Multi-level DEA Approach in Research Evaluation

It is well known that the discrimination power of DEA models will be diminishing if too many inputs or outputs are used. It is a dilemma if the decision makers want to select comprehensive indicators to present a relatively holistic evaluation using DEA. In this work we show that by utilizing hierarchical structures of input-output data DEA can handle quite large numbers of inputs and outputs. We present two approaches in a pilot evaluation of 15 institutes for basic research in Chinese Academy of Sciences using DEA models

A Bibliometrics Portrait of Chinese Research through the Lens of China Economic Review. A research proposal.

Notwithstanding, in the last two decades, there has been a noticeable increase in published work on the research field of Chinese economy. There are few studies, which analyze the evolution of Chinese economics research, and the weight of international economics within it, by resorting to objective methods, namely bibliometrics. Giving our focus on Chinese economics related research, we select to base our empirical analysis on the “seed journal” China Economic Review (CER), which is the most important economic journal especially concerned with the issues of Chinese economy. We classify and assess all the (522) articles that were published in CER from its genesis (1989) up to December 2010. We construct three main databases: the first database as bibliographic database that contains the more than 500 articles published in CER, where we classify articles by themes (such as Macroeconomics, Microeconomics and International Economics) and types(such as formal vs. empirical); the second database includes the references of those 500 articles, which we denominate ‘roots of Chinese economics research’; and the third database, the ‘influence of Chinese economics research’, where we have all the studies that cited (more than 3000 references) the 500 articles published in CER. By undertaking an exploratory statistical analysis on the three databases - bibliographic database, ‘roots’ database and ‘influence’ database, we are able to assess three main group of issues: 1) the importance, within Chinese economics of the topic ‘international economic’; the types of research that are pursued in the period of analysis (formal vs empirical); and the most prolific authors in the area; 2) the ‘roots’ of Chinese economics, that is, who and which outlets are influencing most Chinese economics research; 3) the scope of influence of Chinese economics literature.Evolution of research, Economics, Bibliometrics, China Economic Review

R&D Management Trends in the United States, India and China

This study researches the Management of Research and Development (R&D) in the emerging economies of India and China and compares theirs with R&D in the United States (US). The purpose of this research is to forecast the future of R&D in these three countries. Because R&D is changing rapidly, particularly in China, understanding where they will be in the future is of interest to the scientific, academic, government and business segments of each country. Our research consisted of gathering industry standard measures of R&D from 1996 through 2009. These measures are as follows: R&D spending as a percentage of GDP (total government, industry and universities), researchers per million inhabitants, number of patents granted each year, number publications each year and total number of graduates in all programs in thousands. We gathered and logged the metrics for each year from 1996 through 2009 and used the historical data to forecast future positioning of R&D in these countries. An overview of each country is provided in the introductory portion of this paper. This provides the context for the historical performance of R&D and for expected future performance of R&D in the US, India and China

Efficiency of the R&D Sector in the EU-27 at the Regional Level: An Application of DEA

The main aim of the paper is to measure the relative efficiency of the R&D sector in the EU-27 at the regional level. For this purpose, the paper applies a non-parametric approach, i.e. data envelopment analysis (DEA), to assess the relative technical efficiency of R&D activities across selected EU (NUTS-2) regions. The empirical analysis integrates available inputs (R&D expenditures, researchers and employment in high-tech sectors) and outputs (patent and high-tech patent applications) over the 2005–2010 period. The empirical results show that among regions with a high intensity of R&D activities the most efficient performers are Noord-Brabant (Netherlands), Stuttgart (Germany) and Tirol (Austria). In contrast, a wide range of NUTS-2 regions from the Baltics, Eastern and Southern Europe is characterized by an extremely low rate of knowledge production and its efficiency, particularly in Poland (Mazowieckie), Lithuania (Lietuva), Latvia (Latvija), Romania (Bucuresti-Ilfov), Bulgaria (Yugozapaden), Slovakia (Západné Slovensko), Greece (Attiki), Spain (Canarias) and Italy (Sardegna)

Efficiency Evaluation of Basic Research in China

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