research topic about hospitality industry at pandemic

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Peer-reviewed

Research Article

COVID-19, government measures and hospitality industry performance

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Business Administration, Ono Academic College, Kiryat Ono, Israel

Roles Data curation, Investigation, Validation, Visualization, Writing – original draft, Writing – review & editing

Roles Investigation, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Management, Guilford Glazer Faculty of Business and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel

Roles Conceptualization, Investigation, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Economics and Accounting, Ruppin Academic Center, Emek Hefer, Israel

Roles Investigation, Methodology, Resources, Software, Writing – review & editing

Affiliation Department of Business Administration, Faculty of Management, University of Haifa, Haifa, Israel

• David Yechiam Aharon, 
• Arie Jacobi, 
• Eli Cohen, 
• Joseph Tzur, 
• Mahmoud Qadan

• Published: August 6, 2021
• https://doi.org/10.1371/journal.pone.0255819
• Peer Review
• Reader Comments

This study explores the interplay between public measures adopted by the U.S. government to combat COVID-19 and the performance of the American hospitality industry. The recent global pandemic is a natural experiment for exploring the role of government interventions and their direct impact on hospitality stock returns in the U.S. financial market. Overall, our findings show that most of the government interventions were associated with a negative response in the returns of the hospitality industry, a response that became more negative as the COVID-19 pandemic evolved. Similar patterns were also detected for other industries such as entertainment and transportation that are closely related to hospitality. The findings we document are fundamental to understanding the trends and fluctuations in hospitality stocks in the current crisis and any similar crisis in the future.

Citation: Aharon DY, Jacobi A, Cohen E, Tzur J, Qadan M (2021) COVID-19, government measures and hospitality industry performance. PLoS ONE 16(8): e0255819. https://doi.org/10.1371/journal.pone.0255819

Editor: Stefan Cristian Gherghina, The Bucharest University of Economic Studies, ROMANIA

Received: March 5, 2021; Accepted: July 23, 2021; Published: August 6, 2021

Copyright: © 2021 Aharon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The recent COVID-19 crisis may be one of the most influential and unprecedented events for firms, investors, policy makers and many other market participants. Along with the worldwide outbreak of the disease, it has also spilled over economically to major capital markets and sectors, thereby also adversely affecting the performance and stability of the hospitality industry.

The negative impact of the COVID-19 crisis is mainly affecting service-oriented sectors such as the hospitality industry. The latter functions as a powerful vehicle for economic growth and job creation all over the world. It is directly and indirectly responsible for regional development, numerous types of jobs, industries and sub-industries, and underpin many economic activities. According to the U.S. travel association ( https://www.ustravel.org/research/travel-facts-and-figures ), in 2019, travel alone generated $2.6 trillion in total economic output, supported 15.8 million American jobs, and accounted for 2.9% of the U.S. gross domestic product (GDP). These statistics highlight the economic importance of travel and tourism to the U.S. economy as well as to the global economy as a whole.

According to the World Health Organization (WHO), the COVID-19 pandemic was first reported in Wuhan, China on December 31, 2019. The pandemic spread quickly all over Asia, leaving behind it health and economic crises. On March 2, 2020, COVID-19 was first reported in the US and 10 days later Europe became the epicenter of the pandemic, both leading to even worse health and economic catastrophes. On June 1, 2020, there were over 6 million confirmed cases, and more than 370,000 confirmed deaths worldwide. Remarkably, as of May 20, 2021, the WHO reported that there had been 166,346,635 confirmed cases of COVID-19, including 3,449,117 deaths.

During the COVID-19 crisis, governments have taken different measures in the health, public and economic fields. These interventions were aimed at containing the spread of the virus in an attempt to minimize the adverse effects of the COVID-19 outbreak on both the health and economic realms. A brief review of such interventions reveals that governments imposed different actions such as canceling public gatherings, closing workplaces and schools, requiring social distancing, and also providing economic support, creating contact tracing and offering COVID-19 testing policies.

Using a unique dataset by Hale et al. [ 1 ] tracking the U.S. government’s interventions to the COVID-19 spread, we explore the response of U.S. hospitality stocks to different types of government interventions. In addition, we extend our examinations to additional firms operating in sectors closely related to the hospitality industry, given the possibility of a spillover effect from the hospitality industry to its close sub-industries.

We contribute to the literature in three areas. First, we add to the growing body of research dealing with the impact of epidemics and crises on asset pricing (e.g., [ 2 – 15 ]) by examining the immediate and short-term effect of the COVID-19 outbreak on the price evolution of stocks in the hospitality sector using the event study method. Second, we contribute to the literature dealing with the impact of government interventions and their reflection in asset prices during times of crisis (e.g., [ 11 , 16 – 22 ]) by sorting the intervention into economic (e.g., income support, debt contract relief) and non-economic (e.g., travel restrictions, school closings) measures and exploring their consequences. Overall, the results show that both economic and non-economic interventions imposed on the public can affect the prices of hospitality stocks. The magnitude of the short-term negative effect increases with the timeline of the evolution of the epidemic and the increased level of uncertainty.

Finally, we contribute to the literature dealing with changes in government policy and uncertainty in the stock market (e.g., [ 23 ]), by exploring the Granger-causality relationship between uncertainty due to infectious disease and variations in the hospitality stock returns. In addition, we examine how uncertainty reacts to government intervention. The results highlight that the hospitality business is very sensitive to economic uncertainty. When faced with adverse economic conditions, consumers typically tend to postpone using disposable income for travel and tourism in favor of more basic needs [ 24 ].

Our main empirical findings documented here show that the major challenge during the spread of COVID-19 was uncertainty. This uncertainty originated in two different, yet related, sources. The first source stemmed from the pandemic itself and the intensified ambiguity about the real consequences for the economy in terms of the time required for economic recovery, the rapidity of the spread of the infection and its lethality. This contention is confirmed using textual analysis of unique data from approximately 3,000 U.S. newspapers.

The second source was related to the uncertainty originating in the government interventions themselves. There was a great deal of ambiguity about the economic and non-economic consequences of government interventions. In addition, the public was uncertain about whether the government planned future interventions.

In this spirit, empirical studies have shown that increased ambiguity about government policy and spending has direct implications for the steady state of many macroeconomic variables such as debt, the GDP and consumption (e.g., [ 25 ]).

To summarize, during a crisis like a pandemic, the leading challenge a government faces is reducing both types of uncertainty. Doing so is vital for industries that are sensitive to such uncertainty such as the hospitality sector. Policy makers might be well-advised to impose measures with detailed transparency about their long-term plans to promote certainty. Ambiguity about current and future government spending (and stimulus packages) creates uncertainty in the stock market [ 23 ] and disrupts many macroeconomic variables such as debt, GDP and consumption (e.g., [ 25 ]). Our findings can also help policy makers fine-tune their aid policy and help tourism planners prepare better for possible future government interventions during subsequent epidemics such as COVID-19.

The remainder of this study is organized as follows. Section 2 presents the scientific background. Section 3 describes the data sources, our research methodology, and the measurement of the variables. Section 4 details the empirical findings, Section 5 discusses policy implications and future recommendations, while the last section provides a summary of the findings.

Literature review

The effects of government interventions during covid-19.

Zaremba et al. [ 22 ] examined the impact of government interventions on stock market liquidity in 49 countries during January-April 2020, and demonstrated that the effect of government interventions is limited in scale and scope. Specifically, they reported that the closures of workplaces and schools reduced liquidity levels in emerging markets, while COVID-19 information campaigns promoted trading activity. In a subsequent study, Zaremba et al. [ 26 ] explored the relationship between government policy responses to the COVID-19 pandemic and stock market volatility. They gathered data about seven non-pharmaceutical interventions from 67 countries and concluded that information campaigns and the cancellation of public events were the major accelerators of market volatility.

Kizys et al. [ 18 ] used 72 stock market indices from both developed and emerging economies and tested whether government policy responses to the COVID-19 pandemic could mitigate investors’ herding behavior. Overall, their results point to the herding phenomenon in international capital markets, but policy responses reduced such behavior. Ozili and Arun [ 27 ] tested the impact of government measures during the COVID-19 epidemic on the performance of leading market indices on four continents: UK, US, Japan and South Africa. They revealed that the increasing number of lockdown days, monetary policy decisions and international travel restrictions severely affected the level of general economic activity and the closing, opening, lowest and highest stock prices of major stock market indices. In contrast, the restrictions imposed on internal movement and increased fiscal policy spending had a positive impact on the level of economic activity.

More recently, Huang et al. [ 28 ] tested the effects of COVID-19 government policies on the hospitality labor market in the U.S. They found that closure policies were associated with a 20% - 30% reduction in non-salaried workers in the hospitality industry. Furthermore, the number of daily confirmed cases adversely affected the hospitality sector’s labor market.

Previous studies such as the work of Adda [ 16 ] explored the unintended consequences of economic activity on the spread of infections and assessed the efficiency of measures that limit interpersonal contacts in France. They found that policies reducing interpersonal contacts such as closing schools and public transportation significantly reduced the spread of disease, although they were not cost-effective. Pennathur et al. [ 20 ] explored the impact of the U.S. government interventions in response to the subprime financial crisis on the stockholder returns of banks, savings and loans firms, insurance companies, and REITs. They found that interventions reduced the wealth and increased the risks of financial institutions. Ding et al. [ 11 ] used an event study approach to examine the Chinese stock market’s response to the lockdown restrictions imposed on Hubei province in light of COVID-19. In general, this response was negative. Furthermore, firms that had a great deal of exposure to Hubei earned significantly lower returns following Hubei’s lockdown measures.

Chen et al. [ 17 ] examined the effect of the SARS epidemic on the stock prices of seven Taiwanese hotel stocks using an event-study approach. They reported that these firms suffered from steep declines in their earnings and stock prices during the SARS outbreak. Ru et al. [ 14 ] explored the cumulative abnormal returns during the COVID-19 epidemic for two groups of stock markets: countries that had experience with SARS, and countries that did not. They documented a stronger negative response in the markets in the experienced countries.

Using daily data about confirmed cases and deaths from the coronavirus and stock market returns from 64 countries, Ashraf [ 10 ] found that stock markets responded negatively to the growth in confirmed COVID-19 cases. Furthermore, there was a weak relationship with the number of deaths. Al-Awadhi et al. [ 9 ] explored companies included in the Hang Seng Index and Shanghai Stock Exchange Composite Index during the COVID-19 pandemic, and established a significant negative relationship between both the daily growth in total confirmed cases and the daily growth in total deaths caused by COVID-19. Recently, Goodell et al. [ 13 ] investigated the abnormal returns of 49 U.S. industry portfolios around COVID-19 news announcements. They documented that on February 26, 2020, when the first domestic case was confirmed in California, 15 industries reacted negatively to this news. The industries most sensitive to the news around February 26, 2020 were utilities, services and restaurants, hotels, and motels. Gerding et al. [ 12 ] examined stock market reactions to the COVID-19 outbreak around the world. They found that the market response was more aggressive in countries with a higher debt to GDP ratio. Finally, Ding et al. [ 29 ] evaluated the degree to which pre-crisis corporate conditions affected stock price behavior with respect to the COVID-19 epidemic. They reported that stock fluctuations were more moderate in firms that engaged in more CSR activities, and had more cash, less debt, and larger profits. They also indicated that stock prices were less exposed to the negative of COVID-19 if they had global supply chains and customer locations, and less entrenched executives. To summarize, we will add to the standing literature by investigating the impact of various U.S. government intervention measures on the tourism industry.

COVID-19’s impact on the hospitality industry

The COVID-19 pandemic had an unprecedented negative impact on the hospitality industry. According to a report published by the American Hotel and Lodging Association ( https://www.ahla.com/sites/default/files/recessiondepression_0.pdf ), the expected US hotels losses are nearly $83.7 ($51.2) billion in room revenue in 2020 (2021), compared with 2019, while job losses in 2020 (2021) are projected to be nearly 630,000 (546,000). In addition, about half of hotel markets, representing 72% of hotel rooms in the US, are still in a recession or depression. These numbers indicate that most of the hotel industry has a long road to recovery, especially when considering that an occupancy rate of 35% or lower makes it impossible for many hotels to stay open. In Fact, individual hotels and major operators are projecting occupancies below 20% ( https://hoteltechreport.com/news/tourism-industry-statistics#hotels ).

Similarly, the general state of the travel and tourism industry is also under a great threat. According to the Economic Impact Report by the World Travel and Tourism Council [ 30 ], prior to the pandemic, the travel and tourism sectors, both directly and indirectly, accounted for 1 in 4 of all new jobs created around the world, 10.6% of all jobs (334 million), and 10.4% of global GDP (US$9.2 trillion). In 2020, 62 million jobs were lost, representing a drop of 18.5% (62/334). The threat of job losses is continuing as many jobs are currently supported by government retention schemes and reduced hours, which without a full recovery in this sector, could be lost.

A careful mapping of the literature shows that several papers have reported supporting evidence for COVID-19’s adverse effect on the performance of the hospitality sector. Hao et al. [ 31 ] reviewed the overall impact of the pandemic on China’s hospitality industry—the country where the health crisis began. The industry witnessed a sharp decline in hotel occupancy rates and a loss of over US$9 billion in revenue. About 74% of the hotels in China were closed in January and February 2020 for an average period of 27 days. Furthermore, from January 14 to 28, the occupancy of the hotels dropped from around 70% to 8% and remained under 10% in the following 28 days. As a result, the hotel and tourism industry reduced their number of employees, leading to a significant drop in cash flow and revenue. Zheng et al. [ 32 ] studied the phenomenon of “travel fear” in China. They reported that perceptions about the severity of the threat and the susceptibility to it can cause “travel fear,” which leads to protective behaviors with regard to travel decisions. Furthermore, “travel fear” can evoke different strategies that increase people’s psychological resilience and adoption of cautious travel behaviors. Villace-Molinero et al. [ 33 ] explored perceptions about travel risks during the pandemic and proposed measures to improve traveler confidence based on the issue-attention cycle. Based on a survey conducted in 46 countries and a qualitative study in which 28 international hospitality experts were interviewed, the authors concluded that in a pandemic scenario, confidence in communications from the local government about personal safety and security are the main factors people consider when making travel decisions.

Lee et al. [ 34 ] tested the impact of COVID-19 on hospitality stock returns in China. They argue that the increasing uncertainty about the COVID-19 outbreak has made the Chinese stock market more turbulent and less predictable. Using a structural vector auto regression (SVAR) framework, they examined the link between the COVID-19 outbreak, macroeconomic fluctuations and hospitality stock returns in China. Their results hint that macroeconomic fluctuations and hospitality stock returns are significantly affected by shocks from the COVID-19 outbreak. Crespí-Cladera et al. [ 35 ] used a stress methodology to estimate the potential performance vulnerability for Spanish hospitality firms. They demonstrated that almost 25% of their sample firms are exposed to financial distress when operational income decreases 60%. They also found that the majority of such firms are generally small ones, which would also suffer from solvency problems. When hospitality firms’ revenues drop 80%, the predictions show that 32% of firms would be in financial distress. Rodríguez-Antón and Alonso-Almeida [ 36 ] reported that the performance of the hospitality industry in Spain has been severely damaged as a result of COVID-19. More specifically, they noted that in the first seven months in 2020, the total hotel overnight stays in Spain declined from 184.7 million in 2019 to nearly 46.4 million. In addition, the pandemic reduced the number of new hotel openings (−22.02%) and the number of employees hired (−30.94%) in March 2020. Finally, a recent study of Clark et al. [ 37 ] documented the negative impact of COVID-19 on the stock performance of hospitality firms. They estimated negative mean cumulative abnormal returns of −17.54% for 54 publicly traded hospitality firms from 23 different countries. Restricting their sample to the US or Japan yielded negative cumulative abnormal returns of −29.67% and −10.68%, respectively.

