The traditional concepts and models of innovation are not always adequate to embrace the complexity for addressing the grand challenges 10,15.
Innovation in the 21st century differs from the model embraced in the last century (i e. profit-oriented
How commensurable are different modes of modeling and other forms of dynamical representation? How can different communities of practice interact in an overall productive and interested way?
not only deal with the collection of data and models; they also involve the interaction of the stakeholders, their ideas, values and capacities for social change.
Rijkens-Klomp, D. S. Rothman, J. Rotmans, Cloudy Crystal Balls, An Assessment of Recent European and Global Scenario Studies And Models, Experts'Corner Report:
traditional versus participatory model building, Interdiscip. Sci. Rev. 32 (2007) 1 20.74 S. Funtowicz, J. Ravetz, Science for the post-normal age, Futures 25 (1993) 735 755.75 A. Jetter, W
such as bibliometrics and modeling to qualitative and participatory tools such as focus groups and scenario building cf. 30.
which can be characterized as a model of linear and science-driven innovation. In this model, technology results from research whereas society has to adapt to technology to make its applications successful.
For its part, the government's role is to improve and accelerate the uptake of technology through funding, education and awareness-raising.
the democratic virtues of the consensus conference model, Public Underst. Sci. 17 (2008) 329 348.25 R. Zimmer, R. Hertel, G.-F. Böl, Bfr Consumer Conference Nanotechnology, Federal Institute for Risk assessment, Berlin
A wide variety of hybrid value creation models with novel configurations of innovation actors emerged. We explain the approach
Early models saw innovation processes as a linear sequence of functional activities distinguishing only between technology push
In the case of scenario building the model-based approach is in widespread use in Europe,
A Model of industrial systems in which all waste materials are reincorporated productively in new production and use phases. 462 E. Schirrmeister, P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466 (2) Participation:
the term‘future-oriented technology analysis'seeks to apply a wider collective identity around several strategic intelligence activities including technology foresight, forecasting, intelligence, roadmapping, assessment and modelling but faces a reality where the community regards FTA as the name
Similar tendencies are visible in investigator-driven Research funding models in most countries evolved but only slowly towards accommodating more interdisciplinary thematic approaches.
While there is as yet no clear methodological answer to the identification issue there have been some institutional responses and new organisational models of FTA.
They use an analytical framework that they call the‘‘Cyclic Innovation Model (CIM)''to make the case for the convergent development of innovation
such as Expert Panels, Interviews, Modelling and Literature reviews. The uncertainty avoidance dimension has several implications for national management and planning cultures.
evidence refers to reliable documentation, such as statistics and indicators or forecasting of economic development through macroeconomic modelling.
Consequently, there was less time to learn from the foresight study in a strategic 1 Particular issues arise in the case of quantitative forecasting models,
In these cases, contradictory information may indeed emerge as a consequence of different assumptions across models.
In the local cases, policy-makers concluded that one of the key challenges with respect to organisational embedding is to find appropriate operational models
(i e. research areas and research topics) that are expected, according to the selected models, to enable the IMS2020 Vision to become a reality.
joint application of integrated management model and roadmapping, Technological forecasting and Social Change 71 (2004) 27 65.6 O. Saritas, Systems thinking for Foresight,(Ph d. thesis), Manchester
. Sriram, Developing a Sustainability Manufacturing Maturity Model. The IMS Summer School Manufacturing Strategy First Edition 2010:
Then, a‘logic model'approach is used to develop an‘objectives hierarchy'describing the relationships between higher level goals
or supply chains 5. However, many of these models display important weaknesses. In particular, they fail to tackle efficiently the communication of the strategy across all organisational levels 6 10,
when used in conjunction with other models such as the BSC, the Quality Function Deployment 26 and the GBN method 27.
in order to efficiently respond to such changes. 4 The fourth phase (strategic learning) is based on the model proposed by Kaplan and Norton 12,
and the Hoshin Kanri 36 37 tools to support the acquisition, representation, modelling and maintenance of a firm's knowledge system.
