Library
|
Your profile |
Finance and Management
Reference:
Kulikova T.A., Petricheva A.S.
An overview of the theoretical aspects and practical experience of foresight in the international context
// Finance and Management.
2024. № 3.
P. 1-36.
DOI: 10.25136/2409-7802.2024.3.70794 EDN: LCFTRB URL: https://en.nbpublish.com/library_read_article.php?id=70794
An overview of the theoretical aspects and practical experience of foresight in the international context
DOI: 10.25136/2409-7802.2024.3.70794EDN: LCFTRBReceived: 18-05-2024Published: 13-06-2024Abstract: Having appeared relatively recently, foresight as a strategic planning tool has become widespread all over the world. However, experts often limit themselves to a narrow set of the most well-known, traditional tools and algorithms for individual countries. At the same time, modern realities require an active exchange of accumulated international experience in the field of strategic planning, the introduction of advanced foresight methods, as well as their further refinement in accordance with specific tasks and specialization of activities. The purpose of the study is to develop recommendations for adapting traditional foresight methods and algorithms to use in conditions of increasing complexity and uncertainty of business conditions, which will contribute to improving the accuracy of forecasts and making effective strategic decisions. The subject of the study is the theoretical aspects and practical experience of using foresight in the international context. The work is based on the method of scientific mapping, which allows analyzing and visualizing the results of research in the field of foresight. A bibliographic analysis of the publications presented in the Elsevier database over the past 23 years has allowed us to systematize knowledge and practical experience in the field of foresight in an international context. A total of 13241 scientific publications were reviewed. Modern approaches to understanding foresight, its role in forecasting in conditions of uncertainty, innovation, and value creation of organizations are considered, actual tasks for which it can be used are identified, and the specifics of organizing interaction between participants in foresight research are highlighted. Using the modeling method, the structure of the "foresight field" for the industry of the region is constructed. It is recommended to pay special attention to the stage of determining the cost items for conducting a foresight and evaluating their feasibility. The refined stage of the post-foresight includes an assessment of the results, the effectiveness of the implemented foresight, as well as planning further iteration of the foresight project. The results of the study contribute to the body of empirical work in the field of foresight and are intended for use by management practitioners and scientists interested in developing fresh ideas for new approaches in strategic management. Keywords: foresight, foresight methods, IT tools in forsyte, strategic planning, technological foresight, uncertainty, innovations, industry, region, foresight fieldThis article is automatically translated. You can find original text of the article here. Introduction The constant expansion of the spectrum, complexity, uncertainty, high dynamism of environmental factors, high variability of the future, intensification of technological development, digitalization, increased threats to economic security complicate the process of strategic planning, reduce the accuracy of forecasts. Business entities are faced with the task of finding a compromise between combating the identified negative factors and, at the same time, determining ways of sustainable development of business entities in accordance with modern challenges. These circumstances lead to a decrease in the effectiveness of traditional planning methods and tools. With the increasing complexity of the economic environment and the expansion of the range of tasks facing organizations, attention should be paid to foresight, which can receive a wider range of applications. At the same time, foresight research is characterized by complexity, requires significant expenditure of both material and time resources, and the involvement of a wide range of participants. Therefore, it is necessary to carefully check the need to use foresight, choose the most appropriate methods and tools for each of the tasks. For the present study, hypotheses are put forward about three main transformations in the foresight: H1. As the economic conditions become more complicated and unpredictability increases, the interest in foresight on the part of scientists and practitioners as an effective tool for strategic planning increases. H2. The high dynamism of environmental factors, globalization, accelerated pace of scientific and technological progress, widespread digitalization necessitate a revision of traditional approaches and methods of foresight, as well as their adaptation to new realities and challenges. H3. The use of foresight in strategic planning at the level of spheres, industries, enterprises requires taking into account the specifics of their specialization. Data and methods The information basis of the review was scientific publications indexed in Scopus, selected using search tools in the Elsevier database. The literature was scanned. According to the keyword "foresight", 32780 publications were found between 2000 and April 2024. These include 20,216 research articles and 1,805 review articles. The following subject areas were taken into account: economics, econometrics and finance (6,223 articles), business, management and accounting (5,178 articles), decision science (2,436 articles). The largest volume of publications fell on the magazines "Technological Forecasting and Social Change" and "Futures". The positive dynamics in the number of publications from 2000 to April 2024 illustrates the increased interest in foresight methodology in strategic planning (Figure 1).
Figure 1. Dynamics of the number of publications in the journals of the SCOPUS database from 2000 to 2023 (source: compiled by the author)
The results of the analysis of the content of the articles allowed us to identify the structure of the theoretical basis of this study. According to the subject of the study, it seemed possible to divide all publications into categories and consistently consider: modern approaches to understanding the essence and roles of foresight in solving various tasks, new methods of foresight, features of interaction between participants in foresight projects, international practice. We also attempted to identify new management tasks presented by various scientists, for which foresight can be applied. The content of this work includes information from 50 sources. The selection of scientific publications was carried out taking into account the following criteria: the object of research – enterprises of the real sector, the subject of research – tools and methods of foresight, technological forecasting. The above hypotheses are discussed and tested using scientific mapping methods to study the theoretical and practical evolution of the foresight field by reviewing publications in scientific journals, as well as modeling a refined foresight algorithm. The verification of the first hypothesis was carried out using bibliometric analysis. The degree of interest in the study of foresight, current trends are determined, and the views of various researchers are systematized. As part of the verification of the 2nd hypothesis, information on the essence and features of the application of modern foresight methods, including for solving new management tasks, is structured in the 2nd section. The increased intensity of use and the constant development of information and communication technologies in the foresight have been revealed. It is concluded that the new methods are more sensitive to weak signals and introduce non-linearity into the assessment of future options, which in turn makes it possible to increase the accuracy of forecasting. The 3rd section contains the results of studying the international experience of foresight, which other countries can introduce into the strategic planning process. The third hypothesis is tested on the basis of the knowledge gained in the previous sections to facilitate the further development of foresight and study the features of using foresight to solve strategic planning problems in industry. The use of the modeling method made it possible to structure and refine the foresight implementation algorithm to predict the future development of the industry at the regional level and identify the factors influencing this. In particular, the composition of the "foresight field" is described. In conclusion, the contribution and limitations of this study are described and areas for further research are proposed.
