Technology roadmapping for competitive technical intelligence

Zhang, Y; Robinson, DKR; Porter, AL; Zhu, D; Zhang, G; Lu, J

Technology roadmapping for competitive technical intelligence

Zhang, Y

Robinson, DKR Porter, AL Zhu, D Zhang, G

Lu, J

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Publication Type:: Journal Article
Citation:: Technological Forecasting and Social Change, 2016, 110 pp. 175 - 186
Issue Date:: 2016-09-01

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Field	Value	Language
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-7731-0301	en_US
dc.contributor.author	Robinson, DKR	en_US
dc.contributor.author	Porter, AL	en_US
dc.contributor.author	Zhu, D	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.date.available	2020-05-25T19:15:08Z
dc.date.issued	2016-09-01	en_US
dc.identifier.citation	Technological Forecasting and Social Change, 2016, 110 pp. 175 - 186	en_US
dc.identifier.issn	0040-1625	en_US
dc.identifier.uri	http://hdl.handle.net/10453/41076
dc.description.abstract	© 2015 Elsevier Inc. Understanding the evolution and emergence of technology domains remains a challenge, particularly so for potentially breakthrough technologies. Though it is well recognized that emergence of new fields is complex and uncertain, to make decisions amidst such uncertainty, one needs to mobilize various sources of intelligence to identify known–knowns and known–unknowns to be able to choose appropriate strategies and policies. This competitive technical intelligence cannot rely on simple trend analyses because breakthrough technologies have little past to inform such trends, and positing the directions of evolution is challenging. Neither do qualitative tools, embracing the complexities, provide all the solutions, since transparent and repeatable techniques need to be employed to create best practices and evaluate the intelligence that comes from such exercises. In this paper, we present a hybrid roadmapping technique that draws on a number of approaches and integrates them into a multi-level approach (individual activities, industry evolutions and broader global changes) that can be applied to breakthrough technologies. We describe this approach in deeper detail through a case study on dye-sensitized solar cells. Our contribution to this special issue is to showcase the technique as part of a family of approaches that are emerging around the world to inform strategy and policy.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP140101366
dc.relation.ispartof	Technological Forecasting and Social Change	en_US
dc.relation.isbasedon	10.1016/j.techfore.2015.11.029	en_US
dc.subject.classification	Science Studies	en_US
dc.title	Technology roadmapping for competitive technical intelligence	en_US
dc.type	Journal Article
utslib.citation.volume	110	en_US
utslib.for	080605 Decision Support and Group Support Systems	en_US
utslib.for	10 Technology	en_US
utslib.for	14 Economics	en_US
utslib.for	15 Commerce, Management, Tourism and Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	110	en_US

Abstract:

© 2015 Elsevier Inc. Understanding the evolution and emergence of technology domains remains a challenge, particularly so for potentially breakthrough technologies. Though it is well recognized that emergence of new fields is complex and uncertain, to make decisions amidst such uncertainty, one needs to mobilize various sources of intelligence to identify known–knowns and known–unknowns to be able to choose appropriate strategies and policies. This competitive technical intelligence cannot rely on simple trend analyses because breakthrough technologies have little past to inform such trends, and positing the directions of evolution is challenging. Neither do qualitative tools, embracing the complexities, provide all the solutions, since transparent and repeatable techniques need to be employed to create best practices and evaluate the intelligence that comes from such exercises. In this paper, we present a hybrid roadmapping technique that draws on a number of approaches and integrates them into a multi-level approach (individual activities, industry evolutions and broader global changes) that can be applied to breakthrough technologies. We describe this approach in deeper detail through a case study on dye-sensitized solar cells. Our contribution to this special issue is to showcase the technique as part of a family of approaches that are emerging around the world to inform strategy and policy.

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http://hdl.handle.net/10453/41076