Anticipating Future Innovation Pathways Through Large Data Analysis

Editors: Tugrul U. Daim, Denise Chiavetta, Alan L. Porter, Ozcan Saritas



Identifies promising future developmental opportunities and applications for Tech Mining

Presents frontier advances in Science, Technology & Innovation (ST&I) text analytics and other approaches

Combines multiple data resources and treats them using multiple methods

This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes:
• The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I).
• The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests.
• Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets.

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 of development 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.

Table of contents (18 chapters)

Front Matter
Pages i-xviii

Data Science/Technology Review
Front Matter
Pages 1-1
FTA as Due Diligence for an Era of Accelerated Interdiction by an Algorithm-Big Data Duo
Pages 3-23
A Conceptual Framework of Tech Mining Engineering to Enhance the Planning of Future Innovation Pathway (FIP)
Pages 25-44
Profile and Trends of FTA and Foresight
Pages 45-58
Recent Trends in Technology Mining Approaches: Quantitative Analysis of GTM Conference Proceedings
Pages 59-69
Anticipating Future Pathways of Science, Technologies, and Innovations: (Map of Science)2 Approach
Pages 71-96

Text Analytic Methods
Front Matter
Pages 97-97
Towards Foresight 3.0: The HCSS Metafore Approach—A Multilingual Approach for Exploring Global Foresights
Pages 99-117
Using Enhanced Patent Data for Future-Oriented Technology Analysis
Pages 119-131
Innovation and Design Process Ontology
Pages 133-151
Generating Competitive Technical Intelligence Using Topical Analysis, Patent Citation Analysis, and Term Clumping Analysis
Pages 153-172
Identifying Targets for Technology Mergers and Acquisitions Using Patent Information and Semantic Analysis
Pages 173-186
Identifying Technological Topic Changes in Patent Claims Using Topic Modeling
Pages 187-209
Semi-automatic Technology Roadmapping Composing Method for Multiple Science, Technology, and Innovation Data Incorporation
Pages 211-227
Generating Futures from Text—Scenario Development Using Text Mining
Pages 229-245

Anticipating the Future-Cases and Frameworks
Front Matter
Pages 247-247
Additive Manufacturing: Importance and Challenges for Latin America
Pages 249-271
The Application of Social Network Analysis: Case of Smart Roofing
Pages 273-302
Building a View of the Future of Antibiotics Through the Analysis of Primary Patents
Pages 303-320
Combining Scientometrics with Patent-Metrics for CTI Service in R&D Decision-Making: Practices of National Science Library of CAS
Pages 321-339
Tech Mining for Emerging STI Trends Through Dynamic Term Clustering and Semantic Analysis: The Case of Photonics
Pages 341-360

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