knowledge and posits. Telepresence and virtual reality systems are enabling much more intensive person-to-person interaction through IT systems.
and sorts of knowledge and posits that result from them. Different stakeholders have not only different interests,
but they also have different modes of access to and use of knowledge: FTA practitioners thus confront the problematique of diverse social goals and power arrangements,
In terms of how knowledge is assessed in FTA, a number of points can be made. Experts (engineers, designers, social analysts, political actors) are seen as possessing particularly valued-and sometimes privileged knowledge.
They may thus be deferred to, with their claims and posits left unchallenged. It can require considerable technical expertise
on the basis of posits about technology development (how realistic these are given current knowledge and activities) and about possible outcomes (have similar things actually occurred).
It will be the task of the‘‘knowledge manager''to design systems that can facilitate this,
of knowledge management in participatory foresight: the case of‘Future',Seville, First International EU US Seville Seminar on Future-oriented technology analysis, 2004 (available at http://forera. jrc. ec. europa. eu/fta/papers
A Framework for Learning in Organizations, Institutions and Culture, Routledge, London, 1995.18 M. H. Boisot, Knowledge Asset:
The Knowledge-creating Company, Oxford university Press, Oxford, 1995.20 R. Dawson, Developing Knowledge-Based Client Relationships, Butterworth-Heinemann, London, 2000.21 A. Eerola, B. H
A Fantasy of Love and Discord, Secker and Warburg, London, 1944.31 C. Warden, An application of some knowledge management concepts in foresight, Technology foresight for Organizers, 2007, Module 1:
I. Miles, Eliciting experts'knowledge: a comparison of two methods, Technological forecasting and Social Change 73 (6)( 2006) 679 704.34 H. Linstone, M. Turoff (Eds.
Create Knowledge and Make Decisions, Oxford university Press, Oxford, 1999.36 J. Naisbitt, Megatrends, Warner Books, New york, 1982.37 L. Georghiou, J. Cassingena Harper, M. Keenan,
knowledge management and knowledge management systems: conceptual foundations and research issues, MIS Quarterly: Management Information systems 25 (1)( 2001) 107 136.39 T. Rogers-Hayden, N. Pidgeon, Moving engagement‘‘upstream''?
and situations as a result of various factors including globalisation, environmental concerns, more knowledge intensive work and lifestyle.
a base of knowledge and abilities that are technically feasible and ethically desirable is needed. Implicitly, sustainable development recognises the need for technology to develop solutions that conserve the Earth's resources,
society and corporate activity A central assumption behind innovation systems theory is that knowledge is the fundamental resource in the modern economy
and claims for novel forms of public involvement and for democratisation of knowledge, raise the need to look at how perceptions and values,
and openness of decision making procedures to stakeholders while acknowledging the relevance of knowledge other than science,
such as experimental, ethical and social knowledge. The foregoing are shown in the uppermost layer of the pictorial metaphor (see Appendix)
and the role of experimental or local knowledge. Thus issues underlying social reaction to new technologies and the undisclosed ways in which industries take decisions must be resolved.
and produces issue-specific knowledge through dialogue, creating joint learning between users and producers, knowledge generation and shared sense of commitment.
Not surprisingly, FTA has relevance in all human activities where there are collective stakes 43. In the 2006 FTA Conference, the FTA COMMUNITY realised the need to address the imperative of improving the two-way linkage between knowledge and the building of a‘common world'.
'To do so a vivid debate took place in trying to grasp the C. Cagnin et al./
10.1016/j. futures. 2010.11.007 Foresight knowledge base regarding the directions and catalysts that are prompting our global future and its various contingencies and uncertainties.
which may be amenable to changes according to one's strategic choices, investments, R&d activities or foresight knowledge and strategies.
Examples of trends by category A b c Society & Culture 66 Growth of knowledge/access and need for management Aging/labor force ratio creating tensions Negative prospects from genetic manipulation‘‘Privacy loss''as 21st century externality Pandemic risks increase Genetically designed children will be possible Dematerialisation the West
Strong classes between cultures, intensification of conflicts between cultural classes Population boom & high competition in job markets Decline of knowledge grounded in local society and history because of less direct human interaction
law and life styles Dependence on anti-factual information, failing roots of knowledge and understanding Declining male fertility Human cloning Science & Tech. 33 Ubiquitous connectivity web
identifying common strategic choices and questions for knowledge, Science and Public policy 37 (1)( 2010) 7 18.2 S. Rijkers-Defrasne, E. Amanatidou, A. Braun, A. Pechmann,
Hence, some FTA outputs may enter the reservoir of knowledge where it may be drawn on at some time in the future.
identifying common strategic choices and questions for knowledge, in: FTA Conference, Seville, 2008.3 J. Calof, J. Smith, Critical success factors for government led foresight, in:
Furthermore, he contributes to knowledge transfer from research into teaching. Vicente Carabias is the corresponding author
to provide knowledge for decision-making. Potential effects of policy interventions should be assessed; risk and uncertainties should be reduced;
Key criteria for the categorisation of methods are their abilities in dealing with different types of missing knowledge.
or incomplete knowledge in transport panning need to be addressed. Although, from a theoretical perspective, it makes sense to state that any intervention may have catastrophic unforeseen consequences,
The question then is how to provide policy making with the best available knowledge about the impacts of interventions (that achieve the intended goals
Positions differ on such typologies of uncertainties and the relationship between knowledge types and uncertainty.
