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This study explores the short- and medium-term effects generated by the Milan Expo 2015, adopting a microeconomic approach. The focus is on the hospitality sector. The study embraces nine years, identifying three intervals: pre- (2011–2014), during- (2015) and post-Expo (2016–2019). The time span does not include the Covid-19 pandemic period, which started in 2020. The dataset is composed of daily data. Three research questions are explored. First, an overall evaluation of the short- and medium-term effects is performed. Second, the seasonal effects are measured. Finally, the impacts for different classes of hotels are considered. The findings are supportive for the legacy generated by the Milan Expo. The results confirm the ability of the Milan Expo to strengthen the leisure segment. Positive results have been observed for all classes of hotels, relevantly augmenting the real revenue per available room (RevPAR). Luxury hotels achieved the highest increase of RevPAR, while economy class hotels registered the highest percentage of increase of RevPAR.

This paper aims to investigate the links between daily review sentiment and the hotel performance measures of occupancy rate (OR), average daily rate (ADR) and revenue per available room (RevPAR).

The authors conducted review sentiment analyses in three moments (−1, −7 and −14 days) before arrival time using a data set of budget hotel performance and online reviews. The aim was to identify the effect of review sentiment in the budget hotel market on the three performance metrics.

Daily sentiment positively affects ADR and negatively affects OR and RevPAR, but only up to a certain threshold, after which the trend reverses. Prices increase with the level of sentiment, and high prices lead to low OR and RevPAR only when the sentiment scores are low. When they are high, they are associated with low rates, which lead to high OR and RevPAR.

Daily review sentiment can be viewed as a valuable “barometer” indicating a hotel’s daily operational effectiveness. Daily sentiment can thus allow hotel managers to adjust their dynamic pricing strategies more accurately.

This study identifies daily sentiment as an alternative predictor of hotel performance. In addition to the roles of valence and volume in the decision-making process, the authors found that daily review sentiment can be an “in-the-moment” factor with a high impact, encouraging consumers to complete their transactions. This study suggests that aggregated measures such as the total number of reviews and overall ratings of the hotel should not be the sole consideration in reputation management.

The purpose of this study is to investigate the effect of the COVID-19 pandemic on key performance metrics of accommodation properties by elaborating on the roles of business models (i.e. franchised, chain-managed and independent hotels, and the sharing economy) and state-level restrictions in the US.

The pandemic is considered a variable interference against the average daily rate, occupancy and revenue per available room, which permits the examination of the before and after effects of the pandemic. The panel data model is used to examine the effect of the recent pandemic on the accommodation sector in the USA.

The results showed that chain-managed hotels were the most adversely impacted by the COVID-19 pandemic, while independent hotels were the least adversely impacted. Interestingly, and consistent with emerging consumer needs suggested by spatial distance theory, the pandemic does not have significant negative effects on Airbnb. The adverse impact of the pandemic on hotels was exacerbated in more restrictive states, while Airbnb remained immune to regulatory differences.

This study addresses the dearth of research on the types, roles and efficacy of business models in the accommodation industry and makes important theoretical contributions to the study of business model resilience in the accommodation industry, leveraging the resource-based theory of the firm and spatial distance theory.

The findings of this study make a significant contribution to the extant literature on the resilience of business models in the accommodation industry and have important implications for hotels, Airbnb owners, accommodation brands and destination and health policymakers. They demonstrate that a lower level of corporate control and greater flexibility in brand and operational standards allow for a more effective response to business disruptions such as a global pandemic.

Using a video revealing unhygienic practices in Chinese five-star hotels as the case study, this study aims to understand the impact of service failure online exposure on hotel revenue performance in terms of seriousness, magnitude and duration, as well as to identify the hotel-characteristics and hotel-responsiveness factors that influence revenue recovery.

This study uses the actual Revenue per Available Room data of ten hotels involved in the incident and five different market segments during 2016–2019. Event study method is used to investigate the effect of online exposure on hotel revenue performance.

