Foresight As Innovation Policy Tool in Smaller Catching up Economies: Grand Narratives

Fourth International Seville Conference on Future-Oriented Technology Analysis (FTA)
FTA and Grand Societal Challenges – Shaping and Driving Structural and Systemic Transformations
Seville, 12-13 May 2011

Foresight as innovation policy tool
in smaller catching up economies:
Grand Narratives or Intelligent Piggybacking?

Marek Tiits

Institute of Baltic Studies,

Tarmo Kalvet

Tallinn University of Technology,

Extended abstract

Keywords: foresight, small economies, catching-up economies

Introduction

Following the example of Western Europe and many other developed economies, the 2000s saw a rise in the popularity of foresight practices in the smaller catching-up economies of Central and Eastern Europe. However, these foresight exercises have not always had an impact on actual policy processes.

The paper raises several methodological issues related to foresight practices in smaller catching-up countries. Two case studies are used to examine the role and impact of recent technology foresight exercises on Estonia’s public policy and to draw lessons from them: (1) the pilot foresight action in the fields of ICTs, biotechnology and nanotechnology within the EU FP6 eForesee project (Tiits et al 2005) and (2) the more recent EST_IT@2018 foresight exercise undertaken by the Estonian Development Fund (Tiits & Rebane 2009).

Methodological issues

Recent foresight literature and practice has treated all economies as largely the same, and has focussed mainly on different foresight methodologies and on the results. Contrastingly, economics literature distinguishes between advanced economies that operate at the cutting edge of the development of new technologies, and catching-up economies that are still striving to reach the technological and living standards of the advanced economies. This means, however, that sources of technological learning, innovation and economic development are very different in these two groups of economies. Furthermore, the smallness of an economy adds an extra layer of innovation-related complexities in the current globalised world (Kattel et al 2010, Tiits 2011).

Recent technology foresight activities in Europe have built on an approach that can be termed ‘Grand Narrative’ - foresight exercises, which aim at defining the possible future development scenarios or trajectories at the cutting edge of a given field of technology. While this approach is a reasonable choice for major industrialized economies, its feasibility for smaller catching-up economies is questionable.

We argue that the smaller catching up economies should opt instead for an ‘Intelligent Piggybacking’ approach to foresight. It is an approach that acknowledges that:

-  the future key technology trends are set by major advanced economies, and it is not feasible for the smaller catching-up economies to influence these;

-  the future growth in market demand is likely to occur in specific areas where there are major socio-economic challenges both domestically and globally.

In other words, the central foresight question for smaller catching-up economies should not be “What are the key technology areas for indigenous technology development”, but rather “How to restructure and upgrade the existing technological and production capabilities, so that the country will be able to adopt the latest (imported) technologies in producing high-value-added exportable goods and services.”

Accordingly, for the successful adoption of the Intelligent Piggybacking approach, it is important to have a good understanding of the scientific and technological capabilities of the particular country. It is also important to have a good command of the main externally defined science and technology trends, and of the country’s position in the global production/innovation networks and trade.

Results and implications

In the eForesee project a major effort was made to map the R&D priorities of the major advanced economies in the fields of ICTs, bio- and nanotechnologies. An important conclusion that emerged was that proper understanding of the economic cycles and techno-economic paradigms can actually serve as very useful guidance in the foresight and the elaboration of policy strategies. As part of Intelligent Piggybacking foresight, the sources of Estonia’s recent economic growth were determined at the level of specific industries. Building on this, as well as on the historically successful catching-up experiences of Finland, Ireland, East Asia and elsewhere, three distinctly different policy scenarios were devised, which discussed technology trends, industry life cycles, flows in foreign direct investments, global market dynamics and the likely relocation of various industries in time (Tiits et al 2005).

The subsequent EST_IT@2018 took note of the fact that the on-going ICT paradigm continues to be an extremely powerful driver for productivity growth. Accordingly, in this work, specific priorities were defined for: (1) the advancement of scientific and technological capabilities, so that Estonia could command the latest ICTs developed in the major advanced countries and (2) the development of new ICT-based products and services in the specific domains where major socio-economic challenges were detected and, in connection with this, also significant growth in market demand was expected elsewhere.