''which involved effects for which knowledge and parameters are available to assess the likelihood of an outcome,
While risk is a quantifiable parameter where there is both significant scientific knowledge about the probabilities of the occurrence of certain effects and reliable knowledge about the nature and extent of possible harm,
uncertainty is characterised by a limited quantifiability, a lack in knowledge, epistemic uncertainty/or unresolved scientific controversies.
''which arise from a lack of knowledge about the appropriate model or theory that might be relevant for a particular phenomenon,
whereas a general differentiation is made between uncertainty due to variability and uncertainty due to limited knowledge of the system.
one must be aware that different levels of knowledge exist. The authors differentiate between four levels;
Against this background, we propose to differentiate between three levels of knowledge (as also presented in Table I:
Solid knowledge is already available. The relationship between cause and effect and the contributing factors are understood well known
maybe some basic knowledge or some evidence about the effects of certain interventions is available,
There is no knowledge about potential effects or cause-effect relations. It is the sheer complexity of the system that might lead to the ex ante assumption that something unintended could happen.
and methods are able to address these types of knowledge. In the following chapter a categorisation is introduced that helps to better understand the limits and potentials of tools and methods for addressing knowns, known unknowns and unknown unknowns.
which is rooted often in the knowledge-base of decision making 1. 3. The methods:‘‘‘‘structurally open''versus‘‘structurally closed''The transport system is embedded in the broader social, economic and environmental systems.
and the nature of its impact, are understood well Related concept Great uncertainty Uncertainty Riska Strategies Build awareness about reasons for fundamental limits to knowledge Attempt to anticipate,
or agent Improve knowledge about causal relationships and their quantification Reduce exposure to the hazardous agent Strategy type Precaution Precautionary prevention Prevention Examples Car friendly urban policy in the 1960's leading to congestion several years
at the other extreme, provide more punctual knowledge from rather different areas and are built mostly on experience,
anecdotical evidence and tacit knowledge (for example brainstorming or open space). Transport models show a certain slice or cut out of the web, with some selected nodes and the linkages between them.
In relation to the typology of levels of knowledge described in chapter 2 it can be concluded that models are focussed mainly on improving knowledge in the field of knowns.
which they seek to PAGE 286 jforesight jvol. 14 NO. 4 2012 integrate knowledge of experts, stakeholders and also of laypeople in the process of policy making.
strongly shaped by qualitative elements causal relationships between parameters Integrate knowledge of experts, stakeholders or lay people Mainly quantitative Help to structure arguments
the process of reflection and systematisation might also improve the knowledge of known unknowns. However, these are rather side effects that do not emanate from the main purpose of the methodology.
and deepen knowledge in a certain field. They help identifying uncertainties, blind spots, contradictions or dilemmas.
and Figure 1 Appropriate FTA METHODS for addressing different types of knowledge PAGE 288 jforesight jvol. 14 NO. 4 2012 help to turn such unknowns into knowns.
It could have been discussed to what extent there is a lack in knowledge which needs further elaborating before a simulation (a structurally closed method) can lead to results accepted by both parties.
In general, these assumptions and simplifications are based on knowledge of different type. Whereas some phenomena are well known
problems of missing knowledge can be clustered in these categories. This sets the basis for the problem-oriented categorisation of FTA METHODS which was introduced above.
or developments where knowledge about the system and its internal structures is rather weak. The latter is falling into the categories of known unknowns
they seek for the integration of knowledge of different quality and character, for example in highly interdisciplinary contexts.
only selective knowledge can be gained on social phenomena through quantification due to the fact that the models normally only consider a reduced amount of variables that describe social realities (Grunwald, 2009).
on their potential role for gaining knowledge that is needed for anticipating unintended effects of policies.
it does not provide directly for new knowledge; even if applied properly, many problems will remain; the future is
providing orientation knowledge for solving problems in the transport sector. However, a broad range of literature exists,
It is linked often to the concept of‘‘Mode 2''knowledge production (see Gibbons et al. 1994). ) The structurally open/structurally closed approach (see chapter 3) could be discussed within this context
Gibbons, M.,Limoges, C.,Nowotny, H.,Schwartzman, S.,Scott, P. and Trow, M. 1994), The New Production of Knowledge:
''Technological forecasting and Social Change, Vol. 72, pp. 1064-9. Grunwald, A. 2007),‘Working towards sustainable development in the face of uncertainty and incomplete knowledge'',Journal of Environmental policy and Planning, Vol. 9
Hessels, L. K. and van Lente, H. 2008),‘Rethinking knowledge production: a literature review and a research agenda'',Research policy, Vol. 37, pp. 740-60.
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