Identification and Evolution of Future (Mega-) Trends in Logistics

Table of Contents

List of Abbreviations

List of Figures

List of Tables

1 Introduction
1.1 Research Problem and Objectives
1.2 Course of the Investigation

2 Foundations of Futures Studies
2.1 Brief Historical Overview
2.2 Classification of Terminologies
2.3 Conceptual Foundations
2.4 Fundamental Characteristics
2.5 Relevant Methods
2.5.1 Overview and Classification Schemes
2.5.2 Scenario Technique
2.5.3 Other Common Methods

3 Futures Studies in a Corporate Context
3.1 Motivation for Future Orientation of Companies
3.2 Theoretical Foundations
3.3 Review of Empirical Findings

4 Logistics and the Logistics Industry
4.1 Defining Logistics
4.2 Theoretical Foundations of Outsourcing
4.3 Classification of Logistics Service Providers
4.4 Relevance of the German Logistics Market
4.5 Review of Trend Studies

5 Research Design and Methodology
5.1 Research Context
5.2 Survey Design
5.3 Interview Design
5.4 Framework for Analysis

6 Research Findings: Future Orientation of Logistics Companies
6.1 Characteristics of Participating Companies and Respondents
6.2 External Impacts
6.3 Orientation Toward the Future
6.4 Information Gathering and Application of Methods
6.5 Organizational Integration and Forms of Cooperation
6.6 Strategic Relevance and Success Evaluation
6.7 Obstacles and Counterarguments
6.8 Future Outlook
6.9 Specific Challenges for the Future

7 Conclusion and Outlook
7.1 Summary
7.2 Theoretical Implications
7.3 Managerial Implications
7.4 Limitations of the Study and Suggestions for Further Research

References

Appendix A – Figures

Appendix B – Tables

Appendix C – Survey

Appendix D – Interviews

List of Abbreviations

illustration not visible in this excerpt

List of Figures

Figure 1. Framework

Figure 2. Course of the Investigation

Figure 3. Historical Overview of Futures Studies and Foresight

Figure 4. European Logistics Market

Figure 5. Overview of Interview Partners

Figure 6. Survey Respondents and Corresponding Companies

Figure 7. Assessments of Hypotheses

Figure 8. External Impacts on Business

Figure 9. Future Orientation

Figure 10. Maximum Planning Horizon

Figure 11. Sources of Information

Figure 12. Futures Studies Methods

Figure 13. Organizational Integration

Figure 14. Fields of Strategic Relevance

Figure 15. Performance Measurement

Figure 16. Evaluation of Success

Figure 17. Obstacles and Counterarguments

Figure 18. Future Relevance

Figure 19. Cluster of Future Trends

Figure A1. Methodological Support of Futures Studies Process

Figure A2. Logistics Performance Index (LPI)

Figure A3. Industry Sector Development in Germany

Figure A4. Number of Employees in Division or Branch

Figure A5. Maximum Planning Horizon (Comparative Analysis)

Figure A6. Top-level Managements‘ Time Spent on Future Orientation

List of Tables

Table B1. Overview of Relevant Journals in the Field of Futures Studies

Table B2. Overview of Organizations Focusing on Futures Studies and Foresight

Table B3. Translation of Commonly Used Terms

Table B4. Taxonomy of Futures Studies Methods

Table B5. Overview of Trend Studies in Logistics

Table B6. Guiding Questions for Semistructured Interviews

Table B7. Relevant Quotations from Interviews.

1 Introduction

1.1 Research Problem and Objectives

Globalization, complexity, and change are some of the terms in vogue in today’s business environment. In this context, uncertainty has become a major issue for deci- sion-makers, where being able to quickly adapt to a changing environment can make the difference between being a market leader and being insolvent (Chermack, Lynham, & Ruona, 2001, p. 7; Porter, 1985, pp. 445-446). Similarly, longer supply chains and fierce competition in a globalized and deregulated market, increasingly complex customer expectations, as well as innovative, changing business models are just some of the key challenges for today’s logistics industry (Christopher, 2005, pp. 210, 228; Singh, 2004, p. 2; Straube, Dangelmaier, Günthner, & Pfohl, 2006, p. 8). Logistics as such has transformed over the last decades from a supporting, cost-absorbing function into a strategic factor with the potential, in a globalized and competitive environment, to be the decisive competitive advantage (Straube et al., 2006, p. 30). In this context, out- sourcing to logistics service providers, which are more often seen as strategic partners by industrial or trading companies that concentrate on core competencies and try to achieve cost efficiencies, becomes increasingly important (Fabbe-Costes, Jahre, & Roussat, 2009, p. 72; Rabinovich, Windle, Dresner, & Corsi, 1999, p. 353). It is a com- monly agreed-upon premise that, for service providers in the logistics sector, mere re- acting will no longer be sufficient in the future. Instead, they will have to anticipate change and require management competencies to turn knowledge of potential develop- ments into a competitive advantage (Baumgarten, Darkow, & Walter, 2000, p. 12). As Jung (2000, p. 21) pointed out, future-oriented designs of value chains with respect to logistics will be some of the predominant challenges of the upcoming decades.

Strategic planning, with its aim to predict the future in a singular and often rather short- term way, can contribute to future-oriented thinking but might not be sufficient alone (Chermack et al., 2001, p. 7). Recently, by utilizing methods of futures studies such as scenario planning, foresight activities, which previously were rather part of governmen- tal policy programs, have become a part of the corporate world. According to Schwarz (2008, p. 237), in addition to an increasing number of corporate foresight activities, the strong managerial interest in the field of futures studies is reflected by a growing number of consultancies and think-tanks, a growing number of conferences, and numer- ous management-oriented publications encouraging companies to initiate and develop future orientation and corporate foresight activities (e.g., De Geus, 1997; Hamel & Prahalad, 1994b; Yates & Skarzynski, 1999).

