O objetivo desta pesquisa é compreender a dinâmica de produção de conhecimento das infraestruturas de pesquisa brasileiras. O estudo utilizou uma amostra de 1.756 infraestruturas nas quais estão alocados 7.714 pesquisadores. Realizou-se uma Análise de Correspondência Múltipla seguida pela Análise de Cluster Hierárquico, por meio das quais foram identificados cinco clusters. Em linhas gerais, as diferenças se concentram na composição do capital humano, representada pela participação dos pesquisadores permanentes, dos estudantes de pós-graduação e dos técnicos, e no escopo das atividades realizadas pelas infraestruturas. Os clusters 1 e 2 caracterizam-se por possuir uma estrutura de capital humano menor do que a dos clusters 3, 4 e 5 e contemplam, proporcionalmente, um número de doutores menor no quadro de pesquisadores permanentes. Já nas infraestruturas dos clusters 3, 4 e 5 a participação dos dos alunos de pós-graduação constitui a principal composição do capital humano, refletindo assim em maior escala. Elas também realizam múltiplas atividades e principalmente nos clusters 4 e 5 as atividades de ciência e tecnologia são realizadas com maior intensidade. Apurou-se que, condicionado ao capital e ao trabalho, as infraestruturas dos clusters 3 e 4 têm uma produção científica 769% e 484% superior ao cluster 1. E embora as do cluster 1 tenham registrado uma produtividade tecnológica maior, as infraestruturas do cluster 4 estão entre as que apresentam os maiores níveis de depósitos de pedidos de patente. Além disso, foi constatado que a produção científica não apenas tornaria as infraestruturas mais predispostas a patentear, como impactaria em uma produtividade tecnológica maior. Também concluiu-se que a produtividade científica é determinada pelo capital físico e pelo trabalho, enquanto a produtividade tecnológica é determinada apenas pelo trabalho. Entretanto, enquanto os pesquisadores permanentes e não permanentes impactam positivamente na produtividade científica, a produtividade tecnológica é determinada apenas pelos pesquisadores permanentes. Estas evidências sugerem que a estrutura de pós-graduação brasileira está mais voltada para a produção científica. Em seguida, os inventores alocados nas infraestruturas foram mapeados, a partir dos quais foram produzidas duas redes de colaboração: uma que incluiu os seus laços de coinvenção e outra que incluiu os seus laços de coautoria. A partir de um modelo multinomial logit com resultados ordenados, foi possível analisar a associação entre clusters e a importância que os inventores possuem em ambas as redes. Os inventores pertencentes às infraestruturas dos clusters 3 e 4 possuem uma probabilidade maior de ocuparem posições centrais tanto na rede de colaboração científica quanto tecnológica Assim, as infraestruturas que combinam um capital humano constituído por uma participação expressiva de pesquisadores não permanentes, uma equipe de pesquisadores permanentes com predominância de doutores ainda que pouco representativa na estrutura do capital humano e engajadas na realização das atividades de ensino, pesquisa e desenvolvimento tecnológico estariam associadas a maior capacidade de articulação entre ciência e tecnologia. / The objective of this research is to understand the knowledge production dynamics of Brazilian research infrastructures. The study used a sample of 1,756 infrastructures in which 7,714 researchers are allocated. A Multiple Correspondence Analysis was carried out followed by the Hierarchical Cluster Analysis, through which five clusters were identified. In general terms, the differences are concentrated in the composition of human capital, represented by the participation of permanent researchers, postgraduate students and technicians, and in the scope of activities performed by the infrastructures. Clusters 1 and 2 are characterized by having a smaller human capital structure than clusters 3, 4 and 5 and proportionally have a smaller number of doctors in the permanent researchers framework. In the infrastructures of clusters 3, 4 and 5, the participation of postgraduate students constitutes the main composition of human capital, reflecting on a larger scale. They also perform multiple activities and especially in clusters 4 and 5 activities related to science and technology are performed with greater intensity. It was found that, based on capital and labor, the infrastructures of clusters 3 and 4 have a scientific production by 769% and 484% higher than cluster 1. And although cluster 1 has registered a higher technological productivity, the infrastructures of cluster 4 are among those with the highest levels of patent filing. In addition, it was found that scientific production would not only make the infrastructures more predisposed to patent, but would also impact on higher technological productivity. It has also been concluded that scientific productivity is determined by capital and labor, while technological productivity is determined only by labor. However, while permanent and non-permanent researchers positively impact scientific productivity, technological productivity is determined only by permanent researchers. These evidences suggest that the Brazilian postgraduate structure is more focused on scientific production. Next, I mapped the inventors, from which two collaborative networks were produced: one that included their co-invention links and another that included their co-authorship links. From a multinomial logit model with ordered results, it was possible to analyze the association between the clusters and the importance that the inventors have in both networks. The inventors belonging to the infrastructures of clusters 3 and 4 are more likely to occupy central positions in both scientific and technological collaboration networks. Thus, infrastructures that combine human capital consisting of an expressive participation of non-permanent researchers, a team of permanent researchers with predominance of doctors although little representative in the human capital structure and engaged in the activities of teaching, research and technological development, would be associated with greater capacity for articulation between science and technology.

