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This study investigates an approach to book metrics for research evaluation that takes into account the complexity of scholarly monographs. This approach is based on work sets – unique scholarly works and their within-work related bibliographic entities – for scholarly monographs in national databases for research output.

This study examines bibliographic records on scholarly monographs acquired from four European databases (VABB in Flanders, Belgium; CROSBI in Croatia; CRISTIN in Norway; COBISS in Slovenia). Following a data enrichment process using metadata from OCLC WorldCat and Amazon Goodreads, the authors identify work sets and the corresponding ISBNs. Next, on the basis of the number of ISBNs per work set and the presence in WorldCat, they design a typology of scholarly monographs: Globally visible single-expression works, Globally visible multi-expression works, Miscellaneous and Globally invisible works.

The findings show that the concept “work set” and the proposed typology can aid the identification of influential scholarly monographs in the social sciences and humanities (i.e. the Globally visible multi-expression works).

In light of the findings, the authors outline requirements for the bibliographic control of scholarly monographs in national databases for research output that facilitate the use of the approach proposed here.

The authors use insights from library and information science (LIS) to construct complexity-sensitive book metrics. In doing so, the authors, on the one hand, propose a solution to a problem in research evaluation and, on the other hand, bring to attention the need for a dialogue between LIS and neighbouring communities that work with bibliographic data.

The purpose of this paper is to analyze the capabilities, functionalities and appropriateness of Altmetric.com as a data source for the bibliometric analysis of books in comparison to PlumX.

The authors perform an exploratory analysis on the metrics the Altmetric Explorer for Institutions, platform offers for books. The authors use two distinct data sets of books. On the one hand, the authors analyze the Book Collection included in Altmetric.com. On the other hand, the authors use Clarivate’s Master Book List, to analyze Altmetric.com’s capabilities to download and merge data with external databases. Finally, the authors compare the findings with those obtained in a previous study performed in PlumX.

Altmetric.com combines and orderly tracks a set of data sources combined by DOI identifiers to retrieve metadata from books, being Google Books its main provider. It also retrieves information from commercial publishers and from some Open Access initiatives, including those led by university libraries, such as Harvard Library. We find issues with linkages between records and mentions or ISBN discrepancies. Furthermore, the authors find that automatic bots affect greatly Wikipedia mentions to books. The comparison with PlumX suggests that none of these tools provide a complete picture of the social attention generated by books and are rather complementary than comparable tools.

This study targets different audience which can benefit from the findings. First, bibliometricians and researchers who seek for alternative sources to develop bibliometric analyses of books, with a special focus on the Social Sciences and Humanities fields. Second, librarians and research managers who are the main clients to which these tools are directed. Third, Altmetric.com itself as well as other altmetric providers who might get a better understanding of the limitations users encounter and improve this promising tool.

This is the first study to analyze Altmetric.com’s functionalities and capabilities for providing metric data for books and to compare results from this platform, with those obtained via PlumX.

This study aims to examine the connection between scholars' research performance and the multidisciplinary nature of their collaborative research. Furthermore, in response to mixed results regarding the effects of multidisciplinarity on research performance, this study explores how human resource management (HRM) practices may moderate this link.

The authors built a model based on the theoretical arguments and empirical evidence found in the review of diversity and HRM literature. The authors also performed a quantitative study based on a sample of scholars in the field of management. Different econometric estimations were used to test the proposed model.

The results of this empirical analysis suggest that multidisciplinary research has a non-linear effect on research performance. Certain HRM practices, such as development and collaboration, moderated the curvilinear relationship between multidisciplinarity and performance, displacing the optimum to allow higher performance at higher levels of multidisciplinary research.

The paper provides advances on previous works studying the curvilinear relationship between multidisciplinarity and the researchers' performance, confirming that multidisciplinarity is beneficial up to a threshold beyond which these benefits are attenuated. In addition, the findings shed light on important issues related to team-oriented HRM practices associated with the outcomes of multidisciplinary research.

Given the magnitude of the literature, a researcher must be selective of research papers and publications in general. In other words, only papers that meet strict standards of academic integrity and adhere to reliable and credible sources should be referenced. The purpose of this paper is to approach this issue from the prism of scientometrics according to the following research questions: Is it necessary to judge the quality of scientific production? How do we evaluate scientific production? What are the tools to be used in evaluation?

This paper presents a comparative study of scientometric evaluation practices and tools. A systematic literature review is conducted based on articles published in the field of scientometrics between 1951 and 2022. To analyze data, the authors performed three different aspects of analysis: usage analysis based on classification and comparison between the different scientific evaluation practices, type and level analysis based on classifying different scientometric indicators according to their types and application levels and similarity analysis based on studying the correlation between different quantitative metrics to identify similarity between them.

This comparative study leads to classify different scientific evaluation practices into externalist and internalist approaches. The authors categorized the different quantitative metrics according to their types (impact, production and composite indicators), their levels of application (micro, meso and macro) and their use (internalist and externalist). Moreover, the similarity analysis has revealed a high correlation between several scientometric indicators such as author h-index, author publications, citations and journal citations.

