Economic policy uncertainty and corporate investment: Evidence from the U.S. hospitality industry

The study of how uncertainty affects hospitality firms’ decisions is gaining attention in recent years. We examine the effect of Economic Policy Uncertainty (EPU) on the investment policy of a sample of 305 hospitality companies in the U.S. for the period 2001–2018. Applying generalized methods of moments (GMM) technique, we find that investment policies in hospitality companies are negatively affected by EPU. Panel quantile estimations reveal that the effect of EPU on corporate investment is only relevant for companies in the lower quantile of capital expenditures ratio. Our paper also provides policy implications to related parties.     

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.     

A quantile regression analysis of tourism market growth effect on the hotel industry

This study used the quantile regression method to investigate how inbound tourism market growth proxied by the growth rate of total foreign tourist arrivals (GTA) affects the growth rate of sales (GS) and financial performance of hotel firms in Taiwan. The ordinary least squares estimation results of panel regression test revealed that GTA significantly affects GS, but has no significant effect on financial performance (proxied by hotel equity return). However, quantile regression tests revealed new and interesting results. GTA has a significant effect on GS at the different quantiles of GS. In comparison, although hotel equity return was not significantly related to GTA at the median and high quantiles, the effect of GTA on hotel equity return was statistically significant at the low quantiles. These results suggest that the effect of GTA on hotel equity return is asymmetric and state-dependent, conditional on the distributions of hotel equity return. The study further identified that GTA has a significant influence only on equity returns of hotels with a small size.     

International ecotourism and economic development in Central America and the Caribbean

Using annual data for the period 1995–2012 for seven Central American and Caribbean countries, six different open-economy growth models that allow for international (eco-) tourism are estimated using panel-data techniques. Two main results of the investigation are that international tourist arrivals per capita have a highly significant impact on real GDP per capita, and also that five different sustainability indicators interacted with international tourism have a positive impact on economic development. Furthermore, quantile regression shows that lower and medium income deciles of the population in particular benefit from international (eco-) tourism. The results are complemented by very similar findings for a set of 12 Central American and Caribbean countries using only two sustainability indicators, thus corroborating the validity of the specification. In addition, control variables are also generally significant and they feature the algebraic signs expected from economic theory.     

Price determinants of sharing economy based accommodation rental: A study of listings from 33 cities on Airbnb.com

The advent of the “sharing economy” challenges not only the business of hotel industry but also the theories and models based on the conventional hotel industry. A key dimension of the hospitality industry is pricing. The aim of this study is to identify the price determinants of sharing economy based accommodation offers in the digital marketplace. Specifically, a sample of 180,533 accommodation rental offers in 33 cities listed on Airbnb.com is investigated using ordinary least squares and quantile regression analysis. Twenty-five explanatory variables in five categories (host attributes, site and property attributes, amenities and services, rental rules, and online review ratings) are explored for the intricacies of the relationships between pricing and its determinants.     

Modelling growth and revenue for Swedish hotel establishments

This paper provides first estimates of the determinants of output growth of Swedish hotels based on establishment data. Growth of overnight stays is modelled as a function of initial size, age, type of accommodation, location and hotel prices measured as average revenues per guest nights. The empirical model accounts for potential endogeneity of hotel prices through the two-stage least absolute deviation model (2SLAD) and the instrumental variable quantile regression method. 2SLAD estimates show a positive and significant relationship between hotel prices and subsequent growth. The relationship is nonlinear with a decreasing impact as the price level increases. Growth of establishments is significantly higher for smaller and younger hotels. An important result is that city hotels, in comparison to tourist and other hotels – which are mainly located outside urban areas (in the mountains and at the sea) – exhibit significantly higher growth rates with a gap between 2.2 and 3.4 percentage points. Furthermore, the positive impact of hotel prices on growth is larger for high-growth establishments. Accommodation prices significantly decrease with the number of local competitors with a non-linear form and increase with size. City hotels and accommodation in the capital city have the highest revenues per guest night.     

