Indicador “Despesa Privada em I&D” , Lisboa, 30-11-2018:

Indicador “Despesa Privada em I&D”: Como quadruplicar o investimento em I&D das empresas

Paulo Madeira (ANI, estudante de doutoramento PDAT)

Porque é que a onda longa é tão longa?, Lisboa, 30-11-2018:

Porque é que a onda longa é tão longa?

Francisco Louçã - Professor Catedrático no ISEG-UL

9th Winter School on Technology Assessment

9th Winter School on Technology Assessment

9ª Escola de Inverno em Avaliação de Tecnologia

Date: November 30st, 2018

Venue: Edifício B1 Sala 0.08, Campus Av. Berna, FCSH-UNL

Evidence in innovation decisions, Campus de Caparica, 09-12-2015:

The construction of evidence in innovation decisions

Nuno Filipe França Gouveia Boavida

5th Winter School on Technology Assessment

5th Winter School on Technology Assessment

Pre-Winter School conference

Ventseslav Kozarev (Univ. Sofia, Bulgaria, estudante de doutoramento): "Social responsibilities and technological innovation: possible applications for technology assessment"

Date: December 5th, 2014

Venue: DCSA Seminar Room, building VII 1st floor, 10h-12h

Winter School

Date: December 10th, 2014

Agnė Paliokaitė

Managing Director/Visionary Analytics

Agnė is in charge of the policy research and evaluation in the fields of innovation and R&D policies and governance dynamics. She is a science, technology and innovation expert with more than 13 years of experience in the evaluation, impact assessments and feasibility studies as well as applied social sciences. She is also an experienced adviser on national STI indicators and establishment of the monitoring systems, and provides research and technical assistance for institutional capacity building.

Boavida, N.  2011.  How composite indicators of innovation can influence technology policy decision? , Monte de Caparica: IET Abstract

This working paper is based on the development of the Thesis Plan presented for the Units Project II and Project III at the 1st Winter School of PhD programme on Technology Assessment at FCT/UNL. It focuses the methodology analysis and includes empirical information elements, in order to understand how composite indicators of innovation can influence technology policy decisions. In order to test the hypotheses raised in the Thesis Plan, two separate phases were designed. On the first part, the work tests hypotheses 1 and partially 2, identifying the quality, depth and limitations of three famous complex indicator-based systems, namely the Science, Technology and Industry Scoreboard, the European Innovation Scoreboard 2008 and Innovation Union Scoreboard 2010. On the second phase, the remaining hypotheses are tested adding media databases analysis, which will provide complementary information to a set of interviews to policy makers, in order to understand the role of the composite indicators on technology decisions.