Proposal of a framework for assessing data quality for technology intelligence: evidence from the building industry

Marina Flamand and Patience Le Coustumer ()
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Patience Le Coustumer: LEREPS - Laboratoire d'Etude et de Recherche sur l'Economie, les Politiques et les Systèmes Sociaux - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - Institut d'Études Politiques [IEP] - Toulouse - ENSFEA - École Nationale Supérieure de Formation de l'Enseignement Agricole de Toulouse-Auzeville

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Abstract: Assessing data quality is a prerequisite for using it effectively to inform decision-making. This general consensus regarding data quality has not been tested from the perspective of technology intelligence, which is an information-based activity to support strategic decision-making in innovation area. This article seeks to fill this gap by proposing an operational data quality assessment framework specifically tailored to the needs of technology intelligence experts. In addition to two traditional dimensions of data assessment (availability and reliability), we have integrated a third dimension: the utility for a technology intelligence approach. It is based on three more specific criteria: relevance, richness of information and the added value for analysing innovation. We demonstrate how to use this framework and illustrate its utility by assessing the quality of technical appraisals (ATec in French and below) to support technology intelligence in the building industry.

Date: 2024
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Published in International Journal of Technology Intelligence and Planning, 2024, 13 (3), pp.191-212. ⟨10.1504/IJTIP.2024.140609⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05526555

DOI: 10.1504/IJTIP.2024.140609

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