An eclectic investigation of tourism multinationals: Evidence from Greece

This paper analyses determinants of profitability differences between subsidiaries of multinational enterprises (MNEs) and domestic enterprises (DMEs) in the tourism industry, using firm-level data. Previous studies focus on the hypothesis that ownership-specific advantages are a major determinant of performance differences. This paper explores performance issues using the eclectic paradigm configuration of tourism multinationals (NACE = 55), operating in Greece and a panel dataset for 95 firms and 10 years. A quantile regression technique is used to estimate the proposed model. Results indicate that, overall, MNEs out-perform their domestic competitors and are generally larger in terms of size. The study reveals, though, that when breaking MNEs into majority and minority owned, the latter perform better, as they make substantial use of local partners. These partners contribute with knowledge of the local market, which is an important aspect for the tourism industry. Finally, the authors discuss the conclusions and managerial implications of the findings.     

A demand-driven analysis of tourist accommodation price: A quantile regression of room bookings

Tourist accommodation expenditure is a widely investigated topic as it represents a major contribution to the total tourist expenditure. The identification of the determinant factors is commonly based on supply-driven applications while little research has been made on important travel characteristics. This paper proposes a demand-driven analysis of tourist accommodation price by focusing on data generated from room bookings. The investigation focuses on modeling the relationship between key travel characteristics and the price paid to book the accommodation. To accommodate the distributional characteristics of the expenditure variable, the analysis is based on the estimation of a quantile regression model. The findings support the econometric approach used and enable the elaboration of relevant managerial implications.     

Expanding our understanding of cruise visitors' expenditure at destinations: The role of spatial patterns,onshore visit choice and cruise category

Cruise tourism is an important and growing source of visitors to destinations. To expand our knowledge of this phenomenon, this study incorporates three new drivers into the analysis of the expenditure patterns of cruise passengers at destinations, namely, spatial intra-destination behavior (single node, multiple node, or hinterland), onshore visit choice (independent or guided), and cruise category (standard, premium, luxury, or exclusive). The study uses quantile regression to unearth the intricacies of the proposed relationships and a dataset that combines GPS tracking technologies and traditional surveys. Results suggest that the mobility pattern, onshore visit choice, and time spent at a destination of cruise visitors have significant effects on their expenditures. However, these effects vary along with the level of expenditure, whereas cruise category does not exert a clear effect on expenditure. The implications for destination management organizations are also discussed.     

You’re the Only One,or Simply the Best. Hotels differentiation,competition, agglomeration,and pricing

Drawing on competition, signalling and agglomeration perspectives, we investigate how vertical and horizontal differentiation influence price, and how hotel competition and agglomeration may moderate any such effects. We argue that vertical differentiation should include online reputation to complement category, and that hotel clustering can provide benefits for incumbents. Hypotheses are tested using quantile regression on a sample of 1870 hotels. In order to account for any service dimensions, an index of differentiation is estimated. We found that local competition and agglomeration moderates the relationship between differentiation and pricing. Furthermore, online reputation effects are more intense for low priced hotels. Indeed, when competition is intense, the positive effect of horizontal differentiation is lower for low priced hotels. Similarly, hotel clustering reinforces the impact of category on price, but it reduces the benefits of offering more services.     

Determining factors in the choice of prices of tourist rental accommodation. New evidence using the quantile regression approach

The disruption in destinations caused by the emergence of new forms of tourist distribution within the framework of the sharing economy gives rise to new challenges in terms of competitiveness, regulation and even investment. This article studies the determining factors that influence consumer decisions in the choice of rental accommodation using both ordinary least square models (OLS) and quantile regression (QR) estimation techniques. The results show the greater interpretative capacity of the QR, which reveals certain overlooked patterns of the relationship between some of the characteristics of the properties, the hosts or the socioeconomic environment and the price paid by the users. These results can facilitate decision making in the destinations by companies, society and the public sector.     

