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This paper analyses the research in Library and Information Science (LIS) and reports on (1) the status of LIS research in 2015 and (2) on the evolution of LIS research longitudinally from 1965 to 2015.

The study employs a quantitative intellectual content analysis of articles published in 30+ scholarly LIS journals, following the design by Tuomaala et al. (2014). In the content analysis, we classify articles along eight dimensions covering topical content and methodology.

The topical findings indicate that the earlier strong LIS emphasis on L&I services has declined notably, while scientific and professional communication has become the most popular topic. Information storage and retrieval has given up its earlier strong position towards the end of the years analyzed. Individuals are increasingly the units of observation. End-user's and developer's viewpoints have strengthened at the cost of intermediaries' viewpoint. LIS research is methodologically increasingly scattered since survey, scientometric methods, experiment, case studies and qualitative studies have all gained in popularity. Consequently, LIS may have become more versatile in the analysis of its research objects during the years analyzed.

Among quantitative intellectual content analyses of LIS research, the study is unique in its scope: length of analysis period (50 years), width (8 dimensions covering topical content and methodology) and depth (the annual batch of 30+ scholarly journals).

In this article, the ideas and methods behind the “patent-paper citation” are scrutinised by following the intellectual and technical development of approaches and ideas in early work on patentometrics. The aim is to study how references from patents to papers came to play a crucial role in establishing a link between science and technology.

The study comprises a conceptual history of the “patent paper citation” and its emergence as an important indicator of science and technology interaction. By tracing key references in the field, it analyses the overarching frameworks and ideas, the conceptual “hinterland”, in which the approach of studying patent references emerged.

The analysis explains how interest in patents – not only as legal and economic artefacts but also as scientific documents – became evident in the 1980s. The focus on patent citations was sparked by a need for relevant and objective indicators and by the greater availability of databases and methods. Yet, the development of patentometrics also relied on earlier research, and established theories, on the relation between science and technology.

This is the first attempt at situating patentometrics in a larger societal and scientific context. The paper offers a reflexive and nuanced analysis of the “patent-paper citation” as a theoretical and historical construct, and it calls for a broader and contextualised understanding of patent references, including their social, legal and rhetorical function.

This study aims to analyze the impact of Artificial Intelligence (AI) and Machine Learning (ML) on heritage conservation and preservation, and to identify relevant future research trends, by applying scientometrics.

A total of 1,646 articles, published between 1985 and 2021, concerning research on the application of ML and AI in cultural heritage were collected from the Scopus database and analyzed using bibliometric methodologies.

The findings of this study have shown that although there is a very important increase in academic literature in relation to AI and ML, publications that specifically deal with these issues in relation to cultural heritage and its conservation and preservation are significantly limited.

This study enriches the academic outline by highlighting the limited literature in this context and therefore the need to advance the study of AI and ML as key elements that support heritage researchers and practitioners in conservation and preservation work.

The measure of companies' Innovation Performance is fundamental for enhancing the value and decision-making processes of firms. The purpose of this paper is to present a new measure of Innovation Performance, called Innovation Patent Index (IPI), which makes it possible to quantitatively summarize different aspects of firms' innovation.

In order to define the IPI, a secondary source, i.e. patent data, has been used. The five dimensions of IPI, i.e. efficiency, time, diversification, quality and internationalization have been defined both analyzing the literature and applying three different machine learning algorithms (regularized least squares, deep neural networks and decision trees), considering patent forward citations as a proxy of the innovation performance.

Results show that the IPI index is a very useful tool, simple to use and very promptly. In fact, it is possible to get important results without making time consuming analysis with primary sources. It is a tool that can be used by managers, businessmen, policymakers, organizations, patent experts and financiers to evaluate and plan future activities, to enhance the innovation capability, to find financing and to support and improve innovation.

Patent data are not widely used in all the sectors. Moreover, the pure number of forward citations is not the only forward looking indicator suggested by the literature.

The demand for a useable Innovation Performance tool, as well as the lack of tools able to grasp different aspects of the innovation, highlight the need to develop new instruments. In fact, although previous studies provide several measures of Innovation Performance, these are often difficult for managers to use, do not appreciate different aspects of the innovation and are not forward looking.

The management of employee happiness and well-being has been gaining interest in academic research in recent years; however, few studies have focussed on the entrepreneur's perspective. The aim of this paper is to analyse the state of research on women-led businesses, well-being and happiness management.

A bibliometric study has been carried out since 1996, the first year in which publications in this field were detected. In total, 128 papers are identified in the most reliable database, Web of Science Core Collection. A network mapping of authorship, citation and co-occurrence of keywords in scientific publications is shown.

The results of this study confirm that societal changes resulting from crises increase research interest in improving organisational environments and happiness. After the economic crises of 2013, there was a boost, and after the pandemic, there is again a boost in research. More than half of the publications and citations on female entrepreneurship and happiness management are post-pandemic. The study offers some research directions and emphasises the role of gender.

This article brings a new approach to the study of well-being in organisations, highlighting the relevance of the role female leadership plays in promoting happiness at work.

This paper presents a follow-on study that quantifies geolingual markers and their apparent connection with authorship collaboration patterns in canonical Digital Humanities (DH) journals. In particular, it seeks to detect patterns in authors' countries of work and languages in co-authorship networks.

