Mapping the Landscape of Business Intelligence Research: A Bibliometric Approach

Title

Mapping the Landscape of Business Intelligence Research: A Bibliometric Approach

Creator

Basha M.S.A.; Raju R.P.K.; Uma Devi A.; Raja S.; Maheshwari A.

Description

The integration of Business Intelligence (BI) is an essential element in contemporary enterprises, facilitating the conversion of voluminous data into valuable insights to support informed decision-making. Consequently, a considerable body of literature has been devoted to investigating the utilization of Business Intelligence (BI) in enhancing company efficiency and competitiveness. The present investigation employs bibliometric methods as a means to examine the research pertaining to Business Intelligence (BI). This includes an examination of the main writers and universities, publication patterns, and the intellectual framework of the domain. This investigation centers on the timeframe spanning from 2000 to 2022 and scrutinizes a corpus of 3729 Scopus articles pertaining to business intelligence. The findings suggest that the domain of Business Intelligence (BI) has experienced a substantial expansion recently. The study's results reveal significant contributors, establishments, nations, and references in the discipline, along with developing research patterns and prospects for further investigation. In general, this research emphasizes the significance of bibliometric evaluation as a means of comprehending the present status of BI research and discovering approaches to enhance the utilization of BI in contemporary organizational decision-making procedures. This study has the potential to provide valuable insights into the present state of research within the field, pinpoint significant trends and themes, and highlight potential avenues for future research. 2023 IEEE.

Source

7th IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions, CSITSS 2023 - Proceedings

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Diamonds; Estimated values; Machine learning; Regression Models and Cross validation

Coverage

Basha M.S.A., Gitam School of Business, Gandhi Institute of Technology and Management, Deemed to Be University, Bengaluru, India; Raju R.P.K., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Uma Devi A., Srm Valliammai Engineering College, Department of Management Studies, Chengalpattu, India; Raja S., School of Management, Vel-Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology, Avadi, India; Maheshwari A., School of Commerce, Finance and Accountancy Christ (Deemed to Be University), Ghaziabad, India

Rights

Restricted Access

Relation

ISBN: 979-835034314-4

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/CSITSS60515.2023.10334155

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181535548&doi=10.1109%2fCSITSS60515.2023.10334155&partnerID=40&md5=12a58e3c159a713a4afc61630113c660