European vs. U.S. airlines: Performance comparison in a dynamic market

This study measures and compares the efficiency and productivity of European and U.S. airlines, over the period from 2001 to 2008. We measure efficiency by estimating a Bayesian distance frontier model subject to regularity constraints. Productivity estimates are also derived parametrically, based on the estimates of the distance frontier model. We estimate both a constrained (i.e. subject to regularity conditions) and an unconstrained model and we show the importance of imposing the monotonicity and curvature conditions on the distance function. The efficiency and productivity results based on the constrained model indicate that European airlines have slightly higher efficiency and productivity growth than U.S. airlines. A comparison based on the type of airlines indicates that low-cost airlines are on average more productive and efficient than full-service airlines. The decomposition of productivity growth and related market discussions are also provided.     

A comparison of the moderating effect of tourism reliance on the economic development for islands and other countries

Tourism is usually one of the top industries in most countries, especially islands. However, there is some question as to whether there is a negative potential impact if a country relies too much on tourism as a means of economic development to the detriment of other industries such as manufacturing and agriculture. The purpose of this paper is to examine the moderating effect of tourism reliance on the relationship between tourism development and economic development for regular countries and island economies, including “small island developing states” (SIDS). This study uses quantile regression on panel data from the WDI database from 1995 through 2014 for all of the countries that report tourism and economic data. The findings demonstrate that tourism reliance does have a moderating effect on the relationship between tourism development and economic development for all countries, but mainly at higher levels of economic development.     

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.     

Booking on-line or not: A decision rule approach

Internet technology has become a prominent distribution channel in the tourism industry. Any insight into decision making behavior in the online environment could be critical to business success. We explore the behavior of Iranian tourists in the online environment to specify how different factors affect tourists' decision to use online hotel booking websites. We use a Dominance-based rough set (DRS) in order to model tourists' choice. Besides the novelty of the model being used, this paper is one of the first to explore Iranian tourists' on-line behavior and it also deepens our general understanding of on-line decision making.     

A Microeconomics Analysis of the Per Diem Expenditure of British Travellers

The aim of this paper is to analyse factors that affect expenditure patterns of British travellers. It is the first study which focuses solely on this market. Using an original questionnaire, data are collected and a sample of 1178 is retained. To obtain robust estimates, the data are analysed using quantile regression technique. The study shows that income length of stay, employment status and types of accommodation used are important factors affecting per diem expenditure. The study contributes to the literature by investigating an additional dimension of demand determinant by analysing the effect of variables related to the home country. Transfer cost in the UK is found to be significant in determining total tourism expenditure abroad.     

A phenomenological approach of blogger’s view on cultural distance

This paper is intended to determine the influence of cultural distance on the international destination choices by tourists. We adopted a phenomenological approach and data were obtained from 17 bloggers with structured interview form and evaluated by content analysis. We evaluated the research data as three processes, as pre-travel, during travel and post-travel. We identified a tangible and an intangible preparation stage in the pre-travel process. We observed that an increase in cultural distance caused an increase in the destination obscurity and thus in the mental preparation. We found cultural experience, cultural acquisition and personal change themes during traveling. In the meantime, the increase in the geographic distance influences the cultural distance perception. We determined that destinations that are geographically remote (especially the Asian countries) are also culturally remote and interesting. We proposed a model that cultural distance is a moderator variable between travel motivation and destination choice.     

A Bayesian non-parametric stochastic frontier model

In this paper, we introduce a new Bayesian non-parametric stochastic frontier (SF) model that addresses the endogeneity problem and relaxes problematic assumptions regarding functional form, and distributional properties. The model can be seen as a competitor to DEA. We show how the model outperforms its parametric counterpart in all critical diagnostic tests. The application we use covers a unique sample of US hotels that operate within competitive clusters. We utilize the efficiency results obtained from this model to shed light on the extent to which performance spillover (i.e. agglomeration effects) may differ based on the varied characteristics of hotels within these clusters. We obtain interesting findings and discuss their implications for hotels contemplating future co-location strategies.     

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.