An investigation into the Relationship between Revenue Management Practices and Financial Performance in Star-Rated Hotels in Sri Lanka
Keywords:revenue management, financial performance, classified star-rated hotels, financial outcomes, Sri Lanka
Purpose: The purpose of this study is to examine the Relationship between Revenue Management Practices and Financial Performance in Star-Rated Hotels in Sri Lanka.
Method: A quantitative research design was employed, utilizing a cross-sectional approach to collect data at a specific point in time. The sample was selected using stratified random sampling to ensure representation across hotels. Data was gathered through structured questionnaires and supplemented with secondary data from financial reports and industry publications.
Results and Conclusions: The study revealed that 40.9% of surveyed hotels had fully implemented revenue management procedures, emphasizing their strategic importance. Significant positive correlations were found between revenue management practices and financial performance indicators, including ADR, occupancy rate, RevPAR, GOPPAR, and return on investment. Effective revenue management practices were shown to enhance competitive advantage and market differentiation. Regression analyses further highlighted the substantial impact of "Revenue per Available Room" on return on investment, underlining the importance of optimizing this metric. The research underscores the strategic importance of revenue management practices in the hospitality industry and their positive influence on financial performance.
Research Implications: Hoteliers should consider these findings when formulating strategies to remain competitive and financially viable. Effective revenue management contributes to enhancing competitive advantage and market positioning.
Originality/Value: Study provides insights into the pivotal role of revenue management practices in shaping the financial performance of star-rated hotels in Sri Lanka. Ethical considerations were a cornerstone of this study, ensuring the well-being and rights of participants and setting a high standard for future research in the field.
Anderson, J. C., Kumar, N., & Narus, J. A. (2007). Value pricing: A new model for achieving customer loyalty and profitability. Simon and Schuster.
Anismar, Ainol Mardhiah, Lahmuddin Lubis, & Yusri Ibrahim. (2023). "Implementation of Hospitality Management in the Program Islamic Tourism in South Aceh." Environmental and Social Management Journal, 17(6), Page Range https://rgsa.emnuvens.com.br/rgsa/article/view/3549/1050
Berman, S. J., & Marshall, A. S. (2020). Enhancing financial performance through technology adoption: The mediating influence of business process capabilities. Journal of Business Research, 122, 266-277.
Bitran, G. R., & Caldentey, R. (2017). Revenue management without forecasting or optimization: An adaptive algorithm for dynamic pricing with limited demand information. Operations Research, 65(3), 779-800.
Bitran, G. R., & Mondschein, S. V. (2019). Revenue management integration in practice. Production and Operations Management, 28(3), 552-566.
Brynjolfsson, E., & McAfee, A. (2017). The business of artificial intelligence: What it can (and cannot) do for your organization. Harvard Business Review, 95(1), 62-70.
Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlström, P., & Henke, N. (2018). Artificial intelligence: The next digital frontier? McKinsey Global Institute.
Cachon, G. P., & Fisher, M. L. (2019). Inventory management and the bullwhip effect. Management Science, 65(6), 2587-2602.
Chiang, W. C., & Chen, H. C. (2018). The effects of pricing strategies on hotel performance: Focusing on the moderating role of market competition. Journal of Hospitality & Tourism Research, 42(4), 597-624.
Chen, Y., & Xie, Y. (2021). Channel performance analysis in online retailing: A literature review and future research agenda. Journal of Retailing and Consumer Services, 61, 102572.
De Silva, C., & Samaratunge, R. (2018). Impact of revenue management practices on financial performance: Evidence from the hotel industry in Sri Lanka. International Journal of Management and Applied Research, 5(3), 145-156.
Fildes, R., & Nikolopoulos, K. (2017). Forecasting and operational research: A review. Journal of the Operational Research Society, 68(9), 939-954.
Gatto, M., & di Foggia, G. (2019). Demand forecasting accuracy and external factors: Evidence from the Italian hotel industry. Journal of Revenue and Pricing Management, 18(2), 130-144.
Grewal, R., Saini, A., & Kumar, V. (2020). The impact of dynamic pricing on firm's financial performance. Journal of Retailing, 96(4), 485-500.