Other studies have examined the impact of previous pandemics, such as the severe acute respiratory syndrome (SARS), on the performance of the hospitality industry. Chien and Law [ 38 ] showed that the outbreak of SARS in March 2003 had a strong negative impact on the hotel business in Hong Kong. The occupancy rates of many hotels in Hong Kong fell to 10% or less in March and April 2003, which normally is the peak season. Similarly, Hendersom and Ng [ 39 ] reported statistics from the Singapore Tourism Board confirming the severity of the impact of SARS on the hospitality sector there. According to the report, the average hotel occupancy rate for the second quarter of 2003 was 21%, compared with 74.5% for the previous year, and average room rates dropped by 18.8%. In addition to this report, they also surveyed hotels in Singapore to estimate the economic loss resulting from SARS. They noted that in their own surveyed hotels the average occupancy rates were also relatively low, in the range of 27.7% to 42.3%.

Kim et al. [ 40 ] tested the effect of SARS on the Korean hotel industry. They examined six Korean hotels and reported that the occupancy rate dropped nearly 14% from February to July 2003. They argued that the reason seemed to be that inbound tourists saw Korea as an unsafe tourism destination within the territory of the SARS-affected Asian Pacific zone. Revenue per available room (RevPAR) during the three months from April to June was 215,849 won (US$180) in 2002, whereas it was 115,676 won (US$96) in 2003, a 100,173 won (US$83) difference. Finally, there was a 16% drop in profit margins from April through June in 2003 compared to the same period in 2002. The average rate per room also declined by 19% as hotels attempted to cope with the sharp decline in demand. Tew et al. [ 41 ] used a questionnaire designed to investigate, among other points, the impact of SARS on hotel performance in Canada. Respondents were asked to assess the impact that the SARS crisis had on their hotel’s performance. Over 82% of respondents reported that SARS had an extremely negative or very negative impact on their hotel’s performance. In addition, Tew et al. (2008) [ 41 ] also reported that the Niagara Falls region experienced a loss of over 122,000 room nights in the second quarter of 2003. This loss translated into a loss of $19 million in room revenue. Finally, Chen et al. [ 17 ] examined the effect of the SARS epidemic on Taiwanese hotel stock price movements using an event-study approach. They showed that for seven publicly traded hotel companies there were steep declines in earnings and stock prices during the SARS outbreak period. More specifically, they reported that in April 2003 hotel companies experienced drops in earnings in the range of −49.81% to −11.14%. They also showed that these drops worsened significantly when extending the period examined for two months (April–June, 2003), with reductions varying from −76.89% to −20.00%. Finally, they calculated the cumulative abnormal returns of stocks in this sector during 10 and 20-day windows from the day of the SARS outbreak. The negative returns they found were also robust using different types of models to estimate the abnormal returns.

Importantly, COVID-19 has not only directly affected the hospitality industry performance, but also created collateral damage that might indirectly harm it. The literature suggests several possible additional factors behind the poor performance of the hospitality industry that might delay its future recovery. These effects are evident in the labor force (Jung et al. [ 42 ]), its mental health (Yan et al. [ 43 ]), and the willingness to travel and the spreading of fake news (Alvarez-Risco et al. [ 44 ]).

To summarize, these studies show that in addition to the negative effect that government interventions usually have on financial markets, COVID-19 also had various detrimental effects on the hospitality industry. Therefore, combining these two pieces of evidence, we might expect that the impact of government interventions on the hospitality industry would also be negative.

Data and methodology

Sample construction and data sources.

Our sample consists of the daily log returns of stock portfolios consisting of firms operating in the hospitality industry in the following COMPUSTAT SIC codes: Retail‒eating places (5800‒5819), Restaurants, hotels, motels (5820‒5829), Eating and drinking places (5890‒5899), Hotels, other lodging places (7000‒7000), Hotels and motels (7010‒7019), Membership hotels and lodging (7040‒7049) and Services–linen (7213‒7213). We refer to these related industries collectively as the hospitality industry.

We use market prices as a proxy for the overall state of the hospitality industry as well as for the other related sectors. This approach might have limitations, albeit temporary ones, which stem from behavioral biases. Nevertheless, using market prices is still a prevalent method that reflects the present value and state of securities. Additionally, we retrieved data for the log returns of stocks in nine other related industries (Food Products, Candy & Soda, Beer & Liquor, Entertainment, Consumer Goods, Apparel, Personal Services, Transportation and Retail). All firms in each portfolio are traded on the NYSE, AMEX, and NASDAQ exchanges. The data are publicly available on Kenneth French’s website and cover the period of December 31, 2018 to April 30, 2020. They include 336 daily returns for each industry portfolio and a total sample of 3,360 daily observations ( http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html ). We also retrieved data from Kenneth R. French’s data library about the performance of a market portfolio (MARKET). According to French’s definition, the market portfolio consists of the value-weighted returns of all CRSP firms incorporated in the US and listed on the NYSE, AMEX, or NASDAQ (See also [ 45 ] for a complete description).

Table 1 as well as Fig 1 present information about the cumulative returns of the hospitality and other related industries for January 2020 to April 2020, compared to the general market’s performance. As can be seen, the overall negative performance is not limited to the hospitality industry. In fact, several other industries are associated with excess negative returns compared with the hospitality industry. Note too that the worst month for all of these industries was March 2020, when most of the interventions occurred. During this month negative returns abounded. Indeed, the hospitality industry lost about 45% of its cumulative market value. The recovery in the market value of the various sectors, including the hospitality industry, took place in April 2020. However, nearly all industries ended the period with a substantial decrease in their market value.

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A . The figure depicts the cumulative returns of the S&P 500, the hospitality industry and the indices of numerous related industries since the outbreak of COVID-19 in January 2020. “c,” “e” and “h” denote closures, economic and health measures, respectively.

https://doi.org/10.1371/journal.pone.0255819.g001

https://doi.org/10.1371/journal.pone.0255819.t001

Our empirical discussion also utilizes Baker et al.’s measure of uncertainty due to infectious diseases [ 46 ]. The data come from their Economic Policy Uncertainty website and are available since 1985 ( http://policyuncertainty.com/infectious_EMV.html ). In designing this index, Baker and colleagues created an index based on the frequency with which various terms appeared daily in approximately 3,000 US newspapers. They classified these articles into three categories: E: economic, economy, financial; M: stock market, equity, equities, Standard and Poors; and V: volatility, volatile, uncertain, uncertainty, risk, and risky. Finally, these articles must also mention one or more terms related to epidemic, pandemic, virus, flu, disease, coronavirus, MERS, SARS, Ebola, H5N1, or H1N1. The resulting counts were scaled by the count of all articles on the same day. Fig 2A and 2B plot the evolution of epidemic-based uncertainty. As can be seen, uncertainty skyrocketed upwards multiple times above the average. The maximum value reached was 112.93, recorded on March 15, 2020.

(A) The dotted line is a one-week moving average of the index. The figure indicates that starting from the last week of February 2020, pandemic-driven uncertainty skyrocketed to record values. The figure includes 7-day-a-week observations. (B) The solid bold red line is Baker et al.’s daily index of uncertainty due to infectious diseases [ 46 ]. This uncertainty measure considers the frequency of U.S. newspaper articles that include terms related to economy, risk, financial market, uncertainty and epidemic. The uncertainty index observations correspond with the trading days on the stock exchange. The correlation between this form of uncertainty and variations in returns is 0.46 (t-stat = 4.66). Overall, the message of the figure is that high levels of uncertainty do not bode well for a quick recovery in the hospitality sector.

https://doi.org/10.1371/journal.pone.0255819.g002

Fig 2A provides a combined snapshot of the uncertainty due to infectious diseases and the performance of the hospitality portfolio, NASDAQ and S&P500. The overall picture illustrates a clear inverse relationship. A high level of uncertainty is accompanied by a decrease in the hospitality returns (as well those of the market portfolios), and vice versa.

Event study

Event study methodology explores the response to a specific event by assessing whether it creates abnormal stock returns that can be attributed to new information released. Therefore, in using this method, our first step was determining the event of interest and defining the length of the event’s window. To do so, we collected the dates of the government responses to COVID-19 from Hale et al.’s database [ 1 ] (See the Oxford COVID-19 Government Response Tracker on https://covidtracker.bsg.ox.ac.uk/ ). This database is constructed from publicly available sources such as news articles and government press releases and briefings. We also identified March 19, 2020 as another significant date because it marked the day when President Trump signed a $100 billion economic aid package.

Table 2 presents the list of U.S. government interventions with a definition for each intervention variable. The responses appear chronologically to illustrate how the government’s actions evolved over the full period of COVID-19’s spread.

https://doi.org/10.1371/journal.pone.0255819.t002

Next, we defined the length of the event window in which we examined the behavior of the equity prices of stocks in the hospitality sector and those in related industries. In fact, there is no golden number for the length of the event window. On one hand, a longer window relying on a large number of daily returns may reveal more information. On the other hand, other events occurring during a long-time window might contaminate the results. Given the proximity of events, we focused on a relatively narrow timeframe to minimize the possibility of confounding events. We adopted this approach to isolate the impact of each intervention, and because the COVID-19 period was followed by many events apart from the interventions. In addition, using a long timeframe might increase the chances of contemporaneous and inter-temporal residual correlations that could result in underestimates of the standard errors [ 47 ]. Brown and Warner [ 48 , 49 ], as well as McWilliams and Siegel [ 50 ] argued that a long event window also reduces the power of the test statistics and leads to false interpretations. Therefore, we chose an event study that spans three days, that is, from t -1 to t +1 days, which should cover the impact of government interventions on equity indices.

The center of each event study (t 0 ) is the announcement day (henceforth, day zero). Using Hale et al.’s [ 1 ] database, we defined day zero as the first day on which the intervention was announced to the public. If the announcement was made on a day when the exchange was closed, we defined day zero to be the first day when the exchange was open again. For instance, if the intervention was publicly announced on Saturday or Sunday, day zero would be the following Monday.

The subsections provide a detailed explanation of how we measured the returns, expected returns and abnormal returns as well as additional information concerning government interventions.

Abnormal returns (AR)

The term in parentheses on the right-hand side of Eq ( 1 ) is the expected normal return. The error term is the industry-specific component or the unexpected return, which can be attributed to the new information released such as the intervention. We explored each point in time separately from the market performance.

We estimated the coefficients’ parameters in Eq ( 1 ) using a pre-event estimation period (December 31, 2018-December 30, 2019) consisting of 252 trading days before the outbreak of COVID-19, as on December 31, 2019, the WHO was informed of cases of pneumonia of an unknown cause in Wuhan City, China. Finally, we aggregated the abnormal returns (CAR) and computed the t-statistics, following Brown and Warner [ 49 ].

Causality tests

OLS and regression analysis

Lastly, after testing the potential relationship between hospitality stock returns and uncertainty, we explore the uncertainty levels around the interventions themselves. To do so, we employ OLS estimations, which link government interventions with uncertainty. Such examination will allow us to reveal whether government interventions induce uncertainty, fear and anxiety, which will be then translated to hospitality stock returns performance. To obtain heteroscedasticity and autocorrelation consistent covariance matrix estimates, we employed Newey and West’s [ 55 , 56 ] estimation method.

Empirical findings

Table 3 presents a summary of the effect of each measure on the hospitality industry and related industries sorted by the type of intervention. We present and discuss the findings chronologically to understand how the government’s actions evolved throughout the spread of COVID-19.

https://doi.org/10.1371/journal.pone.0255819.t003

In parallel, Fig 1 plots a comparison of the cumulative returns of the market portfolio (S&P 500), the hospitality equity portfolio, and other related industries relative to various event dates associated with COVID-19’s outbreak. The figure illustrates the high degree of co-movement between the hospitality and other related industries, and the shocks to these industries relative to the market portfolio.

As the table indicates, most of the events are associated with a significantly negative response to U.S. government interventions. The only exception is the aid package (e3), announced on March 19, 2020, which mostly had a significant positive effect.

As illustrated in Fig 1 , between January 2, 2020 and February 20, 2020, the cumulative returns of the hospitality industry portfolio (depicted in red) rose moderately, implying that the government’s earlier actions had no influence on the performance of hospitality companies. More specifically, the interventions of contact tracing (h3) and restricting international travel (c8) did not have any statistically significant effect on the hospitality industry’s performance and most of the related industries. One explanation for this result might be the common belief in the early stages of the COVID-19 pandemic that it would not spread to the U.S. Naturally, people were still optimistic that COVID-19 was just another form of the flu that would have a minor effect on the economy. Apart from the explanation for this relatively passive market response coming from the fact that this date was part of the early stage of the outbreak, many may have believed the claim of China’s Foreign Ministry on the very same day that the U.S. government was reacting inappropriately to the outbreak and spreading fear by enforcing travel restrictions.

From this point in time, which we can call the realization period, the U.S. engaged in more frequent and extensive interventions, underscoring the severity of COVID-19. In fact, the period from February 21 to March 18 is characterized by a sharp decline in the hospitality industry’s performance as well as on other related industries. It was during this period that a series of interventions were imposed that also had an increasingly negative impact on the hospitality industry and the economy as a whole. During this period of time, even the economic intervention of debt/contract relief (e2), which postponed debt payments, had a negative effect (CAR = ‒5.36%) on the hospitality industry and also for the food (‒3.396%) and entertainment (‒2.149%) industries. These findings raise the possibility that the market was overwhelmed by negative sentiment. However, it may also reflect that the expectations about economic aid and substantial government support were much more meaningful. As evident in its cumulative negative returns, the hospitality industry regarded the announcements about debt/contract relief (e2) as insufficient, especially, due to the opinion that the hospitality sector would be the first to be hurt and the last to recover. In addition, according to the Oxford database, the debt/contract relief intervention in the U.S. provided only limited relief because it just postponed debt payments with no clear indication about real economic recovery, or any guidance about plans for the long term. When we delved deeper, we also reveal that February 26, 2020 was a significant milestone. It was the date on which the first U.S. coronavirus case of unknown origin was documented, which possibly induced negative response.

The next intervention of the U.S. government occurred in the health field and involved the announcement about a COVID-19 testing policy. The policy sets the criteria for who is to be tested for COVID-19. Intuitively, such a measure should be interpreted as good news. However, the overall response of the hospitality industry to the U.S. government’s testing policy intervention (h2) was negative (CAR = ‒4.195%). As for the related industries, the findings show mainly insignificant negative responses on the event date. The only exceptions are entertainment (‒3.810%) and transportation (‒3.092%). One explanation for this counterintuitive outcome might be that testing was offered only to those who had apparent symptoms and met specific conditions. Therefore, the industry regarded this as a minor and insufficient step in stopping the pandemic.

Several days afterwards, on Monday, March 1, 2020, the canceling of public events (c3) was imposed. The results indicate a clear negative effect on the hospitality industry’s performance; the cumulative abnormal returns (‒3.394%) were negative and statistically significant. Actually, in most of the industries, there were statistically significant and consistently negative abnormal returns. These findings highlight the powerful effect of cancelling public events on this industry, which may be a main source of the hospitality companies’ income.

This major negative response may also be a result of two additional events that occurred on the same weekend when the stock market was closed. The first event was the official record of the first coronavirus death in the U.S., and the second was an extension of the travel restrictions to include Italy and South Korea. These events probably intensified the negative market response. Apparently, now, the market starts to comprehend that the coronavirus is here to stay, and is far from being a trivial episode. In addition, canceling public events is a real business obstacle, and with the overall comprehension of the new challenging and unclear business activity, it might explain the overall negative response.

A quick glance at Fig 2A and 2B supports this notion. The figures show that the measure of COVID-induced economic uncertainty in Baker et al.’s index [ 46 ] started to deviate from the mean values observed prior this period implying that the media and newspapers devoted extensive attention to the pandemic and to its economic consequence. In this spirit, prior works have documented that media-driven pessimism–fueled by the outbreak of a pandemic–has a remarkable impact on stocks exposed to intense media coverage (e.g., [ 57 ]).

From this point forward, the U.S. engaged in more frequent and severe interventions. The findings show the clear negative response of both the hospitality sector and most of its closely related industries to these announcements. On March 5 and March 11, 2020, the closure interventions were extended and included new restrictions such as school closings (c1) and restrictions on gatherings (c4). The results in Table 3 demonstrate an evident adverse impact that was much more aggressive in terms of its magnitude. Specifically, for the hospitality industry, the abnormal returns in the wake of school closings were ‒3.786%, while restrictions on gatherings had a total negative effect of ‒5.550%. Note that on the evening of March 11, 2020, President Trump expanded the travel restrictions on foreign travelers, banning entry for the next 30 days from 26 countries in Europe except for Ireland and the United Kingdom. This announcement probably intensified the negative market reaction on March 12, 2020. The negative market reaction was also reflected in the significant cumulative abnormal returns for the hospitality industry (‒10.490%), and for the entertainment and personal services industries (‒14.561% and ‒8.879%, respectively).

