Abstract
Technological changes in the hotel and hospitality sector prompt the essence of effective revenue management to enhance customer service and profit growth. For this reason, hotels need to apply automated revenue management systems (ARMS) to foster the optimization of revenues. InterContinental Sydney is one of the 5-star hotels that can apply efficient revenue management systems to boost their performance in the Australian market.
Technological changes influence the distribution channels in the hotel sector, thereby calling for the integration of ARMS to facilitate the analytics of customer trends. The real-time and re-optimizable pricing aspects of ARMS have the potential of increasing the revenue growth of InterContinental Sydney by an annual average of 3%.
Introduction
Revenue management is one of the critical aspects of running successful business organizations. The concept of revenue management is mainly the art and science of foreseeing instantaneous customer demands at the micro-market category and facilitating the optimization of price, as well as improving the availability of products (Mauri, 2013). In other words, revenue management entails the process of selling the right product to the intended customer at the correct time featuring the most reasonable prices (Yang, Pan, & Song, 2014).
Flexibility is crucial for revenue management to perform better in the hotel and hospitality sector, owing to the changes in different market forces (Suryakant, 2012). Some trends that are currently shaping the hospitality sector include:
- Relationship Marketing
- Partnership marketing and Strategic alliances
- Technology
- Guest Preferences
- Media Planning
- Globalization
- Product segmentation and branding
- Consolidation
- Environmental awareness
Therefore, the revenue management approach focuses on improving customer service, as well as the maximization of profits.
InterContinental Sydney is one of the notable 5-star hotels in Australia. The figure below shows an image of this world-class hotel. Situated in the Sydney central business district (CBD), InterContinental Sydney has been offering quality hospitality and hotel services to customers from different parts of the world for over three decades. The hotel upholds the essence of timely service delivery with an irresistible touch of luxury (Cannon, 2014).
Over the years, the business has recorded an impressive growth of its customer base, owing to the pricing it offers during off and peak seasons experienced in the hotel and hospitality sector. Notably, the InterContinental Hotels Group (IHG) proposed the incorporation automated revenue management systems (ARMS) model that facilitates the efficiency of the individual hotels situated globally. Importantly, the ARMS applies revenue analytics to develop visionary capabilities in the pricing and management of revenue. For this reason, InterContinental Sydney offers one of the best prices for rooms to its customers at any given time.
Undoubtedly, it is relevant to analyze the practices that have accounted for the success of the hotel’s revenue management over the few decades it has been operating in Sydney. In this view, it becomes crucial to justify the integration of ARMS at a given 5-star hotel with regards to its influence on the delivery of effective customer services besides bolstering the maximization of profits in the highly competitive hotel industry (Jayawardena, Lawlor, Grieco, Savard, & Tarnowski, 2013).
Therefore, the purpose of the research is to investigate the importance of ARMS in the hotel industry. This paper identifies how automated revenue management systems can be applied at InterContinental Sydney to enhance its competitiveness in the hotel sector in Australia. In this respect, the study will conduct a review of the relevant literature addressing the incorporation of ARMS in the hotel industry before leading a discussion of the findings.
Literature Review
Efficient revenue management is crucial in enhancing the profitability of a hotel business. In this light, Noone (2016) asserts that the revenue management approach in the hotel industry needs to guarantee the optimization of rates concerning the peaks and valleys experienced over time to realize meaningful occupancy figures. Hence, the need to consider the finer details of revenue management goes a long way in ensuring that the hotel company makes good use of the data required in pricing the rooms by understanding how much money customers are willing to pay at a given time.
Hua, Morosan, and DeFranco (2015) underline that taking care of the practical details of revenue management can introduce complexity to the important process of offering quality services to the right clients at the right price and in real-time. For this reason, hotel owners, as well as managers, need to adopt automated revenue management systems to realize a balance in the process of offering rooms to the right clients at the correct price in real-time (Hayes & Miller, 2011).
According to Hayes and Miller (2011), the changing distribution channels in the hotel and hospitality industry require players to embrace strategies that meet the needs of consumers. Law, Leung, Lo, Leung, and Fong (2015) assert that technological changes, especially the increased use of the Internet, affect the distribution of products and services in the hospitality and tourism sector. In this light, hotel managers need to incorporate technological advancements that capture the new distribution channels used by customers to access pricing information and the availability of rooms besides the offers presented by different competitors in the industry.
Additionally, Law et al. (2015) observe that technological advancements render traditional travel agencies irrelevant. In a similar line of thought, Kracht and Wang (2009) hold that changes in the distribution channels in the tourism industry prompt players to collaborate with other service providers such as software developers to foster the effectiveness of revenue management. Therefore, hotel managers need to embrace technologies that boost the growth of their revenues amid the changing distribution channels.
