Factors Influencing Cities' Publishing Efficiency

Recently, a vast number of scientific publications have been produced in cities in emerging countries. It has long been observed that the publication output of Beijing has exceeded that of any other city in the world, including such leading centres of science as Boston, New York, London, Paris, and Tokyo. Researchers have suggested that, instead of focusing on cities' total publication output, the quality of the output in terms of the number of highly cited papers should be examined. However, in the period from 2014 to 2016, Beijing produced as many highly cited papers as Boston, London, or New York. In this paper, I propose another method to measure cities' publishing performance; I focus on cities' publishing efficiency (i.e., the ratio of highly cited articles to all articles produced in that city). First, I rank 554 cities based on their publishing efficiency, then I reveal some general factors influencing cities' publishing efficiency. The general factors examined in this paper are as follows: the linguistic environment, cities' economic development level, the location of excellent organisations, cities' international collaboration patterns, and the productivity of scientific disciplines

Factors predicting the scientific wealth of nations

It has been repeatedly demonstrated that economic affluence is one of the main predictors of the scientific wealth of nations. Yet, the link is not as straightforward as is often presented. First, only a limited set of relatively affluent countries is usually studied. Second, there are differences between equally rich countries in their scientific success. The main aim of the present study is to find out which factors can enhance or suppress the effect of the economic wealth of countries on their scientific success, as measured by the High Quality Science Index (HQSI). The HQSI is a composite indicator of scientific wealth, which in equal parts considers the mean citation rate per paper and the percentage of papers that have reached the top 1% of citations in the Essential Science Indicators (ESI; Clarivate Analytics) database during the 11-year period from 2008 to 2018. Our results show that a high position in the ranking of countries on the HQSI can be achieved not only by increasing the number of high-quality papers but also by reducing the number of papers that are able to pass ESI thresholds but are of lower quality. The HQSI was positively and significantly correlated with the countries’ economic indicators (as measured by gross national income and Research and Development expenditure as a percentage from GDP), but these correlations became insignificant when other societal factors were controlled for. Overall, our findings indicate that it is small and well-governed countries with a long-standing democratic past that seem to be more efficient in translating economic wealth into high-quality science

Catalan competitiveness: Science and business

Science has been shown to be an important driver of economic growth and performance. In this chapter we take a careful look at a key ingredient of this driver for Catalonia: the link between science and business. We argue that the Catalan innovation system faces three important challenges in order to better connect science to business: 1) the need for a sufficient supply of high quality science; 2) the need for a sufficient demand for science by companies, and 3) the ability to connect science and business, i.e., science needs different channels to connect with business and requires coordinated efforts between the different players in the innovation system. We find that the science landscape at Catalan (Spanish) scientific institutions has improved considerably in the last decade. Demand for science by Catalan firms, on the contrary, is still very weak. Nevertheless, we do find that industry and universities use a large variety of channels for knowledge interaction. In addition, we show that the three large Catalan universities have very different profiles in their interactions with industry. However, our analysis does indicate that there is currently a lack of basic information about the Catalan innovation system to help inform and direct such important policy measures. Some coordination on recording this information systematically would improve matters considerably.Competitiveness; Catalonia; Science; Business;

The metric tide: report of the independent review of the role of metrics in research assessment and management

This report presents the findings and recommendations of the Independent Review of the Role of Metrics in Research Assessment and Management. The review was chaired by Professor James Wilsdon, supported by an independent and multidisciplinary group of experts in scientometrics, research funding, research policy, publishing, university management and administration. This review has gone beyond earlier studies to take a deeper look at potential uses and limitations of research metrics and indicators. It has explored the use of metrics across different disciplines, and assessed their potential contribution to the development of research excellence and impact. It has analysed their role in processes of research assessment, including the next cycle of the Research Excellence Framework (REF). It has considered the changing ways in which universities are using quantitative indicators in their management systems, and the growing power of league tables and rankings. And it has considered the negative or unintended effects of metrics on various aspects of research culture. The report starts by tracing the history of metrics in research management and assessment, in the UK and internationally. It looks at the applicability of metrics within different research cultures, compares the peer review system with metric-based alternatives, and considers what balance might be struck between the two. It charts the development of research management systems within institutions, and examines the effects of the growing use of quantitative indicators on different aspects of research culture, including performance management, equality, diversity, interdisciplinarity, and the ‘gaming’ of assessment systems. The review looks at how different funders are using quantitative indicators, and considers their potential role in research and innovation policy. Finally, it examines the role that metrics played in REF2014, and outlines scenarios for their contribution to future exercises

Standing on Academic Shoulders: Measuring Scientific Influence in Universities

This article measures scientific influence by means of citations to academic papers. The data source is the Institute for Scientific Information (ISI); the scientific institutions included are the top 110 U.S. research universities; the 12 main fields that classify the data cover nearly all of science; and the time period is 1981-1999. Altogether the database includes 2.4 million papers and 18.8 million citations. Thus the evidence underlying our findings accounts for much of the basic research conducted in the United States during the last quarter of the 20th century. This research in turn contributes a significant part of knowledge production in the U.S. during the same period. The citation measure used is the citation probability, which equals actual citations divided by potential citations, and captures average utilization of cited literature by individual citing articles. The mean citation probability within fields is on the order of 10-5. Cross-field citation probabilities are one-tenth to one-hundredth as large, or 10-6 to 10-7. Citations between pairs of citing and cited fields are significant in less than one-fourth of the possible cases. It follows that citations are largely bounded by field, with corresponding implications for the limits of scientific influence. Cross-field citation probabilities appear to be symmetric for mutually citing fields. Scientific influence is asymmetric within fields, and occurs primarily from top institutions to those less highly ranked. Still, there is significant reverse influence on higher-ranked schools. We also find that top institutions are more often cited by peer institutions than lower-ranked institutions are cited by their peers. Overall the results suggest that knowledge spillovers in basic science research are important, but are circumscribed by field and by intrinsic relevance. Perhaps the most important implication of the results are the limits that they seem to impose on the returns to scale in the knowledge production function for basic research, namely the proportion of available knowledge that spills over from one scientist to another.