A spur to stem cell research

正China Society for Cell Biology released six standards on stem cells and China National Accreditation Service for Conformity Assessment (CNAS) awarded the country's first biobanking accreditation certificate to China National Stem Cell Resource Center on March 20.     

Determinants of research productivity

Earlier researchers like Turkeli, suggested that ‘the factors which determine the productivity of scientists are admittedly complex and perhaps not amenable to real scientific analysis′. The present investigation was designed with the sole purpose of confronting such a complex problem. Nearly 200 variables influencing research productivity were collected through relevant literature, analysis of biographies of great scientists, and discussion with eminent scientists. Finally, through a critical examination, 80 variables were selected for the use of Q-sort technique. The sample for the study consisted of a cross section of scientists ranging from Fellows of Indian National Science Academy to young agricultural scientists. Mailed questionnaires and personal interview methods were used for collecting data. Out of a total of 912 respondents, reply was obtained from 325. On the basis of Q-sorted data, 26 variables were selected for further analysis and they were subjected to principal component factor analysis. The results indicated eleven factors affecting research productivity of scientists. They were: persistence, resource adequacy, access to literature, initiative, intelligence, creativity, learning capability, stimulative leadership, concern for advancement, external orientation, and professional commitment.     

The publication productivity of international agricultural research centers

The literature output over one year, 1990, of 22 International Agricultural Research Centers (IARCs), including 16 Consultative Group on International Agricultural Research (CGIAR) centers, was examined. Total output of the IARCs was 1,694 items, of which on average 42% were primary (refereed) literature; 24% were reports and monographs; 18% proceedings papers; 8% book chapters; and 8% semitechnical/popular literature. Total literature production from the IARCs is similar in magnitude to that of FAO. There were 1,230 internationally recruited scientists in the IARCs, with an average annual productivity of 1.38 items per scientist, including 0.58 primary literature articles. There was no correlation between scientific productivity and numbers of scientists in a center. However, there was a significant positive correlation between scientific productivity and center budget, indicating higher efficiency in the larger centers. In view of the nature of IARCs' literature output, we argue that IARCs should reject the trend for scientists to be assessed only by citations in core primary literature; and that IARCs should set up an international standard, perhaps based on the present proportionality of types of their literature output in order to assess IARC individual scientists and the health of their institutional output.     

Assessing improvement in management research in Taiwan

Research performance is difficult to evaluate because most of the criteria are incommensurable, and assessing its improvement over time is even more difficult. This paper assesses the performance improvement in management research in Taiwan between 2006 and 2010 using the Malmquist productivity index (MPI). The criteria for measuring research performance are journal publications, where the journals are classified as SI-, TI-, other international-, and other local-types. While the number of papers has increased for three types and decreased in one, the MPI indicates that the aggregate performance has improved significantly. The areas of management covered in this study are management information systems, production and operations management, and marketing. For all these areas the performance has improved, although the improvement in marketing is insignificant. The assessment sheds some light on the area and category of journals that contribute to the improvement of research performance, and which are useful for setting goals to reach higher levels.     

Exploring size and agglomeration effects on public research productivity

The paper assesses the empirical foundation of two largely held assumptions in science policy making, namely scale and agglomeration effects. According to the former effect, scientific production may be subject to increasing returns to scale, defined at the level of administrative units, such as institutes or departments. A rationale for concentrating resources on larger units clearly follows from this argument. According to the latter, scientific production may be positively affected by external economies at the geographical level, so that concentrating institutes in the same area may improve scientific spillover, linkages and collaborations.  Taken together, these arguments have implicitly or explicitly legitimated policies aimed at consolidating institutes in public sector research and at creating large physical facilities in a small number of cities. The paper is based on the analysis of two large databases, built by the authors from data on the activity of the Italian National Research Council in all scientific fields and of the French INSERM in biomedical research. Evidence from the two institutions is that the two effects do not receive empirical support. The implications for policy making and for the theory of scientific production are discussed.     

A causal model of productivity in a research facility

The problem addressed concerns the conditions that foster productivity among natural scientists in a large research laboratory. We take several variables identified as important in two major perspectives in the literature on productivity, and use these variables to construct a causal model. Using path analysis, we test the model by employing data from a sample of 295 scientists working at an atomic research facility in West Germany. In general, educational level of the scientists has an important, positive impact on productivity; years of service has a varying and more modest positive effect. Rank of the scientist has an intermediate positive impact on productivity; psychological factors have a negligible effect. Finally, the influence the scientist has on his research endeavors has a modest positive impact on productivity.I am happy to acknowledge several people who provided considerable help on this research: Professors Edward O.Laumann, of the University of Chicago, Franz U.Pappi, of the Universitat zu Kiel, and Michael S.Flynn and Mary FrankFox, of the University of Michigan, and a number of research assistants, including in particular HaraldKlingemann and E. DanielAyres. Financial support for the data collection was freely provided by the Landesamt fur Forschung in Ministerium für Wissenschaft and Forschung des Landes Nordrhein-Westfalen. Financial support for the data analysis came from the National Science Foundation (GS-32002). Data collection was conducted under the auspices of the Zentralarchiv der Universität zu Köln.     

