Key points are not available for this paper at this time.
Artificial intelligence (AI) is increasingly important in manufacturing supply chain operations. Considering its effects on consumer personalisation (CPE) and cost reduction (CRE), the manufacturer (M) is motivated to acquire licences from the AI supplier (S). However, high AI licence fees and consumer resistance due to data privacy concerns render M not reaping benefits from AI. Moreover, S may not benefit from AI because of the high development costs. To explore optimal strategic interactions between S and M and achieve “win-win” situations, we establish a game-theoretical model to characterise the equilibrium and analyse the impacts of the CPE, CRE, and consumer resistance on such “win-win” situations. Our findings show that when consumer product quality perception is low, “win-win” situations only arise if S’s AI development efficiency is high. Conversely, “win-win” situations occur only if both S’s development efficiency and M’s unit reducible cost are large. Finally, both AI’s CPE and CRE enhance M’s AI adoption and S’s motivation to raise its licence fee, promoting “win-win” situations. However, consumer resistance does not necessarily impair consumer utility, especially when consumers strongly prefer safeguarding their private data, but invariably impedes the “win-win” for M and S.
Zhao et al. (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: