Average Room Rate Research Articles

The curious case of Hotel King’s Cross

Learning outcomes The learning outcomes of this study are to recall the fundamental concept of revenue management in the hotel industry (remembering); explain the various performance measures used to evaluate room revenue in hotels (understanding); use revenue management strategies to improve room revenue in hotel operations (applying); and examine and evaluate the optimal solution for revenue enhancement, considering factors such as capacity management, duration control and differential pricing (analyzing). Case overview/synopsis This case study delves into the challenges faced by Hotel King’s Cross, a business hotel located in Pune, Maharashtra, in the year 2022. A week before Christmas Eve, Soham Dande, the hotel’s revenue manager, sought a meeting with Rohan Chopra, the director of sales and marketing, to discuss “revenue optimization for the hotel.” During their meeting, Dande mentioned that the hotel had fallen behind its budgeted room sales targets for 2022 across various metrics, such as room booking nights, occupancy percentage, average room rate and revenue per available room. Furthermore, the hotel was trailing behind its competitors. The situation was compounded by the management’s decision to raise the targets for 2023 by 5%–7%, factoring in upcoming events, competitive performance and pandemic-related losses over the past two years. Chopra faced the dilemma of formulating an action plan to achieve the ambitious 2023 targets and establish Hotel King’s Cross as a market leader. Complexity academic level Students undertaking executive development programs and graduate-level courses in non-profit hospitality and tourism management, as well as revenue management courses in the executive MBA, management development and graduate MBA programs, may all benefit from this case study. Supplementary materials Teaching notes are available for educators only. Subject code CSS12: Tourism and hospitality.

A reinforcement learning approach for hotel revenue management with evidence from field experiments

AbstractWe consider a budget hotel chain's revenue management problem of deciding how to dynamically allocate capacity to multiple segments of customers. Our work solves an industrial‐sized problem faced by practitioners, with the reality of implementation motivating us to develop a tailored reinforcement learning approach. Our approach proceeds in two steps. First, a recommended average discount is computed with a reinforcement learning algorithm. Then, the recommended average discount is turned into a capacity allocation through a linear program. This approach overcomes the challenges of characterizing demand and estimating cancellations, and it facilitates hotel managers' acceptance of the revenue management system. We implement this approach in the hotel chain in a pilot study and assess its effectiveness using synthetic control methods. Our approach improves the key operational performance measure—revenue per available room—by 11.80%. There is heterogeneity in how the pilot hotels improve their revenue per available room. Some mainly increase their occupancy rate, some mainly increase the average daily room rate, while others experience significant increases in both. Further analysis shows that our approach uncovers the individual sources of suboptimal performance in pilot hotels and correspondingly improves decision‐making. Our work demonstrates that a reinforcement learning approach for hotel revenue management is promising.

Comparative Analysis for Strategy Implementation in Indonesia's Hotel Business Sector During Covid-19

This paper examines the performance of differentiation strategies employed by two prominent holding hotel companies, Intercontinental Group, and ACCOR Group, within different hotel categories. This research objective is to compare the revenue performance of 3-star and 4-star hotels, specifically Holiday Inn and Holiday Inn Express (from Intercontinental Group) also Ibis and Novotel (from ACCOR Group). The data analysis involves the calculation of revenue percentages for each hotel category over seven years, from 2016 to 2022. This research adopts descriptive and comparative approaches by contrasting the performance metrics of RevPAR, Occupancy Rate, and Average Room Rate (ARR). In conclusion, in 2016-2019, both the 4-star hotels of ACCOR Group and InterContinental Group tended to experience a downward trend in performance on all metrics. However, on the metrics of ARR and RevPAR, Novotel looks to dominate Holiday Inns. Even though the Occupancy Rate (OCC) metrics, the two hotel brands are balanced. In the 3-star hotels, both hotels also experienced a downward trend in 2016-2019. Both Holiday Inn Express and Ibis were unable to withstand in 2020, so the decline in their performance plummeted. On the positive side in 2021-2022, both hotels seemed to be back on their feet with significant increases and Ibis from ACCOR Group tends to excel in all three metrics. In terms of revenue percentage, it can be concluded that the 3-star hotel strategy is successful even in uncertain conditions. Meanwhile, the 4-star hotel strategy needs to be evaluated whether it is resilient enough to deal with unexpected situations