Theoretical aspects of foresight Modern approaches to understanding foresight Definitions of corporate foresight generally reflect two different approaches: the ability of an organization to anticipate future changes, and the actions that companies take to prepare for future changes. That is, some researchers point to a vision of a preferred future, while others point to a variety of alternative options. Kalle A.Piirainen and Rafael A. Gonzalez [1] identify foresight at three levels: knowledge creation activity, process, and social/organizational intervention. A systematic approach is gaining popularity, understanding foresight as a set of opportunities, relationships and knowledge about processes, strategic objects and intermediate events [2]. Foresight at the ecosystem level, rather than at a single firm, will avoid duplication of work, communication gaps and a fragmented knowledge base. The concept of business foresight is also considered to include a triad of assumptions: anticipation, innovation and communication of the future. A review of scientific publications has shown that at present, researchers mainly emphasize the role of foresight in forecasting under conditions of uncertainty, innovative, technological development, and value creation of an organization. Foresight experts argue that predicting the future at a certain point in time, which is the task of traditional forecasting methods, is impossible due to increasing uncertainty and the likelihood of failures in the medium and long term. Sukhacheva V.I. and Smotrova T.I. [3] note that foresight allows integrating the ways proposed by strategic management to combat uncertainty: increasing the accuracy of forecasts or flexibility, adaptability. Foresight includes aspects of networking and preparing solutions related to the future, improves the adaptability and sustainable development of the organization, allows you to increase its value, minimize damage or maximize benefits. Researchers agree on the existence of a close relationship between foresight and the innovative potential of companies. In maximizing the innovative potential of a company, corporate foresight plays the role of a strategist, initiator of new scientific research, opponent – in order to improve quality, challenges innovative projects, coordinator of scientific and technical policy and response to conditions of uncertainty and changes in the innovation environment. Foresight also acts as a joint creative broker of knowledge about the future for the innovative activities of local companies in forming a common understanding of the regional future for public policy development, as well as in collective vision and strategy building; Matthias Weber and Petra Schaper-Rinkel [4] conclude that foresight projects at the industry level are rarely carried out compared to foresights focused on technology or social issues, or retrospective studies of industry innovation systems. At the same time, Nadezhda Gaponenko [5] notes: industry technological foresight will make it possible to respond more quickly to the growing complexity, rapid changes and the changing role of various participants in evolution, stimulate dialogue between industry participants and interconnected industry innovation systems. As part of the development of foresight in innovation, models of cyclical innovation, organizational foresight based on structural capabilities are proposed [6], management of new technologies by moving to a “state of negotiation” in conditions of increasing diversity and the emergence of new risks [7]. The traditional foresight algorithm is shown in Figure 2.
Figure 2. The main stages of foresight (source: compiled by the author)
Anastasia Andreeva [8] draws attention to the fact that in the foresight, an important role is played by the assessment of events with a low probability, but a great potential impact on the future of the sphere under study, called "black swans". These include catastrophes and pandemics, but also random luck, the approach of which is not noticed, believing in the causal relationship of everything and everything. Mastering foresight will allow you to develop "antifragility", that is, the ability to benefit from collisions with chaos, harden in failures and become stronger from this. Many researchers point to problems in transforming the results of foresight, the gap between practice and theory, as well as barriers at the very beginning of foresight research in organizations engaged in research and technology development. Currently, foresight is in the process of catching up with innovation research, gradually including the consequences of a systematic understanding of innovation. Kononyuk A. [9] notes that currently not many enterprises, especially small and medium-sized businesses, have foresight maturity. The author draws this conclusion based on an assessment of 36 criteria and reveals that the degree of foresight maturity of organizations of this scale depends on their type and geographical level of activity. It is also noted that manufacturing companies are more actively engaged in calculating alternative prospects, as they work in an intensively changing technological environment. The players of the international market are in a similar position in relation to local companies. A review of the literature revealed a lack of research devoted to evaluating the results of technological foresight, mainly for reasons of a long period of time, numerous influencing factors and high uncertainty, the inability of experts to systematically reason in abstract terms throughout the foresight process. However, work in this direction is underway, so, developed: - methodology for mitigating biases and managing the occurrence of false positives and false negatives [10]; - a model that includes eight factors: the most important are the role of the "foresight leader" and a multi-channel communication strategy [11]. Research on improving the effectiveness of foresight at the pre-foresight stage is also limited. Thus, Piirainen [1] offers a system for the systematic evaluation of future research, and part of it is related to the preliminary assessment. The issues of preliminary assessment of activities at three levels are determined: usefulness and implementation, technical and ethical levels. Anna Sokolova [12] proposes a methodology that is carried out at the preliminary forecasting stage, focuses on identifying potential barriers and problems for the full integration of foresight results into STI policy and developing a plan to eliminate them at the beginning of the project. Regarding the criteria for evaluating the results of foresight, the opinions of researchers differ: - achievement of initial goals, the scale and nature of direct, expected impacts, as well as impacts related to how foresight measures are developed and implemented; - creation, dissemination and assimilation of knowledge; social capital and networking, public involvement in policy development, the evolution of strategies to cope with or avoid the negative consequences of a "risk society"; - increasing the value of the organization by acquiring the ability to perceive changes, interpret, promptly make informed and effective decisions at a critical moment, organizational learning; - creation of conditions for outstripping the actions of competitors, gaining leadership positions, formation and long-term preservation of competitive advantages. At the same time, only regular and active participation in the foresight will be effective, and not just consumption of the final results.
Interaction of foresight research participants Wright et al. [7] note the effectiveness of inter-organizational collaboration, especially with a heterogeneous partner structure, within the framework of foresight activities. At the same time, companies should be similar enough, as well as geographically close, to facilitate training and anticipate future developments. Specific framework conditions and the use of neutral intermediaries are useful for coordinating participants. Transparent consideration and discussion of reliability and quality issues, the introduction of innovative forms of expressing participants' preferences with different motives and interpretative frameworks increases the effectiveness of foresight projects. Despite all the advantages of inter-organizational interaction in the implementation of foresight research, there is a risk of excessive groupthink, threats to the independent position of participants, and conscious decision-making by high-ranking officials. In order to prevent the negative consequences of inter-organizational interaction, new approaches are constantly being developed. Maree Conway [13] proposes a new structure for conversations about the future to expand organizational discussions about the future and its application in the present. Liviu Andreescu et al. [14] identify three key features of foresight — distancing, integrity and intensity of participation and note that the construction of normative descriptions can be interpreted in terms of efforts to smooth out the tension inherent in the scenario. Cristiano Cagnin and Totti K?nn?l? [15] formulated the principles for the development and management of global international foresight events: understanding interconnected innovation systems, responsiveness to different languages and cultures, the ability to reconfigure international networks, focus on "local" impact. Kirk Weigand et al. [16] argue that joint bottom-up foresight and as a complement to top-down strategy development increases the sustainability of an organization by improving the formulation of ideas, identifying problems and reaching consensus in long-term strategies, as well as increasing the diversity of perspectives when creating scenarios.
