981 resultados para innovation models
Resumo:
There is a major concern in economic literature about innovation, which is the interaction between internal and external factors.. In this paper those activities are hypothesized as being determined by some territorial characteristics like labour skills, technological infrastructure, educational facilities, agglomeration economies and industrial structure. This assumption allows understanding why those innovative activities are not spread across space and are located into specific areas. We use a detailed survey containing microdata for 497 SMEs located in Catalonia.
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Solving multi-stage oligopoly models by backward induction can easily become a com- plex task when rms are multi-product and demands are derived from a nested logit frame- work. This paper shows that under the assumption that within-segment rm shares are equal across segments, the analytical expression for equilibrium pro ts can be substantially simpli ed. The size of the error arising when this condition does not hold perfectly is also computed. Through numerical examples, it is shown that the error is rather small in general. Therefore, using this assumption allows to gain analytical tractability in a class of models that has been used to approach relevant policy questions, such as for example rm entry in an industry or the relation between competition and location. The simplifying approach proposed in this paper is aimed at helping improving these type of models for reaching more accurate recommendations.
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This article provides a theoretical and empirical analysis of a firm's optimal R&D strategy choice. In this paper a firm's R&D strategy is assumed to be endogenous and allowed to depend on both internal firms. characteristics and external factors. Firms choose between two strategies, either they engage in R&D or abstain from own R&D and imitate the outcomes of innovators. In the theoretical model this yields three types of equilibria in which either all firms innovate, some firms innovate and others imitate, or no firm innovates. Firms'equilibrium strategies crucially depend on external factors. We find that the efficiency of intellectual property rights protection positively affects firms'incentives to engage in R&D, while competitive pressure has a negative effect. In addition, smaller firms are found to be more likely to become imitators when the product is homogeneous and the level of spillovers is high. These results are supported by empirical evidence for German .rms from manufacturing and services sectors. Regarding social welfare our results indicate that strengthening intellectual property protection can have an ambiguous effect. In markets characterized by a high rate of innovation a reduction of intellectual property rights protection can discourage innovative performance substantially. However, a reduction of patent protection can also increase social welfare because it may induce imitation. This indicates that policy issues such as the optimal length and breadth of patent protection cannot be resolved without taking into account specific market and firm characteristics. Journal of Economic Literature Classification Numbers: C35, D43, L13, L22, O31. Keywords: Innovation; imitation; spillovers; product differentiation; market competition; intellectual property rights protection.
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This paper explores how absorptive capacity affects the innovative performance and productivity dynamics of Spanish firms. A firm’s efficiency levels are measured using two variables: the labour productivity and the Total Factor Productivity (TFP). The theoretical framework is based on the seminal contributions of Cohen and Levinthal (1989, 1990) regarding absorptive capacity; and the applied framework is based on the four-stage structural model proposed by Crépon, Duguet and Mairesse (1998) for setting the determinants of R&D, the effects of R&D activities on innovation outputs, and the impacts of innovation on firm productivity. The present study uses a twostage structural model. In the first stage, a probit estimation is used to investigate how the sources of R&D, the absorptive capacity and a vector of the firm’s individual features influence the firm’s likelihood of developing innovations in products or processes. In the second phase, a quantile regression is used to analyze the effect of R&D sources, absorptive capacity and firm characteristics on productivity. This method shows the elasticity of each exogenous variable on productivity according to the firms’ levels of efficiency, and thus allows us to distinguish between firms that are close to the technological frontier and those that are further away from it. We used extensive firm-level panel data from 5,575 firms for the 2004-2009 period. The results show that the internal absorptive capacity has a strong impact on the productivity of firms, whereas the role of external absorptive capacity differs according to nature of the each industry and according the distance of firms from the technological frontier. Key words: R&D sources, innovation strategies, absorptive capacity, technological distance, quantile regression.
Resumo:
This paper analyses whether a firm’s absorptive capacity and its distance from the technological frontier affect the choice between innovation and imitation in innovative Spanish firms. From an extensive survey of 5,575 firms during the 2004-2009 period, we found two significant results. With regard to the role of absorptive capacity, the empirical evidence shows that when innovative firms have difficulties in accessing external information and hire skilled workers, their innovative capacity is reduced. Meanwhile, with regard to distance from the technological frontier, the firms that reduce this gap manage to increase their innovative capacity at the expense of imitation. To summarise, when we studied firms’ absorptive capacity and their relative position to the technological frontier in tandem, we found that the two factors directly affected firms' ability to innovate or imitate. Key words: R&D sources, innovation and imitation strategies, absorptive capacity, technological frontier, ordered probit.
