Impact of strategic performance measures on performance: The role of artificial intelligence and machine learning

This study highlights the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on business logistics and operations, driving efficiency and strategic decisionmaking. With the logistics AI market anticipated to reach USD 31.58 billion by 2028, AI and ML's role in enhancing operational performance and reducing costs is evident. Despite this, the application of AI and ML in improving strategic performance measures-namely Information Sharing, Decision Synchronization, and Logistics Efficiency-and their influence on firm and operational performance remains underexplored. This research bridges this gap by leveraging the Dynamic Capabilities View to explore how AI and ML technologies influence the relationship between strategic performance indicators and both firm and operational performance. Utilizing a multi-method analysis, including PLS-SEM and fuzzy-set Qualitative Comparative Analysis, we explore the complex dynamics between strategic performance outcomes and the integration of AI and ML technologies. Our findings from PLS-SEM indicate that AI and ML significantly influence Firm Performance but not Operational Performance. Further analysis highlights that logistics efficiency, integrated with AI and ML, can enhance firm performance, showcasing AI and ML as critical components of firm success. This study contributes to the fields of information systems and supply chain management by offering an innovative perspective on how AI and ML can empower firms, particularly within the United States and Canadian Business to Business and Business to Government sectors, to improve their firm and operational performance. It provides a strategic framework for managers to leverage these technologies effectively, enriching both theory and practice.