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This study aims to analyse and evaluate the methodology followed by the Times Higher Education Impact Rankings (THE-IR), as well as the coverage obtained and the data offered by this ranking, to determine if its methodology reflects the degree of sustainability of universities, and whether their results are accurate enough to be used as a data source for research and strategic decision-making.

A summative content analysis of the THE-IR methodology was conducted, paying special attention to the macro-structure (university score) and micro-structure (sustainable development goals [SDG] score) levels of the research-related metrics. Then, the data published by THE-IR in the 2019, 2020 and 2021 edition was collected via web scraping. After that, all the data was statistically analysed to find out performance rates, SDGs’ success rates and geographic distributions. Finally, a pairwise comparison of the THE-IR against the Times Higher Education World University Rankings (THE-WUR) was conducted to calculate overlap measures.

Severe inconsistencies in the THE-IR methodology have been found, offering a distorted view of sustainability in higher education institutions, allowing different strategic actions to participate in the ranking (interested, strategic, committed and outperformer universities). The observed growing number of universities from developing countries and the absence of world-class universities reflect an opportunity for less-esteemed institutions, which might have a chance to gain reputation based on their efforts towards sustainability, but from a flawed ranking which should be avoided for decision-making.

University managers can be aware of the THE-IR validity when demanding informed decisions. University ranking researchers and practitioners can access a detailed analysis of the THE-IR to determine its properties as a ranking and use raw data from THE-IR in other studies or reports. Policy makers can use the main findings of this work to avoid misinterpretations when developing public policies related to the evaluation of the contribution of universities to the SDGs. Otherwise, these results can help the ranking publisher to improve some of the inconsistencies found in this study.

Given the global audience of the THE-IR, this work contributes to minimising the distorted vision that the THE-IR projects about sustainability in higher education institutions, and alerts governments, higher education bodies and policy makers to take precautions when making decisions based on this ranking.

To the best of the authors’ knowledge, this contribution is the first providing an analysis of the THE-IR’s methodology. The faults in the methodology, the coverage at the country-level and the overlap between THE-IR and THE-WUR have unveiled the existence of specific strategies in the participation of universities, of interest both for experts in university rankings and SDGs.

The purpose of this paper is to determine the effect of the chosen search engine results page (SERP) on the website-specific hit count estimation indicator.

A sample of 100 Spanish rare disease association websites is analysed, obtaining the website-specific hit count estimation for the first and last SERPs in two search engines (Google and Bing) at two different periods in time (2016 and 2017).

It has been empirically demonstrated that there are differences between the number of hits returned on the first and last SERP in both Google and Bing. These differences are significant when they exceed a threshold value on the first SERP.

Future studies considering other samples, more SERPs and generating different queries other than website page count (<site>) would be desirable to draw more general conclusions on the nature of quantitative data provided by general search engines.

Selecting a wrong SERP to calculate some metrics (in this case, website-specific hit count estimation) might provide misleading results, comparisons and performance rankings. The empirical data suggest that the first SERP captures the differences between websites better because it has a greater discriminating power and is more appropriate for webometric longitudinal studies.

The findings allow improving future quantitative webometric analyses based on website-specific hit count estimation metrics in general search engines.

The website-specific hit count estimation variability between SERPs has been empirically analysed, considering two different search engines (Google and Bing), a set of 100 websites focussed on a similar market (Spanish rare diseases associations), and two annual samples, making this study the most exhaustive on this issue to date.

Google Scholar Citations (GSC) provides an institutional affiliation link which groups together authors who belong to the same institution. The purpose of this paper is to ascertain whether this feature is able to identify and normalize all the institutions entered by the authors, and whether it is able to assign all researchers to their own institution correctly.

Systematic queries to GSC’s internal search box were performed under two different forms (institution name and institutional e-mail web domain) in September 2015. The whole Spanish academic system (82 institutions) was used as a test. Additionally, specific searches to companies (Google) and world-class universities were performed to identify and classify potential errors in the functioning of the feature.

Although the affiliation tool works well for most institutions, it is unable to detect all existing institutions in the database, and it is not always able to create a unique standardized entry for each institution. Additionally, it also fails to group all the authors who belong to the same institution. A wide variety of errors have been identified and classified.

Even though the analyzed sample is good enough to empirically answer the research questions initially proposed, a more comprehensive study should be performed to calibrate the real volume of the errors.