The next intervention (mixed (1)) was an even more significant one, given that it involved several measures of different types. The mixed (1) intervention involved three events: domestic-travel restrictions (c7) on local movement between cities and regions, stay at home requirements (c6) and public information campaigns (h1) to raise awareness of the coronavirus. These steps were publicly announced between Saturday, March 14, 2020 and Monday, March 16, 2020. As the reported results in Table 3 illustrate, the combined effect of these interventions had a particularly strong impact on the hospitality industry’s performance (CAR = ‒21.98%), indicating the severe effects of the stay at home and public transportation restrictions which also spilled over to the entertainment (CAR = ‒16.29%) and apparel (CAR = ‒11.94%) industries.

On March 17, 2020, the closing of public transportation (c5) was the most significant event affecting the stock prices of the hospitality industry. The market value of the hospitality industry plunged almost 29% in three days (CAR = ‒28.72%), while the entertainment industry lost almost one-third of its market value in just three days (CAR = ‒30.59%). The record level of uncertainty due to the pandemic observed on this day appears in Fig 2A and reflects the tense atmosphere in the economy.

There are two possible explanations for this clearly significant tendency for negative returns following the government’s interventions, rooted in two different, but somewhat related, reasons. The first is the ambiguity about the government’s future fiscal steps that increased the uncertainty in the stock market [ 23 ]. The public finance literature has established that frequent changes in government policy may have direct implications for the stability of macroeconomic variables such as GDP, consumption and debt (e.g., [ 25 ]). The second reason is related to the uncertainty surrounding the pandemic itself and the unclear picture in its initial stages. This uncertainty includes the ambiguity about the real consequences for the economy, the time required for economic recovery, the rapidity of the spread of the infection and its lethality. All of these factors offset the impact of the interventions, or at least postponed their immediate effect until a bit later.

Another set of several interventions imposed together are described in the mixed (2) interventions in Table 3 . The mixed (2) intervention involved two events. On March 19, the government announced a new restriction that required all but essential workplaces to close and people to work from home if they could (c2). In addition, on Wednesday evening, March 18, 2020 when the exchange was closed, President Trump signed a $100 billion coronavirus emergency aid package, which included provisions for emergency paid leave for workers as well as free testing (e3). Table 3 shows that the good news about the assistance package announced on March 18 during the evening overcame the negative news of workplace closures. This result is both interesting and important given that according to the American Hotel and Lodging Association, job losses in the industry are expected to be extensive. In 2020, job loss was projected to be nearly 630,000, while in 2021 job loss were still expected to be around 546,000. Given that about half of hotel markets, representing 72% of hotel rooms in the US, are still in a recession or depression, it seems that providing economic aid might help calm the adverse effect of the expected job losses and the negative impact of imposed closures. Finally, the economic assistance had a major positive impact not only on the hospitality industry but also on several other industries such as entertainment, apparel and retail (CAR = +9.292%, +5.147% and 5.432%, respectively).

Indeed, the announcement about closing workplaces probably was expected, given all of the former restrictions, especially after the stay at home requirement made only three days before. Note that the aid package (e3) was a turning point in the behavior of the hospitality industry performance. It ended the one-month period of decline and started a positive upward trend that continued, though with fluctuations, through April 30, 2020, when the cumulative returns of the hospitality industry portfolio matched the cumulative returns of the S&P 500 index (see Fig 1 ).

Lastly, and in line with the Keynesian theory that countercyclical fiscal policy actions such as lower taxes or more fiscal spending under adverse economic conditions may help the economy recover (e.g., [ 58 ]), on Friday, March 27, the U.S. government announced a new intervention of income support. The aim of this stimulus was to cover the salaries or provide direct cash payments to people who had lost their jobs or could not work (e1). It also included payments to firms if explicitly linked to payroll or salaries. It was the most substantial stimulus package in U.S. history, and included payments of up to $1,200 for individuals or $2,400 for married couples. Parents also received $500 for each qualifying child. In spite of these generous fiscal steps, the results in Table 3 show a decline in the hospitality performance on the event date. This negative response is probably because this package of income support included payments to firms if explicitly linked to payroll or salaries but did not compensate the hospitality industry for its massive loss of revenues. In addition to the results reported above, additional findings for different time windows are available in the S1 Appendix . The results remained similar.

In the next subsection, we examine the impact of pandemic-driven uncertainty developed by Baker et al. on the price variations in the hospitality sector [ 46 ].

Causality test results

Table 4 reports the Granger-causality test results about the causal relationship between uncertainty due to infectious disease and variations in the hospitality stock portfolio. We follow the literature and use the squared returns as a proxy for price variations (e.g., [ 59 ]). The table lists the F-statistics of the Granger-causality test. For robustness, we set the lag-length of the model using the Schwarz Bayesian information criterion and run the Granger procedure for five different order lags to gain insights into the dynamic relationship between the two variables.

https://doi.org/10.1371/journal.pone.0255819.t004

The results, illustrated in Table 4 , reports relatively large F-statistic values which indicates a major rejection of the null hypothesizes that uncertainty does not Granger-cause the variations in returns. In other words, the results suggest that the uncertainty driven by the COVID-19 pandemic is a strong driver of the variations taking place in the equities of hospitality firms. This result is in line with the view that the intensity of news and media coverage contributes to the variability of the stock market (e.g., [ 60 ]).

Table 4 illustrates the results of the test conducted on the data between December 31, 2018 and April 30, 2020. The results reported here are straightforward and indicate that this type of uncertainty drives price fluctuations in hospitality as well as other closely related industries. In line with a battery of studies documenting the link between the stage of the outbreak and equity returns (e.g., [ 10 ]), our results go one further step. They confirm that the most significant factor during pandemics, particularly for the hospitality industry, is uncertainty.

It is also worth noting that a possible source of the high levels of uncertainty might be the strong government interventions and the frequency of the interventions themselves. Pastor and Veronesi [ 23 ] presented a general-equilibrium model according to which changes in government policy create two types of uncertainty: impact uncertainty and political uncertainty. The former is the uncertain impact a particular policy will have on the profitability of firms. The latter is the general uncertainty resulting from changes in policy. In equilibrium, these types of uncertainty lead to increased volatility when the government changes its policy.

The results in Table 5 lend support to this contention. We examined the average values of uncertainty on the day of and the day following government intervention. For robustness, we utilized three different proxies for uncertainty, and they include: the CBOE S&P 500 volatility index VIX, the pandemic-driven uncertainty developed by Baker et al. [ 46 ] and the squared returns of the hospitality sector. Overall, the picture emerged in Table 5 indicates that intervention days as well as the day following were associated with increased uncertainty. Therefore, one of our main conclusions is that governments should be transparent about their future actions and interventions regarding the hospitality industry.

https://doi.org/10.1371/journal.pone.0255819.t005

Furthermore, decision makers and businesses operators in the hospitality industry should make their best efforts to increase their transparency and make their transactions with consumers as comfortable as possible. Reducing the degree of uncertainty is a key element in rebuilding the hospitality industry and making government actions efficient, with minimum financial and economic damage.

Policy implications and recommendations

Our findings have important implications and suggestions for the hospitality industry managers, investors exposed to this industry, and policy makers at both the firm and state levels. We demonstrated that the impact of COVID-19, as well as government interventions, is not limited to the hospitality industry alone, but also affects other industries related to it. However, as a sector that relies on people’s disposable income, the hospitality industry is particularly sensitive to economic upheaval. When the economic situation is uncertain, consumers typically tend to put off their consumption of hospitality in favor of more basic products. Furthermore, the sudden, widespread outbreak of COVID-19 caught everyone by surprise.

Governments groped in the dark in an effort to find ways of dealing with the situation. Their frequent changes in policy stoked the uncertainty surrounding the situation. One method that governments can use to reduce uncertainty and increase public confidence is transparency. Since time is crucial in managing a crisis, government policies should be announced publicly as soon as possible. To deal with the uncertainty related to the spread of the virus itself, governments must continuously provide as much information as possible about the evolution of the pandemic. For example, they can use campaigns, create special pandemic or crisis management websites, and provide contacts and information—all aimed at giving the public the maximum sense of control.

Regarding the second type of uncertainty, which relates to government policy, governments should be transparent about the types of interventions they plan to use, how they expect to implement them and their planned duration. Governments should publicize their plans for dealing with economic and non-economic issues, indicating how they will affect individuals, investors, employees, employers and business owners. Moreover, since one of the main concerns is loss of revenue and the instability of the economy, the government should be pro-active and set up vehicles such as a national savings fund to remove any ambiguity about the state’s financial ability to manage the crisis. In addition, it should announce the availability of income aid, debt payment relief and fiscal spending that is immediate, widespread and generous. In addition, the public should be informed precisely how the government plans to finance this spending (imposing taxes, increasing deficits and debt ceilings, etc.). Transparent policies may mitigate the uncertainty in the short term and allay fears about the economy.

Implications for investing

Our findings imply that investors, funds and portfolios managers should account for possible extreme events such as pandemics followed by governmental interventions, which may spillover to other industries and capital markets.

Investors can improve their investment tactics by paying more attention to the characteristics of the economic measures imposed to deal with infectious diseases and their resulting uncertainty, knowing now that they will have a negative impact on the performance of the hospitality industry. Hence, investors exposed to the hospitality industry should keep an eye on changes in Baker and colleagues’ index of uncertainty due to infectious diseases. By doing so, they can safeguard the value of their investments using techniques such as short positions, derivatives, forwards or any financial instruments that have a weak or negative correlation with the performance of the hospitality and tourism sectors.

In the midst of COVID-19 and its economic implications, several opportunities may arise in other related industries, as evident in the unprecedented growth in their equity prices. According to AHLA’s report, the hotel occupancy in the U.S. will increase to 52% in 2021, and to 61% in 2022, compared with 66% level in 2018–2019 ( https://www.ahla.com/sites/default/files/2021_state_of_the_industry_0.pdf ). In addition, the report projects that U.S. restaurant sales are about to increase to 11% in 2021 to $731.5 billion, but still far behind 2019’s $864.3 billion. In this respect, future studies can examine the performance of hospitality and related industries before, during and after the COVID-19.

Implications for policy making for the hospitality sector

While governments around the globe, including the U.S., have started to make interventions, recovery back to pre-crisis levels may not be immediate, but will take a longer time. During this time, owners and businesses operators in the hospitality industry can prepare for future activity and the post COVID-19 tourism environment. In addition, stakeholders should adjust their businesses for both the short and long terms and minimize the sensitivity of their businesses to the possibility of future government restrictions even after reopening the hospitality economy. They also have to consider innovations in their businesses in terms of social distancing and keeping a sanitized environment. Owners and hospitality service-related vendors such as airline companies, cruise companies and multinational hotel chains must cooperate with each other, and enforce strict protocols for the handling and preparing of food. Travel agencies can encourage people to travel by offering flexible rebooking options and free health insurance that covers COVID-19 during the trip. Fast COVID-19 tests before departure and after landing will help airline companies and airport authorities restore confidence in the safety of travel, which will encourage tourism and prevent infection in public areas.

For national policy makers, our results highlight the devastating response of the capital market to interventions, particularly closures. The main factor hurting the hospitality sector and other related industries is uncertainty. Indeed, at this point, there is still great uncertainty about the rapidity of the spread of the disease and its lethality, whether a second wave of infection will occur, the time required to develop and distribute vaccines to the public, the real effectiveness and outcomes of social distancing and whether government policy responses and interventions will become permanent.

Therefore, governments should try to be as transparent as possible in devising a clear plan and definitive goals for the near and far future. They should do so by working with the other state economic authorities in order to minimize the negative impact of uncertainty. This approach is crucial because the cumulative evidence indicates that uncertainty reduces economic growth and firms postpone investment and hiring [ 46 ]. Furthermore, unclear, inconsistent government policy creates uncertainty that commands an equity risk premium, and may, in turn, affect the weighted average cost of capital, which ultimately affects firms’ innovation activities (e.g., [ 61 ]).

Our results also underscore the adverse effect that closures have on the performance of the hospitality industry. Therefore, governments should be extremely transparent before enacting such regulations. They should also follow them with economic support to reduce not just the negative effect of the closures, but also the negative effect of the uncertainty about when the restrictions will be lifted. An important recommendation derived from our results is providing financial assistance alongside regulations that close workplaces. As our results hint, it is a key condition for providing significant relief from the detrimental impact of labor market closures. Since the labor market is an important component of the soundness and growth of the economy, especially in the hospitality industry, governments should consider mitigating the negative impact of closures with financial measures that support employees, employers and the economy. In this respect, it is important to consider the long-term implications of the COVID-19 crisis. Beyond their immediate impact, the measures put in place today will shape the future of hospitality. This outbreak is an opportunity for governments and businesses to develop new concepts of hospitality by reducing costs, utilizing green and clean energy and implementing new health protocols for safe travel. Governments should encourage the digital, low carbon, structural transitions needed to build a stronger, more sustainable and resilient hospitality economy.

Finally, scholars can use our findings to explain why the performance of the hospitality industry deviated so much from that of other service-oriented and economic sectors. They can incorporate the uncertainty resulting from infectious diseases and interventions into their pricing kernels.

To conclude, the massive fiscal stimulus adopted during the subprime crisis of 2008 showed that the intervention of government as well as other monetary and economic authorities was crucial in halting the financial deterioration of the finance sector and, consequently, the real economy (e.g., [ 61 , 62 ]). Thus, the outcomes could have been even more destructive without the quick, massive, generous government measures. While these measures did not have an immediate positive effect because of the great uncertainty and public panic at that point, they might have had a lagged effect. Fig 2B depicts the gradual effect following the economic steps during the pandemic outbreak. Nevertheless, stimulus plans are controversial. Politicians must decide whether they want to stimulate the economy by increasing debt-financed spending, increasing balanced-budget spending financed through higher taxes in the future or providing debt-financed tax cuts.

Summary and conclusions

This study explored the effects of interventions by the U.S. government on the market value and stock returns of the hospitality sector and industries closely related to it. We used an event study methodology to explore the impact of four types of interventions: economic, health, closures and mixed types of interventions.

Closures had a consistently negative effect on the hospitality industry. The closing of public transportation (e5), domestic travel restrictions (e7) and stay at home requirements (e6) had a strong negative impact on the hospitality industry. Such interventions had a direct negative impact on the revenues of this industry.

The only intervention that had a significantly positive effect on the hospitality industry was the $100 billion COVID-19 aid package, signed by President Trump on the evening of March 18, 2020. Contrary to what we might expect, the economic interventions of income support (e1) and debt/contract relief (e2) had a significantly negative effect on the hospitality industry.

Possible explanations for these results might be the uncertainty originated in the unclear and inconsistent government policy itself. The latter is viewed in the public finance literature as a source of ambiguity with a direct effect on the stability of key macroeconomic variables. In addition, the hospitality sector expected more meaningful and substantial government support, especially, due to the expectation that this industry would have a late recovery. Similarly, the package provided payments to firms that were explicitly linked to payroll or salaries but did not compensate companies in the hospitality sector or closely related industries for their massive loss of revenue. Furthermore, the resulting uncertainty driven by the pandemic in terms of the spread of the pandemic, its lethality, time required to develop vaccines, unknown economic implications, etc., played a major role in the price fluctuations of hospitality equities. In periods of uncertainty, firms always invest less and hire fewer people. Similarly, people tend to save money rather than spend it. Accordingly, such unprecedented uncertainty was translated into a sharp decline in the value of hospitality firms.

These conclusions are relevant to both regulators and the leaders of the hospitality industry. Government policy is not just about choosing a deficit level, but also about influencing public expectations. Hence, leaders of the hospitality sector must prompt regulators to develop clear policies aimed at reducing economic uncertainty and persuade them that a gradual lifting of the closures will allow the hospitality industry to recover.

Supporting information

S1 appendix. additional results for different time windows..

https://doi.org/10.1371/journal.pone.0255819.s001

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Hospitality and COVID-19: How long until ‘no vacancy’ for US hotels?