For the former the Cyclic Innovation Model (CIM) is utilized as analytical framework and applied to three cases.
by applying the Cyclic Innovation Model (CIM) and by analyzing foresight activities therein in terms of type, scope,
Up to the 1980s, futures research focused on forecasting future developments by applying s-curves, Delphi studies and mathematical models 18 20.
and backcasting or the above-mentioned s-curves, Delphi studies and mathematical models. Thus, it supports companies'efforts to sense change
In this paper, this relationship is investigated by applying the Cyclic Innovation Model to three cases. Moreover, activities observable in the three cases are Table 1 Generations of innovation management and futures research (based on van der Duin 3
and new theories, models and solutions 42. Case study research is recommended therefore for exploratory qualitative research characterized by scant previous knowledge 43 45.
and openness of the three networks we applied the Cyclic Innovation Model as an analytical framework.
the link of future orientation, futures research and the network is analyzed by connecting the CIM analysis with the character of the foresight activities. 3. 2. Analytical framework 3. 2. 1. The Cyclic Innovation Model The main
principles of the Cyclic Innovation Model are (1) that innovating is predominantly a cyclic interaction between different actors who exchange knowledge
image of the future, process model and transition path. For instance, the transition path aims at realizing the 2 Critics argue that the active involvement in day-to-day work creates bias in the participant-observers in that they may partly
Thus, RWS is continuously searching for innovations in their Fig. 1. Level 1 of the Cyclic Innovation Model:
roadmapping and target costing 39, business modeling and future studies. The outcome of the applied futures research methods is broadened substantially in projects with interdisciplinary character and a combination of knowledge and insight from various industries.
plans and evaluates new business modeling concepts Singular activity 2. 6 Business case analysis Provide revenue,
performance and conformance Projects 3. 4 Spearhead Research grants additional research funds to facilitate collaborative research activities in high-potential topics Projects 3. 5 Business modeling Supports
and deployment of business modeling concepts in yet underexplored business fields Project, singular activity 3. 6 Technology transfer program Increases the transfer activities from academia to business by detecting, stimulating
and knowledge exchange. 2. Beneficiaries of networked foresight activities are the network partners within the predefined project settings. 3. For developing the process model,
Activity Initiator role Strategist role Opponent role Scope 1. 1 Inspirational workshops (&) & Contract partners 1. 2 Business modeling
& (&)( &) Contract partners 2. 5 Business modeling & Contract partners 2. 6 Business case analysis
(organizations and end-users) 3. 3 Testbeds and simulation tools & Closed network 3. 4 Spearhead research & (&) Closed network 3. 5 Business modeling & (&) Open
When recalling the application of the Cyclic Innovation Model to the three cases at least three issues are noticeable:
and inside-out) information flow from the perspective of the partners it is an inside-out information flow. 6. Conclusions This paper aimed at exploring futures research in innovation networks by applying the Cyclic Innovation Model as analytical framework to three cases
The application of the Cyclic Innovation Model shows that the envisioned and practiced openness of the three networks differs substantially.
and (2) to adjust the process models and eventually the transition path. Doing this with the networks'partners promises to sharpen the results by including additional perspectives
a conceptual model of context, antecedents, and outcomes, Academy of Management Review 21 (1996) 1143 1191.34 W. Qualls, R. W. Olshavsky, R. E. Michaels, Shortening of the PIC an empirical test
Table 2 shows examples of modelling and horizon scanning. Horizon scanning is a rather new FTA tool,
curve modelling, leading indicators, envelope curves, long wave models Expert opinion Survey, Delphi, focus groups, participatory approaches Modelling and simulation Innovations systems descriptions
, complex adaptive systems modelling, chaotic regimes modelling, technology diffusion or substitution analyses, input output modelling, agent-based modelling Logical/causal analyses
and data of three governmental horizon Table 2. FTA scores for modelling and horizon scanning FTA score for modelling FTA score for horizon scanning Characteristic Score Comment Characteristic
Score Comment Future orientation***Future orientation***Participation*(*Consultation of experts for certain parameters**Validation of modelling output in a workshop***Validation through wide consultation Participation**(Depends on size of community involved
The scenarios revealed an EID lifecycle model, which helps to understand how technology can be used to combat EID at every stage of their lifecycle.
develop a model for continuous data sharing and comparison; compare working methods and methodologies used by the different horizon scans
and Public policy February 2010 16 weak signals and wild cards that may be used to assees the robustness of results that may come from other forward-looking tools as planning, scenarios and quantitative modelling.
which aim to support the formattio of policy strategies and associated governance models. Among others, he has been involved in the Europeea projects FISTERA and EPIS, both dealing with the future of the information society.
What are the critical differences in national foresiigh program models? Please provide examples. Structure and organization?
