The present study is devoted to the development of science and technology forecasting methodology, with a particular focus on foresight instruments. Advancement of foresight studies allows forming well-grounded advice and policy recommendations for decision-makers in science, technology and innovation. The study was focused on six key research areas outlined below:
1. Methodological recommendations for evaluation of corporate foresight
Goal of research: to develop methodological recommendations for an evaluation of foresight-projects on a corporate level.
Methodology: theoretical analysis, desk research, comparative analysis.
Empirical base of research: scientific publications and analytical reports on corporate foresight and foresight evaluation.
Results of research: Methodological recommendations for evaluation of corporate foresight were developed. They are based on integration of results of existing approaches in this field and also take into account accumulated theoretical and practical experience of national foresight evaluation. Key evaluation blocks with set of criteria for each of them were also identified: goals, project team, methodology, design, resources, participants, risks, realization, results, distribution of results, effects, influence and barriers.
Level of implementation, recommendations on implementation or outcomes of the implementation of the results: the developed recommendations could be used in companies during development and realization of foresight-projects and foresight specialists for further development the theory in this field and using it on practice for conducting projects on a corporate level.
2. Development of methodological approaches to the integration of corporate foresight and lean production.
Goal of research: development of methodological approaches to the integration of corporate foresight and lean production to meet the objectives of strategic planning and forecasting.
Methodology: system analysis, analysis of literary sources, methods of foresight and lean production.
Empirical base of research: more than 50 academic papers written by the authors from more than 10 countries.
Results of research: based on the analysis of the global best practices of lean management and the investigation of integration opportunities of lean management and Foresight techniques, the recommendations on the use of lean management to meet the challenges of strategic planning and forecasting were developed.
Level of implementation, recommendations on implementation or outcomes of the implementation of the results: the proposed integrated methodology that combines advantages of lean management and Foresight can be used in strategic planning system in any company.
3. Development of methods and approaches to integrating national energy security factors in science and technology foresights for the energy industry.
Goal of research: to study the methods and approaches for integration of various energy security aspects in the science and technology foresight studies and forecast documents in the energy industry.
Methodology: content analysis of publications, analysis of statistical indicators in the database of the International Energy Agency, case studies (foresight studies).
Empirical base of research: over 20 English language publications, database of the International Energy Agency.
Results of research: The research allowed identifying the necessary methods for integrating national energy security issues in the science and technology foresights in the energy industry and the sequence of their application. National energy security-related provisions were identified in the national science and technology foresights and systematized.
Level of implementation, recommendations on implementation or outcomes of the implementation of the results: The research outcomes may be used in planning foresight studies and in development of strategic planning documents at the sectoral and national levels.
4. Development of methodology and instruments to support identification, processing and systematization of high tech markets forecasts with high impact on science and technology policy.
Goal of research: The purpose of the study is the development of methodological approaches and instruments for processing, aggregation and systematization of forecast market estimates based on texts and metadata of market reports and forecasts.
Methodology: system analysis, natural language processing, text mining, semantic analysis, knowledge extraction, named entity recognition, entity linking, mapping.
Empirical base of research: more than 20 thousand analytical reports of international organizations covering various industry topics, websites of the major consulting and marketing companies, as well as several hundreds of thousands of news describing market indicators.
Results of research: Identification of five main types of sources of information that describe the market forecasts. Instruments for uploading and processing of documents for extraction of market forecasts based on text mining. Criteria to identify markets related to high-tech goods and services based on calculations of term relevance, entity linking of terms to priority science and technology areas and identification of semantic pattern of forecast estimates. Methodology for mapping the forecasts of high tech markets. Processing and systematization of high tech markets forecasts with high impact on the agenda of the science and technology policy with examples based on two case studies.
Level of implementation, recommendations on implementation or outcomes of the implementation of the results: The results of this study can be practically used as tools for collection, processing, systematization and mapping of markets of high-tech goods and services for the purposes of setting the agenda of science and technology policy, as well as for the development of corporate strategies. In addition, long-term implications can be made for China and Brazil based on the results of two case studies.
5. Improvement of existing methods of urban planning based on Foresight with the participation of various stakeholders.
Goal of research: to improve existing methods of urban planning based on Foresight with the participation of various stakeholders.
Methodology: case study, scenario planning, roadmapping.
Empirical base of research: Russian State Statistics Office; Department of Information Technologies of Moscow, Information Technologies and Communications Department of Kazan, Regional Innovation Development Rating, Higher School of Economics.
Results of research: the proposed approach combining the advantages of existing methods of urban planning and Foresight with the participation of various stakeholders. This approach includes the formation of principles for the integrated planning of the development of smart cities (for example, in Moscow and Kazan), including the identification of drivers and barriers to the implementation of these processes, as well as the identification and involvement of participants in urban planning and development priorities. The formation of perspective approaches to the implementation of the concept of "smart city" within the existing systems of urban planning and management is based on the construction of scenarios for the development of three cities: Winterthur, Moscow and Kazan, which differ in the areas of implementation of individual priorities. The priorities in each scenario were used to create strategy and roadmap for the next phases of the project. The roadmap is a "guide" for decision-makers on activities whose implementation will contribute to the onset of a scenario for the development of a smart city .
Level of implementation, recommendations on implementation or outcomes of the implementation of the results: the proposed approach combining the advantages of existing methods of urban planning and Foresight can be used in the urban planning system in various regions of the Russian Federation.
6. Development of a methodological basis for long-term forecasting of R&D indicators.
Goal of research: development of the industry specific methodology for long-term forecasting of R&D indicators.
Methodology: long-term forecasting methods, simulation models, regression analysis, scenario analysis methods, cluster analysis methods.
Empirical base of research: OECD Science and technology Indicators; OECD Structural Analysis Database (OECD STAN); UNESCO Institute for Statistics (UIS) Science, Technology and Innovation (full dataset); World input output database (WIOD); World KLEMS.
Results of research: The most relevant methods for developing sectoral forecasts of the R&D indicators in Russia for the long term have been identified; levels of complexity of economic sectors for Russia and some of the most developed countries have been estimated; a system of forecasting models is formed; estimates of long-term predictive dynamics of key indicators of scientific and technological development of Russia have been obtained; relationships between these indicators and technological changes in the structure of the Russian economy have been estimated; long-term estimates of the dynamics of the sectors of the Russian economy have been provided.
Level of implementation, recommendations on implementation or outcomes of the implementation of the results: The results of this study can be used by the relevant ministries and government departments when developing programs for the long-term scientific and technological development of the Russian Federation, as well as for development programs of specific sectors of the Russian economy.