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1 – 10 of 333
Article
Publication date: 12 February 2024

Hamid Reza Saeidnia, Elaheh Hosseini, Shadi Abdoli and Marcel Ausloos

The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the…

Abstract

Purpose

The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.

Design/methodology/approach

By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.

Findings

(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.

Originality/value

This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 17 July 2023

Anaile Rabelo, Marcos W. Rodrigues, Cristiane Nobre, Seiji Isotani and Luis Zárate

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

Abstract

Purpose

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

Design/methodology/approach

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

Findings

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

Originality/value

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

Details

Information Discovery and Delivery, vol. 52 no. 2
Type: Research Article
ISSN: 2398-6247

Keywords

Open Access
Article
Publication date: 28 July 2020

Julián Monsalve-Pulido, Jose Aguilar, Edwin Montoya and Camilo Salazar

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently…

1792

Abstract

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

Details

Applied Computing and Informatics, vol. 20 no. 1/2
Type: Research Article
ISSN: 2634-1964

Keywords

Article
Publication date: 14 February 2022

Helio Aisenberg Ferenhof, Andrei Bonamigo, Louise Generoso Rosa and Thiago Cerqueira Vieira

Knowledge is companies’ crucial asset, especially when they are inserted in continuous collaboration and value co-creation. However, problems related to knowledge may occur…

Abstract

Purpose

Knowledge is companies’ crucial asset, especially when they are inserted in continuous collaboration and value co-creation. However, problems related to knowledge may occur without proper management, which can compromise the strategic objectives associated with a business collaboration network. Given the presented gap, this study aims to propose and test a business-to-business (B2B) knowledge management (KM) framework focused on value co-creation. Therefore, this study seeks to answer the following guiding questions: what are the main elements that a KM model should present in a context of value co-creation between companies? What are the limitations? What are the advantages and disadvantages? Is there any group that would benefit most from it?

Design/methodology/approach

This is an exploratory study grounded on mixed methods, having a qualitative approach (systematic literature review and content analysis) followed by a quantitative approach (exploratory and confirmatory factor analysis), which grounded the proposed framework.

Findings

The qualitative approach grounded on the systematic literature review resulting in 38 articles that were submitted to content analysis, which resulted in six record units: active communication between the organization, employees and other stakeholders; documents and organizational knowledge stored; knowledge map; collaborative network; searching tools and database, which provided the KM elements to develop and test the proposed framework by the quantitative approach. The results have shown that the framework may assist in managing knowledge in B2B value co-creation relationships.

Research limitations/implications

As an exploratory study, the chosen research approach used nonprobabilistic for convenience sampling. Therefore, the results may lack generalizability. Thus, researchers are encouraged to use probabilistic sampling techniques to ensure generability. Also, more and better items should be used to upgrade the initial questionnaire, improving it and, by doing so, have a better scale.

Practical implications

Assuming the proposed framework’s effectiveness, company managers can use it to drive knowledge within the network of interested parties to promote cooperative products and services. In addition, due to the theoretical framework’s broad vision, it can serve as a strategic aid to leverage innovation, productivity and competitive advantage. This study also provides an initial instrument that assists in understanding KM elements, which may assist in value co-creation.

Originality/value

It was learned that the elements, tools, concepts and KM preconized solutions can assist in value co-creation. Considering that value assists business performance, and value co-creation is one way to enhance it, furthermore, by knowledge sharing, the value co-creation may occur in the B2B ecosystem. Also, it is the first theoretical KM framework proposed to assist companies to understand better ways that could get advantages on structuring knowledge, meaning mapping it, sharing it through a system that can retain what is needed and release it to the ones that need and have the defined access to receive it.

Details

VINE Journal of Information and Knowledge Management Systems, vol. 54 no. 2
Type: Research Article
ISSN: 2059-5891

Keywords

Article
Publication date: 19 December 2022

Sukjin You, Soohyung Joo and Marie Katsurai

The purpose of this study is to explore to which extent data mining research would be associated with the library and information science (LIS) discipline. This study aims to…

Abstract

Purpose

The purpose of this study is to explore to which extent data mining research would be associated with the library and information science (LIS) discipline. This study aims to identify data mining related subject terms and topics in representative LIS scholarly publications.

