AI-Driven Consumer Search Behavior and Price Competition in Agile Supply Chains: A Game Theoretic Approach

Price competition is one of the most important issues in supply chain management and industrial economics. In digital markets, the rapid development of artificial intelligence (AI) technologies has significantly changed consumer search behavior and firms’ pricing strategies. AI-powered recommendation systems, intelligent price comparison tools, and digital platforms have reduced customer search costs and increased market transparency. This study investigates the impact of AI-driven consumer search behavior on price competition in a multi-level supply chain.A game theoretic model based on Bertrand competition is developed in which two manufacturers and two agile retailers compete in price while consumers use AI-assisted search technologies. Consumers are divided into AI-assisted searchers and traditional consumers. The model analyzes how AI adoption changes equilibrium prices, firms’ profits, and consumer welfare.The results show that increasing AI adoption intensifies price competition and reduces equilibrium prices in the market. Furthermore, agile retailers benefit more from AI-driven markets due to their faster responsiveness and pricing flexibility. Sensitivity analysis demonstrates that higher AI accuracy and lower search costs increase consumer welfare while reducing the pricing power of firms.

کلیدواژه ها:

Supply Chain Management ، Game Theory ، Bertrand Competition ، Artificial Intelligence ، Consumer Search Behavior ، Agile Retailing