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limitations of parametric approaches given that various production or cost functions should be assumed as certain forms of function in advance (Brown and Svenson 1998 ; Geisler 1995 ). Data envelopment analysis (DEA) is generally accepted as a

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Abstract  

In this study we continue the application of Data Envelopment Analysis (DEA) to assess the efficiency and effectiveness of the R&D effort of European countries. We use GDP, active population and R&D expenditure as inputs, and publications and patents as outputs. Being effective means that, in order to obtain a maximum efficiency score countries are forced to perform on every output goal. A discussion of each country's performance and a comparison with May'sScience results concludes our analysis.

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Data envelopment analysis as a tool for constructing scientometric indicators Scientometrics 40 45 – 56 . 3. Rousseau , S

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Technical efficiency in agriculture of 10 new EU member states is analysed by Data Envelopment Analysis and econometric panel data analysis. Technical efficiency in agriculture is significantly positively associated with agricultural factor endowments, average farm size, farm specialisation, small-scale farms, and technological change. Foreign direct investments have an ambiguous effect. Reform and institutional developments, large-scale privatisation and price liberalisation, and urban- rural income gap are associated with technical efficiency in agriculture positively. An increase in technical efficiency in agriculture and the development of the rural economy are seen as a strategy to boost the level of living standards in agriculture and in rural areas.

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This paper presents a methodology for measuring the technical efficiency of research activities. It is based on the application of data envelopment analysis to bibliometric data on the Italian university system. For that purpose, different input values (research personnel by level and extra funding) and output values (quantity, quality and level of contribution to actual scientific publications) are considered. Our study aims at overcoming some of the limitations connected to the methodologies that have so far been proposed in the literature, in particular by surveying the scientific production of universities by authors’ name.

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Following the increasing investment on basic research in China, the outputs of basic research have been greatly enhanced. In this paper, the relative efficiency of investments in basic research is analyzed by adopting statistical regressions and Data Envelopment Analysis (DEA) method. Preliminary results show that injected investment seems to be the main driving force for the increased basic research outputs in China. It is found that there were significant improvements on overall efficiency from 1991 to 1996, although this trend has noticeably slowed down since 1996. Possible causes of this slow-down are discussed.

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Scientometrics
Authors:
K. C. Garg
,
B. M. Gupta
,
Tabassum Jamal
,
Santanu Roy
, and
Suresh Kumar

Summary An analysis of 330 questionnaires received from project investigators funded by AICTE indicates that project investigators preferred to present their research results at conferences rather than in national and international journals. Impact of funding has been better on human resource capability development as compared to research and technological output. Analysis of data using data envelopment analysis indicates that projects funded under electronics and communication engineering, mechanical engineering, electrical engineering and management displayed some consistency and uniformity with regard to impact on various output parameters.

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Scientometrics
Authors:
Geraldo Da Silva E Souza
,
Eliseu Alves
, and
Ant onio Flávio Dias ávila

Abstract  

We define and model research production at Embrapa, the major Brazilian institution responsible for applied agricultural research. The main theoretical framework used is Data Envelopment Analysis — DEA. The economic interpretation of these models is explored to assess scale, congestion and cost efficiencies. Efficiency results are used to test for differences among types of research units and for the scale of operation. A further analysis of agricultural research in Brazil is carried out with the inclusion of three research centers in Argentina. Finally, DEA estimates are compared with the fit of a stochastic frontier.

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A major difficulty with bibliometric measures of departmental research contributions based upon publications counts has concerned the summing of publications of different types. An attempt is made in this paper to bypass this aggregation problem by appeal to the methods of Data Envelopment Analysis (DEA). In this way we investigate the technical efficiency of UK university departments of economics as producers of research. The data set used is an extended version of the one which informed the recent Universities Funding Council peer review, and the results obtained here are compared with those obtained by the Council. We conclude that, although due caution is needed in the interpretation of results, DEA has a positive contribution to make in the development of meaningful indicators of university performance.

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This paper presents a methodology for measuring the improvements in efficiency and adjustments in the scale of R&D (Research & Development) activities. For this purpose, this study decomposes academic productivity growth into components attributable to (1) world academic frontier change, (2) R&D efficiency change, (3) human capital accumulation, and (4) capital accumulation. The world academic frontier at each point in time is constructed using data envelopment analysis (DEA). This study calculates each of the above four components of academic productivity for 27 countries over 1990–2003, and finds that the components which contribute to academic productivity growth vary with the different countries’ characteristics and development stages. Human capital has more weight in terms of the quantity of academic research, and capital accumulation plays a more important role in the citation impact of academic research.

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