Mapping issues and envisaging futures: An evolutionary scenario approach

Technological Forecasting & Social Change 79 (2012) 509–529

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Technological Forecasting & Social Change

Mapping issues and envisaging futures: An evolutionary scenario approach Ozcan Saritas ⁎, 1, Yanuar Nugroho 1, 2 Manchester Institute of Innovation Research, University of Manchester, Manchester M13 9PL, UK

a r t i c l e

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Article history: Received 10 November 2010 Received in revised form 20 September 2011 Accepted 27 September 2011 Available online 25 November 2011 Keywords: Systemic Foresight Scanning Big picture survey Network analysis Scenarios Evolutionary scenarios

a b s t r a c t In parallel with the increasing complexity and uncertainty of social, technological, economic, environmental, political and value systems (STEEPV), there is a need for a systemic approach in Foresight. Recognizing this need, the paper begins with the introduction of the Systemic Foresight Methodology (SFM) is introduced briefly as a conceptual framework to understand and appreciate the complexity of systems and interdependencies and interrelationships between their elements. Conducting Foresight systemically involves a set of ‘systemic’ thought experiments, which is about how systems (e.g. human and social systems, industrial/sectoral systems, and innovation systems) are understood, modelled and intervened for a successful change programme. A methodological approach is proposed with the use of network analysis to show an application of systemic thinking in Foresight through the visualisation of interrelationships and interdependencies between trends, issues and actors, and their interpretation to explain the evolution of systems. Network analysis is a powerful approach as it is able to analyse both the whole system of relations and parts of the system at the same time and hence it reveals the otherwise hidden structural properties of the systems. Our earlier work has attempted to incorporate network analysis in Foresight, which helped to reveal structural linkages of trends and identify emerging important trends in the future. Following from this work, in this paper we combine systemic Foresight, network analysis and scenario methods to propose an ‘Evolutionary Scenario Approach,’ which explains the ways in which the future may unfold based on the mapping of the gradual change and the dynamics of aspects or variables that characterise a series of circumstances in a period of time. Thus, not only are evolutionary scenarios capable of giving a snapshot of a particular future, but also explaining the emerging transformation pathways of events and situations from the present into the future as systemic narratives. © 2011 Elsevier Inc. All rights reserved.

1. Introduction The 2000s have witnessed increasing complexities in societies. The new global context suggests increased financial, trade and investment flows in leading to a more interconnected and interdependent world, which is accelerated by rapid technological progress in areas such as Information and Communication Technologies (ICTs), fuel cells and bio- and nano-technologies. Besides scientific and technological advancements, other developments such as social and economic instability and hostility due to the economic recession, lack of fresh water, food and energy supply, climate change, regional conflicts, and respective population movements have emerged as main drivers of change. The new ICT-enabled society demands inclusiveness and equity through freedom of association and expression with full protection of human rights. There is an emerging need for new international regulations to govern trade, quality,

⁎ Corresponding author at: Manchester Institute of Innovation Research (MIoIR), University of Manchester, Oxford Road, M13 9PL, Manchester, UK. Tel.: +44 161 275 5931; fax: +44 161 275 0923. E-mail addresses: [email protected] (O. Saritas), [email protected] (Y. Nugroho). 1 Both authors share equal contribution to the paper. 2 Manchester Institute of Innovation Research (MIoIR), University of Manchester, Oxford Road, M13 9PL, Manchester, United Kingdom. Tel.: + 44 161 275 5904; fax: + 44 161 275 0923. 0040-1625/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.techfore.2011.09.005

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labor, environment and intellectual property rights. Thus, it is observed that the nature of situations involved in the real world has changed and has become more complex and uncertain. Recognizing the complexity and uncertainty of the present and future systems, Systemic Foresight Methodology (SFM) has been introduced by Saritas [1] 3 to tackle situations that involved human and social systems, which are open in nature, due to the unpredictability of the behaviors of system elements. Investigations into these systems require (i) anticipation with the intention of being prepared for whatever might follow from the ongoing and future social, economic and political mayhem with a rich understanding of systems, their history and possible futures, (ii) analysis of different stakeholder perspectives and their social relationships, which can affect and be affected by the Foresight process, and (iii) investigation on the formal and informal networks and procedures, which may be in favor or in conflict with other systems. Conducting Foresight systemically involves a set of ‘systemic’ thought experiments, which is about how systems (e.g. human and social systems, industrial/sectoral systems, and innovation systems) are understood, modelled and intervened for a successful change programme. The current paper proposes a methodological approach with the use of network analysis to show an application of systemic thinking in Foresight through the visualisation of interrelationships and interdependencies between trends, issues and actors, and their interpretation to explain the evolution of systems. The process consists of the sequential steps of “Scanning,” “Network Analysis” and “Evolutionary Scenario Building.” Scanning phase involves the analysis of Trends, Drivers of Change, Weak Signals, Wild Cards/Shocks, and Discontinuities. The scanning data presented in this paper was obtained through the Big Picture Survey [4] with the participation of about 300 experts worldwide. The Big Picture Survey (BPS) generated 382 trends, 225 drivers of change, 217 wild cards/shocks, 171 weak signals, and 70 discontinuities. In an earlier paper we proposed a method of incorporating network perspective in Foresight [5] especially when dealing with a large number of linked variables which is difficult to comprehend. In the current paper we use this method: we map the links among those variables in certain time periods and look at the network measures to uncover the structural features in each period for each set of variables. As such, the network analysis helps reveal the structure of the network while Foresight contributes in offering explanation to such structural features and making sense of them. In the network analysis, networks are represented with a set of “sociograms,” which are visual maps of relationships between actors, organizations, concepts and issues emerging from the scanning phase [5]. Sociograms reveal patterns of relationships or structure visually and provide cluster, collaboration and diffusion networks by portraying emerging effects which cannot otherwise be exposed [24,25]. After identifying the trends, uncertainties and issues through the scanning phase, and mapping and visualizing the relationships between them, in the third phase, evolutionary scenarios are developed. Evolutionary Scenario approach, as we define here, is a method to understand the ways in which the future may unfold, by mapping the gradual change and the dynamics of variables that characterize a set of situations in a particular period of time in the future. Therefore, not only are evolutionary scenarios capable of giving a snapshot of a particular future, but also explaining the emerging transformation pathways of events and situations from the present into the future as systemic narratives. These narratives reveal one particular alternative of how the future unfolds, leaving other alternatives open depending on how this particular set of situations is interpreted. The originality of this approach is twofold. While the use of network approach contributes to systematically map and analyze the variables that characterize a particular scenario, it also leaves the interpretation of how the future unfolds open and allows the development of multiple scenarios. We start the paper by reviewing the literatures in three central areas: Systemic Foresight Methodology, Scenarios, and Network Analysis. We then outline the methods to show how the scanning input is transformed into evolutionary scenarios first, through the network analysis of each scanning item (i.e. trends, drivers of change, discontinuities, wild cards, and weak signals in subsequent sections) in subsequent sections. Each section presents an interpretation of networks in a narrative format based on three time horizons. The synthesis section brings the narratives from each section together based on three time horizons and explains the evolution of developments from the present to beyond 2025. Overall, the paper concludes that the scanning component of the approach helps to identify the factors that can be significantly affected across time; then the network element maps the relationships among those factors and unveils the structural characteristics of the system built by those factors. Finally, evolutionary scenarios explain how the future trajectory might gradually develop and lead to the emergence of new future systems.

