Measuring Technology Maturity

Operationalizing Information from Patents, Scientific Publications, and the Web
1. Auflage 2016
ISBN: 978-3-658-12131-0
Verlag: Springer

Buch, Englisch, 311 Seiten, Book, Format (B × H): 148 mm x 210 mm, Gewicht: 4447 g

Reihe: Forschungs-/Entwicklungs-/Innovations-Management

Till Albert presents a
machine learning based approach to harnessing information contained in big data
from different media sources such as patents, scientific publications, or the
internet. He shows how this information can be used for automated maturity
evaluation of yet unknown technologies. Elaborate patent based indicators contain
very useful information on technological aspects of maturity but lack for
others such as social, economic, ecological, or political factors. The approach
presented in this book is able to incorporate these other factors and provide a
firm basis for robust technology maturity and speed of maturity evaluation.

Zielgruppe

Research

Autoren/Hrsg.

Albert, Till

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Management Forschung & Entwicklung (F&E), Innovation
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management

Inhaltsverzeichnis

Information Scattering in Different Text Media.- Identifying Text Media
Suitable for Informetric Analyses and Deriving Relevant Indicator Values.- Using Machine Learning
to Gauge the Maturity Classification Performance of a Set of Indicators.- Representation,
Interpretation, and Utilization of Maturity Analysis Results.

Über Autor(innen)

Till Albert wrote this
dissertation with Professor Martin G. Moehrle at the Institute of Project
Management and Innovation (IPMI) of the University of Bremen. He now works in
the area of data driven approaches to support innovation and technology
management, such as patent analysis, scientometrics, webometrics, social
network analysis, and combinations thereof.