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    Öğe
    Decision tree analysis of consumers' intentions to purchase coffee in glass flasks
    (2021) Irmak, Sezgin; Demir, Mehmet Özer
    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.
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    Öğe
    Voter classification based on susceptibility to persuasive strategies: A machine learning approach
    (Springer, 2020) Demir, Mehmet Özer; Simonetti, Biagio; Başaran, Murat Alper; Irmak, Sezgin
    The current literature on the campaigns of political marketing is based on mass communication. However, the online community introduces new opportunities, one of them is captology. As a part of captology, the persuasive strategies take increasing attention from both authors and practitioners. There is a growing literature that persuasive technologies are useful in the attitudinal and behavioral change of the targeted group, which is the aim of political marketing. This research introduces the persuasive strategies into political marketing literature. In this manuscript, respondents are discriminated based on their susceptibility to the persuasive strategies to determine which persuasive strategy has effects on liberals and conservative. Findings suggest that liberals and conservatives can be discriminated based on their susceptibility to persuasive strategies using machine learning algorithms. The findings of the study offer new insights into political marketing campaigns.