The paper aims to analyse the evolution of forward-looking activities in Russia vis-à-vis science, technology and innovation policy challenges and its development over the last century, with a particular focus on the period of transition to a market economy.With the development of more complex and elaborate policy instruments, demand for a better grounded long-termvision of social and economic trends has been growing both among policy makers and the S&T community. The study illustrates the emergence of technology foresight in Russia and its evolution along relevant stages of economic development, from an information source for S&T and innovation policy towards a fully-fledged anticipatory policy instrument.
Technology Foresight (TF) became an increasingly popular approach for science, technology and innovation (STI) policymakers from the mid-1990s on. Achieving prominence in Japan and Western Europe, it attracted the attention of researchers and policy analysts in many parts of the world in subsequent decades. TF is often seen as a set of tools for informing decisions about STI priorities within established innovation systems. These priorities have necessarily changed as scientific knowledge, technological opportunities, and social demands have evolved. But so too have the ways in which innovation processes operate, and understandings of the roles that STI policies can play. Accordingly TF has also been applied to inform efforts to restructure innovation systems - and, indeed, it was often seen as also providing tools to assist in such efforts. The need for such restructuring has been particularly acute in countries undergoing massive transitions. These include transitions from centrally planned to market economies, from non-industrial to newly industrialized countries, and from being imitation-oriented to becoming innovation pioneers. Correspondingly, considerable effort has been put into TF in many such countries. But much of this TF effort has been largely invisible, or at best poorly documented. TF may itself require redesign, taking different forms in various contexts, and as experience with the tools has accumulated. This might involve different patterns of emphasis of, and ways of articulating: the methods that are employed; the stakeholders engaged; the linkages with STI policymaking; and so on. Informed by the contents of this Special Issue, this essay considers the issues arising from this diffusion and evolution of practice, outlining the main capabilities required to mount successful TF exercises in different contexts.
In the last decade, the Internet of Things (IoT) has affected the approach of organizations to innovation and how they create and capture value in everyday business activities. This is compounded in the so-called Smart Cities, where the objective of the IoT is to exploit information and communication technologies (ICTs) to support added-value services for citizens, giving companies more opportunities to innovate through the use of the latest technologies. In this context, multinational enterprises (MNEs) are building alliances, starting several projects with public and private city stakeholders aimed at exploring new technologies for cities but also at exploiting new IoT-based devices and services in order to profit from them. This implies that companies need to manage and integrate different types of knowledge to efficiently and effectively support the simultaneous pressure of exploration and exploitation, at a project portfolio level. Using structural equations modeling with data collected from 43 IoT smart city project alliances in Italy, this paper tests and finds evidence that MNEs need to develop knowledge management (KM) capabilities combined with ICT capabilities if they want to obtain greater ambidexterity performance at the project portfolio level. More specifically, we highlight that KM capabilities enhance alliance ambidexterity indirectly through firms' ICT capabilities, suggesting that MNE managers should design KM tools and develop new ICT skills. Implications for academics, managers and future lines of research are proposed.
Despite rigorous empirical research exploring the changes in innovation dynamics triggered by Social Media Networks (SMNs), the benefits coming from the use of these digital platforms for knowledge search in innovative activities for small to medium enterprises (SMEs) are still unexplored. Customers become the new trailblazers. Thus, by adopting a customer led innovation perspective, this paper seeks to measure the effect on return on investment (ROI) of the use of SMNs as external drivers for supporting internal innovation search processes. On the basis of the extant literature on information system and social network analysis, the research describes and evaluates the multidimensional activities interwoven into the open innovation process, driven by integrating the five constructs of structural dimension, relational behaviour, cognitive dimension, knowledge transfer, and legitimization into our hypothesised conceptual model.Empirical research was conducted via the Classification Regression Tree (CART) on a sample of 2548 SMEs belonging to the fashion industry and based in Italy and in the United Kingdom. This study is of importance to academics and practitioners due to the increasing significance taken on by the adoption of social media networks in the fashion industry to improve innovation search. Recommendations are made to fashion managers and social media experts to support the planning and development of new products and services. New contributions are offered to the innovation and knowledge management literature. In addition, theoretical implications and avenues for future research are also considered.
In recent decades, the attention of researchers and policymakers has turned to state-owned enterprises (SOEs), in particular the role they play in science, technology and innovation and the methods they use to implement innovation strategies. In this paper, we look at Russian state-owned companies and their development plans, as well as the management tools they employ to forecast and prioritize technologies. Although most Russian SOEs rarely implement corporate foresight and technology roadmapping, certain successful cases are presented and discussed in the paper. Based on these case studies, we suggest a common structure of a technology roadmap that is suitable for SOEs.
This paper argues that innovation behavior roots in specific socio-psychological set-ups that crystallize in daily practices and routines. The latter are easy to observe and have great potential for the identification of user-innovation behavior.We study the practices and routines of Russian user-innovators aroundmedia consumption, internet and technology-usage, consumer preferences and civic engagement in comparison with a sample of mere users. The derived model correctly classified 73% of the original grouped cases of user-innovators. We conclude that a set of practices relative to the certain economic, social and cultural background explains user-innovation engagement and how support could be provided. Although some of our findings are probably specific to Russia, the results are encouraging for further research into the importance of practices and routines in identifying userinnovators in various environments.
Many foresight exercises have been undertaken with the aim of improving the performance of innovation ecosystems. These ecosystems extend across different layers including the organisational, sectoral, regional, national and international dimensions. The interconnectedness of these layers has not have received much attention in foresight literature and practise. However, both the development and diffusion of innovations are subject to framework conditions not only within, but also across, multiple layers of innovation ecosystems.
The design and management of foresight exercises are thus liable to addressing and serving these different layers — especially when the goal is to improve the performance and impact of such “interconnected and interdependent systems”. This paper develops further the concept of ‘multi-layered foresight’ by addressing multiple layers of innovation ecosystems in foresight design and management. We explore the implications of applying this type of foresight on improving systemic understanding, enhancing stakeholder networking and developing innovation capacities across the layers of ecosystems. The theoretical underpinnings are tested through a case study of the ‘Personal Health Systems (PHS) Foresight’ project. This project explored international future developments in the health sector, which is characterised by multiple disciplines, communities of practise, technologies, and geographical contexts. In the case of PHS the emerging innovation ecosystems are often conditioned by fragmented development communities, major barriers to market development, and duplication of efforts. The project combined analytical, social networking, online envisioning and scenario building methods to address complexity and create impact in multiple layers. Possible futures for personal health systems were explored through intense dialogues with stakeholders and a desirable future state was sketched through the success scenario methodology. The implications and strategic issues for different groups of stakeholders were outlined, enabling these stakeholders to articulate their efforts as part of a broader agenda at the multiple layers of innovation ecosystems.