The adoption of third-party distribution metrics is critical in the current business environment. In this respect, Maier (2012) delved into an inquiry to assess the relevance of adopting the distribution metrics offered by third parties to foster the marketing aspects of a company to realize the set revenue management goals and objectives. The price parity aspect of the distribution metrics offered by third-party developers facilitates the real-time optimization of prices to realize maximum revenues. Maier (2013) insists that hotels that use the traditional revenue management approach portray incompetency in their price parity.
The optimization and adjustment of prices for the services offered by a given hotel company are crucial in streamlining revenue management. According to Jasin (2014), the manual management of the finite inventories and stochastic demands, as well as the selling horizon, brings about cumbersomeness in revenue management in the wake of complexities in the hotel sector. The need to remove such difficulties calls for the incorporation of the static price control system in revenue management (Jasin, 2014).
Importantly, ARMS such as the static price control requires a single optimization of prices at the start of the selling horizon without the need for re-optimization. Automated revenue management systems offer relief to managers who were traditionally needed to engage in substantial computations, in particular, for considerably large applications with regular adjustments of the price. Moreover, Bodea and Ferguson (2014) underline that the integration of ARMS is responsible for the realization of high-standard revenue performance, owing to the real-time adjustment, as well as re-optimization.
Pekgün et al. (2013) delved into a study to gauge the relevance of integrating innovative revenue optimization systems in the management of hotels. Particularly, the study assessed the collaboration between Carlson Rezidor Hotel Group (CRHG) and JDA Software Group in their efforts towards the application of operations research to heighten revenue gains, as well as bolstering the competitiveness of hoteliers.
The JDA Software Group offered an ARMS system referred to as Stay Night Automated Pricing (SNAP) to facilitate enterprise demand prediction in at least 600 hotels in the US in 2007. Pekgün et al. (2013) uncover that compliant hotels acquired a 2-4% revenue growth compared to companies that failed to integrate the SNAP system in their revenue management. The global rollout of SNAP by CRHG in collaboration with JDASoftware Group has seen hotels in America record a significant 416 million revenue growth annually (Pekgün et al., 2013). Therefore, to a considerable degree, the integration of ARMS in the hospitality industry is crucial in promoting the desired growth and competitiveness.
The InterContinental Hotels Group (IHG) is one that upholds the use of new technologies in its revenue management strategies. In this light, Koushik, Higbie, and Eister (2012) purposed to uncover the impacts of one of the large-scale implementation of ARMS in the hospitality industry by studying the outcomes of the PERFORM, a price optimization software.
The ARMS mainly focuses on improving price optimization by conducting an automated determination of room rates founded on price elasticity, occupancy, and the competitiveness of prices in the market. Surprisingly, the IHG has experienced an incremental growth of its revenue to the tune of $145 million since the implementation of the PERFORM system in its price optimization processes (Koushik et al., 2012).
Important to note, ARMS discourages the application of the traditional revenue management approaches, which assume that price independence or interdependence influences the level of demand (Bodea & Ferguson, 2014). Conversely, ARMS promotes the use of price elasticity, price competitiveness, and occupancy to foster revenue optimization.
The need to abandon the traditional assumptions of determining customer demand patterns in the hotel industry calls for the incorporation of advanced revenue management systems. Mauri (2016) posits that the traditional assumption of assessing customer demand trends in the hotel sector perceives how the customers engaging in the late booking of rooms have the willingness of paying higher prices compared to the consumers who make an early booking (Law, Leung, Au, & Lee, 2013).
Additionally, the traditional approach assumes that weekend demand for occupancy is usually higher than the weekday demand (Mauri, 2016). Nonetheless, changing consumer trends question the validity of the traditional approach in the fast-changing hotel industry. In this light, there is a need for managers to incorporate advanced mechanisms for gauging demand trends throughout the week and on weekends.
Viglia, Mauri, and Carricano (2016) assert that the simultaneous adjustment of prices by players in the hotel industry affects the decisions of customers significantly. Such decisions can undermine the revenues of a particular company. In this concern, there is a need for the embracement of independent behavior among competitors in the hotel sector. The integration of ARMS is one of the strategic approaches to fostering autonomous behavior in revenue management. ARMS discourage simultaneous and leader-follower approaches to revenue management by ensuring that a company in the sector sets and optimizes its prices independently, owing to the automated features of such systems.
The effective management of revenues about multiple-night stay at the hotel realizes a considerable efficiency through the implementation of automated revenue management systems that uphold the importance of customer service and profit optimization. In this concern, Aslani, Modarres, and Sibdari (2013) underline that automated revenue management systems go a long way in ensuring that customers experience an effective arrival rate after placing their bookings for a hotel.
