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Foresight is an area within Futures Studies that focuses on critical thinking concerning long term developments, whether within the public sector or in industry and management, and is something of a sub-section of complexity and network science. This book examines developments in foresight methodologies and relates in its greater part to the work done in the context of the COSTA22 network of the EU on Foresight Methodologies. Foresight is a professional practice that supports significant decisions, and as such it needs to be more assured of its claims to knowledge (methodology). Foresight is practiced across many domains and is not the preserve of specialized ‘futurists’, or indeed of foresight specialists. However, the disciplines of foresight are not well articulated or disseminated across domains, leading to re-inventions and practice that does not make best use of experience in other domains.

The methodological development of foresight is an important task that aims at strengthening the pool of the tools available for application, thereby empowering the actors involved in foresight practice. Elaborating further on methodological issues, such as those presented in the present book, enables the actors involved in foresight to begin to critique current practice from this perspective and, thirdly, to begin to design foresight practice. The present trends towards methodological concerns indicates a move from ‘given’ expert-predicted futures to one in which futures are nurtured through a dialogue among “stakeholders.” The book has four parts, each elaborating on a set of aspects of foresight methodologies. After an introductory section, Part II considers theorizing about foresight methodologies. Part III covers system content issues, and Part IV presents foresight tools and approaches.




Chapter 1. In Search of Foresight Methodologies: Riddle or Necessity

To study the future is to study potential change – unveiling what is likely to make a systemic or fundamental difference over the next 10–25 years or more. Studying the future is not simply economic projection or sociological analysis or technological forecasting, but a multidisciplinary examination of change in all major areas of life in order to find the interacting dynamics that are creating the next age.
Maria Giaoutzi, Bartolomeo Sapio


Chapter 2. Defining the Future: Concepts and Definitions as Linguistic Fundamentals of Foresight

The future is explored and created through language. Terminology, concepts and definitions form fundamental ingredients for foresight, leading into inferences, conjectures, narratives and stories. Many futures methods rely on a specific lingo, some of which has even been trademarked. Although not always duly recognised, the importance of language as an instrument for foresight cannot be overstated. Or, in the words of Richard Slaughter (1996), introducing his Advanced Futures Glossary: “It’s well known that concepts and words are bearers of thoughts and ideas. What’s less well known is that the language of Futures Studies is a rich and powerful symbolic resource in its own right that opens up new worlds of understanding and possibility”.
Ruud van der Helm

Chapter 3. Classification of Tools and Approaches Applicable in Foresight Studies

Are predictive quantitative methods too limited to serve as tools in foresight studies? This concern has recently been met by the emerging application of qualitative methods as a means to complement and compensate for the perceived weaknesses of quantitative methods. It is particularly in terms of reflecting sudden changes or detecting incremental and weak signals of change in real societies that quantitative methods are deemed too static. A productive foresight analysis will need a more differentiated sense-making and robust repertoire (Rossel 2010, 2012). Krawczyk and Slaughter (2010: p. 75) state:
Jan Erik Karlsen, Hanne Karlsen

Chapter 4. Bridging Qualitative and Quantitative Methods in Foresight

There is a long-lasting and controversial discourse on the role of quantitative and qualitative data and methods in science, at least since the “Newtonian turn” in physics in the seventeenth century. After this successful step in the mathematical formalization of a large branch of physics, nowadays called “classical mechanics”, it was used as a kind of paradigmatic case by many theorists of science. Thereby, standards for scientific processes and theory structures were imposed on realms of science dealing with dramatically different subjects and having different purposes than classical mechanics. This was controversially discussed within the debate on positivism, but it still has a strong influence on our understanding of science.
Matthias K. B. Lüdeke

