• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
Of all publications in the section: 46
Sort:
by name
by year
Article
Dranev Yu., Chulok A. Technological Forecasting and Social Change. 2015. Vol. 101. P. 320-327.

We present a new approach to technology road mapping (TR) which allows one to assess interactions of technologies and markets. Unlike the traditional methodology of TR that mostly relies on qualitative techniques, the proposed approach combines qualitative and quantitative methods. This bottom-up economic model allows the aggregation of estimates on different levels from the product group to industry used to quantify the market development. The KLEMS (capital, labor, energy, materials and services) production factors and multifactor productivity embedded in the model play the role of parameters measuring interactions between market outputs and technology innovation according to market-pull and technology-push effects. The qualitative methods include: STEEPV trend identification, 2 × 2 scenario analysis, and expert procedures. This allows for decreasing the number of parameters, inputs and calculations in the economic model. At the same time, balance between qualitative and quantitative techniques provide more realistic estimates for technological and market parameters. The assessment of interactions between technologies and markets is illustrated using the case of civil aircraft manufacturing in Russia. Technology impact is measured in terms of output growth of the industry.

Added: Oct 12, 2015
Article
Gershman M., Gokhberg L., Kuznetsova T. et al. Technological Forecasting and Social Change. 2018. No. 133. P. 132-140.

This paper analyzes the numerous governments' attempts to build a bridge between science and innovation, starting from the times of the Russian Empire up to the present day. We argue that throughout the whole history of Russian science, the government, being the main driver of scientific development, has largely failed to organize knowledge transfers and incentivize companies to innovate. The empirical evidence shows that nowadays only a very small share of Russian manufacturing enterprises considers R&D cooperation with knowledge producers important and only this small minority benefits from the government's science, technology and innovation (STI) policies. The reasons behind this remain an underdeveloped institutional setting and a lack of market competition.

Added: Apr 13, 2018
Article
Burmaoglu S., Saritas O. Technological Forecasting and Social Change. 2017. Vol. 116. No. March . P. 151-161.

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.

Added: Apr 7, 2017
Article
Carayannis E., Goletsis Y., Grigoroudis E. Technological Forecasting and Social Change. 2018. Vol. 131. P. 4-17.

Innovation is a complex, dynamic, socio-technical, socio-economic and socio-political phenomenon which needs to be approached in a holistic manner to be properly measured and assessed. In this paper, we revisit the national and regional Innovation Scoreboards using a multiple criteria decision analysis (MCDA) approach in the context of the Quadruple Innovation Helix (QIH) framework. We deploy an MCDA approach combining AHP and TOPSIS methods which merges data from Government, University, Industry, and Civil Society sectors (the four QIH actors or helices) and overcomes limitations of the existing Innovation Scoreboard approach by incorporating the different preference systems of the QIH Helix actors. The findings illustrate the power and promise of our approach as an alternative composite innovation metric. Estimating the different preferences of innovation stakeholders gives the ability to develop policies and practices oriented towards specific QIH actors. Estimating the importance that each QIH actor assigns to different innovation aspects is critical policy-wise and practice-wise as it provides a perspective on relative efficacies and potential ways and means to calculate differential efficacies for alternative configurations of resource allocations. These results underlie specific policies, practices, and priorities therein based on the relative re-distribution of weights.

Added: Feb 6, 2019
Article
Feige D., Vonortas N. Technological Forecasting and Social Change. 2017. Vol. 119. P. 219-226.

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.

Added: Sep 25, 2016
Article
Ivanova I., Strand Ø., Kushnir D. et al. Technological Forecasting and Social Change. 2017. Vol. 120. P. 77-89.

