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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.

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.

Every second, vast amounts of data are generated and stored on the Internet. Data scraping makes these data accessible and usable for business and scientific purposes. Web-scraped data are of high value to businesses as they can be used to inform many strategic decisions such as pricing or market positioning. Although it is not difficult to scrape data, particularly when they come from public websites, there are six key steps that analysts should ideally consider and follow. Following these steps can help to better harness the business value of online data.

DeLone and McLean (D&M) has been amongst the most widely used models to assess the success elements of information systems (IS) since 1992. A decade later in 2003, D&M proposed a revised design that included several components which have been left out of original proposed model. This study aims to rely on the review of a number of papers casing the era 2011–2022 that satisfies a specific set of requirements to identify the research gaps in this area and to prepare a future research agenda.

This study is a systematic review: a technique that identifies and evaluates pertinent research. This gathers and analyses data from selected studies with objective to catalogue all empirical research studies, which responds to a certain study topic or hypothesis to meets predetermined inclusion criteria. Data collection method was divided into four stages, and selection details are determined through flow chart.

This research discovered D&M 2003 model use in many contexts, countries and cultures to better comprehend the topic and addresses its gaps, particularly with regard to public sector and its particularities. Publications have frequently emphasized the significance of this idea while studying public sector information systems by using associated variables-related items. Findings also include a summary of key components and dimensions used in reviewed studies in relation to each of the seven variables, and associated particularities in government sector over the world.

To the best of the authors’ knowledge, this is the first ever effort in this developing country in discipline of Information Management to execute such kind of study to review D&M ISS model in detail at this stage to evaluate nonacademic public sector information systems around the world.

The purpose of this study is to provide a series of indicators to determine the limits to urban tourism growth, tourism gentrification and overtourism. The study addresses overtourism within the frame of urban liveability through a proxy analysis of tourism-relevant indicators for major European tourist cities.

Based on the various indicators, a composite overtourism indicator is derived. The following dimensions are considered for the composite indicator: total number of overnight stays per relevant tourist area in km²; number of museum visitors per population; average annual change in total nights between 2009 and 2017; and foreign nights per population.

Based on the results, Venice is the city with the highest degree of overtourism, followed by Florence, Seville and Lisbon. The remaining cities have a lower than average overtourism potential as indicated by the negative z-score.

This study and the composite overtourism indicators are only a starting point that can lead to further research in the field. Recommendations for further studies include the assessment of visitor flow and overtourism at different times of the year and to expand the study to other European urban destinations.

The paper suggests that policymakers should use these indicators when managing urban tourism development and monitoring visitor growth. Furthermore, they can be a starting point from which to assess the impact of tourism on the quality of life of local residents.

This study provides a starting point from which to assess the causes for social unrest tied to overtourism. If the city under study is found to have a lower than average overtourism potential, this indicates that there may be other social or psychological issues at play apart from sheer overcrowding.

To date, there has been no composite indicator that considered the different numerical aspects of overtourism altogether. This study provides a set of key indicators and a composite overtourism indicator to provide a preliminary appraisal of overtourism as a demand-side phenomenon with evidence from a range of established European urban destinations.

Sustainability issues are crucial in today’s competitive environment. The integration of technology plays a vital role in the attainment of sustainability objectives. The study aims to investigate the relationship between green intellectual capital (IC), green information systems (IS), green management initiatives (GMI) and green technology adoption in light of natural resource-orchestration theory (ROT). Moreover, digital technology adoption mediates between green IC, green IS, GMI and sustainable performance. Finally, digital transformation strategy is used as a moderator between green technology adoption and sustainable performance.

A sample of 484 managers from automobile manufacturing companies was used in this study to evaluate the proposed relationships using the Structural Equation Modeling (SEM) methodology.

Findings reveal that green IC, green IS and GMI significantly influence green technology adoption. Besides, green technology adoption plays a crucial role in improving sustainable performance. Moreover, green technology adoption significantly mediates between green IC, green IS, GMI and sustainable performance. Finally, a digital transformation strategy significantly strengthens the relationship between green technology adoption and sustainable performance.

The organizations need green technology adoption to address environmental concerns, respond to consumer demand, achieve cost savings and comply with government regulations. Besides, in decision-making, organizations must focus on green IC, green IS, GMI, green technology adoption and digital transformation strategy to boost sustainable performance.

The originality of this study lies in its use of the natural ROT as a framework to examine the impact of multiple green resources on green technology adoption, leading to sustainable performance. Digital transformation strategy is used as a moderator between green technology adoption and sustainable performance. This study provides a comprehensive and integrated perspective on the subject with empirical evidence and relevant insights, contributing to the advancement of the field.

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.

This paper aims to investigate the relationship between the level of subsidiaries’ internal and external relational embeddedness and the degree of subsidiaries’ knowledge transfer. More specifically, the aim is to explore dual embeddedness of subsidiaries involved in the knowledge transfer process within multinational corporations’ (MNCs) network.

The authors empirically analyse 165 European subsidiaries to demonstrate the crucial role of dual relational embeddedness in the transfer of knowledge within MNCs. Data were collected via a close-ended questionnaire and processed through an ordinary least squares regression model.

Results show that internal embeddedness directly and positively influences the degree of subsidiaries’ knowledge transfer, whereas external embeddedness does not. Notwithstanding, a higher level of both types of embeddedness – known as dual embeddedness – generates multiplicative and positive effects on the degree of subsidiaries’ knowledge transfer.

Best practices and relevant knowledge follow a reverse transfer of knowledge from the subsidiaries to the internal MNC network that is facilitated by the relational embeddedness of subsidiaries. This has resulted in developing a dual embeddedness, which introduces new routines and scripts, as well as more relational links.

The research emphasises the relevance of the knowledge transfer process in multiple directions, evoking the central role of dual-embedded subsidiaries.