3,569 research outputs found

    Software tools for conducting bibliometric analysis in science: An up-to-date review

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    Bibliometrics has become an essential tool for assessing and analyzing the output of scientists, cooperation between universities, the effect of state-owned science funding on national research and development performance and educational efficiency, among other applications. Therefore, professionals and scientists need a range of theoretical and practical tools to measure experimental data. This review aims to provide an up-to-date review of the various tools available for conducting bibliometric and scientometric analyses, including the sources of data acquisition, performance analysis and visualization tools. The included tools were divided into three categories: general bibliometric and performance analysis, science mapping analysis, and libraries; a description of all of them is provided. A comparative analysis of the database sources support, pre-processing capabilities, analysis and visualization options were also provided in order to facilitate its understanding. Although there are numerous bibliometric databases to obtain data for bibliometric and scientometric analysis, they have been developed for a different purpose. The number of exportable records is between 500 and 50,000 and the coverage of the different science fields is unequal in each database. Concerning the analyzed tools, Bibliometrix contains the more extensive set of techniques and suitable for practitioners through Biblioshiny. VOSviewer has a fantastic visualization and is capable of loading and exporting information from many sources. SciMAT is the tool with a powerful pre-processing and export capability. In views of the variability of features, the users need to decide the desired analysis output and chose the option that better fits into their aims

    Human Resource Management and Artificial Intelligence: A Bibliometric Exploration

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    The concept of artificial intelligence, a driving force behind human resource management, has recently gained popularity in the academic community. This study explores the intellectual structure of this field using the Scopus database in the subject area of business, management and accounting. Bibliographic analysis, a recent and rigorous method for delving into scientific data, is used in this investigation. The approach used is a structured and transparent process divided into four steps: (1) search criteria; (2) selection of database and documents; (3) selection of software and data pre-processing; and (4) analysis of findings. We employ bibliometric mapping to observe their numerous linkages and performance evaluation to learn about their structure. A total of 67 articles were collected from the Scopus database between 2015 and 2022 using certain keywords (artificial intelligence, expert systems, big data analytics, and human resource management) and some specific filters (subject–business, management and accounting; language-English; document–article, review articles and source-journals). Ten research clusters were identified: Cluster 1: multi-agent system; Cluster 2: decision support system; Cluster 3: internet of things; Cluster 4: active learning; Cluster 5: decision tree; Cluster 6: optimisation; Cluster 7: software design; Cluster 8: data mining; Cluster 9: cloud computing; Cluster 10: human-robot interaction. The findings could be helpful for researchers and practitioners in the HRM field to extend their knowledge and understanding of AI and HRM research. This study can provide notable guidance and future directions for quite a few firms in expanding the use of AI in HRM. Keywords: Artificial intelligence, human resource management, bibliometric analysi

    Internet of things: Conceptual network structure, main challenges and future directions

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    Internet of Things (IoT) is a key technology trend that supports our digitalized society in applications such as smart countries and smart cities. In this study, we investigate the existing strategic themes, thematic evolution structure, key challenges, and potential research opportunities associated with the IoT. For this study, we conduct a Bibliometric Performance and Network Analysis (BPNA), supplemented by an exhaustive Systematic Literature Review (SLR). Specifically, in BPNA, the software SciMAT is used to analyze 14,385 documents and 30,381 keywords in the Web of Science (WoS) database, which was released between 2002 and 2019. The results reveal that 31 clusters are classified according to their importance and development, and the conceptual structures of key clusters are presented, along with their performance analysis and the relationship with other subthemes. The thematic evolution structure describes the important cluster(s) over time. For the SLR, 23 documents are analyzed. The SLR reveals key challenges and limitations associated with the IoT. We expect the results will form the basis of future research and guide decision-making in the IoT and other supporting industries.Coordenaç~ao de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) - Finance Code 001 and the Spanish Ministry of Science and Innovation under grants PID2019-105381 GA-100 (iScience)Consejo Nacional de Ciencia y Tecnología (CONACYT) and Direcci on General de Relaciones Exteriores (DGRI

    Supply Chain in Library: A Bibliometric Analysis

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    The research objective of this paper is to identify and map supply chain research in a library. This study conducted a bibliometric analysis using the Scopus electronic database. The article search is done by filtering search results in the system and manual exploration to get relevant articles. The collected articles are processed with the VOSviewer application to obtain research mapping results. A total of 81 articles were obtained from 1999 to 2021, with an increasing trend in the number of articles each year. The United States and China are the most productive countries in this field. Three cluster topics were obtained: supply chain integration in digital libraries, the benefits of open source applications in libraries, and digital data issues in libraries. The results of this study provide an additional overview of supply chain mapping in libraries

    Comparative Analysis of Web of Science and Scopus on the Energy Efficiency and Climate Impact of Buildings

