Vision 2023: Turkey’s National Technology Foresight Program – a contextualist description and analysis

This paper describes and analyses Vision 2023 Turkish National Technology Foresight Program. The paper is not about a mere description of the activities undertaken. It analyses the Program from a contextualist perspective, where the Program is considered in its own national and organizational contexts by discussing how the factors in these contexts led to the particular decisions taken and approaches adopted when the exercise was organized, designed and practiced. With the description and analysis of the Vision 2023 Technology Foresight Program, the paper suggests that each Foresight exercise should be considered in its own context. The exercise should be organized, designed and practiced by considering the effects of the external contexts (national, regional and/or corporate) and organizational factors stemming from these different context levels along with the nature of the issue being worked on, which constitute the content of the exercise.Foresight, contextualism, Vision 2023, Turkey, Science and Technology Policy

Future-oriented technology analysis: Its potential to address disruptive transformations

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

On concepts and methods in horizon scanning: Lessons from initiating policy dialogues on emerging issues

Future-oriented technology analysis methods can play a significant role in enabling early warning signal detection and pro-active policy action which will help to better prepare policy- and decision-makers in today's complex and inter-dependent environments. This paper analyses the use of different horizon scanning approaches and methods as applied in the Scanning for Emerging Science and Technology Issues project. A comparative analysis is provided as well as a brief evaluation the needs of policy-makers if they are to identify areas in which policy needs to be formulated. This paper suggests that the selection of the best scanning approaches and methods is subject to contextual and content issues. At the same time, there are certain issues which characterise horizon scanning processes, methods and results that should be kept in mind by both practitioners and policy-maker

On concepts and methods in horizon scanning : lessons from initiating policy dialogues on emerging issues

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)Future-oriented technology analysis methods can play a significant role in enabling early warning signal detection and pro-active policy action which will help to better prepare policy- and decision-makers in today’s complex and inter-dependent environments. This paper analyses the use of different horizon scanning approaches and methods as applied in the Scanning for Emerging Science and Technology Issues project. A comparative analysis is provided as well as a brief evaluation the needs of policy-makers if they are to identify areas in which policy needs to be formulated. This paper suggests that the selection of the best scanning approaches and methods is subject to contextual and content issues. At the same time, there are certain issues which characterise horizon scanning processes, methods and results that should be kept in mind by both practitioners and policy-makers

Big data augmentated business trend identification: the case of mobile commerce

Identifying and monitoring business and technological trends are crucial for innovation and competitiveness of businesses. Exponential growth of data across the world is invaluable for identifying emerging and evolving trends. On the other hand, the vast amount of data leads to information overload and can no longer be adequately processed without the use of automated methods of extraction, processing, and generation of knowledge. There is a growing need for information systems that would monitor and analyse data from heterogeneous and unstructured sources in order to enable timely and evidence-based decision-making. Recent advancements in computing and big data provide enormous opportunities for gathering evidence on future developments and emerging opportunities. The present study demonstrates the use of text-mining and semantic analysis of large amount of documents for investigating in business trends in mobile commerce (m-commerce). Particularly with the on-going COVID-19 pandemic and resultant social isolation, m-commerce has become a large technology and business domain with ever growing market potentials. Thus, our study begins with a review of global challenges, opportunities and trends in the development of m-commerce in the world. Next, the study identifies critical technologies and instruments for the full utilization of the potentials in the sector by using the intelligent big data analytics system based on in-depth natural language processing utilizing text-mining, machine learning, science bibliometry and technology analysis. The results generated by the system can be used to produce a comprehensive and objective web of interconnected technologies, trends, drivers and barriers to give an overview of the whole landscape of m-commerce in one business intelligence (BI) data mart diagram

Systems thinking for foresight

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