COVID-19 has affected every sector across the globe, and the hotel industry is among the hardest hit. Our research suggests that recovery to pre-COVID-19 levels could take until 2023—or later. Investors are providing similar views of hotel companies’ prospects, as seen in the underperformance of US lodging real estate investment trusts (REITs). Like so many industries, hospitality will also see both subtle and substantial shifts in the post-pandemic era. Some are already apparent today.

In this article, we will examine a set of recovery scenarios for US hotels, including differing return and recovery timelines for hotels ranging from luxury to economy segment. On the consumer side, we will look at what guests say will make them feel safe when traveling, including contactless check-ins and check-outs, and an added emphasis on hygiene. And we will review the factors affecting the initial return of travel in the domestic business and leisure segments.

Today: High vacancy

COVID-19 is a challenge to both our lives and livelihoods. The crisis is unprecedented and moving quickly, yet still deeply uncertain.

To put parameters around that uncertainty, our colleagues created nine potential scenarios for recovery of national economies , based on the extent to which the pandemic spread is controlled, as well as the effectiveness of economic policies intended to counter the effects of quarantine (Exhibit 1).

Our recent survey  of 2,000 global business executives found that scenarios A3 and A1 are seen as most likely. Each scenario has distinct implications. A3 projects GDP recovery as early as 2021. The more conservative A1 projects a delay in GDP recovery until 2023.

On the hotel front, we analyzed the long-term historical relationship between industry performance and economic data. There is variation across chain scales (from luxury to economy), but we found the strongest relationship between changes in revenue per available room (RevPAR) and the unemployment rate. Based on this relationship, we used the unemployment rate projections from our colleagues to set a baseline for hotel performance. We then adjusted the baseline to account for additional impacts of COVID-19, factoring in the likely length of shelter-in-place restrictions, changes in company travel policies, consumer sentiment and willingness to travel, and structural changes to demand, such as videoconferences instead of in-person events.

In scenario A3, the virus’s spread is contained, and the economy recovers slowly, revenue per available hotel room (RevPAR) falls by 53 percent in 2020, and returns to very near pre-crisis levels in 2022 (Exhibit 2).

In A3, travel restrictions are lifted for most domestic travel in June 2020 and some international travel in July 2020. In this scenario, it will take six months after restrictions are lifted before buying behavior is based on economic, rather than health-related factors driven by effective, at-scale treatment and/or availability of vaccinations. A3 also assumes limited structural, long-term impact on demand from visiting family and relatives (VFR) and leisure travelers, though transient business travel and groups are reduced by 5 to 10 percent.

A1 is more dire: this scenario presents a sustained, systemic shock for hotels. Recovery to something like 2019’s level does not occur until beyond 2023. RevPAR falls by 60 percent in 2020, and only recovers slightly in 2021.

Economy class is faring better than others

Many US hotels are closed, especially luxury hotels. Occupancy rates show what’s happening. In early May, occupancy was less than 15 percent for luxury hotels and around 40 percent for economy.

Looking ahead, we expect economy hotels to have the fastest return to pre-pandemic levels, and luxury and upper upscale hotels to have the slowest (Exhibit 3). That’s in part because economy hotels are better able to tap segments of demand that remain relatively healthy despite travel restrictions, including truck drivers and extended-stay guests.

Operating economics are also significant: economy hotels can stay open at lower occupancy rates than other chain scales. In all hotels, revenue is a function of average daily rate, number of rooms, and occupancy—plus food and beverage where available. Costs are threefold: variable (with revenue); semi-fixed (may be eliminated if hotel suspends operations); and fixed. For owners considering suspending operations, variable and semi-fixed costs are factors, since fixed costs don’t change, no matter what.

Our analysis indicates that to cover variable and semi-fixed costs, luxury hotels conservatively need occupancy rates 1.5 times greater than economy hotels. Many economy hotels can further reduce their variable and semi-fixed costs, especially if they use family labor. Many luxury hotels, on the other hand, require more than 100 employees to operate.

Better demand and lower operating costs suggest that economy hotels will recover faster. That would be consistent with what we’ve seen in past crises. But there will likely be pockets of resilience and recovery across the market. We are already hearing stories about hotels that are sold out for Labor Day weekend. Similarly, there could be air pockets in otherwise solid chain scales. Hotels reliant on meetings, incentives, conferences, and events (MICE) revenue could face deep shortfalls. Owners will need to monitor bookings carefully, to distinguish between one-off blips in growth and a sustained recovery.

Investors are pessimistic

While publicly traded hotel companies have done much worse than the broader market—bottoming out at a 60 percent share price decrease, 25 percentage points below the S&P 500—lodging REITs, which make up a large portion of publicly traded hotel groups, have fared even worse. Mid-cap REIT share prices have fallen as much as 70 percent since January 1, and some small-cap funds have fared even worse. That’s driven by the structure of the REIT, a pass-through vehicle required to pay out 80 to 90 percent of its net income as shareholder dividends. Shareholders’ confidence in REITs has fallen, as many assume that with component properties hit hard, REITS will not be able to pay dividends, their primary value proposition.

Investors are distinguishing among REITs in a few ways, including debt structure and balance-sheet resilience, geography, and the chain scale of the lodging portfolio. Larger REITs are retaining shareholder confidence, for two reasons: most have more liquidity (cash, mainly) with which to cover fixed costs, and larger REITS tend to be less leveraged than smaller REITs.

The road to recovery: Making the hotel experience safe

When asked what it would take to get them to travel again, most US leisure travelers want additional health and safety measures, according to the McKinsey Consumer Leisure Travel Survey, which surveyed 3,498 travelers from five countries in April 2020 (Exhibit 4).

No one measure, however, satisfies those queried. Survey participants were asked to select all the answers that applied, and respondents said, essentially, “yes”—they do not distinguish among the safety measures, and think these all are more or less valuable.

As they ponder those results, many hotels are wondering what steps to take, in what order, to make their properties safe, and demonstrate that to reluctant customers. Some answers may be emerging from China, the first nation affected by the crisis, and the first one to start coming out of it. Leading Chinese hotels are deploying a range of health and hygiene measures that may be helpful as examples.

Would you like to learn more about our Travel, Logistics & Transport Infrastructure Practice ?

Some Chinese hotels are fine-tuning their booking tools to remind customers about the restrictions in place, and hotels follow up with guests about those before they arrive. Upon check-in, some hotels require guests to provide proof (via a QR code) that they have not been in contact with infected people. Some also measure guests’ body temperature several times: at check-in, anytime they enter and exit the hotel during their stay, as well as upon their checkout. For Western hotels to adopt the same standards would of course require changes in government policy and public-health approaches.

Chinese hotels have also instituted new cleaning processes. Some leading chains have also added touchless or contactless elements to the customer experience, including contactless checkouts  via app or email, and robots to deliver food, beverages, and the like. Some operators are limiting food and beverage options to prepackaged meals, to be consumed inside guests’ rooms versus common restaurant or bar areas. Additional hotel amenities like gyms, spas, and laundry facilities may be closed. At the same time, many Chinese hotels have increasingly targeted their offerings toward the local population and those traveling within short distances—for example, by offering meal plans for locals, or weekend getaways for those who want to spend time outside the city or their apartments.

See “ The way back: What the world can learn from China’s travel restart after COVID-19 ” to read how hotels are testing and learning to see what’s effective all along the customer journey, from prebooking through checkout.

Implications for travel and hospitality

Travel will return. But the recovery will likely take longer than in other industries, and will vary across segments. Business and leisure travel will return at different paces, as will domestic and international travel. What’s certain is that the next normal will be marked by structural shifts, especially around customer expectations for hygiene and flexibility.

For business travelers, demand will likely come back unevenly. Essential travel will differ by industry. According to executives and chief human resources officers in North America, interviewed in April 2020 across an array of industries, every one of their companies is using technology as a substitute for nonessential travel. Most expect that certain types of travel—like internal meetings—will never fully return to pre-COVID-19 levels.

Companies say they plan to turn off their travel restrictions in phases, and are developing decision-making processes and more agile travel policies to account for safety before authorizing travel. Client-facing visits such as site visits and sales calls are likely to return first. Day trips and self-drive travel are likely to return earlier since physical-distancing measures, exposure, and risk will be more manageable. Conferences and industry events will likely be the last to return.

In leisure, we expect that travel to visit friends and relatives will return first, likely by car. Travel restrictions combined with economic uncertainty will likely translate into a higher share of domestic and close-to-home travel. Longer international leisure trips will be slow to return, and travelers will expect greater flexibility in cancelation and change fees. The recovery may include extremely short planning cycles driven by gradual lifts of the travel restrictions and very short booking windows as travelers monitor the situation.

Recent trends in China may offer a glimpse of the weeks ahead for US travelers. As domestic travel in China slowly returns , cautious travelers prefer to stay close to home, either driving or taking trains to regional destinations (Exhibit 5).

Hotels face the prospect of a long recovery. Over the coming months and years, properties’ circumstances will vary based on a number of factors, including chain scale, location, and demand profile. There is no one right response for everyone, but some guidelines apply universally. Hotels must care for their employees, staying engaged with them through the pandemic and keeping them safe when they return. They must manage customer expectations, recognize that these will continue to evolve, and prepare to act agilely to address health and safety concerns. And they must revise their commercial strategy for the restart, with an eye toward the next normal. In the long term, travel will return because of an important shift in consumption—an accelerated pivot from buying things to buying experiences.

We hope the ideas in this article stimulate your thinking and we look forward to hearing your thoughts.

Vik Krishnan is a partner in McKinsey’s San Francisco office, Ryan Mann is an associate partner in the Chicago office, Nathan Seitzman is a partner in the Dallas office, and Nina Wittkamp is an associate partner in the Munich office.

The authors wish to thank Peter Boehm, Andrew Curley, Ben Kohlmann, Melinda Peters, Ganesh Raj, Kyle Snyder, Peimin Suo, and Edison Yu for their contributions to this article.

This article was edited by Justine Jablonska, an editor in the New York office.

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Affiliation.

• 1 Rosen College of Hospitality Management, University of Central Florida, Orland, FL 3819, USA.
• PMID: 34720330
• PMCID: PMC8542563
• DOI: 10.1016/j.ijhm.2021.102986

The COVID-19 pandemic has significantly disrupted the hospitality industry. This research combines different data to examine the US labor market trends during COVID-19. It is found that low-preparation jobs in leisure and hospitality are the hardest hit and slow to recover. The pandemic has highlighted growing issues in workplace safety, skill gaps, technology adoption, and work reorganization in the hospitality industry. This paper develops two propositions about preparing hospitality workers for the future of work and providing flexible work arrangements.

Keywords: Adaptation; COVID-19; Flexible work arrangements; Job trends; Skill training; Workers.

© 2021 Elsevier Ltd. All rights reserved.

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Covid-19 research in hospitality and tourism

Our lives and our industry have been deeply impacted by the pandemic and the global lockdown that came with it. In these unprecedented times researchers at the School of Hospitality and Tourism Management have worked closely with industry to learn about the needs and requirements of businesses and travellers to be able to return to a new normality when it comes to travelling and the prosperity of businesses. We are dedicated to support the hospitality, tourism, events, transport industry, and related sectors with our research and wish to share it as widely as possible.

Impact of Covid-19 on Asia Pacific visitor forecasts 2020-2024

Centre for Competitiveness of the Visitor Economy

Professor Gang Li and Dr Anyu Liu , in collaboration with Professor Haiyan Song’s team at The Hong Kong Polytechnic University, produced  Asia Pacific Visitor Forecasts 2020-2024  for the Pacific Asia Travel Association (PATA). The report has paid particular attention to the impact of Covid-19 on the visitor demand and the market recovery in 39 destinations of the region. Both Professor Li and Dr Liu were invited as panellists to PATA’s webinar on this topic on 14 May 2020. 

Consumer purchasing intention in restaurants and hotels post-Covid-19 lockdown

Dr Yoo Ri Kim and Dr Anyu Liu are working on an experimental study regarding understanding consumers’ purchasing intention in restaurants and hotels after the Covid-19 lockdown measures are lifted. This study aims to provide both theoretical and practical implications for the hospitality industry after the lockdown measures have been lifted by informing consumer behavioural intention on social distancing measures and promotion offers.

Examining the resilience of hospitality companies during the Covid-19 pandemic

Centre for Competitiveness of the Visitor Economy and Centre for Digital Transformation in the Visitor Economy

Dr Tracy Xu is working with Mark Ashton and Dr Yanning Li to study the resilience capacity and real-time adaptive strategies hospitality organisations need to have in order to sustain in the Covid-19 pandemic. This project aims to provide insights into how business strategies for hospitality organizations may be better formulated to build sustainable competitive advantage.

Covid-19 impact on the Chinese air transport markets

Dr Frankie O'Connell  is working on studying the knock-on effects of the Covid-19 crisis on airline traffic (business and leisure passengers) within the Chinese domestic market as well as the China to Europe and China to other Asian markets. This study aims to uncover which type of passenger segment as well as which type of airline business model showed more resilience to the pandemic and which are most likely to rebound firs

Connecting with Nature During Times of Crisis: Understanding alternative use of spaces of leisure and recreation during lockdown

Centre for Digital Transformation in the Visitor Economy

Professor Caroline Scarles and Dr Tracy Xu are working in collaboration with Dr Birgitta Gatersleben and Dr Kayleigh Wyles from the School of Psychology to investigate the impact of Covid-19 on people’s use of local, everyday spaces of leisure and recreation. The research seeks to understand how behaviour during lockdown is significantly different to pre-lockdown behaviours and how experiences during lockdown may influence changes in behaviour going forward. This is an ongoing survey and results will be shared in due course.

Virtual Experiences of Travel During Lockdown

Professor Caroline Scarles , Dr Tracy Xu and Dr Daisy Liu and Ayeisha Green are collaborating to investigate how experiences of virtual travel effect wellbeing during lockdown and how these experiences may affect travel planning and decision making going forward as the tourism industry moves into a post-Covid-19 era. This is an ongoing survey and the results will be shared in due course.

The impact of the UK’s Covid-19 lockdown on dog owners' wellbeing

Postgraduate researcher Lori Hoy  in the School of Hospitality & Tourism Management is investigating the lockdown’s impact on dog owners’ feelings, thoughts, behaviours, and wellbeing. The project is receiving input from various stakeholders including MP Luke Pollard, Shadow Secretary for Environment, Food & Rural Affairs. This project aims to generate information for government, businesses, and charities in future crises. Lori is supervised by Dr Brigitte Stangl and Professor Nigel Morgan.

Sustainable mobility and Autonomous Vehicles after Covid-19

SHTM/SWELL has been administering in the UK a user survey focusing on travel preferences and Autonomous Vehicles. This is an activity of WISE-ACT , which is an international network of experts chaired by Dr Nikolas Thomopoulos . Since this user survey is coordinated with the Eurobarometer and administered in several countries across Europe, SHTM/SWELL researchers will collaborate with WISE-ACT to control user responses received before and after the Covid-19 lock-down across participating countries. Findings will be published in this upcoming special Issue .

Pandemics, tourism and global change: a rapid assessment of Covid-19

Professor Daniel Scott co-authored the assessment of Covid-19 on the tourism industry that is currently the most read journal article in the world on this topic. It reviews how the current ban on travelling is affecting the tourism industry and what the consequences for the sector may be. The article was published in April 2020. 

Changes in air passenger demand as a result of the Covid-19 crisis

Using data on 5,000 million air passenger searches on Skyscanner, we found that desire to fly in 2020 drop by 50% in Asia and 30% in Europe and the Americas, and intention to fly dropped by a further 20%, while most source markets remain optimistic about air travel during the last quarter of 2020. Professor Xavier Font and Dr Inma Gallego developed a methodology to detect the reactivation of tourist markets to help mitigate the effects of the Covid-19 crisis, with a traffic light dashboard that shows how destination managers can use air travel Big Data. The final article  was published in June 2020. 

Examining the wellbeing of gig workers during Covid-19

Dr Yanning Li and Dr Tracy Xu are investigating the wellbeing of gig economy workers during lockdown. It aims to uncover how the Covid-19 pandemic influences the wellbeing of workers in the gig economy in the UK. This project will be beneficial for local authorities and public healthcare managers to address the needs of low-income and relatively insecure group.