Features of modern foresight methods The recent turn in policy in the field of research, technology and innovation towards problem-solving strategies, as well as the expansion and complication of management tasks for which foresight is used, necessitates the adaptation and development of its methods in accordance with modern realities. The foresight discipline applies more than 30 different methods to obtain reliable and in-depth conclusions about future events and scenarios. In scientific publications in the field of foresight methodology, identical methods are most often presented, which can be grouped as qualitative, quantitative and synthetic. As practice shows, the use of qualitative approaches to the development of foresight cannot provide the required accuracy. The reasons for this are: high cost and low speed of the research process; subjectivity and contradictory opinions of intellectuals and experts, as well as limited knowledge and information that they can refer to The desire to improve the accuracy of foresight stimulates the constant development and development of new methods. The author's position on each of the presented foresight methods is to identify their advantages and disadvantages (Table 1).
Table 1. Characteristics of modern foresight methods (source: compiled by the author)
Special attention should be paid to the IT tools in the forsite. There is a growing interest among researchers and practitioners in the design, accessibility, application and development of information and communication technology-based systems for foresight processes. Many prototypes and applications for ICT, complex software complexes that integrate and link several methods, are being developed around the world (Table 2).
Table 2. New ICTs in the foresight (source: compiled by the author)
ICT will help shift the focus in foresight exercises from scanning and extracting data to higher-quality stages (interpretation, decision-making and implementation), more efficient and accurate forecasting processes with improved information availability, easy-to-use collaboration tools, data and knowledge linkages, quantitative modeling tools and process optimization. Small and medium-sized enterprises are expected to benefit particularly from the use of ICT. Together, new approaches to the revision of basic foresight methods introduce non-linearity in the assessment of historical paths and the future, and make foresight methods sensitive to weak signals.
International practical experience of foresight The study showed that not only developed, but also developing countries, thanks to the application of foresight methodology, were able to ensure the development of industry. For example, in the United States, foresight is perceived as a management technology aimed at advancing the creation of mechanisms for institutionalizing innovation. In Japan, scientific and technological foresights are conducted by the government every 5 years, and according to the results of the organization, an R&D plan is drawn up. European countries use foresight to identify competitive advantages, critical technologies, and priorities in technological development. At the same time, expert assessment, Delphi, macro scenarios, expert panels, diagnostic studies, seminars are used. Great Britain turns to Fawcett to determine the guidelines of the scientific and technical policy of the state, strengthening the innovative potential of science. The main methods are the knowledge bank, scanning, expert panels, seminars, scenarios. Latin American and Caribbean countries use foresight at the regional level for research in the food industry, agro-industrial complex, information and communication technologies and climate change. Based on existing experience, it should be noted that in countries such as the United Kingdom, Germany, Hungary, France, Spain, foresight is promoted by the government, in Sweden, Italy and Portugal it was initiated by the business community [44]. Over the past 30 years, developed and developing countries have faced challenges in implementing major national foresight programs. These include: long planning times leading to lagging behind an ever-changing environment, huge investments in resources unsuitable for countries with limited resources, and bottlenecks such as the inefficiency of planning processes related to the promotion of subsequent projects. In developing countries, there is a particular lack of coherence between technological foresight and industrial policy.
Refinement of the foresight algorithm for industrial research at the regional level Based on the research results of Matthias Weber and Petra Schaper-Rinkel [4], which revealed the lack of foresight projects at the industry level, this article attempts to refine the foresight algorithm in industry at the regional level based on information obtained as a result of studying modern foresight methods and international practical experience in its application. Strategic planning is complicated by increasing dynamism, uncertainty, a variety of environmental factors, and the expansion of the range of management tasks facing individual organizations and entire industries. Therefore, modern realities require a revision of traditional algorithms for implementing foresight. The stage of determining the circle of experts and consumers of the results of foresight research can be simplified by visualizing their structure in the form of a "field of foresight" for the industry (Figure 3) Small Oval - subjects interested in foresight and financing it. The middle oval is those who feel the impact of the expected changes, but are not actively involved in their implementation. Let's agree with Penkova I. V. [45] on the importance of the role of analysts, which consists in analyzing the relevance of a particular project or identifying what needs to be done to make this project in demand, and include them in this oval. The big oval is to a small extent interested, understanding and feeling the impact of the coming changes.
Figure 3. Foresight field (source: compiled by the author)
Determining the composition of the participants in each circle is particularly difficult when constructing the foresight field. Therefore, the foresight field is complemented by factors that influence its composition and the number of stakeholders in each oval. The goals and directions of the foresight are a key factor and will determine all the features of its implementation, the specialization of experts, the level of government agencies involved, educational institutions, the public and other stakeholders. Initially, it is necessary to outline the range of interests of the participants, their level of interest and possible influence on the process (for example, the availability of necessary knowledge, expert opinion, financing) and the result of foresight research (implementation of planned activities). Influence implies the expected contribution of the stakeholder to achieving the set goal (dissemination of information about the project, lobbying at the legislative level, financing, etc.), and the ability to influence other participants, especially decision makers. The interest represents the value of the foresight results for the stakeholder personally. The foresight horizon indicates the time frame for attracting stakeholders. Since it is recommended to keep the composition of foresight participants unchanged throughout its entire period, it is necessary to find out in advance whether they have the opportunity to participate on such a condition. The presence of experts in the field under study, their level of competence and teamwork skills will mainly affect the composition, capabilities and expected result of the work of participants in a small circle of foresight. The level of innovativeness of the set goals will indicate the need to attract specialists in innovation, representatives of research organizations, innovative entrepreneurs, etc. The range of potential sponsors of the foresight will allow you to understand who is ready to finance the research and to what extent. This will be a decisive factor in determining the duration of the foresight, the scope of the tasks to be solved, as well as the number, level of competence and rank of stakeholders, since they can often expect a certain reward for participating in the study. The experience of various countries shows that the willingness to implement foresight may be higher if it is initiated by the private sector; at the same time, the sustainability of the approach will be achieved if the foresight is in demand in the country/region, and not imposed from the outside by a third-party institution. [46] Therefore, special care should be taken to consider the composition of representatives of business structures, and focus on those of them who are most interested in obtaining results, can have an impact, information, financial and other support. Upon completion of the foresight field, specific forms of stakeholder participation should be determined depending on the type of tasks to be solved and the expected results. In order to increase the effectiveness of foresight, the difference between the achieved result and the costs incurred to ensure it should be increased. Therefore, it is recommended to carefully determine the cost items and amounts for conducting a foresight, depending on the tasks, location, scale of the study and other factors. This may be the cost of: - payment of taxes; - advertising and informational materials; - expert and consultant services; - carrying out necessary activities, business trips; - the work of the project team; - conducting surveys, etc. When implementing foresight, it is advisable to separately assess the factors that may slow down or stimulate the implementation of a particular scenario. In order not to overload the foresight study, to optimize the cost of resources for its implementation from the entire variety of indicators of the development of industrial enterprises, it is recommended to choose no more than 4 key indicators. The stages of implementation of the foresight project, indicated in the work of Fesyun A.V. [47]: pre-foresight, selection of participants, generation, action, updating, it is advisable to supplement the post-foresight stage. It includes an assessment of the results, the effectiveness of the implemented foresight, as well as planning for further iteration of the foresight project. Hindsight is recommended as a tool to identify the causes of inefficiency of previous similar projects in order to prevent them in future foresight studies.
