time & dates

ART80.pdf

Adaptive Robust Design under deep uncertainty Caner Hamarat, Jan H. Kwakkel, Erik Pruyt Delft University of Technology policy Analysis Department, PO BOX 5015,2600 GA Delft

Received 14 may 2011 Received in revised form 2 july 2012 Accepted 27 august 2012 Available online 8 november 2012 Developing strategies,

And policies that are optimal for dynamically complex issues at a particular point in time often fail at other moments in time.

Hence, in case of complex issues under uncertainty, there is a strong need for policies that are designed to adapt over time to new circumstances and surprises,

Characteristic for these techniques is that they aim at charting the Technological forecasting & Social Change 80 (2013) 408 418 Corresponding author.

and the importance to present a spectrum of runs under very different hypotheses covering the range of their variation was recognized decades ago 14, p. 149,

their development over time is dynamically complex, and many aspects related to these systems and their future developments are deeply uncertain.

The initial ideas for this paradigm were developed almost a century ago. Dewey 25 put forth an argument proposing that policies be treated as experiments,

with the aim of promoting continual learning and adaptation in response to experience over time 26.

where policies are designed fromthe outset to test clearly formulated hypotheses about the behavior of an ecosystem being changed by human use 32.

and time-urgent and postpone other actions to a later stage. In order to realize this, it is suggested that a monitoring system

/Technological forecasting & Social Change 80 (2013) 408 418 Fig. 1 shows a framework that operationalizes the high level outline of adaptive policy-making.

In a recent special issue of Technological forecasting and Social Change on adaptivity in decision-making, the guest editors conclude that Adaptive policy-making is a way of dealing with deep uncertainty that falls between too much precaution and acting too late.

/Technological forecasting & Social Change 80 (2013) 408 418 operationalizing the Adaptive Policy-making Framework is structured through workshops 35.

Hence, our Adaptive Robust Design (ARD) approach starts along the lines of the EMAMETHODOLOGYWITH:(1) the conceptualization of the problem,(2) the identification of uncertainties (and certainties),

/Technological forecasting & Social Change 80 (2013) 408 418 explicitly considers the opportunities that uncertainties can present.

and construction times are open to surprises affecting the actual completion time. Other important uncertainties are related to learning effects on costs and technological performance.

lifetime of a technology Parametric Varying between 15 and 50 years for different technologies Delay orders of lifetimes Orders of the decommissioning delays Categorical 1st, 3rd, 10th,

and constructing new capacity for a technology Parametric Varying between 1 and 5 years for different technologies Progress ratios Ratio for determining cost reduction due to learning curve Parametric Varying

rate Parametric Randomly fluctuating between-0. 01 and 0. 035 (smoothed concatenation of 10-year random growth values) Investment preference structures Preference criteria

/Technological forecasting & Social Change 80 (2013) 408 418 In order to explore the problem and the uncertainties of energy transitions,

The figure shows the behavior over time for the outcome indicator‘fraction of new technologies of total energy generation'as well as the Gaussian Kernel Density Estimates (KDES) 56 of the end states.

These results show that the fraction of new technologies seems to be concentrated around 60%of total generation capacity by the simulated year 2100,

which means that over the 100 year simulation time, the fraction of new technologies remains below 60%for about half of the runs.

and a short planning and construction time for Technology 1 also hinder the transition toward sustainability,

i e. a policy that will be implemented in any case from the start. 3. 2. 2. Basic policy Shortening the lifetime of Technology 1 could be achieved by increasing its decommissioning,

/Technological forecasting & Social Change 80 (2013) 408 418 fraction of new technologies for the no policy ensemble (in blue) and the basic policy ensemble (in green) as well as the KDES of the end states of all

/Technological forecasting & Social Change 80 (2013) 408 418 this signpost. Using this trigger, the corrective action would be to stop investing in Technology 2

Each of the economic growth parameters indicated in the third region corresponds to the value of economic development for ten years

and together they constitute the overall behavior of economic development over 100 years. Although it is difficult to interpret the combination of these economic growth parameters,

Hence, the costs of Technologies 2, 3 and 4 are monitored over time and when their costs are close enough to the cost of the dominant technology,

a 20%cost reduction of the new technologies is triggered over a period of 10 years. To further address this vulnerability, we also add a hedging action to the basic policy in the form of additional commissioning of Technologies 3 and 4 in their early years.