ANALYSIS OF FACTORS AFFECTING HOTEL TAX REVENUE IN TASIKMALAYA CITY

This study aims to prove the effect of Average Room Rate, Number of Tourists, and Constant Gross Regional Domestic Product (GRDP) on Hotel Tax Revenue in Tasikmalaya City. The data used in this study is data for 2018 – 2021 which aims to analyze Hotel Tax Revenues in Tasikmalaya City. By using secondary data sourced from the Regional Revenue Service of the City of Tasikmalaya and the Central Bureau of Statistics of the City of Tasikmalaya. Data analysis in this study used Multiple Linear Regression analysis using SPSS. The results of this study indicate that the average room rate has a positive and significant effect on Hotel Taxes, the number of tourists has a positive and significant effect on Hotel Taxes, and constant GRDP has a positive and insignificant effect on Hotel Taxes.

Understanding customer's online booking intentions using hotel big data analysis

The presented article focuses on the issue of customer segmentation in the hospitality industry and its use for price optimisation. To identify the market segments article uses the Two-Step cluster analysis. The analysis was based on the seven variables (length of stay, average room rate, distribution channel, reservation day, day of arrival, lead time and payment conditions). Six clusters were identified as following segments: Corporates, Early Bird Bookers, Last Minute Bookers, Product Seekers, Values Seekers and Last Minute Bookers. To optimise the price for these segments, article works with the coefficient of price elasticity of demand for the presented market segments. The price elasticity of demand is measured by the log-log regression analysis. Data were colected from the four-star hotel in Prague, Czech Republic and analysis is based on more than 9000 transactions. Last minute bookers segment was the only one with the positive coefficient of price elasticity and has the lowest value of lead time (9,27 in average). Product seekers have the highest coefficient of price elasticity (−3,413) and highest average room rate (3573 CZK in average). Early bird bookers, Long time stayers, Corporates and Value seekers was identified as pricely inelastic.

A Study of Determinants of Hotel Prices in Lagos, Nigeria

The research study is aimed at determining the Hotel prices in Lagos metropolis. Attributes of the location, chain firms, years of operations, numbers of rooms, and numbers of house-keepers influence room rates in hotels. A regression model was developed for various hotel segments in Lagos state. Regression model provides a more flexible and complete characterization of the determinants of the hotel prices at the higher and lower tail of the distribution. Data was obtained using structured questionnaires through non-probability sampling in Victoria Island, Ikoyi and Lekki Pennisula were various hotels are located. The 30 questionnaire recovered was analyzed using SPSS and interpreted using descriptive statistic The findings reveal that, franchise, resort location of hotels and year of establishment are significant attributes that determines hotel average room rate in Lagos, Nigeria.

An estimate of the value of the beachfront with respect to the hotel room rates in Thailand

An economic assessment for a non-market resource like sandy beaches is always a challenge for Thailand's coastal policy planners due to the lack of data availability, especially on the national scale. While beach tourism in Thailand has been an essential part of the Thai economy, the sandy beaches are probably exposed to the future sea-level rise. Therefore, the need for tourism benefits of the beaches should be conducted. The research attempted to measure the effect of sandy beach characteristics and hotel location on hotel room rates. A sample of 3319 hotel rooms across Thailand's coastal sub-districts, covering the entire sandy beaches in Thailand, was collected through a hotel-booking online database during the country's peak season. The considered variables include hotel room attributes, sandy beach characteristics, hotel locations, and coastal infrastructures. Through a hedonic price model based on geographically weighted regression analysis, the relationship between the dependent variables (hotel room rate) and the independent variables (selected beach variable) was estimated to evaluate the marginal effect and its spatial variations. The tourism benefit was calculated assuming the marginal effect of the hotel's beachfront locations on hotel price. The study suggested that the location in front of the beach raised the average hotel room rates by 13–41%. The results emphasized the significant spatial variability of the effect of beachfront location on the hotel price. In addition, the effect of beach protection structures (i.e., seawall, breakwaters, groins) on the hotel price was also investigated and implied a slight drop by 8–15% of the average price. The other sandy beach variables (such as beach length, width, and slope) effects on hotel price were also investigated. The finding of this study aims to help policymakers select and design proper adaptations to coastal erosion on tourist beaches in Thailand.

