Model

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Model (593)
Modelling (185)

Synopsis: Model:

content and process. 3. Models and voices This session concentrated on the combination of expert opinion with qualitative techniques.

This approach should provide enhancement to models in the future. The other major discussion focussed on experts,

However, although the dominant model of foresight pursues a more modest level of aspiration than forecasting,

of the scope of forward-looking exercises can be interpreted as a reflection of the abandoning of linear models of technological change and the adoption of a systemic understanding of socio-technical change.

Therefore, a consolidated integration of analytical and exploratory scientific methods (e g. system analysis and modelling) on the one hand and of participatory processes and interactions with experts and stakeholders on the other would help enhance the scientific credibility of foresight results. 7‘Environmental scanning'along the lines

This work may also be supported usefully by (normally simple) simulation models. It is not uncommon that the scenario ideas derived at the workshop have to be modified considerably at this stage,

In back-office work also the same types of simulation models as in Phase 3 can be useful. 476 E. A. Eriksson, K. M. Weber/Technological forecasting & Social Change 75

Models still need to be developed of how to establish AF as continuous learning activities within public and private institutions.

The strength of AF could be enhanced further by building where appropriate on new modelling approaches.

An example in this spirit is the Pardee Center at RAND who work with large scale modelling of

but the financial resources necessary for this approach are rarely available in the settings we are used to working in We also tend to prefer a larger role for verbal reasoning as opposed to mathematical modelling

Robust Portfolio Modeling Available online at www. sciencedirect. com Technological forecasting & Social Change 75 (2008) 483 495 Corresponding author.

and multi-criteria analyses based on Robust Portfolio Modeling (briefly RPM Screening; see 9, 10. Particular attention is given to the development of a foresight design that responds to scalability requirements (e g.,

which is a variant of the Robust Portfolio Modeling (RPM) methodology for the analysis of innovation ideas and innovative concepts 9, 10,18, 19.

In technical terms, RPM Screening is based on an additive preference model where the overall value of an issue is expressed as the weighted sum of its criterion-specific scores.

Therefore, in the model, it was assumed that each issue, if pursued, would consume an equal amount of funding resources.

Change 74 (5)( 2007) 608 626.10 J. Liesiö, P. Mild, A. Salo, Preference programming for Robust Portfolio Modeling and project selection, Eur.

Policy 1 (1)( 2004) 70 88.18 J.,Liesiö, P.,Mild, A.,Salo, Robust Portfolio Modeling with incomplete cost information and project interdependencies, Eur.

Older attempts at planning the future by developing heuristic models (in the sense of futurology) were based on the assumption that the future is predefined as a linear continuation of present trends 12,13.

matching policy instruments and methodologies Innovation surveys Econometric models Control group approaches Cost benefit analysis Expert panels/peer review Field/case studies Network analysis Foresight/Technology assessment

Construction of an econometric model based on theoretically defined relation of regulations and standards and goal variables;

This pattern supports again our conceptual model by highlighting that terminology and measurement and testing standards are especially relevant for the organisations focusing on basic research,

Nanotechnology is still in an emerging phase, according to our conceptual model. The current standardisation activities are focused still on terminology and measurement and testing standards.

Technical paradigms are‘models 'and‘patterns'for finding solutions to selected technological problems, based on selected principles derived from natural sciences and on selected material technology().

Van den Belt and Rip 36 extended the Nelson Winter Dosi models for the late 19th synthetic dye industry,

This model argues that a path comes into existence behind the backs of all actors concerned

This model seeks to conceptualise path dynamics both at the actor and aggregate level (similar to technical paradigms).

This model has a crucial advantage: by repositioning the notion of path as something that is evolving/emerging in real-time,

and entanglements. 2. 2. The models of path used in this project For this project we draw on the notion of socio-technical path in its two forms:

the agreement being that new models need to be sought. For innovation chain 3 this is indeed a challenge.

