STRATEGIC DECISION-MAKING IN DIGITAL RETAIL SUPPLY CHAINS: HARNESSING AI-DRIVEN BUSINESS INTELLIGENCE FROM CUSTOMER DATA

Abstract

In the evolving landscape of digital retail, the evaluation of vendor performance has become a strategic imperative, driven by the integration of advanced technologies such as Artificial Intelligence (AI), blockchain, the Internet of Things (IoT), and cloud computing. This systematic review critically examines 102 peer-reviewed studies published between 2010 and 2022 to explore how AI-enabled tools are transforming vendor performance evaluation within digital retail supply chains. By synthesizing literature from supply chain management, information systems, and operations strategy, the review identifies core themes, methodological trends, and theoretical gaps, offering a holistic understanding of the digital transformation underway in performance evaluation frameworks. The findings reveal that digital technologies have transitioned from auxiliary functions to foundational elements in retail performance systems. AI and machine learning emerged as the most widely adopted tools, cited in 61 of the reviewed studies, and are primarily leveraged for predictive modeling, anomaly detection, and optimization of vendor-related decisions. IoT-enabled real-time monitoring and blockchain-based traceability were also prominent, underscoring a shift from static performance reporting to continuous, intelligent data ecosystems. These technologies have collectively enabled real-time dashboards, algorithmic forecasting, and dynamic KPI systems that directly support strategic decisions such as supplier selection, sustainability investment, and omnichannel distribution planning. The review further highlights the importance of context in designing and deploying performance evaluation systems, particularly in multinational supply chains. Cultural, regulatory, and infrastructural differences were found to shape the interpretation and effectiveness of performance models across global operations. Hybrid systems that balance global consistency with local adaptability are gaining traction as viable solutions to these challenges. Despite the technological and operational advances, the review notes a lack of cohesive theoretical frameworks underpinning performance evaluation practices in the digital era. While several studies propose novel models, theoretical fragmentation remains a major limitation, preventing broader generalization and cross-industry application. This study contributes to the literature by proposing a context-aware, technology-integrated framework for vendor performance evaluation and calls for future research to develop unified models that incorporate strategic alignment, technological enablers, and ethical governance. The findings offer valuable insights for academics, digital transformation leaders, and supply chain practitioners aiming to optimize performance management in an increasingly complex and data-driven retail environment.