Diss. Univ. Frankfurt am Main, 2006.

Zugl.: Diss. Univ. Freiburg, 2005.

Zugl.: Diss. Univ. Duisburg-Essen, 2006.

O objetivo desta pesquisa é compreender a dinâmica de produção de conhecimento das infraestruturas de pesquisa brasileiras. O estudo utilizou uma amostra de 1.756 infraestruturas nas quais estão alocados 7.714 pesquisadores. Realizou-se uma Análise de Correspondência Múltipla seguida pela Análise de Cluster Hierárquico, por meio das quais foram identificados cinco clusters. Em linhas gerais, as diferenças se concentram na composição do capital humano, representada pela participação dos pesquisadores permanentes, dos estudantes de pós-graduação e dos técnicos, e no escopo das atividades realizadas pelas infraestruturas. Os clusters 1 e 2 caracterizam-se por possuir uma estrutura de capital humano menor do que a dos clusters 3, 4 e 5 e contemplam, proporcionalmente, um número de doutores menor no quadro de pesquisadores permanentes. Já nas infraestruturas dos clusters 3, 4 e 5 a participação dos dos alunos de pós-graduação constitui a principal composição do capital humano, refletindo assim em maior escala. Elas também realizam múltiplas atividades e principalmente nos clusters 4 e 5 as atividades de ciência e tecnologia são realizadas com maior intensidade. Apurou-se que, condicionado ao capital e ao trabalho, as infraestruturas dos clusters 3 e 4 têm uma produção científica 769% e 484% superior ao cluster 1. E embora as do cluster 1 tenham registrado uma produtividade tecnológica maior, as infraestruturas do cluster 4 estão entre as que apresentam os maiores níveis de depósitos de pedidos de patente. Além disso, foi constatado que a produção científica não apenas tornaria as infraestruturas mais predispostas a patentear, como impactaria em uma produtividade tecnológica maior. Também concluiu-se que a produtividade científica é determinada pelo capital físico e pelo trabalho, enquanto a produtividade tecnológica é determinada apenas pelo trabalho. Entretanto, enquanto os pesquisadores permanentes e não permanentes impactam positivamente na produtividade científica, a produtividade tecnológica é determinada apenas pelos pesquisadores permanentes. Estas evidências sugerem que a estrutura de pós-graduação brasileira está mais voltada para a produção científica. Em seguida, os inventores alocados nas infraestruturas foram mapeados, a partir dos quais foram produzidas duas redes de colaboração: uma que incluiu os seus laços de coinvenção e outra que incluiu os seus laços de coautoria. A partir de um modelo multinomial logit com resultados ordenados, foi possível analisar a associação entre clusters e a importância que os inventores possuem em ambas as redes. Os inventores pertencentes às infraestruturas dos clusters 3 e 4 possuem uma probabilidade maior de ocuparem posições centrais tanto na rede de colaboração científica quanto tecnológica Assim, as infraestruturas que combinam um capital humano constituído por uma participação expressiva de pesquisadores não permanentes, uma equipe de pesquisadores permanentes com predominância de doutores ainda que pouco representativa na estrutura do capital humano e engajadas na realização das atividades de ensino, pesquisa e desenvolvimento tecnológico estariam associadas a maior capacidade de articulação entre ciência e tecnologia. / The objective of this research is to understand the knowledge production dynamics of Brazilian research infrastructures. The study used a sample of 1,756 infrastructures in which 7,714 researchers are allocated. A Multiple Correspondence Analysis was carried out followed by the Hierarchical Cluster Analysis, through which five clusters were identified. In general terms, the differences are concentrated in the composition of human capital, represented by the participation of permanent researchers, postgraduate students and technicians, and in the scope of activities performed by the infrastructures. Clusters 1 and 2 are characterized by having a smaller human capital structure than clusters 3, 4 and 5 and proportionally have a smaller number of doctors in the permanent researchers framework. In the infrastructures of clusters 3, 4 and 5, the participation of postgraduate students constitutes the main composition of human capital, reflecting on a larger scale. They also perform multiple activities and especially in clusters 4 and 5 activities related to science and technology are performed with greater intensity. It was found that, based on capital and labor, the infrastructures of clusters 3 and 4 have a scientific production by 769% and 484% higher than cluster 1. And although cluster 1 has registered a higher technological productivity, the infrastructures of cluster 4 are among those with the highest levels of patent filing. In addition, it was found that scientific production would not only make the infrastructures more predisposed to patent, but would also impact on higher technological productivity. It has also been concluded that scientific productivity is determined by capital and labor, while technological productivity is determined only by labor. However, while permanent and non-permanent researchers positively impact scientific productivity, technological productivity is determined only by permanent researchers. These evidences suggest that the Brazilian postgraduate structure is more focused on scientific production. Next, I mapped the inventors, from which two collaborative networks were produced: one that included their co-invention links and another that included their co-authorship links. From a multinomial logit model with ordered results, it was possible to analyze the association between the clusters and the importance that the inventors have in both networks. The inventors belonging to the infrastructures of clusters 3 and 4 are more likely to occupy central positions in both scientific and technological collaboration networks. Thus, infrastructures that combine human capital consisting of an expressive participation of non-permanent researchers, a team of permanent researchers with predominance of doctors although little representative in the human capital structure and engaged in the activities of teaching, research and technological development, would be associated with greater capacity for articulation between science and technology.