2. Background of the evolutionary scenarios 2.1. Systemic Foresight methodology As an unavoidable human trait of thinking about the future [34], ‘Foresight’ is not a new concept. It has been there since the existence of the first human being on earth and humans have always been concerned about their future actions and the consequences of those actions on them. The use of individual Foresight in a collective and participative way, however, is a rather new phenomenon, which led to today's more formal, ‘institutional,’ Foresight practice. More recently Foresight has been a widely acclaimed activity associated with participative and inclusive policy making by government, industry and other organisations to shape the society's future. Foresight practice as an institutional activity has evolved in time as the situations in the world changed. Societies have been more concerned with the future and have endeavoured to predict and shape it in times when they faced uncertainty and

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Loveridge and Saritas [2], and Saritas and Aylen [3] provide further details on the Systemic Foresight Methodology.

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transformations. These are the times when Foresight practice has evolved and new ideas were introduced due to a growing need for dealing with changing contexts and situations involved in them. These emerging new situations have been increasingly more complex and more difficult to deal with, and earlier approaches were usually unable to deal with them [34]. As the complexity of societies has increased in the 2000s, the scope and focus of Foresight activities have widened to cover a wide variety of issues. This has been mainly due to the increasing importance of technological and organisational innovation; the development of service economies; and other developments such as rapid globalisation, and changing nature of demographical structures, cultural practices, environmental affairs and social services [7]. These resulted in a world which is more interconnected, interdependent and complex than ever. Although, it is observed that the nature of the situations has changed and has become more complex and uncertain, the way Foresight deals with them has remained largely unchanged [1]. Although the complexity and uncertainty has been recognized by various scholars [8-10,32,49], institutional Foresight exercises designed and practiced for policy making have suggested “Systematic” method-bound Foresight processes [6,7] to tackle “systemic” situations involved in human and social systems, which are “open” in nature [8,9]. The notion of “open” system comes from the unpredictability of the behaviours of the system elements. In this respect, systems, particularly human and social systems, behave differently both spatially and in time under different circumstances [10]. Investigations into human and social systems require specific approaches each and every time, which are developed following a comprehensive “understanding” phase, which includes understanding the context, content and process of Foresight. Consequently, a need has occurred to improve the Foresight practice to tackle these new situations in a more sensible way and to respond to more sustainable policy needs. Any new Foresight approach in this regard should aim for understanding these complex systems and their behaviors, thus needs to be ‘systemic’ [1]. Forward looking activities aiming to introduce change, like Foresight, should be linked to a broader context [34]. The lack of attention away from the context, whether this to be global, national, or regional leaves the critical issues unrecognized, which has been the case in methodologically bounded activities. It is recognized that Foresight should not strive to understand the issues as episodes divorced from the historical, organizational and/ or economic and social systems from which they emerge. The content of the Foresight activity is constructed from its context by capturing the promising points of leverage that can provide social, economic and environmental benefits in the future. The process of Foresight under the guidance of the systemic Foresight methodology (SFM) is then designed in line with the characteristics of its context and content (see Saritas [1] and Loveridge [34] on further theoretical and practical underpinnings of systemic Foresight). • An important feature of SFM is its emphasis on inclusivity and behavioural matters involved in Foresight [11]. Because of their overt techno-economic purpose, earlier Foresight studies have relied on the opinions of a relatively narrow body of technologically oriented people [12]. However there is now a greater need for widening the scope of consultation in Foresight to turn it into a much wider social process. This need is largely prompted by recognition of the limitations of Foresight regarding participation, the lessons learned from the corporate sector regarding the benefits of stakeholder and end user involvement in the product and service development process [43], and trends for increased inclusivity across all areas of policy making. In order to achieve this inclusivity, the practitioners of the activities need to put much effort into understanding the behavioural matters. Consequently, important drivers for the development of the SFM include: • Information to understand complex interactions between products, services, users and other stakeholders in multiple contexts in which these products and services are used • Intelligence through scanning to explore novel ideas, unexpected issues and shocks, as well as persistent problems or trends • Imagination in a holistic innovation ecosystem by integrating Foresight, Creativity and Design for scientifically possible, technologically feasible and socially desirable futures • Interaction with the systematic involvement of stakeholders in an inclusive process with long-term perspective for the analysis of different perspectives and their social relations in the system, which can affect and be affected by the process with an effective Implementation for a successful transformation programme. During the process of information collection and generation, intelligence gathering, imagination and interaction, SFM considers present and future issues as a system of interrelated and interconnected elements in line with the basic notions of systems thinking including causality [13], holism [14,15], hierarchy [9,16,17] and continuity [18]. The whole system of Foresight can be represented as illustrated in Fig. 1. The figure illustrates that Foresight is embedded in various other systems and there is a close relationship between the context, content and process of Foresight, which is the main starting point of the SFM. As represented in Fig. 1 two context levels can be distinguished considering the nature of the Foresight activity: (1) External context, and (2) Internal context. The external context consists of social, technological, economic, environmental, political and value systems, which exist as an interconnected and interdependent whole in real world systems. These systems have influence on the design and deployment of Foresight activities and implementation of the policies formulated. The internal context includes political, structural and behavioural elements within organizations where Foresight activities take place. It involves the organisers, participants and audience of the Foresight activity. Foresight is embedded in these two contexts which produce and are produced by the activity through information collection and generation. The Foresight activity is then about (1) Systemic understanding (through a holistic scanning exercise to understand and appreciate situations and to capture points of intervention, which constitute the content of the change programme) (2) Systems synthesis and modelling (anticipating and designing futures to build models of alternative futures), (3) Systemic analysis and selection (analysing alternative futures and prioritising them), (4) Systemic transformation (establishing links between the desired future and the present), and (5) Systemic action (informing present day decisions). Looking at the nature and society as systems composed of interrelated and interdependent elements from a systemic perspective;

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external context Social systems Technological systems

internal context

perceived context

Economic systems

Management Routines

Environmental systems

Processes

content

Motivation

process

Politics

Skills

Power

Culture

Political systems

Value systems

Fig. 1. Systemic Foresight Methodology (SFM). Source: [1].

networks of system elements and actors become inherently key issues in both Foresight processes and outcomes. Network analysis itself is a powerful approach that it is able to analyse both the whole system of relations and parts of the system at the same time and hence reveals the otherwise hidden structural properties of the systems [19-21]. Unveiling structural properties through disentangling relationships among systems components in network analysis can be a potent method to analyse complex, co-existent situations. The ability to capture the structure of the whole, or parts, of interacting system might be what makes SNA particularly interesting for researchers working on organisations or systems approaches [22]. This feature complements Systemic Foresight and makes the incorporation of network analysis in Foresight prevailing as a method. Probably there have been a lot of attempts to do so with this regard, but not adequately published in academic outlets. 2.2. Network perspective in Foresight A recent attempt was carried out to incorporate network analysis, particularly social network analysis (SNA) in Foresight, which is done through (i) the inclusion of network analysis into the formal methods of Foresight and (ii) the incorporation of network perspective in Foresight's phases [5]. The inclusion of network analysis as a methodological tool to analyse Foresight data can enrich the existing formal methods in Foresight. The ability of network analysis to investigate complex social phenomena (e.g. [19,22-24]) makes it able to inform Foresight research and analysis. Further, “with Foresight becoming more relevant in and for other fields, the incorporation of SNA in Foresight may give more weight as SNA itself has emerged as a key technique in modern social science and has also been widely used in other fields like anthropology, biology, communication studies, economics, geography, information science, organisational studies and social psychology. While SNA can be directly used in a variety of ways in a Foresight process, it is perhaps important to draw attention to the distinctiveness of SNA relative to other methods in Foresight. Firstly… the power of SNA mainly comes from its difference from traditional social scientific methods, which focus on the attributes of individuals (which are common in statistics-based methods). Secondly, SNA is also more holistic in providing explanations by focusing on the wholeness rather than partiality ([5]: 29–30, emphasis added).” SNA is able to show crucial relationships and associations between objects of different types that cannot otherwise be shown in isolated pieces of information. This approach has proven useful to explain real-world phenomena for often the explanation rests within the structure of the network [22,25]. Another way to incorporate a network perspective in Foresight is through a formal approach, which means that network analysis contributes to the each phase of Foresight: “In the scoping phase, SNA could help to draw the boundaries of the exercise and to decide what topics/issues are crucial and how different topics/issues relate to each other. … In participation (recruitment) phase, SNA could be used to map key actors and their positions in the network and map the importance of their affiliations relative to others. In the generation phase, network analysis can be used to build understanding of the structure upon which the Foresight exercise is based. During the action phase, network perspective can contribute to the set up of more effective collaboration and interdisciplinary actions. In the evaluation phase, network analysis could be used in the evaluation of the whole process of Foresight ([5]: 30, emphasis added).” We believe this attempt is novel as to the best of our knowledge there has been no previous effort to formally do so. Prior to this initiative, scholars had tried to link SNA and Foresight but indirectly, such as the work of Giusti and Georghiou [26] who use

