Comparing data sources for identifying technology trends
This paper considers the strategies for working with different data sources for identifying technology trends. For this purpose, a comparative analysis of technology monitoring results using various data collections (scientific publications, patents, media, foresight projects, conferences, international projects, dissertations and presentations) is conducted. Guidance on how to use them to ensure the greatest output is presented. Green energy is taken as an example for comparative analysis and provides improvements in reducing inputs (time) and increasing output (coverage). The factors that affect data processing results are considered and discussed to more efficiently use quantitative and qualitative procedures for identifying, correcting and updating technology trends. The results of the study can be interesting for government bodies financing foresight studies and setting priorities in science and technology, for companies scanning disruptive innovations in the markets to support their corporate strategies and academic community developing the methodology for technology trends monitoring.
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.
Foresight studies provide essential information used by the government, industry and academia for technology planning and knowledge expansion. They are complicated, resource-intensive, and quite expensive. The approach, methods, and techniques must be carefully identified and selected. Despite the global importance of foresight activities, there are no frameworks to help one develop and plan a proper foresight study. This paper begins to close this gap by analyzing and comparing different schools of thought and updating the literature with the most current tools and methods. Data mining techniques are used to identify articles through an extensive literature review. Social Network Analysis (SNA) techniques are used to identify and analyze leading journals, articles, and researchers. A framework is developed here to provide a guide to help in the selection of methods and tools for different approaches.
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.