In the literature, there is an ongoing discussion on the context and relevance of futures studies (e.g., Bell, 2001; Masini, 2001). Much attention has been given to methodologi- cal approaches, either in the form of overviews (e.g., Fink & Siebe, 2006; Steinmüller, 1997) or by focusing on single approaches (e.g., Barber, 2006; Gordon, 1994b). A large part of the latter discussion is dedicated to the scenario technique (e.g., Bishop, Hines, & Collines, 2007; Gausemeier, Fink, & Schlake, 1998). Recently, authors have aimed at establishing theoretical links between foresight and corporate strategy (e.g., Gruber & Venter, 2006; Major, Asch, & Cordey-Hayes, 2001). This theoretical discussion is accompanied by a growing number of studies on corporate foresight activities, mostly in large companies, in the form of large-scale studies (e.g., Schwarz, 2008), focusing on case studies (e.g., Ruff, 2004), or both (e.g., Burmeister, Neef, Albert, & Glockner, 2002; Müller, 2008).¹ Only very recently, have small and medium-sized enterprises (SMEs) also been considered (e.g., Burmeister & Schulz-Montag, 2008). In the logistics field, future-oriented studies mostly have the objective to identify or evaluate new management concepts or technologies (Baumgarten et al., 2000, p. 12). Therefore, most future-oriented studies aim at identifying specific trends (e.g., Straube & Borkowski, 2008; Straube et al., 2006). Jung (2000, pp. 21-22) concluded that, with regard to the logistics field, both the scientific community and the corporate world show a distinct deficit of future orientation. This is specifically true for the question of how logistics service providers themselves deal with future challenges.

The identified research gap at this point is thus to embed future orientation based on theoretical considerations of futures studies and corporate foresight in a logistics indus- try, which is increasingly exposed to future challenges. This is done by systematically analyzing how mainly German logistics companies, across the logistics service industry, address future issues. Therefore, the empirical contribution of this thesis follows a prac- tice-oriented research approach based on a standardized online survey and more profound semistructured interviews. The decision to use this approach is based on two considerations: First, from a futures studies perspective, Coates (2001) identified a lack of knowledge of “how the study of the future is conducted or used in the business community in the United States and Europe . . . because businesses have not been asked how they do it” (p. 5). Second, with regard to the logistics industry, Craighead, Hanna, Gibson, and Meredith (2007) recommended that a practice-oriented, “applied research” approach is appropriate and beneficial given the relative novelty of the research stream explicitly focusing on the logistics field. Furthermore, the regional focus on German (and a small number of Swiss) companies is justified by the outstanding importance of the German logistics industry (cf. chapter 4.4) as well as the fact that there is “very little literature on the usage of future studies in German corporations” (Schwarz, 2008, pp.

237-238).² Finally, the industry-wide setup of the study offers the potential to compare companies of different sizes and with different business models and helps achieve the aim of providing a broad and holistic picture of the industry.

The objective associated with this research approach is to get an overview of the status quo of logistics service providers’ future orientation and their exposure to corporate foresight thinking and methodologies of futures studies as well as to identify specific future challenges in an attempt to comprehensively investigate how service providers prepare for upcoming challenges. An important managerial implication of the study is to create awareness among the participating companies of the potential of foresight and its various methods for applications in the ever more complex and rapidly changing logis- tics industry.³ This further goal of the thesis seems noteworthy given that, from a practi- tioner’s view, Hines (2002) observed that “there is general agreement . . . that current organizational approaches to futures thinking are inadequate – that organizations are essentially doing a poor job vis-à-vis the future” (p. 344). Thereby, the underlying as- sumption, which is also reflected in the illustrative framework (Figure 1), is that logistics service providers are heavily impacted by their external context. Moreover, foresight activities and methodologies are, in accordance with the title of the thesis, assumed to be of benefit for the identification and evolution of future trends and their corresponding strategic relevance.

Figure 1. Framework.

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Source: Own illustration.

In line with the mentioned research goals, the benefits of this thesis are twofold: First, it contributes to the emerging discussion on foresight activities in corporations by adding an industry-specific analysis. Second, this thesis can help draw the attention of decision- makers to the fact that foresight might become one of the most important sources of competitive advantage in tomorrow’s economy (Hines, 2002, p. 339).

1.2 Course of the Investigation

To achieve the desired research objectives, theoretical considerations on futures studies and corresponding methodologies are combined with findings from existing foresight studies as well as specifics of the logistics industry (Figure 2).

The remainder of this thesis is organized as follows. Chapter 2 introduces the concept of futures studies as a systematic way to create future orientation. Although the field of futures studies is comparably new and lacks a profound theoretical conceptualization, the characteristics and methods of the field provide valuable insights. Thus, this chapter provides the foundation for the entire discussion. Within the chapter, after a brief histor- ical overview, a short discussion on frequently used terminologies and theoretic- conceptual characteristics of futures studies follow. Then, a conceptual overview of methods with the ability to support a systematic future orientation is provided. In chapter 3, the rationale behind future orientation of companies is outlined. After the discussion of a rather intuitive motivation for corporate future orientation, some theoret- ical remarks on the link between corporate foresight and corporate strategy are dis- cussed. Furthermore, existing empirical investigations on corporate foresight activities will be reviewed, which provide valuable insights for the empirical part of the thesis. Especially for the theoretical insights of chapters 2 and 3, relevant literature was searched for primarily using the keywords future(s) studies, future(s) research, futurology, foresight, corporate foresight, strategic foresight, Zukunftsmanagement, and Zukunftsforschung. Those keywords were moreover combined with other terms reflect- ing the structure of the chapters such as theory, methodology, history, definition, or characteristics. Where possible, the search was performed for varying elements of meta data (e.g., search in abstracts or tagged words) rather than focusing only on titles. The search was conducted mainly using the databases EBSCO, Emerald Insight, as well as Science Direct and was complemented by searches on Google Scholar. Moreover, several journals explicitly focusing on futures studies were screened.⁴ A list of those journals is provided in Table B1 in the appendix.⁵ Lastly, accommodating the fact that, with regard to futures studies, numerous books have been published, the search was extended to the e-book service SpringerLink, Google Books, and the interlending service subito using identical keywords.

Chapter 4 starts by introducing the logistics industry with a definition of the term and a demarcation from supply chain management (SCM). Afterwards, a theoretical introduc- tion to the concept of outsourcing as a fundamental reason for the increasing importance of logistics service providers is provided. Consequently, the next subchapter draws on these findings and identifies the different business models of logistics service providers, which are also used in the empirical part. Third, the relevance of the German logistics sector as the primary regional focus of the investigation is outlined before, finally, recent trend studies on the future of the logistics industry are reviewed. For the first two subchapters, a similar search algorithm as described earlier has been applied, however, in combination with keywords such as logistics, transportation, supply chain management, outsourcing, third party logistics, fourth party logistics, 3PL, or 4PL. The third subchapter is mainly based on an online search using Google. For the final sub- chapter, studies published by the German Bundesvereinigung Logistik (BVL) and the Deutsche Verkehrs-Zeitung (DVZ) have been reviewed. As a result, universities with active research institutions in logistics such as the Technische Universität (TU) Berlin and the Supply Chain Management Institute (SMI) at the European Business School (EBS) were identified and contacted to get access to corresponding studies.

Figure 2. Course of the Investigation.

