Table of Contents

Handbook of Innovation Indicators and Measurement

Handbook of Innovation Indicators and Measurement

Elgar original reference

Edited by Fred Gault

This Handbook comprehensively examines indicators and statistical measurement related to innovation (as defined in the OECD/Eurostat Oslo Manual). It deals with the development and the use of innovation indicators to support decision-making and is written by authors who are practitioners, who know what works and what does not, in order to improve the development of indicators to satisfy future policy needs.

Chapter 9: The OECD measurement agenda for innovation

Fernando Galindo-Rueda

Subjects: business and management, organisational innovation, economics and finance, economics of innovation, innovation and technology, economics of innovation, innovation policy, organisational innovation, politics and public policy, public policy


This chapter seeks to explain how the Organisation for Economic Co-operation and Development (OECD) develops indicators to help member countries and other economies build an environment conducive to translating science, technology and knowledge into innovation to enhance economic performance and improve social welfare. It highlights some illustrative examples from recent OECD experience in implementing its innovation measurement agenda and reviewing the innovation measurement framework, from which it draws some implications for the development and revision of measurement guidelines and the future of indicator development at the OECD. The mission of the OECD is to promote policies that will improve the economic and social well-being of people around the world. In support of this mission, indicators play a key role in presenting an accurate and comparable picture of the state of play of innovation and innovation policies across countries. Measurement matters as the ‘first essential step in the direction of learning any subject’, as famously noted by Lord Kelvin (1883), who went on to add that ‘when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind.’ This argument in support of the relevance of measurement has a clear resonance for those who work on a regular basis with policy makers in the domain of science, technology and innovation (STI).

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