Authors: Ying Wan Loh; Letizia Mortara
Addresses: Institute for Manufacturing, Department of Engineering, University of Cambridge, 17 Charles Babbage Road, Cambridge, CB3 0FS, UK ' Institute for Manufacturing, Department of Engineering, University of Cambridge, 17 Charles Babbage Road, Cambridge, CB3 0FS, UK
Abstract: Technology intelligence (TI) is an activity that supports decision-making at many levels. However, practitioners often find that evaluating the quality of TI activities can be very challenging. Whilst several papers in current literature discuss performance assessments in innovation contexts, less research specifically addresses the issue of performance measurement for TI. This paper aims to start to fill this gap by developing empirical evidence about the current evaluation methods adopted in industry, and the challenges posed by the metrics used in assessing TI. A framework is proposed, which suggests that the metrics used for TI follow two logics: the first is that they are activity- or outcome-based, and the second is that they apply either to specific projects or to the entire firm. This classification of metrics could help practitioners structure their future measuring and evaluating strategies.
Keywords: technology intelligence; technology scouting; performance measure; assessment; evaluation; metrics; decision-making; open innovation; information quality; innovation management measurement; efficiency; effectiveness.
International Journal of Technology Intelligence and Planning, 2017 Vol.11 No.3, pp.187 - 211
Received: 07 Aug 2015
Accepted: 26 Jun 2016
Published online: 28 Jul 2017 *