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Source: Own illustration.

After details of logistics and the logistics industry have been outlined, chapter 5 describes the methodology used for the empirical analysis, arguing why a combined research approach in the form of an online survey and subsequent semistructured inter- views was selected and explaining the process of data collection. The combined research approach was selected after a brief literature review of suggested research methods for the field of futures studies and validated by suggested research approaches for the field of logistics. At the end of chapter 5, the relevant findings are combined to form a framework for the empirical investigation.

Consequently, in chapter 6, the results of the empirical analysis are presented and discussed in light of the theoretical foundations. Here, for each aspect, the results of the survey are presented before insights from the interviews are applied. To reflect the results in light of the previous findings of the thesis, an assessment of the results is in- cluded by the author.

Finally, chapter 7 presents the overall conclusions of the thesis. After a summary, impli- cations for theory as well as for management are determined. Moreover, limitations of the study and suggestions for further research are outlined.

2 Foundations of Futures Studies

After highlighting the goals associated with this thesis, this chapter introduces the field of futures studies. Therefore, a brief historical recap of the field will be provided, and various terminologies clarified for the discussion. Afterwards, a review of different attempts regarding a sound conceptual foundation is given before the general character- istics are introduced and important methods outlined.

2.1 Brief Historical Overview

Whether in the ancient world or in numerous other old cultures, humankind has always had an interest in methods of identifying and influencing the future (Kreibich, 2006, p. 3; Masini, 2006, p. 1158). However, until the 1930s and 1940s, future-oriented think- ing was limited to either utopias and philosophical models of society (e.g. by Thomas Morus or Karl Marx) or confined projections of natural scientific-technical processes (Kreibich, 2006, pp. 3-4). The end of World War II marked the starting point of the his- tory of modern futures studies especially through the development of specific research methods (Kreibich, 2006, p. 4). Although the future was and still is unpredictable, the developing field of futures studies can help to foresee certain developments and to think of alternatives. Therefore, preparing for the future and attempts to actively shape it no longer happen arbitrarily (Cuhls, 2003, p. 93).

In 1943, the German professor and emigrant Ossip K. Flechtheim coined the term futurology to describe a critical and systematic engagement with the future (Steinmüller, 1997, p. 10). Soon after World War II, efforts to “anticipate events through scientific analysis of trends and indicators of change” (Masini, 2006, p. 1159) first developed in the United States. The founding of the RAND Corporation, which invented such methods as the scenario technique and the Delphi method for military purposes, coin- cides with this time (cf. Table B2; chapter 2.5). Initially, also French scientists in partic- ular dealt with the scientific and political foundations of the future. In the seminal 1964 book L’Art de la Conjecture (The Art of Conjecture), Bertrand de Jouvenel developed the term futuribles, specifically emphasizing an alternative-based, nondeterministic concept of futures studies (Steinmüller, 1997, p. 10). Similar to the French futuribles, the English plural futures is heavily used to symbolize the open character of the future and thus marks an additional differentiating factor from the deterministic term forecasting (see Table B3 for a brief translation of terms) (Steinmüller, 1997, p. 11).⁶

One of the fundamental studies of the futures studies field, which had a sustainable im- pact on future thinking of politics, economy, and the civil society, was the 1972 The Limits to Growth commissioned by the Club of Rome, which is composed of 100 mem- bers in science, economy, politics, and culture from 40 countries. The study abstracted from mere technological developments and demonstrated the probable development paths of economic growth and global population with regard to the limitations of natural resources (Kreibich, 2006, p. 5). According to Bell (2001), after this publication, “it was no longer possible to ignore the worldwide dimensions of the challenges facing the hu- man community” (p. 64). However, due to a still large focus on quantitative methods and point forecasts, which often proved to be wrong, as well as the early development phase, the discipline stagnated until the 1990s and was rather neglected by decision- makers in the government and public administration sector, at least in Europe (Cuhls, 2003, pp. 94-95; Göpfert, 2009b, pp. 2-3). Since then and in light of the huge number of diverse and complex challenges due to globalized economies, environmental issues, social conflicts, and rapid technological innovations, talk of the future is in vogue again (Steinmüller, 1997, p. 2). Next to initial applications of the discipline in scientific or policy institutions, futures studies, in the form of corporate foresight, nowadays has a growing importance for corporations, too (Schwarz, 2008, p. 237). Figure 3 presents an illustrative graphical overview of the milestones in modern futures studies with special

regard to institutional and corporate futures studies activities.⁷ As can be seen, today, national or supranational foresight studies such as the Futur initiative in Germany (Fink & Siebe, 2006, pp. 63-64) and corporate activities are in the focus as well as numerous consultancies, institutions, and communities such as the two principal communities in the United States, the World Future Society and the World Futures Studies Federation.

Mermet, Fuller, and Van der Helm (2009) spoke in this context of “networks of practi- tioners, academics and consultants” (p. 68) as distinctive elements of the field. Table B2 provides additional information on well-known organizations. Next to the acknowl- edgement of these organizations, the novelty of the field and its continuing roots in pol- icy are the main insights gained from this brief historical overview.

Figure 3. Historical Overview of Futures Studies and Foresight.

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Source: Adapted from Ruff (2007), p. 3.

2.2 Classification of Terminologies

Among others, the different influences and the early development stage of the field out- lined in the previous chapter are responsible for the lack of consensus among authors. Thus, a common understanding in the form of a clear definition of what until now was called futures studies can hardly be obtained (Glenn, 1994c, p. 4; Major et al., 2001, p. 91). Instead, a range of terminology has emerged over time. While some authors use terms such as futures studies or futures research largely synonymously (Göpfert, 2009b, p. 2; Mermet et al., 2009, p. 67), others see slight differences in meaning (Glenn, 1994c, pp. 6-7; Müller, 2008, p. 18). The following paragraphs try to highlight some differ- ences in connotations of frequently used terms:⁸

As mentioned before, the term futurology was introduced in 1943 to describe a critical and systematic engagement with the future and marks the starting point of the modern, scientific field of futures studies (Göpfert, 2009b, p. 2). However, today, the term itself is largely regarded as outdated (Von der Gracht, Däneke, Micic, Darkow, & Jahns, 2008a, p. 12) and will thus not be further used within this thesis.

To reflect the military orientation of logistics at that time, the German professor Horst Wagenführ coined the term futurologistics in the 1970s, understood as an ancillary dis- cipline of futurology with the aim of providing the “infrastructure” in form of supplies required by futurology (Von der Gracht et al., 2008a, p. 12). Göpfert (2009a, p. 69), however, pointed out that futurologistics addresses logistics as part of futures studies, whereas the aim of this thesis is, vice versa, to discuss futures studies in logistics. Therefore, the term futurologistics is inappropriate in the context of this thesis.