Phase 2 of the first study focused the interviews on deriving a deeper understanding of the models
Mcluhan Tetrad Model) Define priority areas for technology policy Survey national technological development Stimulate development in priority areas of technology development and research;
there were many consistent comments in the interviews that provides the beginnings of a model on
Applying the critical success factors to Canada's foresight program Our studies have identified eight critical success factoors The strength of any model is its ability to assist
The model Was developed in Roadmapping I Developed in Roadmapping II Figure 3. Structure of technology roadmaps Biosecurity and emerging infectious diseases in Asia-pacific Science and Public policy February 2010 46 proposed at the workshop
) According to the model, technological approaches can be used to combat EIDS at every stage of their life cycle, from preventive measures such as vacciine to biosensors for surveillance, bioassays for detection, drugs for treatment,
has proposed a decision model to identify and evaluate an optimum mix of interventions and measures for a specific disease, such as improvements in health infrastructure,
The model will take into account the existing situation on the ground, evidencebaase metrics of coverage and efficacy, financial requirements,
and detection (S&d) Treatment (Tr) Prevention of spread (Pos) Vaccine Animal tracking Diagnostic Ubiquitous computing Vaccine Drugs Modeling Figure 5. Contribution of technologies
and information was provided to this surveillance project especiaall with respect to the technological trends and policy recommendations of technologies in ubiquittou computing, modeling,
The life cycle model can be linked to six significaan technology domains: vaccines, diagnostics, ubiquitous computing, tracking, modeling and drugs.
Each of these provides opportunities for technologiie to converge and make significant contributions to R&d
the availability of realistic models can assist policy-makers in developing options for coping with outbreaks but they cannot be used in real time
The‘people factors'are crucial features of disease management through all phases of the life cycle model from detection to response.
and modeling of electromagneeti fields around base stations for mobile communications related to the health effects of the exposure to electromagneeti radiation.
regression with fixed effects or‘difference in differencces'selection models and matching methods based on direct comparisons of the participating
Evaluation methodologies, econometric models: microeconometric models. In RTD Evaluatiio Tool Box: Socioeconomic Evaluation of Public RTD Policies (EPUB), W Polt, J. Rojo, A Tübke, G Fahrenkrog and K Zinöcker (eds.
pp 101 118. Vienna: European commission. Arvanitis, S, H Hollenstein and S Lenz 2002. The effectiveness of government promotion of advanced manufacturing technologiie (AMT:
the experience of international organisations established to provide a supranational mechanism for addressing such issues suggests that these models are incapable of engaging with such issues.
>References Brummer, H. L. 2005)‘ A dynamic competitive analysis model for global mining firms',Doctor of commerce thesis, University of South africa.
We argue that such a transformation of policy models is also underway, blending the traditional focus on large-scale missions with a pluralist funding of individual projects and scientific institutions,
The emergence of a new priority-setting model has been driven by growing internal criticism of what are described as cumbersome and opaque allocation models.
In an article in People's Daily in August 2010, prominent academmic complained that the current S&t system is overfunnde but institutionally weak (Zhao et al. 2010.
and which of these models may be suited best to fulfill the goal of making China a global scientific superpoowe (see also Hao 2008).
Instead, China seems to be forging its own way with an evolving mixture of planning, decentralization and deliberation. 1. 1 Trends in setting priorities Explicit models for science policy priority-setting devellope late and with great tensions.
In most‘mature'research systems in Western societies, several models for priority-setting exist side by side: floor funding to universities,
Which interests do the funding model and the mixture of allocation streams reflect?.How is the funding model related to current trends of‘coordinated decentralization'in science policy?
Beginning with the founding of People's republic of china in 1949, a Socialist centralized S&t system was built in the 1950s by adding the Soviet model of centralized planning onto the S&t system that had emerged in the Republic of china (e g.
Thus China has continued on the Soviet model of using plans (jihua, or guihua) to drive the development of S&t,
In order to conduct a systematic analysis of the strengths and weaknesses of different organisational models of FTA,
Drawing on recent experiences with alternative models of FTA systems, solutions will be identified based on a combinattio of social
What kinds of models for FTA systems exist? How can they be systematised in conceptual terms?.
What kinds of developments can we observe in terms of how these models are used in practice?.What do these findings suggest with regard to the future direction to take for organising FTA ACTIVITIES?
and the types of organisational models and governance contexts that make up FTA systems. Section 3 will draw primarily on recent empirical research presented at the FTA 2011 Conference, 1
The analysis will clarify the potential of different institutional models for tackling different types of future requirements.
Different types of grand challenges call for different transformation models and policy strategies. The distinction between disrupptiv and recognised grand challenges referred to in the European Science Foundation report (European Science Foundation 2010) highlights the fact that areas of disruptiiv grand challenges can be exogenous
three ideal-type organisational models for FTA can be identified, taking into account the speed of change
Setting up dedicated and temporary FTA projects or programmes has been a very common model over the past two decades.
