La evolución de la industria discográfica: un análisis de los procesos de innovación en Europa

454 p.

Influence activity and the organization of research and development

The organizational design of research and development conditions theincentives of the researchers of the research project. In particular,the organizational form determines the allocation of effort of theresearcher between time spent on research and time spent lobbying management. Researchers prefer to spend their time on research. However,the researchers only get utility from performing research if theproject is approved for its full duration. Spending time lobbyingmanagement for the continuation of the researcher s project increasesthe probability that the management observes a favorable signal aboutthe project. Organizing a research joint venture increases theflexibility of the organizational form with respect to the continuationdecision. For low correlation between the signals of the partners aboutthe expected profitability of the project, we find that the organizationof a research joint venture reduces influence activity by the researchersand increases expected profits of the partners. For high correlationbetween the signals, internal research projects lower influence activityby the researchers. We try to relate the correlation of the partnerssignals to the characteristics of basic research versus more appliedresearch projects, and find that the model is consistent with theobservation that research joint ventures seem involved in more basicresearch projects compared to internal R&D departments, whichconcentrate on more applied research.

On the fundamentals of research and development (R&D) spillovers in competitive markets

Rivals may voluntarily share Research and Development (R&D) results even in the absence of any binding agreements or collusion. In a model where rival firms engage in non-cooperative independent R&D process, we used optimization and game theory analysis to study the equilibrium strategy of the firms. Our work showed that, while minimal spillover is always equilibrium, there may be another equilibrium where firms may reciprocally choose high, sometimes perfect, spillover rates. The incentive for sharing R&D output is based on firms' expectations of learning from their rivals' R&D progress in the future. This leads to strategic complementarities between the firms' choices of spillover rates and thus policy implication follows. ^ Public research agencies can contribute more to social welfare by providing research as public goods. In a non-cooperative public-private research relationship where parallel R&D is conducted, by making its R&D results accessible, the public research agency can stimulate private spillovers, even if there exists rivalry among the private firms who can benefit from such spillovers. ^

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.