Innovation in Innovation Indicators? The use of sensitivity analysis to analyse the coherence of composite indices and dominant policy discourses

Composite Indicators are ever more diffused tools that not only measure phenomena such as innovation, but also shape discussions, policy design and implementation. The synthesis that emerges from the debate about their strengths and weaknesses recognized their intrinsic normative nature, and underlines the need for exercising conceptual and statistical clarity and transparency, and responsible use. In this paper, we consider composite indicator rankings as “fingerprints” of the values, ideas and priorities shared by the stakeholders involved in their development. Thus, we expect composite innovation indicators not only to reflect policy priorities through the underlying indicators that are the most important drivers of rankings, but also to be able to observe policy priority changes reflected in changes in the key drivers of ranks. We identify 3 key innovation policy priorities over the past two decades. By applying sensitivity analysis, we identify the statistically most important component indicators of two of the most widely used composite indices, the Summary Innovation Index and the Global Innovation Index. Examining these indicators, we find that neither of the two indices followed shifts in the innovation policy discourse from a focus on R&D to a focus on job creation. This discrepancy calls for both a better measurement of Schumpeterian Mark I entrepreneurship and firm scale-up activity at the country level, and the need for better communicating non-correlating measures of innovation

Innovation in Innovation Indicators? The use of sensitivity analysis to analyse the coherence of composite indices and dominant policy discourses

Composite Indicators are ever more diffused tools that not only measure phenomena such as innovation, but also shape discussions, policy design and implementation. The synthesis that emerges from the debate about their strengths and weaknesses recognized their intrinsic normative nature, and underlines the need for exercising conceptual and statistical clarity and transparency, and responsible use. In this paper, we consider composite indicator rankings as “fingerprints” of the values, ideas and priorities shared by the stakeholders involved in their development. Thus, we expect composite innovation indicators not only to reflect policy priorities through the underlying indicators that are the most important drivers of rankings, but also to be able to observe policy priority changes reflected in changes in the key drivers of ranks. We identify 3 key innovation policy priorities over the past two decades. By applying sensitivity analysis, we identify the statistically most important component indicators of two of the most widely used composite indices, the Summary Innovation Index and the Global Innovation Index. Examining these indicators, we find that neither of the two indices followed shifts in the innovation policy discourse from a focus on R&D to a focus on job creation. This discrepancy calls for both a better measurement of Schumpeterian Mark I entrepreneurship and firm scale-up activity at the country level, and the need for better communicating non-correlating measures of innovation

The impact of artificial intelligence on labor productivity

evidence indicates an upsurge in artificial intelligence and robotics (AI) patenting activities in the latest years, suggesting that solutions based on AI technologies might have started to exert an effect on the economy. We test this hypothesis using a worldwide sample of 5257 companies having filed at least a patent related to the field of AI between 2000 and 2016

Intumescent material fire stop device

An intumescent material fire stop device, comprising a support body shaped so as to take a collar-like shape around an axis and to define an opening intended to house a pipe, an expandable element, made up of at least one intumescent material and positioned in the support body, and one or more foldable fin joined to the support body by at least one respective hinge portion along a radially inner peripheral edge of said opening. Due to the expansion of the expandable element, the fins are movable between an initial position, in which the fins are substantially parallel to each other and not intercepting said opening, to a closing position, in which the fins converge towards the axis to close at least partially the opening. Advantageously the expandable element is made of at least one first intumescent material, expandable at temperatures equal to or greater than a first activation temperature T1, and at least one second intumescent material, expandable at temperatures equal to or greater than a second activation temperature T2 higher than said first activation temperature T1. The first intumescent material and the second intumescent material are axially staggered

Open for growth? Evidence on EU countries and sectors

The Open Innovation (OI) concept has pervaded the academic and policy debate due to its potential to further stimulate the circulation of knowledge between business partners and institutions and, consequently, to increase their innovation potential. This paper studies the relationships between OI and innovation and economic returns at the \u2018aggregate\u2019 level, i.e. at the country and industry levels. It exploits three waves of the Community Innovation Survey to conduct an empirical analysis on sectoral data for 16 EU countries. Results confirm the role of OI in stimulating \u2013 even at the aggregate level \u2013 innovation, with returns increasing at diminishing rates. OI also has an indirect impact on value added by strengthening the positive effect exerted on aggregate economic performance by R&D expenditure. The mutual reinforcement of R&D intensity and collaborations between companies and business partners is coherent with the principles underlying \u2018smart specialization\u2019 policies of the European Union

AI technologies and employment: micro evidence from the supply side

In this work we investigate the possible job-creation impact of artificial intelligence (AI) technologies, focusing on the supply side, where the development of these technologies can be conceived as product innovations in upstream sectors. The empirical analysis is based on a worldwide longitudinal sample (obtained by merging the EPO PATSTAT and BvD-ORBIS databases) of more than 3,500 front-runner companies that patented AI-related inventions over the period 2000-2016. Based on system GMM estimates of dynamic panel models, our results show a positive and significant impact of AI patent families on employment, supporting the labour-friendly nature of AI product innovation

Openness and innovativeness across the value chain. Evidence on EU countries and industries

The Open Innovation concept has pervaded the academic and policy debate, due to its potential to further stimulate the circulation of knowledge across business partners and institutions and, consequently, to increase their innovation potential. The contribution of this paper is to unveil the economic returns associated to such a model, to answer the main question whether the productivity growth slowdown observed in the EU in recent years could be overcome through a more open and dynamic innovation environment. An empirical analysis conducted on sectoral data for 16 EU countries is provided, exploiting three waves of the Community Innovation Survey. Results confirm the role of Open Innovation in stimulating \u2013 even at the aggregate level \u2013 innovation, and, to a limited extent, to economic returns. However, when testing for the association between Open Innovation and economic growth, no robust effect emerges

AI technologies and employment: micro evidence from the supply side

In this work we investigate the possible job-creation impact of artificial intelligence (AI) technologies, focusing on the supply side, where the development of these technologies can be conceived as product innovations in upstream sectors. The empirical analysis is based on a worldwide longitudinal sample (obtained by merging the EPO PATSTAT and BvD-ORBIS databases) of more than 3,500 front-runner companies that patented AI-related inventions over the period 2000-2016. Based on system GMM estimates of dynamic panel models, our results show a positive and significant impact of AI patent families on employment, supporting the labour-friendly nature of AI product innovation