Conclusions

Failures in the transfer of policies from one country to another are widely acknowledged. Similar failures can also occur in the transfer of policy intelligence and policy making tools, such as foresight. Therefore, critical assessment of the context and the adaption of the methodology toolbox are very necessary.

The key lesson from the two recent foresight exercises in Estonia is that the traditional approaches to technology foresight, which are typically employed in larger advanced economies, are not applicable to smaller catching-up economies. We argue that the Intelligent Piggybacking approach is much more suitable for those countries than the traditional Grand Narratives approach. The reason for this is that the smaller catching-up economies rely extensively both on imported technologies and on export markets. This is why the foresight exercises carried out in such smaller countries need to be carried out as truly international efforts that secure an access to the state-of-the-art in frontier R&D, and to the latest strategic thinking in the relevant global production networks.

References

Kattel, Rainer, Tarmo Kalvet and Tiina Randma-Liiv (2010) Small States and Innovation. In: R. Steinmetz and A. Wivel (Eds.) Small States in Europe: Challenges and Opportunities. Aldershot: Ashgate.

Tiits, Marek, Rainer Kattel and Tarmo Kalvet (2005) Made in Estonia. Tartu: Institute of Baltic Studies, http://www.ibs.ee/MiE/.

Tiits, Marek and Kristjan Rebane (2009) Eesti infotehnoloogia tulevikuvaated [Future outlooks of Estonian ICT], Tallinn: Estonian Development Fund, http://www.arengufond.ee/eng/foresight/estit2018/.

Tiits, Marek (2011) Technology Foresight and the Catching-up Strategy in Small Countries: The Case of Estonia, Tallinn: Tallinn University of Technology.

Working draft, 6 May 2011

Foresight as an innovation policy tool in the small catching up economies: Grand Narratives or Intelligent Piggybacking?

Summary

The current article discusses the role of the technology foresight in the small catching-up countries. It reflects on the lessons from the foresight activities which were carried out in Estonia during the last decade, including the pilot foresight action in the field of ICT and biotechnology within the eForesee project (Tiits et al 2005) and the more recent ICT 2018 foresight exercise (Tiits and Rebane 2009).

As the starting point, we introduce clear distinction between advanced economies that are on cutting edge of development of new technologies, and catching up economies that seek to reach the technological and living standards of more advanced economies. As we discuss, the technological capability building and innovation occurs very differently in the catching-up economies as compared to the advanced economies. Furthermore, the small economies are characterised by their own constraints and advantages. Accordingly, as we argue, the whole setup of the foresight process needs also to be very different in the (small) catching-up economies from the one used in the larger advanced economies.

We argue that the “Grand Narrative” approach, which is typically employed in larger advanced economies for defining the future technology development trajectories, is not very practicable for catching up economies. With “Grand Narratives” we refer to the foresight practice, which focuses primarily on the domestic scientific and technological activities, and the future socio-economic benefits the indigenous technological development is expected to bring about. We argue that the smaller catching up economies, like Estonia, should opt instead for an “Intelligent Piggybacking” approach to the foresight, as a more suitable alternative. With “Intelligent Piggybacking” we refer an approach which relies on the extensive analysis of the science and technology priorities of the larger advanced economies and uses this as a crucial input for the priority setting in the education, science and technology as well as in the entrepreneurship and foreign investment policies, etc. in the catching-up economy.

1  State of the art in the research and in the foresight practice

Both the foresight activities as well as research on foresight have vastly developed since the first foresight activities were carried out in the 1970s (Miles et al. 2008). Miles (2010) argues that technology foresight took especially rapidly off in the 1990s, as countries sought new policy tools to deal with problems in their science, technology and innovation systems. Large-scale exercises drew in numerous stakeholders as sources of knowledge and influence, and the prominence of these exercises led to the term foresight being used much more widely for describing the futures activities of many kinds. While few new tools and techniques have been developed in these exercises, they represent an unprecedented diffusion of forecasting, planning and participatory approaches to long-term issues. Futures approaches are, in consequence, far more officially acceptable and legitimate than in the past (Miles 2010).

Over this time foresight has developed from largely technology forecasting activities (with the analyses driven mainly by the internal dynamics of technology) to more simultaneous inclusion of technology and markets, and also social dimension at the later stage. The modern foresight programmes seek increasingly to inform the strategic decision-making or even be included into the preparatory phases of it (Miles et al. 2008, 15-21; Georghiou 2001).

