Laura Trinchera

Laura Trinchera is a Professor of Statistics at NEOMA Business School, specializing in data analysis, statistical learning methods, and structural equation modeling. She holds a Master’s in Economics and Management from the University of Naples Federico II, Italy, and a PhD in Statistics (2008) from the same institution. Her research focuses on advanced statistical methodologies such as Partial Least Squares (PLS), clustering algorithms, and applications in supply chain management and marketing. She has held visiting researcher positions at institutions including University of California Santa Barbara, University of Michigan, Hamburg University, and HEC Paris.

Her work spans interdisciplinary fields, including:

• Development of PLS-based methodologies for complex data structures
• Analysis of unobserved heterogeneity in longitudinal growth models
• Applications of AI in environmental performance and retail analytics
• Exploration of consumer behavior in sustainable diets and eating disorders

Recent publications highlight her contributions to:

• AI-driven dynamic capabilities for environmental management
• Statistical methods for detecting hidden patterns in longitudinal data
• Impact of mobile commerce on retail performance
• Role of marketing capabilities in SMEs

Her collaborative network includes partnerships with leading universities worldwide, emphasizing methodological advancements in data science and their practical applications. She actively participates in academic conferences, contributing to the advancement of PLS techniques and composite indicator systems.