The impacts of domestic and global economic policy uncertainties on the hotel room demand: Evidence from Singapore

Applying cointegration analysis on the monthly data of Singapore, this research note examines the impacts of global economic policy uncertainty (GEPU) and domestic economic policy uncertainty (DEPU) on the hotel room demand. Although control variables, such as average room rates, industrial production index and international tourist arrivals, are used and the specific-to-general modelling is adopted, the results show that the standard diagnostic tests may be incapable of identifying possible model mis-specification. The main findings show that DEPU has a negative impact, but GEPU has a positive impact on the hotel room demand. DEPU is linked to the political instability of Singapore, which discourages international travellers to visit Singapore. GEPU enhances Singapore’s position as a stable business and financial hub in relation to others and thereby increases business travel.

Customers’ purchasing intentions for enhanced cleaning services in hotels during COVID-19: establishing price strategies

PurposeThis paper aims to contribute to the literature investigating hotel customers’ preventive behavior during the COVID-19. Because there is no timely research discussing cleaning and disinfection services as a premium service in China, the authors conducted research to examine customers’ perceptions based on the information–motivation–behavioral skills (IMB) model and to explore potential marketing exits. Moreover, based on the price-sensitive measurement, this study reveals the price range and optimal price of the service, which could assess the feasibility of the service and balance the operation cost.Design/methodology/approachAn internet-based, self-reported survey was designed to collect the data during the outbreak of COVID-19 in April 2020. The yield was 874 usable and valid responses, which were purposefully analyzed using confirmatory factor analysis and structural equation modeling.FindingsThe results indicate a significant influence of dimensions (information, motivation, health behavior skills) on hotel customers’ preventive behavior regarding purchase intention of cleaning and disinfection service. The optimal price of this service is 20% of the average room rate, and the range of acceptable prices is 15% of the average room rate.Originality/valueThe present study represents academic attempts to contribute to the literature by applying the IMB model to consumer behavior in a hotel industry context, emphasizing the importance of each dimension in behavioral intention during the current ongoing global issue. Additionally, the results indicate that the hotel industry could consider satisfying the needs of this market based on the suggested price.

The Effect of Organizational Culture on Financial Performance: Based on Cameron and Quinn Model (CVF)

The research objective is to investigate the impact of organizational culture (OC) based on the Cameron and Quinn model (The Competing Value Framework) on financial performance (FP) in Egyptian hotels. The research used five dimensions (occupancy percentage, average room rate, RevPAR, average market share, and average revenue) to measure FP in hotels. Quantitative methods were used to achieve the research objective through the questionnaire. A total of 416 questionnaires were provided to general, executive, HR, and quality managers working in four five-star hotels in Sharm El Sheikh city 104 hotel in Egypt. The research used three main data analysis techniques: descriptive analysis, correlation, and multi-regression by SPSS V25. Empirical findings showed that OC positively affected the FP of hotels. The research recommends that hotels in Egypt to attention to the consolidation of OC types because of their positive impact on enhancing the FP of hotels. Hotels should also promote organizational values such as fairness, equality, teamwork, and employee cooperation and, in addition, enhance the interest in organizational beliefs such as the human element and job satisfaction to increase rewards and incentives.

Financial Ratio Analysis to Assess Financial Performance of the Hotel Industry

Analysis of financial performance can be implemented to all companies, including to hotel industries. For the last few years, there are many issues that income of hotel industry increases because of the soaring numbers of foreign and domestic tourists in Indonesia. This study aims to analyze financial ratio to assess the financial performance of hotel industry in 2015-2018. Research sample were 12 companies of 35 hotel industries that were listed in Indonesian Stock Exchange in 2015-2018. Analysis tool used in this research were liquidity ratio, profitability ratio, activity ratio, leverage ratio, and operational ratio. Research result showed good ratios; they were liquidity ratio that was indicated by current ratio, profitability ratio that was pointed by net profit margin, return on asset, and return on equity, also paid occupancy percentage on activity ratio. While the not good ratio, which was activity ratio was pointed by total asset turnover, then leverage ratio by equity multiplier, debt to asset ratio, and debt to equity ratio, also operational ratio which was showed through average room rate and food and beverage cost. Research result of hotel performance in 2015-2018 which is based on financial ratio, they are liquidity, activity, profitability, leverage, and operational, describes that hotel performance is fluctuated. Generally seen, a good ratio in this study is the liquidity ratio that is pointed by current ratio, then profitability ratio that are demonstrated by NPM, ROA, and ROE, also paid occupancy percentage in activity ratio.

