Industrial Management & Data Systems focuses on the convergence of industrial engineering, management science, and data analytics. It provides insights into the application of data-driven approaches to improve operational efficiency, enhance decision-making, and optimize processes within industrial settings. This journal is a relevant resource for academics, professionals, and decision-makers seeking to leverage data for business improvement.
Covering diverse topics, including data mining, business intelligence, decision support systems, supply chain optimization, and knowledge management, Industrial Management & Data Systems provides a holistic view of data applications in industry. It features original research articles, case studies, and reviews, highlighting practical methodologies and their impact on organizational performance. Indexed in databases like Scopus and Web of Science, Industrial Management & Data Systems ensures broad visibility. The audience includes industrial engineers, data scientists, and managers.
Authors are encouraged to contribute their data-driven insights to Industrial Management & Data Systems. By disseminating innovative applications of data analytics, the journal plays a vital role in fostering more efficient, competitive, and informed industrial practices, ultimately driving organizational success and innovation.