Ozcan Saritas – författare

This timely book presents a collection of expert insights into the impacts of COVID-19 in a broader socio-economic context. In each chapter, the authors identify the current impact of COVID-19 by demonstrating transformative signals and project these signals to the future by considering their alternative futures and implications.

Using a new methodology for foresight studies, this book presents new findings and policy recommendations to improve living conditions and make progress toward achieving the Sustainable Development Goals (SDGs). Using the case of South Africa, the respective chapters show how social and economic challenges can be addressed in an inclusive and sustainable way. The book also provides guidelines for practitioners by introducing them to cutting-edge ways of formulating Science, Technology, and Innovation (STI) policies.  

The new foresight methodology uses a combination of qualitative and quantitative methods, including horizon scanning and scenario planning, as well as big data analysis, scientometric and semantic methods. The innovative approaches developed throughout the book are subsequently demonstrated using a national foresight study in South Africa. The outputs and outcomes generated by the study can be used to inform the identification and selection of priorities for the next decadal plan for STI. The book offers a valuable asset for emerging and developing economies in Africa and around the world in terms of tackling the grand challenges of the 21st century, such as water, food, energy, climate change, health and education.

This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes:

Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of “Big Data” analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI.  Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development. 

A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant.  Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy.  CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date.  Efforts to bridge from those recent histories ofdevelopment to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP.

Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of  interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy.