azar ghyasi; hanieh rashidi
Abstract
Due to the inherent complexity and increasing competition, today's business environment requires new approaches in organizing and managing. One of the new approaches is business intelligence, which is the most critical technology to help manage and deliver smart services, especially business reporting. ...
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Due to the inherent complexity and increasing competition, today's business environment requires new approaches in organizing and managing. One of the new approaches is business intelligence, which is the most critical technology to help manage and deliver smart services, especially business reporting. Business intelligence enables firms to manage their business efficiently to meet the needs of businesses at different macro, middle and even operations levels. In this paper, while investigating the feasibility of implementing business intelligence in firms, designing business intelligence to report and present new services is discussed. In order to demonstrate the capabilities of this type of intelligence, an approach based on the concept of Bayesian network in the application layer of business intelligence is presented. This approach is implemented for one of the companies governed by the Iranian Industrial Development and Renovation Organization, and the effects of important accounting and financial variables on the firm goals are investigated.
Machine Learning
Seyyed Mousa Khademi; Abbas Shams Vala; Somayyeh Jafari
Abstract
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 ...
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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.