Chapter 5. New Emerging Issues and Wild Cards as Future Shakers and Shapers

Foresight and other forward-looking activities like scenarios, future modelling and planning all play an important role in anticipating future developments. Where appropriate, they are used not only to examine future options but also to shape developments more to our common will. On many occasions, these forward-looking activities fail, however, to anticipate what is referred to as ‘high-impact’ new emerging issues and wild cards because of their high unpredictability and uncertainty. Therefore, many countries have organized horizon-scanning activities that focus on the identification of high-impact issues and wild cards and their accompanying signals, in order to support more resilient policymaking. In 2007, an attempt was made to align and compare the results of the national horizon scans from three countries (Van Rij 2010); in these scans, the concepts of (new) emerging issues, wild cards and weak signals were used frequently.
Victor van Rij


Chapter 6. Forms of Reasoning in Pattern Management and in Strategic Intelligence

The contemporary world is full of information. It has been said that in the seventeenth century, an average person acquired the same amount of information in their whole lifetime about their world as we get from a single newspaper every day (Scholte 1996). The amount of information flowing constantly around us is huge, but only a small fraction of it is useful or valid for us as such. Not so long ago, information and knowledge were scarce and therefore very valuable. Nowadays, most information is free and easy to access, but a rapid understanding of it is rare (Weick 2001).
Tuomo Kuosa

Chapter 7. Micro-Meso-Macro: From the Heritage of the Oracle to Foresight

While ‘foresight’ has become a vogue word for some successful participatory, future-oriented activities, the need for abstract definitions or theoretical underpinnings has arisen to improve efficiency. Defining foresight would be certainly easier if foresight could be included in a special category of practice or if foresight fell under some of the major categories of academic activities. Indeed, some of the foresighters regard foresight as a practice, while others consider it to be more of a science.
Péter Alács

Chapter 8. Going from Narrative to Number: Indicator-Driven Scenario Quantification

Scenario analysis has more than a half-century of history behind it (Glenn and The Futures Group International 2003), and a wide range of scenario methods and techniques are now available (Bishop et al. 2007). While the term “scenario” refers to a story about the future – that is, a narrative – many scenario exercises include a quantitative analysis. This is particularly true in the environmental realm, and recent important examples include the Special Report on Emissions Scenarios for the Intergovernmental Panel on Climate Change (Nakićenović and Swart 2000), the United Nations Environment Programme’s Global Environment Outlook (UNEP 2007), the Millennium Ecosystem Assessment (Carpenter et al. 2005) and the Comprehensive Assessment of Water Management in Agriculture (CA 2007).
Eric Kemp-Benedict

Chapter 9. On Foresight Design and Management: A Classification Framework for Foresight Exercises

The gradual paradigm shift in innovation research and policy from linear to systemic innovation models has also challenged also the conventional technocratic technology-driven forecasting practices and called for new participatory and systemic foresight approaches (Smits and Kuhlmann 2004). In the 1980s, publicly funded foresight activities were commonly seen as an instrument for assisting in the development of priorities for research and development (R&D) resource allocation (Irvine and Martin 1984). Later on, stakeholder participation and networking have been regarded as increasingly important elements of foresight activities for ‘wiring up’ the multilayered innovation systems both in the public (Martin and Johnston 1999) and private sectors (e.g. Salmenkaita and Salo 2004). Reports from recent foresight projects have, in turn, emphasized the importance of common vision building as a step towards the synchronization of the innovation system (Cuhls 2003). In these developments, the locus of foresight activities has tended to shift from positivist and rationalist technology-focused approaches to the recognition of broader concerns that encompass the entire innovation system, including its environmental, social and economic perspectives. The High Level Expert Group appointed by the European Commission crystallized these trends by defining foresight as follows (European Commission 2002): ‘A systematic, participatory, future intelligence gathering and medium-to-long-term vision-building process aimed at present-day decisions and mobilizing joint action’.
Totti Könnölä, Toni Ahlqvist, Annele Eerola, Sirkku Kivisaari, Raija Koivisto

Chapter 10. Will Entrepreneurship, Knowledge Management and Foresight Emerge in a System?

