New Concepts in Innovation Output Measurement

During the 1980s and 1990s, ‘evolutionary’ or ‘Schumpeterian’ issues rose higher on the agenda of social and economic research. The growing interest in the study of innovation and technological change stands in contrast to the availability of adequate statistical data. The provision of data for empirical research is deficient in several respects, one problem being that data collection by statistical agencies tends to be confined to indicators of the ‘input’ side of the innovation process, mainly to R&D. There are attempts in several countries to extend the data collection to non-R&D innovation ‘inputs’. Examples are data on so-called ‘intangible’ investments (e.g. software, marketing or design expenditures), or (heroic) attempts to measure the total innovation expenditures of firms, including a number of non-R&D innovation cost categories (see also Chapter 7 of this book).

The state of knowledge regarding technological change has generally been shaped by the nature of the data which were available to scholars for analysis. Such data have always been incomplete and, at best, represented only a proxy measure reflecting some aspect of the process of technological change. Simon Kuznets observed in 1962 that the greatest obstacle to understanding the economic role of technological change was a clear inability of scholars to measure it. More recently, Cohen and Levin (1989) warned:

A fundamental problem in the study of innovation and technical change in industry is the absence of satisfactory measures of new knowledge and its contribution to technological progress. There exists no measure of innovation that permits readily interpretable cross-industry comparisons. Moreover, the value of an innovation is difficult to assess, particularly when the innovation is embodied in consumer products.

In spite of considerable public concern about industrial innovations in Austria there exist only four databases (of poor quality) which allow for quantitative innovation research. This was a reason to engage in the collection of literature-based innovation output data in Austria. This chapter reports on our experience from a first round of data collection.

The need to improve economic performance through innovation is recognised in Ireland as a national priority. The Department of Education (1992) has proposed making ‘enterprise and technology studies... mandatory for all second-level students at both junior and senior cycle’ and a Department of Industry report (Sectoral Development Committee, 1991, p. 14) states that ‘a supportive R&D infrastructure... geared to and capable of generating an innovative capacity’ is an imperative for Irish industry.

This chapter discusses a series of research projects at the Technology Policy Unit that have employed document-derived innovation output indicators. The projects addressed a variety of innovation policy issues, including the consequences of innovation for employment and skills and the successful management of innovation. All of the projects prompted a need for direct and discrete measures of innovation output for both analytic and policy purposes.

As indicated in the introduction to this book, almost in parallel with the collection of innovation output indicators from the trade literature, efforts have been undertaken in order to develop an internationally harmonised questionnaire for postal innovation surveys in the OECD area. Whereas the former concentrated on output measurement, the harmonised questionnaire is intended to cover a wider range of potentially useful information about the innovation process.

As the European unification process proceeds, there is an increasing need for the collection of internationally comparable innovation data. Unfortunately, in the past there were too many isolated attempts at developing new innovation indicators. This holds in particular for innovation indicators in postal surveys. Due to a lack of communication and coordination, people did not learn from each other’s mistakes. Moreover, in spite of remarkable conceptual similarities, definitions and standards were often just sufficiently different to prevent straightforward comparisons of results between countries. Fortunately, following a recent test of an international draft questionnaire for innovation surveys (see Chapter 7), there is now a good prospect that a harmonised international ‘core’ questionnaire for innovation surveys will soon be used in large-scale surveys.