Policy 6 (1)( 1977). 36 H. Van den Belt, A. Rip, The Nelson Winter Dosi model and synthetic dye chemistry, in:

Logic model; Networking; Actors'alignment 1. Introduction The present article presents results to date2 from research leading towards the production of a Phd thesis entitled Assessing the contribution of Foresight to a more participatory knowledge society.

Given this, there is need to develop a model capable of describing and understanding how this happens.

A model is needed thus that links all the different variables and reference levels. In this paper, a‘logic model'approach is used to develop an‘objectives hierarchy'describing the relationships between higher level goals,

such as the evolution of knowledge societies and participatory governance systems, and the lower level sets of goals that have to be attained

a‘logic model'approach is used also to provide checklists of the foresight inputs and activities likely to lead to the attainment of both lower and higher level system goals,

and identify those elements affected by foresight exercises can be regarded as a generic objectives model for foresight exercises likely to contribute to a more participatory‘knowledge society'.

to develop an impact assessment framework based on a‘logic model'approach which links the generic goal of a participatory knowledge society with the reported impacts of framework exercises.

Typically, logic model approaches start with specific programme goals and objectives and attempt to identify paths to potential goal attainment by treating foresight programmes as systems comprised of a number of basic elements, namely context, actors, processes

and b. 7. From the impact assessment framework to the logic model The above framework can be enriched further by findings from studies of other foresight exercises in different countries,

a logic model approach 18 can be used to build an impact assessment model incorporating the two previous models illustrated in Fig. 3a

and b. This model is depicted in Fig. 5. 8. Impact area specificity: networks and actor alignment Given the peculiar nature of the task at hand, namely the search for diverse impacts (from changes in social capital to more informed publics and better networking) that may

A model is needed thus capable of explaining the interdependencies and interrelatiionship between foresight system elements such as actors, processes, inputs, outputs and impacts,

The model presented in Fig. 3a and b helps to identify the main internal criteria

it is essential to complete the model with findings from other foresight exercises in different countries,

This model can then direct the development of a common impact assessment framework based on the‘logic model'approach.

and a series of interviews with foresight specialists to complete the development of the model describing the dynamics of foresight exercises in different contexts.

Using Logic models, The results of a study exploring how logic models can be used to develop a methodological framework for the high-quality assessment of IST-RTD effects at the Strategic Objective level, Commission Contract No 29000,2006. 19 W. W. Powell, in:

B. M. Staw, L. L. Cummints (Eds. Neither market nor hierarchy: network forms of organisation, Research in Organisational Behavior, vol. 12,1990, pp. 295 336.20 L. Blatter, Beyond hierarchies and networks:

Second, a huge diversity can be observed among continents (note the differences among the broad models of higher education e g. in the US, Asia and Europe), across countries on the same continent,

In short, that was the Humboldtian model of universities: assuming a unity of teaching and research, based on the idea of higher education through exposure to,

6. Further proliferation of the already existing diversity of governance and management models, and more pronounced professionalisation of university management.

There is already a wide variety of governance models (different ways and weights of involving stakeholders:

The diversity of governance and management models, therefore, is likely to further proliferate, even inside the group of similar universities,

Finland and Sweden points to the possibility of a‘reformed European socioeconomic model'46,47. b This vision requires an efficient co-ordination of a number of policies,

Thus, the method itself should not be judged by the choice of these simplified types of universities, taken as somewhat arbitrary‘inputs'for‘modelling'.

close co-operation with businesses Some of the‘elite'universities are adapted already well to this model,

The Humboldtian model of universities higher education and basic research as almost inseparable‘Siamese twins'is still a prevailing notion in many professors'and policy-makers'mindsets.

Policy 27 (6)( 1998) 569 588.46 K. Aiginger, Copying the US or developing a New European Model policy strategies of successful European countries in the nineties, paper presented at the UN

The essence of Cunningham's model is that the application of hierarchical random graphs of technology characteristics to questions as complex as:

enables a probability model to be constructed that anticipates novel combinations of technologies. Using this model he identified a range of technology changes associated with new standards for accessible internet applications within 100days of their emergence and without prior reference to the individual technology morphologies pathways progression.