Results In accordance with hypothesis 1, it is assumed that as the economic conditions become more complicated and unpredictability increases, interest in foresight from scientists and practitioners as an effective tool for strategic planning increases. The confirmation of this hypothesis is indicated by a significant steady increase in the number of publications on the topic of foresight since the early 2000s. At the same time, there is an expansion of the scale and range of tasks for which foresight is used, as well as the development of approaches, methods and tools of foresight. Scientific mapping has shown that foresight is a dynamic activity, the driver of which is the changes taking place in the economy, society, politics, science, technology, management and its evolution will continue in the coming years. The second hypothesis states that the high dynamism of environmental factors, globalization, accelerated pace of scientific and technological progress, widespread digitalization necessitate a revision of traditional approaches and methods of foresight, as well as their adaptation to new realities and challenges. This hypothesis has been confirmed by the development and application of refined foresight methods at the international level, including the active use of information and communication technologies. New methods are characterized by the ability to quickly capture weak signals from the external environment, interpret them more thoroughly and react quickly, increase forecast accuracy, and bring flexibility to strategic planning. In addition, it was revealed that modern foresight methods are adapted to solve urgent problems: innovative and technological development, reducing uncertainty, forecasting at the ecosystem level, improving the consistency of participants. According to the third hypothesis, the use of foresight in strategic planning at the level of spheres, industries, and enterprises requires taking into account the specifics of their specialization. The hypothesis was tested using the example of an industry at the regional level. To do this, the composition of the subjects of the "foresight field" was specified, the cost items caused by the foresight research were noted, and the post-foresight stage was clarified. In general, our research presents generalized results of existing knowledge in the field of foresight, makes a contribution to the existing literature and practice of foresight. On the basis of studying and combining empirical studies, the information obtained concerning concepts, approaches to understanding, algorithms, methods, features of interaction between foresight participants, approaches to evaluating its effectiveness were structured. It can act as an integrative and unifying platform for the implementation and expansion of corporate foresight research. It is established that the use of foresight methodology in strategic planning will allow organizations to ensure innovative development and adapt to new economic conditions, both in developed and developing countries. The practical significance of this article is to present a refined foresight algorithm that will improve the accuracy of forecasting. An in-depth analysis of the foresight literature also revealed key gaps in this area and identified several areas for future research. The grouping of identified problems in the field of strategic planning and recommendations developed to solve them based on the use of foresight is reflected in Table 3.
Table 3. Recommendations for solving strategic planning problems (source: compiled by the author)
Studying the experience of using foresight made it possible to identify the problems of its organization and develop recommendations for their solution (Table 4).
Table 4. Problems of foresight organization and developed recommendations for their solution (source: compiled by the author)
Discussion and conclusions The recommendations developed in this study can be applied to ensure the achievement of the national development goals of the Russian Federation, defined by the Decree of the President of Russia dated May 07, 2024 (hereinafter - the Decree) [49]. According to this Decree, the President sets the task for the Government to develop a spatial development strategy and a plan to achieve national development goals. To form them, it is advisable to turn to foresight, which will create an organizational mechanism for the implementation of the Decree, develop programs and plans for the development of the economy and society based on scientific principles. Taking into account the factors determining the specifics of building the foresight field and the content of the designated Decree, it will take the form shown in Figure 4. To determine the range of experts and consumers of the results of strategizing, it is proposed to form an appropriate foresight field. The small oval will include Government at various levels interested in the social, patriotic, spiritual and moral development of society, large entrepreneurs aimed at economic development, the formation of healthy competition, high efficiency and technology, as well as educational institutions capable of training the necessary number of highly qualified specialists in the right fields. At the same time, the second entity, along with the state, can be involved in financing foresight research. The average oval is represented by the population of the country, medium and small organizations that will feel the results of achieving the goals set in the Decree. The large oval will include segments of the population with a fairly high standard of living, who do not need support from the state, as well as enterprises that are actively engaged in innovation, technical and technological development, and the introduction of digitalization on their own. At the same time, it is advisable to differentiate the experts who will enter the small oval in accordance with their specialization according to the seven goals outlined in the Decree.
Figure 4. The foresight field formed to solve the tasks indicated in the Decree Thus, the inclusion in the field of foresight, along with experts, representatives of the interests of various organizations and the public, especially those who do not have a personal interest in the results, will increase objectivity and prevent possible distortions of the results. The working group should represent the interests of various organizations. In order to increase the optimality of foresight research, increase the accuracy of forecasts, and level the subjectivity factor, it is proposed to adopt the methods of foresight that have become widespread and have proven their effectiveness abroad, including using ICT. Thus, the method developed by Hansen M.S. et al. [40], combining scenario analysis and computer modeling with discrete events, will improve the quality of risk assessment, carry out continuous strategy development, and reduce the knowledge gap at different levels of the organization. Kuklina I. R. [50] notes that it is a mistake to directly transfer foresight topics, questionnaires and "key growth points" developed on the basis of analytical work from one country to the realities of another, since it is important to take into account national peculiarities. Therefore, the expediency of copying a particular foreign method and foresight themes should be carefully evaluated. It is particularly important to use foresight in the framework of achieving the national goal of "Technological leadership", since it is technological forecasting that is the most well-developed area of strategizing. The study of the theoretical aspects and international long-term practice of foresight has confirmed its effectiveness as a strategic planning tool in conditions of increasing uncertainty. Despite the variety of foresight projects, they are mainly focused on forecasts of technological development. The latter occupy an important place in the development of innovation strategies at the international, national, regional and corporate levels. Constantly emerging new tasks in the context of increasing dynamism, uncertainty, and globalization expand the range of possibilities for using foresight, which in turn necessitates the development and increase in the variety of its methods. Among the foresight methods developed in recent years, those involving the use of ICT stand out, which is consonant with the digitalization that has covered all spheres. However, despite the advantages of ICT, one cannot completely abandon the creative component of foresight.