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co-nomination analysis (ego network) to register the structure of a research community as part of the evaluation of the UK national IT programme. Nedeva et al. [27] followed up nearly ten years, went beyond ‘communication networks’ among researchers [28] by incorporating ego network in identifying Foresight experts. This is the first attempt that explicitly incorporates SNA in Foresight despite that it serves a relatively peripheral purpose: identification of actors. Yet, it is an affirmation that in combination with Foresight, SNA can offer information about the types of linkages which exist among actors in question. We note another recent attempt to look at the use of network analysis with Foresight aspects, although not a full process, in nanotechnology [40]. We are also aware that networks of systems are covered extensively by Christensen in his disruption theory [42], however what we are looking for is a formal approach incorporating network analysis in Foresight. From the work of Nedeva et al.[27] to the work of Nugroho and Saritas [5], there were not many attempts to combine SNA and Foresight in a formal approach — and the term ‘network’ is mostly used as metaphor rather than actual network analysis; and even if such work exists, they are mostly trivial due to lacking of methodological grounding. As argued by Nugroho and Saritas [5], the practical application of incorporating network perspectives in Foresight require at least four generic steps: (1) identification of the nature of the network: what the nodes and what the links are; (2) positioning of the network analysis within the Foresight phase; (3) identification of network measures; and (4) analysis and implication in which network measures should inform Foresight analysis. It is outside the remit of this paper to go into the details of network analysis techniques and how it is incorporated in Foresight (for such purpose, please consult [5]). However it might be helpful to know that depending on the data being analysed, there are two basic types of network analyses: ego network analysis and complete network analysis [19,20]. In the ‘ego network’ analysis, the focus is on the nodes or actors (which could be an individual person, organisation, or even abstract concept) and their interaction with other nodes/actors. Ego network normally involves assessment of the feature of an actor's networks or relating attributes of ego with attributes of their alters. On the other hand, ‘complete network’ analysis endeavours to capture all the relationships among a set of nodes/actors, which resulted with the introduction of the terms including cluster analysis and measures like density. Having reviewed our previous work [5] and situate it within the literatures, we believe that network perspective can enrich Foresight analysis in that it helps reveal structural linkages between factors that characterise changes (like trends, drivers, discontinuities, weak signals, wild cards) and thus can better identify emerging future issues, both of which are critical in Foresight. 2.3. Scenarios for the future Scenarios are the narratives of alternative futures. These narratives are created in a participative process, usually in workshops. Like many other early forecasting techniques, the scenario method is a post war planning concept [29–31]. Following the work of Herman Kahn and others at RAND and the Hudson Institute in the 1960s, scenarios reached a new dimension with the work of Pierre Wack in Royal Dutch/Shell. Wack [32] defines scenario planning as: “a discipline for rediscovering the original entrepreneurial power of creative Foresight in context of accelerated change, greater complexity and genuine uncertainty”. Scenarios help direct attention to driving forces, possible avenues of evolution, and the span of contingencies that may be confronted. They are particularly useful when many factors need to be considered, and the degree of uncertainty about the future is high [7]. They may also foster or accommodate change within an organisation (see also the work of Burt on scenario planning [41] based on the work of Christensen on disruption theory [42], among other contributors). According to Van der Heijden [33], well-written scenarios are: 1. 2. 3. 4. 5. 6.

Internally consistent Link historical and present events with hypothetical events in the future Carry storylines that can be expressed in simple diagrams Plausible Reflect pre-determined elements Identify signposts or indicators that a given story is occurring

Following the identification of a focal issue or decision, a scenario development process can start. For instance, Gausemeier et al. [44] describe five phases of scenario development and management including (i) Scenario preparation with the assessment of the decision field; (ii) Scenario-field analysis with the identification of key factors; (iii) Projections on possible developments; (iv) Scenario development; (v) Scenario transfer to the decision-field. Loveridge [34] describes the process of scenario development, analysis and use, which begins with a comprehensive learning programme and boundary setting to discover core driving forces. Then assumptions and ideas are converged around a framework of alternative event strings and trends. Scenarios are explained and analysed to derive alternative strategies, which are finally evaluated with a particular attention on resource allocation and routes to achieve desired ends. A number of generic ways have been suggested for the development of scenarios [45, 46, 55, 56]. Participatory scenarios are usually developed through scenario workshops. A scenario workshop brings together a range of knowledge and experience in an environment where views can be exchanged and insights developed. It is useful to have both experts and practitioners among participants. Diversity of experience in workshops is an asset for an institutional Foresight exercise. Scenarios can be presented in different formats including [36]: - Scenario: covers a wide range of features of the future and provides a multidimensional overview - Vignette: illustrates one element of the scenario in detail, usually through a narrative and focus on one dimension - Profile: a skeletal description of the future in terms of key parameters

