Networking for sustainable Foresight: A Russian study
A key element of any government's Science, Technology and Innovation policy is stable analytical infrastructure to support strategic decision making. Experience from many countries shows that substantial policy decision making requires collecting and analysing a broad range of information to develop proactive and future-oriented policies. Accordingly, infrastructure providing this information as well as evidence for policy-making must possess the capabilities for collecting, assessing, and processing information. However, information in this context is highly specific and subject related information, which is frequently embodied within expert knowledge holders. Therefore, information management in this light imposes special challenges on infrastructure. The present study discusses some methodological approaches and practical studies to set up a network of STI Foresight network in Russia, integrated into the national Foresight and planning system. We outline the principles for goal setting, network architecture, creating a network of experts, selecting key information products, and methodological support. Russia's STI Foresight network, built on principles presented here, has been fully operational since 2011 and provides expertise on a large scale for a variety of governmental and industry organizations.
This book develops foresight techniques to turn future societal challenges into opportunities. The authors present foresight approaches for innovation policy and management. Future developments in fields such as education, energy, new materials, nanotechnologies are highlighted for different countries. Readers will discover tools and instruments to capture the potentials of the grand societal challenges as defined by the United Nations. This book is a valuable resource for researchers and scholars with an interest in foresight methods and gives practical hints for policy makers and managers to take account of the grand opportunities in their business and policy strategies.
Decision-makers at all levels are being confronted with novel complexities and uncertainties and face long-term challenges which require foresight about long-term future prospects, assumptions, and strategies. This book explores how foresight studies can be systematically undertaken and used in this context. It explicates why and how methods like horizon scanning, scenario planning, and roadmapping should be applied when dealing with high levels of uncertainty. The scope of the book moves beyond “narrow” technology foresight, towards addressing systemic interrelations between social, technological, economic, environmental, and political systems. Applications of foresight tools to such fields as energy, cities, health, transportation, education, and sustainability are considered as well as enabling technologies including nano-, bio-, and information technologies and cognitive sciences. The approaches will be illustrated with specific actual cases.
This paper aims to present a set of strategic options for Research and Innovation (R&I) stakeholders in the light of new and emerging ways of organising and performing research. Design/methodology/approach: The paper first reviews the evolution of the R&I landscape and identifies the most influential stakeholders engaged in R&I. In the light of the scenarios developed for the year 2030, a set of strategic options are identified and assessed for each stakeholder group. Findings: R&I systems are now more complex than 50 years ago and will be even more in the future. Radical changes are expected in terms of the ways research is funded, organised and carried out. Some of these transformations are captured by the scenarios developed. The analysis of scenarios indicated that their feasibility and desirability differ across different sectors of industry, and research areas within the research landscape. Research limitations/implications: Scenarios and strategies presented in the paper bring new considerations on the way research activities are practiced. Further research is considered to be useful on the new modes of research and implications for academia, industry, society and policy makers. Practical implications: The discussion around the responses of different stakeholders vis-à-vis specific scenarios about the future in R&I practices and organisation gives a practical view about how to deal with associated emerging trends and issues. Social implications: Society is a crucial stakeholder of all R&I activities. The transformative scenarios suggest that society will not only be playing a reactive role on the demand side but also more proactive role on the supply side in the decades to come. Originality/value: The paper is based on work undertaken within the Research and Innovation (RIF) 2030 project. As R&I activities will be important for the development and competitiveness of the EU and its member states, the work presented here is considered to be of value by highlighting how to create more resilient strategies in a fast-changing R&I landscape.
Purpose – This paper aims to describe and discuss the architecture of Russia’s Technology Foresight System (TFS). This paper introduces the reader to the integration of the TFS into the public administration system and, specifically, into the national strategic planning system.
Design/methodology/approach – To do so, the authors fall back on more than 10 years of experience in performing foresight exercises for Russian policy makers of their institution.
Findings – Thereby, the paper highlights the implications arising from the interaction between sectoral and national components of TFS and on application of the results of foresight studies (implemented within the framework of TFS) for the strategic planning.