Impact of Covid-19 Mobility Restriction in China on People’s Travel Intention—Evidence from Weibo Data

Dr. Anyu Liu and Dr. Yoo Ri Kim with collaborators in China are working on a project to investigate the impact of the Covid-19 mobility restriction on people’s travel intention. The travel intention is measured by the daily sentiment score of 31 provinces/municipalities in China and the casual relationship is examined by the spatial DID approach. The findings of the ongoing study will be updated in due course.

Creating virtual encounters with art in times of crisis

Professor Caroline Scarles ,  Professor Gang Li ,  Dr Jason Chen and Dr Husna Zainal Abidin are evaluating the impacts of virtual engagement with and experience of art during times of crisis. The objectives of this research project are as follows: firstly, to critique the shifts in visitor behaviour patterns throughout this time of crisis as they move from predominantly physical, on-site encounters with art, to engaging with art and curated tours through platforms such as Smartify; secondly, to evaluate the future opportunities for arts and heritage organisations in reframing existing business models to adopt greater virtual, greener and technology-led solutions for engaging with art galleries and associated exhibitions. This project is funded by the SME Innovation Voucher Scheme, in collaboration with Smartify .

Innovative pricing: Pay-as-you-wish as a means to attract customers to museums post-Covid-19

All around the globe tourism organizations are looking for ways to build trust to get customers back to travel, to visit sights, and to generally engage in tourism related activities. Dr Brigitte Stangl and Dr Margit Kastner ( WU Vienna ) are examining the implementation of innovative pricing strategies namely Pay-As-You-Wish (PAYW) for example for museums. PAYW brings benefits for suppliers and consumers. Organizations attract consumers, who can pay the price they can afford (considering the impact the lockdown had on the income of many people). Generated revenue allows organizations to cover costs and to continue operating the business in the usual quality, diversity, and excellence.

Service design and information provision requirements based on proxemics

Dr Brigitte Stangl , Dr Margit Kastner ( WU Vienna ) and Owen Grainger-Jones are examining the change of proxemics introduced by Edward Hall in the early 60s. Potential changes of the four personal interaction zones intimate-, personal-, social- and public distance will be revealed in the context of tourism. A picture-based survey-approach is used to compare pre and post Covid-19 perceptions and differences between segments visiting museums will be revealed. Results of the study will allow to give suggestions concerning consequences for the design of services, such as museums, and information provision requirements post Covid-19.

Tourism recovery, risk and uncertainty

The School of Hospitality and Tourism Management has been awarded an ESRC grant of £175,000 to study how tourism intentions are shaped by Covid-19 risks and uncertainties. Professor Allan Williams , Professor Gang Li and Dr. Jason Chen , together with Professor Vladimir Baláž of the Slovak Academy of Science, will analyse how risk and uncertainty impact on the UK's inbound, outbound and domestic markets. The two-stage project will first analyse a specially-commissioned survey of 17,500 potential tourists in the UK and its four main markets: France, Germany, USA and China. This will be followed by experimental research to assess how tourists respond to contrasting future Covid-19 health and containment scenarios.

This research will provide a new evidence base on tourist intentions that can underpin more accurate demand forecasts, and more targeted market research and policy measures for UK tourism. The project is undertaken in collaboration with VisitBritain and the Association of British Travel Agents.

(Re)engaging with Sport Fans post-Covid

Drs  Yanning Li , Bora Kim and Tracy Xu are investigating how the most hit Sport Industry can recover from the pandemic through (re)engaging with fans. Primarily, their project is examining spectators’ motivations to attend a game and potential apprehensions post-Covid. A Covid-19 recovery strategy will be developed for sport clubs. This project is funded by the Research England SME Innovation Voucher Scheme, in collaboration with Coventry United Ladies Football Club.

Virtual experiences in a post-Covid climate: SMARTIFY, augmented reality and future hybrid business models

Professor Caroline Scarles , Professor Gang Li and Dr Husna Zainal-Abidin have been awarded an ESRC IAA grant in partnership with Smartify to engage with organisations in the arts and heritage sector to increase knowledge transfer of the benefits of adopting technology-based solutions for visitor engagement in arts and heritage. The project will offer organisations hands-on experience of Smartify, support the development of virtual tours, and facilitate increased reach to new and existing audiences. The timeliness of the project is important as during Covid-19 galleries and museums have faced forced closures of physical sites, decimating visitor numbers and significantly impacting organisational revenue streams. This research aims to provide augmented reality solutions that enable organisations to deliver online, virtual tours to allow visitors’ continued exploration of exhibits and collections while on-site visits remain restricted, whilst also opening opportunities for developing new ways of engaging visitors beyond traditional means of physical visitation in a post-Covid climate.

UK Residents Attitudes toward Vaccine Passports

Professor Iis Tussyadiah  and  Dr Athina Ioannou , in collaboration with Brunel University, have been conducting a series of studies to identify public opinions on Covid-19 immunity certifications, also known as vaccine passports or immunity passports, in relation to their travel behaviour. The first part of the study included mining opinions on Twitter, analysing sentiment polarisation as well as extracting themes using topic modelling. This was followed by an online survey targeting circa 1000 UK residents (adults, general population) to learn more about people's perception of the benefits and risks of using vaccine passports for travel and access to services, including hospitality. Preliminary findings from the first-stage study can be found in the  final report , a two-minute explainer Video , and press release .        

Centre stage: women’s empowerment during the covid-19 recovery

While most people’s lives and work have been negatively affected by covid-19, it is estimated that women’s jobs and livelihoods have and continue to be overall more vulnerable to the pandemic. The elimination of gender discrimination at work has become a major challenge of the international political agenda. A study lead by Albert Kimbu and Yanning Li and supported by Tracy Xu , Whitney Smith , and Xavier Font aims to develop a framework that will inspire and guide key tourism sector stakeholders in the four participating countries (Costa Rica, the Dominican Republic, Jordan and Mexico) and beyond in promoting the development of a holistic and integrated approach utilising empirical data and information to equip policymakers and businesses with the capacity and tools to enable better gender-sensitive policy formation during the recovery from the pandemic in 2022. 

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The Hospitality Industry in the Face of the COVID-19 Pandemic: Current Topics and Research Methods.

Author information, affiliations.

• Davahli MR 1
• Karwowski W 1
• Apostolopoulos Y 3

ORCIDs linked to this article

• Karwowski W | 0000-0002-9134-3441
• Sonmez S | 0000-0003-1761-2241
• Davahli MR | 0000-0003-4021-1235

International Journal of Environmental Research and Public Health , 09 Oct 2020 , 17(20): E7366 https://doi.org/10.3390/ijerph17207366   PMID: 33050203  PMCID: PMC7601428

Abstract 

Free full text .

The Hospitality Industry in the Face of the COVID-19 Pandemic: Current Topics and Research Methods

Mohammad reza davahli.

1 Department of Industrial Engineering and Management Systems, University of Central Florida, 12800 Pegasus Dr., Orlando, FL 32816, USA; ude.fcu@rakw

Waldemar Karwowski

Sevil sonmez.

2 College of Business Administration, University of Central Florida, 12744 Pegasus Dr., Orlando, FL 32816, USA; ude.fcu@lives

Yorghos Apostolopoulos

3 Complexity & Computational Population Health Group, Texas A&M University, 2929 Research Pkwy, College Station, TX 77845, USA; ude.umat@otsopay

This study reports on a systematic review of the published literature used to reveal the current research investigating the hospitality industry in the face of the COVID-19 pandemic. The presented review identified relevant papers using Google Scholar, Web of Science, and Science Direct databases. Of the 175 articles found, 50 papers met the predefined inclusion criteria. The included papers were classified concerning the following dimensions: the source of publication, hospitality industry domain, and methodology. The reviewed articles focused on different aspects of the hospitality industry, including hospitality workers’ issues, loss of jobs, revenue impact, the COVID-19 spreading patterns in the industry, market demand, prospects for recovery of the hospitality industry, safety and health, travel behavior, and preference of customers. The results revealed a variety of research approaches that have been used to investigate the hospitality industry at the time of the pandemic. The reported approaches include simulation and scenario modeling for discovering the COVID-19 spreading patterns, field surveys, secondary data analysis, discussing the resumption of activities during and after the pandemic, comparing the COVID-19 pandemic with previous public health crises, and measuring the impact of the pandemic in terms of economics.

• 1. Introduction

On December 8, 2019, the government of Wuhan, China, announced that health authorities were treating dozens of new virus cases, identified as coronavirus disease 2019 (COVID-19) [ 1 ]. Since then, COVID-19, a new strain of SARS (SARS-CoV-2), has grown into a global pandemic and spreading across many countries. A highly transmissible respiratory disease, COVID-19 spreads through contact with other infected individuals, with symptoms such as fever, cough, and breathing problems [ 2 ]. Transmission can also occur from asymptomatic individuals, with up to 40% of infected persons remaining asymptomatic [ 3 ]. Other factors that facilitate infection include (1) speed and efficiency of COVID-19 transmission; (2) airborne transmission [ 4 ]; (3) close contact between infected and non-infected individuals; (4) vulnerability of immunocompromised individuals with specific underlying health conditions (e.g., hypertension, diabetes, cardiovascular disease, respiratory problems); (5) susceptibility of persons over 65; and (7) contact with persons who have traveled to locations with a high number of cases [ 5 ].

Critical global responses to control the spreading of the COVID-19 pandemic have included travel restrictions, shelter-in-place and social distancing orders. Most countries around the world have imposed partial or complete border closures, with travel bans affecting the majority of the world’s population [ 6 ]. With millions suddenly unemployed, uncertainty over economic recovery, and global fears of continuing COVID-19 spread and its future waves, the hospitality industry was among the first industries affected, and it will be among the last industries to recover [ 7 ].

On 20 January 2020, the United States reported its first COVID-19 confirmed case [ 8 ]. In February and through March 2020, the pandemic began to exact unprecedented economic and social consequences. Since public health concerns started to escalate in mid-February 2020, U.S. hotels have lost room revenues [ 9 , 10 ]. As of 3 June 2020, six out of ten hotel rooms remain empty across the country [ 11 , 12 ]. Since August 2020, almost half of the hotel industry employees are still not working, and five out of ten rooms are empty [ 10 ].

The present study focuses on understanding the current research on the hospitality industry’s topic in the face of the COVID-19 pandemic. A systematic review of the contemporary literature is considered to identify and classify research that focuses on the hospitality industry in the time of COVID-19. The systematic review’s primary purpose is to identify, summarize, and analyze the findings of all relevant individual studies that are addressing predefined research questions [ 13 ].

Although no study used a systematic literature review to investigate the hospitality industry in the face of the COVID-19 pandemic, conducting the systematic review is common in the context of hospitality. For example, Yu et al. [ 14 ] conducted a comprehensive review of abusive supervision in hospitality and tourism. Gorska-Warsewicz and Kulykovets [ 15 ] conducted a systematic literature review and selected 26 studies to analyze hotel brand loyalty. The study used the Joanna Briggs Institute’s critical appraisal checklist to address the risk of bias among the included records. Sharma et al. [ 16 ] used a systematic review and analyzed 403 published papers in 13 established hospitality journals to address green hospitality practices. The study proposed a unified conceptual framework based on discovering seven research areas under eco-innovative procedures. Chi et al. [ 17 ] discussed applying artificial intelligence in the hospitality industry, specifically service delivery. The study reviewed 63 publications and identified seven major themes.

Regarding the COVID-19 pandemic, many researchers used a systematic literature review to summarize and evaluate the results of all relevant studies. For example, de Pablo et al. [ 18 ] presented a systematic review of physical and mental health outcomes in health care workers exposed to COVID-19. The study reviewed 115 grey literature publications and published papers in Web of Science until 15th April 2020. Luo et al. [ 19 ] conducted a systematic review using Google Scholar, PubMed, Embase, and WHO COVID-19 databases on the psychological and mental impact of COVID-19 among the general population, healthcare workers, and patients with higher COVID-19 risk. The study selected sixty-two studies with 162,639 participants from seventeen countries.

For the present study, the preferred reporting items for systematic reviews and meta-analyses (PRISMA) are considered for ensuring reliable and meaningful results of the systematic literature review studies. The PRISMA protocol consists of 27 items that help researchers prepare and report scientific evidence accurately and reliably, which improves the quality of research [ 13 ]. This review is structured as follows: the methodology section discusses inclusion and exclusion criteria and the risk of bias; the results, research approaches used, and discussion sections provide outputs of the literature search and describes the status of the hospitality industry at the time of COVID-19.

• 2. Methodology

The literature review follows Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 13 , 20 ] and contains two main features: developing research questions and determining search strategy. The following research questions have guided this review:

RQ1. What aspects of the hospitality industry at the time of the COVID-19 pandemic have been studied?

RQ2. What research methodologies have been used to investigate the impact of COVID-19 on the hospitality industry?

In order to address the above questions, a search strategy was developed to list and review all relevant scientific papers by (a) defining keywords and identifying all relevant materials, (b) filtering the identified records, and (c) addressing the risk of any bias [ 13 ]. One of the main steps in a systematic review is developing specific keywords. Herein, our objective was to target all critical segments of the hospitality industry (e.g., hotels, restaurants) and the broadly defined tourism industry. The defined keywords are shown in Table 1 .

Keywords used in the literature search.

Web of Science, Science Direct, and Google Scholar were used as database search tools. Keywords were used to discover relevant articles and identify 175 articles with relevant content. Because this topic is rapidly evolving, it is important to mention that article discovery was finished at the end of August 2020. After developing the main database and identifying all relevant papers, a formal screening process based on specific exclusion and inclusion criteria was followed. Because of the very timely issue of the COVID-19 pandemic, we included documents in the forms of peer-reviewed academic publications, grey literature, and pre-print articles. However, we excluded secondary sources that were not free or open access, letters, newspaper articles, viewpoints, presentations, anecdotes, and posters.

The screening of the titles, abstracts, conclusions, and keywords in the identified records after removing duplication ( n = 168) resulted in excluding articles ( n = 115) because of not enough relating to the topic. The remaining articles ( n = 53) were read in full against the eligibility principle, and three articles were excluded for not addressing the research questions.

Selection bias in a systematic review can occur by the erroneous application of inclusion/exclusion criteria and/or the specification of included papers’ dimensions. To address the first type of bias, two researchers (MD and WK) independently reviewed the title, abstract, and conclusions of the identified records to select articles for the full-text review. Subsequently, the two researchers compared their selected articles to reach a consensus. After reading the full text of the selected papers, the authors decided whether to include the article—which was considered and included upon reaching an agreement. Disagreements were resolved by the input of the other two authors (S.S. and Y.A.). To address the second type of bias, two researchers (MD and WK) independently specified the included papers’ classifications and subsequently compared the results, resolving disagreements by consultation with the other authors (S.S. and Y.A.). The selection strategy, as per PRISMA guidelines, is illustrated in Figure 1 .

Chart of the selection strategy following PRISMA guidelines [ 13 ].

All included articles were categorized and stored in the main database according to year, source of publication, the industry segment, geographic location, research approach, aspect of the hospitality industry, and methodology. The characteristics of the included papers are shown in Table 2 .

Characteristics of the included papers.

The publication sources of the included papers are illustrated in Figure 2 . The most popular publication sources include Tourism Geographies , International Journal of Infection Diseases , and Journal of Tourism and Hospitality Education .

Publication source among included papers.

To generate a better picture of the included papers, the map of the co-occurrence of terms in the title and abstract is shown in Figure 3 . The colorful nodes are associated with specific terms, and their sizes represent the frequency of term occurrence, and links between two nodes indicate the co-occurrence of the terms. In this Figure, frequently co-occurring terms create clusters and appear closer with the same color. A first glance at Figure 3 reveals the central cluster (blue color) with terms including COVID-19, health, travel, effect, and global tourism.

The map of the co-occurrence of the terms in the title and abstract of recorded papers.

Fifteen papers investigated the hospitality industry in the face of COVID-19 on the global scale, as shown in Figure 4 . Other articles focused on a specific country or location such as China (nine papers), India (six papers), or the United States (four papers).

Geographic location among recorded papers.

