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Khademi, Seyyed Mousa, Shams Vala, Abbas, Jafari, Somayyeh. (1402). Business Intelligence in Management of Knowledge Assets: Co-Word Analysis of Scientific Productions. سامانه مدیریت نشریات علمی, 2(1), 133-161. doi: 10.22054/jdsm.2024.79561.1047
Seyyed Mousa Khademi; Abbas Shams Vala; Somayyeh Jafari. "Business Intelligence in Management of Knowledge Assets: Co-Word Analysis of Scientific Productions". سامانه مدیریت نشریات علمی, 2, 1, 1402, 133-161. doi: 10.22054/jdsm.2024.79561.1047
Khademi, Seyyed Mousa, Shams Vala, Abbas, Jafari, Somayyeh. (1402). 'Business Intelligence in Management of Knowledge Assets: Co-Word Analysis of Scientific Productions', سامانه مدیریت نشریات علمی, 2(1), pp. 133-161. doi: 10.22054/jdsm.2024.79561.1047
Khademi, Seyyed Mousa, Shams Vala, Abbas, Jafari, Somayyeh. Business Intelligence in Management of Knowledge Assets: Co-Word Analysis of Scientific Productions. سامانه مدیریت نشریات علمی, 1402; 2(1): 133-161. doi: 10.22054/jdsm.2024.79561.1047

Business Intelligence in Management of Knowledge Assets: Co-Word Analysis of Scientific Productions

Journal of Data Science and Modeling
دوره 2، شماره 1 - شماره پیاپی 3، اسفند 2023، صفحه 133-161    اصل مقاله (1008.98 K)
نوع مقاله: Research Manuscript
شناسه دیجیتال (DOI): 10.22054/jdsm.2024.79561.1047
نویسندگان
Seyyed Mousa Khademi1؛ Abbas Shams Vala2؛ Somayyeh Jafari* 3
1Department of Strategic Management, Payam University Noor, Tehran, Iran.
2Department of Management, Payam Noor University, Tehran, Iran.
3PhD in Information and Knowledge Management, University of Tehran, Tehran, Iran
چکیده
The purpose of this research is to explain the application of business intelligence in managing knowledge assets, utilizing the co-word analysis technique on scientific productions related to "knowledge assets management and business intelligence". In this applied research, the method of content analysis and the techniques of co-word analysis, social network analysis, hierarchical clustering, and strategic diagram have been used. The research community is 929 scientific productions related to "business intelligence and knowledge management" from the 1990s to 2022 in the Web of Science database. Data analysis was conducted using Histcite, BibExcel, UCINET, and Excel software, while the maps were created using VOS Viewer and SPSS software. The results indicated that the average annual growth rates for publication and production impact were 28% and 8.9%, respectively. Among the keywords, "big data," "data mining," and "data warehouse," as well as "big data," "management," and "system," and "design science," "Industry 4.0," and "discovery" exhibited the highest frequency, links, and citations, respectively. Co-word analysis resulted in the formation of eight clusters comprising a total of 138 keywords. In hierarchical clustering, five clusters—namely, business intelligence tools in knowledge management, infrastructures and technologies of business intelligence, and business process management through the management of knowledge assets—are considered mature and are positioned at the center of this research field. This research provides a comprehensive perspective by identifying the main topics and clusters discussed in the fields of business intelligence and knowledge management. It can be valuable for researchers, educators, policymakers, and organizational managers.
کلیدواژه‌ها
Business intelligence؛ knowledge management؛ Data؛ Information؛ Scientometrics؛ Co-occurrence
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تعداد مشاهده مقاله: 81
تعداد دریافت فایل اصل مقاله: 96


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