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

Emmanuel Dornyoh; Mary Acquaye Moore; Richmond Yeboah; Abdul-Muhaeminu Tamakloe Ocloo; Franklin Dzormeku Dacosta

doi:doi:10.11648/j.ijhtm.20261001.12

Research Article |

| Peer-Reviewed

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

Emmanuel Dornyoh

, Mary Acquaye Moore

, Richmond Yeboah^*

, Abdul-Muhaeminu Tamakloe Ocloo

, Franklin Dzormeku Dacosta

Published in International Journal of Hospitality & Tourism Management (Volume 10, Issue 1)

Received: 1 November 2025 Accepted: 7 January 2026 Published: 16 January 2026

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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.

Published in	International Journal of Hospitality & Tourism Management (Volume 10, Issue 1)
DOI	10.11648/j.ijhtm.20261001.12
Page(s)	7-21
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

Revenue Management, Profitability, Hotels, Dynamic Pricing, Inventory, Technology

1. Introduction

Hotels are inherently characterized by stable capacity, perishable inventory, high fixed costs, variable demand, and intense competition

[32]

. Dolnicar et al.

[17]

indicated that the sector is highly sensitive to external factors, including technological advancements (integration of AI, IT, and robotics), economic fluctuations (recessions, inflation, and rising costs), health crises (pandemics and epidemics), geopolitical events (the Russia-Ukraine conflict), and evolving customer preferences (remote work, rise of Airbnb, etc). These factors contribute to ongoing occupancy challenges, directly affecting revenue generation and profitability.

Traditionally, hotels have relied on reactive measures to address low occupancy, such as no booking (walk-ins only) or excessive overbooking

[28, 37]

. However, these measures often prove counterproductive. To effectively meet guest needs while maintaining service quality, hotels have increasingly adopted proactive approaches framed as “revenue management” strategies

[28]

. Revenue management is defined as “the process of allocating the right type of capacity to the right kind of customer at the right price to maximize revenue or yield”

[36]

. It involves strategies such as market segmentation, demand forecasting, efficient room inventory allocation, strategic pricing, and distribution channel optimization

[39]

. These strategies take into account fluctuations in demand and market conditions

[2]

to optimize revenue, profitability, and a hotel’s overall potential

[30]

Research demonstrates that effective revenue management strategies enable hotels to leverage pricing elasticity and market segmentation to generate additional revenue from specific customer segments

[61]

. This not only improves short-term revenue but also enhances hotels’ long-term competitiveness and financial sustainability

[30]

. Given the diversity and dynamism of hotel markets and consumer preferences, revenue management strategies must be tailored to specific market conditions and hotel segments

[69]

. Thus, despite significant research on revenue management, gaps remain in understanding its effectiveness in diverse contexts, particularly in Ghana’s unique socio-economic and cultural environment.

Ghana’s hospitality industry faces challenges such as seasonal demand fluctuations, inadequate infrastructure, and evolving consumer preferences

[6]

. Owusu

[44]

emphasizes that Ghana’s hotel revenue management practices are influenced by economic factors, cultural nuances, and infrastructure constraints. Furthermore, Ghana’s membership in the World Tourism Organization (UNWTO) has exposed local hotels to heightened competition from international operators. To thrive in this competitive environment, the industry must adopt robust operational management techniques. Several studies have explored aspects of revenue management within Ghana’s hotel industry. For instance, Asamoah and Gyapong

[9]

, Owusu et al.

[43]

, Amuah

[6]

, and Owusu

[44]

have examined revenue management practices from different facets of the hospitality sector. Ansah, Abor, and Biekpe

[8]

investigated financial management practices in Ghanaian hotels, highlighting the importance of efficient financial strategies for long-term viability. Their findings underscore the close connection between financial decision-making and revenue management.

Similarly, Yeboah and Amoako

[64]

studied branding and marketing, emphasizing their role in enhancing competitiveness and driving revenue generation. Teye, Sirakaya-Turk, and Sönmez

[54]

explored destination image and tourist perceptions, shedding light on factors influencing visitor behaviour and spending habits, key insights for tailoring revenue management strategies. Adongo, Abubakari, and Narteh

[1]

examined the impact of governmental policies and regulations on Ghana’s hotel sector, focusing on taxation, licensing, and other legal frameworks that directly affect revenue management and profitability. While these past studies provide valuable insights into specific aspects of revenue management, there remains a gap in comprehensive research addressing the holistic effectiveness of revenue management strategies within Ghana’s unique socio-economic and cultural context. This study seeks to bridge this gap by evaluating the effectiveness of revenue management strategies on profitability, focusing on a sample of hotels in the Cape Coast Metropolis. By addressing existing research deficiencies, this study aims to offer practical recommendations for hotel managers to enhance revenue management and improve profitability in a highly competitive market. The study answers the research question: to what extent do revenue management strategies influence profitability?

2. Theoretical Framework

The Dynamic Capabilities Theory (DCT), as introduced by Teece, Pisano, and Shuen

[53]

, has emerged as a critical framework for understanding how organizations sustain competitive advantage in rapidly changing environments. The theory posits that firms can achieve long-term success not merely by controlling valuable resources but by dynamically reconfiguring their resource base to meet evolving market demands. DCT posits that this can be achieved through three core processes: sensing opportunities and threats; seizing opportunities; and transforming organizational resources to remain competitive.

Sensing involves identifying opportunities and threats through market intelligence, customer behaviour analysis, and demand forecasting. In the hospitality sector, this involves analyzing historical data, customer feedback, and external market indicators for shifts in customer preferences, technological advancements, and competitor strategies to inform revenue management. For example, during peak periods like festivals, hotels can anticipate increased demand and adjust pricing strategies accordingly. During low-demand periods, promotional pricing and targeted discounts can help attract more customers

[27, 42]

Dolnicar et al.

[17]

assert that the seizing phase focuses on deploying resources to capitalize on opportunities identified in the previous phase. It can entail implementing dynamic pricing, market segmentation, and inventory control, which is tailored to current market conditions. To achieve this requires real-time rate adjustments based on factors such as occupancy levels and competitor pricing, maximizing revenue from high-spending guests while minimizing vacancies during slower periods. The transforming phase emphasizes continuous enhancement of these practices. Therefore, this phase for hotels will focus on staff (re) training, technology upgrades, and service enhancements to improve customer satisfaction and operational efficiency. Such enhancements not only improve operational efficiency but also drive long-term profitability.

