This study investigates the impact of asymmetric information on pricing and facility planning decisions in independent coffee shops. By applying Principal Agent Theory, the research models how shop owners (principals) make decisions without knowing whether customers (agents) intend to dine in or take away. Using incentive compatible and individual participation constraints (IPCs), two pricing scenarios, dine-in and takeaway pricing packages are formulated and compared through expected revenue analysis. Results show that dine-in pricing consistently yields higher revenue across varying customer behaviours, particularly as the dine-in probability increases. This finding suggests that strategically segmenting pricing based on customer intention can bridge the information gap, optimise resource allocation, and enhance profitability in small service enterprises. The study offers a practical decision-making framework that is especially relevant for businesses with limited access to behavioural data analytics.
Fadhilah et al. (Thu,) studied this question.