The growing competition among coffee shops demands effective strategies, including the development of optimal pricing. An optimal pricing strategy must account for both changes in coffee ingredients and consumers' willingness to pay (WTP). This study investigated the factors influencing consumers' WTP and determined optimal prices through sensory evaluations of iced coffee. This study explored how demographic factors and sensory characteristics affect consumer WTP. This study involved direct consumer tastings, where participants provided subjective ratings of iced coffee and indicated their WTP. The coffee samples included variations in milk (white and black coffee) and sugar content (granulated sugar, palm sugar, and no sugar). To measure WTP, the Becker-DeGroot-Marschak (BDM) mechanism was employed, while a demand function was used to determine the optimal price. Stepwise backward logistic regression further analyzed the factors affecting WTP. The factors influencing willingness to pay were further analyzed using stepwise backward logistic regression. The findings reveal that optimal pricing varies, with iced coffee that includes both granulated sugar and milk commanding the highest WTP. Consumer WTP is significantly influenced by factors such as gender, frequency of coffee consumption, and individual taste preferences. There was a marked difference in WTP based on the amount of milk and sugar added, with coffee variations containing both granulated sugar and milk achieving the highest WTP. These results can serve as a valuable reference for coffee shops, helping them to determine the ideal product composition and pricing strategies to maximize revenue.
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