891 resultados para adoption of R D


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Does the graying of scientific research teams matter? This study addresses how workgroup processes and external environmental factors contribute and inhibit the effect of age diversity in R&D project groups on the production of innovative publicly usable knowledge outcomes in the form of publication outputs. We examined the relationships between group age diversity (age cohort diversity, mean age, age dispersion), R&D workgroup member self-ratings of workgroup processes, their supervisor�s assessment of the external environmental factors the project groups faced, and their supervisor�s ratings of group performance, the number of scientific publicly available publications produced by the group and the use of multiple authorships on publications. Usable data was obtained from 32 R&D workgroups of a large Government Agricultural Research and Development Agency. Consistent with the literature, workgroup processes and external environmental factors were found to directly effect innovation outcomes. Contrary to expectation, but consistent with Social Identity theory, workgroup age diversity generally negatively impacted upon innovation outcomes. An exception was where multiple authorship on publications for project groups increased as the dispersion of age within groups increased. Importantly, workgroups that were both more age homogeneous and perceived to have optimally functioning work processes produced more R&D innovation outcomes than other groups. Generally, these differences appear to be related to the greater division of labor practices (and less multi-tasking) employed by the older and more homogeneous workgroups. Implications for R&D workgroup resource theory and practices are discussed.

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What does endogenous growth theory tell about regional economies? Empirics of R&D worker-based productivity growth, Regional Studies. Endogenous growth theory emerged in the 1990s as ‘new growth theory’ accounting for technical progress in the growth process. This paper examines the role of research and development (R&D) workers underlying the Romer model (1990) and its subsequent modifications, and compares it with a model based on the accumulation of human capital engaged in R&D. Cross-section estimates of the models against productivity growth of European regions in the 1990s suggest that each R&D worker has a unique set of knowledge while his/her contributions are enhanced by knowledge sharing within a region as well as spillovers from other regions in proximity.

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This paper extends previous analyses of the choice between internal and external R&D to consider the costs of internal R&D. The Heckman two-stage estimator is used to estimate the determinants of internal R&D unit cost (i.e. cost per product innovation) allowing for sample selection effects. Theory indicates that R&D unit cost will be influenced by scale issues and by the technological opportunities faced by the firm. Transaction costs encountered in research activities are allowed for and, in addition, consideration is given to issues of market structure which influence the choice of R&D mode without affecting the unit cost of internal or external R&D. The model is tested on data from a sample of over 500 UK manufacturing plants which have engaged in product innovation. The key determinants of R&D mode are the scale of plant and R&D input, and market structure conditions. In terms of the R&D cost equation, scale factors are again important and have a non-linear relationship with R&D unit cost. Specificities in physical and human capital also affect unit cost, but have no clear impact on the choice of R&D mode. There is no evidence of technological opportunity affecting either R&D cost or the internal/external decision.

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The UK has a relatively low ratio of business R&D to GDP (the BERD ratio) compared to other leading economies. There has also been a small decline in UK’s BERD ratio in the 1990s, whereas other leading economies have experienced small rises. The relatively low BERD ratio cannot be explained solely by sectoral or industry-level differences between the UK and other countries. There is, therefore, considerable interest in understanding the firm-level determinants of investment in R&D. This report was commissioned by the DTI to analyse the link between R&D and productivity for a sample of firms derived from merging the ONS’s Business Research and Development Database (BERD) and the Annual Respondents Database (ARD). The analysis estimates the private rates of returns to R&D, and not the social rates of return, since it is the private returns that should drive firms’ decisions. A key objective of this research is to analyse the productivity of R&D in small and medium sized enterprises (SME). The analysis is intended to allow comparisons to the results in Rogers (2005), which uses publicly available data on R&D in medium to large UK firms in the 1990s.

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This paper offers an extensive survey and a critical discussion of the empirical literature on the driving factors of R&D. These factors are subsumed under five broad types. The paper first summarises the key predictions from theory regarding each type's R&D effect. It then examines for which factors differences in the theoretical predictions can also be found in empirical studies, and for which factors the empirical evidence is more unanimous. As the focus is on the empirical literature, methodological issues are also highlighted. The major factor types identified in the literature are, individual firm or industry characteristics, particularly internal finance and sales; competition in product markets; R&D tax credits and subsidies; location and resource related factors, such as spillovers from university research within close geographic proximity, membership of a research joint venture and cooperation with research centres, and the human capital embodied in knowledge workers; and spillovers from foreign R&D. Although on balance there is a consensus regarding the R&D effects of most factors, there is also variation in results. Recent work suggests that accounting for non-linearities is one area of research that may explain and encompass contradictory findings.