The interest in this study lies deeply in identifying the strengths and weaknesses of research groups and guides their actions. This evaluation contributes to the advancement of scientific research and to the motivation of researchers. Moreover, this paper can be applied as a complete in-depth guide to help new researchers select appropriate measurements to evaluate scientific production. The selection of evaluation measures is made according to their types, usage and levels of application. Furthermore, our analysis shows the similarity between the different indicators which can limit the overuse of similar measures.

The purpose of this paper is to advance the comprehension of the role that geographic proximity plays in relation to non-spatial proximity in the context of international university-industry knowledge transfer.

The paper is designed as a multiple-case study. It looks at selected instances of contract research at Tallinn University of Technology that represents a typical technical university in Central and Eastern Europe characterised by relatively short period of market economy and university-industry cooperation.

The results indicate that there emerge different configurations of proximity nationally and internationally. In case of domestic cooperation cognitive (education), organisational, social and institutional (institutional setting) proximity exist simultaneously with geographic proximity. International cooperation is characterised by lack of geographical proximity, but the existence of cognitive and social proximity indicating a substitution.

The research is limited to analysing instances of contract research and relations between spatial and non-spatial forms of proximity. Further research could consider the differences between various channels of knowledge transfer and address the relationship between non-spatial forms of proximity.

The paper contributes to the existing body of knowledge by using proximity dimensions operationalised at aggregate and individual levels to study the university knowledge network. It is proposed in this paper that attention has to be paid to distinguishing between organisational and individual levels of analysis and their differing results. Proximity at organisational level does not necessarily translate into proximity between individuals and vice versa.

Mendeley reader counts have been proposed as early indicators for the impact of academic publications. The purpose of this paper is to assess whether there are enough Mendeley readers for research evaluation purposes during the month when an article is first published.

Average Mendeley reader counts were compared to the average Scopus citation counts for 104,520 articles from ten disciplines during the second half of 2016.

Articles attracted, on average, between 0.1 and 0.8 Mendeley readers per article in the month in which they first appeared in Scopus. This is about ten times more than the average Scopus citation count.

Other disciplines may use Mendeley more or less than the ten investigated here. The results are dependent on Scopus’s indexing practices, and Mendeley reader counts can be manipulated and have national and seniority biases.

Mendeley reader counts during the month of publication are more powerful than Scopus citations for comparing the average impacts of groups of documents but are not high enough to differentiate between the impacts of typical individual articles.

This is the first multi-disciplinary and systematic analysis of Mendeley reader counts from the publication month of an article.

The purpose of this paper is to carry out a bibliometric analysis of the development of Chinese research in superconductivity since the advent of high‐temperature superconductivity (HTS) in the mid‐1980s, and to compare Chinese research with that of its international competitors.

This research used publications, citations, journals, subject categories and institutional data from the Web of Science database.

Chinese HTS research has grown steadily in importance over the period, with a significant increase in peer‐recognition, as measured by citations from non‐Chinese researchers. A comparison with superconductivity research in England, France, Germany, Japan, Russia and the USA shows that the impact of the Chinese work is growing relative to the other countries, with a cluster analysis showing that the current bibliometric status of Chinese research is most similar to that of England, France and Russia.

This is both the first bibliometric study of Chinese research in superconductivity and the first bibliometric comparison of different countries' research in superconductivity since the advent of HTS. Cluster analysis provides an interesting way of identifying analogous international bibliometric profiles.

The purpose of this paper is to explore, by a quantitative analysis, growth rates of, and trends in, global publications in the field of library and information science (LIS) produced by library science professionals.

A survey approach was used in this paper. Journal Citation Reports 2010 was the major source for selecting 40 LIS core journals. A bibliometric analysis was conducted. Visualization and mapping software was utilized to present a picture of the growth in and trends relating to LIS publications.

A total of 18,371 research articles were published from 2003 to 2012. A significant growth rate (11.37 per cent) was found in 2009. Self-citation tendencies have been increasing, with an average rate of 38.56 per cent. Of all publication types, “article” was the most popular among LIS researchers. China has contributed remarkably in terms of collaborative publications.

The present study could be helpful for library professionals, subject specialists and policy makers. These findings may encourage library professionals to integrate and monitor library functions through bibliometric analysis.

This paper identifies growth and trends in publications by LIS researchers through use of bibliometrics.

The main objective of the present study is to determine the role of citation-based metrics (PageRank and HITS’ authority and hub scores) and non-citation metrics (Goodreads readers, reviews and ratings, textbook edition counts) in predicting educational ranks of textbooks.

The rankings of 1869 academic textbooks of various disciplines indexed in Scopus were extracted from the Open Syllabus Project (OSP) and compared with normalized counts of Scopus citations, scores of PageRank, authority and hub (HITS) in Scopus book-to-book citation network, Goodreads ratings and reviews, review sentiment scores and WorldCat book editions.

Prediction of the educational rank of scholarly syllabus books ranged from 32% in technology to 68% in philosophy, psychology and religion. WorldCat editions in social sciences, medicine and technology, Goodreads ratings in humanities, and book-citation-network authority scores in law and political science accounted for the strongest predictions of the educational score. Thus, each indicator of editions, Goodreads ratings, and book citation authority score alone can be used to show the rank of the academic textbooks, and if used in combination, they will help explain the educational uptake of books even better.

This is the first study examining the role of citation indicators, Goodreads readers, reviews and ratings in predicting the OSP rank of academic books.