Design/methodology/approach

A large set of bibliographic records over 38,000 was collected from a scholarly database representing the fields of LIS and the data mining, respectively. A multitude of text mining techniques were applied to investigate prevailing subject terms and research topics, such as influential term analysis and Dirichlet multinomial regression topic modeling.

Findings

The findings of this study revealed the relationship between the LIS and data mining research domains. Various data mining method terms were observed in recent LIS publications, such as machine learning, artificial intelligence and neural networks. The topic modeling result identified prevailing data mining related research topics in LIS, such as machine learning, deep learning, big data and among others. In addition, this study investigated the trends of popular topics in LIS over time in the recent decade.

Originality/value

This investigation is one of a few studies that empirically investigated the relationships between the LIS and data mining research domains. Multiple text mining techniques were employed to delineate to which extent the two research domains would be associated with each other based on both at the term-level and topic-level analysis. Methodologically, the study identified influential terms in each domain using multiple feature selection indices. In addition, Dirichlet multinomial regression was applied to explore LIS topics in relation to data mining.

Details

Aslib Journal of Information Management, vol. 76 no. 1
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 26 March 2024

Md. Nurul Islam, Guangwei Hu, Murtaza Ashiq and Shakil Ahmad

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of…

Abstract

Purpose

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

Design/methodology/approach

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

Findings

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

Originality/value

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 9 October 2023

Chih-Ming Chen and Ya-Chu Yang

A makerspace has recently been identified as an essential learning field for cultivating students’ creative and thinking abilities. Creating a makerspace service within a…

Abstract

Purpose

A makerspace has recently been identified as an essential learning field for cultivating students’ creative and thinking abilities. Creating a makerspace service within a university library is vital, as it fosters innovation, interdisciplinary learning, practical skills, entrepreneurship and career readiness while transforming the library into a dynamic centre for hands-on education and collaboration. Nevertheless, the wide-ranging functions and uses of makerspace equipment can potentially lead to a situation where librarians are overwhelmed by their duties due to manpower constraints. Therefore, this study aims to develop a novel game-based augmented reality navigation system (GARNS) based on the Octalysis gamification framework and scaffolding theory to support makerspace user education, hoping to promote learners’ learning motivation and their immersive experience and to enhance the learning performance of makerspace user education.

Design/methodology/approach

With a true experimental research method, 24 grade 11 students from a high school in Keelung City, Taiwan, were recruited to participate in the experiment on makerspace user education. Among them, ten students were randomly assigned to the experimental group using the GARNS and the other seven students were randomly assigned to a control group using the Web navigation system. The remaining seven students were assigned to a second control group using the narrative guided tour with a librarian to conduct makerspace user education.

Findings

Analytical results show that learners can achieve significant learning effectiveness using the GARNS, Web navigation system or traditional narrative guided tour with a librarian for makerspace user education. There were no significant differences in learning effectiveness and motivation neither between the GARNS group and the narrative guided tour with a librarian group nor between the Web navigation system group and the narrative guided tour with a librarian group. However, there were significant differences in learning effectiveness and motivation in terms of the value and expectation dimensions of learning motivation between the GARNS group and the Web navigation system group, and the GARNS group was significantly better than the Web navigation system group.

Practical implications

The study’s practical implication on makerspace user education is to reduce the manpower of a university library with makerspace services by the proposed GARNS that can offer a practical solution to enhance the learning effectiveness and motivation of makerspace through immersive game-based autonomous learning. Additionally, the study’s theoretical contribution lies in its innovative combination of game-based learning and scaffolding theory, while its practical significance stems from its potential to revolutionize makerspace user education, enhance motivation and performance and influence the broader landscape of educational technology.

