معرفی
Arash Laghaie is an Assistant Professor at NOVA School of Business and Economics (NOVA SBE), NOVA University Lisbon, Portugal. His research focuses on advancing methodological frameworks in marketing and econometrics, particularly in causal inference and measurement modeling.
His research interests lie at the intersection of marketing science, behavioral economics, and statistical modeling. He investigates mediation analysis under measurement error, causal modeling with latent variables, and discrete choice behavior through the lens of rational inattention. These themes reflect a strong methodological orientation aimed at improving the validity and interpretability of empirical marketing models.
The analysis of his recent publications reveals a consistent focus on methodological rigor in marketing research. His work integrates Bayesian inference, causal mediation, and behavioral decision theory, particularly in modeling consumer choices under information constraints. The research contributes to both theoretical and applied marketing by enhancing the robustness of inferences in the presence of measurement imperfections and unobserved heterogeneity.
While no scientific awards are explicitly mentioned in the provided text, Arash Laghaie's work has been published in top-tier journals such as Journal of Marketing Research and Quantitative Marketing and Economics, indicating recognition within the academic community.
There is no publicly listed information regarding student advising or research grants in the provided content. However, his active research output and collaboration with established scholars like Tom Otter suggest engagement in ongoing research projects and potential mentorship roles.
Arash Laghaie is involved in research networks related to marketing analytics and econometric modeling. His work contributes to the broader fingerprint of topics including mediation, measurement error, causal models, and discrete choice, forming a cohesive research profile centered on improving empirical methods in marketing science.
