AN ANALYSIS OF THE FACTORS AFFECTING THE CONSUMPTION OF GEOGRAPHICALLY INDICATED PRODUCTS USING DECISION TREE AND ARTIFICIAL NEURAL NETWORKS
Yazarlar (4)
Muğla Sıtkı Koçman Üniversitesi, Türkiye
Prof. Dr. Nuray KIZILASLAN
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Prof. Dr. Halil KIZILASLAN
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Muğla Sıtkı Koçman Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
|
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | Journal of Animal and Plant Sciences |
| Dergi ISSN | 1018-7081 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q4 |
| Makale Dili | İngilizce |
| Basım Tarihi | 08-2022 |
| Cilt No | 32 |
| Sayı | 4 |
| Sayfalar | 1062 / 1071 |
| DOI Numarası | 10.36899/JAPS.2022.4.0510 |
| Makale Linki | https://www.thejaps.org.pk/ |
| Özet |
| 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. |
| Anahtar Kelimeler |
| data mining | machine learning | algorithm | geographical indication | decision tree |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| SCOPUS | 1 |
| Google Scholar | 3 |