The two terms futures studies and futures research are arguably the most commonly used terms. Often, authors do not explicitly prefer one or the other. To support the argument, in a poll conducted by the World Future Society in 1975 to derive the pre- ferred terms for the field, only these two terms received net positive responses (Von der Gracht, 2008, p. 10). Van der Duin (2004) explained his preference for futures research mainly because the term “research implies that no a priori standpoint is taken about whether the future can be predicted, made or explored” (p. 91). For Glenn (1994c, p. 6), the different connotation of the two terms can be summarized as follows: While futures research is rather decision-oriented and oriented toward decision-making, (academic) futures studies are subject- or question-oriented. Müller (2008) additionally described futures studies as “academic investigations” (p. 18). Therefore, and because the term futures studies is arguably more widespread among authors, the latter is used throughout the theoretical discussions of this thesis.

As already indicated in Figure 3, foresight is a rather modern term. It is often used in connection with national or supranational foresight programs, often also with a technol- ogy focus (Cuhls, 2003; Major et al., 2001). Coates (1985, p. 30, as cited in Cuhls, 2003, p. 96) saw the term as a step in policy planning to create an understanding of in- formation generated by looking in the future. Moreover, foresight is usually seen as a part of futures studies (Van der Laan, 2008, p. 28). According to Marien (2002, p. 270), foresight is, moreover, one of the most commonly used terms in the future field at the moment.⁹

Both variations, corporate or strategic foresight, are used to describe future-oriented activities of companies aiming at analyzing the long-term perspectives of business envi- ronments, markets, and technologies as well as their impact on strategies and innovation (Ruff, 2006, p. 279). These terms can thus be interpreted as the corresponding terms for futures studies within companies (Burmeister, Neef, & Beyers, 2004, p. 12). Futures studies in a corporate context will be further elaborated on in chapter 3. The term used there will consequently be corporate foresight.¹⁰

In conclusion, futures studies and its corporate application, corporate foresight, are the identified terms that will be used in the discussion. With respect to the title of this thesis, these terms and corresponding concepts form the ideal basis for approaching the identification and evolution of future (mega-) trends and their strategic relevance, where megatrends are understood as the selection and aggregation of most relevant trends with a lasting impact (Fink & Siebe, 2006, p. 126; Kreibich, 2006, p. 6).

2.3 Conceptual Foundations

As noticed by different authors, futures studies and corresponding methods have not been strongly rooted in theory yet (Chermack, 2004, p. 16; Göpfert, 2009b, p. 34; Higed, 2007, p. 36; Von der Gracht, 2008, p. 14; Wilkinson, 2009, p. 112). According to a recent statement of Wilkinson (2009), for instance, “scenario practices are under- researched and under-theorised” (p. 112). Two circumstances might, however, be responsible for this low stage of theoretic-conceptual development: First, for rather young scientific disciplines as futures studies, such a backlog is not unusual (Göpfert, 2009b, p. 34). Second, the fact that the discipline mainly emerged from practice ampli- fies this argument (Mermet et al., 2009, p. 67; Von der Gracht, 2008, p. 14).

In the words of Horx (2008, p. 5), current theory-based research approaches trace back to existing theoretical structural models. Consequently, authors name different theories as contributors to the futures field. Göpfert (2009b, pp. 34-36) briefly introduced connections to model theory, systems theory, evolutionary theory, creativity theory, and chaos theory. Model theory, for instance, can add valuable insights to develop models for the description, explanation, and projection of alternative future developments. In turn, model theory also contributes to the knowledge generation on the functionality of the system, which demonstrates that model theory and system theory complement one another (Göpfert, 2009b, pp. 34-35). With special focus on the scenario technique, Chermack (2004) particularly elaborated on the role of systems theory, finding that “the ultimate contribution of system theory to scenario planning seems to be the concept of self-organization” (p. 27). In light of the system theory, people might be able to recog- nize complexity, uncertainty, and causal relationships (Von der Gracht, 2008, p. 16). In addition to the theories already mentioned, Kreibich (2006, p. 4) and Von der Gracht (2008, pp. 19-20) discussed connections of futures studies to game theory. According to Von der Gracht (2008, p. 19), using game theoretical approaches can help in describing and simulating complex decision situations under uncertainty. Horx (2008, p. 5) men- tioned a number of additional contributing theories such as complexity theory, whereas Wilkinson (2009, pp. 111-112) referred to attempts to characterize scenarios in light of the social science theoretical frameworks of causal textures theory and sensemaking. With regard to the causal textures theory, scenario methods “help stakeholders to devel- op a better systemic understanding of the causal textures of the contextual environment” (Ramirez, Van der Heijden, & Selsky, 2008, p. 27) and at the same time “help in build- ing common ground among disparate stakeholders . . . that shuts turbulence out” (p. 27). Thereby, scenario thinking can support decision-makers to increase their “perceived adaptive capabilities” (Wilkinson, 2009, p. 111) under turbulent environment condi- tions.

In a special issue of Futures in March 2009, Mermet et al. (2009, p. 69) postulated two endeavors for a theoretical underpinning of futures studies: First, in accordance with the previously cited attempts, a mobilization of theories from other fields. In this context, Fuller and Loogma (2009) found that social constructionism is “implicit in many epis- temological assumptions underlying futures studies” (p. 71). According to the authors, futures studies are a social construction as well as a mechanism for social construction, which should be acknowledged as this will lead to “greater rigour and legitimacy” (p. 71). Booth, Rowlinson, Clark, Delahaye, and Procter (2009) focused on scenarios and put them in the context of modal narratives, concluding that confronting the modal nature of futures studies methodologies more explicitly might give “more secure philo- sophical foundations for their deployment” (p. 87). Second, however, Mermet et al. (2009, p. 69) also claimed a theoretical renewal from within the field. Therefore, Mermet (2009) started with analyzing crossovers to environmental research before eventually proposing an enlargement of the futures field and a discussion of an “open framework” as a theoretical basis and a guide for each study on futures.

A final note should be made on another current stream in literature that tries to establish a conceptual foundation for futures studies by utilizing contributions from integral theo- ry such as the four-quadrant model from Ken Wilber (Slaughter, 2001) to develop what is called “Integral Futures” (Slaughter, 2008a, 2008b). Voros (2008) described Integral Futures as an approach to futures inquiry based on “a meta-paradigmatic integral meta- perspective” (p. 199). According to Slaughter (2008a), the integral framework, for in- stance, established a focus on the “personal (and to some extent, social) interiors” (p. 104) from which futures studies methods emerged and enables an enhancement of the methodological basis (p. 107).

