AN ANALYSIS OF THE FACTORS AFFECTING THE CONSUMPTION OF GEOGRAPHICALLY INDICATED PRODUCTS USING DECISION TREE AND ARTIFICIAL NEURAL NETWORKS Authors: T. Çukur, N. Kızılaslan, H. Kızılaslan, F. Çukur Journal: Journal of Animal and Plant Sciences (JAPS) ISSN: 1018-7081 (Print), 2309-8694 (Online) Volume: 32 Issue: 4 Pages: 1062-1071 Year: 2022 DOI: http://doi.org/10.36899/JAPS.2022.4.0510 URL: https://doi.org/http://doi.org/10.36899/JAPS.2022.4.0510 Publisher: Pakistan Agricultural Scientists Forum Abstract:

In the present study, the consumer perception and consumption level of Geographically Indicated Products (hereafter GIP) in the Tokat province of Turkey has been investigated. The data were collected from 382 consumers through a questionnaire. Artificial neural networks and decision tree models were used to determine the factors affecting the consumers' consumption of the specified products. Results indicated that the variables of monthly walnut consumption, whether Niksar walnuts are known to be a GIP, monthly income level, the willingness to pay more for a GIP and whether they read labels on GIP packaged products affected consumption.

Keywords: data mining, machine learning, algorithm, geographical indication, decision tree