A comparative analysis of emerging scientific themes in business analytics. (2018)

• Record Type: Journal Article
• Authors: Vanani, Iman Raeesi; Jalali, Seyed Mohammad Jafar
• Is Part Of: International journal of business information systems. Volume 29:Number 2(2018)
• Page Start: 183
• Page End: 206
• Publication Date: 2018
• Subjects: business analytics -- burst detection -- text clustering -- words occurrence -- decision support; Information storage and retrieval systems -- Business -- Periodicals; Business -- Data processing -- Periodicals; Management information systems -- Periodicals; System design -- Periodicals; System analysis -- Periodicals; 651.8
• Languages: English
• ISSNs: 1746-0972

Abstract

The purpose of this research is to investigate the emerging scientific themes in business analytics through the utilisation of burst detection, text-clustering and word occurrence analysis in top information systems journals in order to provide an insight about the future scientific trends of business analytics for scholars and practitioners in the field. Researchers have gathered a rich set of business analytics articles from top journals which are indexed in the well-known scientific database of web of science (WoS) core collection. The study provides clues, directions, and knowledge-based guidelines on the recent business analytics scientific trends through the utilisation of mentioned algorithms over paper abstracts, titles, and keywords. This study also highlights the most important areas of research and the future research directions that might be interesting to business analysts through an in-depth analytical discussion.