Comparison of Studies Conducted in the Field of Neuromarketing and Artificial Intelligence Using Bibliometric Method - Abdullah Ballı (Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi)
AbstractNeuromarketing research focuses on consumer purchase intention, decision-making processes, purchase behavior, brand awareness, brand loyalty, and repeat purchase behavior. In these studies, consumer behavior has been analyzed using neuroscientific methods and tools. The most commonly used tools include Functional Magnetic Resonance Imaging (fMRI), Eye Tracking, Electroencephalogram (EEG), Positron Emission Tomography (PET), Transcranial Magnetic Stimulation (TMS), Magnetoencephalogram (MEG), Steady State Topography (SST), Implicit Association Test (IAT), Facial Electromyography (fEMG), Automatic Face Coding (AFC), Skin Conductance Response (SCR), and other methods for measuring physiological responses. However, the use of these neuroscientific tools is not always possible due to economic constraints and lack of experimental design. Neuroscientific imaging and measurement methods are not preferred in every study due to their high costs and expertise requirements. However, when neuromarketing studies are examined, it is seen that methods such as Eye Tracking, EEG and fMRI are used more widely. These tools contribute to a deeper understanding of consumer behavior. In order to better analyze consumer behavior, it is of great importance to convey marketing stimuli and messages correctly. In the field of marketing, the effect of stimuli conveyed to consumers using the five senses is one of the focal points of neuromarketing. More than one neuroscientific method should be used together to understand consumer intentions, thoughts and purchasing behaviors. In this way, the obtained data can be analyzed more comprehensively and clearer insights can be provided about neuromarketing. The aim of this study is to present a comprehensive assessment of the use of neuroscientific tools by examining the publications in the field of neuromarketing in the Web of Science database between 2010-2024 with bibliometric analysis. The study will address the limitations of not using more than one neuroscientific tool together in neuromarketing research and the inadequacy of analyses supported by artificial intelligence. A more holistic approach will be proposed to address these shortcomings and a guiding resource for future research will be created.