A third model, more accessible to countries and organisations with limited resources, is the network model
However, which of these three basic organisatioona models best fits the requirements is also a matter of the governance mode (co-existence, competition, cooperattio or integration)
organisational model and governance mode need to be compatible with each other. 3. Diversity of FTA systems in practice Against this backdrop,
is a change in both governance and organisational models. A much higher degree of policy coordination seems to be needed to address societal challennge as well as a much more continuous and‘embedded'approach to FTA.
which FTA is embedded and the organisational Table 2. Framework for analysis of FTA systems Dimensions Transformation types Organisational models of FTA Governance modes Sub-categories.
and consequent models on organising FTA ACTIVITIES (see Table 4). Our analysis of the selected papers indicates an increasing emphasis in FTA objectives on improved understanndin of transformations.
2011) have analysed types of Table 3. Changing rationales for FTA APPROACHES on FTA systems Dimensions Transformation types and consequent challenges Governance modes Organisational models of FTA Traditional
Tiits and Kalvet (2011) learned from recent foresight exercises in Estonia that the Table 4. Diversity of FTA systems in practice Approaches in FTA systems Transformation types Governance modes Organisational models
forms and types of transformations, modes of governance and organisational models. A number of crosscutting observations can be drawn on the current evolution of FTA, on emerging requirements and possible responses to them. 3. 2. 1 Observation 1:
and challenges can be addressed by combinations of governance contexts and appropriate organisational models of FTA. 3. 2. 2 Observation 2:
Different models of FTA systems can be complementary in many respects. Service providers as well as FTA instituttion need to be able to draw on networks for many purposes,
Whether a specific model of FTA is appropriate for a transformative problem or not strongly depends on the wider institutional and organisatioona environment in
an intelligent combinaatio of FTA models needs to be put at the disposal of decision-makers,
In turn three organisation models of FTA are identified: short-term projects and programmes, dedicated embedded FTA units,
The complementarity between models of FTA is apparent with service providers and FTA units drawing on networks, blurring the divide between the two.
The future preferences of states on socioeconomic development models will impact on international science. The present range of options extends from market-based economies to stronger developmental state intervention to communism,
Models of state sovereignty may be challenged by regional groupings, which may in turn lead to the development of a strongly multipolar world of regional blocs.
The traditional models of academic careers and ways of evaluating scientists may change in the light of changes to any of the above drivers.
which a linear model of policy-making has been replaced with a more learningbaase cyclical model. This observation means that policy-making is systemic in a double sense:
At present, one of the most importaan enabling technologies is 3d and product model technologies, like building information models.
like carbon footprinting Large scale modelling and simulation technologies enable system-level LCA and digital product processes Advanced modelling,
optimisation and artificial intelligence enable intelligent products and recycling solutions Modelling and simulation technologies required for LCA tools Wireless sensors Image processing technologies AMR hardware and software Mobile technologies Advanced identification and recognition technologies
for waste management and recycling Web 3. 0 in advanced identification and recognition technologies for waste management and recycling Data mining technologies 3d environments and
The modelling and simulation technologies required for LCA methods are also available. Wireless sensors as well as image processing technologies help in the object recognition needed for automatic waste recycling.
large-scale modelling and simulation technologies will enable system-level LCA, digital product processes, and a smart energy supply.
In the long term, advanced modelling, optimization and artificial intelligence methods will enable intelligent products, recycling and energy grid solutions.
Concepts and methods in horizon scanning. 213 Step 5 Tentative modelling of emerging issues into possible emerging issues.
As facilitated by policy workshops Concepts and methods in horizon scanning. 219 model-based forecasting. In general, model-based forward-looking results are taken into account far more seriously by policy-makers than horizon scanning data
even though economic models completely failed to forecast the financial crisis of 2007 8, even in the shortest term.
or causal modelling do not suffice (Linstone 1999). In this setting, where policy-makers are almost bound to be taken by surprise,
JRC-IPTS proposed that a robust portfolio modelling (RPM) screening process (Ko nno la et al. 2007;
The engagement of stakeholders into collective sensemakkin in horizon scanning may follow different organizattiona models. Specifically
2012) consider three ideal-type models for FTA, namely:.individual projects or programmes of limited duration and with targeted objectives. dedicated units providing continuous input to their embedding
a self-regulating financial model is used to allocate basic funding among the institutes. A large amount of the above-mentioned basic funding is distributed to the institutes via a competitive key
This financial model strengthens the competitiveness of the individual institutes in the industrial contract research market,
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