Through an in-depth co-authorship network analysis, this study analysed bibliometric data from three canonical DH journals over a range of 52 years (1966–2017). The results are presented as visualised networks with centrality calculations.

The results suggest that while DH scholars may not collaborate as frequently as those in other disciplines, when they do so their collaborations tend to be more international than in many Science and Engineering, and Social Sciences disciplines. DH authors in some countries (e.g. Spain, Finland, Australia, Canada, and the UK) have the highest international co-author rates, while others have high national co-author rates but low international rates (e.g. Japan, the USA, and France).

This study is the first DH co-authorship network study that explores the apparent connection between language and collaboration patterns in DH. It contributes to ongoing debates about diversity, representation, and multilingualism in DH and academic publishing more widely.

This study investigates how important the preprint arXiv is for Slovenian scientists, whether there are differences between scientific disciplines and the reputation of arXiv among Slovenian scientists. We are also interested in what advantages and disadvantages scientists see in using arXiv.

A voluntary sample of active researchers from the scientific fields covered by arXiv was used. Data were collected over 21 days in September 2021 using a 40-question online survey. In addition to descriptive statistics, nonparametric statistical methods such as Pearson's chi-squared test for independence, Kruskal-Wallis' H-test and Mann-Whitney's U-test were applied to the collected data.

Among Slovenian scientists there is a wide range of different users of arXiv. The authors note differences among scientific disciplines. Physicists and astronomers are the most engaged, followed by mathematicians. Researchers in computer science, electrical engineering and systems science seem to have recognized the benefits of the archive, but are still hesitant to use it. Researchers from the other scientific fields participated in the survey to a lesser extent, suggesting that arXiv is less popular in these scientific fields. For Slovenian scientists, the main advantages of arXiv are faster access to knowledge, open access, greater impact of scientists' work and the fact that publishing in the archive is free of charge. A negative aspect of using the archive is the frustration caused by the difficulties in assessing the credibility of articles.

A voluntary sample was used, which attracted a larger number of researchers but has a higher risk of sampling bias.

The results are useful for international comparisons, but also provide bases and recommendations for institutional and national policies to evaluate researchers and their performance.

The results provide valuable insights into arXiv usage habits and the reasons for using or not using arXiv by Slovenian scientists. There is no comparable study conducted in Slovenia.

Strategic agility is a fuzzy concept that has become crucial to cope with environmental uncertainty and instability; hence, more in-depth studies are highly needed. The aim of this paper is to shed light on the still diffuse research area of strategic agility by clarifying its scope and concept, as well as identifying the different topics that have been examined thus far. Finally, the intent of this paper is to show the existing gaps in the literature to provide scholars with a clear roadmap for future research.

Bibliometric and content analyses are used in this study to review the most impactful papers in strategic agility between 1996 and 2021. Citation and mapping analyses are conducted through SciMAT software, and a dynamic approach is adopted by assessing and discussing the evolution of strategic agility throughout five different periods.

This study reveals that strategic agility is a research line that has neither gained consensus nor reached maturity and that it is linked to several thematic areas or topics. The study offers a complete understanding of the state of the art of strategic agility over time and underscores its main future research lines.

This study presents a complete map of the strategic agility research thus far by using novel bibliometric techniques. This approach is especially interesting because it allows for identifying the dynamic relationships among themes within the topic over five different periods.

策略靈活性是一個模糊概念。這個概念對應付環境的不確定性和不穩定性至為重要, 因此, 我們極須對其作更深入之研究。目前, 對策略靈活性的研究範圍仍很分散。本文擬為這研究範圍提供解說, 方法是透過闡釋策略靈活性的範疇和概念, 及確定至今曾被探討過的課題。最後、本文擬顯示目前文獻中的研究缺口, 以為學者提供一個未來研究的清晰藍圖 。

研究利用文獻計量分析法與內容分析法, 去審視1996年至2021年期間研究策略靈活性最有影響力的文章, 透過SciMAT可視化軟件進行引用文獻及繪圖分析, 亦採用動態方法, 去評估及討論橫跨五個不同時期策略靈活性的演變。

研究顯示、策略靈活性為一既無共識, 也未臻成熟的研究線; 研究亦顯示、策略靈活性與多個專題領域及主題相關連。本研究使我們對策略靈活性隨著時間推移的最新理念得到全面的理解, 研究亦強調了策略靈活性未來主要的研究線。

本研究透過新穎的文獻計量分析法, 提供了一個策略靈活性研究發展至今的完整藍圖。這方法至為有趣, 因其能確定橫跨五個不同時期、在同一課題下各個主題間的動態關係。

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

The purpose of this paper is to investigate the potential of altmetric and webometric indicators to aid with funding agencies’ evaluations of their funding schemes.

This paper analyses a range of altmetric and webometric indicators in terms of suitability for funding scheme evaluations, compares them to traditional indicators and reports some statistics derived from a pilot study with Wellcome Trust-associated publications.

Some alternative indicators have advantages to usefully complement scientometric data by reflecting a different type of impact or through being available before citation data.

The empirical part of the results is based on a single case study and does not give statistical evidence for the added value of any of the indicators.

A few selected alternative indicators can be used by funding agencies as part of their funding scheme evaluations if they are processed in ways that enable comparisons between data sets. Their evidence value is only weak, however.

This is the first analysis of altmetrics or webometrics from a funding scheme evaluation perspective.