The included papers used different research approaches to investigate the impact of COVID-19 on the hospitality industry (see Figure 5 ). Each approach is explained in the following section.

Research approach among included papers.

• 4. Research Approaches Used

The reviewed papers used different research approaches and focused on various subjects related to the hospitality industry during the COVID-19 pandemic. However, all papers have been classified into six groups as follows: (1) developing simulation and scenario modeling, (2) reporting impacts of the COVID-19 pandemic, (3) comparing the COVID-19 pandemic with previous public health crises, (4) measuring impacts of the COVID-19 pandemic in terms of economics, (5) discussing the resumption of activities during and after the pandemic, and (6) conducting surveys. Since some of the reviewed papers belong to more than one group, these have been assigned to the dominant group.

4.1. Developing Simulation & Scenario Modeling

Eight included papers in this review applied simulation & scenario modeling to estimate aspects of tourism demand and the COVID-19 spreading pattern. The studies used different models and analyses, including a dynamic stochastic general equilibrium (DSGE) model, supply and demand curve, agent-based model, epidemiological model, and susceptible exposed infected recovered (SEIR) model.

Yang et al. [ 2 ] applied DSGE, a macroeconomics technique that depicts economic phenomena based on the general equilibrium framework, to investigate the impacts of increasing health disaster risk (the pandemic) and its persistence on the model parameters such as tourism demand. He incorporated two indicators (health status, and health disaster) and three categories of decision-makers (the government, households, and producers) into the DSGE model concerning the tourism sector. The findings are not surprising and point out that the longer pandemic will have a more devastating effect on the hospitality industry.

Bakar and Rosbi [ 1 ] utilized a supply and demand curve to analyze the economic impact of COVID-19 on the hospitality industry. In order to develop the supply and demand curve, the demand function was created by using factors of price setting of selected goods, tastes and preferences of customers, customers’ expectations, the average income of certain countries, and the number of buyers . Meantime, the supply function is developed by using elements of production techniques, resource price, price expectations, price of related goods, supply stocks, and numbers of sellers . The supply and demand curve was then developed in the market equilibrium condition where the demand in the market is equal to the supply in the market. Finally, changes in market equilibrium as the result of the COVID-19 outbreak were investigated. The results indicate that the pandemic created some "panic" level among people and consequently decreased overall demand in the tourism and hospitality industry [ 1 ]. The study urged governments to discover a vaccine as quickly as possible and identify policies to prevent the further decrease in demand for tourism and hospitality services during the post-pandemic period [ 1 ].

D’Orazio et al. [ 38 ] used an agent-based model to determine the virus spreading in tourist-oriented cities and, consequently, discover sustainable and resilient strategies [ 38 ]. The model represented simulated individuals’ movement and the contagion virus spreading approach (the epidemic rules based on previous studies) in a touristic urban area. The model calculated the probability that an infector: (i) could infect a susceptible individual j based on a linear combination of the current incubation time of (i), the exposure time, and the mask filter adopted by both i and j. The model evaluated the number of infectors within the touristic urban area over time and the number of visitors who return home being infected over time. After analyzing different scenarios, such as “social distancing-based measures” and “facial mask implementation”, the results reveal that “social distancing-based measures” were related to significant economic losses [ 38 ]. This phenomenon appears to be an effective policy in locations with the highest infection rates [ 38 ]. However, “social distancing-based measures” lose their advantage in areas of low infection rates and a high degree of "facial mask implementation" [ 38 ].

Five studies investigated COVID-19 cases and spreading patterns on the Diamond Princess cruise ship. On February 1, 2020, a disembarked passenger from the ship tested positive for COVID-19 [ 69 ], after which the 3711 passengers were quarantined [ 69 ]. By the end of the quarantine, more than 700 passengers were infected with COVID-19 [ 69 ]. Fang et al. [ 33 ] developed the flow of passengers (crowd flow simulation model) on the Diamond Princess cruise ship, and then created the virus transmission rule between individuals to simulate the spread of the COVID-19 caused by the close contact during passengers’ activities. Mizumoto and Chowell [ 34 ] and Mizumoto et al. [ 35 ] developed an epidemiological model based on discrete-time integral equations and daily incidence series. Rocklöv et al. [ 36 ] collected data on confirmed cases on the Diamond Princess cruise ship. They used the SEIR model (compartmental technique estimating the number of susceptible (S), exposed (E), infected (I), and recovered (R) individuals) to calculate the primary reproduction number. The basic reproduction number is the expected number of cases directly generated by one case in a population where all individuals are susceptible to infection [ 70 ]. Zhang et al. [ 37 ] collected data of daily incidence for COVID-19 on the Diamond Princess cruise ship, data of a serial interval distribution ( the time between successive cases in a chain of transmission [ 71 ]), and applied "projections" package in R to calculate the basic reproduction number. The studies concluded that the cruise company’s immediate response in following recommended safety guidelines and early evacuation of all passengers could prevent mass transmission of COVID-19 [ 33 , 34 , 35 , 36 , 37 ].

4.2. Reporting the Impacts of the COVID-19 Pandemic

Seventeen papers applied secondary data analysis to report COVID-19 pandemic’s impacts on the hospitality industry. Because of the ongoing pandemic and publication time of included papers, secondary data sources have been invaluable for most studies in this review. The studies reported impacts of the pandemic on different aspects of the hospitality industry, including job loss, revenue losses, access to loans, market demand, emerging new markets, hostile behaviors towards foreigners, and issues of hospitality workers and hotel cleaners.

Nicola et al. [ 49 ] summarized the pandemic’s impact on the global economy by reviewing news distributed by mass-media, government reports, and published papers. To better understand the impacts of the pandemic, the study divided the world economy into three sectors of primary (including agriculture, and petroleum & oil), secondary (including manufacturing industry), and tertiary (including education, finance industry, healthcare, hospitality tourism and aviation, real estate, sports industry, information technology, and food sector). They reported job loss, revenue losses, and decreasing market demand in the hospitality, tourism, and aviation sectors [ 49 ].

Ozili and Arun [ 51 ] provided a list of COVID-19 statistics, including confirmed cases, confirmed deaths, recovered cases in several countries and continents, and discussed the global impact of COVID-19 on the travel and restaurant industries. The study reviewed different policy measures implemented by different countries around the world to deal with COVID-19. Ozili and Arun [ 51 ] categorized these into four groups of (1) human control measures; (2) public health measures; (3) fiscal measures; and (4) monetary measures. In the human control policies measures, different actions including foreign travel restrictions, internal travel restrictions, state of emergency declarations, limiting mass gathering, closing down of schools, and restricting shops and restaurants, have also been identified [ 51 ].

Several studies reported the effect of COVID-19 on specific critical domains of the hospitality industry, such as undocumented workers and hotel cleaners. Williams and Kayaoglu argued that the most vulnerable workers in the industry need governmental financial support but cannot receive assistance, most likely because they are undocumented immigrants [ 55 ]. Furthermore, Rosemberg [ 50 ] highlighted the issues of job insecurity, risk of exposure to COVID-19, lack of health insurance, added pressure due to increased workload, and extra time required for ensuring complete disinfection during the pandemic [ 50 ].

Other studies focused on the pandemic’s impacts on specific countries, including China, Malaysia, Nepal, and India. Wen et al. [ 54 ] reviewed literature and news on Chinese tourist behavior, tourism marketing, and tourism management; they concluded the growing popularity of luxury trips, free and independent travel, and medical and wellness tourism post-COVID-19 period [ 54 ]. They indicated that new forms of tourism would be more prevalent in post-COVID-19, including (1) slow tourism, which emphasizes local destinations and longer lengths of stay, and (2) SMART tourism, which uses data analytics to improve tourists’ experiences [ 54 ]. Another study used automated content analysis to investigate newspaper articles and identified nine key themes among 499 newspaper articles, including, “ COVID-19’s impact on tourism, public sentiment, the role of the hospitality industry, control of tourism activities and cultural venues, tourism disputes and solutions, national command and local response, government assistance, corporate self-improvement strategies, and post-crisis tourism product ” [ 42 ].

4.3. Comparing COVID-19 with Previous Public Health Crises

Two papers compared the COVID-19 pandemic with previous public health crises. In the first study, lessons learned from previous crises and pandemics are discussed, including malaria, yellow fever, Ebola, Zika virus, Middle East respiratory syndrome (MERS-CoV), avian influenza (H5N1), Creutzfeldt-Jakob disease (Mad Cow disease), swine flu (H1N1), and severe acute respiratory syndrome (SARS) [ 22 ]. This paper concluded that the impacts of COVID-19 on the global economy and China’s tourism and hospitality industry, in particular, are likely to differ from previous pandemics, from which the tourism and hospitality industry recovered relatively quickly [ 22 ].

Gössling et al. [ 21 ] reviewed the impact of previous crises on global tourism, including the Middle East Respiratory Syndrome (MERS) outbreak (2015), the global economic crisis (2008–2009), the SARS outbreak (2003), and the September 11 terrorist attacks (2001) [ 21 ]. The authors indicated that previous crises did not have long-term impacts on global tourism. The authors also warned about increasing pandemic threats for several reasons, including the fast-growing world population, rapidly developing global public transportation systems, and increasing consumption of processed/low-nutrition foods [ 21 ]. Gössling et al. [ 21 ] also discussed the impact of COVID-19 on different hospitality industry sectors. The authors distinguished the impact of COVID-19 in view of two different aspects of (1) observed impacts (e.g., declines in hotel occupancy rates, liquidity problems in the restaurant industry); and (2) projected impacts (e.g., revenue forecasts in the accommodations sector, estimation of revenues) [ 21 ].

The still-evolving understanding of the coronavirus’s behavior makes it difficult to predict the industry’s recovery in the near future. However, suggestions have already been made for post-COVID-19 management of the tourism and hospitality industry. These include: (1) focusing primarily on domestic tourism; (2) ending mass tourism and pilgrimage tourism; (3) focusing more on conference tourism, virtual reality tourism, and medical tourism; and (4) building a more sustainable tourism and hospitality industry rather than a return to "business as usual" [ 21 , 22 ].

4.4. Measuring the Impacts of COVID-19 in Terms of Economics

Five papers measured the impacts of the pandemic on the hospitality industry in terms of economics. These studies used different models and analyses, including seasonal autoregressive integrated moving average model, scenario analysis, and trend analysis. The economic impact of COVID-19 on the tourism and hospitality industry has been examined in terms of lost earnings or jobs. Centeno and Marquez [ 29 ] developed seasonal autoregressive integrated moving average models for the Philippines’ tourism and hospitality industry, forecasting the total earnings loss of around 170.5 billion PHP (Philippine Peso)—equivalent to $3.37 billion—from COVID-19 just until the end of July 2020. To ease the pandemic’s effects on the hospitality industry, the authors propose dividing the country into two regions according to the level of infection risk (high-risk and low-risk of COVID-19) to allow domestic travel into low-risk regions or areas [ 29 ].

Günay et al. [ 30 ] applied a scenario analysis technique to calculate the impact of COVID-19 on Turkey’s tourism and hospitality industry. Their model predicts the total loss of revenues in the best and the worst scenarios as 1.5 b i l l i o n a n d 15.2 billion, respectively, for 2020 [ 30 ]. The worst-case scenario involves the closing of borders for four months without any economic recovery [ 30 ]. The authors indicated that this would be one of Turkey’s worst tourism crises under the worst-case scenario, exceeding the losses from public health crises due to Swine flu, Avian Flu, and SARS [ 30 ].

Mehta [ 31 ] estimated the effect of COVID-19 on India’s economy at an earnings loss of about $28 billion in 2020, along with 70% job losses for tourism and hospitality workers, and mass bankruptcies [ 31 ]. Trend analysis was also used to examine the impact of COVID-19 on the global tourism and hospitality industry and global GDP [ 32 ]. According to Priyadarshini [ 32 ], the real global GDP growth will drop from 2.9% in 2019 to 2.4% by the end of 2020, while global revenues for the tourism and hospitality industry will drop by 17% compared to 2019. The study also predicts that North America, Europe, and Asia will experience the most massive losses in global revenues. The tourism and hospitality revenues will fall in the U.S., Germany, Italy, and China by 10%, 10%, 24%, and 40%, respectively [ 32 ].

Cajner et al. [ 28 ] analyzed the COVID-19 pandemic impact on the U.S. labor market. The study calculated that about 13 million paid jobs were lost between March 14 to 28, 2020. To better understand this number’s significance, the authors pointed out that only nine million private payroll employment jobs were lost during the Great Recession of the 1930s (less than 70% of the pandemic job loss) [ 28 ]. The study also highlighted that the leisure and hospitality industry was the hardest hit and most affected industrial sector [ 28 ].

4.5. Resumption of Activities during and after the Pandemic

Thirteen papers recommended various remedial and management actions for the resumption of activities during and after the pandemic. The consequences of COVID-19 on the hospitality industry, such as empty hotels and loss of jobs, are discussed in one paper that offers a positive outlook that the industry will receive a significant flow of guests upon the easing of travel bans and restrictions [ 63 ]. The author stressed the importance of support for the hospitality industry during the pandemic and the need for proper guidance to ensure successful reopening during the post-pandemic period. Taking a different perspective, another study suggests that the hospitality industry may not do well after the lifting of travel bans and mobility restrictions [ 58 ]. The study refers to a survey that found more than half of the participants would not order food even after the pandemic ends. The author also recommends a series of actions for restaurants to attract customers in the post-COVID-19 period, such as including island-sitting arrangements to assure maximum physical distances between people, live cooking counters to allow customers to watch their food being prepared to instill confidence in its safety, and having appropriate hygiene and cleaning procedures throughout [ 58 ].

Bagnera et al [ 68 ] investigated the impact of COVID-19 on hotel operations and recommended a series of actions for hotel owners and managers, including using fewer rooms (reducing hotel capacity); emphasizing take-out or delivery options to reduce public dining, implementing intensified cleaning/sanitizing protocols; committing to the use of personal protective equipment (PPE) for workers and increasing attention to personal hygiene; communicating new COVID-19 policies to guests and employees; implementing physical distancing practices in public areas, and implementing protocols for guests exposed to or infected by COVID-19 [ 68 ]. It should be noted that the World Health Organization (WHO) produced a guide titled "Operational Considerations for COVID-19 Management in the Accommodations Sector" to provide practical assistance to the hospitality sector in particular [ 64 ]. The report is divided into sections for the management team, reception and concierge, technical and maintenance services, restaurants and dining rooms and bars, recreational areas for children, and cleaning and housekeeping with a list of responsibilities to help manage the threat of COVID-19 [ 64 ]. Furthermore, Jain discussed different hotel industry strategies to bring back customers, including disposable utensils in rooms, emphasizing staff health and hygiene, and using UV light to disinfect [ 59 ].

Specific steps for an exit strategy and the reopening of activities in different business sectors are presented by Peterson et al. [ 62 ]. Primary steps include implementing widespread COVID-19 testing, having enough PPE supply, lifting social distancing and mobility restrictions, using electronic surveillance, and implementing strategies to decrease workplace transmission [ 62 ]. Emphasis was placed on the daily screening of hospitality sector staff for COVID-19 by using real-time reverse transcription-polymerase chain reaction or serology tests [ 62 ]. In this aspect, another study used primary and secondary data and applied the descriptive analysis method to explore revitalization strategies for small and medium-sized businesses, especially in the tourism industry, after COVID-19 in Yogyakarta [ 56 ]. The study recommended several policies, such as implementing banks’ credit policies with simpler processes and lower interest [ 56 ].

Several papers discussed redesigning and transforming the tourism and hospitality industry after COVID_19 pandemic. The proposed ideas include increasing resilience and security of the tourism and hospitality workforce in post-COVID-19 by cross-training and teaching different skills to workers [ 61 ]; exploiting the unique opportunity presented by COVID-19 to transform and refocus the tourism and hospitality industry towards local attractions rather than global destinations, and redesigning spaces to assure a 6-foot distance between tourists [ 57 , 60 , 67 ]. Hao et al. [ 65 ] developed a COVID-19 management framework as a result of reviewing the overall impacts of the COVID-19 pandemic on China’s hotel industry. The framework contains three main elements of an anti-pandemic process, principles, and anti-pandemic strategies. The anti-pandemic process adopted the six phases of disaster management, including the pre-event phase (taking prerequisite actions), the prodromal phase (observing the warning signs), the emergency phase (taking urgent actions), the intermediate phase (bringing back essential community services), the recovery phase (taking self-healing measures), the resolution phase (restoring the routine).