Originality/value

This study combines game-based learning with augmented reality tools to develop a novel GARNS, which provides an innovative and effective learning tool suitable for the characteristics of makerspace and contributes to promoting makerspace user education and diversified learning modes. Additionally, most interviewees believed that using GARNS for educating makerspace users could assist them in consistently evaluating, choosing and discovering educational tasks in a library makerspace. This study contributes to promoting the popularization of makerspace user education.

Details

The Electronic Library , vol. 42 no. 1
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 6 June 2023

Cynthia Weiyi Cai, Rui Xue and Bi Zhou

This study reviews existing cryptocurrency research to provide answers to three puzzles in the literature. First, is cryptocurrency more like gold (i.e., a commodity) or should…

Abstract

Purpose

This study reviews existing cryptocurrency research to provide answers to three puzzles in the literature. First, is cryptocurrency more like gold (i.e., a commodity) or should it be classified as a new financial asset? Second, can we apply our knowledge of the traditional capital market to the emerging cryptocurrency market? Third, what might be the future of cryptocurrency?

Design/methodology/approach

Bibliometric analysis is used to assess 2,098 finance-related cryptocurrency publications from the Web of Science (WoS) Core Collection database from January 2009 to April 2022. Three key research streams are identified, namely, (1) cryptocurrency features, (2) behaviour of the cryptocurrency market and (3) blockchain implications.

Findings

First, cryptocurrency should be viewed and regulated as a new asset class rather than a currency or a new commodity. While it can provide diversification benefits to the portfolio, cryptocurrency cannot work as a safe haven asset. Second, crypto markets are typically inefficient. Asset bubbles exist and are exacerbated by behavioural finance factors. Third, cryptocurrency demonstrates increasing potential as a medium of exchange and store of value.

Originality/value

Extant review papers primarily study one or two particular research topics, overlooking the interaction between topics. The few existing systematic literature reviews in this area typically have a narrow focus on trend identification. This study is the first study to provide a comprehensive review of all financial-related studies on cryptocurrency, synthesising the research findings from 2,098 publications to answer three cryptocurrency puzzles.

Details

Journal of Accounting Literature, vol. 46 no. 1
Type: Research Article
ISSN: 0737-4607

Keywords

Open Access
Article
Publication date: 13 February 2024

Ke Zhang and Ailing Huang

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user…

Abstract

Purpose

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.

Design/methodology/approach

To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.

Findings

In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.

Originality/value

This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.

Details

Smart and Resilient Transportation, vol. 6 no. 1
Type: Research Article
ISSN: 2632-0487

Keywords

Open Access
Article
Publication date: 3 January 2024

Eloy Gil-Cordero, Pablo Ledesma-Chaves, Rocío Arteaga Sánchez and Ari Melo Mariano

The aim of this study is to examine the behavioral intention (BI) to adopt the Coinbase Wallet by Spanish users.

10422

Abstract

Purpose

The aim of this study is to examine the behavioral intention (BI) to adopt the Coinbase Wallet by Spanish users.

Design/methodology/approach

A survey was administered to individuals residing in Spain between March and April 2021. There were 301 questionnaires analyzed. This research applies a new predictive model based on technology acceptance model (TAM) 2, the unified theory of acceptance and use of technology (UTAUT) model, the theory of perceived risk and the commitment trust theory. A mixed partial least squares structural equation modeling (PLS-SEM)/fuzzy-set qualitative comparative analysis (fsQCA) methodology was employed for the modeling and data analysis.

Findings

The results showed that all the variables proposed have a direct and positive influence on the intention to use a Coinbase Wallet. The findings present clear directions for traders, investors and academics focused on improving their understanding of the characteristics of these markets.

Originality/value

First, this study addresses important concerns relating to the adoption of crypto-wallets during the global pandemic. Second, this research contributes to the existing literature by adding electronic word of mouth (e-WOM), trust, web quality and perceived risk as new drivers of the intention to use the Coinbase Wallet, providing unique and innovative insights. Finally, the study offers a solid methodological contribution by integrating linear (PLS) and nonlinear (fsQCA) techniques, showing that both methodologies provide a better understanding of the problem and a more detailed awareness of the patterns of antecedent factors.

Details

International Journal of Bank Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-2323

Keywords

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