This chapter discusses a theme related to methodological settings, learning and knowledge production in the realm of futures studies and foresight. The author focuses on the synergy that comes from combining an entrepreneurial mindset and transdisciplinary research with organizational and personal knowledge management activities in the context of foresight initiatives and projects. Evolving ideas and concepts to develop research, which deals with the integration of entrepreneurship, foresight and knowledge management, have been put forward in several national-level initiatives, projects and higher education modules in Latvia (2003–2009).
Arturs Puga

Chapter 11. Scenario Transfer Methodology and Technology

Many research activities have been carried out over the years in the area of scenario methodologies (see, e.g. Godet 1987; Georgantzas and Acar 1995), but no great efforts have been devoted to facilitating the fruition, by end-users, of the results obtained through the application of these methodologies. That is, enormous attention has been paid over time to the theoretical aspects of formal scenario methods, but the gap between the analytical details of the ensuing findings in various application fields and the necessity of easy-to-learn knowledge by decision makers and strategic planners has not been adequately bridged. In other words, yet again, the availability of only complex mathematical outputs has often discouraged top managers from adopting suggestions derived from the utilization of the relevant methods and has frustrated the precious potentialities of their conceptual frameworks and computerized tools.
Bartolomeo Sapio, Enrico Nicolò


Chapter 12. Willingness of Stakeholders to Use Models for Climate Policy: The Delft Process

Participatory integrated assessments (PIAs) can be defined as ‘an IA approach in which social stakeholders… contribute their knowledge and policy preferences to the assessment of complex policy problems’ (Schlumpf et al. 1999: p. 2). PIAs often involve dialogues between scientists, decision-makers and other stakeholders. Participatory research is increasingly used in integrated assessments (IAs) of climate change (Dahinden et al. 2000; Kloprogge and van der Sluijs 2006). PIAs differ with respect to their degree of involvement of stakeholders (Van de Kerkhof 2004). Here, we focus on PIAs with co-productive participation, where the IA is carried out in co-production between stakeholders and scientists (Van de Kerkhof 2004). In co-productive PIAs, participants decide what information to use and therefore also decide what models they are willing to use for producing the integrated insights in the PIA.
Serge Stalpers, Carolien Kroeze

Chapter 13. Linking Narrative Storylines and Quantitative Models to Combat Desertification in the Guadalentín Watershed (Spain)

Desertification in Spain is largely a society-driven problem, which can be effectively managed only through a thorough understanding of the principal ecological, sociocultural, and economic driving forces (UNCCD 1994). This calls for a more active role of decision-makers and other stakeholders. We present a promising approach, involving stakeholders in the scenario-development process and linking these narrative storylines with an integrated quantitative model. Within the framework of a larger EC-financed project, dealing with desertification in the Mediterranean region, multi-scale scenarios were developed for Europe, the Northern Mediterranean, and four local areas. In the same project, a policy-support system (PSS) was developed. The main objective of this exercise was to establish a link between the qualitative scenarios and the PSS for the watershed of the Guadalentín river in Spain. From the results of two scenario workshops, three scenarios were selected, all linked to the same Mediterranean scenario. Our selection aimed to maximize both the variety in the narrative storylines and the expected output of the PSS. The scenarios were subsequently formalized, ensuring that the same information was present for all three scenarios; semi-quantified (translated) by linking them to the main entry points of the PSS; and quantified by parameterizing the model. The results indicate the potential of the constructed quantitative scenarios. This chapter illustrates the practical potential and pitfalls of linking qualitative storylines and quantitative models. Future research should, however, also focus on the more fundamental theoretical obstacles that are easily overlooked.
Kasper Kok, Hedwig van Delden

Chapter 14. Scenario Planning as a Tool in Foresight Exercises: The LIPSOR Approach

Foresight is a future-oriented activity that supports decision-making processes by focusing on the management of the complexity involved within a turbulent environment in a long-term planning context (Giaoutzi et al. 2012). Scenario planning, as a strategic and effective planning and learning tool, should constitute an integral part of any foresight exercise.
Anastasia Stratigea, Maria Giaoutzi

Chapter 15. Foresights, Scenarios, and Sustainable Development: A Pluriformity Perspective