Hao et al. [ 65 ] recommended four principles for the different phases of disaster management, including disaster assessment, ensuring employees’ safety, customer & property, self-saving, and activating & revitalizing business. Finally, the study discussed the main anti-pandemic strategies in the categories of leadership & communication, human resource, service provision, corporate social responsibility, finance, and standard operating procedure. Recently, Sönmez et al [ 66 ] reviewed the impacts of the COVID-19 pandemic on immigrant hospitality workers’ health and safety. The study indicated that while a significant rise in occupational stress has been observed in immigrant hospitality workers over the past 15–20 years, the COVID-19 pandemic can add more pressure on workers and potentially deteriorate their mental and physical health condition. The authors recommended different actions in aspects of public and corporate policy, workplace policy, and future research areas.

4.6. Conducting Surveys

Five papers conducted survey studies to investigate different hospitality industry aspects, including social costs, customer preference, expected chance of survival, and travel behavior. Qiu et al. [ 25 ] developed the contingent valuation method to estimate costs borne by residents of tourist destinations (social costs) due to the COVID-19 pandemic. Contingent valuation is a survey-based economic technique for the valuation of non-market resources [ 72 ]. The survey asks questions about how much money residents would be willing to pay to keep a specific resource. The study attempted to investigate how residents perceive the risk of tourism during the COVID-19 pandemic. By considering three Chinese urban destinations, Qiu et al. [ 25 ] quantified tourism’s social costs during the pandemic. The results indicate that most residents were willing to pay for risk reduction, but this payment differs based on respondents’ age and income.

Alonso et al. [ 27 ] focused on the theory of resilience and conducted a survey from a sample of 45 small hospitality businesses to answer questions about participants’ main concerns regarding the COVID-19 pandemic. How small hospitality businesses are handling this disruption. Furthermore, what are the impacts of the pandemic on day-to-day activities. Alonso et al. [ 27 ] analyzed the qualitative responses through content analysis. The study highlighted nine theoretical dimensions about owners-managers’ actions and alternatives when confronted with the COVID-19 pandemic.

Kim and Lee [ 26 ] studied the impacts of the perceived threat of the COVID-19 pandemic on customers’ preference for private dining facilities. The study conducted a survey and concluded that the salience of the COVID-19 increases customers’ preference for private dining facilities.

Bartik et al. [ 23 ] discussed the impact of COVID-19 on the U.S. small businesses, especially restaurants and tourism attractions, and highlighted their fragile nature in the face of a prolonged crisis. Such companies typically have low cash flow, and in the face of this pandemic, they will either have to declare bankruptcy, take out loans, or significantly cut expenses [ 23 ]. Their restaurant owners’ survey found that the expected chance of survival during a crisis lasting one month is 72%, for a crisis that lasts four months is 30%, and for a crisis that lasts six months is 15%. The result also indicated that more than 70% of U.S. small businesses want to take up the CARES Act Paycheck Protection Program (PPP) loans, even though most of them believe it would be challenging to establish eligibility for receiving such loans [ 23 ].

Finally, a survey study by Nazneen et al. [ 24 ] investigated the pandemic’s impact on travel behavior and reported that it had significant impacts on tourists’ decisions to travel for the next 12 months. The authors also concluded that respondents are concerned about hotels’ safety and hygiene, recreational sites, and public transports [ 24 ]. It has also been postulated that hygiene and safety perception will play a significant role in travel decisions in post-COVID-19 times [ 24 ].

• 5. Discussion

Even though included papers studied different aspects of the hospitality industry during the COVID-19 pandemic (see Figure 6 ), the main topics relate to recovery of the industry (19% of papers), market demand (18% of papers), revenue losses (16% of papers), the COVID-19 spreading patterns in the industry (14% of papers), job losses (10% of papers), safety and health aspects (8% of papers), issues related to the employment of hospitality workforce (7% of papers), travel behaviors (4% of papers), preferences of customers (2% of papers), and social costs of pandemic (2% of papers).

Research aspects of the hospitality industry among included papers.

The employment issues of hospitality workers have been mentioned by 7% of papers in the categories of “reporting the impacts of the COVID-19 pandemic” and “discussing the resumption of activities”. These papers discussed job insecurity, financial, and health issues among documented and undocumented workers. Ten percent of included papers reported or measured job losses in the hospitality industry as the result of the COVID-19 pandemic. Revenue losses, market demand, and recovery of the industry were the most popular aspects of the hospitality industry, and 16%, 18%, and 19% of the included papers, respectively, discussed these topics. It should be noted that these aspects were mainly discussed in the framework of “reporting the impacts of the COVID-19”. The aspect of COVID-19 spreading patterns was the most popular topic in the approach of “developing simulation & scenario modeling”. Eight percent of included papers recommended different safety actions for the resumption of activities during and after the pandemic. Travel behaviors, preferences of customers, and social costs were mainly analyzed in the “conducting surveys” approach.

The reviewed papers used a variety of research models and analyses to study the hospitality industry in the face of COVID-19 (see Figure 7 ). Secondary data analysis was utilized to study almost all aspects of the hospitality industry. COVID-19 spreading patterns were investigated by using several quantitative models, including the SEIR models, epidemiological models, agent-based models, and crowd flow simulation models. The seasonal autoregressive integrated moving average model was used to calculate job loss and revenue losses. The contingent valuation method, content analysis, and analyzing questionnaire data were parts of the “conducting surveys” approach and were used to analyze social and behavioral aspects of the hospitality industry response to the COVID-19 epidemic.

Research models and analyses of included papers.

• 6. Conclusion

This paper provides a systematic review of the published research topics relevant to the understanding of the hospitality industry in the time of COVID-19 pandemic. By selecting keywords and following PRISMA guidelines, we explored two main research questions related to the objective. A total of 50 papers that met the predefined inclusion criteria were included in the review. The following two research questions have been explored:

The included papers were classified into six thematic groups, including: (1) developing simulation and scenario modeling, (2) conducting surveys, (3) reporting impacts of the COVID-19 pandemic, (4) comparing the COVID-19 pandemic with the previous public health crises, (5) measuring impacts of the COVID-19 pandemic, and (6) proposing different remedial and management actions (discussing resumption of activities). These papers focused on different aspects of the hospitality industry, including the recovery of the industry after the pandemic, market demands, revenue losses, the COVID-19 spreading patterns in the industry, job losses, safety and health, employment issues of hospitality workers, travel behavior, preference of customers and social costs. The reviewed papers used a variety of research methodologies, such as the SEIR model, epidemiological model, agent-based model, supply and demand curve, DSGE model, crowd flow simulation model, secondary data analysis, seasonal autoregressive integrated moving average model, scenario analysis, trend analysis, descriptive analysis, contingent valuation model, content analysis, and analyzing questionnaire data.

In general, conducting a systematic literature review has several limitations. The first limitation is identifying and analyzing papers published in a specific time frame. The second limitation is the inability to discover individual relevant papers arising from a limited number of keywords. The third limitation is using a limited number of search databases for article discovery.

Although we defined several search keywords and followed PRISMA guidelines, it is possible that some papers that met the inclusion criteria were not considered in our review. We did not include the papers published after August 2020 as several papers on the topic have just started to emerge. Second, we selected papers only from Web of Science, Science Direct, and Google Scholar databases. Third, we could not include articles where authors investigated the hospitality industry at the time of the COVID-19 pandemic without mentioning the hospitality industry, tourism industry, event industry, hotel industry, and restaurant industry. Fourth, one of the main challenges of this review was defining inclusion criteria. Because of the very timely issue of the COVID-19 pandemic, we defined broad inclusion criteria. Therefore, we could not include several studies that met inclusion criteria but generated by institutions outside of the traditional academic publishing and distribution channels.

Despite the above limitations, we identified the hospitality industry’s main aspects in the face of the COVID-19 pandemic. These include the recovery of the hospitality industry (discussed by 19% of included papers), market demand (18% of papers), revenue losses (16% of papers), the COVID-19 spreading patterns in the industry (14% of papers), job losses (10% of included papers), safety and health aspects (8% of papers), issues related to the employment of hospitality workforce (7% of papers), travel behaviors (4% of papers), preferences of customers (2% of papers), and social costs of pandemic discussed by 2% of included papers.

It should be noted that there are numerous other fertile research areas and methodologies that can be applied by multidisciplinary research teams to study the effects of the COVID-19 pandemic on the hospitality industry. Such approaches and methods include (1) using complex system science frameworks such as syndemics, (2) developing simulation modeling in different types of system dynamics, discrete event simulation, agent-based modeling, and Monte Carlo/risk analysis simulation, (3) investigating the application of new technologies such as educational technology, information technology, and robotics in response to the pandemic, (4) using artificial intelligence in different types of machine learning, deep learning and neural networks, and (5) developing the best practices concerning the pandemic (see Figure 8 ). These research approaches can be used to analyze the main aspects of the hospitality industry at the time of the COVID-19 pandemic, such as developing sustainable industry, recovery and resilience of the hospitality industry, the safety of customers, issues of undocumented workers, market demand, and emerging the new market, hostile behavior toward customers, and the risks of resumption of activities during the pandemic.

Future research approaches to study the hospitality industry in the face of COVID-19.

For example, due to the complex and dynamic nature of the current pandemic, the use of a wide array of complex systems science frameworks and simulation modeling can make an important contribution by examining how the synergistic effects of work and living conditions, as well as COVID-19 government and corporate responses, can influence the long-term health and safety of tourism and hospitality workers. Along these lines, the development and application of new technologies and equipment in the hospitality industry should protect guests and workers alike. Finally, other potential areas of research include the use of machine learning and artificial intelligence in building a more sustainable tourism and hospitality industry and developing the best practices in improving the industry’s resilience in the future.

• Author Contributions

Methodology and writing—original draft and revisions, M.R.D.; conceptualization, writing—review and revisions, editing, and supervision, W.K.; review and revisions, and editing, and methodology, S.S.; review and revisions, editing, and methodology, Y.A. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

• Conflicts of Interest

The authors declare no conflict of interest.

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Hospitality industry looks strong for 2023 – despite recession fears

EY Americas Real Estate, Hospitality & Construction Consulting Leader

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Despite economic headwinds stoking fears of a 2023 recession, the hospitality industry still defies expectations and posts strong numbers..

• Travel demand, while currently robust, may be impacted if companies need to cut costs in the face of a worsening economic outlook.
• The industry should continue to focus on efficiencies at the hotel and corporate levels, prioritizing customer experience, analytics and automation.
• Transaction activity is likely to be slower; due diligence is critical so teams are prepared when the right deal comes along.

T here is one cautionary note that is always important to keep in mind when evaluating the hospitality industry. Market performance of hospitality has exceeded other industries such as technology and retail, with the gap widening in the second half of the year.¹ Add the fact that revenue per available room (RevPAR) has exceeded GDP growth during the current economic cycle, and 2023 should be a good year for the hospitality sector (see graphic).

• As per a CBRE study, during the 2009 recession, 10.2% of the properties that experienced a decline in RevPAR saw their rooms revenue drop by more than 30%. On average, these properties also suffered a 35.3% drop in total revenue, but the decline in Gross operating profit averaged 57.0%.
• As per a CBRE study, in 2001, properties that experienced a decline in RevPAR, only 2% saw RevPAR fall by more than 30%. On average, these properties suffered a 35.3% drop in total revenue which resulted in a 54.2% decline in Gross operating profit.
• The impact of Covid-19 ended the nine-year trend of profit growth and positive RevPAR for U.S. hotels since 2010, with a significant upwards spike of RevPAR starting in 2020.

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“Historically there has been a strong correlation between GDP growth and RevPAR,” said Umar Riaz, EY Americas Hospitality Sector Leader, in a recent interview with HOTELS Magazine. “But it’s my opinion that given the current dynamics of the travel industry, even if there is a mild recession in the next six months or so, the travel industry will still perform strongly.”

The post-pandemic urge to travel remains strong, which should drive continued growth in 2023. In the US, RevPAR was up 8.1% in 2022 from 2019, and Europe was up 6.1% for the same period. Asia, driven primarily by China, was the weak spot with a 31.2% RevPAR decline from 2019 to 2022. The industry’s average daily rate (ADR), which measures the average rental revenue earned by an occupied room per day, was up 13.6% last year in the US and 18.5% in Europe, when compared with 2019 figures.²

Business travel is also poised for recovery as companies ramp up their travel budgets. Trade shows and conferences are selling out, reflecting the pent-up demand that persists across all industries to get out of the office. Another factor in the industry’s resurgence is the growing work-from-home (WFH) segment of the workforce. In some cases, those employees build their travel plans around both business and leisure. Bleisure travel, where business travelers add on a day or budget extra time in their work trip for sightseeing or some other type of leisure activity, is a growing trend. The result of these market developments is more revenue and continued economic recovery for the hospitality sector.

Reasons for optimism in hospitality sector

The EY organization projects that the global economic picture is mixed heading into 2023, depending on the region, but the long-simmering slowdown will likely turn into a global recession. In the US, the economy is visibly cooling because of persistent inflation, rising borrowing costs, deteriorating private sector morale and rapidly slowing global economic activity. Elevated inflation and a lingering energy crisis will lead to a moderate recession in the Eurozone. In China, the economic outlook remains uncertain, with growth constrained by the recently lifted zero-COVID-19 policy, a lingering property sector downturn and weakening global trade activity.

However, several factors contribute to optimism for the hospitality sector in 2023:

• Leisure demand, group business travel poised to remain strong: Consumer surveys show that most people are planning at least one leisure trip over the next six months. Rising inflation might mean that consumers will make different choices when they travel, but demand still remains strong. As for group business travel, key statistics, such as a convention center booking increase of 13% in 2023 relative to 2022, point to a strong year for group travel.³ According to a survey conducted by American Express, 65% of respondents expect their spend on meetings and events to increase in 2023.⁴
• Business travel recovery: According to a recent survey by Morgan Stanley of global corporate travel managers, travel budgets are likely to be 98% of 2019 levels, with nearly half the respondents expecting an increase of budgets relative to 2019.⁵
• China’s re-opening: Before the pandemic, China was the world’s largest outbound travel market, with Chinese travelers taking 154 million trips and spending $255 billion.⁶ With the lifting of COVID-19 travel restrictions, Chinese travelers will begin to travel again in 2023. While there are still significant airline capacity constraints, there will be a measurable impact on both the domestic and international hospitality industries.
• The rise of the digital nomad:  According to a recent EY survey of companies , 87% said that COVID-19 has had a profound effect on the workplace, with 72% saying that they now have a hybrid remote/office approach and 75% saying that they anticipate no central office in the foreseeable future. As these workplace trends take hold and people become untethered to their offices, these digital nomads will become even more mobile and will work from places where they want to travel.
• Infrastructure Investment and Jobs Act: Spending associated with the Infrastructure Investment and Jobs Act (IIJA) that was passed in the US in 2022 should lead to additional spending on hotels.

Deals market could see a slowdown

One aspect of the hospitality sector that isn’t expected to be so strong in 2023 is the transaction market. 

With the Fed continuing to raise interest rates in an attempt to drive down inflation, the cost of borrowing money will continue to go up. As a result, transaction activity is likely to be slow in 2023. Deals will still get done, and there will be opportunities to create value and drive growth through M&A activity in the hospitality sector. Transaction due diligence will be even more critical to identifying the right transaction, given the market circumstances. In some cases, 2023 will be a good time to focus on organic growth. But teams still need to monitor what’s happening in the industry and be prepared should the right deal come along.

Boomerang workers?

During the pandemic, the hospitality industry lost much of its workforce as travel restrictions forced hotels to make severe staffing cuts. The industry’s unemployment rate leapt from 5.7% in February 2020 to 39.3% in April 2020, according to the U.S. Bureau of Labor Statistics (BLS).⁷ Many of these workers took jobs in the technology sector, which desperately needed to fill positions to keep up with sudden demand created by lifestyle changes that came about due to the pandemic.