Although the Dynamic Capabilities Theory (DCT) offers a valuable framework for understanding how organizations adapt to changing environments, it also has several limitations. One major critique of DCT is the lack of clarity in its definitions and operationalization. The core concepts of sensing, seizing, and transforming are often described in broad terms, making it challenging to apply the theory in a real-life setting

[41, 47]

. Also, it assumes that organizations can constantly adapt, which may be unrealistic for firms facing significant resource constraints, particularly small businesses

[27]

. Moreover, DCT can be difficult to implement in highly dynamic or volatile markets where firms struggle to sense and respond quickly enough

[53]

. Finally, the theory tends to emphasize firm-level capabilities, sometimes overlooking the influence of external factors like market conditions or competition

[19]

. Notwithstanding, the dynamic capabilities theory has been applied to study strategic decision-making in dynamic environments

[19]

, an adaptation of businesses to international settings

[48, 66]

, technological changes

[5, 64]

, and supply chain management

[4, 21]

. Within the specific context of hospitality,

[45]

, and

[50]

have applied DCT to understand how hotels use dynamic capabilities to adapt to various external factors. This theory is particularly applied in this study because revenue management strategies are a manifestation of dynamic capabilities. In the sense that revenue management requires hotels to adapt their pricing, distribution, and marketing approaches in response to fluctuating demand.

3. Literature Review

3.1. Revenue Management in the Hotel Industry

The origins of Revenue Management (RM) can be traced back to the airline industry in the 1970s, when yield management strategies were employed to optimize seat pricing and revenue

[58]

. Inspired by these early innovations, other sectors with perishable inventory, such as hotels and car rentals, began adopting similar tactics to manage their capacity and occupancy, laying the groundwork for modern revenue management practices

[15, 30]

As RM systems improved in efficiency and functionality as a result of the progress in information technology and the internet

[38, 49]

, academic interest also burgeoned. Particularly, RM has gained considerable attention in the field of operations research (OR), following the works of

[20]

. The focus thus far has been on strategic matters such as forecasting, booking limits, dynamic pricing, and overbooking

[38]

. The definition of what revenue management (RM) is or entails has gone through changes over time. The first recognized definition of RM was by

[30]

, who defined it as the strategic allocation of capacity to specific customers at optimal prices to maximize revenue. This definition was later expanded to include the concept of selling at the most opportune time

[30]

. In 2018,

[24]

further defined RM as a strategic approach to maximizing revenue by efficiently allocating resources through variable pricing over time.

Expanding on Huynh’s

[24]

definition, Ng et al.

[38]

highlighted three types of RM decisions: structural, pricing, and quantity-based, and noted that RM can be approached in terms of quantity control or price-based strategies. Hayes et al.

[22]

modernized the definition of RM by incorporating selling through appropriate distribution channels. According to

[30]

, RM is best suited for industries characterized by stable capacity, perishable inventory, and fluctuating demand. Hayes et al.

[22]

highlight that the hotel industry, which is characterized by diverse customer segments with varying price sensitivities and demand elasticities, coupled with the intangibility and impermanence of its services, is well-suited to RM strategies. According to

[22]

, such industries allow for the optimization of revenue through the tailoring of prices based on customer willingness to pay.

3.2. Traditional Revenue Management Techniques in the Hotel Industry

Early applications of RM centered on maximizing revenue through dynamic pricing and efficient inventory control. Over time, these conventional approaches have evolved to include demand forecasting and distribution channel optimization. With the advancement in technology and globalization, other revenue management strategies have emerged. Despite advancements, traditional revenue management principles remain integral, providing a foundation for optimizing revenue streams in an increasingly competitive and dynamic market environment.

3.2.1. Pricing Strategies

The core principle of traditional revenue management is to apply pricing strategies to optimize revenue by balancing supply and demand. One widely used tactic is dynamic pricing, which involves real-time adjustments of hotel rates based on factors such as demand fluctuations, seasonality, and booking lead times

[22, 38]

. This approach allows hotels to capitalize on high-demand periods by increasing prices while offering discounted rates during low-demand periods to stimulate occupancy

[55]

. Additionally, tiered pricing structures, such as early-bird discounts and non-refundable rates, are used to encourage early bookings and maximize revenue yield

[42]

. These strategies incentivize guests to commit earlier, providing more predictable revenue streams. Further, length-of-stay restrictions and minimum stay requirements are employed to manage inventory availability, ensuring optimal room utilization during peak periods

[36]

. These pricing tactics highlight the complexity of revenue management in the hospitality industry, combining dynamic, tiered, and duration-based strategies to enhance profitability while responding to market conditions.

3.2.2. Demand Forecasting

Accurate demand forecasting is essential for effective revenue optimization in the hotel industry, as it informs key decisions regarding pricing and inventory management. Conventional forecasting methods rely on historical data, market trends, and segmentation research to predict future demand patterns

[18]

. Techniques such as time-series analysis, regression models, and moving averages provide insights into seasonal fluctuations, market dynamics, and other factors affecting demand

[16]

. Additionally, segmentation analysis enables hotels to identify distinct market segments with unique demand characteristics, allowing for tailored pricing and promotional strategies that align with the preferences and behaviours of each segment

[23]

. These approaches collectively enhance a hotel’s ability to optimize revenue while meeting diverse customer needs.

3.3. Emerging Technologies Transforming Revenue Management in Hotels

In recent years, emerging technologies have had a significant impact on revenue management practices. It has revolutionized the way businesses optimize their pricing, distribution, and capacity decisions

[3]

. These technologies, such as artificial intelligence, machine learning, and data analytics, enable businesses to collect, analyze, and utilize vast amounts of data to make more informed and precise revenue management decisions. With the use of emerging technologies, businesses can now leverage advanced forecasting methods to predict consumer demand accurately. They can also optimize pricing strategies in real-time, taking into account factors such as competitor prices, customer preferences, and market trends

[66]

Furthermore, emerging technologies enable businesses to implement dynamic pricing and personalized marketing strategies, tailoring offers and promotions to individual customers based on their past behaviour and preferences. By incorporating emerging technologies into revenue management practices, businesses can better understand customer behaviour, improve decision-making processes, and ultimately drive revenue growth

[56]

. Additionally, emerging technologies allow for the automation of revenue management tasks, reducing manual effort and increasing operational efficiency. This automation streamlines processes such as pricing updates, inventory management, and demand forecasting, saving businesses time and resources. Moreover, the integration of emerging technologies into revenue management practices also opens up new opportunities for businesses to reach customers

[67]

. This increased efficiency frees up employees to focus on strategic initiatives and customer engagement, enhancing the overall customer experience.