The Economic Complexity Index (ECI; Hidalgo & Hausmann, 2009) measures the complexity of national economies in terms of product groups. Analogously to ECI, a Patent Complexity Index (PatCI) can be developed on the basis of a matrix of nations versus patent classes. Using linear algebra, the three dimensions—countries, product groups, and patent classes—can be combined into a measure of “Triple Helix” complexity (THCI) including the trilateral interaction terms between knowledge production, wealth generation, and (national) control. THCI can be expected to capture the extent of systems integration between the global dynamics of markets (ECI) and technologies (PatCI) in each national system of innovation. We measure ECI, PatCI, and THCI during the period 2000-2014 for the 34 OECD member states, the BRICS countries, and a group of emerging and affiliated economies (Argentina, Hong Kong, Indonesia, Malaysia, Romania, and Singapore). The three complexity indicators are correlated between themselves; but the correlations with GDP per capita are virtually absent. Of the world’s major economies, Japan scores highest on all three indicators, while China has been increasingly successful in combining economic and technological complexity. We could not reproduce the correlation between ECI and average income that has been central to the argument about the fruitfulness of the economic complexity approach.

Added: Feb 28, 2017
Article
Proskuryakova L. N. Technological Forecasting and Social Change. 2017. Vol. 119. P. 205-210.
Added: Jun 20, 2016
Article
Fischer B. B., Rücker Schaeffer P., Vonortas N. Technological Forecasting and Social Change. 2018.

Due to its ability to create and disseminate knowledge, the modern university is understood as a central agent in innovation systems and technology upgrading dynamics. The main objective of this article is to assess the evolution of universities' embeddedness within the innovation system of an emerging economy in terms of patenting activity and linkages to industry. The study is based on information relating to the twelve most eminent universities in Brazil for the years 1994, 2004 and 2014. These institutions are found responsible for a substantial share of Brazilian patents – with an upward trend over the years - and these institutions have demonstrated a progressive embeddedness to the national innovation system. Such behavior seems to have co-evolved along with improvements in the national institutional environment, leading to expectations that academia can become strategic in shaping the catching-up conditions in Brazil for the coming years. However, deeper connections with both domestic and foreign agents and multinational corporations are needed in order to accelerate the pace of university contribution to value chains and technology upgrading.

Added: Sep 27, 2018
Article
Grinin L. E., Korotayev A., Grinin A. L. Technological Forecasting and Social Change. 2017. Vol. 115. P. 52-68.

In the present article we analyze the relationships between K-waves and major technological breakthroughs in history and offer forecasts about features of the sixth Kondratieff wave. We use for our analysis the basic ideas of long cycles' theory and related theories (theories of the leading sector, technological styles etc.) as well as the ideas of our own theory of production principles and production revolutions. The latest of production revolution is the Cybernetic Revolution that, from our point of view, started in the 1950s. We assume that in the 2030s and 2040s the sixth K-wave will merge with the final phase of the Cybernetic Revolution (which we call a phase of self-regulating systems). This period will be characterized by the breakthrough inmedical technologies which will be capable to combine many other technologies into a single system of MANBRIC-technologies (medico-additive-nano-bio-roboto-info-cognitive technologies). The article also presents a forecast of the process of global ageing and argueswhy the technological breakthrough will occur in health care sector and connected spheres.

Added: Nov 30, 2016
Article
Abankina I., Aleskerov F. T., Belousova V. et al. Technological Forecasting and Social Change. 2016. No. 103. P. 228-239.

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

Added: Oct 14, 2015
Article
Haegeman K., Spiesberger M., Veselitskaya N. et al. Technological Forecasting and Social Change. 2015. Vol. 101. P. 200-215.

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.

Added: Oct 24, 2013
Article
Saritas O., Burmaoglu S. Technological Forecasting and Social Change. 2016. Vol. 102. P. 331-343.

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.

Added: Sep 23, 2016
Article
Cagnin C., Havas A., Saritas O. Technological Forecasting and Social Change. 2013. Vol. 80. No. 3. P. 379-385.

