Assessing stem cell research productivity

Honour Index (HoI), a method to evaluate research performance within different research fields, was derived from the impact factor (IF). It can be used to rate and compare different categories of journals. HoI was used in this study to determine the scientific productivity of stem cell research in the Asian Four Dragons (Hong Kong, Singapore, South Korea and Taiwan) from 1981 to 2001. The methodology applied in this study represents a synthesis of universal indicator studies and bibliometric analyses of subfields at the micro-level. We discuss several comparisons, and conclude the developmental trend in stem cell research for two decades. This revised version was published online in August 2006 with corrections to the Cover Date.     

Determinants of expert judgement of research performance

The relationship between indicators of and expert judgement of, research performance were compared in the context of mission oriented pharmaceutical research. Expert judgment is very highly correlated with measures of publication activity, much more so than with very plausible measures of research output and research quality. Furthermore, expert judgement appears to be an additive function of publication size (another name for which might be visibility) and publication quality, with the principal component being size/visibility. These results are very similar to those found byAnderson, Narin, andMcAllister in the context of academic research, but these findings emerge from a context which allows other variables to compete in predicting expert judgement, and are therefore to that degree more robuts. In addition this study finds a clear pattern of subject specificity, which implies that visibility is a function of the judge's subject field.     

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.     

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.     

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.     

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.     

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.     

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.     

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     

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.     

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.     

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.     

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.     

The model of maximum productivity for research universities SciVal author ranks,productivity, university rankings,and their implications

Scientometrics - Aware of the growing importance of global rankings, universities aim to enhance their positions. However, the exact relation between research productivity and ranking positions is...     

Boosting research productivity in top Russian universities: the circumstances of breakthrough

The Russian project for enhancing competitive ability enforced top 21 universities to stimulate the research output actively. The results surpassed expectations with the fivefold increase in the number of publications from 2010 to 2016. This paper discusses the background and reasons for this phenomenal rise and explores in detail the most significant strategies to boost research productivity and publication output. In our study, a classification of university publications is proposed in accordance with the strategies for stimulating the publication activity, mainly corresponding with the set of measures applied by university management. The analysis made it possible to rank the strategies for contributing to the growth of publication activity, to identify the leading strategies for individual universities, and showed a significant difference between universities in the set of explicitly or implicitly applied strategies. The most effective strategy was the Additional paper, associated with the authors, indicated the affiliation of the university as complementary to their main institution. The next most important and fastest growing was the Russian conferences strategy thanks to the efforts of the organizers of domestic conferences to promote their proceedings in Scopus. A notable place is also occupied by the strategy connected with the attraction of prominent authors, which we called Headhunted author. It was possible to determine the role of the Predatory journals strategy in the growth of the publication activity, fortunately, this strategy turned out to be highly localized in only 2 of the 21 universities participating in the project and is visibly declining. It was possible to show that the share of publications in domestic journals, despite the constant increase in their presence in Scopus is steadily falling in the case of leading universities. One of the significant results of the study is an assessment of the dynamics of the average authors’ productivity, which grows insignificantly and almost reached one article per author per year. This fact also shows that the growth of publication activity of top Russian universities is mainly associated with an increase in the number of faculty involved.     

The contribution of star scientists to overall sex differences in research productivity

The state of the art on the issue of sex differences in research efficiency agrees in recognizing higher performances for males, however there are divergences in explaining the possible causes. One of the causes advanced is that there are sex differences in the availability of aptitude at the “high end”. By comparing sex differences in concentration and performance of Italian academic star scientists to the case in the population complement, this work aims to verify if star, or “high-end”, scientists play a preponderant role in determining higher performance among males. The study reveals the existence of a greater relative concentration of males among star scientists, as well as a performance gap between male and female star scientists that is greater than for the rest of the population. In the latter subpopulation the performance gap between the two sexes is seen as truly marginal.     

Impact of mergers & acquisitions on research productivity within the pharmaceutical industry

Several major econometric studies have looked at mergers and acquisitions (M&As) across various industries and concluded that, in general, there is no synergy created or released by M&A activity. This investigation concentrates upon research and development (R&D) performance in the pharmaceutical industry to examine the impact of M&A activity on corporate productivity. Findings indicate that, when compared to those companies within the pharmaceutical industry that did not experience merger activity during comparable time periods, as well as to the industry as a whole, pharmaceutical companies that merged were able to achieve more favorable post-merger productivity scores than were attained prior to their merger.