Towards Smart Warehouse Management in Vietnam: A Review on AI and IoT Integration in the Logistics Industry

Smart warehouse management powered by Artificial Intelligence (AI) and the Internet of Things (IoT) has emerged as an important area of research and application in logistics. This paper conducts a literature review by retrieving data from the Scopus database and performing bibliometric analysis with VOSviewer to identify prominent trends, authors, countries, and research themes. The findings reveal that international studies have mainly focused on four clusters: connectivity infrastructure and big data, automation and robotics, smart device applications, and data-driven decision-making. The study also highlights the benefits, challenges, and research gaps in the implementation of smart warehouses in emerging economies, particularly in Vietnam. Based on these insights, the paper proposes a smart warehouse model together with research directions and policy recommendations to foster the adoption of AI and IoT in warehouse management, thereby enhancing supply chain efficiency and competitiveness in the context of globalization. Research purpose: The study aims to analyze global research trends, themes, and gaps in smart warehouse management using AI and IoT technologies and to propose a model and policy recommendations suitable for emerging economies such as Vietnam. Research motivation: With the rapid development of AI and IoT, warehouse management is shifting to smarter and more data-driven systems. However, most of the research and applications are concentrated in developed countries, creating a gap in understanding and implementing smart warehouses in developing countries. Research design, approach, and method: A systematic literature review was conducted using data retrieved from the Scopus database. Bibliometric analysis was performed with VOSviewer to visualize key research clusters, influential authors, and emerging topics related to AI- and IoT-based warehouse management. Main findings: The analysis identified several key research clusters and proposed a smart warehouse model to improve operational efficiency and guide future research and practice. Practical/managerial implications: The proposed smart warehouse model and policy recommendations provide guidance for managers and policymakers to adopt AI and IoT technologies effectively, enhance supply chain performance, and strengthen competitiveness in the era of digital transformation.