Measurement of R&D and Innovation

R&D Statistics, Patent Statistics, and Innovation Surveys.

It is a manual that defines R&D and provides rules and tips about how R&D statistics should be collected.

The Oslo Manual

It counts the number of patents and analyses the citations to patents.

1) Does your firm have a patent (yes/no)? This is the easiest question that could be asked. It is not detailed, and firms can easily answer it. The researcher can make a difference between patent applications and granted patents.

2) How many patents does your firm have? Here the researcher can gather count data, which basically reflects the number of patents granted. Again, one could differ between patent applications and granted patents.

3) The information on other types of IPR could be collected as well.

1) we do not know whether a patent is commercialised

2) sometimes patents inhibit innovation in an area

3) when patents and number of patents are compared, it is assumed that quality is the same, but it may differ

Any survey that attempts to measure innovation following the definitions and methodology of the Oslo Manual.

A typical innovation survey collects information that could be used as control variables (the size of the firm, the location of firm, export markets, R&D expenditure, R&D personnel, applications to patents, licensing IPR, etc.), data on innovation-active firms (whether the firm had product, process, marketing, or organisational innovations, the knowledge sources of innovation, how innovation is financed, etc.), and factors that inhibit innovation or that led firms to stop innovation activities.

40%

He/she can either obtain micro clustered data from Eurostat for a selected number of European countries or consult the Statistics Office of the country that collects the data.

Treating text as data, using AI to measure innovation, treating innovation as a latent construct.

To create a new measure of technological innovation using patent text analysis, which can be consistently applied across time and space.

Innovation activity is very much cyclical, and there are clusters of breakthrough inventions in certain times.

This research introduces a novel method for creating web-based innovation indicators. By leveraging readily available web data and machine learning, the authors develop a system capable of identifying product innovator firms at a large scale.

In this case, we do not observe innovation. We accept that innovation cannot be measured correctly. So rather than trying to collect data on innovation directly, why not use other available data that are correlated with innovation? There are various attempts in this direction, and as available data sources (especially at the firm and regional level) increase, the efforts to measure innovation as a latent construct increase. For instance, to determine the quality of the patent after it has been granted, or even before it has been granted, researchers use a wide set of indicators to infer patent quality, which informs patent value. Such measurement of innovation is usually used in tandem with conventional measures.

R&D and innovation statistics are in general used for three purposes. First, academic researchers have been developing and using conventional measures for a long time and even experimented on non-conventional measurement techniques. Part of this research using conventional measures informs policy. Thus, secondly, researchers and the state officially use these statistics to come up with evidencebased policy. Finally, firms are using especially non-conventional measures to devise technology and innovation strategies

Framework conditions: 8 indicators that measure the environment to do innovation, such as human resources, the attractiveness of the research system, and digitalisation.

Investments: 8 indicators that measure investment and funding for innovation, such as firm investments, government R&D grants, and investment in skilled personnel.

Innovation: 8 indicators that measure the innovation process, such as intellectual assets, product and process innovators, and linkages that produce innovation.

Impacts of innovation: 8 indicators on sales of innovation, employment effects, and environmental effects.

8 indicators that measure the environment to do innovation, such as human resources, the attractiveness of the research system, and digitalisation

8 indicators that measure investment and funding for innovation, such as firm investments, government R&D grants, and investment in skilled personnel.

8 indicators on sales of innovation, employment effects, and environmental effects.