The study showed that foresight can find a more extended application: to solve new urgent tasks set by various scientists. Tim Haarhaus and Andreas Liening [51] note that companies need dynamic capabilities to flexibly respond to an uncertain environment and shape its conditions. Foresight is able to provide this. In the work of Wibeck et al. [52] It is noted that many of the problems currently faced by societies around the world need to be solved using a different type of thinking than the one that created them. Foresight can be proposed as a new type of thinking, which expands the possibilities of traditional forecasting. This idea is supported by Siri Boe-Lillegraven and Stephan Monterde [53]. However, they mention that organizational aspects such as available time and perceived risks and benefits are likely to deter participation in foresight thinking, which affects the number of new perspectives being considered. Cultural control mechanisms also influence motivation to participate in the foresight. The approach to building the foresight field refined in this study can help solve the problem of increasing the foresight maturity of small and medium-sized enterprises, which Anna Kononyuk focuses on [9], through careful selection and involvement of stakeholders. Meanwhile, one cannot agree with A. A. Chulok [54], who argues that in the near future foresight can replace the traditional branches of marketing and strategic analysis of organizations. Due to the complexity of the organization and the high cost of implementing foresight, it will not be completely accessible to small enterprises. Mikko Dufva and Toni Ahlqvist [2], an der Duin et al.[55] note the urgency of switching to systemically distributed forecasting covering various sectors and administrative levels. At the same time, Wibeck et al. [52] indicate that a high degree of flexibility and adaptability is required for the success of interdisciplinary projects. It is possible to ensure effective inter-organizational interaction and prompt response to changes in business conditions through the implementation of foresight. Agreement on the need to attract as many foresight participants as possible is found in the works of V. P. Tretyak [44] and A.A. Sitnikova [56]. They emphasize that they note that the significant advantage of foresight is the involvement of a wide range of participants, including business, government, the scientific and technical sphere, the public, as well as the presence of elements of active influence on the future. The position opposite to Tretyak V. P. [44] is expressed by Kuklina I. R. [50]. She notes that the participation of a large number of interested groups or a wide range of topics under consideration can lead to a blurring of the priority system, replacing them with a simple summation of the technological requests of all foresight participants. Natalia Veselitskaya and Sergey Shashnov [57] also pay considerable attention to the issue of forming the composition of participants in foresight research and the end users of their results - stakeholders, or stakeholders. In their work, the authors note that the range of participants in modern foresight has become more diverse due to the inclusion of not only professional experts, but also representatives of the public and other potential beneficiaries. This allows us to take into account the interests of all parties as much as possible and ensure the applicability of the results without compromising their quality while maintaining the high role of experts. Our proposed approach to the formation of the foresight field in the future can be supplemented with elements of the method of stakeholder analysis developed by this scientist in terms of the classification of participants. Karasev O.I. and Mukanina E.I. [58] also develop criteria for selecting respondents to a foresight study and differentiate them into necessary and sufficient ones. Chernysheva T.Y. [59] built a hierarchical model for evaluating and selecting experts. An important characteristic of the respondent is a broad outlook and knowledge in the subject area. These approaches can also be applied in the formation of the foresight field. Sidelnikov Yu.V. [60] notes the importance of such a quality of the future expert as the stability of opinion, which determines the individual position in the field of study of the respondent and the most isolated point of view from the results of other experts. However, during the foresight, experts will have to interact with each other, so it is advisable, in addition to professional competencies, to evaluate teamwork skills, since the purpose of foresight is precisely to develop a common compromise solution. Self-criticism, the ability of experts to admit the presence of alternative points of view, to listen to opponents, to compromise, not to flaunt their experience, regalia, connections, to use the rules of team interaction will allow you to get balanced, undistorted results of the foresight. Hidehito Honda, Yuichi Washida, Akihito Sudo, Yuichiro Wajima, Keigo Awata, Kazuhiro Ueda [61] found that experts generate more unique scenarios, refer to a greater variety of information sources than non-specialists. Therefore, the information collected in the process of foresight research from experts will help to increase the reliability of the assessment, find an original approach to solving problems, and eliminate problems. David Sarpong and Mairi Maclean [62] note the importance of using the potential of middle management, whose representatives have appropriate detailed knowledge about future developments and organizational capabilities. Foresight will ensure close constant interaction of employees at different levels in the organization. At the same time, in the process of foresight research, the problem of collecting information may arise, since not all organizations and individuals are ready to disclose it to third parties. To smooth out this obstacle, Wong Wai-Huen [63] recommends that reputable stakeholders be involved in data collection, to whom companies are more likely to provide the required information due to the desire to form business relationships. Another disadvantage of foresight is noted by N.V. Meshkova [64]: the final documents are not intended for participants in the field of foresight research. In our opinion, this indicates the incompleteness of work within the framework of foresight research in terms of evaluating the results of the entire project, and understanding the validity of the