Technology roadmapping for competitive technical intelligence

Yi Zhang, Douglas K. R. Robinson (), Alan L. Porter, Donghua Zhu, Guangquan Zhang and Jie Lu
Additional contact information
Yi Zhang: BIT - Beijing Institute of Technology
Douglas K. R. Robinson: LISIS - Laboratoire Interdisciplinaire Sciences, Innovations, Sociétés - INRA - Institut National de la Recherche Agronomique - UPEM - Université Paris-Est Marne-la-Vallée - ESIEE Paris - CNRS - Centre National de la Recherche Scientifique
Alan L. Porter: School of Public Policy - Georgia Institute of Technology [Atlanta]
Donghua Zhu: LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] - UVSQ - Université de Versailles Saint-Quentin-en-Yvelines - INSU - CNRS - Institut national des sciences de l'Univers - Université Paris-Saclay - CNRS - Centre National de la Recherche Scientifique - DRF (CEA) - Direction de Recherche Fondamentale (CEA) - CEA - Commissariat à l'énergie atomique et aux énergies alternatives

Post-Print from HAL

Abstract: 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.

Keywords: Text mining; Competitive technical intelligence; Technology roadmapping; Tech mining (search for similar items in EconPapers)
Date: 2015-12
Note: View the original document on HAL open archive server: https://hal.science/hal-01276909v1
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Published in Technological Forecasting and Social Change, 2015, pp.175-186. ⟨10.1016/j.techfore.2015.11.029⟩

Downloads: (external link)
https://hal.science/hal-01276909v1/document (application/pdf)

Related works:
Journal Article: Technology roadmapping for competitive technical intelligence (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01276909

DOI: 10.1016/j.techfore.2015.11.029

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().