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 causality examination between demand uncertainty and hotel failure: A case study of international tourist hotels in Taiwan

The hotel business is highly sensitive to economic cycles, as the industry faces high frequency and high fluctuation of uncertainty over the demand for lodging services. Without a thorough consideration on the issue, hotels may undergo a business crisis. This research therefore investigates the influence of demand uncertainty on hotel failure by using the operation data of international tourist hotels in Taiwan during 1995–2008. The analysis applies two stages of estimation. The first stage employs a first-order autoregressive model, AR(1), to model lodging demand uncertainty. The second stage estimates the likelihood of hotels’ failure by using a logit model. The results are supportive to determine that the demand uncertainty causes hotel failures.     

Factors affecting hotel human resource demand in Taiwan

This study explores the factors affecting hotel human resource (HR) demand and focusing on the organizational, industrial and macroeconomic factors of the hospitality industry. A prediction model was built with eight independent variables and four dummy variables. Secondary data was collected via a governmental statistic database, and regression analysis was performed using the Generalized Least Squares (GLS) method. The results show that the HR demand of international tourist hotels is more likely to be affected by industrial factors and macroeconomic factors, while the HR demand of standard tourist hotels is less complex, and is mainly affected by organizational factors.     

Seasonal concentration of the hotel demand in Costa del Sol: A decomposition by nationalities

Costa del Sol is a mature Mediterranean destination in the South of Spain with a degree of seasonality that has shown little variation during the last 20 years. In this paper, we apply the decomposition of the Gini index of seasonal concentration by nationalities. The main outcome of this decomposition is the estimation of relative contributions to the overall seasonal concentration and marginal effects by nationalities. These measures can be of great help in the design of counter-seasonal policies. Our results suggest that planners interested in reducing seasonality may concentrate their efforts in consolidating markets with negative marginal effect over the index of concentration, like the British and Nordic ones. In addition, marketing targets may be focused primarily in the winter season for the markets with positive relative marginal effect.     

Novel deep learning approach for forecasting daily hotel demand with agglomeration effect

Increasing competition and adoption of revenue management practices in the hotel industry fuel the need for accurate forecasting to maximize profits and optimize operations. Considering the limitations of relevant research, this study focuses on the daily hotel demand with consideration of agglomeration effect, and proposes a novel deep learning-based model, namely, Deep Learning Model with Spatial and Temporal correlations. This model contributes to relevant research by introducing the agglomeration effect and integrating the attention mechanism and Bayesian optimization algorithm. Historical daily demand data of 210 hotels in Xiamen, China are used to verify the model performance. Results show that the proposed model is significantly better than the benchmarks. This study can help hotel managers improve revenue management through better matching potential demand to available capacity.     

Impact of financial/economic crisis on demand for hotel rooms in Hong Kong

The main objectives of this study are (1) to identify the factors that influence the demand for hotel rooms in Hong Kong and (2) to generate quarterly forecasts of that demand to assess the impact of the ongoing financial/economic crisis. The demand for four types of hotel room from the residents of nine major origin countries is considered, and forecasts are generated from the first quarter of 2009 to the fourth quarter of 2015. Econometric approaches are employed to calculate the demand elasticities and their corresponding confidence intervals, which are then used to generate interval demand predictions. The empirical results reveal that the most important factors in determining the demand for hotel rooms in Hong Kong are the economic conditions (measured by income level) in the origin markets, the price of the hotel rooms and the ‘word of mouth’ effect. Demand for High Tariff A and Medium Tariff hotel rooms is estimated to have experienced negative annual growth in 2009 due to the influence of the financial/economic crisis, whereas that for High Tariff B hotel rooms is thought to have grown in 2009 after having decreased in 2008. The demand for tourist guesthouse rooms is expected to be the least affected by the crisis. Overall demand is predicted to recover gradually from 2010 onwards.     