These actions together aim at making the sustainable technologies more cost efficient once their costs are reasonably affordable levels

and to promote the transition toward new technologies in their early years. The economic action is successful in promoting sustainable technologies

and increasing the total fraction after the first 10 years (around 2020). The adoption of the new technologies in later years is also higher than under the basic policy,

suggesting that these cost reductions are effective. To improve the performance of the adaptive policy even further,

/Technological forecasting & Social Change 80 (2013) 408 418 4. Discussion and implications for Future-oriented technology analysis (FTA) In this paper we proposed an iterative computational approach for designing adaptive policies that are robust

Fig. 5 shows that these actions are effective in the early years, but lose their effect after 2020 due to the time-restricted nature of the hedging action.

However it is not possible to conclude that this reduction in effectiveness is caused only by the nature of the hedging action.

To reveal the underlying mechanism leading to a decline after 2020, it is necessary to identify those runs that improve around 2020 and then collapse.

A modified classification in combination with PRIM could be utilized for such an analysis. This study also has implications for Future-oriented technology analysis (FTA.

That is, EMA could be used to support an inclusive modeling process from the start, where different beliefs about how a system functions,

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, Monterey, CA, 1984.417 C. Hamarat et al.//Technological forecasting & Social Change 80 (2013) 408 418 Caner Hamarat is a Phd researcher at the Faculty of technology, Policy and Management of Delft University of Technology.

He obtained an MSC degree in Industrial Engineering from Sabanci University. His research interests are exploration and analysis of dynamically complex systems under deep uncertainty.

/Technological forecasting & Social Change 80 (2013) 408 418

ART81.pdf

Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty Jan H. Kwakkel, Erik Pruyt Faculty of technology, Policy,

Received 14 may 2011 Received in revised form 12 july 2012 Accepted 27 august 2012 Available online 29 october 2012 Exploratory Modeling

which are key activities of FTA. 2012 Elsevier Inc. All rights reserved. Keywords: Future-oriented technology analysis Exploratory Modeling and Analysis Deep uncertainty System dynamics Adaptive policymaking Agent-based modeling 1. Introduction Future-oriented technology analysis (FTA) is understood as an umbrella label for various approaches

it showed that theory was‘a far more effective means than observation for precisely characterizing complex orbital motions physical theory gained primacy over observation for purposes of answering specific questions about the world'3. Over the course of the eighteenth century,

Similarly, if the Technological forecasting & Social Change 80 (2013) 419 431 Corresponding author. Tel.:++31 15 27 88487.

E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 that policy or planning debates can often be served even by the discovery of thresholds, boundaries,

and assists in developing a plan that can adapt over time to how uncertainties unfold.

and even some base metals such as copper 19 22 and lead 23 may in a few decades become more difficult and expensive to mine and process,

and analyzing their resulting nonlinear behaviors over time in order to develop and test structural policies 24, 25.

Under conditions of deep uncertainty, long time horizons, and high dynamic complexity, a more exploratory use of models is called for 26.

Mineral and metal scarcity is characterized by long time horizons diverging beliefs and ideas about system functioning,

E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 This small and simplistic System Dynamics model was developed in about one day in close collaboration with a mineral/metal expert

Typically plus and minus 50%of the default value Orders of time delays There are various time delays, such as building of new recycling capacity and mines.

These nonlinear relations are varied by changing the start, end and slope. Start, end, slope Fig. 1. Causal loop diagram of the scarcity model 18.422 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80 (2013

) 419 431 structural variations. The exploration is handled using the python programming language 28, utilizing the Vensim DLL 27,29 to parameterize the model,

This figure shows more examples of cyclical behavior and it appears that the cycles can become worse over time.