Imagining the prospects if this technique can be developed more widely conjures up exciting possibilities for the anticipation of future innovation system developments.

This implies a renewed dedication to alternative exploratory modeling, robustness analysis and many of the other similar tools referenced below in the papers and a technical note.

Thus, exploratory modeling is used to explore Technological forecasting & Social Change 76 (2009) 1138 1149 E-mail address:

In addition, the paper outlines several important caveat about the use of these models in forecasting new technology:

the model lacks a model of the actor; full validation of the model requires a longitudinal analysis;

missing links may signal poor quality source materials; and content scoring remains a subjective process. 2. Application to distributed design environments Our purpose in exploring this topic is to better consider the information needs of designers.

Therefore, without a generative model of the data, the interpretation of the data may not be robust.

Using the model is a two-part process of simulating a range of possible networks specified by the model,

In the following section we provide a brief and qualitative account of this model. Extensive technical details of this data structure are available in the literature on complex networks.

while the generative model is connected a graph, specific realizations of the model may be disconnected. Hierarchical random graphs such as the one presented in Fig. 1 are generative models,

meaning we can use the model to infer the likelihood that any given realization will be generated by the model.

Realization 1 is a more likely representation since the most of the high probability links are observed,

and few of the low probability links are observed. This network configuration should be expected to be observed 4. 3%of the time,

According to the specification of the model there may be little or no hierarchical structure, or a network which is structured richly across multiple layers.

ð1þ 3. 4. Model search process The model simulation and fitting process allows a comprehensive search process for small models.

The sufficient statistics for the observed network can be calculated. Every possible network consistent with the data can be enumerated,

Nonetheless, a systematic technique for searching through the space of models is still necessary. A Monte carlo simulation provides a systematic search process which guarantees several desirable properties.

The search procedure guarantees no degradation in model fit as the search progresses. The Monte carlo simulation invests more computational results in the best available models,

thereby driving the search to the most promising possibilities. Gill 25 provides a relevant and comprehensive account of Monte carlo simulation for data analysis.

which can be interpreted only in light of a more elaborate model of the data. A concluding section of the paper reflects upon the sociology of science,

scripting languages (Activex, Java Applets and Visual basic Script), document models (DOM and XHTML), alternative implementations of Ajax (using JSON and IFRAME),

The Monte carlo simulation procedure evaluated a range of competing solutions to the model. There are many common features shared among the set of best solutions of the algorithm.

Nonetheless, the principal virtue of this hierarchical graph approach is the ability to use this probability model to anticipate novel combinations of technologies.

& Social Change 76 (2009) 1138 1149 As seen in Table 3 the model anticipates a threefold combination of Internet explorer, rich Internet applications and the World wide web consortium (W3c), with a likelihood of 81%.

through use of a model which anticipates architectural evolution. Furthermore, the structured representation of the data may help identify areas where competences may need to be strengthened further or even completely restored.

as provided by machine learning models and delivered by decision support systems, may contribute to an open innovation paradigm where firms work together as part of an extended technological network 11.

and case studies. 6. Interpretations from the philosophy and sociology of science The hierarchical random graph is one possible model of science, technology and innovation data.

whether such a model is consistent with what is postulated about the sociology and epistemology of science.

The goal in doing this survey is neither to validate the use of the model,

The hierarchical random graph model is missing a model of the actor. In other words, it attempts no explanation of the capabilities or interests of the innovator,

Hierarchical models might be built before and after critical time periods, and the resultant predictions compared. Alternatively, a dynamic extension to the hierarchical random graph might be envisaged.

a cyclical model of technological change, Adm. Sci. Q. 35 (1990) 6045 6633.4 A l. Porter, A t. Roper, T. W. Mason, F. A. Rossini, J. Banks, Forecasting and Management of Technology

a conceptual basis for uncertainty management in model-based decision support, Integrated Assessment 4 (1)( 2003) 5 17.8 G. S. Altshuller, Creativity as an Exact Science

Des. 117 (Special B)( 1995) 2 10.15 C. Marchetti, N. Nakicenovic, The Dynamics of Energy systems and the Logistic Substitution Model, International Institute for Applied Systems analysis

infrastructure organizations are confronted with an increasing amount of future uncertainty 3 that calls for a fundamental reconsideration of the former success model, at least in three respects:(

The proposed process thus follows the model of an analytic deliberative decision making process 54. As a result, these procedures will most likely not provide very specific recommendations which can be implemented directly.