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The research and development costs of 106 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms. These data were used to estimate the average pre-tax cost of new drug and biologics development. The costs of compounds abandoned during testing were linked to the costs of compounds that obtained marketing approval. The estimated average out-of-pocket cost per approved new compound is $1395 million (2013 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a real discount rate of 10.5% yields a total pre-approval cost estimate of $2558 million (2013 dollars). When compared to the results of the previous study in this series, total capitalized costs were shown to have increased at an annual rate of 8.5% above general price inflation. Adding an estimate of post-approval R&D costs increases the cost estimate to $2870 million (2013 dollars).

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We develop a mediation model in which firm size is proposed to affect the scale and quality of innovative output through the adoption of different decision styles during the R&D process. The aim of this study is to understand how the internal changes that firms undergo as they evolve from small to larger organizations affect R&D productivity. In so doing, we illuminate the underlying theoretical mechanism affecting two different dimensions of R&D productivity, namely the scale and quality of innovative output which have not received much attention in previous literature. Using longitudinal data of Spanish manufacturing firms we explore the validity of this mediation model. Our results show that as firms evolve in size, they increasingly emphasize analytical decision making, and consequently, large-sized firms aim for higher-quality innovations while small firms aim for a larger scale of innovative output.

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Ramsey pricing has been proposed in the pharmaceutical industry as a principle to price discriminate among markets while allowing to recover the (fixed) R&D cost. However, such analyses neglect the presence of insurance or the fund raising costs for most of drug reimbursement. By incorporating these new elements, we aim at providing some building blocks towards an economic theory incorporating Ramsey pricing and insurance coverage. We show how coinsurance affects the optimal prices to pay for the R&D investment. We also show that under certain conditions, there is no strategic incentive by governments to set coinsurance rates in order to shift the financial burden of R&D. This will have important implications to the application of Ramsey pricing principles to pharmaceutical products across countries.

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Empirical evidence on the effectiveness of R&D subsidies to firms has produced mixed results so far. One possible explanation is that firms and project selection rules may be quite heterogeneous both across agencies and across industries, leading to different outcomes in terms of the induced additional private effort. Here we focus on the participation stage. Using a sample of Spanish firms, we test for differences across agencies and industries. Our results suggest that firms in the same industry face different hurdles to participate in different agencies’ programs, that participation patterns may reflect a combination of agency goals, and that patterns differ across high-tech and low-tech industries.

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The implementation of public programs to support business R&D projects requires the establishment of a selection process. This selection process faces various difficulties, which include the measurement of the impact of the R&D projects as well as selection process optimization among projects with multiple, and sometimes incomparable, performance indicators. To this end, public agencies generally use the peer review method, which, while presenting some advantages, also demonstrates significant drawbacks. Private firms, on the other hand, tend toward more quantitative methods, such as Data Envelopment Analysis (DEA), in their pursuit of R&D investment optimization. In this paper, the performance of a public agency peer review method of project selection is compared with an alternative DEA method.

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This paper investigates relationships between cooperation, R&D, innovation and productivity in Spanish firms. It uses a large sample of firm-level micro-data and applies an extended structural model that aims to explain the effects of cooperation on R&D investment, of R&D investment on output innovation, and of innovation on firms’ productivity levels. It also analyses the determinants of R&D cooperation. Firms’ technology level is taken into account in order to analyse the differences between high-tech and low-tech firms, both in the industrial and service sectors. The database used was the Technological Innovation Panel (PITEC) for the period 2004-2010. Empirical results show that firms which cooperate in innovative activities are more likely to invest in R&D in subsequent years. As expected, R&D investment has a positive impact on the probability of generating an innovation, in terms of both product and process, for manufacturing firms. Finally, innovation output has a positive impact on firms’ productivity, being greater in process innovations.

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This paper investigates relationships between cooperation, R&D, innovation and productivity in Spanish firms. It uses a large sample of firm-level micro-data and applies an extended structural model that aims to explain the effects of cooperation on R&D investment, of R&D investment on output innovation, and of innovation on firms’ productivity levels. It also analyses the determinants of R&D cooperation. Firms’ technology level is taken into account in order to analyse the differences between high-tech and low-tech firms, both in the industrial and service sectors. The database used was the Technological Innovation Panel (PITEC) for the period 2004-2010. Empirical results show that firms which cooperate in innovative activities are more likely to invest in R&D in subsequent years. As expected, R&D investment has a positive impact on the probability of generating an innovation, in terms of both product and process, for manufacturing firms. Finally, innovation output has a positive impact on firms’ productivity, being greater in process innovations. Keywords: innovation sources; productivity; R&D Cooperation