Karar Ağaçları Kullanılarak Tüketicilerin Cam Ambalajda Kahve Satın Alma Niyetlerinin Analizi

Year 2021, Volume: 16 Issue: 1, 17 - 33, 01.04.2021

Sezgin Irmak , Mehmet Özer Demir

https://doi.org/10.17153/oguiibf.663171

Abstract

Bu araştırma, tüketicilerin cam ambalajda sunulan hazır kahve tüketimi niyetlerini belirlemeye dönük olarak algılarını ve karakteristiklerini tanımlamayı amaçlamaktadır. Bu bağlamda çalışma, tüketicilerin cam ambalajda sunulan içilmeye hazır kahve konusundaki beklentilerini belirlemek için, gıda ile ilgili yaşam tarzı ve paketleme seçimi ölçeklerini değerlendirmektedir. Çalışmada karar ağaçlarını yapılandırmak ve elde edilen en iyi karar ağacını görselleştirmek için CHAID algoritmasından yararlanılmıştır. Satın alma niyeti hedef değişken olup, 16 faktör değişkeni ve 12 demografik değişken de tahmin edici değişkenlerdir. Sonuçlar, tüketicilerin cam ambalajda sunulan içilmeye hazır kahve alma niyetlerinin doğru koruma, çekicilik, sağlıklılık ve kahve türü tercihi değişkenleri ile belirlenebileceğini göstermektedir. Karar ağacı modeli satın alma eğilimlerine göre tahmin edici değişkenler bakımından tüketici profilini ortaya çıkarmaktadır.

Keywords

Karar Ağaçları, Tüketici Niyeti, CHAID, Kahve Ambalajlama

Decision Tree Analysis of Consumers’ Intentions to Purchase Coffee in Glass Flasks

Abstract

The aim of this research is to determine the perceptions and the characteristics of consumers to determine their intentions to purchase ready to drink coffee in glass flasks. In this context, this study assesses the food-related lifestyle, and the packaging choice scales to investigate consumers' expectations about ready to drink coffee offered in glass flasks. The study operationalizes CHAID algorithm to build decision trees and visualizes the best obtained decision tree. Intention to purchase is the target variable, 16 factor variables and 12 demographic variables are predictive features. Results suggest that consumers’ intentions to purchase ready to drink coffee in glass flasks can be determined by correct preservation, attractiveness, healthiness, and the type of coffee preferences. Decision tree model reveals the consumer profiles in terms of the predictive variables.

Keywords

Decision Trees, Consumer Intentions, CHAID, Coffee Packaging

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