Manuscript Abstract

AN ANALYSIS OF THE FACTORS AFFECTING THE CONSUMPTION OF GEOGRAPHICALLY INDICATED PRODUCTS USING DECISION TREE AND ARTIFICIAL NEURAL NETWORKS
T. Çukur, N. Kızılaslan, H. Kızılaslan, F. Çukur

T. Çukur, N. Kızılaslan, H. Kızılaslan and F. Çukur

1Muğla Sıtkı Koçman University, Milas Vocational School, Milas, Muğla, Turkey

2Tokat Gaziosmanpaşa University, Agricultural Faculty Department of Agricultural Economics, Tokat, Turkey

Corresponding Author: tayfun.cukur@hotmail.com
Page Number(s): 1062-1071
Published Online First: January 06, 2022
Publication Date: July 30, 2022
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
Open Access: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).


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