Therefore, the positive image created by satisfactory customer services is instrumental in improving the competitiveness of the hotel, thus raising its revenues because of the growth of its customer base. Furthermore, Phumchusri and Maneesophon (2014) point out that ARMS ensures that hotel owners and managers take into consideration the avoidance of “customer losses” arising from the perception of expensive nights during a customer’s stay (p. 262). Notably, effective revenue management focuses on selling a product or a service to the right customer at a reasonable price that is also in line with the supply and demand trends in the industry.
Findings and Discussion
Hotel owners and managers need to integrate critical requirements for the efficient functioning of ARMS. Importantly, the reviewed literature shows that profit management experts need to engage in strategic pricing analysis that facilitates the establishment of revenue targets over a specified period. The setting of revenue targets is an important requirement for the incorporation of revenue management technology since its integration in the hotel seeks to realize the shared goals and objectives.
Therefore, if InterContinental Sydney seeks to attain a given number of bookings for its rooms, adopting the ARMS can facilitate the pricing analytics to meet the target by taking into account the market trends in the hotel industry. In this light, setting revenue targets is one of the key requirements that drive the efficiency of ARMS in InterContinental Sydney.
Additionally, the study unearths that the changing distribution channels in the hotel sector prompt the incorporation of technologies, including ARMS. The changing distribution channels affect the behavior of consumers, especially their willingness to pay for occupancy at a given hotel such as InterContinental Sydney. The embracing of ARMS is critical since it incorporates analytics to facilitate the optimization of prices. In this view, the study reveals that the acquisition of third-party distribution metrics is crucial for enhancing the competency of a hotel, thus facilitating the attainment of revenue management goals and objectives.
Furthermore, the study reveals that the elements of real-time adjustment and re-optimization of the ARMS applied in InterContinental Sydney are integral in facilitating the attainment of high-standard revenue management performance. The features relieve managers of the cumbersomeness of large computations that require constant readjustment of prices. Importantly, the technological systems apply analytics to establish the right prices for consumers, thus bolstering the optimization of revenues in the 5-star hotel.
The large-scale implementation of ARMS in hotels has the potential of boosting revenues by an average of 3% annually (Koushik et al., 2012). Notably, the modern revenue management tools foster the decision-making processes undertaken by hotel owners and managers by selling the preferred room to the intended client at the right time at a reasonable price. By so doing, the automated system supports the offering of quality customer service, which leads to the maximization of profits.
The traditional revenue management assumptions undermine the efficient pricing of hotel products, owing to the change in consumers’ preferences, marketing trends, and technological advancements. ARMS improves the prediction of customer demands by applying analytics that incorporates relevant and updated data. In this respect, the real-time optimization of prices denotes the irrelevance of applying outdated assumptions to determine the demand trends in the hotel sector.
Based on the results, revenue managers need to determine the most suitable pricing in every market situation. In the hotel industry, the determination of pricing is a crucial aspect of attracting the increased occupancy of the hotel rooms. In this respect, the incorporation of ARMS at InterContinental Sydney will simplify the pricing analytics aspect of revenue management by offering managers the right prices for customers to pay for rooms at any particular time.
The retail price optimization element of the ARMS will be integral in bolstering revenue increment of InterContinental Sydney by at least 3% annually. Important to note, retail price optimization improves the estimation of price elasticity in the hotel industry. Thus, it facilitates the optimization of the InterContinental Sydney hotel’s pricing strategy. Therefore, the smart revenue optimization tools of the ARMS will see InterContinental Sydney achieve instantaneous decision-making processes, as well as suggestions for optimum rates in just a click.
Revenue management requires experts in the field to set the best rates and apply them effectively. The effective establishment of rates is crucial in fostering the distribution of prices across different and multiple distribution channels. In this light, the implementation of automated revenue management systems at InterContinental Sydney will guarantee the swift setting of rates besides pushing them for application in the various processes of the hotel industry.
Therefore, the integration of such technologies relieves busy managers from the hassle of setting and managing prices across various distribution channels. In this light, managers at InterContinental Sydney can quickly come up with reliable forecasts and reports developed through the help of the automated systems. Additionally, the multidimensional view of the revenue management aspects fosters a greater understanding of the extent to which market trends influence the pricing aspect of the hotel industry.
Conclusion
The expositions made in this paper present the revenue management practice in business organizations as crucial for predicting customer demands. The practice bolsters the optimization of inventory, as well as price availability to reinforce revenue growth. This study has focused on the hospitality and hotel industry where revenue management is pivotal, especially in ensuring that managers offer rooms at the right prices depending on the market demand at a given time.