3.4. The Effectiveness of Various Revenue Management Practices in the Hotel Industry

Revenue management is an essential aspect of businesses across various industries, from hospitality to retail

[58]

. However, with advancements in technology and analytics, contemporary RM approaches have become more sophisticated. These modern strategies leverage data-driven decision-making processes and personalized pricing, enabling hotels to respond more effectively to market conditions, enhance customer experiences, and ultimately improve financial performance. Dynamic pricing remains a cornerstone of revenue management in the hotel industry.

[33, 61]

highlight the effectiveness of dynamic pricing models in optimizing room rates by accounting for demand fluctuations, competitor pricing, and market segmentation. By leveraging real-time data and predictive analytics, hotels can adjust prices dynamically to respond to changes in demand, thereby maximizing revenue potential. In addition to pricing, efficient inventory control and capacity management are critical for successful revenue management. Chae and Kim

[12]

and Liu et al.

[35]

emphasize the strategic allocation of room inventory across various distribution channels to reduce inventory wastage and enhance revenue. The integration of revenue management software and algorithms further supports capacity management by identifying opportunities for upselling and optimizing room allocation.

Accurate demand forecasting is another essential component of revenue management. The studies by Zhang et al.

[69]

and Wang and Nicolau

[58]

underscore the importance of predictive analytics in understanding demand patterns and customer behaviour. By analyzing historical data, market trends, and econometric models, hotels can forecast demand with greater precision and adjust pricing and inventory strategies accordingly. This enables them to make data-driven decisions, improving overall revenue performance and ensuring competitive advantage in a dynamic market environment.

3.5. Benefits and Challenges of Integration in Revenue Management

Integration in revenue management within the hospitality industry offers significant advantages, particularly in enhancing decision-making and forecasting

[57]

. The adoption of advanced data analytics and predictive modeling empowers hotels to optimize pricing strategies and maximize revenue potential. Zhang et al.

[69]

highlight the role of machine learning algorithms in accurately forecasting demand, enabling hotels to make strategic decisions regarding pricing, inventory allocation, and distribution management. Furthermore, the integration of real-time analytics allows for swift adaptation to market changes, as evidenced by

[59]

findings. This adaptability ensures that hotels can monitor performance metrics, promptly address deviations from goals, and capitalize on emerging revenue opportunities. Moreover, integrating external data sources, such as competitor pricing and economic indicators, provides hotels with a comprehensive understanding of market dynamics, facilitating informed decision-making

[29, 33]

Another critical benefit of integration lies in improved pricing and demand management. Dynamic pricing, supported by real-time data and predictive analytics, enables hotels to adjust room rates based on demand fluctuations, optimizing revenue across various market segments.

[62]

demonstrated that such models consider demand patterns, competitor pricing, and customer behavior to ensure competitive yet profitable pricing strategies. Also, automated revenue management systems streamline operations by minimizing errors and maintaining consistent pricing across channels, enhancing overall efficiency and profitability

[26]

. Demand forecasting further complements these efforts by providing precise predictions, allowing for strategic planning in pricing, promotions, and resource allocation

[68]

Finally, the integration of customer experience and personalization into revenue management significantly boosts both customer satisfaction and revenue optimization. Technologies like customer relationship management (CRM) systems and artificial intelligence (AI) enable hotels to create detailed guest profiles, allowing for tailored marketing, personalized service offerings, and customized pricing incentives

[34, 51]

. Additionally, mobile technologies enhance guest engagement through features like digital concierge services and personalized recommendations, fostering convenience and loyalty. The combined effect of dynamic pricing and personalized incentives, as noted by

[61]

, not only drives repeat bookings but also increases sales of ancillary services, ultimately maximizing revenue while meeting diverse customer needs.

4. Methodology

A qualitative case study design was adopted to capture data within a defined period and to generate a comprehensive understanding of revenue management practices within the hotel sector in Cape Coast. The research focused on star-rated hotels, given their structured managerial systems and technological integration. Hotel managers were purposively selected as key informants due to their direct involvement in pricing, forecasting, and distribution channel decisions. The sample size was determined by data saturation, culminating in ten (10) interviews with managers who possessed extensive experience in revenue management. Data were collected through in-depth, semi-structured interviews conducted between 16 and 27 September 2024. Each session, lasting between 45 and 60 minutes, explored four major areas aligned with the study objectives: (i) revenue management practices, (ii) profitability outcomes, (iii) integration of emerging technologies, and (iv) implementation challenges. Complementary observational data on pricing adjustments, promotional strategies, and channel management practices were documented to enhance contextual understanding. Data analysis followed Clarke and Braun’s

[14]

six-phase thematic analysis approach. Interview transcripts were first subjected to open coding, where key ideas such as “dynamic pricing,” “inventory control,” and “rate parity” were identified. These initial codes were then grouped through axial coding under broader categories directly reflecting the research objectives, such as revenue management practices and technological integration. Finally, selective coding refined these into core themes that demonstrated the interconnections between management strategies and profitability outcomes. The final thematic structure maintained a clear alignment with the study’s objectives, emphasizing four key insights: dynamic pricing strategies, predictive analytics and forecasting, automated revenue management systems, and human capital development. To contextualize these findings, the study noted quantifiable impacts: AI-driven pricing models increased revenue per available room (RevPAR) by 15-20%; predictive forecasting reduced booking volatility by 30%; automated systems lowered pricing errors by 25%; and staff training improved forecasting accuracy and adaptability. This methodological approach ensured analytical coherence, transparency, and practical relevance, yielding actionable insights for hospitality managers seeking to leverage emerging technologies for revenue optimization.

5. Results and Discussions

5.1. Revenue Management Practices

Revenue management practices in hotels are essential for optimizing financial performance and ensuring competitive positioning in the market. The interviews revealed that dynamic pricing is a predominant strategy across the hotels in the Cape Coast Metropolis. This approach involves real-time adjustment of room rates based on demand, market conditions, and competitive landscape.

Theme 1: Dynamic Pricing Strategies

Dynamic pricing emerged as a predominant strategy among the hotels interviewed. This approach involves real-time adjustment of room rates based on various factors such as demand, market conditions, and the competitive landscape.

Manager 1, aged 35, emphasized, “flexible pricing models allow us to adjust rates dynamically, ensuring we capture maximum revenue during peak periods while remaining competitive during off-peak times.” This practice is further supported by seasonal promotions aimed at attracting guests during low-demand periods, thereby smoothing out revenue fluctuations.

These findings corroborate that of

[61]

, who indicated that dynamic pricing allows hotels to maximize revenue by leveraging data-driven insights into demand patterns, competitor pricing, and customer behaviour. Another research by Wang et al.

[59]

underscores the role of dynamic pricing in enhancing revenue management efficiency.