The discovered affiliation link errors prevent institutions from being able to access the profiles of all their respective authors using the institutions lists offered by GSC. Additionally, it introduces a shortcoming in the navigation features of Google Scholar which may impair web user experience.

Some institutions (mainly universities) are under-represented in the affiliation feature provided by GSC. This fact might jeopardize the visibility of institutions as well as the use of this feature in bibliometric or webometric analyses.

This work proves inconsistencies in the affiliation feature provided by GSC. A whole national university system is systematically analyzed and several queries have been used to reveal errors in its functioning. The completeness of the errors identified and the empirical data examined are the most exhaustive to date regarding this topic. Finally, some recommendations about how to correctly fill in the affiliation data (both for authors and institutions) and how to improve this feature are provided as well.

Title and URL mentions have recently been proposed as web visibility indicators instead of inlink counts. The objective of this study is to determine the accuracy of these alternative web mention indicators in the Spanish academic system, taking into account their complexity (multi-domains) and diversity (different official languages).

Inlinks, title and URL mentions from 76 Spanish universities were manually extracted from the main search engines (Google, Google Scholar, Yahoo!, Bing and Exalead). Several statistical methods, such as correlation, difference tests and regression models, were used.

Web mentions, despite some limitations, can be used as substitutes for inlinks in the Spanish academic system, although these indicators are more likely to be influenced by the environment (language, web domain policy, etc.) than inlinks.

Title mentions provide unstable results caused by the multiple name variants which an institution can present (such as acronyms and other language versions). URL mentions are more stable, but they may present atypical points due to some shortcomings, the effect of which is that URL mentions do not have the same meaning as inlinks.

Web mentions should be used with caution and after a cleaning-up process. Moreover, these counts do not necessarily signify connectivity, so their use in global web analysis should be limited.

Web mentions have previously been used in some specific academic systems (US, UK and China), but this study analyses, in depth and for the first time, an entire non-English speaking European country (Spain), with complex academic web behaviour, which helps to better explain previous web mention results.

The purpose of this paper is to detect whether both file type (a set of rich and web files) and language (English, Spanish, German, French and Italian) influence the web visibility of European universities.

A webometrics analysis of the top 200 European universities (as ranked in the Ranking web of World Universities) was carried out by a manual query for each official URL identified by using the Google search engine (April 2012). A correlation analysis between visibility and file format page count is offered according to language. Finally, a prediction of visibility is shown by using the SMOreg function.

The results indicate that Spanish and English are the languages that correlate most highly with web visibility. This correlation becomes greater – though moderate – when considering only PDF files.

The results are limited due to the low correlation between overall page count and visibility. The lack of an accurate search engine that would assist in link counting procedures makes this process difficult.

An observed increase in correlation – although moderate – while analysing PDF files (in English and Spanish) is considered to be meaningful. This may indirectly confirm that specific file formats and languages generate different web visibility behaviour on European university web sites.

The purpose of this paper is to describe the obsolescence process of Microsoft Academic Search (MAS) as well as the effects of this decline in the coverage of disciplines and journals, and their influence in the representativeness of organizations.

The total number of records and those belonging to the most reputable journals (1,762) and organizations (346) according to the Field Rating indicator in each of the 15 fields and 204 sub-fields of MAS, have been collected and statistically analysed in March 2014, by means of an automated querying process via http, covering academic publications from 1700 to present.

MAS has no longer been updated since 2013, although this phenomenon began to be glimpsed in 2011, when its coverage plummeted. Throughout 2014, indexing of new records is still ongoing, but at a minimum rate, without following any apparent pattern.

There are also retrospective records being indexed at present. In this sense, this research provides a picture of what MAS offered during March 2014 being queried directly via http.

The unnoticed obsolescence of MAS affects to the quality of the service offered to its users (both those who engage in scientific information seeking and also those who use it for quantitative purposes).

The predominance of Google Scholar (GS) as monopoly in the academic search engines market as well as the prevalence of an open construction model (GS) vs a closed model (MAS).

A complete longitudinal analysis of disciplines, journals and organizations on MAS has been performed for the first time identifying an unnoticed obsolescence. Any public explanation or disclaimer note has been announced from the responsible company, something incomprehensible given its implications for the reliability and validity of bibliometric data provided on disciplines, journals, authors and congress as well as their fair representation on the academic search engine.