A simultaneous equations model of the hotel room supply and demand in Hong Kong

The purpose of the study is to identify the important factors that influence the hotel room supply and demand, and their overall impact on the Hong Kong hotel industry. Nineteen years of time series data are used and a simultaneous equations econometric model is employed. The overall goodness-of-fit of both demand and supply models is very high, suggesting high predictive power. Empirical results indicate that “hotel room price” and “tourist arrivals” are significant factors driving the demand for hotel rooms. In addition, “1990–91 recession” and “the 1997–98 Asian financial crisis” had a significant negative impact on the demand for hotel rooms in Hong Kong. At the same time, “hotel room quantity demanded”, “room occupancy rate”, “last period's room price”, “labor cost”, “last period's average price of Grade A private offices”, and “the Asian financial crisis” all have a significant impact on room price in the short run.     

Determinants of Tunisian hotel profitability: The role of managerial efficiency

Using financial data derived from 27 hotel companies operating in Tunisia, the paper reports an analysis of hotel profitability. Using Data Envelopment Analysis (DEA) and the Return On Assets (ROA) analysis managerial efficiency is shown to be important when holding geographical and operating contracts as constants. Nonetheless these two aspects have important implications for hotel profitability. Hotel size, level of indebtedness, exposure to crisis events and levels of managers' education are also influential. The implications for management tenure and optimal age of a hotel are discussed.     

Unemployment effects of economic crises on hotel and residential tourism destinations: The case of Spain

This paper analyses the effects of economic crises on tourism destinations from a city and regional point of view. The objective is to determine which kind of Spanish “Sun and Beach” tourism destinations, residential or hotel, has better weathered the most recent economic crisis in Spain, linked to the Global Financial Crisis of 2007/8. For this purpose, the authors have analysed the increases in the unemployment rates of a pool of 138 tourist destinations located on the Spanish Mediterranean coastline. The main finding of the paper is that during the crisis, residential destinations experienced a greater destruction of employment than hotel destinations. This result is consistent with previous literature that indicates a better economic performance of the hotel tourism development model.     

The effect of hotel chain affiliation on economic performance: The moderating role of tourist districts

This paper offers a pioneering analysis of the impact that integration in different types of hotel chains has on firm performance, and the moderating effect of the tourist destination in this relationship. Studies in the literature examine both size and location independently, without reconciling the apparently contradictory trends of globalization and conservation of the local base. The aim of the research is to analyze the comparative effects on tourism firms’ performance of belonging to different types of hotel chains while maintaining the advantages of location in a tourist destination. Based on a study of 292 Spanish hotels, the authors test the proposed hypotheses using hierarchical regression analysis. The results show the advantages of non-equity chains over independent establishments. The study also finds a positive moderating effect of location in a district on the results yielded by belonging to a chain, whatever organizational form it takes.     

Impact of location on profitability in the Spanish hotel sector

This paper analyzes the impact of market structure on hotel profitability in a sample of 8992 Spanish hotels in 2005–2011, using variables relating to the hotel and tourist destination in addition to structure–conduct–performance (SCP) and Chicago School frameworks simultaneously. The results show that profitability depends largely on the market structure and the level of demand of the tourist destination and we confirm the SCP proposals. Regarding characteristics of each hotel, there are unobservable characteristics which influence on profitability and we identify the existence of economies of scale.     

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.     

An expectancy theory model for hotel employee motivation

The purpose of this study is to apply expectancy theory to employee motivation in the hotel setting and confirm the validity of expectancy theory. The proposed expectancy theory model for motivation was tested using data from 289 hotel employees. The results show that a modified expectancy theory with five components (expectancy, extrinsic instrumentality, intrinsic instrumentality, extrinsic valence, and intrinsic valence) best explains the process of motivating hotel employees. This study also indicates that intrinsic motivation factors are more influential than extrinsic factors for hotel employees, suggesting that hotel managers need to focus more on intrinsic factors to better motivate employees.     

The characteristics of hotel websites and their implications for website effectiveness

Hotels are increasingly taking advantage of the Internet as a marketing tool able to provide direct contact with customers, but is the full potential of this tool being exploited? This article constructs and validates an instrument for the measurement of website characteristics and relates those characteristics to website performance, using structural equation modeling. The results indicate that small and medium size hotels in the Balearic Islands in Spain, a developed tourist destination, and in the South of Brazil, a developing destination, are using their websites as mass media tools; ignoring the potential for interactivity and one-to-one communication. It is suggested that hoteliers should adopt a more strategic approach to the Internet, preparing the ground for direct contact with customers.     