This brief review of the theoretic-conceptual foundations of futures studies revealed underdeveloped, heterogeneous approaches mostly seeking contributions from more established theories. To better grasp the essence of futures studies, however, the following chapter tries to highlight some important characteristics of futures studies before methods as the central elements of the field are introduced.

2.4 Fundamental Characteristics

Fundamental to any discussion of futures studies is the fact that future developments can neither be forecasted nor predicted in a complete and accurate fashion (Göpfert, 2009b, p. 4). With this in mind, futures studies postulate prospective thinking (Bell, 1997, p. 42). In the words of Bell (1997), the purpose is to “seek to know what can or could be (the possible), what is likely to be (the probable), and what ought to be (the preferable)” (p. 42). Therefore, the goal of futures studies is not to predict the future but to produce valuable orientation and decision knowledge as well as to provide process and methodological foundations (Burmeister et al., 2002, p. 13). As a field of study, futures studies contributes to increased efficiency and effectiveness of future-oriented research in scientific disciplines and practice, which is to be maximized (Göpfert, 2009b, p. 10). Applied in an organizational context, futures studies can thus, for in- stance, serve knowledge creation (Mendonca, Cunha, Kaivo-oja, & Ruff, 2004, p. 209).

As a consequence of the fact that futures studies do not aim at making exact predictions, the dominant notion is to think in alternatives. Voros (2005, p. 88) summarized this no- tion by arguing that although “pre-dictive”, futures studies are not about the common sense of the word but rather about thinking, writing, and speaking about which alterna- tive futures might happen. This is also why the plural futures is preferred over the singu- lar future (Von der Gracht, 2008, p. 13). In this context, the final future state of an ob- ject is usually less important than the change process leading to this state (Göpfert, 2009b, p. 5).

Futures studies are, per se, not connected to a specific object of investigation but can be universally applied. Thereby, the field has a multidisciplinary character and can be understood as a form of methods science similar to statistics (Göpfert, 2009b, pp. 6-7). In this context, Göpfert (2009b, p. 7) argued that futures studies provide foundations and methodological competence, whereas the application of these general methods has to remain in the corresponding disciplines. This characteristic is fundamental for this thesis since methodological basics will be discussed in the following chapter and analyzing the current state of the application in the logistics field is one of the goals within the empirical part in chapter 6.

In conclusion, futures studies can be regarded as a systematic way of thinking about alternative futures (Blass, 2003, p. 1042). Although statements on future affairs cannot be robustly proven (Mermet et al., 2009, p. 67), Blass (2003) described futures studies as essentially being “postmodern research, while also being interpretive and scientific” (p. 1053).¹¹ The following chapter will introduce basic futures studies methods, which are arguably the core of futures studies and should therefore largely build on the charac- teristics identified above (Göpfert, 2009b, p. 12; Mermet et al., 2009, p. 67).

2.5 Relevant Methods

A fundamental knowledge of methods used in the area of futures studies is a crucial step for the further discussion (Müller & Müller-Stewens, 2009, p. 25) since the methods significantly support the scientific or corporate foresight process (Göpfert, 2009b, p. 13). This chapter aims first of all at providing a brief overview of different classifica- tion schemes of futures studies methods. Moreover, frequently mentioned methods will be explained in detail, starting with the scenario technique. Thus, this chapter should deliver the required methodological basis for the following sections on corporate foresight in theory and practice.

2.5.1 Overview and Classification Schemes

There are numerous overviews of futures studies methods (Cornish, 2004, pp. 65-79; Fink & Siebe, 2006; Glenn & Gordon, 1994; Göpfert, 2009b, pp. 13-34; Marien, 2008; Müller & Müller-Stewens, 2009, pp. 235-242; Popper, 2008, pp. 64-66; Steinmüller, 1997, pp. 28-101). Authors have classified and clustered those methods in various ways. At the same time, although some methods are frequently mentioned, the range of methods is hardly similar among different authors.

Possibly the broadest classification of methods is provided by Marien (2008, pp. 2-3), who suggests the “5 P’s and a Q” (p. 2), referring to probable futures (e.g., forecasting), possible futures (e.g., scenarios and risks), preferred futures (e.g., strategies and agendas for change), present trends (e.g., indicators), panoramic views (e.g., systems), and ques- tioning. Although such a broad perspective gives valuable hints, for instance, on adja- cent research fields such as strategy (cf. chapter 3.2) or limits of the field as indicated by “questioning,” the classification and range of methods are not regarded as specific enough for this thesis. A rather “simple taxonomy of futures research methods” (Glenn, 1994c, p. 8) was established in 1994. As can be seen in Table B4, this classification uses two criteria: technique and purpose. In terms of technique, normative methods, which are based on norms and values and address the goal-oriented question of what future is desirable, can be differentiated from exploratory methods, which focus on the question of which futures are possible. Moreover, in terms of purpose, quantitative methods can be differentiated from qualitative methods (Coates, 1994, p. 1; Glenn, 1994c, p. 7). However, in both cases, the differentiations are not mutually exclusive. Especially with regard to normative or exploratory, the large number of double entries suggests that the majority of methods can essentially be used for both.¹²

Before the following two chapters focus on introducing specific methods, two remarks on the usage of methods shall be made. First, a tendency toward an increased use of qualitative methods in theory and practice can be observed. According to Göpfert (2009b, p. 18), qualitative methods are better suited for the specific requirements of scientific foresight. In practice, Hines and Trudeau (1999, p. 29) noticed a shift from quantitative to qualitative methods first in the consulting realm before a transfer to organizational futurists took place. In light of the already mentioned characteristics of futures studies, this seems logical given that qualitative approaches do not suggest non- existing security and might be able to better prepare for unexpected incidents (Hines & Trudeau, 1999, p. 33; Müller & Müller-Stewens, 2009, pp. 25-26). Second, methods should not be understood as distinct alternatives. Rather, results might often be used complementarily since no one method is appropriate in isolation (Blass, 2003, p. 1041; Hines, 2002, p. 343). Thus, applying several futures tools in a comprehensive way is “the rule rather than the exception in futures work” (Hines & Trudeau, 1999, p. 33). To further emphasize this, Göpfert (2009b, p. 33) attempted to allocate contributions of methods in a process model of futures studies (Figure A1).¹³ Looking at the difference between exploratory and normative approaches, Coates (1994, p. 1) argued that, in an organizational context, feedback among different methods is required to provide direc- tion for the organization.

