Digital Transformation, Supply Chain Management and AI Adoption in Business Operations
This research community examines how organizations adopt information technology, artificial intelligence, and digital tools to manage operations, supply chains, and decision-making processes.
The work focuses on the integration of artificial intelligence, machine learning, and big data into business models and supply chain logistics. Recurring themes include the management of lead times, technology outsourcing, and the impact of digital transformation on innovation and sustainability. The community also investigates the adoption of open-source software, the role of social media in business, and the application of decision support systems in higher education and professional services. Methodologies frequently cited include systematic literature reviews, case studies, and ontology engineering to structure knowledge management.
The community is most prominent in research tracked for Tin, accounting for 0.2% of that element's literature, followed by Indium (0.2%) and Neon (0.5%). Tin also represents the highest paper count within this group, with 278 papers.
The community comprises 11,089 papers, with the majority published in the Journal of the Association for Information Systems, the European Journal of Operational Research, and the International Journal of Production Economics.
Recent work addresses the use of large language models for web accessibility and job scheduling, the resilience of distribution networks, and the detection of cyber threats using neuromorphic learning.