The prevalence and impact of university affiliation discrepancies between four bibliographic databases – Scopus, Web of Science, Dimensions, and Microsoft Academic

Research managers benchmarking universities against international peers face the problem of affiliation disambiguation. Different databases have taken separate approaches to this problem and discrepancies exist between them. Bibliometric data sources typically conduct a disambiguation process that unifies variant institutional names and those of its sub-units so that researchers can then search all records from that institution using a single unified name. This study examined affiliation discrepancies between Scopus, Web of Science, Dimensions, and Microsoft Academic for 18 Arab universities over a five-year period. We confirmed that digital object identifiers (DOIs) are suitable for extracting comparable scholarly material across databases and quantified the affiliation discrepancies between them. A substantial share of records assigned to the selected universities in any one database were not assigned to the same university in another. The share of discrepancy was higher in the larger databases, Dimensions and Microsoft Academic. The smaller, more selective databases, Scopus and especially Web of Science tended to agree to a greater degree with affiliations in the other databases. Manual examination of affiliation discrepancies showed they were caused by a mixture of missing affiliations, unification differences, and assignation of records to the wrong institution. Peer Review https://publons.com/publon/10.1162/qss_a_00175

THE DECADES OF RESEARCH ON SCM AND ITS ADVANCEMENTS: COMPREHENSIVE FRAMEWORK

Supply Chain Management (SCM), a corporate strategy approach to materials and distribution management, has been evolving over the last decades from traditional marketing and production functions. The purpose of the study is to explore the bibliometric data of Supply Chain Management and its advancements. Besides, it describes from the origins of traditional SCM to the progress of modern SCM 4.0, with reference to the benefits, function, importance and limitations of all five branches of SCM. The methodology includes a detailed and systematic review of scientific articles published in Scopus indexed journals. The data were obtained from the Scopus database between 1990 and 2021 in order to achieve the study’s desired outcome. Boolean operators and filtering were applied to obtain relevant data. In addition, VOSviewer software is used to visually classify and analyse bibliometric data distribution and network using cluster maps. The study’s findings were divided into three main categories: publication period, coauthorship and citations, with the results demonstrating the diverse needs of SCM in the globalised digital era. Further, the results emphasise that SCM and its advancements have unique merits around the world, but Sustainable SCM and SCM 4.0 remain the most popular as they play a vital role in changing environmental concerns. In addition, the findings reveal that the visualization networks of each category exhibit the strengths and connections of publications. These visualization networks, followed by their analysis, explain the new insight to the present research. This research also paves the way for future research into the evolving trends of SCM in today’s technologically advanced world.

Suitability of scienciometric analysis targeting Loop Mediated Isothermal Amplification Assay applied to farm animals / Adequação da análise cienciométrica direcionada ao ensaio de Amplificação Isotérmica Mediada por Alça aplicada à animais de produção

The objective of the study was to carry out, with the aid of Scopus®️, a scientometric analysis of Loop Mediated Isothermal Amplification Assay (LAMP) applied to farm animals. The research has considered articles from January 2000 to December 2019 and only open or closed access articles published in English. The bibliometric matrices were run through RStudio, applying Biblioshiny as a web interface to Bibliometrix resources for R environment. Later, several bibliometric data were collected with the aid of Bibliometrix, most of which were converted into graphs using Microsoft Excel®️. The scientometric analysis base of the current study was composed by 438 articles from 504 researched in the Scopus®️. Of the 438 articles analyzed, it stands out as results: 1) the years of 2015 (11,4%) and 2019 (11,4%) had equally the highest number of publications in the area; 2) Journal of Virological Methods (12,5%) ranked first in the ranking of journals according to total articles published; 3) China (49,8%), Japan (12,7%) and India (7,1%) have been countries of more published articles; 4) most articles applied the assay to detect microorganisms affecting the farm animals; and, 5) together, the animal groups fish, bovine, poultry, and swine corresponded to 2/3 (71,1%) of the animals used in scientific research using the LAMP method. With all these results, it is concluded that the scientometric analysis showed an overview of the information in the articles about LAMP applied to farm animals.

Scholar Metrics Scraper (SMS): automated retrieval of citation and author data

Academic departments, research clusters and evaluators analyze author and citation data to measure research impact and to support strategic planning. We created a tool, Scholar Metrics Scraper (SMS), to automate the retrieval of this bibliometric data for our research team. The project contains Jupyter notebooks (publicly-shared here) that take a list of researchers as an input to export a CSV file of citation metrics from Google Scholar and figures to visualize the group's impact. SMS is a scalable, open and publicly-accessible solution for automating the retrieval of citation data over time for a group of researchers.

