Integration of Data Mining and Business Intelligence in Big Data Analytics

The purpose of this chapter is to analyze and explore the research studies for scholarly publication trends and patterns related to the integration of data mining in particular business intelligence in big data analytics domains published in the period of 2010-2019. Research patterns explore in highly prestigious sources that have high impact factors and citations counted in the ISI Web of Science Core Collection database (indexes included SCI-Exp and SSCI). Bibliometric analysis methods applied for this study under the research limitations. Research questions formed based on bibliometric principles concentrating fields such as descriptive of publication, author productivity, country-regions distribution, keyword analysis with contribution among researchers, citation analysis, co-citation patterns searched. Findings showed strong relations and patterns on these important research domains. Besides this chapter would useful for researchers to obtain an overview of publication trends on research domains to be concerned for further studies and shows the potential gaps in those fields.

CONTRIBUTIONS TO THE INDIAN JOURNAL OF VETERINARY AND ANIMAL SCIENCES RESEARCH (IJVASR): A SCIENTOMETRIC ANALYSIS

A Scientometric study was performed on 235 research articles published in the Indian Journal of Veterinary and Animal Sciences Research (IJVASR). For the current analysis, six volumes of the journal totalling 30 issues from 2016 to 2020 were considered. The amounts of contributions, authorship patterns, author productivity, average article length, and average keyword density have all been examined. Only 20 of the 235 contributions were single-authored, while the rest were multi-authored, with an average degree of collaboration of 0.91 and a week of collaboration between the writers. The increasing tendency of co-authored publications was highlighted by the pattern of co-authorship. According to the research, author productivity is 0.26.

Literasi Keuangan pada UMKM (Studi Pemetaan Sistematis dan Analisis Co-Authorship pada Basis Data Scopus)

Financial literacy has been widely discussed in various countries with a wide range of subject areas, focuses, and loci. The purpose of this paper is to map the trends of scientific publications and map the network of authors on financial literacy, especially in the MSME sector. We have developed bibliometric analysis through VOSviewer software, supplemented by literature reviews. A total of 126 articles were obtained from Scopus related to the topics "financial literacy" and "micro small medium enterprise". We present trends in financial literacy research, author productivity, and journals, as well as detailing the network of co-authorships who have researched and published in the scientific domain. The results of the study are known that 1) The application of financial literacy in MSMEs only appeared in 2010 and experienced a significant upward trend. 2) Penulis most productive comes from china, where there are 2 authors each produce 3 articles. 3) Co-authorship has not been established between writers in each country and between countries. 4) Indonesia contributes financial literacy publications in MSMEs the most compared to other countries, with the number of publications as many as 34 articles. Lastly, the mapping provides an overview of which countries and writers are concentric and collaborate with each other on the topic of financial literacy in MSMEs.

Author productivity pattern and applicability of Lotka’s inverse square law: a bibliometric appraisal of selected LIS open access journals

Purpose The purpose of this paper is to know whether the authors’ productivity pattern of library and information science (LIS) open access journals adheres to Lotka’s inverse square law of scientific productivity. Since the law was introduced, it has been tested in various fields of knowledge, and results have varied. This study has closely followed Lotka’s inverse square law in the field of LIS open access journals to find a factual result and set a baseline for future studies on author productivity of LIS open access journals. Design/methodology/approach The publication data of selected ten LIS open access journals pertain to authorship, citations were downloaded from the Scopus database and analysed using bibliometric indicators like authorship pattern, collaborative index (CI), degree of collaboration (DC), collaborative coefficient (CC) and citation counts. This study has applied Lotka’s inverse square law to assess authors’ productivity pattern of LIS open access journals and further Kolmogorov-Smirnov (K-S) goodness-of-fit test applied for testing of observed and expected author productivity data. Findings Inferences were drawn for the set objectives on authorship pattern, collaboration trend and authors’ productivity pattern of LIS open access journals covered in this study. The single authorship pattern is dominant in LIS open access journals covered in this study. The CI, DC and CC are found to be 1.95, 0.47 and 0.29, respectively. The expected values as per Lotka’s law (n = −2) significantly vary from the observed values as per the chi-square test and K-S goodness-of-fit test. Hence, this study does not adhere to Lotka’s inverse square law of scientific productivity. Practical implications Researchers may find an idea about the authors’ productivity patterns of LIS open access journals. This study has used the K-S goodness-of-fit test and the chi-square test to validate the authors’ productivity data. The inferences found out from this study will be a baseline for future research on author productivity of LIS open access journals. Originality/value This study is significant from the viewpoint of the growing research on open access journals in the field of LIS and to identify the authorship pattern, collaboration trend and author productivity pattern of such journals.

Integration of Data Mining and Business Intelligence in Big Data Analytics

The purpose of this chapter is to analyze and explore the research studies for scholarly publication trends and patterns related to the integration of data mining in particular business intelligence in big data analytics domains published in the period of 2010-2019. Research patterns explore in highly prestigious sources that have high impact factors and citations counted in the ISI Web of Science Core Collection database (indexes included SCI-Exp and SSCI). Bibliometric analysis methods applied for this study under the research limitations. Research questions formed based on bibliometric principles concentrating fields such as descriptive of publication, author productivity, country-regions distribution, keyword analysis with contribution among researchers, citation analysis, co-citation patterns searched. Findings showed strong relations and patterns on these important research domains. Besides this chapter would useful for researchers to obtain an overview of publication trends on research domains to be concerned for further studies and shows the potential gaps in those fields.