Originality/value – Russia has a long history of technological planning and forecasting and engages regularly in extensive foresight activities of both national and sectoral relevance. Also, Russia’s leadership repeatedly stresses the importance of such foresight activities which are outlined by a national law since 2014.
Technology mining (TM) helps to acquire intelligence about the evolution of research and development (R&D), technologies, products, and markets for various STI areas and what is likely to emerge in the future by identifying trends. The present chapter introduces a methodology for the identification of trends through a combination of “thematic clustering” based on the co-occurrence of terms, and “dynamic term clustering” based on the correlation of their dynamics across time. In this way, it is possible to identify and distinguish four patterns in the evolution of terms, which eventually lead to (i) weak signals of future trends, as well as (ii) emerging, (iii) maturing, and (iv) declining trends. Key trends identified are then further analyzed by looking at the semantic connections between terms identified through TM. This helps to understand the context and further features of the trend. The proposed approach is demonstrated in the field photonics as an emerging technology with a number of potential application areas.
Foresight has gained much attention as a tool for developing and informing science, technology and innovation policy and company strategies. It is frequently used for detecting not only potential development paths of technologies but also possible economic and societal changes; and for identifying challenges that nations, societies and companies might face in the future. Raising awareness within the respective communities of trends and challenges is critically important—and the biggest challenge is how we can develop measures to meet these anticipated challenges. Paradoxically, perhaps, it may be more helpful for creating and implementing successful measures if these are elaborated by thinking about grasping opportunities, rather than framing them in terms of threats that have to be responded to. Accordingly there is a need to change the mindsets in science, technology and innovation policy making—and to engender solution and opportunity orientation among scientists and engineers.
Technology foresight has been increasingly undertaken by developing countries to identify technologies whose adoption might serve as a platform for future economic growth. However, foresight activities have not, by and large, resulted in well-developed policy initiatives. Three factors are relevant for improvement. First, foresight activities would benefit from being more informed by the convergence literature and global convergence experience over the past several decades, and should therefore incorporate organically the concepts of absorptive capacity and technology gap into foresight exercises. Second, certain preconditions – in particular the existence of a functional national innovation system – enhance the likelihood that foresight exercises will be successful. Third, in order to achieve wide buy-in and promote the sustainability of initiatives generated by the foresight activity, developing countries are advised to consult widely in the foresight process. Policies emanating from foresight activities should additionally address two core challenges: a) a clear definition of those technologies that should be developed internally vs. those that should be sourced from abroad and b) identification of the internal capabilities to be developed in conjunction with those technologies targeted for acquisition from abroad.
Science, technology and innovation (STI) involves numerous policy fields which are championed by different government ministries or agencies. A consistent and coherent anticipatory policy mix is understood to be one that ensures a timely development and implementation of various forward-looking policy instruments. Such timely implementation is crucial for the eventual impact of the policy measures. This also requires that foresight for STI policies looks beyond the potential development paths and challenges but includes the time dimension and the outline of necessary policy responses including a relevant implementation framework. In addition the institutions which are part of the National Innovation Systems (NIS) should to be considered thoroughly for a well-balanced and comprehensive policy mix. Not only national but also regional and local actors need to be involved—and they need to be involved not only in the implementation of policy but at much earlier stages in the foresight and subsequent design procedures of the policy mix. One practical approach for convincing and engaging NIS actors at different levels is to stress opportunities which offer advantages to each of them, instead of just focusing on challenges and problems.
Smoking is a problem, bringing signifi cant social and economic costs to Russiansociety. However, ratifi cation of the World health organization Framework conventionon tobacco control makes it possible to improve Russian legislation accordingto the international standards. So, I describe some measures that should be taken bythe Russian authorities in the nearest future, and I examine their effi ciency. By studyingthe international evidence I analyze the impact of the smoke-free areas, advertisementand sponsorship bans, tax increases, etc. on the prevalence of smoking, cigaretteconsumption and some other indicators. I also investigate the obstacles confrontingthe Russian authorities when they introduce new policy measures and the public attitudetowards these measures. I conclude that there is a number of easy-to-implementanti-smoking activities that need no fi nancial resources but only a political will.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.