Artificial intelligence (AI) is said to incorporate enormous potential for reducing the operational costs of car manufacturers and their suppliers all over the globe. Nevertheless, recent studies suggest that many of them are still struggling with adopting it at large scale. Therefore, in this article we develop a research model explaining the decision-making of organisations from the automotive industry regarding the question whether to adopt AI for car (part) manufacturing purposes or not. To do so, we contextualise the Technology-Organization-Environment (TOE) framework by taking a multiple case study approach including 39 expert interviews in 25 different firms all over the globe. Based on that, we propose a research model that theorises 16 different context-specific factors that influence that decision. Four of them are already well-known from the TOE framework but are renamed for a better contextual accuracy, whereas twelve can be regarded as new in this contextualised setting. The proposed model addresses research gaps in both the organisational adoption research literature and the literature on the application of AI in the automotive environment.
Demlehner, Quirin and Laumer, Sven, "Shall We Use It or Not? Explaining the Adoption of Artificial Intelligence for Car Manufacturing Purposes" (2020). In Proceedings of the 28th European Conference on Information Systems (ECIS), An Online AIS Conference, June 15-17, 2020.
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