‘If … then …’ is a conditional proposition that describes precisely a logical causal statement about possible future events. Obtaining due insight into an uncertain future has been a permanent source of rational speculation in the history of mankind. In the Hellenistic period, the foundation for systematic foresight analysis was already laid by the Oracle of Delphi which – in contrast to popular wisdom – was not based on the incoherent utterances of an ancient intoxicated goddess but on evidence-based information collected by her through listening to the subordinates of any political figure who wanted to pick up a useful hint on how to face the future. The medieval and premodern literature was also full of seemingly rational attempts to predict uncertain future events, such as catastrophes or wars. The aim to acquire political power was often an inspiration for obtaining strategic future information on unknown territories, as is clearly reflected in the support of leading dynasties in European countries for the great voyages of discovery from the fifteenth to the eighteenth century.
Eveline van Leeuwen, Peter Nijkamp, Aliye Ahu Akgün, Masood Gheasi

Chapter 16. Methodological Challenges in Combining Quantitative and Qualitative Foresight Methods for Sustainable Energy Futures: The SEPIA Project

This chapter presents a reflection on the challenges of combining participatory fuzzy-set multi-criteria analysis (MCA) with narrative scenario building and energy modelling, in the context of the SEPIA project. SEPIA aims to investigate participatory decision support systems for sustainable energy policymaking. More precisely, SEPIA elaborates on aspects of sustainability assessment (SA) in the energy policy context in order to reach consensus among the stakeholders involved. SEPIA provides the basis for an SA procedure adapted to the context of Belgian energy governance.
Erik Laes, Da Ruan, Fre Maes, Aviel Verbruggen

Chapter 17. Building Strategic Policy Scenarios for EU Agriculture: AG2020

The agricultural sector is one of the most important production sectors of the global economy, as it largely determines not only the population’s survival and quality of life but also the development potential of a significant part of the European territory – the rural regions. Agriculture is largely associated with the economic prosperity, tradition, production systems, culture, etc., of European farmers. Given the multifunctional role of the agricultural sector, which largely affects the environmental, social and economic development of rural regions, it has become an imperative for future policies in agriculture to focus on sustainability targets, incorporating at the same time the quality–safety dimension in agricultural production. To reach the goal of sustainable agricultural development, a process of exploring the future is required, determining trends, key drivers and uncertainties, which may form the basis for strategic decisions in the field.
Maria Giaoutzi, Anastasia Stratigea

Chapter 18. Opportunities for Combining Quantitative and Qualitative Approaches in Scenario Building: The Experience of the ‘Estonia 2010’ Project

Linking the qualitative and quantitative approaches or, figuratively speaking, narratives and numbers is one of the most challenging problems in the development of the methodology of foresight/futures studies. This problem frequently emerges in the framework of implementing user-oriented scenarios. The multiple-scenario method is not just one of the futures studies methods out of many but is rather a broader methodological construction, within which other particular methods can be applied (Bell 1997: p. 239). The aforementioned problem can be presented in the following form: how could the qualitative and quantitative methods be combined in scenario building so as to ensure, on the one hand, the adequacy of the reality of the created constructs and, on the other hand, their convenient usability for the decision makers. It should be pointed out here that this task of combining two approaches can have quite different forms. The first variant emerges in the case of scenarios built on some quantitative model (let us not concentrate here on the fact that the model itself and its usability in a specific situation are based on a certain qualitative notion, which may not be easy to convey), which must be made ‘palatable’ for practical users unable to comprehend the model and the results of its use, that is, the numerical results should be complemented by a qualitative text to explain them. The second option, which is quite frequent, emerges in cases when the qualitative scenario description is written first and later made more concrete by including in the text some calculation results or expert opinions. Of course, a combination of the above two variants is also possible – the author does write (at least initially) a qualitative description of the scenario, but while doing that, he considers, either consciously or subconsciously, certain calculation results, qualitative indicators taken from similar development analogies, trend extrapolations, etc.
Erik Terk
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