Gunawardana, P. G. (2018). Impact of revenue management practices on financial performance of star-class hotels in Sri Lanka. Kelaniya Journal of Management, 7(1), 30-46.
Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S. F., Childe, S. J., Hazen, B., & Akter, S. (2019). Supply chain 4.0 and digitalization: A review and future directions. International Journal of Operations & Production Management, 39(12), 1748-1772.
Hemantha, S. B. K. C., & Weerasinghe, W. M. P. I. (2018). The impact of revenue management practices on financial performance: A study of star class hotels in Sri Lanka. Journal of Tourism and Hospitality Management, 6(2), 43-54.
Huang, Z., Li, Z., & Huang, G. Q. (2021). Dynamic pricing and channel management in the airline industry. Transportation Research Part E: Logistics and Transportation Review, 146, 102219.
Huang, X., Sakhartov, A., Singhal, V., & Zhang, X. (2020). The effect of demand forecast accuracy on financial performance in the retail industry. Production and Operations Management, 29(3), 604-623.
Jain, V., & Singh, P. (2020). Price discrimination and financial performance: The mediating role of demand elasticity and pricing strategy. Journal of Business Research, 121, 350-362.
Kim, B., Park, S., & Kim, J. (2021). The role of artificial intelligence in hotel revenue management: An exploratory study. Journal of Hospitality Marketing & Management, 30(2), 172-189.
Kim, B. R., & Kimes, S. E. (2014). The relationship between hotel revenue-management practices and performance in U.S. hotels: An exploratory study. Journal of Hospitality & Tourism Research, 38(4), 487-510.
Kim, J., & Bai, B. (2018). The impact of revenue management on hotel performance: Evidence from South Korea. Journal of Travel Research, 57(8), 1077-1092.
Kimes, S. E. (2020). The future of hotel revenue management. Journal of Revenue and Pricing Management, 19(1), 1-3.
Kimes, S. E. (2011). The basics of yield management. Journal of Revenue and Pricing Management, 10(3), 209-222.
Kimes, S. E., & McGuire, K. A. (2012). A dynamic pricing model for co-managed hotel revenue streams. Journal of Revenue and Pricing Management, 11(6), 619-634.
Kimes, S. E., & McGuire, K. A. (2019). The impact of market segmentation on demand forecasting accuracy and revenue optimization. Journal of Hospitality & Tourism Research, 43(7), 1029-1051.
Kubičkova, V., & Benešová, D. (2023). Management of Ecological Innovations in Urban Hotels. Management of Ecological Innovations in Urban Hotels, 17(8), Page Range https://rgsa.emnuvens.com.br/rgsa/article/view/3727/1134
Kwon, H., Lee, H., Baek, J., & Lee, D. (2021). The effect of demand forecasting accuracy on firm financial performance. Journal of Business Research, 122, 559-567.
Lee, H., & Jang, S. (2019). The impact of channel integration in hotel revenue management. Journal of Travel Research, 58(4), 643-659.
Lee, S., & Jang, S. S. (2019). The impact of channel integration on revenue management performance: The mediating role of information integration. Journal of Hospitality Marketing & Management, 28(7), 721-739.
Legohérel, P., Medaglia, A. L., & Cucculelli, M. (2020). How does revenue management affect hotel performance? The mediating role of innovation. International Journal of Hospitality Management, 89, 102553.
Li, X., & Lin, S. (2019). Information technology capability and firm performance: Role of industry context. Information & Management, 56(7), 103-117.
Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z. G. (2020). Defining supply chain management. Journal of Business Logistics, 41(1), 1-25.
Nagle, T. T., & Hogan, J. E. (2016). The strategy and tactics of pricing: A guide to growing more profitably. Routledge.
Park, J., & Jang, S. S. (2020). Data analytics and decision-making in hotel revenue management. Journal of Hospitality Marketing & Management, 29(3), 276-294.
Sigala, M., & Christou, E. (2020). The impact of online travel agency presence on hotel revenue. Journal of Hospitality Marketing & Management, 29(5), 555-580.
Sigala, M., & Christou, E. (2020). Distribution mix and hotel performance in the sharing economy: A fully moderated model. Journal of Travel Research, 59(2), 289-305.
