The Impact of Discounting Room Rates on In-House Restaurant Sales

This study investigates whether discounting hotel room rates during low seasons of demand influences in-house hotel restaurant sales in a positive way. A linear regression function was utilized to assess the relationship between discounting room rates and the hotel's in-house restaurant sales. The model summary provided results indicating that the discounting of room rates during the low season did not significantly influence in-house restaurant sales. The value of this study lies in the empirical results that may provide guidance to the revenue management practices of hotel managers.     

How do advertising expenditures influence hotels’ performance?

Existing studies have shown a positive relationship between advertising and hotel room revenue. However, it is not clear through which channel advertising affects hotel revenue. We contribute to the literature by showing that advertising has a significant positive impact on hotel room price, but not on room occupancy. Thus, advertising affects room revenues through room price, not quantity demanded.     

Data Mining For Hotel Occupancy Rate: An Independent Component Analysis Approach

The recent global financial crisis and the threat of a worldwide H1N1 influenza epidemic have greatly affected the tourism and hospitality industries around the world. Both hospitality practitioners and researchers are interested in finding analytical methods that enable forecasts to be made of hotel room demand under the uncertain conditions likely to affect the industry. In this article, a novel data mining technique called independent component analysis (ICA) is proposed to establish the major factors determining the hotel occupancy rate in Hong Kong. Then, extension of the model is suggested, incorporating these factors to decompose hotel occupancy rates and examine the effect of each factor on the hotel occupancy rate. Empirical findings show that outbreaks of infectious diseases, economic performance, and service price were the major determinants of the hotel occupancy rate in Hong Kong over the period studied.     

Effect of monumental heritage sites on hotel room pricing

This study measures the effect of historic monuments on hotel room pricing in Seville, Spain. A hedonic model including classic explanatory variables and the city’s heritage site was specified to explain hotel room rates. Variables related with heritage sites were determined to explain room rates and an iso-values map was obtained for the rates of a ‘standard hotel’ to show the impact of historic buildings on hotel rates. The maps display the area of influence of the heritage site. These results may be of interest to entrepreneurs, consumers, or the administration, among others, due to it permits them to determine which location maximizes rates.     

Globalization or localization of consumer preferences: The case of hotel room booking

The purpose of this study is to investigate potential differences in attitudes between Chinese and Western tourists towards various hotel room reservation policies. The study is meant to help the revenue managers of international hotel companies make informed choices on whether to pursue a globalized or a localized approach in the design of hotel room rates and rate restrictions. Three ranges of room prices and four types of rate restrictions are evaluated. The rate restriction policies considered are: a) rule type, b) advance requirement, c) refundability, and d) changes allowed. The results of customer surveys show that the Chinese and Western respondents do not express significantly different preferences concerning room rates, advance requirement, rule type, or refundability. They differ significantly only concerning the changes allowed policy. This result indicates that revenue managers of international hotel companies can take a globalized approach in designing rate restrictions. The identification of these customer preferences provides hotel revenue managers with empirical data on the attitudes of culturally diverse consumers, and this information can enable the design of hotel pricing policies that attract consumers in the global market.     

Determinants of revenue per available room: Influential roles of average daily rate,demand, seasonality and yearly trend

Determining price per room to be charged to customers is an important decision to be taken by hotel management. Hotels frequently change their room rates based on the demand of room, occupancy rate, seasonal pattern, and strategies undertaken by other hotels on pricing. We formulated four models to analyse how various influencing variables, such as hotel price, demand, yearly trend and monthly seasonality influence hotel revenue per available room (RevPar). To analyse a case, we used monthly accommodation statistics for Sweden taken for Swedish Agency for Economic and Regional Growth and Statistics from January 2008 to July 2017. We carried out data analysis using both multiple regression and Multivariate Adaptive Regression Splines (MARS) model and found that application of MARS can help establishing a nonlinear relationship of RevPar with other determining variables in a superior way. We also proposed the possibility of developing a better forecasting model using MARS.     

Pricing determinants in the hotel industry: Quantile regression analysis

Due to the skewed distribution of hotel prices, quantile regression provides a more flexible and complete characterization of the determinants of the hotel prices at the higher and lower tail of the distribution. This study applies quantile regression approach to investigate the major determinants of hotel room pricing strategies. The ordinary least square regression is also used for comparative purposes. The data are drawn from 58 international tourist hotels in Taiwan and average room rate (ARR) is used as the proxy of hotel room price. The results of OLS and quantile regression share common characteristics but also have differences in some aspects. The OLS results reveal that number of rooms, hotel age, market conditions and number of housekeeping staff per room are the main attributes of hotel room rate. The quantile regression results further demonstrate that room number and the number of housekeeping staff per guest room do not significantly influence hotel price at the low price quantile. Hotel age and market conditions are only significant determinants in high-price category. Additionally, for the high-priced quantile hotels, the proportion of foreign individual travellers positively and significantly influences room price. The empirical results can help hoteliers in shaping investment and pricing strategies.     