Mengelola Pendapatan Kamar Hotel yang Optimum (Yield Management)


 
 
 The market is always changing and increasing competition. In this condition, the hotel needs to improve responsiveness to the environment to service. Hotels should be able to establish a policy with the best results. Yield management offers a concept for each hotel is able to put himself in the best position in the changing environment. Revenues need to be managed well for a more popular method is called yield management or revenue management Currently, yield management, has become a very important innovation in the hospitality industry. The main objective of yield management is to maximize the occupancy room and at the same price achieved average room rate is high. The rooms are the same product, but have different market segments, both used by the guest or guest tours individual. Each market segment may be subject to different prices for the same period. Demand for each segment in the future, have a fairly high level of uncertainty in thiscase, management does not know how much and when the individual guest is coming. Individual guest room reservations typically do on arrival or a few days prior to say, while guest tour groups generally pay full price and keep the rooms are not already sold to the tourist gueist at cheap prices or discounts. Profit oriented hotel management and have broad freedom of action to increase revenue at the optimum level of demand for rooms is very high. This is to compensate low income or cover losses in the period of very Iow occupancy rates, where rooms are sold at discount in nearly all segments. Room sales management to achieve optimum opinions need to plan how many rooms are sold at a discount and how many rooms were sold at full price. In addition . to avoid loss of revenue due to cancellation of booking rooms during periode of high demand for rooms, management needs to accept room reservations exceeds the number of rooms available for sale
 
 

City or beach hotel? Location as a determinant of customer satisfaction and room rate

Purpose This research aims to reveal that accessibility of hotels to major points of attraction in the urban–territorial continuum of Catalonia, with its urban and coastal landscapes, has a direct impact on the dependent variables of customer satisfaction and average room rate. Design/methodology/approach The study collected data from 84 of 4-star hotel establishments, divided into urban and coastal hotels. Both coastal and urban hotels were differentiated depending on their distance to, the beach and the urban city center, respectively. Customer satisfaction and average room rate data were retrieved from online review platforms. Findings The study proves that hotels located in the urban–territorial continuum of Catalonia have different behaviors in terms of customer satisfaction and hotel pricing according to the variables of distance and landscape. The study shows that room rate and customer satisfaction are both higher in urban landscapes than in coastal landscapes. Urban hotels present significant differences in their levels of customer satisfaction and room rates depending on their location in the city of Barcelona. However, coastal hotels do not represent significant differences in room rates depending on their location, although they do represent significant differences in terms of customer satisfaction. Originality/value The originality of this study is based on how a dynamic urban–territorial model consisting of Barcelona and the Maresme coast, the hotel location and distances to main interest points impact in the variables of customer satisfaction and average room rate.

STRATEGI PENINGKATAN OCCUPANCY RATE DAN AVERAGE ROOM RATE PADA MASA PANDEMI COVID-19 DI HOTEL NOORMANS SEMARANG

The Covid-19 pandemic has caused unrest for all citizens of the world in the health, trade, economy, security, politics, transportation, human mobility and tourism sectors. As the second largest contributor to foreign exchange in Indonesia in 2019, tourism, especially hospitality, has experienced a significant decline in business. Starting from canceling room reservations to canceling various activities at the hotel. As a consequence, the hotel occupancy rate and average room rate dropped dramatically to 10% - 25%. This was also experienced by Hotel Noormans Semarang, which only had an occupancy rate of 15% in April 2020 with an average room rate below the price of IDR 300,000.00. The aim of this paper is to observe the strategy to increase the occupancy rate and average room rate during the Covid-19 pandemic at the Hotel Noormans Semarang. This research was designed with a descriptive qualitative paradigm. This research shows that the strategy of increasing the occupancy rate and average room rate during the pandemic at Noormans hotels in 2020 does not show positive results. However, what happened was the opposite, a decline from 2019 to 2020. The occupancy rate decreased from 70% to 36% and the average room rate decreased from IDR 332,094.00 to IDR 258,250.00. Keywords: occupancy rate, average room rate, hotel, Covid-19

АНАЛІЗ ЕКОНОМІЧНОЇ ЕФЕКТИВНОСТІ ОРГАНІЗАЦІЇДІЯЛЬНОСТІ ГОТЕЛІВ ШТАТУ ФЛОРИДА (США) ПІД ЧАС ПАНДЕМІЇ КОРОНАВІРУСНОЇ ХВОРОБИ COVID-19