This study confirms the significant negative effect of online exposure and that hotels take nearly nine months to fully recover. The results indicate that hotel size, hotel age and response strategy play an important role in reducing negative impacts. Moreover, this study reveals the dynamic spillover effects of online exposure on different hotel market segments. These effects change from a competitive to a contagious effect with a decrease in class ratings.

Low-class hotel managers should take effective actions to avoid possible negative spillovers from others’ service failure incidents. Hotel managers could consider the synergy of different strategies rather than a single response strategy to minimize losses.

This study theoretically broadens knowledge about the negative impact of online exposure on Chinese hotel revenue. Additionally, the findings examine the dynamic spillover effects on hotels in different segments. Furthermore, they extend the existing findings on the negative impact of online public opinion crises.

本研究以一段揭示中国五星级酒店不卫生行为的视频为案例, 旨在了解网上曝光的服务失败事件在严重程度、规模和持续时间方面对酒店收入绩效的影响, 并确定影响收入恢复的酒店特征和酒店回应因素。

本研究使用了2016–2019年期间10家涉及酒店和5个不同的细分市场的实际每间可用房收入（RevPARs）数据。采用事件研究法（ESM）来研究网上曝光对酒店收入绩效的影响。

本研究证实了网上曝光的显著负面效应, 酒店需要近9个月的时间才能完全恢复。结果表明, 酒店规模、酒店年龄和回应策略在减少负面影响方面发挥了重要作用。此外, 本研究还揭示了在线曝光对不同酒店细分市场的动态溢出效应。这些效应随着酒店星级的下降而从竞争效应变为传染效应。

低星级酒店管理者应采取有效行动, 避免其他酒店的服务失败事件可能带来的负面溢出效应。酒店管理者可以考虑不同策略的协同作用, 而不是单一的回应策略来减少损失。

本研究从理论上拓宽了关于网上曝光对中国酒店收入绩效的负面影响的知识。与此同时, 本研究的结果考察了不同细分市场的酒店的动态溢出效应。此外, 还扩展了现有的关于网络舆情危机的负面影响的研究结果。

Este estudio utiliza los datos reales de ingresos por habitación disponible (RevPAR) de 10 hoteles implicados en el incidente y cinco segmentos de mercado diferentes durante 2016-2019. Se utiliza el método de estudio de sucesos (ESM) para investigar el efecto de la exposición en línea en el rendimiento de los ingresos de los hoteles.

Utilizando como caso de estudio un vídeo que revela prácticas antihigiénicas en hoteles chinos de cinco estrellas, este estudio pretende comprender el impacto de la exposición online de fallos en el servicio sobre el rendimiento de los ingresos hoteleros en términos de gravedad, magnitud y duración, así como identificar las características y los factores de respuesta del hotel que influyen en la recuperación de los ingresos.

Este estudio confirma el importante efecto negativo de la exposición online, tardando los hoteles casi nueve meses en recuperarse totalmente. Los resultados indican que el tamaño del hotel, su antigüedad y la estrategia de respuesta desempeñan un papel importante en la reducción del impacto negativo. Además, este estudio revela los efectos indirectos dinámicos de la exposición online en diferentes segmentos del mercado hotelero. Estos efectos cambian de un efecto competitivo a un efecto contagioso con una disminución de las calificaciones de la categoría o clase hotelera.

Los revenue managers de los hoteles de categoría baja deberían tomar medidas eficaces para evitar posibles repercusiones negativas de los fallos en el servicio de otros hoteles. Los directores de hotel podrían considerar la sinergia de diferentes estrategias en lugar de una única estrategia de respuesta para minimizar las pérdidas.

Este estudio amplía teóricamente los conocimientos sobre el impacto negativo de la exposición online en los ingresos de los hoteles chinos. Además, los resultados examinan los efectos indirectos dinámicos en hoteles de diferentes segmentos. Además, amplían los resultados existentes sobre el impacto negativo de las crisis de opinión pública online.