How demand uncertainty and market concentration affect long-term price instability

The object of this paper was to investigate the long-term influences of demand uncertainty and market concentration on price instability in the hotel industry. We applied 1996–2008 price and room revenue data collected by Taiwan's Tourism Bureau to test the following two hypotheses: (1) demand uncertainty is negatively associated with price instability in the hotel industry; (2) the market concentration is negatively associated with hotel price instability. We constructed a two-stage price instability model and the estimate results produced the following two findings: First, the uncertainty in room demand significantly contributed to the price instability. Second, the effects of market structure on price instability were heterogeneous across different levels of price instability distribution. Notably, when the distribution of price instability moved from lower to higher quantiles, the relationship between market concentration and price instability altered from positive to negative.     

Successfully selling accommodation packages at online auctions – The case of eBay Austria

In this era of e-commerce online auctions have emerged as a valuable distribution channel (36 and 52). Displaying low entry and exit barriers but also vast coverage rates, online auctions may effectively augment the distribution potential of hotel businesses. This paper identifies those factors that positively affect the final price level obtained in online auctions for hotel room vouchers. Based on data gathered at eBay comprising 53,406 auctions, linear structural equation modelling (SEM) was conducted to identify significant relationships between auction characteristics and the obtained final price for hotel room vouchers. By drawing on these results and through an example of the Austrian eBay platform, selling strategies for successfully listing accommodation packages at online auctions are proposed.     

Tourist tax elasticity in Florida: Spatial effects of county-level room tax rate variation

We examine the spatial, county-level incidence of changes to tourist tax rates in Florida from 2003 to 2014. Florida allows county-level visitor tax increments to fund various tourism-related initiatives. As a result, there is considerable variation in visitor tax rates across counties and across time. Using a dynamic spatial autoregressive panel model, we show that direct and indirect effects of room tax rate changes on taxable hotel room expenditures are relatively small and largely exported to visitors. Because these taxes have recently been allowed for funding Major League Baseball Spring Training facilities, we also test whether these facilities impact hotel tax collections. We find no measurable effects of a small number of facility relocations on hotel spending in the new or previous home-counties. We also discuss the importance of considering contiguous spillovers and the use of cluster-robust standard errors in panel estimation of tax incidence for tourism.     

Initially Testing an Improved Extrapolative Hotel Room Occupancy Rate Forecasting Technique

SUMMARY

The existing time series forecasting models either capture the informationof the last few data in the data series or the entire data series is used for projecting future values. In other words, the time series forecasting models are unable to take advantage of the last trend in the data series, which always have a direct influence on the estimated values. This paper proposes an improved extrapolative time series forecasting technique to compute future hotel occupancy rates. The performance of this new technique was tested with officially published room occupancy rates in Hong Kong. Forecasted room occupancy rates were compared with actual room occupancy rates in several accuracy performance dimensions. Empirical results indicate that the new technique is promising with reasonably good forecasting results.     

The effects of Airbnb on hotel performance: Evidence from cities beyond the United States

Although Airbnb's impact on hotels has been quantified for major hotel markets in the United States, these effects have not been quantified in international hotel markets. Accordingly, the purpose of this study is to examine the effects of Airbnb listings on key hotel performance metrics in an international context. In particular, we examine the effects of Airbnb listings on hotel revenue per available room (RevPAR), average daily rate (ADR), and occupancy rate (OCC) in major international hotel markets, namely London, Paris, Sydney and Tokyo. The results show that Airbnb listings in these major cities have been increasing more than 100% year over year and that the effect of Airbnb on hotel RevPAR and OCC is negative and statistically significant. In particular, a 1% increase in Airbnb listings decreases hotel RevPAR by between 0.016% and 0.031% in these hotel markets. The implications of these findings for destinations and hoteliers are discussed.     

What caused the rise of Airbnb? An examination of key macroeconomic factors

The social and economic implications of the Airbnb phenomenon have been the subject of much research. Yet, the academic literature on Airbnb is nascent. Specifically, the issue of whether major macroeconomic conditions affect the supply of Airbnb has not been investigated. To address this gap, we propose a conceptual model that explains the determinants of Airbnb supply and examine the extent to which major macroeconomic factors affect the supply of Airbnb. Specifically, we analyze the effects of hotel room rates (ADR), hotel demand, tourism demand, house prices, gross domestic product (GDP), wages and unemployment on the supply of Airbnb in 50 U.S. states. Results show that increases in hotel ADR, house prices, and GDP have contributed to an increase in the supply of Airbnb, whereas increases in unemployment rates and wages have adverse effects on Airbnb supply. Theoretical and policy implications are discussed within realms of macroeconomic theory.     