Computer science research: more production,less productivity

It is commonly accepted that scientific research or, more precisely, the number of scientific publications, in computer science has greatly increased over the last few years. The reason would appear to be the pressure to publish, coined by the expression ”Publish or perish”, which is, among other things, necessary for promotions and applications for grants or projects. In this paper we have conducted a study that covers computer science publications from 1936 to 2010 in order to quantify this increase in publications regarding computing research. We have considered the computing conferences and journals available in the DBLP computer science bibliography (DBLP 2013) database, including more than 1.5 million papers, and more than 4 million authors (more than 900,000 different people), corresponding to about 1,000 different journals and 3,000 different conferences and workshops. Our study confirms and quantifies these increases with regard to the number of papers, number of authors, number of papers per author, etc. However, it also reaches a surprising conclusion: the real productivity of researchers has decreased throughout history. The reason for this decrease is the average number of authors per paper, which has grown significantly and is currently three.     

Publication, cooperation and productivity measures in scientific research

The literature on publication counting demonstrates the use of various terminologies and methods. In many scientific publications, no information at all is given about the counting methods used. There is a lack of knowledge and agreement about the sort of information provided by the various methods, about the theoretical and technical limitations for the different methods and about the size of the differences obtained by using various methods. The need for precise definitions and terminology has been expressed repeatedly but with no success. Counting methods for publications are defined and analysed with the use of set and measure theory. The analysis depends on definitions of basic units for analysis (three chosen for examination), objects of study (three chosen for examination) and score functions (five chosen for examination). The score functions define five classes of counting methods. However, in a number of cases different combinations of basic units of analysis, objects of study and score functions give identical results. Therefore, the result is the characterization of 19 counting methods, five complete counting methods, five complete-normalized counting methods, two whole counting methods, two whole-normalized counting methods, and five straight counting methods. When scores for objects of study are added, the value obtained can be identical with or higher than the score for the union of the objects of study. Therefore, some classes of counting methods, including the classes of complete, complete-normalized and straight counting methods, are additive, others, including the classes of whole and whole-normalized counting methods, are non-additive. An analysis of the differences between scores obtained by different score functions and therefore the differences obtained by different counting methods is presented. In this analysis we introduce a new kind of objects of study, the class of cumulative-turnout networks for objects of study, containing full information on cooperation. Cumulative-turnout networks are all authors, institutions or countries contributing to the publications of an author, an institute or a country. The analysis leads to an interpretation of the results of score functions and to the definition of new indicators for scientific cooperation. We also define a number of other networks, internal cumulative-turnout networks, external cumulative-turnout networks, underlying networks, internal underlying networks and external underlying networks. The networks open new opportunities for quantitative studies of scientific cooperation.     

Artificial stem cell niches

Stem cells are characterized by their dual ability to reproduce themselves (self-renew) and specialize (differentiate), yielding a plethora of daughter cells that maintain and regenerate tissues. In contrast to their embryonic counterparts, adult stem cells retain their unique functions only if they are in intimate contact with an instructive microenvironment, termed stem cell niche. In these niches, stem cells integrate a complex array of molecular signals that, in concert with induced cell-intrinsic regulatory networks, control their function and balance their numbers in response to physiologic demands. This progress report provides a perspective on how advanced materials technologies could be used (i) to engineer and systematically analyze specific aspects of functional stem cells niches in a controlled fashion in vitro and (ii) to target stem cell niches in vivo. Such "artificial niches" constitute potent tools for elucidating stem cell regulatory mechanisms with the capacity to directly impact the development of novel therapeutic strategies for tissue regeneration.     

A framework for assessing and rewarding a scientist's research productivity

A contest for world leadership in science and technology exists. New ways to motivate scientists seem as important to contest outcome as new sources of funds. A framework formed by cross-tabulating question difficulty and answer generality should help to identify the contribution of a research scientist. A reward relationship based on this framework should help to ensure that scientists will work on the most difficult research problems, a necessity for a high quality research program.     