This paper reflects on the potential of future-oriented analysis (FTA) to address major change and to support decision-makers and other stakeholders in anticipating and dealing with transformations. It does so by critically reflecting on the selected papers for this special issue as well as on the discussions that took place at the fourth Seville International Conference on Future-oriented Technology Analysis. Considering the potential roles of FTA in enabling a better understanding of complex situations and in defining effective policy responses leads to the understanding that appropriate FTA practices are needed to enable FTA to fulfil such roles. Dealing with disruptive changes - and grand challenges in particular -, therefore, raises several conceptual, methodological and operational issues. Two of them are general, while further two are specific to the so-called grand challenges: i) distinguish known unknowns, unknown knows and unknown unknowns, ii) combine quantitative and qualitative approaches in a relevant and feasible way, iii) understand the complex and systemic nature of grand challenges, and iv) orchestrate joint responses to grand challenges. After a brief explanation of these issues, the paper outlines the main ideas of the papers published in this special issue. These present various methodological aspects of FTA approaches as well as some advances needed in practice to assist FTA practitioners and stakeholders in comprehending transformations and in tackling the so-called grand challenges.

Added: Feb 7, 2013
Article
Vishnevskiy K., Karasev O., Meissner D. Technological Forecasting and Social Change. 2015. Vol. 90. P. 433-443.

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.

Added: Jun 1, 2014
Article
Vishnevskiy K., Karasev O., Meissner D. Technological Forecasting and Social Change. 2016. Vol. 110. P. 153-166.

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.

Added: Feb 28, 2016
Article
Meissner D., Shmatko N. A. Technological Forecasting and Social Change. 2017. No. 123. P. 191-198.

Universities are increasingly seen as institutions which anticipate and address the challenges induced by interactions within the Knowledge Triangle (KT). The interactions between actors in the KT force individual agents to adjust and refine their models of operation and provide targeted output which supports the activities of other agents. Among companies, we saw the emergence of the open innovation concept which stresses the will of companies to cooperate in innovation. At the same time, the scientific community is increasingly challenged by open access to research findings and by online learning courses. These two recent developments are among the most important that were significantly initiated by gatekeepers, themselves especially important actors within the KT because they possess the power to orchestrate and direct the linkages between KT actors.

Until recently, the role of gatekeepers within the KT has been little analysed. The paper suggests that understanding the role and characteristics of gatekeepers is essential for substantial and sustainable interactions between KT agents and the fulfilment of the Third Mission of universities. Therefore, the linkages go beyond purely knowledge and technology transfer linkages but rather show how gatekeepers influence competency-building for delivering information and technologies to other organizations and enhancing institutions' absorptive capacity which is argued to be crucial for implementing effective, targeted, and productive interactions of universities. It is argued that universities need to be aware of gatekeepers' competences and powers well in advance to make use of knowledge exchange with other parties to shape society. In addition, it is argued that universities' skill base – as shown in researchers' competences – is a vital element of universities' intellectual capital which should be included in universities' performance evaluation frameworks. Finally, the paper argues that it is important for policy making in science, technology and innovation to possess knowledge of gatekeepers' position in the KT to enhance collaboration between KT agents and provide research institutions, namely universities, with the competences needed to vitalize the universities' ‘Third Mission’.

Added: Aug 17, 2016
Article
Meissner D., Carayannis E., Sokolov A. Technological Forecasting and Social Change. 2016. Vol. 110. P. 106-108.
Added: Sep 22, 2016
Article
Ivanova I., Leydesdorff L. Technological Forecasting and Social Change. 2015. No. 96 (2015) . P. 254-265.

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.

Added: Jan 25, 2016
Article
Korotayev A., Zinkina J. V. Technological Forecasting and Social Change. 2011. Vol. 78. P. 1280-1284.
Added: Mar 7, 2013
Article
Saritas O., Nugroho Y. Technological Forecasting and Social Change. 2012. Vol. 79. No. 3. P. 509-529.

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.

Added: Dec 25, 2012
Article
Oleg V. Ena, Chulok A., Sergey A. Shashnov. Technological Forecasting and Social Change. 2017. Vol. 119. P. 268-279.

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.

Added: Jun 2, 2016