The Role of Artificial Intelligence-Driven Pricing Strategies in Shaping Competitive Advantage within the Triple Helix Innovation Ecosystem
Fidan Safarova 
Abstract. This study examines the impact of pricing strategies on competitive development within the framework of the Triple Helix model, emphasizing the interaction among government, universities, and industry in fostering innovation-driven economic growth. In contemporary knowledge-based economies, pricing strategies have evolved beyond traditional cost-oriented approaches and have become strategic instruments for the commercialization, diffusion, and market acceptance of innovative products and services. The research explores the effectiveness of value-based pricing, dynamic pricing, and psychological pricing mechanisms in enhancing firms’ market positioning, customer value perception, and innovation performance.
Particular attention is given to the role of collaborative innovation ecosystems, where universities generate knowledge, industries transform research outputs into marketable innovations, and governments establish supportive regulatory and financial environments. Within this ecosystem, pricing decisions significantly influence technology transfer processes, research commercialization outcomes, and the sustainable competitiveness of enterprises. The study further investigates the integration of artificial intelligence (AI) and advanced analytics into pricing models, demonstrating how machine learning algorithms facilitate real-time market analysis, demand forecasting, customer segmentation, and adaptive pricing decisions.
Keywords: Triple Helix model, innovation commercialization, artificial intelligence-based pricing, competitive advantage, sustainable economic development