forecasts of individual participants. In turn, monitoring and final comparison of expected and actual situations would help to improve the composition of the foresight field in future studies. The role of foresight is not limited to its use in forecasting, planning and innovation. Bootz et al. [65] use a collaborative and systematic foresight approach to study I4.0 trajectories under uberization conditions. In our opinion, foresight acquires special value in conditions of uncertainty, as it is based not only on an accurate assessment of the influence of various factors and the construction of trends, but also involves the independent design of the desired future and the development of ways to ensure it using risk management. The researchers also consider the specifics of using foresight in order to discover entrepreneurial opportunities [66], choose a specialization [67], form key competencies, and competitive advantage [68]. Conclusion The research is based on the accumulated experience of foreign and Russian scientists and creates new aspects of conducting foresight sessions in terms of determining the range of experts and stakeholders. The scientific novelty of this study lies in clarifying the foresight field by factors influencing the formation of its composition, as well as systematizing problems in the field of strategic planning and foresight and proposing solutions to them. In addition, the authors emphasize the need to take into account the criteria for selecting experts "teamwork skills". The use of such a concept as foresight field circles provides a clear and detailed understanding of who and how the project or research participants will cooperate with, who the research is aimed at, which will increase the effectiveness of preparation and facilitate its implementation. It seems advisable to integrate foresight into government planning. This will make it possible to create mechanisms for taking into account long-term trends and scenarios in the development of legislation and economic policy. In particular, the need for foresight research is determined by the Decree. The presented work is not devoid of a number of limitations related to the presence of barriers preventing the wider implementation of foresight. As the complexity of the study increases, the benefits of foresight decrease, and its results may not be taken into account in the processes of developing regional strategies. The methods developed in the field of forecasting recurring events are inadequate for identifying and modeling low-frequency events due to the inability of experts to systematically reason in abstract terms throughout the foresight process. Further research can be aimed at determining the expediency and features of using foresight in micro and small enterprises, correlating the expected result, benefits with the cost of money and time. References
1. Piirainen, K.A., & Gonzalez, R. A. (2015). Theory of and within foresight – “What does a theory of foresight even mean?” Technological Forecasting and Social Change, 96, 191-201. Retrieved from doi.org/10.1016/j.techfore.2015.03.003
2. Dufva, M., & Ahlqvist, T. (2015). Elements in the construction of future-orientation: A systems view of foresight. Futures, 73, 112-125. Retrieved from doi.org/10.1016/j.futures.2015.08.006 3. Sukhacheva, V.I., & Smotrova, T.I. (2023). About foresight technologies and their applications at the regional management level. Modern economy: problems and solutions, 5(161), 31-49. Retrieved from https://journals.vsu.ru/meps/article/view/11334/11438 4. Weber, M., & Schaper-Rinkel, P. (2017). European sectoral innovation foresight: Identifying emerging cross-sectoral patterns and policy issues. Technological Forecasting and Social Change, 115, 240-250. Retrieved from doi.org/10.1016/j.techfore.2016.09.007 5. Gaponenko, N. (2022). In search of sectoral foresight methodology: Bridging foresight and sectoral system of innovation and production. Futures, 135, 102859. Retrieved from doi.org/10.1016/j.futures.2021.102859 6. Paliokaitė, A., & Pačėsa, N. (2014). The relationship between organisational foresight and organisational ambidexterity. Technological Forecasting and Social Change, 101, 165-181. Retrieved from doi.org/10.1016/j.techfore.2014.03.004 7. Wright, G., O'Brien, F., Meadows, M., Tapinos, E., & Pyper, N. (2020). Scenario planning and foresight: Advancing theory and improving practice. Technological Forecasting and Social Change, 159, 120220. Retrieved from doi.org/10.1016/j.techfore.2020.120220 8. Andreeva Anastasia. What is foresight and how to use it. Retrieved from https://trends.rbc.ru/trends/futurology/5eb542c89a79470ed74f2d21?from=copy 9. Kononyuk, Anna. (2022). Determinants of Foresight maturity of small and medium-sized businesses in Poland. Foresight, 16(1), 69-81. Retrieved from https://foresight-journal.hse.ru/data/2022/04/02/1811271052/6-Кононюк-69-81.pdf 10. Apreda, R., Bonaccorsi, A., Orlettac, F., & Fantoni, G. (2019). Expert forecast and realized outcomes in technology foresight. Technological Forecasting and Social Change, 141, 277-288. Retrieved from doi.org/10.1016/j.techfore.2018.12.006 11. Rhisiart, M., Störmer, E., & Daheim, C. (2017). The 2030 Future of Work scenarios. Technological Forecasting and Social Change, 124, 203-213. Retrieved from doi.org/10.1016/j.techfore.2016.11.020 12. Sokolova, A. (2022). Pre-foresight integrative methodology for STI policy: Increasing coherence and impact. Futures, 135, 10-28. Retrieved from doi.org/10.1016/j.futures.2021.102875 13. Conway, M. (2022). An integrated frame for designing conversations about futures. Futures, 136, 102887. Retrieved from doi.org/10.1016/j.futures.2021.102887 14. Andreescu, L., Gheorghiu, R., Zulean, M., & Curaj, A. (2013). Understanding normative foresight outcomes: Scenario development and the ‘veil of ignorance’ effect. Technological Forecasting and Social Change, 80(4), 711-722. Retrieved from doi.org/10.1016/j.techfore.2012.09.013 15. Cagnin, C., & Könnölä, T. (2014). Global foresight: Lessons from a scenario and roadmapping exercise on manufacturing systems. Futures, 59, 27-38. Retrieved from doi.org/10.1016/j.futures.2014.01.007 16. Weigand, K., Flanagan T., Dye K., & Jones P. (2014). Collaborative foresight: Complementing long-horizon strategic planning. Technological Forecasting and Social Change, 85, 134-152. Retrieved from doi.org/10.1016/j.techfore.2013.08.016 17. Mozuni, M., & Jonas, W. (2017). An Introduction to the Morphological Delphi Method for Design: A Tool for