Technology policy

Résumé

There are several approaches to defining the substance and scope of technology policy. According to the American scientist and policy advisor Lewis M. Branscomb, technology policy concerns the "public means for nurturing those capabilities and optimizing their applications in the service of national goals and interests". Branscomb defines technology in this context as "the aggregation of capabilities, facilities, skills, knowledge, and organization required to successfully create a useful service or product". Other scholars differentiate between technology policy and science policy, suggesting that the former is about "the support, enhancement and development of technology", while the latter focuses on "the development of science and the training of scientists". Rigas Arvanitis, at the Institut de recherche pour le développement in France, suggests that "science and technology policy covers all the public sector measures designed for the creation, fundin

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https://en.wikipedia.org/wiki/Technology_policy

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This course addresses the issue of designing innovation strategies and technology policies to support transitions towards sustainable development goals.

The course offers an introduction to technology policy and regulation with a particular focus on the infrastructures. In these infrastructures technology policy and regulation basically translates into sectoral (e.g., energy, transport, water) and cross-sectoral approaches (information society).

This course examines key technological developments and challenges from an ethical and policy perspective. The primary aim of this course is to get students to think critically about the ethical-social dimensions of technology, taking into account both normative and applied ethics questions.

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A policy insight into the R&D-patent relationship

Gaétan Jean A de Rassenfosse

Contrary to an accepted wisdom, this paper shows that cross-country variations in the number of patents per researcher do not only reflect differences in the propensity to patent but also signals differences in research productivity. We put forward and test an empirical model that formally accounts for the productivity and the propensity component of the R&D-patent relationship. The two components play an important role, as witnessed by the impact of several policies, including education, intellectual property and science and technology policies. Indicators based on domestic priority filings reflect research efforts and are primarily affected by varying propensities to patent. In contrast, international filings, especially triadic patents, rather capture variations in research productivity. © 2008 Elsevier B.V. All rights reserved.

2009

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The urgency indices which are used to schedule multiclass production systems are calculated for production flows characterized by M/G/1 dynamics. The calculation of the indices is based on a myopic policy for which the time look-ahead distribution is chosen to be a Gamma distribution with its first two moments matching either those of the waiting time or the busy period distributions of the M/G/1 queue. For a single item, the priority index can also be used to determine the position of an optimal hedging stocks. It is shown that only the priority indices obtained from waiting time look-ahead produce consistent results with the optimal values of the hedging obtained in solving directly the optimal control problem for a markovian dynamics. Additionally, consistency is also guaranteed when the diffusive approximation is used to discuss the heavy traffic regimes. © 2001 Elsevier Science B.V. All rights reserved.

2001

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Information structure and coordination in technology policy: a theoretical model and two case studies

Dominique Foray

1996

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