Engaging scientometrics in information systems

Big data and infectious disease epidemiology: A bibliometric analysis and research agenda

BACKGROUND

Infectious diseases represent a major challenge for health systems worldwide. With the recent global pandemic of COVID-19, the need to research strategies to treat these health problems has become even more pressing. Although the literature on big data and data science in health has grown rapidly, few studies have synthesized these individual studies, and none has identified the utility of big data in infectious disease surveillance and modeling.

OBJECTIVE

This paper aims to synthesize research and identify hotspots of big data in infectious disease epidemiology.

METHODS

Bibliometric data from 3054 documents that satisfied the inclusion criteria were retrieved from the Web of Science database over 22 years (2000-2022) were analyzed and reviewed. The search retrieval occurred on October 17, 2022. Bibliometric analysis was performed to illustrate the relationships between research constituents, topics, and key terms in the retrieved documents.

RESULTS

The bibliometric analysis revealed internet searches and social media as the most utilized big data sources for infectious disease surveillance or modeling. It also placed the US and Chinese institutions as leaders in this research area. Disease monitoring and surveillance, utility of electronic health (or medical) records, methodology framework for infodemiology tools, and machine/deep learning were identified as the core research themes.

CONCLUSIONS

Proposals for future studies are made based on these findings. This study will provide healthcare informatics scholars with a comprehensive understanding of big data research in infectious disease epidemiology.

Artificial intelligence in E-Commerce: a bibliometric study and literature review

This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes guidelines on how information systems (IS) research could contribute to this research stream. To this end, the innovative approach of combining bibliometric analysis with an extensive literature review was used. Bibliometric data from 4335 documents were analysed, and 229 articles published in leading IS journals were reviewed. The bibliometric analysis revealed that research on AI in e-commerce focuses primarily on recommender systems. Sentiment analysis, trust, personalisation, and optimisation were identified as the core research themes. It also places China-based institutions as leaders in this researcher area. Also, most research papers on AI in e-commerce were published in computer science, AI, business, and management outlets. The literature review reveals the main research topics, styles and themes that have been of interest to IS scholars. Proposals for future research are made based on these findings. This paper presents the first study that attempts to synthesise research on AI in e-commerce. For researchers, it contributes ideas to the way forward in this research area. To practitioners, it provides an organised source of information on how AI can support their e-commerce endeavours.

BIBLIOMETRIC ANALYSIS: NANOTECHNOLOGY AND COVID-19

BACKGROUND

COVID-19 pandemic information is critical in order to study it further, but the virus has still not been confined. In addition, even if there is no longer any threat, more knowledge may be gathered from these resources.

METHODS

The data used in this study was gathered from several scientific areas and the links between them. Due to the fact that the COVID-19 pandemic has not been fully contained and additional information can be gleaned from these references, bibliometric analysis of it is important.

RESULTS

In total 155 publications on the topic of "COVID-19" and the keyword "nanotechnology" were identified in the Scopus database between 2020 and 2021 in a network visualization map.

CONCLUSION

As a result, our analysis was conducted at the appropriate time to provide a comprehensive understanding of COVID-19 and nanotechnology and prospective research directions for medicinal chemistry.

A structured literature review of scientometric research of the knowledge management discipline: a 2021 update

Purpose

The purpose of this study is to conduct a structured literature review of scientometric research of the knowledge management (KM) discipline for the 2012–2019 time period.

Design/methodology/approach

A total of 175 scientometric studies of the KM discipline were identified and analyzed.

Findings

Scientometric KM research has entered the maturity stage: its volume has been growing, reaching six publications per month in 2019. Scientometric KM research has become highly specialized, which explains many inconsistent findings, and the interests of scientometric KM researchers and their preferred inquiry methods have changed over time. There is a dangerous trend toward a monopoly of the scholarly publishing market which affects researchers’ behavior. To create a list of keywords for database searches, scientometric KM scholars should rely on the formal KM keyword classification schemes, and KM-centric peer-reviewed journals should continue welcoming manuscripts on scientometric topics.

Practical implications

Stakeholders should realize that the KM discipline may successfully exist as a cluster of divergent schools of thought under an overarching KM umbrella and that the notion of intradisciplinary cohesion and consistency should be abandoned. Journal of Knowledge Management is unanimously recognized as a leading KM journal, but KM researchers should not limit their focus to the body of knowledge documented in the KM-centric publication forums. The top six most productive countries are the USA, the UK, Taiwan, Canada, Australia and China. There is a need for knowledge brokers that may deliver the KM academic body of knowledge to practitioners.

Originality/value

This is the most comprehensive, up-to-date analysis of the KM discipline.

What drives citations of frontier application publications?

A large body of literature exists on analysis of citation and reviews of application of efficiency frontier. However, the reviews that assessed the determinants of citation counts did not focus on frontier applications. We contribute to the literature by identifying the drivers of citations of frontier application publications on Ghana. We employed two-part mixture modelling with inverse hyperbolic sine (IHS) transformation of the second part, which was found to be more appropriate than single equation IHS transformation modelling, for our data. Use of stochastic frontier analysis or data envelopment analysis did not drive citations counts. However, quality of journals in which frontier application studies were published and accessibility of the journals to readers, drive citation counts. Authors, institutions and funders of studies on frontier applications may consider these over collaborations, in seeking growth in citation counts.

Patterns of citations for the growth of knowledge: a Foucauldian perspective

Purpose

The purpose of this paper is to sensitize researchers to qualitative citation patterns that characterize original research, contribute toward the growth of knowledge and, ultimately, promote scientific progress.

Design/methodology/approach

This study describes how ideas are intertextually inserted into citing works to create new concepts and theories, thereby contributing to the growth of knowledge. By combining existing perspectives and dimensions of citations with Foucauldian theory, this study develops a typology of qualitative citation patterns for the growth of knowledge and uses examples from two classic works to illustrate how these citation patterns can be identified and applied.

Findings

A clearer understanding of the motivations behind citations becomes possible by focusing on the qualitative patterns of citations rather than on their quantitative features. The proposed typology includes the following patterns: original, conceptual, organic, juxtapositional, peripheral, persuasive, acknowledgment, perfunctory, inconsistent and plagiaristic.

Originality/value

In contrast to quantitative evaluations of the role and value of citations, this study focuses on the qualitative characteristics of citations, in the form of specific patterns of citations that engender original and novel research and those that may not. By integrating Foucauldian analysis of discourse with existing theories of citations, this study offers a more nuanced and refined typology of citations that can be used by researchers to gain a deeper semantic understanding of citations.