One way of analyzing the results is to identify runs that share the same dynamic behavior over time.

The behavior over time can be understood as being a concatenation of atomic behavior patterns 30.

E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 otherwise. Next, we tried to identify subspaces in the overall uncertainty space that show a high concentration of crises runs using the Patient Rule Induction Method 31 33.

Amsterdam Airport Schiphol has been working over the last couple of years on a plan for guiding its long-term development 37,38.

3. Evolution of market price for a 1000 runs. 424 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 3. 2

At the moment, Schiphol is considering expanding the airport by adding a new runway that is to become operational in 2020.

Moreover, a participatory process has resulted in the agreement that no more than 510,000 operations can be scheduled at Schiphol in 2020.

Up to 70,000 short haul operation are to be relocated from 2015 onwards to the existing airport Eindhoven,

and Lelystad Airport which is to be developed in the coming years. Using a conjugant gradient optimization algorithm

The construction of a new runway and the moving of operations are in this approach not planned for a particular moment in time,

minimizing the time required to realize the change. To address the potential overshoot of negative external affects

or logistic performance increase Weather Percentage of change in days with severe wind conditions per year.

-1%+4%425 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 could serve as a starting point for slightly modifying the outlined dynamic adaptive plan,

Outcome indicators Static plan Adaptive plan Size of noise contour after 30 years (km2) 13.2 63.8 10.2 47.4 Cumulative Average Casualty Expectancy (ACE

) 0. 9 2. 7 1. 1 2. 3 Ratio practical capacity to demand after 30 years 0. 25 2. 48 0. 89 1

E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 can be decommissioned. Generation companies'expansion decisions are driven mainly by profit expectations,

which the option evolves during the time horizon of the simulation. 3. 3. 3. Analysis of results Fig. 5 shows a performance envelope for five outcome indicators.

That is, in most cases, the fraction of fossil based generation in the final year is higher than 0. 6. Thus,

slope change fraction Yearly fractional change in the slope of the load duration curve-0. 01 0. 01 Planning horizon of the generation companies Upper bound for the planning horizon of the generation companies.

Planning horizon for each generation company is initialized randomly using a uniform distribution with a lower (i e. 5 years) and an upper bound) 6 12 Mean return on investment of generation companies Average expected return

E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 irreducible uncertainties inherent in the forces driving toward an unknown future beyond the short term

E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 some structural uncertainties were taken into account.

(2013) 419 431 scenario discovery. Another major avenue of research is on the communication of EMA that results to policy-makers and FTA practitioners.

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)( 2008) 201 214.430 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 Jan Kwakkel is a postdoctoral researcher at Delft

from short-term crises to long-term transitions. 431 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431

ART82.pdf

Received 4 july 2011 Received in revised form 24 june 2012 Accepted 23 august 2012 Available online 11 november 2012 In recent years, accelerated by the economic and financial crisis,

it is not sensible to extrapolate the future from data and relationships of the past.

whereas scenarios consist of a logical sequence of images of the future 2. 1. 1. Developing

and using scenarios and orienting innovation systems and research priorities 6. Technological forecasting & Social Change 80 (2013) 432 443 Corresponding author.

In addition, uncertainty increases as policy targets move progressively further from the present and it is uncomfortable:

At a strategic level, the European union took up this challenge via the Innovation Union Flagship Initiative as part of the Europe 2020 strategy launched in 2010.

/Technological forecasting & Social Change 80 (2013) 432 443 2. Material and methods How can we learn about orienting innovation systems from future scenario practice?

This means that practice, such as scenario practice, is rooted in a particular moment and place. In accordance with Cunliff 27 and to be consistent with reflexive inquiry,

The development of innovation theory over the past decades has involved a major reformulation, with innovation no longer seen primarily as a process of discovery,

Due to the socially dynamic characteristic of innovation 37, new socio-technical (sub systems will emerge over time 22.

