Business Intelligence Strategies, Best Practices, and Latest Trends: Analysis of Scientometric Data From 2003 To 2023 Using Machine Learning

dc.authorid GURCAN, Fatih/0000-0001-9915-6686
dc.authorid Menekse Dalveren, Gonca Gokce/0000-0002-8649-1909
dc.authorid Ayaz, Ahmet/0000-0003-1405-0546
dc.authorscopusid 57194776706
dc.authorscopusid 57338589200
dc.authorscopusid 57201658878
dc.authorscopusid 35408917600
dc.authorwosid GURCAN, Fatih/AAJ-7503-2021
dc.authorwosid Menekse Dalveren, Gonca Gokce/HHS-4591-2022
dc.authorwosid Ayaz, Ahmet/JBJ-2146-2023
dc.contributor.author Gurcan, Fatih
dc.contributor.author Ayaz, Ahmet
dc.contributor.author Dalveren, Gonca Gokce Menekse
dc.contributor.author Derawi, Mohammad
dc.contributor.other Information Systems Engineering
dc.date.accessioned 2024-07-05T15:22:35Z
dc.date.available 2024-07-05T15:22:35Z
dc.date.issued 2023
dc.department Atılım University en_US
dc.department-temp [Gurcan, Fatih] Karadeniz Tech Univ, Fac Econ & Adm Sci, Dept Management Informat Syst, TR-61080 Trabzon, Turkiye; [Ayaz, Ahmet] Karadeniz Tech Univ, Digital Transformat Off, TR-61080 Trabzon, Turkiye; [Dalveren, Gonca Gokce Menekse] Atilim Univ, Fac Engn, Dept Software Engn, TR-06830 Ankara, Turkiye; [Derawi, Mohammad] Norwegian Univ Sci & Technol, Fac Informat Technol & Elect Engn, Dept Elect Syst, N-7034 Gjovik, Norway en_US
dc.description GURCAN, Fatih/0000-0001-9915-6686; Menekse Dalveren, Gonca Gokce/0000-0002-8649-1909; Ayaz, Ahmet/0000-0003-1405-0546 en_US
dc.description.abstract The widespread use of business intelligence products, services, and applications piques the interest of researchers in this field. The interest of researchers in business intelligence increases the number of studies significantly. Identifying domain-specific research patterns and trends is thus a significant research problem. This study employs a topic modeling approach to analyze domain-specific articles in order to identify research patterns and trends in the business intelligence field over the last 20 years. As a result, 36 topics were discovered that reflect the field's research landscape and trends. Topics such as "Organizational Capability", "AI Applications", "Data Mining", "Big Data Analytics", and "Visualization" have recently gained popularity. A systematic taxonomic map was also created, revealing the research background and BI perspectives based on the topics. This study may be useful to researchers and practitioners interested in learning about the most recent developments in the field. Topics generated by topic modeling can also be used to identify gaps in current research or potential future research directions. en_US
dc.identifier.citationcount 3
dc.identifier.doi 10.3390/su15139854
dc.identifier.issn 2071-1050
dc.identifier.issue 13 en_US
dc.identifier.scopus 2-s2.0-85164913188
dc.identifier.scopusquality Q2
dc.identifier.uri https://doi.org/10.3390/su15139854
dc.identifier.uri https://hdl.handle.net/20.500.14411/2220
dc.identifier.volume 15 en_US
dc.identifier.wos WOS:001028127500001
dc.identifier.wosquality Q2
dc.institutionauthor Dalveren, Gonca Gökçe Menekşe
dc.language.iso en en_US
dc.publisher Mdpi en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 15
dc.subject business intelligence en_US
dc.subject topic modeling en_US
dc.subject text mining en_US
dc.subject trend analysis en_US
dc.subject machine learning en_US
dc.title Business Intelligence Strategies, Best Practices, and Latest Trends: Analysis of Scientometric Data From 2003 To 2023 Using Machine Learning en_US
dc.type Article en_US
dc.wos.citedbyCount 7
dspace.entity.type Publication
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