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Scenarios can be both exploratory and normative. Exploratory scenarios start from the present and ask questions such as “What next?” and “What if?” Particularly interesting trends or uncertainties can be selected (e.g. locating areas of high importance and high uncertainty) for the development of explorative scenarios. Normative, or inward scenarios, involve backcasting, typically starting with the most desirable future. Typical questions for normative scenarios are “Where to?” and “How to?” [47]. Various typologies have been suggested for the development of scenarios. The following typologies are used commonly: 1. Profile scenarios (usually developed around a 2 × 2 matrix) with the cross-fertilisation of the extremes of two key issues or drivers of change 2. Archetype scenarios (Alpha, Beta and Delta scenarios). Typically Alpha scenarios represent a ‘business as usual’ future. Beta scenarios consider, in particular, some of the many things go wrong in the future. Finally, Delta scenarios represent potential changes in direction [37] 3. Success scenario (one single normative scenario) According to Miles [36] scenarios can describe: 1. Images of the future: description of a future set of circumstances, a portrait of the state of affairs (at a more or less tightly specified date or period, or after a particular set of developments)2. Future history: description of a future course of events, sequence of developments, often highlighting key events, decisions, or turning points Scenario methods have been commonly used in Foresight [36]. However, it has also its own challenges. Scenarios can be considered as labour and time intensive as it takes time to generate scenarios, to write narratives and to discuss their policy implications [50]. Another criticism to scenarios is about their credibility as they may reflect the subjective opinions of its creators and debatable assumptions, which might be contested. However, a great challenge lies in the complexity of developing plausible models of the future, which can capture the complex interrelated systemic elements and can explain interdependencies in a holistic and internally consistent way [34]. Considering that scenarios deal with soft systems boundary setting can also be crucial problematic, which may require lengthy discussions and agreement [51-54]. In the current paper, the scenario process described above is embedded in an overall Systemic Foresight process, where the scenario method is integrated with other methods including Horizon Scanning and Network Analysis. The integration of different methods in a Foresight exercise is desirable as each method used in Foresight is able to produce certain outputs/outcomes and has its strengths and weaknesses. There have been other attempts to integrate scenario method with other methods such as Technology Roadmapping. For examples, see Saritas and Oner [35] and Saritas and Aylen [3]. The evolutionary scenarios proposed in this paper are used to describe both images of the future as snapshots of different future situations in a particular time in the future. Furthermore, the scenarios aim to describe this evolutionary process, as the change from the existing system to a future system is only possible through transformations and changes. There are not many examples of scenarios which describe both of these at the same time. Halal's [38] scenarios “A virtual trip through time” (p.146) can be given as an example, which were developed based on the forecasts of 100 experts from around the world in the scope of the TechCast project. Furthermore, by combining network analysis and scenarios, the evolutionary scenarios approach will be able to visualise the core and peripheral issues with the strength of interrelationships between them. Therefore, it is considered that this new approach will be able to contribute to the boundary setting discussions as one of the key problematic areas in scenario creation. Having discussed the need for systems thinking in a complex and uncertain world, and the role of network analysis to portray the relationships between different trends, issues and actors, in the following sections we will demonstrate the evolutionary scenarios and how they are build based on scanning input generated from the Big Picture Survey. 3. Method, data and analyses In light of what we elaborate in the earlier section we build on and extend our recent endeavour in incorporating a network perspective and Foresight [5] in our current attempt to see what the future might unfold. We propose an ‘Evolutionary Scenario Approach’, which we define as: a method to understand the ways in which the future may unfold by mapping the gradual change and the dynamics of variables that characterize a set of situations in a particular period of time in the future. The Foresight component of this approach helps identify the factors that can significantly affect and shape a certain, or across, periods; whereas the network element maps the relationships among those actors and unveils the structural characteristics of the system built by those factors. Together, this approach will be able to reveal a scenario that explains how the future will gradually develop. We show how this approach work by featuring the data gathered in a recent survey conducted in 2008, i.e. the Big Picture Survey (BPS) [4]. The survey is aimed at using the assembly of Foresight experts to gain insight into the state of future regarding critical issues and trends, drivers of change and prospective discontinuities that might be expected within 5–10 to 15–25 years and beyond as the character of the 21st century begins to become firmly established. The BPS was conducted in the scope of Future-oriented Technology Analysis (FTA) 2008 Conference with the following key premises: • The FTA community is one of the most capable assemblies of strategic Foresight expertise • Building on a survey of FTA conference attendees (experts) about critical trends, drivers, wild cards/shocks, discontinuities and weak signals, new insights can be gained about the state of Foresight and future uncertainties, which should be useful to the community The survey consisted of two main parts. The first part collected demographic data about the respondents (experience in Foresight, country of residence and affiliation). Then, in the second part, the respondents were asked to identify a list of trends, drivers of change,

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wild cards/shocks, weak signals and discontinuities, with an expected time of occurrence. Despite the limitation, in Futures studies trends, drivers of change, wild cards/shocks, discontinuities, and weak signals are considered as the critical elements and essential outputs of Horizon Scanning [4]. The respondents were also asked to assess their entries by considering their impact, discontinuities (as low, medium or high) and estimated time horizon (2008–2015, 2015–2025, and beyond 2025). In total 293 respondents participated in the survey and defined 382 trends, 225 drivers of change, 217 wild cards/shocks, 171 weak signals, and 70 discontinuities. For practical purposes, we term these variables – trends, drivers of change, wild cards, weak signals and discontinuities – as ‘scenario variables.’ These are the variables that have been identified by the experts that might appear, disappear, or change and therefore affect and shape the future. We then apply our approach: we unfold how the future will develop across those periods of time and what particular aspects characterise them. Firstly, we categorised and grouped the scenario variables. We categorized 382 trends under 27 themes; 225 drivers under 19 themes; 217 wild cards under 18 themes, 171 weak signals under 26 themes; and 70 discontinuities under 23 themes (see Appendix 1). Then, we apply the network analysis approach as proposed by Nugroho and Saritas [5] with the use of same dataset as in our earlier attempt, from which we learn that: “…network depiction by horizon has the potential to be more sensitive in that it can reveal emerging clusters (indicated as the least centralised network). We also know that analysis based on region can uncover relatively more delicate links constituting the structure of the whole network (as such network is relatively more inert for change as indicated by the highest centralisation…). Therefore we use horizon as the main determinant to construct the more detailed network maps based on the region… (p.35)” We then map the links among those scenario variables in certain time periods consistent with the time horizon slots as in the survey, and look at the network measures to uncover the structural features in each period for each set of variables. What we have here is set of network maps of scenario variables that are shared globally. We then carry out the analysis from both Foresight and network perspectives. The network analysis helps revealing the structure of the network through mapping and identifying the density of the network, the degree of centrality of the variables and how they form linkages with each other. 4 Likewise, Foresight contributes in offering explanation to such structural features and making sense of them. Finally we put the analysis together in an evolving scenario detailing the development of the future. 3.1. Trends We map the trends into the network diagram and calculate the network measures, then we position them in sequence to help analyse the dynamics. See Table 1, which also appears in Nugroho and Saritas [5]. The 2008–2015 period shows that environmental and sustainability concerns are shared by all world regions. The tight link between changing socio-economic patterns and environmental and sustainability concerns are noteworthy, indicating that behavioural changes such as in manufacturing and consumption are needed in order to deal with problems like global warming. Due to the present financial crisis, this point is underlined as a core issue. In the period of 2016–2025, the relationships between environmental and sustainability concerns, the use of alternative energy sources and the role of Science and Technology (S&T) to reduce environmental harm and to provide sustainability are appreciated by all regardless from which regions the respondents are from. Ageing population is a more shared concern in this period. Different than 2008–2015, financial crisis is considered more as a peripheral issue. Looking into the longer term future (beyond 2025), it is seen that climate change is still a big issue appreciated by all world regions. More emphasis is given on the scarcity of natural resources, probably due to the fact that oil reserves will be closer to exhaustion. The network diagrams made clear that there would be no mention of financial crises, new diseases and pandemics, and globalisation beyond 2025. The global community might have learned how to deal with these issues by the 2030s. This last point is supported by the findings of the Tech Cast process reported by Halal [38]: “Civilisation (…) will probably survive globalisation” (p.148). This might be because better mechanisms would have been developed to deal with these problems by the end of the third decade of the twenty-first century from the experience gained. The BPS does reveal the aggregate statistics of the trend and it shows that the top five trends identified by the experts across the whole time period are (the numbers indicate the occurrence of the trends): 1. 2. 3. 4. 5.

Environmental-Sustainability Awareness (36) Alternative Energy Sources (35) Enhancement of Science and Innovation (25) Towards Miniature Mobile Technologies (20) Climate Change (20)

This gives us a rough idea what trends are important and might have an impact in the development of future scenarios across the whole periods. However, such simple analysis cannot help us understand the dynamics of the trends. For in any evolutionary analysis, the understanding of dynamics is imperative, and for this reason we need to move beyond this ‘snapshot’ (one-at-a-time) analysis.

4

[5].

It is not our aim to elaborate in detail the methodology of incorporating network analysis into Foresight. For such purpose please consult Nugroho and Saritas

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Table 1 Network maps of trends identified by regions according to the horizon. Source: Nugroho and Saritas ([5]:36).