In this vein, this paper aims to provide empirical evidence on the following questions: Which expansion strategies offer better operational and economic performance? What effects does performance-related diversification have? How do other factors such as size, quality, service offered, location or seasonality interact with performance.

In this paper, the analysis of the effects of growth strategies and hotel attributes on performance is carried out with a sample of 255 hotels that operate internationally. Using panel data and quantile regression, this study evaluates the effect of expansion and diversification on the hotels’ performance.

From these findings, it appears that the equity strategy (own hotels) outperforms non-equity strategies (hotels under rental, franchise and management contract) at the operational level. However, the economic return of the property, both adjusted and unadjusted to risk, is lower under the property ownership strategy than under the franchise and management strategies because, in general, it requires a higher investment. Regarding diversification, the growth strategy based on related diversification in food and beverage services has a negative impact on performance, calling into question the synergies between the two businesses. However, an exception to this effect is seen among those hotels, mainly those in the Caribbean, that opt to provide all-inclusive services, since these hotels achieve better occupancy rates and more stable results.

This study has not taken into account the effect of hotel property revaluation on the performance of the ownership strategy, as there is no information on the historical average revaluation at the level of each individual hotel. This study has also been unable to include information regarding the level of competition and seasonality of sales.

This paper considers a wide number of factors that can influence the performance of hotels. Second, this is the only paper that studies the impact of growth strategies from the point of view of the hotel chain. Also, the sample considered uses data at the individual level on hotels and this research analyses not only operational performance but also economic performance.

The purpose of this study is to test the local impact of COVID-19 pandemic on hotel performance at the individual property level, and further examine the roles of hotel attributes and business mix in potentially moderating or intensifying the impact of a crisis.

Using a sample of 5,090 hotel properties in Texas, USA from January 2020 to December 2021, this study estimates a monthly hotel performance model to evaluate how the pandemic affected hotels’ operational performance based on revenue per available room.

Results show that a 10% increase in the monthly number of confirmed COVID-19 cases led to a 0.522% decrease in hotel performance. Also, a series of moderators were identified within the pandemic–performance relationship: the negative impact of the pandemic was more severe among higher-end hotels and newer hotels; urbanization and localization diseconomies prevailed during the pandemic; and there was a smaller negative effect of COVID-19 on high rated hotels in the category of economy hotels.

The moderators highlighted in this paper shed light on the heterogeneity of COVID-19’s effects on hotel operations. Findings enrich the hospitality literature by considering business resilience in relation to the pandemic.

The study has two objectives, first, to examine the effect of COVID-19 deaths and corruption on the government's policy responses, and second, to investigate the effect of COVID-19, corruption and government response on hotel performance, using the developmental system's framework of resilience theory.

The study utilizes hotel data from ten countries collected from 1st March 2020 to 28th February 2021. The data are analyzed using the panel regression analysis in E-views.

The study confirms that government policies direct impact the hotel performance. Specifically, economic support policies have a positive effect on hotel performance, while COVID-19 deaths and restrictions have a negative impact on hotels. The study also found a strong association between corruption and the level of restrictions that governments choose to implement. Therefore, for effective recovery, governments must be mindful of the context in which businesses operate and the effect of their policies on the hotel industry.

The strong correlation between COVID-19 deaths and RevPAR highlights the significance of understanding and addressing customers' risk perception to enhance the resilience of the hotel industry. The findings emphasize the importance of collaboration between the hotel industry and the government for effective crisis management and policymaking.

This study empirically examines how various policy responses and crisis levels impact hotel performance. It sheds light on why countries respond to crises differently and the effects of different policy responses on the hotel industry. The study has many implications for the industry stakeholders and policymakers.

The study aims to assess the relative impact of intellectual capital (IC) as opposed to tangible assets on profitability and employee performance in hotels in Serbia before and during the coronavirus disease 2019 (COVID-19) pandemic.