The study emphasizes that real-time pricing adjustments, informed by advanced revenue management systems and predictive analytics, help hotels remain competitive in volatile markets. These systems enable hotels to analyze booking trends, forecast demand, and respond promptly to market changes, aligning with Manager 1’s assertion about capturing maximum revenue during peak periods. Furthermore, Noone and McGuire

[40]

highlight the significance of seasonal promotions as a complement to dynamic pricing. Their findings indicate that targeted promotions during low-demand periods not only attract price-sensitive customers but also help hotels maintain occupancy rates, thereby mitigating revenue variability. This aligns with the observed practice of using seasonal promotions to smooth out revenue fluctuations, as described by the hotel managers in this study.

Theme 2: Inventory Control and Management

Another critical component identified was inventory control, which involves managing room availability to maximize occupancy and revenue. Strategies such as length-of-stay restrictions and strategic inventory allocation to different channels were highlighted.

Manager 9, 36 years, noted, “implementing length of stay restrictions and careful inventory allocation enables us to optimize our occupancy rates and revenue.” This practice is particularly important during high-demand periods, such as holidays and special events, where strategic inventory management can significantly impact the hotel’s financial performance.

The findings from Manager 9 support the work of Talluri and Van Ryzin

[52]

, who indicate that length of stay (LOS) restrictions play a crucial role in optimizing both occupancy rates and revenue, particularly during high-demand periods. Their research emphasizes that LOS controls help hotels maximize financial returns by prioritizing bookings that yield the highest revenue, ensuring that room inventory is utilized efficiently. Similarly, the findings align with the studies of

[22, 39]

, who highlighted the importance of strategic inventory allocation in managing demand fluctuations.

They assert that careful inventory control, especially during peak periods such as holidays and special events, enables hotels to prevent overbooking while capitalizing on revenue opportunities. Furthermore, this observation echoes the conclusions of Wang and Nicolau

[58]

, who indicate that dynamic inventory management strategies, including the application of LOS restrictions, significantly enhance revenue performance by allowing hotels to respond flexibly to real-time market conditions. These studies collectively affirm the effectiveness of these practices in improving financial outcomes in the hospitality sector.

Theme 3: Market Segmentation and Targeted Promotions

Market segmentation and targeted promotions were frequently mentioned as effective strategies. This involves categorizing guests into different segments based on their preferences, booking behaviours, and demographics.

Manager 2, 40 years, explained, “by understanding the different segments of our market, we can tailor promotions and packages to meet the specific needs of each group, thereby enhancing our appeal and maximizing revenue.” This approach not only helps in attracting a diverse clientele but also allows hotels to offer personalized experiences, thereby increasing guest satisfaction and loyalty.

The insights provided by Manager 2 align with the findings of Kotler et al.

[31]

, who indicate that effective market segmentation enables businesses to develop targeted marketing strategies that cater to the specific needs and preferences of distinct customer groups. In the context of the hospitality industry, tailoring promotions and packages for various market segments allows hotels to optimize their revenue by appealing to a broader audience while meeting the unique expectations of each segment.

This approach is further supported by Dolnicar et al.

[17]

, who emphasize that personalized marketing strategies not only attract diverse clientele but also enhance customer satisfaction and loyalty. Their study highlights that understanding the behavioural and demographic characteristics of different market segments enables hotels to create tailored experiences that resonate with guests, fostering a sense of value and loyalty.

Theme 4: Data Analytics and Forecasting

The use of data analytics and forecasting is another key practice identified. Advanced data analytics tools allow hotels to analyze historical booking data, market trends, and competitor rates.

Manager 3, 45 years, highlighted, “data analytics provides us with valuable insights into market trends and booking patterns, allowing us to make informed decisions about pricing and promotions.” This practice is crucial in a highly competitive market, where even small pricing adjustments can have a significant impact on revenue.

This aligns with the work of Phillips et al.

[46]

, who emphasize the importance of data analytics in dynamic pricing models. They argue that in highly competitive markets, even minor pricing adjustments based on real-time data can lead to significant revenue gains. By analyzing booking patterns and market conditions, hotels can fine-tune their pricing strategies to remain competitive while maximizing profitability. Moreover, Buhalis and Leung

[11]

suggest that the application of data analytics allows hotels to identify emerging trends and shifts in consumer behavior, enabling proactive adjustments to pricing and promotions. This approach not only enhances revenue performance but also provides a competitive edge by ensuring that pricing strategies are aligned with current market dynamics. Manager 3’s emphasis on data analytics underscores its critical role in making precise, impactful decisions in the hospitality industry.

Theme 5: Integration of Revenue Management Software

The integration of advanced revenue management software and real-time data systems has revolutionized the way hotels manage their pricing and inventory.

Manager 6, 42 years, remarked, “the adoption of sophisticated revenue management systems has enabled us to analyze data in real-time, make quick adjustments to our pricing, and optimize our overall revenue management strategy.” The use of technology in revenue management not only improves efficiency but also provides hotels with a competitive edge in the market.

The observation by Manager 6 aligns with the findings of

[40]

, who indicate that the adoption of advanced revenue management systems (RMS) significantly enhances a hotel’s ability to analyze data in real-time and make timely pricing adjustments. Their research underscores that such systems allow hotels to optimize revenue strategies by leveraging dynamic data inputs, including booking trends, competitor pricing, and market conditions.

Similarly,

[52]

highlights that technology-driven revenue management tools improve decision-making efficiency by automating complex tasks such as demand forecasting, inventory control, and price optimization. These systems enable hotels to respond quickly to market changes, ensuring that they capitalize on revenue opportunities while minimizing risks associated with underpricing or overpricing. As shown in Table 1, the respondents confirmed the various revenue management practices adopted in their respective hotels.

Table 1. Revenue Management Practices.

Theme	Description	Evidence
Dynamic Pricing Strategies	Real-time adjustment of room rates based on demand and market conditions.	“Our pricing is highly flexible; we adjust room rates daily, sometimes even hourly, depending on demand.” (Manager 1)
Inventory Control and Management	Managing room availability to optimize occupancy and revenue.	“We implement length-of-stay restrictions during peak periods to maximize occupancy and revenue.” (Manager 9)
Market Segmentation and Targeted Promotions	Categorizing guests and tailoring promotions based on market segments.	“We have specific promotions for different customer segments, like corporate guests or leisure travelers.” (Manager 2)
Data Analytics and Forecasting	Utilizing data analytics to inform pricing and promotional strategies.	“We rely heavily on analyzing booking patterns and market trends to forecast demand and adjust our pricing.” (Manager 3)
Integration of Revenue Management Software	Use of advanced systems for real-time data analysis and pricing adjustments.	“The adoption of sophisticated revenue management systems has significantly improved our ability to set accurate prices.” (Manager 6)

Source: Dornyoh, Moore, Yeboah, Ocloo & Dacosta 2024

5.2. Impact on Hotel Profitability

The impact of revenue management strategies on hotel profitability cannot be overstated. The interviews revealed that the implementation of dynamic pricing and data-driven forecasting has led to significant improvements in financial performance across the hotels.