2008-2015

TRENDS

2016-2025

N: 25 ; d: 0.740 ; 16-core; Network centralisation: 20.32%

Beyond 2025

N: 26; d: 0.900 ; 22-core; Network centralisation: 22.12%

N: 18; d: 0.768 ; 14-core; Network centralisation: 23.95%

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Here the network perspective offers an invaluable help. By measuring the degree of centrality (Freeman, 1979) across periods of time we can identify the structural position of certain trends (whether they are in a more or less central location in the network) and how they evolve. See Table 2. What we now see is a more apparent ‘movement’ of the trends. For example, ‘Environmental-Sustainability Awareness’ which appears to be the top trend from the statistical analysis is actually true as a top trend only for the time period 2016–2025. In the periods prior and subsequent to that, the trend is less central (indicated by lower degree of centrality. Similarly, what seems to be the top trend in 2008–2015, Towards Miniature of Mobile Technologies, is actually much less central in 2016–2025 and is not listed among the top 5 trends beyond 2025. Despite its popularity at the moment climate change as a trend is not listed among the top 5 trends before 2025. However it is the top trend beyond 2025. Overall, looking at the centrality measures of the trends dynamic we can see that environment-related issues (including alternative energy) remain as a trend that characterise the course of human life. We can also expect that our socio-economic life might change not only in terms of demographic (which will be very apparent in and beyond 2025) but also in terms of how science, technology and innovation impact it.

3.2. Drivers Based on the work conducted for the BPS, Saritas and Smith [4] define drivers of change as “those factors, forces or events– developments which may be amenable to changes according to one's strategic choices, investments, R&D activities or Foresight knowledge and strategies. They are both presently accessible and future relevant” (p.5). As a result of our work, we generate a network map of the drivers and work out the network measures as illustrated in Table 3. The world in 2008–2015 will be typified by the strong links between globalisation, development and innovation drivers. As clearly shown, there are very strong links between R&D technological innovation with local–global cooperation and development and with globalisation and competition. In such context it is understandable why new forms of governance and global policy are needed, especially because there is also a strong connection to what has changed some socio-demographic patterns. Moreover, the world in this period will still witness how central the climate change is as a driver for change although environmental policies and practices might stay peripheral. This situation however is likely to change in the period of 2016–2025. The awareness that our natural resources are limited, and therefore alternative sources are needed, is shared worldwide. We will realise more how our world is actually driven by strong links of drivers, instead of by a number of drivers on their own. Among those links are the major links between R&D technological innovation with the change of socio-demographic patterns, with environmental policies and practices, with globalisation and competition, and with the global policies and new form of governance. Behaviour of consumers might well be a driver which links to ethical awareness but also wider awareness about the scarcity of natural resources religion and ideology, among others, although they are much less central as drivers of change. The world beyond 2025 will see global policies and new forms of governance as one of the drivers, which strongly links with climate change, scarcity of natural resources, and R&D technological innovation. It will also have prominent links with other drivers like globalisation and competition, increasing demand and energy alternatives. Other drivers that are mapped seem to have similar importance in terms that they are quite evenly distributed across the network. However it is interesting that local and global cooperation and development becomes a peripheral driver. When we look at the statistical result of the BPS, the snapshot description shows that the top five drivers of change are: 1. 2. 3. 4. 5.

R&D and Technological Innovation (41) Globalisation and Competition (20) Global Policies and New Forms of Governance (20) Increasing Demand and Energy Alternatives (17) Scarce Natural Resources (13)

We then analyse the dynamics of these drivers across the three periods of time using centrality measures of the network perspective, and we find the following. See Table 4.

Table 2 Centrality measures of the trends using Freeman's degree centrality (Freeman, 1979). Source: Nugroho and Saritas ([5]:37). Rank

Top 5 trends (degree of centrality) 2008–2015

2016–2025

Beyond 2025

1. 2. 3. 4. 5.

Towards Miniature Mobile Technologies (402) Environmental-Sustainability Awareness (398) Changing Socio-Economic Patterns (345) Increasing Conflicts (289) Enhancement of Science and Innovation (286)

Environmental-Sustainability Awareness (828) Alternative Energy Sources (797) Enhancement of Science and Innovation (652) Increased Mobility and Migration flows (477) Towards Miniature Mobile Technologies (471)

Climate Change (187) Environmental-Sustainability Awareness (167) Scarce Natural Resources (150) Ageing Population (96) Alternative Energy Sources (85)

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Table 3 Network maps of drivers identified by regions according to the horizon.

2008-2015

DRIVERS

2016-2025

N:16 ; d:0.69 ;11-core; Network centralisation: 22.33%

Beyond 2025

N:17; d:085 ;14-core; Network centralisation:35.19 %

N:16 ; d:0.87 ; 14-core; Network centralisation: 32.94%

First, as shown by the statistical analysis, R&D and technological innovation is indeed always within the top five all the time, but its position changes from being the top driver from 2008 up to 2025 then moves down to the top four. Secondly, we can quickly spot that global policies and new forms of governance has become more and more central driver from time to time. In contrast, globalisation

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Table 4 Centrality measures of the drivers using Freeman's degree centrality [39]. Rank Top 5 drivers (degree of centrality)

1. 2. 3. 4. 5.

2008–2015

2016–2025

Beyond 2025

R&D and Technological Innovation (219) Globalisation and Competition (159) Local/Global Cooperation and Development (117 Global Policies and New Forms of Governance (109) Change in Socio-Demographic Patterns (67)

R&D and Technological Innovation (504) Global Policies and New Forms of Governance (291) Change in Socio-Demographic Patterns (286) Environmental Policies and Practices (276) Globalisation and Competition (240)

Global Policies and New Forms of Governance (89) Scarce Natural Resources (66) Climate Change (50) R&D and Technological Innovation (48) Increasing Demand and Energy Alternatives (47)

and competition loses its importance as drivers: by beyond 2025 it disappears from the top 5 drivers. Lastly, the concern about changes in socio-demographic patterns as an important driver indeed increases over time up to 2025 but then it is no longer among the top 5 drivers beyond 2025. As a concluding note it is important to understand that the drivers being analysed here can also mean, more or less, the opposite of that have been discussed. Therefore as much as we now focus on the drivers of change, we also need to be aware of the drivers of stability as well — because often the same driver has both features that need to be understood. Such understanding can help envisage different alternative futures.