According to Cornish (2004), although the most common methods are basically refine- ments of commonsense techniques, the methods can still be regarded as “rational, empirical, and scientific” (p. 78) and the opposite of “arcane . . . practices such as crys- tal-ball gazing” (p. 78). The methods identified as most common throughout the litera- ture review will be introduced in the following sections.

2.5.2 Scenario Technique

This section specifically focuses on the arguably most prestigious method of futures studies (Müller & Müller-Stewens, 2009, p. 236), namely the scenario technique.¹⁴

The modern understanding of scenarios has a military background. The technique was initially used in the 1950s by the RAND Corporation, a U.S. research group that was engaged in developing defense management studies for the U.S. Air Force. Hermann Kahn of the RAND Corporation was thus the first to introduce scenarios into planning processes.¹⁵ In a business context, the Royal Dutch Shell company was the first to adopt scenario planning as part of the company’s strategy in the early 1970s, to account for huge internal and external pressures (Bradfield et al., 2005, p. 798; Schoemaker & Van der Heijden, 1993, pp. 157-158). In parallel, the French head of the Department of Future Studies at SEMA, a firm also active in the defense sector, started to develop sce- narios for different French state-owned companies based on the work of the French phi- losopher Gaston Berger (Bradfield et al., 2005, pp. 802-803; Chermack et al., 2001, p. 18). After a period of expansion and success in large corporations in the United States and Europe, the use of scenarios declined in the 1980s due to several reasons such as an economic recession and, potentially, an oversimplified use leading to a mix-up with storytelling or, in other words, a wrong balance between technicality and superficiality (Bradfield et al., 2005, pp. 803-804; Chermack et al., 2001, p. 12). Scenarios are nowadays used in different fields, for instance, in crisis management for civil defense exercises, by public policy makers, futurist or educational institutes, businesses, or the scientific community (Bradfield et al., 2005, pp. 796-797).

After reviewing existing literature on the scenario technique, Bishop et al. (2007, p. 10) classified eight different types of scenario techniques with two or three variations each. Chermack et al. (2001, pp. 17-23) described seven different approaches to scenario development, all comprising slightly different steps or phases.¹⁶ Common elements among those approaches are two core notions of futures studies, namely to apply sys- tems thinking to the object of investigation and to think in multiple, alternative futures (Gausemeier et al., 1998, pp. 113-115). Scenarios thus tell multiple stories; however, each story needs to be plausible itself (Chermack et al., 2001, p. 24). In the following, an exemplary five-step approach relevant to corporate implementation as presented in the work of Gausemeier et al. (1998, pp. 115-126) and Göpfert (2009b, pp. 26-27) will be briefly explained:

- Step 1: Structuring and definition of the decision field: In the first step, the object of the scenario analysis, the decision field, needs to be clearly defined and assessed in its current situation including its structural characteristics.
- Step 2: Scenario-field analysis: A larger scenario field, for example, the envi- ronment of the company, is defined in addition to the decision field with the aim of identifying key influencing factors (internal or external) that either play an important role in the determination of the decision field or that are characteristic of the future development of the field.
- Step 3: Scenario prognostics: Projections, potential future developments for eve- ry key influencing factor, are developed based on explanatory models of the scenario developers, also incorporating extreme images.
- Step 4: Scenario synthesis: To achieve a presentation of possible future scenarios, projections are bundled to consistent combinations, often with the help of a consistency analysis.
- Step 5: Transfer and implementation: To implement the findings, an analysis of the effects of scenarios on the decision field has to be undertaken. Here, strengths and weaknesses as well as opportunities and threats of the decision field, that is, for instance, a company, need to be regarded in light of potential scenarios. In a corporate context, companies can then formulate responsive or proactive strategies.

The scenario technique mostly results in two to three, sometimes up to five, scenarios in the form of a verbal, prosaic, or quantitative description of a future situation and courses of developments (Chermack et al., 2001, p. 24; Müller & Müller-Stewens, 2009, p. 236). According to Burmeister et al. (2004, p. 46), scenarios are the prototype of corporate foresight.

2.5.3 Other Common Methods

After an introduction to the scenario technique, this subchapter will give a brief over- view of a broad range of specific futures studies methods.¹⁷ After a short introduction, in contrast to other overviews, an exemplary application in a corporate context, just as for the scenario technique, will be provided when reasonable. That way, this final sub- chapter leads to the next chapter of futures studies in a corporate context.

Wildcards

Wildcards¹⁸ can be defined as incidents with a low expected probability of occurrence, at the same time, however, having high impacts and consequences for organizations or societies in case of the incidents’ occurrence (Mendonca et al., 2004, p. 203). More pre- cisely, wildcards are “low probability, high impact events that happen quickly” (Barber, 2006, p. 77) and constitute a major shock for the system and a possible turning point of a trend or a social system. According to Mendonca et al. (2004), wildcard events are usually “serious, destructive, catastrophic, or anomalous and essentially not predictable” (p. 202).

In a corporate context, however, only wildcards that leave a chance to react are relevant.¹⁹ Wildcards allow decision-makers to draw conclusions about the consistency of the chosen strategies and the ability of the organizations to react to disruptive chang- es (Müller & Müller-Stewens, 2009, p. 237). As an example of a foresight practice building on wildcards, Mendonca et al. (2004, pp. 205-215) developed a wild- card management system with two components:

- Weak signals: Assuming that some events presage themselves through different levels of knowledge, environmental scanning methodologies can help in analyz- ing weak signals, which are understood as indicators of wildcards. Although not all weak signals turn out to be wildcards, monitoring and preparing for weak signals enables an effective mediation of certain wildcards in the form of an ear- ly warning system.

- Organizational improvisation: In converging conception and execution, organi- zational improvisation complements the monitoring of weak signals to retain the real-time management capabilities of wildcards. Here, organizational as well as process structural elements are required.

Wildcards in a corporate context offer the potential to challenge decision-makers’ mental models and reduce so-called blind spots by disclosing implicit assumptions (Mendonca et al., 2004, p. 216).

Technology Roadmapping

Technology roadmapping²⁰ aims at structuring and visualizing a potential or expected development path (Müller & Müller-Stewens, 2009, p. 238). Thus, this represents a use- ful technique to effectively identify, select, develop, and exploit technologies (Phaal, Farrukh, & Probert, 2001, p. 2). Technology roadmapping is used both in policy or national foresight initiatives and in the industry to support technology management and planning (Phaal et al., 2001, pp. 2-3; Salo & Cuhls, 2003, p. 79).