Innovation in the 21st century differs from the model embraced in the last century (i e. profit-oriented

Thus through trial-and-error and learning-by-doing 1 The Cost Action A22 network was a four year program (2004 2007) entitled Foresight methodologies Exploring new ways to explore the future and funded by the Individuals, Societies, Culture

followed by an open scientific conference in July 2007. The main research questions were: What methodological issues are salient in relation to the identification of emerging trends and change?

/Technological forecasting & Social Change 80 (2013) 432 443 experiments in the policy process, new concepts and sustainable solutions can be found to grand challenges.

One of the often-overlooked elements in the innovation process that hinders smooth communication and interaction within emergent networks is time 44.

time has many meanings beyond‘clock time'.'Adam argues that the meaning of time is constructed socially

and that such meaning is performative. Futurists are used of course to deal with short, medium and long-term perspectives,

but it has been shown that differences in the construction of time play a significant role in the construction of meaning about the future (e g. of nanotechnologies 44).

The generic methodological requirement from this perspective is an explicit account of the construction of time within the context of the study at hand.

For instance, time is considered to be historically and culturally specific. Different historical periods, different cultures, and different stages of the lifecycle all display different relationships to time.

This means that situations are rooted in a particular moment and place and seen through the perspective of a certain set of lenses 45.3.3.

Scenario practice and related techniques Reflecting the uncertain threats of the cold war, the development of scenario practice as a methodology for planning and decision-making probably started more than half a century ago in the field of war game analysis. The Rand Corporation in the US became a major center for scenario thinking and Herman Kahn,

who joined Rand, explored the application of systems analysis and game theory in order to encourage‘thinking the unthinkable'8. Meanwhile in France,

/Technological forecasting & Social Change 80 (2013) 432 443 The concept of the multiple-axes method is based on one of the approaches used by Pierre Wack 52.

Backcasting, inspired by the early work of Lovins 53, starts with defining a desirable future and then works backwards to identify policies

and programs that will connect the future to the present. Backcasting scenarios explore the preconditions that could lead to this desirable future,

A science or technology roadmap is like a highway roadmap that describes how one might proceed from a starting point to a final destination expressed as a vision.

but generally comprises a time-based chart together with a number of layers, which provides a means to link technology and other resources to future products,

/Technological forecasting & Social Change 80 (2013) 432 443 our analysis a better understanding of the linkages between scenario design, methods used and related outcomes.

i e. beyond twenty years, can be difficult. Most often, the scenarios are used to highlight important societal assets under threat.

When considered from the perspective of creating legitimacy for action we also suggest that the scenarios in this group could benefit fromcomplementary techniques connecting the long-term future images to the present via stepping stones.

Getting into the Right Lane for 2050 and AG2020 are good examples here (see Appendix 1). In this group,

Rather, the focus of the scenarios in the second group is oriented towards a sequence of clear targets linked with short-term stepping stones,

i e. 5 10 year. Breaking up the long-term in more tangible time periods helps understand the necessary steps for embracing change.

By mapping time we become clearer on where we have come from and where we are going.

/Technological forecasting & Social Change 80 (2013) 432 443 The images of the future are focused on key internal developments

The future plays the role of the time needed to introduce the necessary changes to comply with the envisaged principles.

Our analysis suggests that scenarios developed with broader stakeholder/expert participation will provide richer future images that go beyond the probable that is determined by the past and present 73,75.

/Technological forecasting & Social Change 80 (2013) 432 443 5. Discussion Due to the social dynamic characteristic of innovation, new socio-technical subsystems are emerging 24.

it is not sensible to extrapolate the future fromdata and relationships of the past. Hence, it is important to recognize that representing scientific and technological diversity offers an important means to help foster more effective forms of innovation

Each of the case elements and aspects of different groups are present, therefore it is not possible to link groups with cases query.