Investigating the whole picture: Comparing the effects of Airbnb supply and hotel supply on hotel performance across the United States

This study examines and compares the extent to which Airbnb and hotel supply affect key hotel performance measures in the United States. The results show that although both Airbnb and hotel supply adversely affect hotel revenues (i.e., RevPAR), the magnitude of the impact of hotel supply on RevPAR is much larger than that of Airbnb. Airbnb adversely affects hotel room prices (i.e., ADR), however; it does not affect occupancy rates (i.e., OCC). Yet, increasing hotel supply negatively affects OCC but not ADR. The results from the state-level analyses further showed that the negative effects of Airbnb and hotel supply on RevPAR, ADR and OCC persist only in states with high hotel supply. Analyzing the joint effects of Airbnb and hotel supply on hotel performance in a manner that is both geographically-comprehensive and spatially-meaningful, this study provides a more complete and nuanced understanding on the economic dynamics of the accommodation industry.     

The Channel That Offers the Lowest Online Room Rates: A Case Study of Hotels in Hong Kong

Online distribution channels increasingly serve as platforms hotels can use to offer competitive room rates to attract price-sensitive customers and maximize yield. Capturing the lowest and highest daily room rates over a 360-day period from five of the most popular online travel agencies, and two batches of data showing the lowest room rates over 28 days from a last-minute bookings website, this study compares the lowest prices offered. The results indicate that no single online channel outperforms the others in any of the hotel star-rating categories, and that the last-minute reservation service provides the lowest hotel room rate across different star ratings.     

The Determinant of the Hospitality Industry's Unsystematic Risk: A Comparison Between Hotel and Restaurant Firms

ABSTRACT

Unsystematic risk is accepted as an important factor in stock valuation. Despite the importance, little has been done to study the relationship of unsystematic risk to stock values in the hospitality industry. This study attempted to advance the understanding of financial variables that could be related to unsystematic risk of hospitality firms. Regression models were developed for hotel and restaurant firms, using unsystematic risk as the dependent variable and financial variables as independent variables. The major findings of this study indicate: 1) more profitable hospitality companies have less unsystematic risk, 2) reducing reliance on debt financing could reduce unsystematic risk, 3) the positive relationship between operating leverage and unsystematic risk, suggesting that decreasing operating leverage could mitigate the stock price volatility of hospitality firms, and 4) large hotel and restaurant firms have less unsystematic risk than small firms. This study should help management of hospitality firms incorporate effects of shareholder expectations into their operational decision making as an integral part of long-range financial planning.     

Do competitive strategy effects vary across hotel industry cycles?

We use metropolitan-level panel data of international tourist hotels (ITHs) in Taiwan to examine whether competitive pricing, quality and advertising effects differ across two business cycle phases of the Taiwanese hotel industry. Following Chen et al.’s (2014. Tourism Econ. 20 (3), 655) conclusion, the Taiwanese hotel industry over the period 2000 to 2010 is divided into two regimes: a high-growth regime (2007–2010) and a low-growth regime (2000–2002 and 2004–2006). We adopt the approach proposed by Enz et al. (2009. Cornell Hospitality Q. 50 (3), 325) on competitive strategies by computing the difference between the value of each hotel and its competitive set on merits of average daily rate, service quality and advertising expenditure. The empirical results indicate that: (1) Competitive pricing strategy has a positive influence on ITHs’ room revenue per available room (RevPar) in the high-growth regime (HGR). (2) Competitive pricing and service quality strategies are positively associated with RevPar in the low-growth regime (LGR). Moreover, service quality improvements relative to the competitive set lead to an increase in occupancy for ITHs in the LGR.     

Identification of the reactions of hotel managers to new competition

This paper arises out of research carried out recently on the impact of a new hotel on the other hotel businesses which are operating in the same market. To ascertain the possible reactions of hotel managers to new competition and the relative importance of alternative price and non-price strategies a postal survey of 250 three-and four-star graded hotels across the U.K. was undertaken. It was found that a change in published tariff rates is regarded as being relatively unimportant whilst sales promotion is given the highest priority. Disaggregation of the sample by hotel size and occupancy rates does not reveal any significant changes in the relative importance of possible strategies. While the survey indicates that both non-price and price competitive strategies are seen by managers as essentially complementary, nevertheless, price competition in the form of secret discounting of published room rates to mass market intermediaries (tour operators and travel agents) and corporations is particularly important. While price discounting is the ‘private’ face of hotel competition much more research is needed on both the ‘public’ and ‘private’ nature of competition in the hotel industry and how these inter-link.     

Money illusion and inflation management in tourism: The hotel industry case

Using regression analysis, this study examines the relationship between inflation, room rates, capacity utilization, and profitability in the hotel industry. The results show that room rates and nominal profits have been strongly related to inflation while occupancy rates and real profits have been independent of inflation over the twenty year period examined. Findings suggest general absence of money illusion implying effective inflation management policies.     

Market demand variations,room capacity,and optimal hotel room rates

This short note develops an optimal hotel room rate model and proposes optimal room rate strategies in both high and low seasons. We then examine our model with the data from tourist hotels in Taipei, Taiwan. The empirical results support our model's major predictions: (1) market demand variations significantly affect the difference between high season and low season optimal room rates; and (2) hotel's room capacity negatively affect the difference between high season and low season optimal room rates, which also means that fixed costs shall negatively affect the high season optimal room rate. This result contradicts with conventional wisdom.