Applied Quantitative Methods in Technology Foresight

Serhat Burmaoglu is an instructor in the Department of Data Science and Analytics at Izmir Katip Celebi University, Turkey. He was a visiting scholar at Georgia Institute of Technology, USA, and dean of the Faculty of Economics and Administrative Sciences at Kyrgyz-Turkish Manas University, Kyrgyzstan. His research focuses on technology foresight, innovation policy, and machine- and deep-learning predictive analytics. With over 15 years of experience, his work appears in leading major international journals, and he co-edited Covid-19 and Society (Springer, 2022).

Chapter 1: Introduction to Quantitative Technology Foresight.- Chapter 2: Fundamentals of Data in Technology Foresight.- Chapter 3: Statistical Foundations for Technology Analysis.- Chapter 4: Bibliometric Analysis of Digital Transformation Research: A Science Mapping Approach.- Chapter 5: Patent Analytics and Technology Mining: Recognition of Hidden Innovation Trajectories.- Chapter 6: Multivariate Analysis for Technology Assessment.- Chapter 7: Machine Learning in Technology Forecasting.- Chapter 8: Deep Learning Applications in Foresight.- Chapter 9: Text Mining and Natural Language Processing.- Chapter 10: AI-Augmented Weak Signal Interpretation for Emerging Technology Foresight.- Chapter 11: Visualization and Communication.- Chapter 12: Data-Led Technology Roadmapping.- Chapter 13: Emerging Technology Detection.- Chapter 14: Strategic Technology Planning.- Chapter 15: Signal in the Noise: AI-Enhanced Evaluation of Quantitative Technology Foresight in an Era of Content Inflation.