3.3. Discontinuities Discontinuities refer to rapid and significant shifts in trajectories without the aspect of being mostly unanticipated or deeply surprising [4]. Opposite to Trends, which existed sometime in the past, are present and likely to exist in the future, discontinuities represent shifts from existing trends to new emerging trends. Discontinuities suggest changes in technologies, the way products and services are delivered, and related structures and behaviours. An example from the 1960s is the introduction of the electronic calculator. In a very short time, slide rules and mechanical calculators disappeared and, in some cases, the companies that made these products were shut down when they could not adapt to or find ways to use the new technology. In the light of definition and examples the network diagrams revealed from the BPS data (Table 5) can be interpreted as follows. In the period of 2008 to 2015, significant discontinuities are observed in the communication technologies and petrol based economies. As of 2010 major discontinuities on communication technologies are already in place. A recent example of is that of using the Internet and the TCP/IP protocol to transport voice calls. This application of the Internet represents a technological discontinuity for traditional telephone companies and provides an opportunity for small entrepreneurs to enter the telephone business with relatively little investment. VoIP applications such as Skype can be given as an example. In addition applications, like Google, Wiki, Facebook and You Tube create powerful forces that change the business and social environments and personal information practices. Shift to Alternative Energy Economy has already started challenging the current production and consumption patterns. Recent reports about accelerated arctic ice shelf melting and greenhouse gas concentrations in the atmosphere may create discontinuities in national and international policy approaches toward climate treaties design and promulgation, which are the first indications of shifting to a Low Carbon Economy in the next period. By 2016–2025, Low Carbon Economies (LCEs) will be implemented with a minimal output of Greenhouse Gas Emissions (GHGs) into the biosphere. The shift to LCEs is expected to introduce major discontinuities in the major sectors of economies including agriculture, manufacturing, transportation and power-generation around technologies and applications to produce and consume energy and materials efficiently with minimal GHG emissions and disposal. For instance, food can be produced as close as possible to the final customers. In the years from 2016 to 2025, the world geopolitics of the may indicate a collapse of some of the current political and economic blocs, which then may give rise to the formation of new blocs. We might see a more loosely connected EU, whilst seeing the emergence of EU like blocs in the Middle East and Central Asia. Some of these transformations and discontinuities in blocs may not be peaceful, but only after regional conflicts and wars. Strong emphasis on shift to alternative energy economy beyond 2025 indicates that the world will enter in a Post carbon era. The discontinuity of the carbon economy and the emergence of a zero-carbon society, through the transformations to sustainable life styles will impede the negative effects of the climate change. The shift to alternative energy economy will be achieved mainly with the introduction of innovative materials. Here, a particular emphasis on nanotechnologies is noteworthy. 2025 and beyond might witness fundamental advances in nanotechnology, genomics and quantum computing, if realized, could fundamentally alter our ways of making materials, practicing medicine and computation-making calculations, with pervasive societal impacts. The analysis of the top five discontinuities from the BPS (See Table 6) indicates that “Shift to Alternative Energy Economy” might be the major discontinuity in the next decades. The centrality measures indicate that in the nearest term the shift to alternative energy economy is number two, but becomes number one in the following years. This might be due to the fact that our current times and near future attempts have been concentrated mostly on energy efficiency. In the following years, major discontinuities will be observed due to the introduction of new ways of energy production and new styles consumption. The emergence of changing political systems and wars and conflicts might mark a turbulent decade for the world on the way to brand new political, economic and social systems, which will be observed in more peaceful times beyond 2025. However, it might be useful to watch out wild cards and shocks which might bring some other global disturbances.

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Table 5 Network maps of discontinuities identified by regions according to the horizon.

2008-2015

D IS C O N T IN U IT IE S

2016-2025

N:16 ; d:0.76 ; 13-core; Network centralisation:25.63 %

Beyond 2025

N:21 ; d:0.77;16-core; Network centralisation: 21.77%

N:16; d: 0.71; 11-core; Network centralisation: 25.14%

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Table 6 Centrality measures of the discontinuities using Freeman's degree centrality [39]. Rank

1. 2. 3. 4. 5.

Top 5 discontinuities (degree of centrality) 2008–2015

2016–2025

Beyond 2025

Communication Technologies (64) Shift to Alternative Energy Economy (53) Socio-Political Crisis (36) Scarcity of Resources (22) Terrorism and Security Threats (22)

Shift to Alternative Energy Economy (213) Changing Political Systems (201) Sustainable Life Styles (112) Wars and Conflicts (108) Precautionary Principle and Ethical Values (99)

Shift to Alternative Energy Economy (135) Climate Change (87) Nanotechnology production (60) Sustainable Life Styles (52) New Advances in Medicine (36)

3.4. Wild cards In Foresight and scenario development in particular, it is important to include some Wild Cards and Shocks first, because they often reshape the trajectories of events and situations, and second, they help to test the resilience of future scenarios under extreme conditions. The working definition of the Wild Cards developed for the purpose of the Big Picture Survey is “those surprise events and situations which can happen but usually have a low probability of doing so — but if they do their impact is very high. These situations tend to alter the fundamentals, and create new trajectories which can then create a new basis for additional challenges and opportunities that most stakeholders may not have previously considered of prepared for” Saritas and Smith [4, p.6]. Steinmuller [48] also mentions the surprising character of Wild Cards to emphasise that they may have high probability and high impact but with an uncertain time of occurrence. The analysis of the BPS data showed a small number of Wild Cards with strong ties between them (Table 7). These include some usual suspects such as natural disasters and nuclear accidents supplemented by several provocative shifts in human psyche, social cohesion factors and ethics. Below, we will look at the three time periods for the surprises and shocks of the coming decades as identified by the participants of the BPS. What is noteworthy between 2008 and 2015 is a clear triangle with three strongly connected Wild Cards on each vertex: (i) Natural disasters, (ii) Decline of World order and collapse of nations, and (iii) Wars and conflicts, all of them considered to have immense negative impacts, though with a low probability of emergence. Besides natural disasters and the decline of world order, other possible reasons for the wars and conflicts include energy and oil crises, nuclear weapons and terrorism. Considering the tension between Iran and the international community, the likelihood of this particular Wild Card seems to have increased. All these wars and conflicts, and political restlessness would cause increasing migration flows. Wars and Conflicts due to terrorism are already evident as in the case of Afghanistan. It is likely that this type of conflict will be high on national security agendas in the near future. The emphasis to energy and oil crises, reminds us straight away of oil spill in the Atlantic Ocean, which has created an environmental catastrophe in the Mexican Gulf and serious threat of bankruptcy for British Petroleum (BP), one of the biggest oil companies in the world. Similar to the strong triangular pattern in the 2008 to 2015 period, 2016 to 2025 indicate a rectangular pattern with the addition of an epidemic outbreaks Wild Card. Similar to the previous period wars and conflicts and decline in world order would result with a new world geopolitics, which was observed in the earlier analysis of discontinuities. The link between terrorism and epidemic outbreaks may give the first hints of new bio-weapons, which would require the development of new security and defence systems. More advanced airport scanning systems would be introduced to detect this type of substance to be transferred even in human body in the form of viruses. Although the world will have shifted into a post carbon era beyond 2025, though the total shift might be sometime around 2050s, the impacts of this transformation on the climate change will be observed only sometime later. Different from the previous maps, there are relatively positive wild cards in the third map such as the emergence of new political/economic alliances and international cooperation agreements, which will be driven mainly by technological breakthroughs and some other shocks including natural disasters and energy and oil crises. It seems like even in a Post Carbon Economy after 2025, the respondents of the Big Picture Survey expect some surprises and shocks around energy and oil issues. Overall, the Wild Cards identified have a clear dominance of geo-politics and security with some emphasis on society and culture. Global order–disorder and natural health and shocks affecting the resilience of the earth are recurring themes treated in many different ways. Top 5 Wild Cards from the Big Picture Survey 1. 2. 3. 4. 5.

Natural Disasters (34) Wars and Conflicts (22) Epidemic Outbreaks (21) Decline of World Order/Collapse of Nations (17) Terrorism (13)

Using centrality measures, we can see the evolutionary dynamics of the wild cards across periods (Table 8). Apparently the future wild cards can be expected to be negative or unfavourable. Although the possibility for wild cards such as wars and conflicts get lower from period to period, the world might need to anticipate natural disasters. Decline of world order

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Table 7 Network maps of wild cards identified by regions according to the horizon.

2008-2015

W IL D C A R D S

2016-2025

N : 15; d:0.69;10-core; Network centralisation:24.65%

Beyond 2025

N:14; d:0.98;13-core; Network centralisation: 26.99%

N:12; d:0.76;9-core; Network centralisation: 37.06%

and collapse of nations is seen as a wild card which becomes more important from 2008–2015 to 2016–2025. Only after 2025 the world can expect a less bleak series of wild card, especially when technological breakthroughs can reach as many people as possible.

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Table 8 Centrality measures of the wild cards using Freeman's degree centrality [39]. Rank Top 5 wild cards (degree of centrality)

1. 2. 3. 4. 5.