For application of technology roadmapping in a corporate context, Phaal et al. (2001, pp. 11-14) proposed a simple, so-called T-Plan process, for instance, to support product planning. This approach envisages four workshops, three focusing on the roadmap lay- ers market, product, and technology, whereas the fourth workshop merges these layers on a time-basis to construct a graphical illustration in form of a Gantt chart known as a generic technology roadmap.

Simulations and Gaming

Simulations describe activities to project different, hypothetical situations in time or place (Rausch, 1994, p. 3). Gaming refers to attempts to emulate dynamic real-world situations, often in the form of role plays (Cornish, 2004, p. 79). The interrelation of games and simulation is given since the latter is often the foundation of the first (Rausch, 1994, p. 4). Gaming methods also originated in a military context, where war- gaming was and still is used as a training instrument (Müller & Müller-Stewens, 2009, p. 240).

As one example from the field of simulation and gaming, wargaming was only recently discovered to be able to contribute to planning and decision-making. Before, wargaming was solely applied to help military personnel prepare for real situations and test plans (Kurtz, 2003, p. 12). The combination “business wargaming” is now used to describe a “role-playing simulation of a dynamic business situation” (Kurtz, 2003, p. 13), includ- ing different teams, which represent entities involved in the situation, and involving different rounds, which represent time frames or phases.²¹ Carried out in a business context, wargaming has the potential to test and focus strategies for the future (Kurtz, 2003, p. 20).

Creativity Techniques

Under creativity techniques, many often rather intuitive methods can be subsumed. In the following two paragraphs, brainstorming and morphological analysis as two well- known creativity techniques will be introduced.²²

Usually, brainstorming follows basic rules: a clear definition of the problem, the di- rective to apprehend each idea independent of how negligible it might sound, and the prohibition to criticize or discuss ideas during idea generation (Göpfert, 2009b, pp. 21- 22). To develop solutions, brainstorming builds on intuition based on experience, factu- al information, or imagination (Göpfert, 2009b, p. 21). A future-oriented, “structured brainstorming” approach is, for instance, presented in Glenn (1994a) with the “Futures Wheel” as an easy way to think through implications and to organize thoughts about future events or trends (p. 2). As with brainstorming, morphological analysis is no orig- inal futures studies method, but can be allocated to the group of creativity techniques (Göpfert, 2009b, pp. 21, 28). Morphological analysis was first applied by Fritz Zwicky for creative reconfigurations of jet engines in the aerospace industry (Coates, 1994, p. 7; The Futures Group, 1994a, p. 1). This analysis offers a way to identify existing or future gaps and enables an “organized invention” of new alternatives filling identified gaps (The Futures Group, 1994a, p. 3). Thus, mostly with regard to innovative issues, a prob- lem is broken down into its elements, which are analyzed individually (Göpfert, 2009b,

p. 28). Two steps are at the heart of morphological analysis: first, the identification and characterization of all relevant parameters leading to a solution, and second, the con- struction of a multidimensional matrix, which is referred to as a morphological box and whose combinations contain all potential solutions a problem (The Futures Group, 1994a, p. 3).

Delphi Technique

As with the commencement of the scenario technique, the Delphi technique, named after the Greek oracle at Delphi, was invented at the RAND Corporation as a way to assess the military potential of future technologies and emerged out of the consideration that, on the one hand, a group of experts has a higher probability of delivering correct predictions, but, on the other hand, expert panels are biased by, for instance, different levels of assertiveness of the members (Gordon, 1994b, p. 1). Thus, anonymity and feedback are the two central characteristics of the Delphi technique, which can best be described as a systematic, multistage questioning approach (Gordon, 1994b, p. 1; Von der Gracht et al., 2008a, p. 14). Among other procedural elements, the selection of participants is the key to a successful Delphi study, which can take place in the form of literature searches, recommendations, or other experts (Gordon, 1994b, p. 6). Please note that by trying to achieve a consensus among experts, the Delphi technique deviates from one of the characteristics of futures studies outlined in chapter 2.4, namely to think in alternatives for the future (Göpfert, 2009b, p. 19). Delphi studies are known for their application in technology, education, or healthcare (Loo, 2002, p. 762). Loo (2002), moreover, demonstrated the benefits of applying the Delphi method in an organizational context. Thereby, a moderator constructs a series of structured questionnaires through- out the Delphi, which are provided to the panel of experts together with feedback reports in an iterative process of three to four rounds (Loo, 2002, p. 763).

Cross-Impact Analysis

Originally developed by Theodore Gordon and Olaf Helmer as a game for the Chemical Company in 1965, cross-impact analysis aims at systematically analyzing interactions among future developments and thus forces attention to chains of causality (Chao, 2008,

p. 45; Gordon, 1994a, p. 1). In basic form, cross-impact analysis requires a list of future developments with initial probabilities. In the next step, the conditional probabilities of these future developments are compiled and displayed in a matrix format. The proba- bilities are then checked for plausibility in the overall context (Gordon, 1994a, pp. 10-13). Many revisions have been conducted by different authors so that at least three major categories for matrix entries have emerged (Chao, 2008, p. 46). Cross- impact analyses are often regarded as a special, quantitative form of the scenario tech- nique (Fink & Siebe, 2006, pp. 51-52).

Trend Analysis / Environmental Scanning

Trend analysis describes different methodological approaches for monitoring, analyz- ing, and interpreting various external trends based on, for instance, the analysis of media publications (Müller & Müller-Stewens, 2009, p. 235).

Müller and Müller-Stewens (2009, p. 235) differentiated five phases: from undirected scanning, profound monitoring, on-site scouting, drivers and context analyzing to evaluating relevant trends.²³ Other authors have described forms of trend analysis as “(environmental) scanning” (Cornish, 2004, p. 78; Gordon & Glenn, 1994). For Cornish (2004, p. 78), the word scanning correctly implies the systematic search of media. A final approach, which is noteworthy in this context, is the trend impact analysis, which aims at incorporating identified perceptions of future events into existing forecasting models. Thus, for instance, expert judgment can be incorporated into extrapolation based on historical data (Gordon, 1994e, p. 1). As the last method, forecasting in the form of time series analysis and econometric models will be introduced as follows.