It is common for an international company to have different brands, products or services, information for investors, a corporate blog, affiliates, branches in different countries, etc. If all these contents appear as independent additional web domains (AWDs), the company should be represented on the web by all these web domains, since many of these AWDs may acquire remarkable performance that could mask or distort the real web performance of the company, affecting therefore on the understanding of web metrics. The purpose of this paper is to determine the amount, type, web impact and topology of the AWDs in commercial companies in order to get a better understanding on their complete web impact and structure.

The set of companies belonging to the Spanish IBEX-35 stock index has been analysed as testing bench. The authors proceeded to identify and categorise all AWDs belonging to these companies, and to apply both web impact (web presence and visibility) and network metrics.

The results show that AWDs get a high web presence but relatively low web visibility, due to certain opacity or less dissemination of some AWDs favoring its isolation. This is verified by the low network density values obtained, that occur because AWDs are strongly connected with the corporate domain (although asymmetrically), but very weakly linked each other.

The categories used to classify the various AWD, although they are clearly distinguishable conceptually, have certain limitations in practice, since they depend on the form adopted by companies to publish certain content or to provide certain services or products. Otherwise, the use of web indicators presents certain problems of accuracy that could be softened if applied with caution and in a relational basis.

Although the processes of AWDs creation and categorisation are complex (web policy seems not to be driven by a defined or conscious plan), their influence on the web performance of IBEX 35 companies is meaningful. This research measures the AWDs influence on companies under webometric terms for the first time.

This paper aims to assess the impact of research in the field of scientometrics by using the altmetrics (social media metrics) approach.

This is an applied study which uses scientometric and altmetrics methods. The research population consists of the studies and their citations published in the two core journals (Scientometrics and Journal of Informetrics) in a period of five years (included 1,738 papers and 11,504 citations). Collecting and extracting the studies directly was carried from Springer and ScienceDirect databases. The Altmetric Explorer, a service provided by Altmetric.com, was used to collect data on studies from various sources (www.altmetric.com/). The research studies with the altmetric scores were identified (included 830 papers). The altmetric scores represent the quantity and quality of attention that the study has received on social media. The association between altmetric scores and citation indicators was investigated by using correlation tests.

The findings indicated a significant, positive and weak statistical relationship between the number of citations of the studies published in the field of scientometrics and the altmetric scores of these studies, as well as the number of readers of these studies in the two social networks (Mendeley and Citeulike) with the number of their citations. In this study, there was no statistically significant relationship between the number of citations of the studies and the number of readers on Twitter. In sum, the above findings suggest that some social networks and their indices can be representations of the impact of scientific papers, similar citations. However, owing to the weakness of the correlation coefficients, the replacement of these two categories of indicators is not recommended, but it is possible to use the altmetrics indicators as complementary scientometrics indicators in evaluating the impact of research.

Investigating the impact of research on social media can reflect the social impact of research and can also be useful for libraries, universities, and research organizations in planning, budgeting, and resource allocation processes.

With the development of Web2.0 and publishing digitalization, traditional libraries and evaluation citation system can no longer indicate academic paper influence validly. Therefore, it is necessary to construct smart library and find the evaluation effect of Internet metrics-Usage.

This study puts forward four indexes of scholars’ evaluation based on Usage (total Usage (U), average Usage rate (U/N), h_u-index and p_u-index), which refer to citation indexes, takes the 35 high-output scholars in the field of library and information science in the WoS database as examples, analyzes performance of different scholars evaluation indexes based on Usage and compares the differences and correlations between “citation indicators” and “usage indicators.”

This study results show that p_u-index is the strongest index to evaluate scholars. Second, there is a high correlation and strong mechanism based on time dependence and interactions between Usage and citation. Third, compared to “citation indicators”, the “usage indicators” has a larger numerical value and wider measurement range, which can break the time limitation of citation, and scientifically evaluate young scholars and newly published paper by scholars.

This paper proposes the p_u-index – a relatively superior mathematical model for Usage and provides reference for the scholars’ evaluation policy of the smart library. This model can not only provide fair evaluation conditions for young scientists but also shorten the evaluation effect of the time lag of cited indicators. In addition, the “usage indicators” in this paper are new scientific evaluation indicators generated in the network environment. Applying it to the academic evaluation system will make the research papers widely accepted by the public and will also encourage scientists to follow the development of the Internet age and pursue research with equal emphasis on quantity and quality.

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。