Wars have been a part of humanity since prehistoric times, and are expected to remain an important component of future human societies. Since the beginning of the history wars have evolved in parallel with the changes in Society, Technology, Economy, Environment, Politics and Values (STEEPV). The changing circumstances unavoidably affect the characteristics of warfare through its motivations, shape and size. Armies have adapted themselves to these changing characteristics of warfare through Revolutions in Military Affairs (RMAs) by introducing new military concepts and technologies. Based on the overview of the evolution of military technologies and concepts as a response to changing conditions, the aim of the present study is to anticipate what and how future technologies and concepts will shape warfare and drive impending RMAs. To answer this question, first the RMA literature is reviewed within a broader historical context to understand the extent to which military concepts and technologies affected the RMAs. Then, a time-based technological trend analysis is conducted through the analysis of military patents to understand the impact of technological developments on military concepts. Following the historical analyses, two scenarios are developed for the future of military R&D based on ‘concept-driven’ and ‘technology-driven’ factors. The article is concluded with a discussion about the implications of future scenarios for military R&D, and likely RMAs through the changes of concepts and technologies, and possible consequences such as transformations in organizational structures of armies, new skill and capacity requirements, military education systems, and decision-making processes.
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.
Over the last few decades, performance-based funding models of universities have been introduced and have made universities build and implement different strategies to enable them to compete and be viable in changing circumstances. In turn, national governments are focused on providing universities with more opportunities to run efficient programmes that advance higher education. This paper includes a detailed review of various taxonomies for structuring university. More importantly, it develops a typology of higher education institutions that is relevant for the Russian context. The Ward method is used to cluster universities on the basis of university distinctions in terms of the availability of resources, education, and research and development. This typology of universities is verified by assessing their efficiency score gained from modified Data Envelopment Analysis,incorporating universities' heterogeneity. Finally, the paper gives a decision tree for classifying universities bearing in mind their diversity. It might be expanded for abroader set of inputs and outputs, namely external projectbased research funding modes and cooperation between universities and industry to pursue the development of innovation. The results can be used for shaping targeted policies aimed at particular university groups
This paper addresses the issue of priority setting for research programming in a multi-layered and multilateral context, taking into account the interests of diverse stakeholder groups. It proposes a framework for reducing complexity in a context where societal challenges are multifaceted and largely interconnected, decisions on research programming are highly fragmented and stakeholders are extremely diverse. The framework includes methodological recommendations for thematic priority setting through the application of Future-oriented Technology Analysis (FTA). Also the importance of achieving clear policy impacts (see Johnston and Cagnin, 2011) is addressed by including principles for optimising this impact. We use the case of an ERA-NET project supported under the EU’s FP7 programme, the ERA.Net RUS, which aims at coordinating R&D and innovation policies and support programmes between EU Member States, countries associated to the 7th Framework Programme (FP7) and Russia. A combination of foresight methodologies such as expert workshops, a Delphi survey, roadmapping elements, and prioritisation techniques were applied to select relevant topics for a research call. The paper highlights how foresight embedded in a multilateral programme cooperation project can support priority setting and how the foresight design can be adapted according to a set of coordination dimensions and design principles. Furthermore lessons will be drawn in order to achieve direct impacts, not only on the programming of calls for research projects addressing grand societal challenges (e.g. climate change, major diseases, demography and migration, etc.) between a wide range of countries and regions belonging to different parts of the world, but also on the EU level policy agenda and on the long-term strategic collaboration between world regions. Strategies for communicating foresight results to relevant policy makers at EU and national levels (e.g. in Russia) and for achieving impact herewith are also outlined.
Due to limited energy sources and growing concerns about environment, secure, safe and sustainable energy has become one of the Grand Challenges at the global level. Likewise in many other aspects of life, energy is crucial for military forces. In parallel to the changing nature of warfare, the need for energy in military operations has increased dramatically. While energy consumption in the World War II was 1 gal per soldier per day, it was 4 gal per soldier per day during the Desert Storm operation in 1991. Not only the quantity, but also the type of energy required for military operations has changed dramatically. Shifts have been observed from individual man power to machines powered by fuel and electricity. Energy demand and type have changed further through the introduction of more sophisticated devices with new capabilities such as to enable night vision, designate targets with lasers, provide advanced sensing and communication capabilities and reduce human involvement in operations through drones and robotic technologies. Investigating the trends in changing nature of warfare and energy through review, technology mining and scientometrics, the present study develops future scenarios, and a strategic roadmap to identify priority technology areas and strategies for the future military energy R&D.
The article elaborates an approach of combining Foresight and integrated roadmapping for corporate innovation management. The proposed management instrument goes beyond the existing roadmapping and corporate Foresight approaches by integrating them and showing the interface to corporate strategy building. Corporate Foresight and integrated roadmaps are closely interlinked and show reasonable potential to maintain the current level of organizational innovation culture and also enable future improvements.We propose a new roadmap structure and reveal the main ways to use this technique in business planning. Finally, the paper applies the suggested approach through case studies of major Russian companies in the oil & gas, energy, and aviation sectors.
