Artikel
Frontiers of business intelligence and analytics 3.0: a taxonomy-based literature review and research agenda
Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research. Thereby, in each decade the rapid development of technologies opened new room for investigation. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. The third wave of BI & A comprises unstructured and sensor data of mobile devices. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. By this means, the paper's contribution is fourfold. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. The analysis provides an overview on the status quo of BI & A 3.0. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Business Research ; ISSN: 2198-2627 ; Volume: 13 ; Year: 2020 ; Issue: 2 ; Pages: 685-739 ; Heidelberg: Springer
- Klassifikation
-
Management
- Thema
-
Business intelligence
Big data
Data analytics
Literature review
Taxonomy development
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Eggert, Mathias
Alberts, Jens
- Ereignis
-
Veröffentlichung
- (wer)
-
Springer
- (wo)
-
Heidelberg
- (wann)
-
2020
- DOI
-
doi:10.1007/s40685-020-00108-y
- Handle
- Letzte Aktualisierung
- 10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Eggert, Mathias
- Alberts, Jens
- Springer
Entstanden
- 2020