Öz
Meeting customer needs in a timely manner has a significant impact on customer satisfaction. For this reason, the planning process has successfully influenced the success of sales activities. The crucial point for the success of the planning process depends on the sales forecasts. Sales forecasting estimates the quantity required by the customer needs. It helps in determining sales targets as campaigns, pricing, brand and product communication, and distribution channels are incorporated in the sales forecast. In this paper, we use regression and artificial neural networks to predict automobile sales in Turkey. The performance of regression is compared with that of an artificial neural network, and it is shown which network is able to predict. Thus, the result of the study, automobile sales in Turkey, was predicted and compared with the actual sales for 2020. The result is that the best prediction method will determine the automobile sales in Turkey.
Anahtar Kelimeler
Sales Prediction Artificial Neural Network Regression Analysis
Kaynakça
- Herrera, M., Torgo, L., Izquierdo, J., & Pérez-García, R. (2010). Predictive models for forecasting hourly urban water demand. Journal of Hydrology, 387(1–2), 141–150. https://doi.org/10.1016/j.jhydrol.2010.04.005
- İbrahim Zeki AKYURT. (2017). TALEP TAHMİNİNİN YAPAY SİNİR AĞL ARIYLA MODELLENMESİ : YERLİ OTOMOBİL ÖRNEĞİ. İSTANBUL ÜNİVERSİTESİ İKTİSAT FAKÜLTESİ EKONOMETRİ VE İSTATİSTİK DERGİSİ, November 2015.
- KILIÇ, G. (2015). YAPAY SİNİR AĞLARI İLE YEMEKHANE GÜNLÜK TALEP TAHMİNİ.
- Loureiro, A. L. D., Miguéis, V. L., & da Silva, L. F. M. (2018). Exploring the use of deep neural networks for sales forecasting in fashion retail. Decision Support Systems, 114(August), 81–93. https://doi.org/10.1016/j.dss.2018.08.010
- Mihriban YÜCESOY. (2011). İSTANBUL TEKNİK ÜNİVERSİTESİ - FEN BİLİMLERİ ENSTİTÜSÜ TEMİZLİK KAĞITLARI SEKTÖRÜNDE YAPAY SİNİR AĞLARI İLE TALEP TAHMİNİ YÜKSEK. Istanbul Teknik Üniversitesi.
- Santoni, M., Piva, F., Porta, C., Bracarda, S., Heng, D. Y., Matrana, M. R., Grande, E., Mollica, V., Aurilio, G., Rizzo, M., Giulietti, M., Montironi, R., & Massari, F. (2020). Artificial Neural Networks as a Way to Predict Future Kidney Cancer Incidence in the United States. Clinical Genitourinary Cancer, 1–8. https://doi.org/10.1016/j.clgc.2020.10.008
- Wang, F. K., Chang, K. K., & Tzeng, C. W. (2011). Using adaptive network-based fuzzy inference system to forecast automobile sales. Expert Systems with Applications, 38(8), 10587–10593. https://doi.org/10.1016/j.eswa.2011.02.100
- Wu, J. Da, & Liu, J. C. (2012). A forecasting system for car fuel consumption using a radial basis function neural network. Expert Systems with Applications, 39(2), 1883–1888. https://doi.org/10.1016/j.eswa.2011.07.139
- YAZICIOĞLU, N. (2010). YAPAY ZEKA İLE TALEP TAHMİNİ. In International Institute for Environment and Development: Vol. 07/80 (Issue 2). https://arxiv.org/pdf/1707.06526.pdf%0Ahttps://www.yrpri.org%0Ahttp://weekly.cnbnews.com/news/article.html?no=124000%0Ahttps://www.fordfoundation.org/%0Ahttp://bibliotecavirtual.clacso.org.ar/Republica_Dominicana/ccp/20120731051903/prep%0Ahttp://webpc.cia
- Uluslararası Yönetim İktisat ve İşletme Dergisi, Cilt 8, Sayı 17, 2012, ss. 87-100 91 Int. Journal of Management Economics and Business, Vol. 8, No. 17, 2012, pp. 87-100
Öz
Kaynakça
- Herrera, M., Torgo, L., Izquierdo, J., & Pérez-García, R. (2010). Predictive models for forecasting hourly urban water demand. Journal of Hydrology, 387(1–2), 141–150. https://doi.org/10.1016/j.jhydrol.2010.04.005
- İbrahim Zeki AKYURT. (2017). TALEP TAHMİNİNİN YAPAY SİNİR AĞL ARIYLA MODELLENMESİ : YERLİ OTOMOBİL ÖRNEĞİ. İSTANBUL ÜNİVERSİTESİ İKTİSAT FAKÜLTESİ EKONOMETRİ VE İSTATİSTİK DERGİSİ, November 2015.
- KILIÇ, G. (2015). YAPAY SİNİR AĞLARI İLE YEMEKHANE GÜNLÜK TALEP TAHMİNİ.
- Loureiro, A. L. D., Miguéis, V. L., & da Silva, L. F. M. (2018). Exploring the use of deep neural networks for sales forecasting in fashion retail. Decision Support Systems, 114(August), 81–93. https://doi.org/10.1016/j.dss.2018.08.010
- Mihriban YÜCESOY. (2011). İSTANBUL TEKNİK ÜNİVERSİTESİ - FEN BİLİMLERİ ENSTİTÜSÜ TEMİZLİK KAĞITLARI SEKTÖRÜNDE YAPAY SİNİR AĞLARI İLE TALEP TAHMİNİ YÜKSEK. Istanbul Teknik Üniversitesi.
- Santoni, M., Piva, F., Porta, C., Bracarda, S., Heng, D. Y., Matrana, M. R., Grande, E., Mollica, V., Aurilio, G., Rizzo, M., Giulietti, M., Montironi, R., & Massari, F. (2020). Artificial Neural Networks as a Way to Predict Future Kidney Cancer Incidence in the United States. Clinical Genitourinary Cancer, 1–8. https://doi.org/10.1016/j.clgc.2020.10.008
- Wang, F. K., Chang, K. K., & Tzeng, C. W. (2011). Using adaptive network-based fuzzy inference system to forecast automobile sales. Expert Systems with Applications, 38(8), 10587–10593. https://doi.org/10.1016/j.eswa.2011.02.100
- Wu, J. Da, & Liu, J. C. (2012). A forecasting system for car fuel consumption using a radial basis function neural network. Expert Systems with Applications, 39(2), 1883–1888. https://doi.org/10.1016/j.eswa.2011.07.139
- YAZICIOĞLU, N. (2010). YAPAY ZEKA İLE TALEP TAHMİNİ. In International Institute for Environment and Development: Vol. 07/80 (Issue 2). https://arxiv.org/pdf/1707.06526.pdf%0Ahttps://www.yrpri.org%0Ahttp://weekly.cnbnews.com/news/article.html?no=124000%0Ahttps://www.fordfoundation.org/%0Ahttp://bibliotecavirtual.clacso.org.ar/Republica_Dominicana/ccp/20120731051903/prep%0Ahttp://webpc.cia
- Uluslararası Yönetim İktisat ve İşletme Dergisi, Cilt 8, Sayı 17, 2012, ss. 87-100 91 Int. Journal of Management Economics and Business, Vol. 8, No. 17, 2012, pp. 87-100
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | İstatistik |
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Yayımlanma Tarihi | 30 Haziran 2023 |
| Gönderilme Tarihi | 8 Aralık 2021 |
| Kabul Tarihi | 8 Temmuz 2022 |
| Yayımlandığı Sayı | Yıl 2023 |
Kaynak Göster