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    Although the body of scientific publications on energy efficiency and climate mitigation from buildings has been growing quickly in recent years, very few previous bibliometric analysis studies exist that analyze the literature in terms of specific content (trends or options for zero‐energy buildings) or coverage of different scientific databases. We evaluate the scientific literature published since January 2013 concerning alternative methods for improving the energy efficiency and mitigating climate impacts from buildings. We quantify and describe the literature through a bibliometric approach, comparing the databases Web of Science (WoS) and Scopus. A total of 19,416 (Scopus) and 17,468 (WoS) publications are analyzed, with only 11% common documents. The literature has grown steadily during this time period, with a peak in the year 2017. Most of the publications are in English, in the area of Engineering and Energy Fuels, and from institutions from China and the USA. Strong links are observed between the most published authors and institutions worldwide. An analysis of keywords reveals that most of research focuses on technologies for heating, ventilation, and air‐conditioning, phase change materials, as well as information and communication technologies. A significantly smaller segment of the literature takes a broader perspective (greenhouse gas emissions, life cycle, and sustainable development), investigating implementation issues (policies and costs) or renewable energy (solar). Knowledge gaps are detected in the areas of behavioral changes, the circular economy, and some renewable energy sources (geothermal, biomass, small wind). We conclude that i) the contents of WoS and Scopus are radically different in the studied fields; ii) research seems to focus on technological aspects; and iii) there are weak links between research on energy and on climate mitigation and sustainability, the latter themes being misrepresented in the literature. These conclusions should be validated with further analyses of the documents identified in this study. We recommend that future research focuses on filling the above identified gaps, assessing the contents of several scientific databases, and extending energy analyses to their effects in terms of mitigation potentials.This work was funded by the Ministerio de Ciencia, Innovación y Universidades de España (RTI2018‐ 093849‐B‐C31), by ICREA under the ICREA Academia programme, and by the foundation SIVL

    Lean Supply Chain Management: Insights from bibliometric analysis and literature review

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    The covid-19 pandemic has impacted many countries and with it arose a growing concern of organizations about the vulnerability and low resilience of global supply chains. The incorporation of lean manufacturing in the supply chains enables the systematic reduction of activities that do not add value in an organization and within a chain could improve business performance, which can be widely extended between areas. Thus, this paper aims to investigate the advancement of knowledge about the lean supply chain through bibliometric indicators of scientific production and literature review. Among the research results, the number of publications increased over the years (1996-2021), and the countries that published the most on the topic are Brazil (46 documents), Malaysia (42), and the United States of America (40). The most applied tool was the Value Stream Mapping (VSM). As for future research, there is a need to propose more applied and comprehensive research; study the impact of lean on the supply chain; evaluate the Lean Supply Chain implementation process, and study the relationship between sustainability and Lean Supply Chain Management

    Science Models as Value-Added Services for Scholarly Information Systems

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    The paper introduces scholarly Information Retrieval (IR) as a further dimension that should be considered in the science modeling debate. The IR use case is seen as a validation model of the adequacy of science models in representing and predicting structure and dynamics in science. Particular conceptualizations of scholarly activity and structures in science are used as value-added search services to improve retrieval quality: a co-word model depicting the cognitive structure of a field (used for query expansion), the Bradford law of information concentration, and a model of co-authorship networks (both used for re-ranking search results). An evaluation of the retrieval quality when science model driven services are used turned out that the models proposed actually provide beneficial effects to retrieval quality. From an IR perspective, the models studied are therefore verified as expressive conceptualizations of central phenomena in science. Thus, it could be shown that the IR perspective can significantly contribute to a better understanding of scholarly structures and activities.Comment: 26 pages, to appear in Scientometric

    Information Technology Adoption on Digital Marketing: A Literature Review

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    Data generation is currently expanding at an astonishing pace, and the function of marketing is becoming increasingly sophisticated and customized. Companies seek to understand their internal corporate environment and externalities and to exponentially enhance their marketing power. This study aims to understand the influence of Big data analysis on digital marketing. The methodologies used to approach this issue were: (a) a systematic literature review based on articles dated between 2014 and 2020; and (b) a bibliometric analysis of articles dated between 2000 and 2020 using the software VOSviewer. The literature review allowed us to conclude that in the next decades, the business world in general, and marketing in particular, will define more oriented strategies based on a more profound knowledge of consumer behavior. Artificial intelligence agents driven by machine learning methods, technology, and Big data will be a conditioning factor in defining these strategiesinfo:eu-repo/semantics/publishedVersio

    Green BPM as a business-oriented discipline : a systematic mapping study and research agenda

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    Green Business Process Management (BPM) focuses on the ecological impact of business processes. This article provides a systematic mapping study of Green BPM literature to evaluate five attributes of the Green BPM research area: (1) scope, (2) disciplines, (3) accountability, (4) researchers and (5) quality control. The results allow developing a research agenda to enhance Green BPM as an approach for environmentally sustainable organizations. We rely on a dichotomy of knowledge production to present research directives relevant for both academics and practitioners in order to help close a rigor-relevance gap. The involvement of both communities is crucial for Green BPM to advance as an applied, business-oriented discipline

    Towards A Taxonomy of Emerging Topics in Open Government Data: A Bibliometric Mapping Approach

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    The purpose of this paper is to capture the emerging research topics in Open Government Data (OGD) through a bibliometric mapping approach. Previous OGD research has covered the evolution of the discipline with the application of bibliometric mapping tools. However, none of these studies have extended the bibliometric mapping approach for taxonomy building. Realizing this potential, we used a bibliometric tool to perform keyword analysis as a foundation for taxonomy construction. A set of keyword clusters was constructed, and qualitative analysis software was used for taxonomy creation. Emerging topics were identified in a taxonomy form. This study contributes towards the development of an OGD taxonomy. This study contributes to the procedural realignment of a past study by incorporating taxonomy building elements for taxonomy creation. These contributions are significant because there is insufficient taxonomy research in the OGD discipline. The taxonomy building procedures extended in this study are applicable to other fields
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