Sigala, M., Dellaert, B., & Christou, E. (2021). Integrating technology solutions in revenue management: A research agenda. Journal of Revenue and Pricing Management, 20(1), 74-88.
Simon, H. K., Wittink, D. R., & Zettelmeyer, F. (2019). The financial effects of value-based pricing. Marketing Science, 38(6), 909-926.
Tang, C., & Zhou, J. (2017). The role of advanced demand information in hotel revenue management. Journal of Hospitality & Tourism Research, 41(1), 3-26.
Tran, K., & Gupta, S. M. (2018). The impact of demand forecast accuracy on financial performance in the hotel industry. International Journal of Hospitality Management, 68, 29-38.
Verma, R., Dewan, S., & Kumari, A. (2019). Demand-driven decision making: A literature review and agenda for future research. Journal of Operations Management, 65(1), 37-55.
Vidalis, M., Syntetos, A. A., & Babai, M. Z. (2018). Inventory control strategies and financial performance: A system dynamics perspective. International Journal of Production Economics, 198, 48-61.
Wang, D., Kim, D., & Law, R. (2018). The impact of online reviews on hotel booking intentions and perception of trust. Tourism Management, 66, 53-64.
Warusawitharana, A. M. M. P. (2019). The impact of revenue management strategies on financial performance in Sri Lankan star class hotels. International Journal of Management and Commerce Innovations, 6(1), 11-20.
Weatherford, L. R., & Kimes, S. E. (2020). The relationship between demand forecasting accuracy and dynamic pricing performance. Journal of Revenue and Pricing Management, 19(3), 196-213.
Xu, X., Chen, J., & Li, X. (2021). Forecasting ancillary revenue streams in hotel industry: An integrated approach. International Journal of Hospitality Management, 94, 102824.
Xie, L., Gao, X., & Zhang, S. (2018). Revenue management automation in the airline industry: Impacts on performance. Journal of Revenue and Pricing Management, 17(4), 281-296.
Yapa, P. G. A. U., & Sudharshan, T. S. (2020). The impact of revenue management practices on financial performance of star class hotels in Sri Lanka. Journal of Tourism Research, 19(1), 60-80.
Zhang, Y., Zhang, X., & Ye, Q. (2019). Revenue management technology adoption and hotel financial performance: The mediating role of revenue management capability. International Journal of Hospitality Management, 83, 215-225.
Zheng, T., & Li, X. (2021). The impact of revenue management system adoption on hotel revenue management performance. International Journal of Contemporary Hospitality Management, 33(1), 384-405.
How to Cite
Copyright (c) 2023 Rohana Bandara Herath, Jacquline Tham, Ali Khatibi, S.M. Ferdous Azam Azam
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Authors who publish in this journal agree to the following terms: the author(s) authorize(s) the publication of the text in the journal;
2. The author(s) ensure(s) that the contribution is original and unpublished and that it is not in the process of evaluation by another journal;
3. The journal is not responsible for the views, ideas and concepts presented in articles, and these are the sole responsibility of the author(s);
4. The publishers reserve the right to make textual adjustments and adapt texts to meet with publication standards.
5. Authors retain copyright and grant the journal the right to first publication, with the work simultaneously licensed under the Creative Commons Atribuição NãoComercial 4.0 internacional, which allows the work to be shared with recognized authorship and initial publication in this journal.
6. Authors are allowed to assume additional contracts separately, for non-exclusive distribution of the version of the work published in this journal (e.g. publish in institutional repository or as a book chapter), with recognition of authorship and initial publication in this journal.
7. Authors are allowed and are encouraged to publish and distribute their work online (e.g. in institutional repositories or on a personal web page) at any point before or during the editorial process, as this can generate positive effects, as well as increase the impact and citations of the published work (see the effect of Free Access) at http://opcit.eprints.org/oacitation-biblio.html
• 8. Authors are able to use ORCID is a system of identification for authors. An ORCID identifier is unique to an individual and acts as a persistent digital identifier to ensure that authors (particularly those with relatively common names) can be distinguished and their work properly attributed.