Scientometric mapping as a strategic intelligence tool for the governance of emerging technologies

Rotolo, Daniele, Rafols, Ismael, Hopkins, Michael and Leydersdorff, Loet (2014) Scientometric mapping as a strategic intelligence tool for the governance of emerging technologies. Working Paper. University of Sussex, Brighton, Sussex.

[img]
Preview
PDF (SPRU Working Paper Series) - Published Version
Download (9MB) | Preview

Abstract

How can scientometric mapping function as a tool of ’strategic intelligence’ to aid the governance of emerging technologies? The present paper aims to address this question by focusing on a set of recently developed scientometric techniques, namely overlay mapping. We examine the potential these techniques have to inform, in a timely manner, analysts and decision-makers about relevant dynamics of technical emergence. We investigate the capability of overlay mapping in generating informed perspectives about emergence across three spaces: geographical, social, and cognitive. Our analysis relies on three empirical studies of emerging technologies in the biomedical domain: RNA interference (RNAi), Human Papilloma Virus (HPV) testing technologies for cervical cancer, and Thiopurine Methyltransferase (TPMT) genetic testing. The case-studies are analysed and mapped longitudinally by using publication and patent data. Results show the variety of ’intelligence’ inputs overlay mapping can produce for the governance of emerging technologies. Overlay mapping also confers to the investigation of emergence flexibility and granularity in terms of adaptability to different sources of data and selection of the levels of the analysis, respectively. These features make possible the integration and comparison of results from different contexts and cases, thus providing possibilities for a potentially more ’distributed’ strategic intelligence.
The generated perspectives allow triangulation of findings, which is important given the complexity featuring in technical emergence and the limitations associated with the use of single scientometric approaches.

Item Type: Reports and working papers (Working Paper)
Keywords: scientometric overlay mappings; emerging technology; strategic intelligence;governance; case-study.
Schools and Departments: University of Sussex Business School > SPRU - Science Policy Research Unit > SPRU Working Paper Series
Subjects: H Social Sciences
Depositing User: Jill Kirby
Date Deposited: 10 Jul 2014 10:48
Last Modified: 01 Nov 2016 16:26
URI: http://sro.sussex.ac.uk/id/eprint/49234

View download statistics for this item

📧 Request an update
http://sro.sussex.ac.uk/id/eprint/49234/
sro.sussex.ac.uk
crawl=CC-MAIN-2022-40
58495
application/http; msgtype=response
sha1:57XI34Z7WTQUW326334C7TSILWTIPB6Z
<urn:uuid:65407877-c779-458b-b665-dc9a5906f320>
2022-10-03T07:41:13Z
139.184.14.227
application/xhtml+xml
sha1:Y7S3WZH5AEQLLJ2EJMIDW6BYDGEYBICI
<urn:uuid:c264196f-5da4-4301-b8c4-61d62bf82bc5>
http://sro.sussex.ac.uk/id/eprint/49234/
response
<urn:uuid:f0798645-d1bb-42b4-ba00-5337cae31913>
isPartOf: CC-MAIN-2022-40
publisher: Common Crawl
description: Wide crawl of the web for September/October 2022
operator: Common Crawl Admin (info@commoncrawl.org)
hostname: ip-10-67-67-45
software: Apache Nutch 1.19 (modified, https://github.com/commoncrawl/nutch/)
robots: checked via crawler-commons 1.4-SNAPSHOT (https://github.com/crawler-commons/crawler-commons)
format: WARC File Format 1.1
conformsTo: https://iipc.github.io/warc-specifications/specifications/warc-format/warc-1.1/