| Yazarlar (5) |
Kemalettin Ağızan
Aydın Adnan Menderes Üniversitesi, Türkiye |
|
Zeki Bayramoğlu
Selçuk Üniversitesi, Türkiye |
Prof. Dr. Hasan Gökhan DOĞAN
Kırşehir Ahi Evran Üniversitesi, Türkiye |
|
Yusuf Çelik
Selçuk Üniversitesi, Türkiye |
|
Zuhal Karakayacı
Selçuk Üniversitesi, Türkiye |
| Özet |
| The primary objective of this study is to assess potential savings opportunities in agricultural enterprises and to determine their feasibility. To this end, face-to-face interviews were conducted with 268 agricultural enterprises in Turkey, selected according to the stratified random sampling method. The results of the interviews revealed the amount of savings accrued by agricultural enterprises and the factors influencing the formation of savings. The data obtained was then used to determine the savings potential of agricultural enterprises using artificial neural networks. The classification analysis in the artificial neural network model enables the prediction of the savings potential of enterprises by classifying them according to all the variables included in the model, in comparison to the classification made with the existing data. This approach allows for the consideration of not only financial indicators but also socio-economic factors, personal factors and environmental factors in determining savings policies, thereby revealing the actual potential of the enterprises. To determine the savings potential of the analyzed enterprises, 29 different models in 9 model classes were tested. Consequently, the model class with the highest accuracy was identified as decision trees. The accuracy of decision trees varies between 82.5% and 85.1%. While 62.69% of the enterprises exhibited high savings because of the modelling process, this value was determined as 60.8% because of the prediction model. Furthermore, the proportion of enterprises with low savings, which was estimated at 32.84% in the data model, was found to be 35.8% in the prediction model. Additionally, the proportion of enterprises with negative savings was determined to be 4.48% in the data model and 3.4% in the prediction model. The study identified the structural, social and economic characteristics of enterprises according to their savings structures and evaluated potential for increasing savings. It was determined that agricultural enterprises should focus on ways to increase savings, increase income, keep expenses under control and make investments for the future. Efficient farming techniques, the formation of agricultural cooperatives and marketing associations, the reduction of energy and input costs, the effective utilization of agricultural machinery, and the investment in renewable energy sources could assist agribusinesses in increasing their economic security and sustainability. All these steps enable agricultural households to have a stronger and more sustainable financial structure and contribute to the economic development of rural areas. |
| Anahtar Kelimeler |
| Agricultural enterprises | Artificial neural networks | Savings |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | ESCI dergilerinde yayımlanan tam makale |
| Dergi Adı | Tekirdağ Ziraat Fakültesi Dergisi |
| Dergi ISSN | 1302-7050 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | ESCI |
| Makale Dili | Türkçe |
| Basım Tarihi | 05-2025 |
| Cilt No | 22 |
| Sayı | 2 |
| Sayfalar | 428 / 440 |
| Doi Numarası | 10.33462/jotaf.1491320 |
| Makale Linki | https://doi.org/10.33462/jotaf.1491320 |
| Atıf Sayıları |
