Demlehner Q, Schömer D, Laumer S (2021)
Publication Language: English
Publication Type: Journal article, Original article
Publication year: 2021
Book Volume: 58
Pages Range: 1-14
Journal Issue: 102317
DOI: 10.1016/j.ijinfomgt.2021.102317
The latest boom of artificial intelligence (AI) has left the information management community in strong need of structure-providing, high-level overview works. Such works are supposed to allow both researchers and practitioners to keep track of that steep development across the technology's numerous possible application domains. So it is among other things that AI is said to incorporate enormous potential for reducing the operational costs of car manufacturers all over the globe. Nevertheless, many of them are still struggling with adopting it at large scale just because of a lack of knowledge on if and where to apply it. This study is therefore designed to find out which general use cases exist for AI within the context of car manufacturing and which ones might be the most promising ones to pursue at this early stage. We conducted a Delphi study with 39 experts in 25 different globally scattered organizations over one and a half years. As a result, we were able to identify 20 different high-level use cases for AI along the entire car manufacturing process. Our panelists have completely ranked and assessed those 20 use cases within two different dimensions, i.e., their estimated business value and their realizability. Besides being the first study to provide such an overview at one glance and to give such quantitative insights on that steeply emerging topic, four use cases from that list have never been discussed in connection with car manufacturing within the scientific literature until now and can therefore be considered as completely new in that regard.
APA:
Demlehner, Q., Schömer, D., & Laumer, S. (2021). How can artificial intelligence enhance car manufacturing? A Delphi study-based identification and assessment of general use cases. International Journal of Information Management, 58(102317), 1-14. https://doi.org/10.1016/j.ijinfomgt.2021.102317
MLA:
Demlehner, Quirin, Daniel Schömer, and Sven Laumer. "How can artificial intelligence enhance car manufacturing? A Delphi study-based identification and assessment of general use cases." International Journal of Information Management 58.102317 (2021): 1-14.
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