Therefore, as highlighted in the paper, through effective revenue management, a hotel would be in a position to offer the right room to the right client with the right timing, for the right price, and through the desired distribution channel. The study concludes that the implementation of ARMS at InterContinental Sydney will be crucial in an array of ways. For instance, it would bolster customer service delivery and profitability. The position is founded on the finding that the changing distribution channels necessitate the use of ARMS in the hotel sector to predict market demands and/or set strategic prices effectively.
ARMS offers real-time and re-optimizable prices to achieve the desired revenue management goals and objectives. The notable significance of ARMS in the management of hotels involves facilitating the attainment of average revenue growth of 3% yearly. Therefore, there is a need for 5-star hotels such as InterContinental Sydney to embrace ARMS to report a high-level performance in customer service and revenue growth in the highly competitive hotel and hospitality industry.
References
Aslani, S., Modarres, M., & Sibdari, S. (2013). A decomposition approach in network revenue management: Special case of hotel. Journal of Revenue and Pricing Management, 12(5), 451-463.
Bodea, T., & Ferguson, M. (2014). Segmentation, revenue management and pricing analytics. London, England: Routledge.
Cannon, M. (2014). Intercontinental: Sydney. London, England: Panacea Publishing International Ltd.
Hayes, D. K., & Miller, A. (2011). Revenue for the hospitality industry. Hoboken, NJ: Wiley.
Hua, N., Morosan, C., & DeFranco, A. (2015). The other side of technology adoption: Examining the relationships between e-commerce expenses and hotel performance. International Journal of Hospitality Management, 45(1), 109-120.
Jasin, S. (2014). Reoptimization and self-adjusting price control for network revenue management. Operations Research, 62(5), 1168-1178.
Jayawardena, C., Lawlor, F., Grieco, J. C., Savard, M., & Tarnowski, M. (2013). Challenges and innovations in hotel operations in Canada. Worldwide Hospitality and Tourism Themes, 5(2), 177-189.
Koushik, D., Higbie, J. A., & Eister, C. (2012). Retail price optimization at intercontinental hotels group. Interfaces, 42(1), 45-57.
Kracht, J., & Wang, Y. (2009). Examining the tourism distribution channel: Evolution and transformation. International Journal of Contemporary Hospitality Management, 22(5), 736-757.
Law, R., Leung, D., Au, N., & Lee, H. A. (2013). Progress and development of information technology in the hospitality industry: Evidence from Cornell hospitality quarterly. Cornell Hospitality Quarterly, 54(1), 10-24.
Law, R., Leung, R., Lo, A., Leung, D., & Fong, L. (2015). Distribution channel in hospitality and tourism: Revisiting disintermediation from the perspectives of hotels and travel agencies. International Journal of Contemporary Hospitality Management, 27(3), 431-452.
Maier, T. (2012). International hotel revenue management: Web-performance effectiveness modeling–research comparative. Journal of Hospitality and Tourism Technology, 3(2), 121-137.
Maier, T. (2013). Revenue management implications of branded vs. independent hotels price-parity and online distribution effectiveness. International Journal of Revenue Management, 7(3-4), 223-243.
Mauri, A. G. (2013). Hotel revenue management: Principles and practices. New York, NY: Pearson.
Mauri, A. G. (2016). Pricing and revenue management in hotel chains. London, England: Routledge.
Noone, B. M. (2016). Pricing for hotel revenue management: Evolution in an era of price transparency. Journal of Revenue and Pricing Management, 15(3-4), 264-269.
Pekgün, P., Menich, R. P., Acharya, S., Finch, P. G., Deschamps, F., Mallery, K., & Fuller, J. (2013). Carlson Rezidor hotel group maximizes revenue through improved demand management and price optimization. Interfaces, 43(1), 21-36.
Phumchusri, N., & Maneesophon, P. (2014). Optimal overbooking decision for hotel rooms revenue management. Journal of Hospitality and Tourism Technology, 5(3), 261-277.
Suryakant, L. (2012). Marketing strategies and quality management of five star hotels in order to improve its revenue with special reference to selected five star hotels in Mumbai. Commerce and Management, 1(4), 28-36.
Viglia, G., Mauri, A., & Carricano, M. (2016). The exploration of hotel reference prices under dynamic pricing scenarios and different forms of competition. International Journal of Hospitality Management, 52(1), 46-55.
Yang, Y., Pan, B., & Song, H. (2014). Predicting hotel demand using destination marketing organization’s web traffic data. Journal of Travel Research, 53(4), 433-447.