Resumo:
This paper analyzes the effect of firms’ innovation activities on their growth performance. In particular, we observe how important innovation is for high-growth firms (HGFs) for an extensive sample of Spanish manufacturing and services firms. The panel data used comprises diverse waves of Spanish CIS over the the period 2004-2008. First, a probit analysis determines whether innovation affects the probability of being a high-growth firm. And second, a quantile regression technique is applied to explore the determinants and characteristics of specific groups of firms (manufacturing versus service firms and high-tech versus low-tech firms). It is revealed that R&D plays a significant role in the probability of becoming a HGF. Investment in internal and external R&D per employee has a positive impact on firm growth (although internal R&D presents a significant impact in the last quantiles, external R&D is significant up to the median). Furthermore, we show evidence that there is a positive impact of employment (sales) growth on the sales (employment) growth. Keywords: high-growth firms, firm growth, innovation activity JEL Classifications: L11, L25, O30
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L’ictus és un dels reptes sanitaris més importants al nostre país ja que l’únic tractament disponible és l’administració de trombolítics durant les 4,5 primeres hores i menys d’un 10% dels pacients poden beneficiar-se’n. Publicacions anteriors han demostrat que el tractament de l’ictus amb estatines pot reduir l’extensió del teixit infartat i millorar la funció neurològica, per això proposem fer un estudi experimental usant un model d’isquèmia en rata, que evidenciï si el tractament combinat de Simvastatina i rt-PA incrementa el benefici obtingut únicament amb fàrmacs trombolítics i avaluï la seva seguretat quan s’administra durant la fase aguda (transformacions hemorràgiques i incidència d’infeccions).
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The lymphatic vascular system, the body's second vascular system present in vertebrates, has emerged in recent years as a crucial player in normal and pathological processes. It participates in the maintenance of normal tissue fluid balance, the immune functions of cellular and antigen trafficking and absorption of fatty acids and lipid-soluble vitamins in the gut. Recent scientific discoveries have highlighted the role of lymphatic system in a number of pathologic conditions, including lymphedema, inflammatory diseases, and tumor metastasis. Development of genetically modified animal models, identification of lymphatic endothelial specific markers and regulators coupled with technological advances such as high-resolution imaging and genome-wide approaches have been instrumental in understanding the major steps controlling growth and remodeling of lymphatic vessels. This review highlights the recent insights and developments in the field of lymphatic vascular biology.
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Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presenceonly evaluators to usual presence/absence measures. We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D-2) compare to presenceonly measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call "continuous Boyce index". All indices were implemented in the B10MAPPER software. We show that the presence-only evaluators are fairly correlated (p > 0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-toexpected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions.
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In this paper, we present a stochastic model for disability insurance contracts. The model is based on a discrete time non-homogeneous semi-Markov process (DTNHSMP) to which the backward recurrence time process is introduced. This permits a more exhaustive study of disability evolution and a more efficient approach to the duration problem. The use of semi-Markov reward processes facilitates the possibility of deriving equations of the prospective and retrospective mathematical reserves. The model is applied to a sample of contracts drawn at random from a mutual insurance company.
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Report for the scientific sojourn carried out at the University of California at Berkeley, from September to December 2007. Environmental niche modelling (ENM) techniques are powerful tools to predict species potential distributions. In the last ten years, a plethora of novel methodological approaches and modelling techniques have been developed. During three months, I stayed at the University of California, Berkeley, working under the supervision of Dr. David R. Vieites. The aim of our work was to quantify the error committed by these techniques, but also to test how an increase in the sample size affects the resultant predictions. Using MaxEnt software we generated distribution predictive maps, from different sample sizes, of the Eurasian quail (Coturnix coturnix) in the Iberian Peninsula. The quail is a generalist species from a climatic point of view, but an habitat specialist. The resultant distribution maps were compared with the real distribution of the species. This distribution was obtained from recent bird atlases from Spain and Portugal. Results show that ENM techniques can have important errors when predicting the species distribution of generalist species. Moreover, an increase of sample size is not necessary related with a better performance of the models. We conclude that a deep knowledge of the species’ biology and the variables affecting their distribution is crucial for an optimal modelling. The lack of this knowledge can induce to wrong conclusions.
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Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence-only data for 50 species in five different regions, to test whether: (1) a 10-fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.