This book aims to identify promising future developmental opportunities
and applications for Tech Mining. Specifically, the enclosed
contributions will pursue three converging themes:
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The increasing availability of electronic text data resources relating
to Science, Technology and Innovation (ST&I).
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The multiple methods that are able to treat this data effectively and
incorporate means to tap into human expertise and interests.
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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.
