Advances in Brain-Computer Interfaces and Neural Integration
A Comparative Study of the Application of Artificial Intelligence in the Target Market: An Interdisciplinary Analysis
Abstract
Seyed Mahdi Fareghi
The purpose of this study is to examine Likert scale data with the aim of grouping and identifying the most flawless grouping through artificial intelligence. This type of data is widely used in various articles and research in various social sciences and humanities around the world. One of these valuable applications is in marketing. Data of this study were collected in the style of humanities research and their reliability and validity were examined and confirmed with common statistical methods worldwide so that their accuracy can be relied upon for generalization to the statistical community on a large scale. 460 sample responses from different individuals were collected using questionnaires from articles published in reputable journals. To analyze the success of clustering and detect similarities between clusters, artificial intelligence criteria and inferential statistics were used together to obtain stronger results. Results,Evaluated through effect size statistical measures, it was found that except for the farthest-first. Others did not show significant performance across the variables. The Findings suggest that clustering from the out toward the center is the most effective approach. This is An effective approach for categorizing when handling Likert-scale data that does not follow a normal distribution and construction.