Theme 1: Financial Performance Enhancement

Revenue management strategies, particularly dynamic pricing, have had a significant impact on hotel profitability.

Manager 1, 35 years, stated, “the use of dynamic pricing during peak periods has been instrumental in boosting our RevPAR, thereby significantly enhancing our overall profitability.” This approach allows hotels to capitalize on high-demand periods by charging premium rates, while also remaining competitive during low-demand times by offering discounts and promotions.

The observation by Manager 6 aligns with the findings of

[40]

Similarly,

[52]

[63]

emphasizes the competitive advantages conferred by technological advancements in revenue management.

They suggest that hotels utilizing sophisticated RMS gain a strategic edge by improving operational efficiency and providing personalized pricing and promotions, which can enhance customer satisfaction. Manager 6’s remarks about real-time data analysis and strategic optimization reflect these advantages, highlighting the crucial role of technology in driving revenue performance in a competitive hospitality market.

Theme 2: Optimization of Key Performance Indicators (KPIs)

The interviews revealed that optimizing KPIs such as Average Daily Rate (ADR), Revenue per Available Room (RevPAR), and Gross Operating Profit per Available Room (GOPPAR) plays a crucial role in financial performance.

Manager 4, 50 years, highlighted, “by closely monitoring and optimizing our ADR and RevPAR, we’ve been able to maintain a healthy financial position, even during challenging economic conditions.” These KPIs provide valuable insights into the hotel’s financial performance and are used to gauge the effectiveness of revenue management strategies.

The remarks by Manager 4 align with the findings of Dolnicar et al.

[17]

, who indicate that key performance indicators (KPIs) such as Average Daily Rate (ADR) and Revenue per Available Room (RevPAR) are critical metrics for assessing a hotel’s financial performance and the success of its revenue management strategies. These KPIs provide a comprehensive view of how effectively a hotel is generating revenue from its available inventory, helping management make data-driven decisions.

Similarly, Anderson and Xie

[7]

emphasize the importance of ADR and RevPAR in monitoring financial health, especially during periods of economic uncertainty. They argue that consistent tracking and optimization of these metrics enable hotels to identify trends and implement corrective measures to sustain profitability. By analyzing fluctuations in these KPIs, hotels can adjust their pricing, promotions, and inventory strategies to respond to changing market conditions effectively.

Theme 3: Targeted Promotions and Profitability

Customized packages targeting different market segments have also contributed to profitability by attracting a diverse clientele.

Manager 5, 37 years, explained, “our targeted promotions have helped us attract high-value guests, leading to higher revenue and improved profitability.” These promotions not only drive bookings but also enhance the guest experience, thereby fostering loyalty and encouraging repeat business.

Theme 4: Operational Efficiency

Revenue management strategies also influence operational efficiency, particularly in managing staffing requirements and operational costs.

Manager 7, 48 years, noted, “efficient revenue management helps us balance our operational costs with revenue generation, ensuring we maintain a healthy profit margin.” This balance is crucial for maintaining high service standards and guest satisfaction, which in turn supports long-term profitability.

The insights shared by Manager 7 align with the findings of Anderson and Xie

[7]

, who indicate that effective revenue management is critical for balancing operational costs with revenue generation, thereby ensuring sustainable profit margins. Their study highlights that a well-executed revenue management strategy allows hotels to optimize pricing and inventory decisions, which helps cover fixed and variable costs while maximizing profitability.

Similarly, Yeoman

[65]

emphasizes that revenue management not only enhances financial performance but also supports the maintenance of high service standards.

They argue that efficient cost management, achieved through strategic revenue practices, enables hotels to allocate resources effectively, ensuring quality service delivery. High service standards lead to increased guest satisfaction, fostering repeat business and long-term profitability. From Table 2, it is clear that revenue management impacts the profitability of hotels.

Theme 5: Market Positioning and Competitiveness

Effective revenue management practices enhance a hotel’s market positioning and competitiveness.

Manager 8, 39 years, remarked, “our ability to adjust our pricing and promotional strategies in response to market conditions has helped us maintain a competitive edge in the market.” By staying attuned to market trends and adjusting their strategies accordingly, hotels can attract more guests, increase their market share, and improve their overall profitability.

The perspective shared by Manager 8 affirms the findings of

[10]

, who asserts that the ability to adjust pricing and promotional strategies in response to market conditions is crucial for maintaining a competitive advantage in the hospitality industry. Their research highlights that flexibility in pricing, guided by real-time market data, enables hotels to respond proactively to fluctuations in demand, thereby attracting more guests and increasing market share.

Similarly, Chen et al.

[13]

corroborate the significance of market responsiveness in enhancing profitability. They emphasize that by closely monitoring market trends, such as competitor pricing, seasonal demand shifts, and changes in consumer behaviour, hotels can fine-tune their promotional strategies to appeal to a diverse clientele. This adaptability not only boosts revenue performance but also reinforces the hotel’s competitive standing in the market. Table 2 affirmed the respondents’ assertion that fact revenue management impacts hotels’ profitability.

Table 2. Impact on Hotel Profitability.

Theme	Description	Evidence
Financial Performance Enhancement	Improved profitability through dynamic pricing and strategic revenue management.	“By implementing dynamic pricing, we’ve seen a significant boost in RevPAR, especially during peak periods.” (Manager 1)
Optimization of KPIs	Enhancing financial performance by optimizing ADR, RevPAR, and GOPPAR.	“Our focus on KPI optimization has been crucial in maintaining our financial health, particularly in challenging market conditions.” (Manager 4)
Targeted Promotions and Profitability	Increasing revenue by offering customized packages to diverse market segments.	“We attract high-value guests by offering tailored promotions, which have had a direct positive impact on our profitability.” (Manager 5)
Operational Efficiency	Balancing operational costs with revenue generation to maintain profitability.	“Efficient management of staffing and costs has allowed us to maintain profitability even during off-peak seasons.” (Manager 7)
Market Positioning and Competitiveness	Strengthening competitive advantage through adaptive pricing and promotional strategies.	“Our ability to make strategic adjustments in pricing and promotions has been key to maintaining our competitiveness in the market.” (Manager 8)

Source: Dornyoh, Moore, Yeboah, Ocloo & Dacosta 2024

5.3. Integration of Emerging Technologies

The integration of emerging technologies into revenue management practices has been a game-changer for hotels in the Cape Coast Metropolis. The interviews highlighted the widespread adoption of advanced revenue management software, artificial intelligence (AI), and machine learning. These technologies have revolutionized the way hotels manage their pricing and inventory, providing them with the tools to make data-driven decisions. Table 3 states the respondents’ views on the integration of emerging technologies within the hotel sector.