The modern foresight discourse has developed a comprehensive toolbox of methodologies that can be applied largely everywhere. The current trends in foresight domain are moving toward the integration of quantitative and qualitative methodology for the design and evaluation of national foresight, and the increasing cross-border and thematic foresight activities as well as using electronic tools.

The modern foresight literature discusses foremost certain methods of social sciences, e.g., scenario writing, vision building, workshops, Delphi surveys, etc. (Gavigan et al. 2001, Georghiou et al. 2008). Although some of the literature (e.g., Havas 2003, Porter 2010) cautions that there is no one way to conduct effective foresight studies and different foresight endeavours call for the application of different foresight methods, the established literature tends still to discuss primarily the various participatory elements and process orientation of the recent foresight exercises. It tells, however, much less about the particular socio-economic and public policy context in which the particular exercises have been carried out (Miles 2010). This, however, limits substantially the possibilities for learning from the various foresight exercises across the different countries and continents.

Still, several gaps can be identified both in the foresight activities as well as in the foresight literature. The remaining unsolved issues are, at least, the further development of the optimal procedures of technology foresight and the more systematic evaluation framework of foresight (Yuan and Cheng, 2010). Also, foresight needs to be virtually always complemented with the relevant strands of technology, social sciences and economics theory that integrate the local context. A more in-depth discussion of the lessons of the previous experiences would prove highly valuable in the above multidisciplinary theory context in particular.

When discussing the economic development, the various foresight exercises build mostly on innovation systems approach (Freeman 1987; Lundvall 1992; Nelson 1993). The community of foresight practitioners overlaps also, partially, with the innovation systems scholars. It is therefore not surprising to see that a number of recent foresight programmes have been specifically aiming the improvement of the functioning of the particular national or regional innovation systems (Miles et al. 2008, 15-21; Georghiou 2001).

The research on science, technology and innovation policies originates from developed countries, most of them large economies, and it is still mostly done based on developed economies (cf. Edquist and Hommen 2008). There are, however, quite substantial differences between the socio-economic development patterns in the advanced economies and the developing (e.g., Cimoli 2000, Lundvall et al. 2009) or catching-up economies (e.g., Radoševic and Reid 2006). Crucially for the current discussion, the dominant sources of the technological inputs are very different in the developed and catching-up/developing countries.

In the catching-up countries, technology transfer and efficiency seeking are the main drivers of growth rather than R&D and technology development. The capacity building and innovation that takes place in these countries is better described by the “doing, using, and interacting” mode rather than the “science, technology, and innovation” mode of innovation (see Jensen et al. 2007). The Nelson’s (1993) narrow approach to innovation systems that focuses predominantly on the R&D systems is, therefore, not suitable for analysing the developing/catching up economies. The broader approach advanced by Freeman (1987) and Lundvall (1992) is much more suited for developing and catching-up economies. It is, however, still insufficiently formalized and proves thereby very difficult to apply. Smallness of countries adds additional level of complexities and is not addressed in enough details in current research (Kattel et al. 2010).

Also, there is an issue related to paradigm-based, activity-specific priority-setting – focusing on economic activities with a high potential for learning, the so-called “high quality economic activities” and policies promoting economic restructuring that have been always important for successful states (Reinert 2007). Indeed, industrial policy – policy “aimed at particular industries (and firms as their components) to achieve the outcomes that are perceived by the state to be efficient for the economy as a whole” (Chang 1994, 60) – has been a cornerstone of economic policy of all successful states. However, much of the recent research on innovation systems considers all types of innovations (from incremental minor changes to the global technological breakthroughs) and all fields of technology and industries largely the same. The Community Innovation Surveys (CIS, Eurostat) and the various research that builds on the CIS data are perhaps the most prominent manifestations of this.

The Porter’s research on clusters (e.g., 1990), as a popular alternative for analysing the innovative activities in the enterprises, is more helpful in allowing the analysts and policy-makers to focus on the existing specialisation of the particular economy and the possible future evolution of it. Porter, like innovation systems literature, is, however, also unable to explain sufficiently why and how the different economic activities get relocated globally in time. Also, it considers, similarly to the above, all technologies and industries to carry the same potential for the future economic development.