An assessment of adopting lean techniques in the construct of hotel supply chain

This paper assesses the adoption of lean techniques across the supply chains of hotels. Literature indicates a growing awareness of sustainability issues and lean adoption for value creation in the hospitality industry. However, there are limited exploratory studies that outline sustainability in terms of lean techniques in the context of a hotel supply chain. This paper addresses this gap using a structured study plan with specific research questions. To this end, a theoretical framework of lean assessment for value creation is first developed and a SIPOC-based construct of a hotel supply chain is used to identify and categorize hotel waste. An empirical study is then conducted to answer research questions and assess the extent of using lean techniques. Study results and the developed framework can be subsequently used by practitioners and researchers in conceptualization and assessment of lean adoption across the supply chains of hotels in different contexts.     

The impact of hotel CSR for strategic philanthropy on booking behavior and hotel performance during the COVID-19 pandemic

During the novel coronavirus (COVID-19) pandemic, some hotels have engaged in corporate social responsibility (CSR) activities to help overcome the crisis. Given that most existing research examines the impact of hotel CSR on a single stakeholder, how hotel CSR activities in a crisis are perceived by multiple stakeholders is unknown. Drawing on the concept of strategic philanthropy, this study examines the impact of hotel CSR activities during the pandemic, such as providing accommodations to healthcare workers, on hotel firms' market value and prospective hotel customers’ booking behavior. Adopting mixed-methods approach, this study finds negative impacts of hotel CSR for strategic philanthropy on firm market value and customer booking behavior. The study result indicates that the value of hotel CSR depends on the nature and environmental contexts of CSR. Specific theoretical and practical implications are provided.     

Modeling a green supply chain in the hotel industry: An evolutionary game theory approach

Despite extensive discussion of environmental management for hotels, little research has been done on the hotel industry’s green supply chain management. This study uses the evolutionary game approach to examine the generation of green behaviors and a green supply chain by hotels. Results show that most hotels do have an incentive mechanism for green growth; hotels with green behaviors are more profitable than those that are not. Furthermore, governments and hotel customers are critical in the “greening” of traditional hotel supply chains. The findings can assist governments in formulating effective environmental policies, provide a theoretical avenue in governing green practice, and guide stakeholders to understand the formation and evolution of green development in the hotel industry.     

An introduction to helpful forecasting methods for hotel revenue management

Revenue management is a key tool for hotel managers’ decision-making process. Cutting-edge revenue management systems have been developed to support managers’ decisions and all have as an essential component an accurate forecasting module. This paper aims to introduce new time series forecasting models to be considered as a tool for forecasting daily hotel occupancies. These models were developed in a state space modelling framework which is capable of tackling seasonal complexities such as multiple seasonal periods and non-integer seasonality. An empirical study was carried out to illustrate how a practitioner may apply and compare the performance of different models when forecasting a hotel’s daily occupancy. Results showed that the trigonometric model based on the new modelling framework generally outperformed the majority of the other models. These findings are potentially useful to the entire revenue management community facing the challenge of accurately forecasting a hotel’s daily demand.     

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.     

Gender and economic performance: Evidence from the Spanish hotel industry

Recent research suggests that the stereotype of underperformance attributed to female management may not be the result so much of poorer management skills as to using unsuitable comparative performance measures, as well as not taking into account structural characteristics that may be detrimental to the financial performance of companies managed by women. Gender differences with regards to conditions and business goals can result in female underperformance when performance measures relate to firm size, such as total sales, assets, or profits. When appropriate measures of relative performance are used, women and men are likely to prove equally effective business managers. Using longitudinal panel data on a large sample of Spanish hotel firms, there are few differences found when growth and profitability are compared by gender within a bivariate framework. What's more, when a regression model designed to control other performance determining factors is estimated, the results show better management by women than by men. As such, the research provides evidence that stereotypes of women as poor performers must be abolished, and the glass ceiling preventing entry of women into management positions shattered.