Future-Oriented Design Research She Ji: The Journal of Design. Economics and Innovation, 3(4), 303-318. Retrieved from doi.org/10.1016/j.sheji.2018.02.004 18. Spickermann, A., Zimmermann, M., & von der Gracht, H. A. (2014). Surface-and deep-level diversity in panel selection – Exploring diversity effects on response behaviour in foresight. Technological Forecasting and Social Change, 85, 105-120. Retrieved from doi.org/10.1016/j.techfore.2013.04.009 19. Cuhls, K., Dragomir, B., Gheorghiu, R., Rosa, A., & Curaj, A. (2022). Probability and desirability of future developments – Results of a large-scale Argumentative Delphi in support of Horizon Europe preparation. Futures, 138, 102918. Retrieved from doi.org/10.1016/j.futures.2022.102918 20. Ecken, P., Gnatzy, T., & von der Grach, H.A. (2011). Desirability bias in foresight: Consequences for decision quality based on Delphi results. Technological Forecasting and Social Change, 78(9), 1654-1670. Retrieved from doi.org/10.1016/j.techfore.2011.05.006 21. Mainzer, K. (2020). Technology Foresight and Sustainable Innovation Development in the Complex Dynamical Systems View. Foresight and STI Governance, 14(4), 10-19. doi:10.17323/2500-2597.2020.4.10.19 22. MacKay, R.B., & McKiernan, P. (2004). The role of hindsight in foresight: refining strategic reasoning. Futures, 36(2), 161-179. Retrieved from doi.org/10.1016/S0016-3287 (03)00147-2 23. Gorelova, G.V., & Pankratova, N.D. (2018). Scientific Foresight and Cognitive Modeling of Socio-Economic Systems. IFAC-Papers OnLine, 51, 145-149. https://doi.org/10.1016/j.ifacol.2018.11.264 24. Yoon, J., Kim, Y. J., Vonortas, N.S., & Han, S.W. (2019). A moderated mediation model of technology roadmapping and innovation: The roles of corporate foresight and organizational support. Journal of Engineering and Technology Management, 52, 61-73. Retrieved from doi.org/10.1016/j.jengtecman.2017.10.002 25. Chen, H., Wakeland, W., & Yu, J. (2012). A two-stage technology foresight model with system dynamics simulation and its application in the Chinese ICT industry. Technological Forecasting and Social Change, 79(7), 1254-1267. Retrieved from doi.org/10.1016/j.techfore.2012.02.007 26. Kayser, V., & Blind, K. (2017). Extending the knowledge base of foresight: The contribution of text mining. Technological Forecasting and Social Change, 116, 208-215. Retrieved from https://doi.org/10.1016/j.techfore.2016.10.017 27. Antoine, S., Könnölä, T., Warnke, P., Barré, R., & Kuhlmann, S. (2011). Tailoring Foresight to field specificities. Futures, 43(3), 232-242. Retrieved from doi.org/10.1016/j.futures.2010.11.002 28. Heinonen, S., & Hiltunen, E. (2012). Creative Foresight Space and the Futures Window: Using visual weak signals to enhance anticipation and innovation. Futures, 44(3), 248-256. Retrieved from doi.org/10.1016/j.futures.2011.10.007 29. Cuhls, K. E. (2017). Mental time travel in foresight processes–Cases and applications. Futures, 86, 118-135. Retrieved from doi.org/10.1016/j.futures.2016.05.008 30. Graefe, A., Luckner, S., & Weinhardt, C. (2010). Prediction markets for foresight. Futures, 42(4), 394-404. 31. Tobias, P., von der Gracht, H.A., & Wohlenberg, H. (2015). Integrating prediction market and Delphi methodology into a foresight support system – Insights from an online game. Technological Forecasting and Social Change, 97, 47-64. Retrieved from doi.org/10.1016/j.techfore.2014.02.021 32. Ilmola, L., & Rovenskaya, E. (2016). The exploration of unknown unknowns in foresight. Technological Forecasting and Social Change, 106, 85-100. Retrieved from doi.org/10.1016/j.techfore.2015.12.015 33. Alizadeh, R., Lund, P.D., Beynaghi, A., Abolghasemi, M., & Maknoon, R. (2016). An integrated scenario-based robust planning approach for foresight and strategic management with application to energy industry. Technological Forecasting and Social Change, 104, 162-171. Retrieved from doi.org/10.1016/j.techfore.2015.11.030 34. Sebillotte, M., & Sebillotte, C. Foresight in mission-oriented research: The SYSPAHMM foresight method (SYStem, Processes, Clusters of Hypotheses, Micro-and Macroscenarios). Futures, 42(1), 15-25. Retrieved from doi.org/10.1016/j.futures.2009.08.013 35. Saritas, O., & Oner, M.A. (2004). Systemic analysis of UK foresight results: Joint application of integrated management model and roadmapping. Technological Forecasting and Social Change, 71(1–2), 27-65. Retrieved from doi.org/10.1016/S0040-1625 (03)00067-2 36. Nazarko, J., Ejdys, J., Halicka, K., Nazarko, Ł., Kononiuk, A., & Olszewska, A. (2017). Factor Analysis as a Tool Supporting STEEPVL Approach to the Identification of Driving Forces of Technological Innovation. Procedia Engineering, 182, 491-496. 37. Spithouraki, G. P., Petropoulos, F., Nikolopoulos, K., & Assimakopoulosa, V. (2015). Amplifying the learning effects via a Forecasting and Foresight Support System. International Journal of Forecasting, 31(1), 20-32. Retrieved from doi.org/10.1016/j.ijforecast.2014.05.002 38. Rantanen, H., & Kahila, M. (2009). The SoftGIS approach to local knowledge. Journal of Environmental Management, 90(6), 1981-1990. Retrieved from doi:10.1016/j.jenvman.2007.08.025 39. Kayser, V., & Shala, E. (2020). Scenario development using web mining for outlining technology futures. Technological Forecasting and Social Change, 156, 120086. Retrieved from doi.org/10.1016/j.techfore.2020.120086 40. Hansen, M. S., Rasmussen, L.B., & Jacobsen, P. (2016). Interactive foresight simulation. Technological Forecasting and Social Change, 103, 214-227. Retrieved from doi.org/10.1016/j.techfore.2015.10.011 41. May, M.C., Overbeck, L., Wurster, M., Kuhnle, A., & Lanza, G. (2021). Foresighted digital twin for situational agent selection in production control. Procedia CIRP, 99, 27-32. Retrieved from doi.org/10.1016/j.procir.2021.03.005 42. Seonho, Kim, You-Eil, Kim, Kuk-Jin, Bae, Sung-Bae, Choi, Jong-Kyu, Park, Young-Duk, Koo, Young-Wook, Park, Hyun-Kyoo, Choi, Hyun-Moon, Kang, & Sung-Wha, Hong (2013). NEST: A quantitative model for detecting emerging trends using a global monitoring expert network and Bayesian network. Futures, 52, 59-73. 