Produktivitas Pengarang Menggunakan Hukum Lotka Dengan Teknik Complete Count Pada Jurnal Kedokteran YARSI Tahun 2009-2018

Researchers research to develop science. Research results are published as a form of scientific communication. One type of scientific publication is a journal article. YARSI Medical Journal is a peer-reviewed journal in the field of medicine and health that is open to the public owned by YARSI University. The author's productivity patterns in the YARSI Medical Journal so far are unknown. Author productivity is the number of papers produced by the author on a particular subject and published in scientific journals in a certain period. This study aims to (1) Determine the author's productivity patterns using Lotka's Law with complete count techniques in YARSI Medical Journal 2009-2018; (2) Testing the suitability of the frequency of Lotka's Law with the author's frequency distribution using the complete count technique in YARSI Medical Journal 2009-2018. The research method used in this study is a quantitative method with bibliometric analysis. Data collection uses documentation method. The results of this study include (1) the pattern of author productivity with an exponent value (n) 2.874110535 and the constant (C) 0.820080499 meaning that the author contributing to one article is 82.00% of the total number of authors, it can be said that the YARSI Medical Journal Author Productivity Pattern 2009- 2018 is low or less productive. (2) Based on the K-S test the maximum deviation is 0 and the critical value is 0.0829206. Dmax is smaller than the critical value, so H0 is accepted. That is, the Author Productivity Pattern uses the Complete Count Technique in YARSI Medical Journal 2009-2018 following Lotka's Law.

Corporate Citizenship: Structuring the Research Field

Corporate citizenship, which is firms’ societal engagement beyond customer and shareholder interests, is a prominent topic in management practice and has led to extensive research. This increased interest resulted in a complex and fragmented scholarly literature. In order to structure and map the field quantitatively, we conducted a temporal analysis of publications and citations, an analysis of the productivity of involved disciplines, an analysis of the productivity of publication forms including journal impact factors, an author productivity and citation analysis, a co-author analysis, an article citation analysis, an article co-citation analysis, and a keyword co-occurrence analysis. Results of these bibliometric analyses show that corporate citizenship research seems to have been in a phase of stagnation since 2014 and shows a rather low degree of interdisciplinarity. Papers are predominantly published in high impact journals. Authors show little collaboration with other researchers. Current research relates to other business ethics topics, addresses philosophical foundations, and starts to relate to human resource management and organization studies.

Scientometric Profile of Biochemistry Research in India a Study Based on Web of Science

The paper examines 25,132 biochemistry research contributions of Indian scientists covered in the Web of Science for a period of 10 years (2004-2013). It was found that the biochemistry research is gradually growing and average annual growth rate was 36.84 per cent. The solo research was not prevalent and team research is more in the Indian biochemistry research and 97.46 per cent publications were contributed by multi- authors. It was observed that the value of co- authorship index was generally increasing and it varied from 93 to 105 during the period of study. Journal articles contribute 89.43 per cent of the total output followed by reviews (7.14 %). Indian researchers collaborate largely with the researchers of USA (2.49 %). The geographical distribution shows that Tamil Nadu, Uttar Pradesh and Delhi lead the list. The study shows that, C. Abdul Jaleel (58) and L. Pai (37) are the top ranked authors in the field. ‘Plos One’ is the top ranked journal and it published 296 papers during the study period. Academic institutions contribute more number of papers (50.26 %) followed by research institutions (28.24 %). The Lotka’s law was not found fit with the observed author productivity distribution of Indian biochemistry research.

Assessment of the NIH-supported relative citation ratio as a measure of research productivity among 1687 academic neurological surgeons

OBJECTIVEPublication metrics such as the Hirsch index (h-index) are often used to evaluate and compare research productivity in academia. The h-index is not a field-normalized statistic and can therefore be dependent on overall rates of publication and citation within specific fields. Thus, a metric that adjusts for this while measuring individual contributions would be preferable. The National Institutes of Health (NIH) has developed a new, field-normalized, article-level metric called the “relative citation ratio” (RCR) that can be used to more accurately compare author productivity between fields. The mean RCR is calculated as the total number of citations per year of a publication divided by the average field-specific citations per year, whereas the weighted RCR is the sum of all article-level RCR scores over an author’s career. The present study was performed to determine how various factors, such as academic rank, career duration, a Doctor of Philosophy (PhD) degree, and sex, impact the RCR to analyze research productivity among academic neurosurgeons.METHODSA retrospective data analysis was performed using the iCite database. All physician faculty affiliated with Accreditation Council for Graduate Medical Education (ACGME)–accredited neurological surgery programs were eligible for analysis. Sex, career duration, academic rank, additional degrees, total publications, mean RCR, and weighted RCR were collected for each individual. Mean RCR and weighted RCR were compared between variables to assess patterns of analysis by using SAS software version 9.4.RESULTSA total of 1687 neurosurgery faculty members from 125 institutions were included in the analysis. Advanced academic rank, longer career duration, and PhD acquisition were all associated with increased mean and weighted RCRs. Male sex was associated with having an increased weighted RCR but not an increased mean RCR score. Overall, neurological surgeons were highly productive, with a median RCR of 1.37 (IQR 0.93–1.97) and a median weighted RCR of 28.56 (IQR 7.99–85.65).CONCLUSIONSThe RCR and its derivatives are new metrics that help fill in the gaps of other indices for research output. Here, the authors found that advanced academic rank, longer career duration, and PhD acquisition were all associated with increased mean and weighted RCRs. Male sex was associated with having an increased weighted, but not mean, RCR score, most likely because of historically unequal opportunities for women within the field. Furthermore, the data showed that current academic neurosurgeons are exceptionally productive compared to both physicians in other specialties and the general scientific community.