Theme 1: AI and Machine Learning in Revenue Management

The integration of AI and machine learning has significantly transformed revenue management practices.

Manager 1, 35 years, emphasized, “the use of AI-driven analytics has transformed our revenue management processes, enabling us to predict booking trends with greater accuracy and optimize our pricing strategies.”

Theme 2: Real-Time Data Integration

The capability to analyze vast amounts of data in real time is a key benefit of emerging technologies.

Manager 9, 36 years, highlighted the use of machine learning models for predictive analytics, stating, “the integration of machine learning has allowed us to analyze historical booking data and market trends with precision, enabling us to forecast demand and set optimal rates.” This real-time data integration provides hotels with a competitive advantage, allowing them to respond quickly to market changes and maximize revenue.

Wang and Nicolau

[58]

corroborate the value of real-time data integration facilitated by machine learning. They highlight that such integration enables hotels to respond swiftly to market changes, adjust pricing strategies, and capitalize on emerging revenue opportunities. This agility provides a competitive edge, particularly in highly volatile markets where timely decisions can significantly impact profitability. Furthermore, Ivanov and Webster

[25]

validate the role of advanced analytics in enhancing the efficiency and effectiveness of revenue management systems. They argue that machine learning models empower hotels to automate complex forecasting processes, reduce manual errors, and implement data-driven pricing strategies.

Manager 9’s observations underscore the strategic advantage gained through the adoption of machine learning, emphasizing its critical role in maintaining competitiveness and maximizing revenue in the hospitality industry.

Theme 3: Mobile Technology and Direct Bookings

The adoption of mobile technology and apps has enhanced direct booking capabilities and provided valuable guest data.

Manager 4, 50 years, noted, “the use of mobile apps has enhanced our direct booking capabilities, allowing us to reach guests directly with targeted promotions and offers.” This direct engagement not only improves the guest experience but also helps hotels reduce their reliance on third-party booking platforms, thereby increasing profitability.

Theme 4: Advanced Data Analytics Tools

The adoption of advanced data analytics tools has been instrumental in refining revenue management strategies.

Manager 3, 45 years, remarked, “advanced data analytics tools have provided us with deep insights into market dynamics, enabling us to make more informed decisions about pricing and promotions.” This data-driven approach not only enhances the accuracy of demand forecasting but also helps hotels identify new revenue opportunities and optimize their pricing strategies.

Theme 5: Customer Relationship Management (CRM) Systems

The integration of CRM systems has also played a key role in understanding guest preferences and personalizing offers.

Manager 6, 42 years, explained, “the integration of CRM systems has enabled us to better understand our guests’ preferences and tailor our offerings to meet their needs.” This personalized approach not only enhances the guest experience but also drives repeat business and increases overall profitability.

Table 3. Integration of Emerging Technologies.

Theme	Description	Evidence
AI and Machine Learning in Revenue Management	Transforming revenue management processes through AI and machine learning.	“With AI, we can predict booking trends more accurately, allowing us to optimize our pricing strategies effectively.” (Manager 1)
Real-Time Data Integration	Leveraging real-time data for accurate demand forecasting and rate setting.	“The precision in forecasting demand and setting optimal rates has significantly improved with real-time data integration.” (Manager 9)
Mobile Technology and Direct Bookings	Enhancing direct booking capabilities and customer engagement through mobile apps.	“Our mobile app allows us to reach guests directly, offering targeted promotions that have increased direct bookings.” (Manager 4)
Advanced-Data Analytics Tools	Refining pricing and promotional strategies through advanced data analytics.	“Advanced analytics provide deep insights into market dynamics, helping us refine our pricing and promotions.” (Manager 3)
Customer Relationship Management (CRM) Systems	Enhancing guest experience and profitability through personalized offers.	“By tailoring our offerings based on guest preferences through CRM, we’ve seen an improvement in guest satisfaction and profitability.” (Manager 6)

Source: Dornyoh, Moore, Yeboah, Ocloo & Dacosta 2024

5.4. Challenges in Revenue Management

While the adoption of advanced revenue management strategies and technologies has brought numerous benefits, it has also presented several challenges. One of the most significant challenges highlighted in the interviews is the issue of market fluctuations and economic uncertainties. The volatility of the market makes it difficult for hotels to accurately forecast demand and set optimal pricing strategies.

Theme 1: Market Fluctuations and Economic Uncertainties

One of the significant challenges identified is the volatility of the market, which complicates accurate demand forecasting.

Manager 2, 40 years, noted, “the unpredictable nature of the market can make it challenging to maintain consistent occupancy levels and pricing strategies, especially during economic downturns.”

Theme 2: Rate Parity Across Distribution Channels

Maintaining rate parity across various distribution channels was highlighted as a complex task.

Manager 1, 35 years, stated, “maintaining rate parity is crucial for preventing revenue leakage and maintaining a positive brand image, but it can be challenging given the number of distribution channels we use.” This challenge is exacerbated by the competitive pressures from other hotels in the region, which often engage in aggressive pricing strategies.

Theme 3: Staff Training and Resource Limitations

Internal challenges, such as staff training and resource limitations, also hinder revenue management efforts. Internal challenges, such as staff training and resource limitations, also hinder the effectiveness of revenue management efforts. The integration of advanced technologies requires a skilled workforce capable of leveraging these tools effectively. From Table 4, it was clear that staff training and resource limitations, balancing revenue and customer satisfaction, are some of the challenges in revenue management, as per the respondents’ view.

Manager 3, 45 years, pointed out, “ensuring that our staff are adequately trained to use advanced revenue management tools and interpret data correctly requires ongoing investment and support.” Additionally, limited financial resources can restrict a hotel’s ability to invest in cutting-edge technology and systems, thereby limiting the scope of its revenue management strategies.

Theme 4: Balancing Revenue and Customer Satisfaction

The balance between maximizing revenue and maintaining high levels of customer satisfaction is a persistent challenge.

Manager 10, 41 years, emphasized, “implementing dynamic pricing requires careful consideration of guest expectations and experiences to avoid negative feedback and ensure guest satisfaction.” This challenge underscores the need for hotels to strike a balance between maximizing revenue and delivering a positive guest experience.

