Ricardo Costa-Climent: On how Firms can use Artificial Intelligence for Economic Value Creation: A Business Model Approach

Abstract

This research provides a novel answer to the following question: How can firms use artificial intelligence (AI), specifically predictive AI, to create economic value? A novel theory is developed by integrating, in a specific way, two complementary theoretical bodies: the theory of data network effects and business model theory. The former accounts for AI’s unique learning ability to generate users’ perceived value but offers no insight into economic value creation at the firm level. To remedy this limitation, business model theory accounts for economic value creation from digital technology use, while not accounting for AI’s unique learning ability. The process of integrating these two theories is carried out using a multi-method research approach, presented here in nine papers. Regarded together, the papers manifest an evolutionary research process with conceptual and empirical work and exploratory and hypothesis-based studies. Spanning several industrial contexts, these studies jointly develop and test the new theory proposed in this thesis. The findings show that when AI is used to create perceived value for its users, and thereby realise data network effects, and when such AI use is positioned adequately within a firm’s business model architecture, one or more of the four business model themes (novelty, efficiency, complementarity and lock-in) can be activated to achieve economic value creation. The key contribution of this thesis lies in explaining how a firm can use AI to create economic value. The findings have practical implications for managers’ investment decisions regarding the use of AI.