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

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| 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

References

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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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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}
}

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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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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  -

Copy | Download