The Intellectual Structure of Business Analytics: 2002–2019

Hyaejung Lim, Chang Kyo Suh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper identifies the intellectual structure of business analytics using document co-citation analysis and author co-citation analysis. A total of 333 research documents and 17,917 references from the Web of Science were collected. A total of 15 key documents and nine clusters were extracted from the analysis to clarify the sub-areas. Furthermore, burst detection and timeline analysis were conducted to gain a better understanding of the overall changing trends in business analytics. The main implication of the research results is in its ability to provide the state of past and present standards to practitioners and to suggest further research into business analytics to researchers.

Original languageEnglish
Title of host publicationMachine Learning, Optimization, and Data Science - 6th International Conference, LOD 2020, Revised Selected Papers
EditorsGiuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Giorgio Jansen, Vincenzo Sciacca, Panos Pardalos, Giovanni Giuffrida, Renato Umeton
PublisherSpringer Science and Business Media Deutschland GmbH
Pages540-550
Number of pages11
ISBN (Print)9783030645823
DOIs
StatePublished - 2020
Event6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020 - Siena, Italy
Duration: 19 Jul 202023 Jul 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12565 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020
Country/TerritoryItaly
CitySiena
Period19/07/2023/07/20

Keywords

  • Author co-citation analysis
  • Business analytics
  • CiteSpace
  • Document co-citation analysis
  • Intellectual structure

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