The article examines the main trends in the functioning and economic aspects of the organization of four-star hotels in Florida, USA in connection with the crisis caused by the COVID-19 pandemic. The article describes the state of the hotel business, which has suffered significant losses due to severe quarantine restrictions caused by the fight against coronavirus infection. Operational activity of hotel facilities is an activity which consists in effective and rational management of operations on performance of the basic functions of hotel. The article states that the pandemic has significantly affected the organizational activities of the hotel, its conditions and pricing policy (forced dumping). To present the scale of the negative impact of COVID-19, the article analyzes the average operating income data, average hotel occupancy data, average daily room rates, and hotel profit statistics for the three quarters of 2020 and 2021. The concept of «profit» is revealed – one of the main economic indicators that reflects the efficiency of the enterprise, its financial condition, success and opportunities in economic development. The coronavirus crisis has led to changes in the implementation of business strategies of the hotel business. Promising areas for hotel product diversification may be improving the quality and safety of services, increasing the role of the Internet and social networks in shaping consumer preferences, finding new forms of cooperation, using new business technologies, the need to develop universal anti-crisis strategies in the hotel business in the United States and in Ukraine. Promising areas of hotel product diversification are improving the quality and security of services, increasing the role of the Internet and social networks in shaping consumer preferences, finding new forms of cooperation, the use of new business technologies. The issues of the need for the state to develop preferential lending conditions and regulatory policy for the transfer of land for the targeted construction of tourist facilities are considered.

The Impact of the New York City Marathon on Hotel Demand

Daily hotel data are employed, along with information on prices, revenue, demand and hotel occupancy, to analyze part of the local economic impact of the annual New York City (NYC) Marathon. As the largest competitive race in the world, the marathon attracts domestic and international competitors and spectators. The cancellation of the 2012 marathon due to Hurricane Sandy was estimated to lead to an increase of 4000 hotel nights as well as a 10% increase in the average daily room rate. Taken together, this is associated with a USD 3 million increase in hotel revenue. The results suggest a significantly lower local economic impact of the race than previously thought.

The cost of losing a National Football League franchise: evidence from hotel occupancy data

ABSTRACT In the past five years, San Diego and St. Louis lost National Football League franchises to Los Angeles. This paper uses daily data on hotel room rentals, average room rates, and hotel revenue to examine the effect that losing NFL franchises will have on those cities. For comparison, other events including professional baseball and hockey franchises, Major League Baseball’s All-Star Game, and two college football bowl games are considered.

The Impact of Conventions on Hotel Demand: Evidence from Indianapolis Using Daily Hotel Occupancy Data

This paper uses daily hotel occupancy data for the Indianapolis metro area from STR to estimate the effect of multi-day conventions on hotel demand. In addition to multi-day conventions, we hand collect data on other major events such as the Indy 500 and major sporting events. Hotel demand is an important part of the economic activity generated by multi-day events because hotel rooms are largely occupied by out-of-town guests and represent new local economic activity. We look at the effect of conventions and other large events in Indianapolis on average daily room rates, revenue per room, demand, occupancy, and total revenue. We find large and statistically significant effects for multi-day conventions on hotel demand with very little evidence of crowding out. A single day of a multi-day convention brings in approximately $928,000 in additional hotel revenue. Our findings contribute to the literature on the economic impact of large events such as conventions and sporting events that attract out-of-town visitors.

Using Customer Characteristics to Manage Marketing and Revenue Management Activities

Understanding customer behaviour is an essential activity for hotel marketers and revenue managers. This article presents the statistical approach based on the data mining techniques focused on the extraction of valuable insight from big data. Using Two-Step Clustering, four major customers segments were identified, including their characteristics. Their description based on the booked room type, rate plan, booking window, net average room rate and length of stay can help the manager to plan better their activities.

Estimating the duration of different seasons and their impact on hotel room prices

The purpose of the study is to accurately measure the span of different seasons and its effect on the fluctuation of the occupancy rate and the average room rates in the hospitality sector. While prior studies have concentrated on measuring seasonality using calendar months, this study takes a different approach by measuring seasons in terms of the date count so that the exact starting and ending date of a season can be identified. This step involves adopting a non-parametric methodology that split the time scale into several small parts to obtain a better fit of the relationship and that can detect the starting and end of the season when given specific dates.