Following the model of action research 56, the project team was involved not only in devising and specifying the method

procedure and methods The steps of the RIF procedure are sketched in this section according to the phase model from Miles

and policy from linear to systemic innovation models has challenged the conventional technocratic and technology oriented forecasstin practices and called for new participatory and systemic foresight approaches 3. Also the R&d functions are moving from the basic science

which structures the information in three dimensional model (I-Space): concrete abstract, undiffused diffused and uncodified codified.

and the prescription phase utilizes the roadmapping, backasting, modelling or simulation methods 42. Altogether, a substantial shift away from the fixed modelling and management towards more contingent and participatory approaches has taken place in all FTA areas.

Possible and potential futures are examined by applying, for instance, scenario, backcasting or roadmapping methods. Among other methods and practices in the field are constructive technology assessment

and also methods for a very detailed analysis, such as index methods and strict quantitative modelling.

o data on the system being analysed and on all the associated substances, o operational model of the system under analysis, o systematic hazard identification procedure and risk estimation techniques,

The project states that a good modelling tool would help to model the future interdependencies supported by an integration of the scenario work and the systematic risk assessment. 3. 2. Managing opportunities,

A generic model of the risk assessment procedure, applicable within the Nordic countries, will initially be framed.

Background information contains, for instance, the modelling of the changes in the river flows based on the climate change scenarios.

and evaluated by modelling them either quantitatively, semi-quantitatively or qualitatively. The same kind of activity is happening in the FTA action phase.

SECI and SLC models give foresight and risk analysis studies a common theoretical ground. Both models organise the knowledge making in three dimensional space generating the knowledge from personal and proprietary to common sense and public,

from tacit to explicit knowledge through sense making and field building, dialogue and interaction. The core idea is to share the knowledge

A good modelling tool would be helpful to model the future interdependencies. Roadmap, SWOT analysis

From fixed modelling and management towards more contingent and participatory approaches. 1174 R. Koivisto et al./

No matter the size of the model or the computer that runs it, some developments are beyond current discovery

mathematical models and simulations of those systems usually use linear assumptions 4. The linear approximations are made

and over vast regions of operation the linear models provide a good match with reality. Linear systems can be stable (that is

But if the model and the real system are in a chaotic state, the results of a policy may be exquisitely dependent on a number of factors other than the policy itself.

quite different results might be obtained on successive runs of a model (or in two bplaysq of reality) with the same policy,

Do these arguments lead to the conclusion that modeling and policy research are dead? We think not,

Second, nonlinear models can be built to simulate real life systems that operate in a stable mode most of the time.

Such models can be used to find conditions that drive the systems they simulate into oscillatory or chaotic states.

Then, using the model, policies can be found that move the system back toward stability.

the nature of modeling changes. In the old days validity was tested by building models with data through some date in the past

and then using the model to bforecastq the interval to the present. If there was a match,

the model could be believed and used in forecasting. Now we see that if the system was in a chaotic state,

it could be almost exactly correct in its match to reality and yet replication of history would be an impossibly stringent criterion.

Nevertheless, such models are useful because they can point the way toward stability, establish reasonable ranges of expected operation, show periodic tendencies,

Fourth, using such models, the analyst can identify the future limits of operation of a system

It will give new salience to agent modeling since the implicit rules of behavior of ever smaller groups will be known with increasing accuracy.

and Infrastructures for Human Living spaces) Productionconsumption 2. 0 Simulation and modelling Time research In order to assess the relevance of all the topics (fields

Complexity, modelling and simulation: new aspects to handle complexity with modelling and simulation require multidisciplinary approaches.