Cooperation structure,group size and productivity in research groups

A research group is considered to be a system and the scientists the elements in this system. The degree of interaction among scientists is determined by means of a complex structure measure for groups. It is shown that optimum cooperation structures depend on group size. In addition, it was possible to determine an optimum group size. Various hypotheses have been verified employing the same data material by using several levels of the structure measure.     

An economic model of the life-cycle research productivity of scientists

Scientific productivity is constant as a scientist ages according to recent studies relying mainly on quantity measures of productivity. An economic model of the life-cycle productivity of scientists is presented which implies that the number of citations made to a scientist's previous work will decline with age. The implication could be consistent with the finding of constant quantity output with age if the decline in quality (as measured by number of citations per article) is large enough.     

Assessing scientific research performance and impact with single indices

We provide a comprehensive and critical review of the h-index and its most important modifications proposed in the literature, as well as of other similar indicators measuring research output and impact. Extensions of some of these indices are presented and illustrated.     

An optimal control model of the life-cycle research productivity of scientists

A continuous time model using optimal control techniques is presented which implies that a scientist's productivity will eventually decline with age. This implication is at variance withCole's empirical findings¹ but is consistent withDiamond's empirical findings.²     

Size,age and productivity of scientific and technical research groups

Varied empirical studies show that the average output (measured in various ways) of a scientific or technical research group is directly proportional to its size (also measured in various ways), when the size and output are measured independently. Hence groups of different sizes have the same average output per unit of size. There is no reliable evidence for the existence of a size or a range of sizes for a research group that maximizes output per unit of size. Present theoretical explanations for the proportionality between size and output are largely inadequate or untested. Similarly, among reported results on group age and output, the only consistency so far is that age, measured as years since the founding or first functioning of the group, is uncorrelated with output per capita. Again, there is no evidence for the existence of an age or a range of ages for a research group that is optimal.This paper was prepared for the conference on Generational Dynamics and Innovation in Basic Science, June 1–2, 1989, organized byKarl Urlich Mayer, and held at the Max-Planck-Gesellschaft zur Förderung der Wissenschaften, Schloß Ringberg, Tegernsee, B. R. D. (West Germany). A German translation of this article has been published in theMitteilungen der Max-Planck-Gesellschaft, Heft 3/90.     

Assessing publication performance of research units: extensions through operational research and economic techniques

Many quantitative measures exist to assess the publishing outputs of research units such as university departments or institutes. In addition to well-known issues with such measures, further shortcomings include inadequate adjustments for relative entity sizes and researcher intensity, the extent to which research is concentrated among a few rather than all researchers and lags between staffing and publication. This article presents a further array of possible measurement indices, based on operational research and economic ratios, which are capable of adjusting for each of these shortcomings, and which analysts can combine with relatively little effort into existing measures.     

Academic inbreeding and research productivity and impact in Australian law schools

This study compares the research productivity and impact of inbred and non-inbred faculty employed at Australian law schools. The sample consists of 429 academics, employed at 21 law schools. To measure research productivity and impact we use articles published in top law journals, defined in six different ways, as well as total citations and two different citation indices. We report results including, and excluding, publications in the academic’s home law review. We find evidence that silver-corded faculty outperform other faculty on one of the measures of publications in top journals, once the endogeneity of academic seniority, grant history and the status of the law school at which the individual is employed is addressed, but this finding is not robust across alternative measures of articles published in the top journals. We find that there is no statistically significant difference between the research productivity and impact of inbred and non-inbred faculty. This finding is robust to a range of different ways of measuring research productivity and impact and alternative econometric approaches, including using two-stage least squares to address the endogeneity of academic seniority, grant history and the status of the law school at which the legal academic is employed.     

Sixty-four years of informetrics research: productivity,impact and collaboration

This paper analyses the information science research field of informetrics to identify publication strategies that have been important for its successful researchers. The study uses a micro-analysis of informetrics researchers from 5,417 informetrics papers published in 7 core informetrics journals during 1948–2012. The most productive informetrics researchers were analysed in terms of productivity, citation impact, and co-authorship. The 30 most productive informetrics researchers of all time span several generations and seem to be usually the primary authors of their research, highly collaborative, affiliated with one institution at a time, and often affiliated with a few core European centres. Their research usually has a high total citation impact but not the highest citation impact per paper. Perhaps surprisingly, the US does not seem to be good at producing highly productive researchers but is successful at producing high impact researchers. Although there are exceptions to all of the patterns found, researchers wishing to have the best chance of being part of the next generation of highly productive informetricians may wish to emulate some of these characteristics.