/Technological forecasting & Social Change 80 (2013) 432 443 The solutions developed should be socially reflexive

we argue that future scenarios developed with a combination of well-designed modes of futures thinking will provide richer future images that go beyond the probable that is determined by the past and present.

and discussed the applicability of future scenarios as narratives to represent different perspectives on present and future developments.

what we know to be prepared for upcoming situations Allows defining (a sequence of) clear steps for innovation Weak on surprise

/Technological forecasting & Social Change 80 (2013) 432 443 acknowledge the limits of our analysis: i e. using a policy perspective for doing an ex-post analysis of future scenario practice.

IPTS and different past and present foresight network initiatives such as the European foresight Platform and Forlearn for organizing creative discussion platforms on foresight and scenario initiatives.

Appendix 1. Overview of the case studies 1. AG2020 DG RTD (2011 Foresight analysis for world agricultural markets (2020) and Europe. www. ag2020. org 2. Danish Technology foresight on Environmentaall Friendly Agriculture K. Borch,(in press) The Danish Technology foresight

on Environmentally Friendly Agriculture, in: K. Borch, S m. Dingli, M. S. Jorgensen (Eds. Exploring the future, The role of interaction in foresight, Edward Elgar, Cheltenham, in press 3. DP21 DP21 (2003), Dierlijke Productie & Consumptie in de 21ste eeuw.

Last accessed on 29/06/11 and available in Dutch at http://www. kbs-frb. be/uploadedfiles/KBS-FRB/Files/NL/PUB 1338 DP21 STAKEHOLDERS. pdf. 4. Duwobo Duwobo (2010), Transitiemanagement

duurzaam wonen en bouwen. Last accessed on 29/06/11 and available in Dutch at http://www. duwobo. be/index. cfm. 5. 2nd SCAR Foresight exercise EC (2008), New challenges for agricultural research:

climate change, food security, rural development, agricultural knowledge systems. The 2nd SCAR Foresight exercise. Last accessed on 29/06/11 and available at http://ec. europa. eu/research/agriculture/scar/pdf/scar 2nd foresight exercise en. pdf 6. 3rd SCAR Foresight exercise EC (2011), Sustainable

food consumption and production in a resource-constrained world. 3rd Foresight exercise. European commission DG RTD, Directorate E Unit E. 4, Brussel. 7. Prelude EEA (2006) Prelude (PROSPECTIVE Environmental analysis of Land use Development in Europe) scenarios.

Available at http://www. eea. europa. eu/multimedia/interactive/prelude-scenarios/prelude. 8. The world in 2025 European commission (2009

The world in 2025. Rising Asia and socio-ecological transition. Research*eu, Brussels. Last accessed on 29/06/11 and available at http://ec. europa. eu/research/social-sciences/pdf/theworrldin-2025-report en. pdf. 9. Givaudan

Givaudan (2011) Sustainability, translating vision into action. Last accessed on 29/06/11 and available at www. givaudan. com. 10.

Research Dialogue in Germany E. Göll, Futur the Research Dialogue in Germany, in: K. Borch, S m. Dingli, M. S. Jorgensen (Eds.

Exploring the future, The role of interaction in foresight, Edward Elgar, Cheltenham, in press. 11. eforesee Malta L a. Pace,(in press) Strategic planning for the Future:

Getting into the Right Lane for 2050 PBL & Stockholm Resilience Centre (2009), Getting into the Right Lane for 2050.

UNEP/RIVM (2003. Four scenarios for Europe. Based on UNEP's third Global Environment Outlook. Last accessed on 29/06/11 and available at http://www. unep. org/geo/GEO3/pdfs/four scenarios europe. pdf. 16.

Buiten de lijnen VLM (2009) Buiten de lijnen. Vlaamse Land Maatschappij, Brussel. Last accessed on 29/06/11 and available in Dutch at http://www. vlm. be/Sitecollectiondocuments/Publicaties/Platteland/VLM BROCHURE DEF. pdf. 17.

Vision 2050: The new agenda for business. WBCSD (2010) Vision 2050: The new agenda for business.

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His professional challenge is connecting science and policy. On a broad range of regional and EU projects, involving foresight and integrated assessment,

/Technological forecasting & Social Change 80 (2013) 432 443

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