Akademik Veri Yönetim Sistemi
Business Process Management Journal, ss.1-34, 2026 (SSCI, Scopus)
Purpose – In today's rapidly evolving artificial intelligence (AI) industry, understanding the factors that drive company performance is crucial for sustaining competitive advantage. This research investigates how knowledge acquisition and sharing abilities influence company performance by examining the mediating roles of innovation culture and technology innovation strategy in AI companies operating in Istanbul/Turkey Technoparks. Design/methodology/approach – Data were collected through face-to-face surveys from 329 senior managers and directors in AI-focused companies located in Technoparks in Istanbul. These companies were selected due to their focus on technologically advanced AI, making them ideal for examining the interaction between innovation and knowledge management. The collected data were analyzed to test the hypothesized mediation effects, and the Jamovi 2.3 program was used to process all data for the research. Findings – The results show that innovation culture significantly mediates the relationships between both knowledge acquisition capability and knowledge sharing capability and firm performance. Furthermore, the mediating role of technology innovation strategy in the relationship between knowledge acquisition capability and firm performance, and in the relationship between knowledge sharing capability and firm performance, is supported. These findings highlight the critical role of knowledge acquisition in driving innovation and improving firm performance in AI-focused firms. Research limitations/implications – The research is limited by its focus on AI firms in a specific geographic region, which may affect the generalizability of the findings. Future research can expand the scope to include other regions and industries to validate and expand the results. Furthermore, longitudinal research may provide deeper insights into the causal relationships between knowledge management capabilities and firm performance. Practical implications – The research provides strategic insights for AI firms, highlighting the importance of developing a strong knowledge management framework to sustain innovation and competitiveness. Managers should prioritize knowledge acquisition efforts and develop an innovation-oriented culture to enhance firm performance. While technology innovation strategy is crucial for evaluating acquired knowledge, firms should explore additional mechanisms to optimize the impact of knowledge sharing. Originality/value – By focusing on AI firms in a rapidly evolving technological environment, this research expands understanding of how knowledge acquisition and sharing affect firm performance. It contributes to the knowledge management and innovation literature by establishing empirical links between these capabilities and strategic innovation processes in AI firms.