Roadmapping is a complex long-term planning instrument that allows for setting strategic goals and estimating the potential of new technologies, products, and services. Until recently, roadmapping was used mainly for strategic planning, either from a technological or amarket research perspective. Roadmaps emphasized either technological development or satisfaction of market demands but rarely both. Consequently, roadmaps either excessively stress the technology side, which might lead to technically sophisticated solutions that lack applicability, or overstress customer needs, neglecting business competence-building. Therefore, this paper develops a newintegrated roadmapping approach that combines these two perspectives: it focuses on strategic planning by firms and public authorities for the long run goals of social and economic development, bringing together the market “pull” and technology “push” approach. This dual technique provides the potential for alternative means of choosing the most effective resource allocation. Integrated roadmaps include the various development stages of prospective innovations, e.g. stages of the existing innovation value chain, including R&D, manufacturing,market entry, services, andmarket expansion as well as prospective stages, including new technologies, products and services. The value of integrated roadmapping lies in its responsiveness to the challenges in innovation planning schemes for firms and sectors; it takes into consideration both future market requirements and the future resource basis for satisfying market needs, an approach not currently offered by traditional techniques. The paper develops a roadmapping methodology that can be used for planning firms' and public authorities' long-term innovation strategies.
Time series of US patents per million inhabitants show cyclic structures which can be attributed to the different knowledge-generating paradigms that drive innovation systems. The changes in the slopes between the waves can be used to indicate efficiencies in the generation of knowledge. When knowledge-generating systems are associated with idem innovation systems, the efficiency of the latter can be modeled in terms of interactions among dimensions (for example, in terms of university–industry–government relations). The resulting model predicts an increase in efficiency with an increasing number of dimensions due to the effects of self-organization among them. The dynamics of the knowledge-generating cycles can be analyzed in terms of Fibonacci numbers; successive cycles are expected to exhibit shorter life cycles than previous ones. This perspective enables us to forecast the expected dates of future paradigm changes.
In parallel with the increasing complexity and uncertainty of social, technological, economic, environmental, political and value systems (STEEPV), there is a need for a systemic approach in Foresight. Recognizing this need, the paper begins with the introduction of the Systemic Foresight Methodology (SFM) is introduced briefly as a conceptual framework to understand and appreciate the complexity of systems and interdependencies and interrelationships between their elements. Conducting Foresight systemically involves a set of ‘systemic’ thought experiments, which is about how systems (e.g. human and social systems, industrial/sectoral systems, and innovation systems) are understood, modelled and intervened for a successful change programme. A methodological approach is proposed with the use of network analysis to show an application of systemic thinking in Foresight through the visualisation of interrelationships and interdependencies between trends, issues and actors, and their interpretation to explain the evolution of systems. Network analysis is a powerful approach as it is able to analyse both the whole system of relations and parts of the system at the same time and hence it reveals the otherwise hidden structural properties of the systems. Our earlier work has attempted to incorporate network analysis in Foresight, which helped to reveal structural linkages of trends and identify emerging important trends in the future. Following from this work, in this paper we combine systemic Foresight, network analysis and scenario methods to propose an ‘Evolutionary Scenario Approach,’ which explains the ways in which the future may unfold based on the mapping of the gradual change and the dynamics of aspects or variables that characterise a series of circumstances in a period of time. Thus, not only are evolutionary scenarios capable of giving a snapshot of a particular future, but also explaining the emerging transformation pathways of events and situations from the present into the future as systemic narratives.
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.
There is a common agreement that innovation is driven by the people that form the heart of any company's innovation activity. Still, people perform innovation in a special institutional environment characterized by rules and regulations that might support or impede innovation. The open innovation paradigm expects companies to engage in external relationships for innovation; however companies often neglect the actual internal openness of employees, which is an absolute must before partnering with external partners. The article finds that company innovation culture comes in five main forms: closed innovation (driven by internal capabilities); doing, using, interacting (ad hoc processes, no link to knowledge providers); outsourcing innovation capabilities; extramural innovation, no matching internal culture/procedures and proactive innovation (match of internal and external openness). The empirical analysis shows that the closed innovation behavior is by far the most widespread among Russian companies whereas proactive innovation behavior remains an exception in the overall sample.
Drawing on the contemporary turn to discursive practices we examine how the organizing practices of industry, university and government facilitate (or impede) developing countries transition to a hybrid triple helix model of innovation. Placing emphasis on the everyday situated practices of institutional agents, their interactions, and collaborative relationships, we identified three domains of practices (advanced research capabilities and external partnerships, the quantification of scientific knowledge and outputs, and collective entrepreneurship) that constitutively facilitate (or impede) partnership and in turn the successful transition to a hybrid triple helix model. Our study also highlights the contextual influence of differential schemata of interpretations on how to organize innovation by the three institutional actors in developing countries.
The Great Divergence and, to a lesser extent, the Great Convergence phenomena have attracted considerable scholarly attention. However, the existing attempts at explaining these phenomena and their background share two significant drawbacks: first, no model (to the best of our knowledge) has managed to account for both the Great Divergence and the Great Convergence so as to explain the timing of the trend change (around 1970s). Second, most existing models concentrate heavily on the economic forces, frequently neglecting the demographic factor. We offer an approach to overcome these drawbacks, revealing a close coupling between phases of global demographic transition and phases of the Great Divergence and Great Convergence. As we account for the crucial role of the demographic component in these processes, we show that the timing of the trend change was not coincidental. Our findings suggest that the dynamics of global population growth and the Great Divergence and Great Convergence therefore may be considered so closely coupled as to be two sides of the same coin. On the other hand, they also suggest that the Great Divergence and Great Convergence should be treated as a single process, as two phases of the global modernization. © 2015 Elsevier Inc.