To work out the similarities in different application may be a first step to adapt the instruments and tools in other disciplines so that in the future even in technical and social science contexts,

A comparison of four scenario exercises related to global change applications suggests climate scenarios are used mostly to support further modeling and analysis,

None of the model-based scenario exercise included surprises 35. In this context another study suggests that standard scenario approaches tend to systematically exclude surprising or paradoxical developments as inconsistent or logical impossible.

Change 75 (4)( 2008) 462 482.13 A. Volkery, T. Ribeiro, T. Henrichs, Y. Hoogeveen, Your vision or my model?

towards a social scientific analysis of storyline-driven environmental modeling, Environ. Res. Lett. 3 (2008) 045015.22 W c. Clark, R. B. Mitchell, D. W. Cash, Evaluating the influence of global environmental assessments, in:

have a particular model of what they expect of the outcome, even though‘implementation'is stressed always as an important element of the programme design.

and Arie Rip have termed pre-engagement through socio-technical scenario building 2. It involves the combination of exploration of dynamics using theoretical models

and the need to reduce complexity, without falling back on the linear model of innovation. Such scenarios should highlight both the multilevel/multi-actor dynamics

model 14 16 and sociology of expectations) 9, 17,18. Evolutionary theories of technical changes emphasise that for innovation one should think of variation and selection (and retention of those selections.

evolutionary models of technical change; the innovation chain+,and endogenous futures. This framework which can help in structuring large amounts of heterogeneous data,

what they have to offer. 2. 1. Lacunae in evolutionary models of technical change How do innovations come to be selected from a number of possible options;

whilst allowing the link to the linear model (reducing complexity to achieve outcomes). It is complementary to the widely used value chain approach,

This model is a complex mix of perspectives, and is a combination of technology studies, innovation and management studies,

Unlike the linear model, the emergence of an innovation is predetermined not, it is more reactive and responsive

which shape action (this is emphasized in the quasi-evolutionary model mentioned earlier). Van Merkerk and Robinson 9 show examples from the field of lab-on-a-chip technology and how expectations have an effect on selection choices of pathways to follow,

Manag. 9 (2)( 1997) 131 148.15 H. van den Belt, A. Rip, The Nelson Winter Dosi model and synthetic dye chemistry, in:

Traditional alternatives to rational-analytical models of decision processes are political models and anarchical models (e g. the garbage-can and muddling-through models).

To these authors there seems to be a relationship between Martin's definition of foresight

In this sense, the strategy processes of the Energy research programme corresponded with the Mode 2 model of research.

and outlined according to rational-analytical models of decision processes whereas research councils seem to follow other models.

There is no doubt that a more rational-analytical approach is appealing, especially for technical research councils. In reality, however, the processes involve a strong element of power play and politicca negotiation.

Initially, the prevailing technocratic and linear process models of policy making (e g. in terms of formulation implementation evaluatiio phases) were replaced by cycle models,

Already in these cycle models, policy learning is seen as an essential ingredient of political governance.

With such an open and distributed model of policy making in mind it is recognised now increasingly that an opening of political processes is necessary to ensure the robustness and the effectiveness of its outcomes.

Weber 2006) which in line with the networktyyp distributed model of policy-making processes are provided simultaneously rather than in distinct phases:(

As a loose analogy, consider the change from the handmade automobile to the assembly line Model T Ford beginning in 1908.

and plot such a model. We then inspect it, decide a different growth limit should be investigated,

The Model T analogy carries over here too (loosely) the availability of this standard vehicle enables an efficient infrastructure to develop around it.

A l. Porter/Technological forecasting & Social Change 72 (2005) 1070 1081 1072 Innovation indicators are rooted empirical measures in models of how technological innovation proceeds.

much as the Model T revolutionized production processes. References 1 A l. Porter S w. Cunningham, Tech Mining:

Management and modelling of biological knowledge 7. Information and communications Sensor technology applications Data mining, analysis, management and retrieval Bio-information technology 8. Understanding and human interaction Multicultural

and to the increasing role of modelling and simulation in developing a better understanding of complexity

and the broader socioeconomic environment and hence for some of their more prominent members to advocate simplistic remedies based on linear model thinking

The model and modelling techniques in use guided the data gathering of the system analysis part. Autonomous There was still a significant degree of freedom to adapt to the perceived needs during the process and the development of roadmaps and scenarios.

