Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/287115 
Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Electronic Markets [ISSN:] 1422-8890 [Volume:] 31 [Issue:] 3 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2021 [Pages:] 643-670
Verlag: 
Springer, Berlin, Heidelberg
Zusammenfassung: 
Artificial Intelligence (AI) and Machine Learning (ML) are currently hot topics in industry and business practice, while management-oriented research disciplines seem reluctant to adopt these sophisticated data analytics methods as research instruments. Even the Information Systems (IS) discipline with its close connections to Computer Science seems to be conservative when conducting empirical research endeavors. To assess the magnitude of the problem and to understand its causes, we conducted a bibliographic review on publications in high-level IS journals. We reviewed 1,838 articles that matched corresponding keyword-queries in journals from the AIS senior scholar basket, Electronic Markets and Decision Support Systems (Ranked B). In addition, we conducted a survey among IS researchers (N = 110). Based on the findings from our sample we evaluate different potential causes that could explain why ML methods are rather underrepresented in top-tier journals and discuss how the IS discipline could successfully incorporate ML methods in research undertakings.
Schlagwörter: 
Machine learning
Artificial intelligence
Information systems
JEL: 
C8
L1
Persistent Identifier der Erstveröffentlichung: 
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