Theme 5: Technological Integration and Adaptation

The rapid pace of technological change poses a challenge for hotels in terms of integrating new systems and ensuring compatibility with existing infrastructure.

Manager 5, 37 years, remarked, “keeping up with the latest technology and integrating it into our operations can be a daunting task, especially given the speed at which new technologies are emerging.” This challenge highlights the importance of continuous learning and adaptation in the field of revenue management.

Table 4 presents the challenges associated with revenue management within the context of hotels. All the respondents affirmed that revenue management comes with its challenges.

Table 4. Challenges in Revenue Management.

Theme	Description	Evidence
Market Fluctuations and Economic Uncertainties	Challenges in maintaining consistent pricing and occupancy due to market volatility.	“During economic downturns, it’s difficult to stick to our pricing strategies, leading to unpredictable revenue streams.” (Manager 2)
Rate Parity Across Distribution Channels	The complexity of ensuring consistent rates across various distribution channels.	“Ensuring rate parity across all platforms is crucial but challenging, as it prevents revenue leakage.” (Manager 1)
Staff Training and Resource Limitations	Internal challenges related to staff training and resource allocation.	“We’ve had to continually invest in staff training and the proper use of tools, which can strain our resources.” (Manager 3)
Balancing Revenue and Customer Satisfaction	The challenge of optimizing revenue while maintaining customer satisfaction.	“Finding the right balance during peak periods is tough; we want to maximize revenue without compromising guest experience.” (Manager 10)
Technological Integration and Adaptation	Difficulties in keeping up with and integrating new technologies.	“The rapid pace of technological change requires continuous adaptation, which can be a significant challenge.” (Manager 5)

Source: Dornyoh, Moore, Yeboah, Ocloo & Dacosta 2024

5.5. Conclusions

This study aimed to investigate the revenue management practices, their impact on hotel profitability, the integration of emerging technologies, and the challenges faced by hotels within the Cape Coast Metropolis. Through qualitative interviews with ten hotel managers, the research uncovered several key insights into the complex dynamics of revenue management in the hospitality industry. The findings revealed that dynamic pricing, inventory control, market segmentation, and targeted promotions are widely used revenue management strategies. These practices align with existing literature that emphasizes the importance of flexible pricing models and market segmentation in optimizing hotel revenue

[30, 65]

Dynamic pricing, in particular, has been highlighted as a critical tool for maximizing revenue, as it allows hotels to adjust room rates in response to real-time demand fluctuations

[40]

. This strategy, coupled with data-driven forecasting and advanced analytics, enables hotels to accurately predict demand and optimize their pricing strategies. The integration of emerging technologies, such as artificial intelligence, machine learning, and advanced data analytics, has revolutionized revenue management practices. These technologies provide hotels with the tools to analyze large datasets, identify market trends, and make informed decisions

[22]

. The adoption of mobile technology and apps has further enhanced the customer experience by facilitating direct bookings and personalized promotions. This technological advancement aligns with the literature, which suggests that technology adoption in revenue management leads to improved decision-making and operational efficiency

[60]

However, the study also identified several challenges, including market fluctuations, maintaining rate parity across distribution channels, internal constraints such as staff training and resource limitations, and the need to balance revenue optimization with customer satisfaction. These challenges are consistent with the findings of previous studies that highlight the complexities and risks associated with revenue management in a dynamic market environment

[22, 65]

. The study concludes that while revenue management is a powerful tool for optimizing financial performance, it must be implemented with a holistic approach that considers both operational efficiency and customer satisfaction. The balance between these two aspects is crucial for sustaining long-term profitability and maintaining a positive brand image.

5.6. Recommendations

It is recommended that to optimize their revenue management practices, hotels should prioritize the adoption of sophisticated revenue management software and advanced data analytics tools. These technologies are essential for enhancing forecasting accuracy and refining pricing strategies. With real-time access to data on market trends, competitor pricing, and customer behavior, hotels can make informed, data-driven decisions that align with current market conditions.

Secondly, the integration of advanced technologies into revenue management processes necessitates a well-trained workforce. Hotels should therefore implement continuous training and development programs that equip their staff with the necessary skills to effectively utilize these tools.

Also, while the primary goal of revenue management is to optimize financial performance, it is equally important for hotels to maintain high levels of customer satisfaction. A balanced approach that prioritizes both revenue and customer experience can lead to long-term success. Hotels can achieve this by offering personalized promotions that cater to the specific preferences and needs of different customer segments.

Finally, to assess the effectiveness of their revenue management strategies, hotels should implement a set of comprehensive performance metrics. Key indicators such as Average Daily Rate (ADR), Revenue per Available Room (RevPAR), Gross Operating Profit per Available Room (GOPPAR), and Market Penetration Index (MPI) are essential for providing valuable insights into the hotel's financial health. These metrics allow hotels to monitor the impact of their revenue management practices on overall performance, identify areas for improvement, and make data-driven adjustments to their strategies.

By regularly analyzing these metrics, hotels can ensure that their revenue management efforts are aligned with their financial objectives and are contributing to sustained profitability.

5.7. Theoretical and Practical Implications of the Study

Firstly, this research aims to provide a complete overview of the methods and strategies used by hotels in the Metropolis to optimize revenue generation by identifying their varied revenue management practices. Acquiring this expertise is essential for hotel managers and industry stakeholders who want to improve their revenue management strategies and maintain competitiveness in the market.

Secondly, assessing the impact of revenue management tactics on hotel profitability yields valuable insights into the correlation between revenue management practices and financial performance. Analyze the effects of various tactics on profitability to make informed decisions and help hotels develop customized revenue management plans that align with their unique requirements and market circumstances.

Again, evaluating the incorporation of new technologies into revenue management strategies provides significant observations regarding the impact of technology on improving revenue optimization endeavours. With the ongoing advancement of technology, incorporating it into revenue management procedures can simplify operations, boost the accuracy of decision-making, and improve overall efficiency in generating income.

Finally, examining the challenges associated with revenue management in hotels in the Cape Coast Metropolis reveals the barriers and constraints that impede the successful implementation of revenue management. Through the process of recognizing and comprehending these obstacles, hotel managers and professionals in the business may formulate plans to conquer them, therefore enhancing the efficiency of revenue management and fostering long-term expansion in the hospitality sector.

Abbreviations

RM	Revenue Management
AI	Artificial Intelligence
OTA	Online Travel Agency
RMS	Revenue Management System
ADR	Average Daily Rate
RevPAR	Revenue per Available Room
GOPPAR	Gross Operating Profit per Available Room
PMS	Property Management System
CRM	Customer Relationship Management
ML	Machine Learning

Acknowledgments

We wish to express our profound appreciation to the Managers and Staff of the Capital Hill Hotel, Samrit Hotel, Pempamsie, and Ridge Royal Hotel for their support during data collection for this work.

