December 6, 2025
Manijeh Bahrainizad

Manijeh Bahrainizad

Academic Rank: Associate professor
Address:
Degree: Ph.D in Business Management- Marketing
Phone: 07733442125
Faculty: School of Business and Economics

Research

Title
Systematic review of neuromarketing studies from 2010 to 2024 in the Web of Science and Scopus databases
Type Thesis
Keywords
واژگان كليدي: مرور سيستماتيك ، بازاريابي ، بازاريابي عصبي ، علوم اعصاب ، رفتار مصرف كننده ، پايگاه داده اسكوپوس ، پايگاه داده وب آف ساينس
Researchers maryam ghayedi (Student) , Manijeh Bahrainizad (First primary advisor) , Zaeimeh Nematolahi (Advisor)

Abstract

Background: In today’s world, understanding the needs and wants of individuals is one of the most important pillars of marketing. Companies and organizations need to have a close relationship with customers to respond to these needs. Given the importance of hidden human needs, researchers and organizations are seeking to understand the human brain and behavior using various methods from cognitive science and other disciplines. These efforts have paved the way for the emergence of neuromarketing, which allows organizations to predict customer behavior and have a significant impact on society. Aim: The present study was conducted with the aim of systematically reviewing neuromarketing studies from 2010 to 2024 in the Web of Science and Scopus databases. In fact, the main goal of this study emphasizes the following: to have a comprehensive and accurate framework for the awareness of marketers, researchers, and people who want to work in this field in their industry. Methodology: In this study, a systematic review of neuromarketing was conducted between 2010 and 2024, and 13 research questions were formulated. Data were collected with a precise search strategy in Scopus and Web of Science databases, and after merging and removing duplicate records with Python, 1014 articles were finalized. Data analysis was performed with VOSviewer and CiteSpace software, and for supplementary questions, text mining and regex dictionary were used in Python. Scientometric indices including Modularity Q, Silhouette Score, and Betweenness Centrality were used to evaluate clusters and the role of nodes. The final results were a combination of software output and coding analysis and were presented in the form of tables, graphs, and science maps. Conclusions: The research findings showed that since 2010, the growth trend of neuromarketing has accelerated and tools such as EEG, fMRI and eye tracking play a key role in studying consumer behavior. Countries such as the United States, Spain and I