Insights from trend analysis, especially when understood as analysis of publications or discussions with experts, can be regarded as the basis for other futures studies activities (Müller & Müller-Stewens, 2009, p. 235).²⁴

Time Series Analysis and Econometric Models

Time series analysis, similar to other statistical modeling techniques, assumes that historical developments can be reduced to quantitative data, which can then be applied to the forecasting of future developments, expecting this development to be, at least, similar (The Futures Group, 1994b, p. 1). Such mathematical methods to fit trend data can be rather simple (e.g., univariate cases, curve plotting) or very complex (e.g., multi- variate cases, regression analyses) (Göpfert, 2009b, p. 15; The Futures Group, 1994b, p. 2) and are often applied in classical forecasting (Müller & Müller-Stewens, 2009, p. 241). As ways of quantitative forecasting, these methods rely on the assumption that the past is “the prologue for the future” (Schwarz, 2008, p. 238). The prerequisites for these methods are, furthermore, the existence of a statistically definable issue and suffi- cient and qualitatively appropriate data (Göpfert, 2009b, p. 16; Müller, 2008, pp. 55- 56). Quantitative forecasting methods are often criticized as futures studies methods, among others, since these methods can hardly incorporate dynamics and discontinuities. However, quantitative forecasting methods still have a high relevance in practice and are thus also included in the empirical investigation (Müller, 2008, pp. 55-56).

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¹ The studies mentioned here can be distinguished from studies on implementations in a governmental or policy context (e.g., Glenn, Gordon, & Dator, 2001, pp. 181-185).

² In a broader context, Steinmüller (1997, p. 2) noticed a “peculiar,” insufficiently established scientific field of futures studies in Germany compared to other countries.

³ To underline this goal, a summarized version of the study results will be provided directly to all com- panies that participated in the survey.

⁴ According to Marien (2002, p. 265), when talking about the “futures journals,” one usually refers to Futures, Foresight, Futures Research Quarterly, Futuribles, and Technological Forecasting & Social Change. Except for the French Futuribles, these journals, among others, have been especially focused on.

⁵ The journal Futures Research Quarterly was not accessible through any of the mentioned databases or via a simple online search. However, the author was able to get in direct contact with a business man- ager of the publisher, World Future Society, to retrieve the requested articles.

⁶ For a more comprehensive overview on the history of modern futures studies in Germany and Europe, see for example Burmeister et al. (2002, pp. 24-29); an overview for the USA can be found in Burmeister et al. (2002, pp. 30-36).

⁷ Ruff (2004, p. 53) furthermore provided a comparison of foresight in the public and private sectors.

⁸ Other terms include, for instance, the French futuribles, which was however limited to western Europe, or futuristics, which was seen as interchangeable with futurology and futuribles (Von der Gracht, 2008, p. 10). See, moreover, Anderson (1997, p. 666) or Cuhls (2003, pp. 95-99) for a demar- cation from the term forecasting.

⁹ Please refer to Amsteus (2008, p. 57) or Müller (2008, p. 24) for an overview of the diverse defini- tions of foresight.

¹⁰ Müller (2008, pp. 17-25) defined the concept of strategic foresight in the form of a combination of the disciplines trend research and future research. Müller (2008, pp. 20-21), moreover, described organi- zational foresight, industry foresight, and managerial foresight in largely similar terms. Apart from that, Rohrbeck (2008) defined other terms by building on the concept of foresight, namely operational foresight, technology foresight, competitor foresight, consumer foresight, and political foresight.

¹¹ For an overview of the discussion whether futures studies can be regarded as a unique discipline, see Von der Gracht (2008, pp. 11-12).

¹² This might be a reason why the differentiation between qualitative and quantitative methods is more often used in literature.

¹³ According to the author, this should, however, not be regarded deterministically, but rather to get an impression of potential application fields within a generic futures studies process. Gordon (1994c, p. 9) provided an alternative approach for this argument by highlighting how methods can support one another.

¹⁴ Next to the term technique, the terms planning, thinking, analysis and development are among others regularly attached to the term scenario, given a variety of mostly slight modifications by different au- thors (Bradfield, Wright, Burt, Cairns, & Van der Heijden, 2005, p. 796) or a hierarchical order so that, for instance, scenario development might be understood as part of scenario planning (Bishop et al., 2007, p. 6). For simplification, these differences are ignored in this overview.

¹⁵ Later on, Kahn established the Hudson Institute, where he applied the scenario technique to social forecasting and public policy, for instance, in his controversial book The Year 2000 (Bradfield et al., 2005, pp. 798-799).

¹⁶ These are approaches explained under the headlines Global Business Network, the French School, Reference Scenarios, Decision Strategies International, Procedural Scenarios, Industry Scenarios, and Soft Creative Methods Approach.

¹⁷ The methods introduced here are identical to the ones asked for in the empirical investigation (cf. chapter 6.4) with the following exceptions: (a) Expert judgment as an intuitively understandable way of collecting information on the future, which is sometimes also referred to as genius forecasting (Coates, 1994, p. 4; Glenn, 1994b, p. 2), was included in the survey but not explicitly further ex- plained at this point. (b) Early warning systems as often indicator-based approaches in a larger risk management process are not necessarily related to futures studies (Müller, 2008, pp. 28-29); however, they are an established and closely-related concept, especially in Germany (Schwarz, 2008, p. 239) and are therefore included in the survey, but not explicitly in this overview. They can, however, be re- lated to the concept of wildcards as will be seen.

¹⁸ Apart from the term wildcards, other terms found to have the same or a similar meaning are disruptive events, structural breaks, discontinuities, surprises, bifurcations, unprecedented developments, etc. (Mendonca et al., 2004, p. 203).

¹⁹ Here, “a meteor hitting the Earth” would, for example, not be considered as leaving a possibility for decision-makers to react (Mendonca et al., 2004, p. 202).

²⁰ With technology sequence analysis, Gordon (1994d) described a similar approach, developed in the 1980s, “to produce a probabilistic forecast of the time at which a technology-dependent system could become available” (p. 1), which is, however, rather based on quantitative assessments.

²¹ According to Kurtz (2003, p. 13), business wargames require extensive preparation as well as usually an interaction of 2 to 4 days and 20 to 50 active participants. For an example of a step-wise approach of business wargaming, see Exhibit 3 on p. 19 in Kurtz (2003).

²² In addition to the introduced methods, other idea-generating methods such as idea mapping also be- long to the group of creativity techniques (Cornish, 2004, p. 79). Moreover, the relevance tree analysis with certain similarities to morphological analyses can be found in Coates (1994, p. 6) or the Futures Group (1994a). Other methods, which could potentially be mentioned here, would be future work- shops, which, however, largely focus on more democratic policy decisions, or as an advancement of the latter, future seminars, often consisting of larger group workshops (Göpfert, 2009b, pp. 31-32; Schwarz, 2008, p. 239). These will, however, not be explained in detail at this point.

²³ See Cornish (2004, p. 78) for a similar approach.

²⁴ Note that, due to this connection, one of the questions within the survey specifically focuses on the usage of media and other sources of information (cf. chapter 6.4).