Author Contribution

Emmanuel Dornyoh: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Project administration, Supervision, Visualization, Writing - original draft, Writing - review & editing

Mary Acquaye Moore: Conceptualization, Formal Analysis, Supervision, Validation, Visualization, Writing - original draft, Writing - review & editing

Richmond Yeboah: Conceptualization, Data curation, Formal Analysis, Investigation, Project administration, Resources, Supervision, Validation, Visualization, Writing - review & editing

Abdul-Muhaeminu Tamakloe Ocloo: Conceptualization, Data curation, Investigation, Methodology, Project administration, Visualization, Writing - review & editing

Franklin Dzormeku Dacosta: Conceptualization, Supervision, Validation, Writing - review & editing

Funding

The authors declare that no funding was received for this study.

Conflicts of Interest

The authors declare no conflicts of interest.

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Dornyoh, E., Moore, M. A., Yeboah, R., Ocloo, A. T., Dacosta, F. D. (2026). The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast. International Journal of Hospitality & Tourism Management, 10(1), 7-21. https://doi.org/10.11648/j.ijhtm.20261001.12

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Dornyoh, E.; Moore, M. A.; Yeboah, R.; Ocloo, A. T.; Dacosta, F. D. The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast. Int. J. Hosp. Tour. Manag. 2026, 10(1), 7-21. doi: 10.11648/j.ijhtm.20261001.12

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Dornyoh E, Moore MA, Yeboah R, Ocloo AT, Dacosta FD. The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast. Int J Hosp Tour Manag. 2026;10(1):7-21. doi: 10.11648/j.ijhtm.20261001.12

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@article{10.11648/j.ijhtm.20261001.12,
  author = {Emmanuel Dornyoh and Mary Acquaye Moore and Richmond Yeboah and Abdul-Muhaeminu Tamakloe Ocloo and Franklin Dzormeku Dacosta},
  title = {The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast},
  journal = {International Journal of Hospitality & Tourism Management},
  volume = {10},
  number = {1},
  pages = {7-21},
  doi = {10.11648/j.ijhtm.20261001.12},
  url = {https://doi.org/10.11648/j.ijhtm.20261001.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijhtm.20261001.12},
  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.},
 year = {2026}
}

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TY  - JOUR
T1  - The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast
AU  - Emmanuel Dornyoh
AU  - Mary Acquaye Moore
AU  - Richmond Yeboah
AU  - Abdul-Muhaeminu Tamakloe Ocloo
AU  - Franklin Dzormeku Dacosta
Y1  - 2026/01/16
PY  - 2026
N1  - https://doi.org/10.11648/j.ijhtm.20261001.12
DO  - 10.11648/j.ijhtm.20261001.12
T2  - International Journal of Hospitality & Tourism Management
JF  - International Journal of Hospitality & Tourism Management
JO  - International Journal of Hospitality & Tourism Management
SP  - 7
EP  - 21
PB  - Science Publishing Group
SN  - 2640-1800
UR  - https://doi.org/10.11648/j.ijhtm.20261001.12
AB  - 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.
VL  - 10
IS  - 1
ER  -

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Author Information

Emmanuel Dornyoh

Department of Tourism Management, Cape Coast Technical University, Cape Coast, Ghana

Contact Email

http://orcid.org/0009-0005-1686-8028
Mary Acquaye Moore

Department of Tourism Management, Cape Coast Technical University, Cape Coast, Ghana

Contact Email

http://orcid.org/0000-0003-1474-9189
Richmond Yeboah

Department of Tourism Management, Cape Coast Technical University, Cape Coast, Ghana

Contact Email

http://orcid.org/0000-0002-5041-8291
Abdul-Muhaeminu Tamakloe Ocloo

Department of Research and Innovation, The CreativeMind, Cape Coast, Ghana

Contact Email

http://orcid.org/0009-0009-3854-5376
Franklin Dzormeku Dacosta

Department of Tourism Management, Cape Coast Technical University, Cape Coast, Ghana

Contact Email

http://orcid.org/0009-0007-2917-9146

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APA Style

Dornyoh, E., Moore, M. A., Yeboah, R., Ocloo, A. T., Dacosta, F. D. (2026). The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast. International Journal of Hospitality & Tourism Management, 10(1), 7-21. https://doi.org/10.11648/j.ijhtm.20261001.12

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ACS Style

Dornyoh, E.; Moore, M. A.; Yeboah, R.; Ocloo, A. T.; Dacosta, F. D. The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast. Int. J. Hosp. Tour. Manag. 2026, 10(1), 7-21. doi: 10.11648/j.ijhtm.20261001.12

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AMA Style

Dornyoh E, Moore MA, Yeboah R, Ocloo AT, Dacosta FD. The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast. Int J Hosp Tour Manag. 2026;10(1):7-21. doi: 10.11648/j.ijhtm.20261001.12

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@article{10.11648/j.ijhtm.20261001.12,
  author = {Emmanuel Dornyoh and Mary Acquaye Moore and Richmond Yeboah and Abdul-Muhaeminu Tamakloe Ocloo and Franklin Dzormeku Dacosta},
  title = {The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast},
  journal = {International Journal of Hospitality & Tourism Management},
  volume = {10},
  number = {1},
  pages = {7-21},
  doi = {10.11648/j.ijhtm.20261001.12},
  url = {https://doi.org/10.11648/j.ijhtm.20261001.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijhtm.20261001.12},
  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.},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - The Science and Speculations Driving Revenue Management Decisions in Hotels in Cape Coast
AU  - Emmanuel Dornyoh
AU  - Mary Acquaye Moore
AU  - Richmond Yeboah
AU  - Abdul-Muhaeminu Tamakloe Ocloo
AU  - Franklin Dzormeku Dacosta
Y1  - 2026/01/16
PY  - 2026
N1  - https://doi.org/10.11648/j.ijhtm.20261001.12
DO  - 10.11648/j.ijhtm.20261001.12
T2  - International Journal of Hospitality & Tourism Management
JF  - International Journal of Hospitality & Tourism Management
JO  - International Journal of Hospitality & Tourism Management
SP  - 7
EP  - 21
PB  - Science Publishing Group
SN  - 2640-1800
UR  - https://doi.org/10.11648/j.ijhtm.20261001.12
AB  - 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.
VL  - 10
IS  - 1
ER  -

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