2008–2015

2016–2025

Beyond 2025

Wars and Conflicts (144) Natural Disasters (131) Decline of World Order and Collapse of Nations (126) Terrorism (84) Increasing Migration Flows (60)

Epidemic Outbreaks (501) Decline of World Order and Collapse of Nations (428) Wars and Conflicts (397) Natural Disasters (394) Terrorism (264)

Natural Disasters (110) Technological Breakthroughs (68) Energy and Oil Crisis (58) New Political/Economic Alliances (41) Wars and Conflicts (40)

3.5. Weak signals We map the weak signals that the experts believe will emerge in the all periods. See Table 9. The world needs to be sensitive for some weak signals are predicted to appear in 2008–2015. These signals should be taken into account not only individually but also in terms of the links they have with other signals. For example, the signal of the recurrence of wars and conflicts is quite strongly linked to rising individualism and nationalism, economic recessions, the widening gap between rich and poor, lack of education and development funds, ICT-associated threats and diversity of religious belief. One interpretation of the emergence of these signals could be that it indicates the world will be in anxiety — socially, economically and politically. Other signals, and their links (e.g. empowerment of citizens, enhancement of innovation, nanotechnology development and virtual communication), also appear although they are not as central as the ones discussed above. The situation becomes different when the world moves forward to 2016–2025. All weak signals identified by the experts to appear during this period seem to share similar centrality (or importance) and they are much more connected to each other than they are in the earlier period. The signal of wars and conflicts remains important and it has strong links with consequences of climate change, emerging societies, and nanotechnology development. But other signals and their links are also important, e.g. empowerment of citizens, new world order and patterns of democracy, etc. What seems to be a remote signal are technologies to improve energy efficiency. As depicted by the network diagram, the world in this period will have to be sensitive to capture and to make sense of a lot of weak signals, which are equally important and equally significant. After 2025, interestingly the map indicates that the world may need to be sensitive towards the emergence of two groups of signals. One group consists of weak signals which may indicate the development of a certain technological area, i.e. nanotechnology and energy, which address the societal problems like impact of the demographic patterns change and pandemics. The other group is also signified by technology-related signals and the links among them, such as artificial intelligence applications, exploration of the space, and technologies to improve energy efficiency. Some emerging signals relate to societal dynamics, like new world order and patterns of democracy and diversity of religious beliefs. ICT-related threats are still a signal to be cautious of, but it becomes marginal. The survey shows the top five weak signals across the whole time periods, which are: 1. 2. 3. 4. 5.

Recurrent Wars and Conflicts (12) Consequences of Climate Change (8) Technologies to Improve Energy Efficiency (7) Exploitation of Human Genome (7) Economic Recession (7)

We compare this snapshot result with the dynamic depiction of the weak signals provided by the network analysis. See Table 10. It is confirmed that the world should be receptive towards signals of wars and conflicts from today until 2025; but this signal will disappear from the top five after 2025. However this does not mean there will be no more negative signals: the consequence of climate change, which is not among top five in 2008–2015 will become suddenly and significantly important signals by 2016– 2025 and beyond 2025. The application of artificial intelligence, too, seems to follow this path: from being outside the top five in 2008–2015 it moves ‘up’ to the top four and is the most important weak signals the world has to be aware of after the year 2025. It seems to us that within the last period, i.e. beyond 2025 the world will need to be alert to new signals that are less important in the previous period, such as efficient energy policy, new world order and patterns of democracy, and availability of information and confidentiality.

4. Synthesis: evolutionary scenario in action Having analysed the dynamics of trend, drivers, discontinuities, wild cards and weak signals across three different time horizons, we now present three evolutionary scenarios for the future by synthesising the short narratives described above based on three time periods starting from 2008 and stretching beyond 2025.

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Table 9 Network maps of weak signals identified by regions according to the horizon.

2008-2015

W E A K SIG N A L S

2016-2025

N:14 ; d: 0.73 ; 11-core; Network centralisation: 34.07%

Beyond 2025

N: 19; d: 0.88;17-core; Network centralisation: 26.76%

N:16; d: 0.51; 10-core; Network centralisation: 27.3%

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Table 10 Centrality measures of the weak signals using Freeman's degree centrality [39]. Rank Top 5 weak signals (degree of centrality)

1. 2. 3. 4. 5.

2008–2015

2016–2025

Beyond 2025

Recurrent wars and conflicts (48) Economic Recession (34) Enhancement of Innovation (32) Rising Individualism and Nationalism (32) Lack of Education and Development Funds (32)

Recurrent wars and conflicts (79) Emerging Societies (69) Consequences of Climate Change (58) Artificial Intelligence Applications (48) New World Order and Patterns of Democracy (48)

Artificial Intelligence Applications (35) Consequences of Climate Change (24) Efficient Energy Policies (23) New World Order and Patterns of Democracy (15) Availability of Information and Confidentiality (13)

Scenario 1: 2008–2015 The 2008–2015 period may be called a ‘turbulent’ or ‘restless’ period when nearly all aspects in our life – social, technological, environmental, economics, politics and norms – start to show they are entering the frequent changes and transformations. This period witnesses signs of the recurrence of wars and conflicts which strongly link to the rise of socio-political issues such as individualism and nationalism and economic and developmental issues such as recessions, the widening gap between rich and poor, lack of education and development funds. In addition to more frequent and higher possibility of natural disaster hitting any parts of the world, the decline of the world order and collapse of nations are among the haunting wild cards: the possibility for them to happen might be low, but once they happen the impact would be catastrophic. This period will also see anxiety surrounding the issues of energy and oil crises, nuclear weapons and terrorism. In terms of technology, ICT not only opens up unlimited possibilities to increase human welfare, but it also becomes a source for unimaginable online threats. With the enhancement of innovation, conventional communication technologies like telephone discontinue and become impasse. Communication network runs over the Internet making possible virtual communication and boost R&D and technological innovations including nanotechnology and biogenetics. The economy of this period will be marked by the local–global cooperation and development and with globalisation and competition. The world's economy will show first strong indications of a shift from petrol based economy to alternative energy economy. Behavioural changes such as in the production and consumption of goods and services become central as it links clearly with the environmental deteriorating condition. In the shadow of energy and oil crises, environment and sustainability remain as central issues with climate change becomes the prima-facie driver for change despite the difficulties to reach global consensus and policies. Politically, the need for new forms of global governance and policy will be stronger. This creates the impetus for the empowerment of citizens at the global level through the emergence of global civil society. This period also witnesses the revival of the diversity of religious beliefs. Scenario 2: 2016–2025 The period of 2016–2025 witnesses the emergence of new societies signified by the high tension between progress and detriments that modernity brings about. The development of biotechnology combined with nanotechnology not only creates new markets and enhances the quality of human life but also creates a possible new threat of bio-weapons, which is difficult to distinguish from natural epidemic outbreaks. This leads to the creation of new societal arrangements marked by a higher level of surveillance and defence systems. More extensive scanning procedures at ports and installation of surveillance devices in public and private spaces are imminent as such threat can manifest in substances easily transferable in the human body in the form of viruses. In technological domain, nanotechnology continues to progress rapidly and becomes one of the most important drivers for a low-carbon economy, together with technology for transportation and production that are material- and energy-efficient. A low carbon economy leads to discontinuities in the major economic sectors: agriculture, manufacturing, transportation and power-generation. This period shows the central importance of R&D as it goes beyond technological innovation and more prominently than ever affects socio-demographic patterns, environmental policies and practices, globalisation and competition, and global policies and new forms of governance. The central attention in environmental and sustainability issues remain to be the climate change focusing on the massive promotion of the use of alternative energy sources. Science and Technology plays a central role to reduce environmental harm and to find alternative sources. In terms of politics, this period witnesses the beginning of a major political change across the world. The geopolitics of the changing world may be an early indicator of a collapse of some of the current political and economic blocs and the emerging of new blocs at the same time. EU countries might become loosely connected, leading to the emergence of blocs like EU in the Middle East and Central Asia. However, this transformation comes at a high price: it may not be peaceful, but after regional conflicts and probably wars. That is why empowerment of citizens and the need of new world order become an important part of social and political engineering. In such situation ethical awareness raises at a global level, not only about the way people see nature and problems such as scarcity of resources and insufficiency of political ideology, but also questioning transcendental values like religion. Scenario 3: 2026–beyond Leaving 2025, we enter the ‘post carbon era.’ It will be marked by the emergence of a zero-carbon society. Technological advancement as well as new awareness spread across globally and transform the world life style and consumption. In a way it can be