Fixed Robust portfolio modelling, online surveys. Autonomous Stakeholder workshops. Extensive Wide stakeholder participation in online surveys. Exclusive Limited but open stakeholder participation in the workshops.

It consisted of data gathering and combination of qualitative scenarios and quantitative modelling. Exclusive The project was conducted mainly by the research partners.

and even if our models are fit for purpose, there are always factors that lie outside of these models that may intervene.

In the case in question we are led typically to think of the‘‘obvious catastrophes''and more or less wild cards mass epidemics, asteroid impacts, supervolcanoes, accelerating climate change, and the like.

Often we may doubt the adequacy of our models, of course, and not only because we believe that they should be able to incorporate at least some of the exogenous factors.

A whole class of economic models, routinely used to inform policy, are based on assumptions about economic affairs tending towards equilibrium that have very little relation with the behaviour of businesses (especially innovating enterprises).

when invoking conventional economic models for short-term analysis and forecasting, at least in less turbulent times.

when there is a real difficulty with applying formal modelling approaches to the topic in question. 2 Such methods allow us to explore the structure of opinion

We can examine their plausibility and limits, their internal consistency and conformity with models and data,

These are the sets of knowledge that are to do with the consequences that our models of situations

the assumptions and models they embody should be explicit and intelligible, open to being assessed critically by participants in,

Similar conflicting forces will affect many smaller-scale FTA ACTIVITIES, in private organisations as well as in the policy sphere. 4 DEMATEL=decision making trial and evaluation laboratory, a structural modelling technique;

For selection to be successful, this step results in a model of what is expected to take place (under various contingencies),

along with formal modelling of one sort or another, and less common techniques such as gaming,(Roughly Horton's subtask (iv).)

and indeed many specific methods involve cycles of data production and analysis, modelling, choice among alternatives,

The knowledge and mental models of practitioners and stakeholders may have to be brought into play in such cases.

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.

This model has been used to characterise a wide range of innovation processes, including FTA ACTIVITIES. The four steps, captured under the label SECI (socialisation, externalisation,

Knowledge acquisition learning how to use models, formulae, equipment, methods etc. Combination: systematising and/or translating formalised concepts into new frameworks, procedures, etc.

and modelling they can determine to what extent each is interpreting given material in the same way,

some organise this information into lists or more structured frameworks even models; some allow for synthesising information into posits, views of alternative futures,

Eerola's account of the various steps and procedures of the Nordic H2 energy foresight are located in terms of the SECI model in Fig. 2

with discussion about the connections between ideas proving a good basis for exchanging information about implicit models and theories.

and the implicit model of the system under consideration; scenarios may be differentiated in terms of key uncertain drivers, broad archetypes about system performance,

Modelling and simulation using a wide variety of different approaches and methodologies (agent-based approaches, neural network-type approaches, fuzzy approaches, etc.

The different sorts of posit that are involved at the extremes of these poles are valued differently in various communities as is clear from the continued demand for more modelling

Formal models (for example, diffusion and substitution analyses) can only go so far for example, with more qualitative analysis required to explore possible factors shaping take off points, ceilings, novel applications of the technology that is diffusing, and so on.

But qualitative speculation about how and how far new technologies may be used will also do well to be grounded in terms of available understanding (i e. models) of product cycles and diffusion curves.

Serious FTA recognises that we can apply formal modelling to some features of the complex systems we encounter,

(and time) to examine the underpinning assumptions of models (not to mention intellectual familiarity with the conceptual underpinnings of social and economic models).

not only arise in the highly formal techniques of modelling. The influences of specific procedures (and the‘‘technical''choices made in implementing them) on the outcomes of creativity sessions

(also published as Models of Doom, Universe Books, New york, 1973). 45 D. H. Meadows, D. L. Meadows, J. Randers, W. W. Behrens III, The Limits

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