The current study was undertaken in 2019, the year before COVID-19, and 2020, the year of COVID-19's major impact. This study utilizes the Value-Added Intellectual Coefficient (VAIC) as a measure of efficient use of IC. Financial data were collected from 163 hotels in Serbia. Structural equation modeling (SEM) was used to test the proposed hypotheses.

The results revealed that IC was a relevant factor for both profitability and employee performance before and during the COVID-19. However, the study reveals a negative moderating effect of tangible capital efficiency (TCE), meaning that with the increase of TCE, the relationship between IC and performance becomes weaker.

The main limitation of the study is rooted in VAIC's ability to fully incorporate all elements of IC, leaving the relational capital out.

To achieve better performance, hotel management should direct resources more towards IC and less toward tangible assets, which implies doing more with less.

The results indicate the importance of IC in a period of crisis for the industry and economy that are not recognized as knowledge intensive. To the best of the authors' knowledge, no other study has attempted to assess the relative contribution of tangible assets and IC before and during the COVID-19 pandemic.

This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.

Using three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.

The models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.

This study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.

This study produced a reliable, accurate forecasting model considering risk and competitor behavior.

This paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.

This study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.

This research aims to answer two major research questions related to the COVID-19 crisis from a longitudinal approach: What is the revenue management (RM) role during the different periods subject to analysis? What are the RM strategies and measures implemented during this crisis in contrast with a non-crisis context? It also aims to propose an RM implementation model that provides a contingency plan to face future crises.

This qualitative study, following a longitudinal approach, analyses three round-table discussions with 11 internationally renowned experts during three key scenarios of the COVID-19 crisis: the lockdown period (from March to June 2020) and the following two summer seasons (the post-lockdown period): Post-lockdown I (the summer campaign, 2020) and Post-lockdown II (the summer campaign, 2021). Based on a deductive approach, thematic analysis is conducted using NVivo.

Further professionalisation of revenue managers, which has enabled the correct application of strategies and measures, highlighting the importance of not lowering prices, the flexibility of booking conditions, the development of other sources of income and the increase in the value of services, amongst others, are key factors in managing this crisis. The longitudinal analysis carried out in three different periods of this crisis shows how these measures have evolved and the contrast with RM application in a non-crisis context. The revenue manager's leadership and proactivity, the holistic organisation of RM marketing, commercial and sales departments and the quick adaptation of RM systems (RMSs) by modifying their algorithms are essential to reducing the impact of COVID-19 on the hospitality industry. This crisis has led the industry to rethink processes and strategies and to increase digitalisation. The proposed model, which considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context, is the cornerstone for developing a graded contingency plan to face future crises. This research sheds light on the widely discussed role of RM during this crisis.

This study has various limitations. First, the three round-table discussions were held online due to the health crisis, and the chosen webinar format may have biased the participants' answers due to its public nature. Second, the survey was carried out in Spanish. Despite the strong international profiles of the participants, cultural distortion may appear, suggesting that the research should possibly be extended to other cultural contexts in the future. Third, some of the participants were unable to attend all the round-table discussions due to their professional duties, so people with similar profiles were invited to the rest of the sessions.

The revenue manager's leadership and proactivity, the holistic organisation of RM marketing, commercial and sales departments and the quick adaptation of RMSs by modifying their algorithms are essential to reducing the impact of COVID-19 on the hospitality industry. This crisis has led the industry to rethink processes and strategies and to increase digitalisation. The proposed model, which considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context, is the cornerstone for developing a graded contingency plan to face future crises. This research sheds light on the widely discussed role of RM during this crisis.

This work contributes to the literature by providing a model that considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context. The novelty of this research is mainly found in the conducting of a deductive and longitudinal study considering previous research focussed on RM strategies applied during the COVID-19 crisis and supplementing it with new measures by applying qualitative techniques.