Wp.Priority Setting, Paris 29 30 Oct. 07

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This document discusses issues related to priority setting in science and technology. It defines priority setting as the deliberate selection of certain activities, actors, or policies over others to impact resource allocation. Evaluation is defined as the systematic assessment of the rationale, implementation, and impact of policy interventions. The document outlines different dimensions of priority setting processes, paradigms, actors involved, and means used. It also discusses the role and limitations of evaluations in informing priority setting decisions.

Technology Education

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Macro and Meso estimates of Return on R&D Source: Godin and Doré

Meso/Micro level: Social Rates of individual technologies Source: LINK (1999)

Mirco level: ‚Stylized results‘ from short-term ex-post CBA for individual projects .. clearly these differences are a guide for public investment ? Source: Bessette, 2003

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Transformations linked to disruptive events are causing a shift in Future-oriented Technology Analysis (FTA) activities from individual large-scale foresight actions to smaller in-house exercises and capacity-building. The reasons are manifold relating to the need for an even tighter embedding of FTA in policy-making in a fast-changing, complex environment as well as to internal drivers for novel forms of future intelligence to support coordinated and coherent decisions within and across organisations. The paper identifies three ideal types; external FTA services, the institutionalisation of FTA, and FTA networks, whilst recognising that in practice these types are complementary. In empirical terms this requires further investigation, in order to understand how different combinations of activities in effect operate in their respective decision-making context. It is important to improve our understanding of how far institutionalised FTA can form part of the solution for building capacity to handle disruptions. Many sorts of combinations of elements from different organisational models are needed to enable learning, experimentation and capability development appropriate for the wider decision making context in which FTA is embedded. This paper explores the extent to which FTA can provide enhanced support to decision-making through customised organisational models and corresponding capability thus enabling them to anticipate and address disruptive change and associated challenges.

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The management of cluster A1 carried out a so-called impact analysis in co-operation with the Institute for Innovation and Technology (iit) in April/May 2012. The objective of the investigations was to find out in which fields and to which extent the players of cluster A had particularly profited from the networking and in which fields the members’ requirements, especially those of the enterprises, could eventually not have been met. The results of the study clearly show that the enterprises in cluster A have generally been able to benefit well or even very well from the net-working activities. Equally important is the fact that the surveyed enterprises had achieved excellent effects specifically in those fields that had been considered particularly important for a large number of cluster participants. This fact illustrates that the management of cluster A had predominantly focused its activities on the fields of high priority and has been able to achieve very positive effects. In the context of limited resources available to the cluster management organisation, this finding is of high relevance. The performance of the enterprises involved in cluster A can be described as good. At least half of the network’s players range above the general industry average regarding typical indicators like turnover or productivity. The impact analysis shows that public investments generally result in monetary benefits for the companies involved in a cluster initiative. The monetary effect (output) hereby has turned out to be larger than the public sector invest-ments (input) made over the same period of time. The output/input leverage amounts to 2.3. Thus, each euro invested to the cluster by public authorities generates a monetary benefit of EUR 2.3 which is an encouraging result. The overall analysis revealed that the sum of monetary effects had been larger than the total number of investments made by the public and private sector (the output-input-rate amounts to 1.3). This result can in fact be interpreted as consolidated legitimization to public investments in recent years.

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