Anticipating Future Innovation Pathways Through Large Data by Tugrul U. Daim,Denise Chiavetta,Alan L. Porter,Ozcan Saritas

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

This publication goals to spot promising destiny developmental possibilities and functions for Tech Mining. in particular, the enclosed contributions will pursue 3 converging themes:

  • The expanding availability of digital textual content info assets when it comes to technology, expertise and Innovation (ST&I).
  • The a number of tools which are capable of deal with this knowledge successfully and contain ability to faucet into human services and interests.
  • Translating these analyses to supply necessary intelligence on most probably destiny advancements of specific rising S&T targets. 

Tech Mining could be outlined as textual content analyses of ST&I info assets to generate aggressive Technical Intelligence (CTI). It combines bibliometrics and complex textual content analytic, drawing on really expert wisdom concerning ST&I. Tech Mining can also be seen as a distinct kind of “Big info” analytics since it searches on a objective rising know-how (or key association) of curiosity in worldwide databases. One then downloads, in general, millions of field-structured textual content files (usually abstracts), and analyses these for invaluable CTI.  Forecasting Innovation Pathways (FIP) is a technique drawing on Tech Mining plus extra steps to elicit stakeholder and professional wisdom to hyperlink fresh ST&I task to most probably destiny development. 

A decade in the past, we demeaned administration of expertise (MOT) as a bit of self-satisfied and ignorant.  Most know-how managers relied overwhelmingly on informal human judgment, mostly oblivious of the possibility of empirical analyses to notify R&D administration and technology coverage.  CTI, Tech Mining, and FIP are altering that. the buildup of Tech Mining learn during the last decade deals a wealthy source of potential to get at rising expertise advancements and organizational networks up to now.  Efforts to bridge from these contemporary histories of improvement to undertaking most probably FIP, besides the fact that, turn out significantly tougher. One concentration of this quantity is to increase the repertoire of data assets; that may enhance FIP.

Featuring situations of novel techniques and purposes of Tech Mining and FIP, this quantity will current frontier advances in ST&I textual content analytics that would be of  interest to scholars, researchers, practitioners, students and coverage makers within the fields of R&D making plans, expertise administration, technological know-how coverage and innovation strategy.

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