The Interview Method in Comparative Politics: The Process of Interviewing Far-Right Actors

Interviews have been the basis for some of the greatest insights in many disciplines but have largely been on the backstage of comparative political inquiry. I first rely on bibliometric data to show the limited use of interviews in research published by major journals in the past 30 years. I then focus on how interviews are used to study a hard-to-reach population: far-right actors. Using the extant literature and reflecting on my field experience with far-right leaders and functionaries, I examine in detail how interviews help investigate this phenomenon; I analyse challenges related to interview access, rapport, analysis and ethics and offer remedies. I argue that comparativists using interviews need to address these challenges by explicating and reflecting on the process through which they collect interview data rather than solely focusing on the data itself.

Why IEEE Xplore Matters for Research Trend Analysis in the Energy Sector

The paper aims to briefly compare and analyze the results of queries to IEEE Xplore and the leading abstract databases Scopus and Web of Science to identify research trends. Some errors were revealed in the Author Keywords in Web of Science. Therefore, a more detailed analysis that involved comparing various types of key terms was made only for IEEE Xplore and Scopus platforms. The study employed IEEE Access journal metadata as indexed on both platforms. Sample matching for IEEE Xplore and Scopus was achieved by comparing DOI. The IEEE Xplore metadata contains more key term types, which provides an advantage in analyzing research trends. Using NSPEC Controlled Terms from expert-compiled vocabulary provides more stable data, which gives an advantage when considering the change of terms over time. Apriori, an algorithm for finding association rules, was used to compare the co-occurrence of the terms for a more detailed description of sample subjects on both platforms. VOSviewer was used to analyze trends in scientific research based on IEEE Xplore data. The 2011-2021 ten-year period was divided into two sub-intervals for comparing the occurrence of Author Keywords, IEEE Terms, and NSPEC Controlled Terms. Bibliometric data of the IEEE conference proceedings was used to illustrate the importance of context in estimating the growth rate of publishing activity on a topic of interest.

An Exploratory Bibliometric Analysis of the Birth and Emergence of Industry 5.0

This study provides an exploratory bibliometric analysis of the emerging literature on Industry 5.0, which is a new visionary concept on the future of industry. Industry 5.0 has in recent years begun to attract the interest of both practitioners and academics, but this new field can still be considered embryonic and not well documented. Therefore, this study aims to map the field and provide a preliminary picture of the emergence and status of the scientific literature on Industry 5.0. Bibliometric data covering the period from 2015 to 2021 were extracted from the Scopus database. Bibliometric analyses of overall publication volume and growth trajectory, influential documents, authors, sources and countries are performed. The exploratory analysis provides a preliminary overview of the birth and emergence of this new research area. The results are discussed in relation to theories on the emergence and evolution of new management concepts. The article closes with some speculations about the future trajectory of Industry 5.0.

Models for maintenance planning and scheduling – a citation-based literature review and content analysis

PurposeThe findings of this study have lightened the focal research areas in maintenance planning and scheduling. These also served as effective guidelines for future studies in this area. This research, therefore, contributes in fulfilling the gap by carrying out an SLR of contemporary research studies in the area of models for maintenance planning and scheduling. At present, SLR rooted in BA has not been carried focusing on a survey over models for maintenance planning and scheduling. SLR uses advanced scientific methodologies from BA tools to unveil thematic structures.Design/methodology/approachWe have systematically reviewed over 1,021 peer-reviewed journal articles. Advanced contemporary tools from Bibliometric Analysis (BA) are used to perform a Systematic Literature Review (SLR). First, exploratory analysis is presented, highlighting the influential authors, sources and region amongst other key indices. Second, the large bibliographical data is visualized using co-citation network analyses, and research clusters (themes) are identified. The co-citation network is extended into a dynamic co-citation network and unveils the evolution of the research clusters. Last, cluster-based content analysis and historiographical analysis is carried out to predict the prospect of future research studies.FindingsBA tools first outlined an exploratory analysis that noted influential authors, production countries, top-cited papers and frequent keywords. Later, the bibliometric data of over 1,021 documents is visualized using co-citation network analyses. Later, a dynamic co-citation analysis identified the evolution of research clusters over time. A historiographical direct citation analysis also unveils potential research directions. We have clearly observed that there are two main streams of maintenance planning and scheduling applications. The first has focused on joint maintenance and operations on machines. The second focused on integrated production and maintenance models in an echelon setting for unrealizable production facilities.Originality/valueThere are many literature review-based research studies that have contributed to maintenance scheduling research surveys. However, most studies have adopted traditional approaches, which often fall short in handling large bibliometric data and therefore suffer from selection biases from the authors. As a result, in this area, the existing reviews could be non-comprehensive. This study bridges the research gap by conducting an SLR of maintenance models, which to the best of our knowledge, has not been carried out before this study.