43. Major, E.J., & Cordey-Hayes, M. (2000). Engaging the business support network to give SMEs the benefit of foresight. Technovation, 20(11), 589-602. Retrieved from doi.org/10.1016/S0166-4972 (00)00006-7 44. Tretyak, V.P. The practice of applying Foresight. Retrieved from https://riep.ru/upload/iblock/c5f/c5f700ec850b994f0d7b246af09a8715.pdf 45. Penkova, I. V. (2015). Circles of the field of the foresight project of a virtual enterprise. Economic and management issues, 2(2), 94-96. Retrieved from https://moluch.ru/th/5/archive/16/387/ 46. Sudakov, Dmitry, Luksha, Pavel, StrietskAilina, Olga, Greg, Ken, Hoffman, Kristina, & Khachatryan, Liana. (2016). A guide to applying technological foresight to identify future competency needs. Geneva: ILO. Retrieved from https://www.skolkovo.ru/public/media/documents/research/sedec/SEDeC_STF_Guidebook_Rus.pdf 47. Fesyun, A.V. (2016). Foresight as a technology for implementing the nanoindustry development strategy. Vestnik VSU. Series: Economics and Management, 1, 144-152. Retrieved from file:///C:/Users/Илья/Pictures/Downloads/9625-Текст%20статьи-14692-1-10-20221228.pdf 48. Ahmed, Y.A., & El-Sabry, A.E. (2024). Evaluating the Performance of Foresight Studies: Evidence from the Egyptian Energy Sector. Foresight and STI Governance, 18(1), 69-79. doi:10.17323/2500-2597.2024.1.69.79 Retrieved from https://foresight-journal.hse.ru/data/2024/03/18/2140218246/6-%D0%AD%D0%BB%D1%8C-%D0%A5%D0%B0%D1%81%D1%81%D0%B0%D0%BD-69-79.pdf 49. Decree of the President of the Russian Federation dated 05/07/2024 No. 309 "On the National Development Goals of the Russian Federation for the period up to 2030 and for the future up to 2036". Retrieved from http://publication.pravo.gov.ru/document/0001202405070015?index=1 50. Kuklina, I. R. Foresight is a tool for active research and shaping the future. Retrieved from https://mniop.ru/wp-content/uploads/2015/05/forsayt-instrument-aktivnogo-issledovaniya-i-formirovaniya-buduschego.pdf 51. Haarhaus, T., & Liening, A. (2020). Building dynamic capabilities to cope with environmental uncertainty: The role of strategic foresight. Technological Forecasting and Social Change, 155, 120033. Retrieved from doi.org/10.1016/j.techfore.2020.120033 52. Wibeck, V., Eliasson, K., & Neset, T. – S. (2022). Co-creation research for transformative times: Facilitating foresight capacity in view of global sustainability challenges. Environmental Science. Policy, 128, 290-298. Retrieved from doi.org/10.1016/j.envsci.2021.11.023 53. Boe-Lillegraven, S., & Monterde, S.(2015). Exploring the cognitive value of technology foresight: The case of the Cisco Technology Radar. Technological Forecasting and Social Change, 101, 62-82. Retrieved from doi.org/10.1016/j.techfore.2014.07.014 54. Chulok, A. A. (2021). Economic analysis of foresight as a tool for strategic management of a company: global trends and Russian experience. The Russian Journal of Management, 19(2), 151–176. Retrieved from file:///C:/Users/Илья/Pictures/Downloads/nyakovleva,+151–176_Чулок.pdf 55. Van der Duin, P., Heger, T., & Schlesinger, M. D. (2014). Toward networked foresight? Exploring t Wright he use of futures research in innovation networks. Futures, 59, 62-78. Retrieved from doi.org/10.1016/j.futures.2014.01.008 56. Sitnikova, A.A. (2014). Modern Practices of Forsight Research of the Future of Social-Anthropological Systems Including Ethnocultural Groups of Northern Regions of the Russian Federation. Sociodynamics, 9, 44-62. Retrieved from doi:10.7256/2306-0158.2014.9.13405 Retrieved from http://en.e-notabene.ru/pr/article_13405.html 57. Veselitskaya, N., & Shashnov, S. (2024). Stakeholders and Their Participation in Foresight Projects. Foresight and STI Governance, 18(1), 80-91. Retrieved from doi:10.17323/2500-2597.2024.1.80.91 58. Karasev, O.I., & Lukonina, E.I. (2019). The method of expert assessments in foresight research. StatisticsandEconomics, 16(4), 4-13. Retrieved from https://statecon.rea.ru/jour/article/view/1375/1190 59. Chernysheva, T.Y. (2009). Hierarchical model of assessment and selection of experts. Management, computer engineering and informatics. Reports of TUSUR, 1(19). Part 1, 168-173. 60. Sidelnikov, Yu.V. (2007). System analysis of expert forecasting. Moscow: Moscow Aviation Institute. 61. Honda, H., Washida, Y., Sudo, A., Wajima, Y., Awata, K., & Ueda, K. (2017). The difference in foresight using the scanning method between experts and non-experts. Technological Forecasting and Social Change, 119, 18-26. Retrieved from www.sciencedirect.com/science/article/abs/pii/S004016251730313X 62. Sarpong, D., & Maclean, M. (2016). Cultivating strategic foresight in practise: A relational perspective. Journal of Business Research, 6(8), 2812-2820. Retrieved from doi.org/10.1016/j.jbusres.2015.12.050 6 63. Wong, W.K., Teh, B.H., & Tan, S.H. (2023). The Influence of External Stakeholders on Environmental, Social, and Governance (ESG) Reporting: Toward a Conceptual Framework for ESG Disclosure. Foresight and STI Governance, 17(2), 9-20. doi:10.17323/2500-2597.2023.2.9.20 Retrieved from https://foresight-journal.hse.ru/data/2023/06/14/2072322178/1-Вонг-Куэн-9-20.pdf 64. Meshkova, N.V., Kozlov, V.A., & Tretyak, V.P. The state of foresight research in Russia. Retrieved from http://www.virtass.ru/admin/pics/24_01_IO.pdf 65. Bootz, J-P, Michel, S., Pallud, J., & Monti, R. (2022). Possible changes of Industry 4.0 in 2030 in the face of uberization: Results of a participatory and systemic foresight study. Technological Forecasting and Social Change, 184, 121962. Retrieved from doi.org/10.1016/j.techfore.2022.121962 66. Hajizadeh, A., & Valliere, D. (2022). Entrepreneurial foresight: Discovery of future opportunities. Futures, 135, 10-28. Retrieved from doi.org/10.1016/j.futures.2021.102876 67. Gheorghiu, R., Andreescu, L., & Curaj, A. (2016). A foresight toolkit for smart specialization and entrepreneurial discovery. Futures, 80, 33-44. Retrieved from doi.org/10.1016/j.futures.2016.04.001 68. Rohrbeck, R., Battistella, C., & Huizingh, E. (2015). Corporate foresight: An emerging field with a rich tradition. Technological Forecasting and Social Change, 101, 1-9. Retrieved from doi.org/10.1016/j.techfore.2015.11.00
First Peer Review
Peer reviewers' evaluations remain confidential and are not disclosed to the public. Only external reviews, authorized for publication by the article's author(s), are made public. Typically, these final reviews are conducted after the manuscript's revision. Adhering to our double-blind review policy, the reviewer's identity is kept confidential.
Second Peer Review
Peer reviewers' evaluations remain confidential and are not disclosed to the public. Only external reviews, authorized for publication by the article's author(s), are made public. Typically, these final reviews are conducted after the manuscript's revision. Adhering to our double-blind review policy, the reviewer's identity is kept confidential.
|