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seen as discontinuity of the pre-2025 economy. In terms of technology nanotechnology innovation takes off and it is in this period that fundamental advances in nanotechnology, genomics and quantum computing not only happen but also already drastically change the way people produce materials and goods, undertaking medical practice and carrying-out calculations. These all happen with pervasive societal impacts as the technological advancement also impacts on the change of demographic patterns. The ‘star-trek vision’ might start to materialise with diffusion of artificial intelligence applications much more widely and new technology improve energy efficiency — making possible a leap in the exploration of the outer space, or of the deep sea. The economy of the world will be much safer from the financial crises as globalisation as we knew it becomes outdated. Global collaboration, instead, will take place to meet the increasing demand for energy alternatives. The shift to alternative energy economy becomes the major discontinuity not only because it is achieved through the introduction of new materials but that it entails new ways of producing energy and new styles in consumption. The awareness that the fossil fuels are not infinite quickly worsens the fear of scarcity of natural resources but may transform the nature climate change issue. In such a situation global policies and new forms of governance becomes a driver for the change of political systems as the risk of wars and conflicts are still not completely out of the picture although politically, economically and socially the world will be much more peaceful. The ideals of the new world order become more prominent and new values emerging around a rich diversity of religious beliefs. 5. Discussion and conclusions Future trajectories of human civilisation have been and will always be the focus of futures studies. The complexity of all aspects of human life (social, economic, political, environmental, technological, among others) have made systemic Foresight prominent in assisting us shape the future. The incorporation of network analysis in Foresight [5] as shown here (advancing other attempts such as [26-28, 40]) has offered a new way for Foresight exercises to be carried out. As extensively shown here, when network analysis is applied to map the links among issues (such as drivers, trends, discontinuities, wild cards and weak signals), it reveals structural features of how the issues link to each other, which in turns opens up a whole new analytical perspective. Furthermore, by making prominent the changes in the network structure over time, this method provides deeper insights on the way scenarios may unfold through and in time. In other words, this approach is able to show how a particular future scenario evolves through a particular and possible trajectory. Such an evolutionary scenario is useful in the sense that it does not only present a set of plausible future but also makes it possible for users to understand and learn from its development. During this process, the use of network analysis assists in understanding the links of factors that characterise a certain scenario and its trajectory. Consequently, this also opens up the possibility for generating alternative scenarios depending on how those links, and the dynamics of the networks, are interpreted under different framework conditions. As argued across the paper, we are convinced that the use of network analysis in Foresight, such as in our evolutionary scenario featured in this paper, offers particular strength than cannot otherwise be achieved by the traditional Foresight methods: understanding structural linkages of the issues. However such an approach relies much on the validity of the issues and the strength of the links among them, which in our case is provided by means of an expert survey. This is the limitation of this method, as the absence of expert opinions will affect greatly the quality of the network data. Evolutionary scenarios as presented in this paper helps us unfold future trajectories, but what we feature here is just one possible scenario among many others. The application of a network perspective in Foresight in a more-or-less formal way as proposed in Nugroho and Saritas [5] and featured here, also opens up many other possible applications, but their exploration will be the subject of our other papers. Acknowledgement We thank the participants of the Future-oriented Technology Analysis (FTA) conference who generously responded to the Big Picture Survey. Appendix 1. Categorisation of Scenario Variables Categorisation of Trends 382 Trends were classified under 27 themes as follows: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Equal opportunities Increase consumption Change in patterns of transport Emergence of new diseases and pandemics Global information access: ethical issues Harmonisation of cultural diversity Increase consumption of GM foods/organisms Privacy and security Economic and financial crisis Increasing differences between rich-poor nations

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11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27.

Converging technologies Changing life styles Scarce agricultural resources worldwide Globalisation Scarce natural resources Emergence of innovative health technologies Reconfiguration of socio-political relations Increased mobility and migration flows Water crisis Ageing population Changing socio-economic patterns Increasing conflicts Climate change Towards miniature mobile technologies Enhancement of Science and Innovation Alternative energy sources Environmental-Sustainability awareness

Categorisation of Drivers of Change 225 Drivers of Change were classified under 19 themes as follows: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19.

Safety and security Efficient transport systems Water management strategies Equity and equality Ethical awareness Interdisciplinarity Education Religion and ideology Better healthcare and disease control Climate Change Local/Global cooperation and development Environmental policies and practices Selective consumer behaviour Change in socio-demographic patterns Scarce natural resources Increasing demand and energy alternatives Global policies and new forms of governance Globalisation and competition R&D and Technological Innovation

Categorisation of Wild Cards 217 Wild Cards were classified under 18 themes as follows: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.

Aging population International cooperation agreements Lack of education Vulnerable security Cyber-attacks Emerging socio-cultural values Sudden and dramatic increase in migration flows Shortage of food Nuclear accidents Emerging economic powers Acceleration of climate change Technological breakthroughs Energy and oil crisis Terrorism Decline of world order / Collapse of nations Epidemic outbreaks

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17. Wars and conflicts 18. Natural disasters Categorisation of Discontinuities 70 Discontinuities were classified under 23 themes as follows: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23.

Changing demographics Cyber trust and online services New transport systems Increase poverty Regionalisation Urban development Emerging economic powers GMOs and food consumption Innovative materials Financial and economic crisis Socio-political crisis Terrorism and security threats Climate change Innovation for economic development Precautionary principle and ethical values Nanotechnology production Increasing wars and conflicts Sustainable life styles Communication technologies New advances in medicine Scarcity of resources Changing political systems Shift to alternative energy economy

Categorisation of Weak Signals 171 Weak Signals were classified under 26 themes as follows: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26.

Urbanisation Virtual communication Widening the gap between rich and poor Availability of information and confidentiality Emerging societies Enhancing networking Exploration of the space Food supply chain Changes in demographic patterns ICT-associated threats Diversity of religious beliefs Efficient energy eolicies Empowerment of citizens Changing life styles New world order and patterns of democracy Widespread of pandemics Enhancement of innovation Nanotechnology developments Lack of education and development funds Rising individualism and nationalism Artificial Intelligence applications Economic recession Exploitation of the human genome Technologies to improve energy efficiency Consequences of climate change Recurrent wars and conflicts

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Ozcan Saritas is a Research Fellow at Manchester Institute of Innovation Research (MIoIR) in Manchester Business School, United Kingdom. His research activity has focused upon long-term policy and strategy making with particular emphasis upon Foresight methodologies and their implementation in science, technology and social fields. Yanuar Nugroho is a Hallsworth Research Fellow at Manchester Institute of Innovation Research (MIoIR) in University of Manchester, UK. His research focuses on technological innovation and social change and he is a member of research group in the area of innovation, development and sustainability at the MIoIR.