معرفی
Flavio Costa Romão is a Visiting Assistant Professor at ISEG, School of Economics and Management, University of Lisbon. He is actively engaged in teaching and research at the intersection of data analytics, artificial intelligence, and management, with applications in operations, marketing, and organizational transformation.
His educational background includes a PhD in Management (2024) from ISEG/University of Lisbon and a Master’s in Statistics and Information Management (2010) from Universidade Nova de Lisboa.
His research centers on how organizations leverage technology to improve decision-making, generate value, and drive meaningful change. Key interests include digital transformation, data democratization, and AI integration in business contexts. He adopts a theory-grounded yet practice-oriented approach, often applying action research and case studies in real-world settings.
The recent articles reflect a strong trend in applying big data analytics and AI to solve business challenges in industries such as telecom and energy. His work emphasizes practical implementation, organizational adoption, and measurable business outcomes.
- Business Benefits from Big Data Analytics: A Multiple Case Study Approach (2024)
- Achieving Business Benefits Through Big Data Analytics: A Case Study in the Telecom Industry (2024)
- Democratizing Data-Driven Decision-Making – An Action Research Study On Sales Teams In An Energy Company (2025)
- e-Business: estratégias e modelos (2010)
- Business sustainability with AI (2023)
He has supervised at least one Master’s student, Carolina Cardoso e Conchinha, on a thesis related to data democratization in energy sector sales teams. While no formal grants are mentioned, his research projects involve direct collaboration with industry, suggesting applied funding or institutional support. He teaches core courses such as Management Information Systems, AI for Management, and Digital Business and Operations across undergraduate and graduate programs.
He is affiliated with ISEG’s research ecosystem, contributing to publications and academic events like MCIS. His work aligns with ISEG’s focus on data-driven management and innovation through labs such as Data Lab and Policy Lab, though direct lab membership is not specified.
