“Big data” driven tech mining and ST&I management: an introduction

Ying Huang (), Xuefeng Wang, Yi Zhang, Denise Chiavetta and Alan L. Porter
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Ying Huang: Wuhan University
Xuefeng Wang: Beijing Institute of Technology
Yi Zhang: University of Technology Sydney
Denise Chiavetta: Search Technology, Inc.
Alan L. Porter: Search Technology, Inc.

Scientometrics, 2022, vol. 127, issue 9, No 8, 5227-5231

Abstract: Abstract Since the first Global Tech Mining (GTM) conference was held in Atlanta in 2011, the GTM conference has created a platform to connect tech mining researchers, exchange ideas and research progress, and promote collaborations. When it came to its 10th anniversary in 2020, COVID-19 forced the GTM conference into an online format. In tumultuous times for ST&I research activity, the GTM conference sought to focus on several issues: How to better collect and combine multiple “large data” sources? How to analyze these data effectively? And how to utilize these results more powerfully in ST&I management? In this collection, 15 papers are selected after evaluating by the science advisory committee, the guest editor team, and our peer review experts to address the following aspects regarding “tech mining”: (1) DATA: Maximizing the potential of traditional and novel data; (2) METHODS: Advancing and integrating methods; (3) APPLICATIONS: Innovative analyses translating to usefulintelligence.

Keywords: GTM; Tech Mining; Competitive Technical Intelligence; Science; Technology & Innovation; Intelligent Bibliometrics (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11192-022-04507-2

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