No description available.

Non-economic factors like culture and politics, as well as the socio-economic background, matter significantly in directing economic development endeavours towards social wellbeing. Therefore, the current narrow definition of economic development must be extended to include overall wellbeing. As one of the primary forms of physical capital constituting a regional economy, transport investments have played a significant role in development plans. Given that accessibility to social infrastructure is a basic need, certain levels of infrastructure are essential. How these investments have an impact on different groups of individuals has kept many scholars busy for a long time. However, the economic spillover effects of these investments into female labour markets have remained largely unexplored. Situating the implications of development initiatives, including transport investments, for female labour markets in social and cultural contexts requires an integrated view of the regional economy. Although economic geography and existing development theories provide extensive conceptual models to elucidate the links between transport, labour markets and culture, the methodological implications are obscure; hence, the empirical evidence remains weak. This thesis explores the economic and non-economic dynamics of regional economies to clarify the links between transport infrastructure, labour markets, and social and cultural conditions. In particular, the association between female labour forces and development efforts, in the form of transport infrastructure development, is conceptually and empirically examined. This thesis conducts a case study on Turkey. With the extensive infrastructure investment that has been made since 2002 and the extremely low rates of female labour force participation (around 25%), compared to EU-15 and OECD averages of around 65%, Turkey serves as an illuminating case. Theoretically, the study shows that the focus of transport economics on the economic growth effect of investments is not consistent with current efforts to extend economic development objectives: transport research requires a broader view to assess its development implications. The study demonstrates how the interactions between the economic, physical, political, cultural and socio-economic attributes of regions significantly affect how individuals benefit from the investments. The overarching policy implications of the study are useful for regional development policy with a gender focus: complementary policy interventions in human capital development and the consideration of social and cultural attitudes should strengthen the positive impacts of physical investments on female labour markets.

Zugl.: Diss. University Duisburg-Essen, 2007.

