The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast

Abstract

This study examined revenue management practices, their effectiveness in optimizing revenue streams, the impact of emerging technologies, and the challenges faced by hotels in the Cape Coast Metropolis. Through qualitative interviews with ten hotel managers, key insights were uncovered regarding dynamic pricing, inventory control, market segmentation, and targeted promotions. For instance, hotels adjust room rates based on real-time demand, increasing prices during peak seasons and offering discounts in low-demand periods. Targeted promotions, such as corporate travel packages and repeat guest discounts, were also common strategies to enhance customer retention. Despite these strategies, challenges persist, including fluctuating market demand, ensuring rate parity across distribution channels, and internal limitations such as inadequate staff training and resource constraints. Managers reported difficulties in maintaining consistent pricing across online travel agencies (OTAs) and direct booking platforms, which sometimes led to booking leakages and customer dissatisfaction. Additionally, balancing revenue optimization with guest satisfaction remained a key concern. The integration of emerging technologies, such as AI-driven pricing models, predictive analytics, and automated revenue management systems, has provided hotels with a competitive edge. Some hotels have adopted AI-powered forecasting tools to predict demand, enabling optimal pricing decisions, while others utilize automated revenue management software to dynamically adjust inventory distribution. The study recommends that hotels invest in sophisticated revenue management software and advanced analytics tools to improve forecasting accuracy. Continuous staff training in data interpretation, market research, and AI applications should also be prioritized to enhance decision-making and optimize revenue management strategies.