Cette thèse rassemble principalement des contributions en économie de la science à laquelle les deux premières parties sont consacrées. La première teste l'importance des choix méthodologiques dans la mesure de la production scientifique et étudie les canaux de diffusion de la connaissance. La deuxième s'intéresse aux déterminants individuels et locaux de la productivité des chercheurs et au différentiel de promotion entre hommes et femmes sur le marché du travail académique. Sont établis les résultats suivants : les choix méthodologiques dans la mesure de la production scientifique n'affectent que très peu les classements des institutions de recherche. Les citations et les poids associés à la qualité des journaux mesurent globalement la même productivité de la recherche. La localisation des chercheurs a un impact sur leur productivité dans la mesure où certaines universités génèrent davantage d'externalités que d'autres. Ces externalités sont plus importantes là où les chercheurs sont homogènes en terme de performances, où la diversité thématique est grande, et dans une moindre mesure dans les grands centres de recherche, lorsqu'il y a plus de femmes, de chercheurs âgés, de stars et là où les chercheurs sont connectés à des co-auteurs à l'étranger. Si les femmes sont moins souvent Professeur des Universités (par opposition à Maître de Conférences) que les hommes, ce n'est ni parce qu'elles sont discriminées dans le processus de promotion, ni que le coût de promotion (mobilité) est plus important pour elles, ni qu'elles ont des préférences différentes concernant le salaire et le prestige des institutions dans lesquelles elles travaillent. / The core of this thesis lies in the field of economics of science to which the two first parts are devoted. The first part questions the impact of methodological choices in the measurement of research productivity and studies the channels of knowledge diffusion. The second part studies the impact on individual publication records of both individual and departments' characteristics and analyse the gender gap in occupations on the academic labour market. The main results are the following: methodological choices in the measurement of research productivity do not impact the estimated hierarchy of research institutions. Citations and journal quality weights measure the same dimension of publication productivity. Location matters in the academic research activity: some departments generate more externalities than others. Externalities are higher where academics are homogeneous in terms of publication performance and have diverse research fields, and, to a lower extent, if the department is large, with more women, older academics, stars and co-authors connection to foreign departments. If women are less likely to be full Professor (with respect to Assistant Professor) than men, this is neither because they are discriminated against in the promotion process, neither because the promotion cost (mobility) is higher for them, nor because they have different preferences for salaries versus department prestige. A possible, but not tested, explanation is that women self-select themselves by participating less in or exerting lower effort during the promotion process.

Cette thèse a pour objectif d’étudier la façon dont les économistes ont théorisé la relation entre science, technologie et croissance économique des années cinquante à aujourd’hui. Nous identifions deux approches des liens entre science, technologie et croissance : une approche « néoclassique » et une approche « évolutionniste ». L’approche « néoclassique » considère les progrès scientifiques et technologiques comme exogènes aux processus économiques et analyse les processus de croissance comme étant soumis à des rendements constants. L’approche « évolutionniste » défend quant à elle une représentation interactionniste des liens entre science et technologie, considère les progrès technologiques et scientifiques comme étant endogènes aux processus économiques et analyse les processus de croissance comme étant soumis à des rendements croissants. Nous analysons l’émergence de ces deux approches dans les années cinquante et soixante et expliquons leur opposition avec une domination de l’approche « néoclassique » jusque dans les années quatre-vingt (Partie 1). Nous montrons ensuite que l’approche « évolutionniste » devient dominante à partir des années quatre-vingt (Partie 2). / The aim of this thesis is to examine the way economists theorized the links between science, technology, and economic growth in the post-war era. We identify two approaches of the links between science, technology, and economic growth : a “neoclassical” approach and an “evolutionary” approach. The “neoclassical” approach considers scientific and technological progress as exogenous to economic processes and makes the hypothesis of constant returns to scale. The “evolutionary” approach defends an interactive representation of the links between science and technology, considers scientific and technological progress as endogenous to economic processes, and makes the hypothesis of increasing returns to scale. We study the development of the two approaches in the fifties and sixties, and explain their opposition and the dominance of the “neoclassical” approach up to the eighties (Part 1). We then show that the “evolutionary” approach has been the most influential since the eighties (Part 2).