Three years later, the world is adjusting again. While tech companies shed jobs in response to the state of the economy in 2023, the hospitality industry is now ready to hire in response to the expected increase in travel. One of the sectors that had the biggest job growth in December 2022 was travel and leisure. Hotels that have struggled to provide the same level of service and amenities they did prior to the pandemic may be able to fill some of these positions and get closer to full strength.

Bottom line: 2023 should be a good year for the travel and hospitality industry.

The hospitality industry has much to look forward to in 2023 as travel demand continues to grow faster than expected over the last few years. Consumer research reveals that leisure and group business travel remains strong and new workplace trends allow people to travel more as they can work from anywhere. While the transaction market slows down, there is still opportunity to find a good deal while still focusing on organic growth.

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Online MS in Hospitality & Tourism

Hospitality and tourism industry prepares for post-pandemic rebound.

Before COVID-19 turned the world upside down, the hospitality and tourism industry was responsible for more than 10 percent of global GDP and one in every 10 jobs worldwide, according to the World Travel & Tourism Council (WTTC). It was also one of the fastest-growing fields, accounting for one in four new jobs created over the previous five years.

The pandemic changed all that, at least temporarily. While few segments of the economy were spared, hospitality and tourism were particularly hard hit. The WTTC reported that the sector lost $4.5 trillion in 2020, with its contribution to GDP plummeting 49.1 percent, compared with just a 3.7 percent decline in the overall global economy.

While COVID-19 has caused significant disruption, the hospitality and tourism industry is resilient and is coming back stronger following previous downturns, such as those caused by the 9/11 terrorist attacks and the 2008 economic crash, according to  Dr. Hicham Jaddoud , who teaches Global Hospitality and Tourism in the USC Bovard College’s Online Master of Science in Hospitality and Tourism program.

“Growth in the sector has become greater after each crisis,” he says. “Why? Because hospitality takes advantage of that slow time to retrain, refresh and develop new concepts that are even more appealing to consumers.”

In spite of the recent tumult—and in many ways because of it—Jaddoud and other experts say the industry is now accelerating some of its longstanding priorities in the areas of sustainability, efficiency, innovation and technology.

Renewed Focus on Renewables

The Environmental Protection Agency estimates an average of 63 million tons of food waste per year in the United States alone, with some 40 percent of that accounted for by hotels and other consumer-facing businesses, according to the American Hotel and Lodging Association. Meanwhile, daily water usage per occupied hotel room averages 100 to 400 gallons.

While many hospitality organizations were introducing more sustainable practices pre-pandemic, in reality it remained challenging for large parts of the sector.

“The industry was moving at such a quick pace,” says Diana C. Beltran , a hospitality management executive who teaches Managing Service Quality in Hospitality and Tourism at USC Bovard. “Tourism was growing exponentially every year. There was just no time to focus on reducing energy consumption, for instance. We should have always been operating smartly and efficiently yet many in the industry were just operating as fast as they could with the priority of making sales. There was no incentive nor time to operate efficiently. Now we really have to buckle our belts and cut costs since the sales are no longer there and there is more time to look at details in the operation.”

“Weaker players are exiting the marketplace or are being absorbed by stronger players,” Leonard Jackson , a specialist in business development and financial management who teaches at USC Bovard, adds. “Some companies are using available government funding to retool, renovate and get their properties ready to come back once this pandemic is over. In a sense, the industry is righting itself.”

This includes upgrades to laundry facilities, showers and toilets in individual rooms, and other methods to reduce water consumption.

Beltran agrees. “Renovations are taking place left and right,” she says. “Facilities that have been closed are taking the time to renovate and become more efficient.”

The industry is fully embracing corporate social responsibility initiatives, says Jackson. “New buildings are incorporating sustainable practices,” he says. “That was becoming the norm, even prior to COVID, but it will increase. This is all consumer-driven. Consumers generally want to stay and host their events at green facilities.”

“Now there’s the opportunity for tourism and hospitality brands to evolve and become more conscientious to attract people who understand why they need to pay extra for a specific initiative that’s sustainable and more mindful of long-term impact,” notes Anna Abelson , a destination marketing expert who teaches Marketing Strategies for Hospitality and Tourism at USC Bovard.

“Guests know what they want from a business, which is to be sustainably and environmentally responsible, and they only support businesses that go that route,” Jaddoud adds. “That goes for minimizing food waste, consumption of water, use of soap and chemicals, and choosing local produce and supplies.”

The Challenge of Disposables

The industry had been retreating from single-use plastics—including flatware and straws—to meet both consumer demand and increased restrictions on such products in environmentally conscious locales. But with the advent of COVID-19, companies returned to disposables for safety reasons and to boost confidence among consumers.

“Single-use utensils are something you want to get away from if you want to protect the climate, but it’s something we have to have right now,” Abelson notes.

“When companies go back to normal flatware, there will be an additional cost,” Jaddoud adds. “Now flatware has to be cleaned in very specific temperatures, using specific chemicals and processes. But at the end of the day, it’s safety that counts.”

He observes that such corporate decision-making revolves around market specifics as well as venue type. For example, he says a steakhouse or other upscale restaurant will avoid disposables whereas in a grab-and-go setting, consumers find them acceptable.

Beltran, however, says she is seeing more travelers willing to pack their own utensils and straws, as well as coffee mugs and water bottles. “The culture of the consumer is changing,” she says. “In addition to being more conscientious about bacteria, germs and viruses, they also want to reduce waste. It’s still going to take some time before we all get there. But it’s changing on both ends—the consumer and the industry.”

This move toward more sustainable practices will only increase, experts predict.

“Changes to operational practices that consumers were asking for during COVID are going to become the norm,” says Jackson. For instance, many restaurants have eliminated printed menus entirely, using QR codes scanned by customers to electronically access menu options. More patrons have opted to forgo hotel room cleaning. “If these trends continue, hotels and restaurants will benefit from an operational standpoint, while reducing their carbon footprint,” he says.

High-Tech vs. High-Touch

Meanwhile, certain trends already underway have sped up. For example, the pandemic expedited the industry’s move to contactless interactions—from hotel check-in to food ordering to booking and boarding flights, Jaddoud notes.

“COVID is reorganizing our industry, and we’re going to emerge stronger, leaner and more technologically savvy,” Jackson adds.

Yet that doesn’t mean the field will lose its human aspect. “Hospitality will always be a human interaction-driven industry but the pandemic has changed the preferences and tastes of the consumer,” Jaddoud says.

“Technology will be important, but hospitality brands should certainly keep that high-touch focus at the forefront, because technology is just one side of the coin,” Abelson agrees. “To build loyalty with customers, you need to make sure that you understand and customize their experience based on their needs and preferences so you really create that meaningful relationship for years to come.”

Retraining the Hospitality Workforce

Personnel must also keep pace with these changes. The WTTC notes that 68 percent of the travel and tourism workforce require some re-skilling in light of innovations occurring throughout the industry. Hospitality companies are also amping up efforts to attract and retain a more diverse talent pool.

The sector is training staff to implement contactless service and heightened hygiene measures, from sophisticated room cleaning approaches to and other protocols that build consumer confidence while protecting customer and employee safety. At many locations, employees will need to be taught how to take guests’ temperatures or how to manage visitors who refuse to comply with health-related policies. Other venues are introducing robots and other advanced technology to aid in the disinfecting process, and staff need to be educated on those efforts as well as encouraged to suggest new innovations.

“Hospitality is becoming more of a career path and not just a paycheck,” Jaddoud says. “This shift has happened in just the last few years—from both the employee and employer standpoint. It has made the hospitality industry better because when you have higher retention, you have more engagement and loyalty from the guests—and reduced training and turnover costs.”

Tourism and hospitality degree programs have seen a surge in applications as a result.

“New job profiles are emerging,” Beltran notes. “These include new positions that merge safety, quality and sustainability.”

The result will be more opportunity.

“I believe it’s the perfect time to be studying the hospitality environment,” Jaddoud says. “When companies come back, they’re going to be looking for more educated, critically thinking employees who are able to drive the industry forward.”

Students in the USC Bovard MS program come from a wide range of sectors within hospitality and tourism, including food and beverage, hotels, government tourism authorities, airlines, cruises, resorts and casinos. “It adds a lot of value,” Jaddoud says of the breadth of backgrounds represented. “Skills are transferable between all segments of hospitality and tourism.”

“Our industry is multifaceted. Students also learn from each other because everybody brings a different perspective,” says Abelson, who adds that students also vary in terms of their expertise and current roles within the industry. “Some have significant experience but want validation or to fine-tune their skills, and some are learning from the ground up,” she notes. “They’re a very impressive group of people who learn and apply the skills or knowledge right away.”

Learn more about the MS in Hospitality & Tourism program .

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Global trends in hospitality ☆

Lerzan aksoy.

a Fordham University, Gabelli School of Business, New York, NY, United States

Sunmee Choi

b School of Business, Yonsei University, Seoul, South Korea

c Dean of College of Business and Management, VinUniversity, Hanoi, Viet Nam

Tarik Dogru

d Florida State University, Dedman College of Hospitality, Tallahassee, FL, United States

Timothy Keiningham

e St. John’s University, Peter J. Tobin College of Business, Queens, NY, United States

Melanie Lorenz

f Florida Atlantic University, College of Business, Boca Raton, FL, United States

J. Bruce Tracey

g Cornell University, School of Hotel Administration, SC Johnson College of Business, Ithaca, NY, United States

The disruptions to the global hospitality industry have been accelerated, particularly after the emergence of the COVID-19 pandemic. As such, it is even more important for scholars to focus on future research that addresses the most relevant and important industry-specific challenges. In this paper, we analyze the recent hospitality research and industry trends to identify the topics that have received the most attention, and then compare these trends to the survey results from two key industry stakeholders – academics (N = 67) and practitioners (N = 235) – regarding the most important short- and longer-terms research priorities. Overall, the findings suggest that both stakeholder groups have placed supply and demand characteristics, as well as technology, as the industry’s most pressing priorities in both the short- and longer-term future. The relative importance of safety and cleanliness is expected to decline over time while environmental sustainability will gain increasing attention in the future.

1. Introduction

The global hospitality industry, which includes hotels and other types of accommodations, as well as restaurants, bars, casinos, cruise ships, travel agencies, tour operators, and similar organizations, accounted for roughly $4.5 trillion in consumer spending during 2020 ( Hospitality Global Market Report, 2020 ). More broadly, the travel and tourism segments accounted for 10.3% of the global GDP in 2019, totaling $8.9 trillion ( WTTC, 2020b ). Unfortunately, it is not surprising that many of the firms that operate within service- and labor-intensive industries have suffered immensely because of the COVID-19 pandemic. As a result of the extensive scope of this global crisis, pre-pandemic industry trend projections alone are unlikely to be helpful in guiding future academic research and managerial actions. The overarching aim of this research is to provide needed insight into the most important short- and long-term trends from the perspectives of hospitality academics and practitioners by combining historic trends with prognostications from both such stakeholders.

This investigation is conducted in three parts: (1) a review of articles in the leading academic hospitality journals; (2) a review of articles in hospitality trade journals; and (3) a survey of hospitality academics and practitioners. By doing so, we identify critical gaps in the literature and significant differences in the perspectives of academics and practitioners—both in terms of established areas of interest and their future expectations.

As might be expected, the findings point to a short-term focus on disease prevention and related issues, which subsequently declines in importance over the longer term. Nonetheless, technology and supply and demand issues stand out amongst both academics and practitioners alike as key trends in both the short- and long-term. In general, however, when significant differences exist between academics and practitioners (e.g., sustainability, branding), practitioners tend to place greater importance on more immediate financial well-being needs, while academics focus on broader, longer-term trends. By identifying the gaps in the literature and differences in the perceived importance of various trends, this investigation offers insight for rigorous and relevant academic research agendas to help guide the recovery of the hospitality industry through the extreme turbulence caused by COVID-19.

2. Literature review

2.1. scope: global hospitality industry.

The travel and tourism sector is recognized as an important driver for job creation and a dynamic engine of employment opportunities ( Dogru and Bulut, 2018 , Wttc, 2020a ). In 2019, one in 10 jobs (total 330 million jobs) were supported by the global travel and tourism sector, and one quarter of all net new jobs were created by this sector over the last five years ( WTTC, 2020b ).

In 2020, however, this industry faced unprecedented challenges and threats from the impact of the COVID-19 pandemic ( WTTC, 2020b ). Community lockdowns, social distancing requirements, stay-at-home orders, travel and mobility restrictions, and dining limitations have resulted in a temporary suspension of many hospitality businesses and significantly decreased the demand for businesses that were allowed to continue to operate ( Bartik et al., 2020 , Gursoy and Chi, 2020 ). While the optimistic scenario projects a 30% reduction in jobs and GDP compared with 2019, the pessimistic scenario projects a 60% reduction in jobs and a 62% reduction in GDP compared with 2019 ( WTTC, 2020b ).

Of all industries, the global hospitality industry is among the hardest hit, while facing reductions of >90% of activities in some markets ( Fernandes, 2020 ). An above average representation of SMEs in sectors such as accommodation and food services have been particularly affected by the crisis ( OECD, 2020 ). As of 22 June 2020, 513 companies in the restaurant segment filed for bankruptcy ( WTTC, 2020c ). Large firms have also suffered from the downturn ( WTTC, 2020c ). For example, Marriott International, which has 174,000 employees globally, placed tens of thousands of workers on furlough, and Hilton Worldwide notified lenders in March 2020 that they would be borrowing a precautionary $1.75 billion under a revolving loan to preserve money and to maintain flexibility ( Nicola et al., 2020 ).

In contrast, it has been suggested that the travel and tourism sector is poised to be the key sector in driving the recovery of the global economy post COVID-19 by generating new jobs, driving visitors back to destinations, and having a positive economic domino effect on suppliers across the entire supply chain ( Dogru and Bulut, 2018 , Wttc, 2020a ). Projected recovery plans involve rebuilding traveler confidence, developing innovative and digital technologies, and offering more affordable products ( WTTC, 2020d ). Transitioning from crisis management to recovery, hospitality is preparing for the “new normal” by ensuring operational excellence; assuring a safe experience for staff and guests through enhanced cleanliness and hygiene best practices; rebuilding trust and confidence through transparency and communication; and implementing new enabling policies ( WTTC, 2020e ).

Having discussed the scope, importance, and disciplinary range of the industry as well as the status and future outlook, the next section explores the academic and practitioner literatures to compare – across disciplines – trends that may influence the current and future developments in the hospitality industry. The goals are to derive important insights about the state of the respective literatures, as well as to identify discrepancies between academics and practitioners in an effort to promote research that is more aligned with the industry’s challenges and that helps stimulate timely and actionable solutions. This is particularly important in the time of COVID-19 as traditional ways of doing business have been hampered, and innovative solutions are desperately needed.

3. Study 1: Review & categorization of academic literature

The goal of Study 1 is to gauge what hospitality researchers believe to be the most important industry trends based upon the topics published in some of the leading academic hospitality journals. This effort is intended to provide a broad overview of the current state of the literature, with the expectation that the topics represent what academic researchers perceive to be of current or future importance in the hospitality industry.

3.1. Procedure & samples

To review and categorize the literature comprehensively, we deviated from the traditional literature approach and instead used a systematic review. First, the research team decided to examine the articles that were published in the following five hospitality research journals: Journal of Hospitality & Tourism Research, Cornell Hospitality Quarterly, International Journal of Contemporary Hospitality Management, Tourism Management, and International Journal of Hospitality Management . These journals were selected because they publish research that is directly aligned with industry-specific challenges and priorities, and they are considered leading journals in the hospitality field (e.g., listed as “A” outlets by the Australian Business Deans Council on journal quality). The period of January 2018 to the end of the year 2020 was chosen to reflect the most recent trends, and we examined all articles including the ones published online but not yet in press.

Following the selection of the journals, two coders (both with advanced degrees and conduct hospitality-specific research) independently reviewed all articles (N = 1,459) and coded them based on disciplinary domain (e.g., consumer behavior, human resources, operations management, etc.) and main focus (e.g., use and utility of social media, employee engagement, efficiency, etc.) to identify the academic origin and primary research themes. The number of articles for each of the journals and interrater agreement indices are list in Table 1 .

Articles by journal and interrater agreements.

3.2. Results

The analysis identified five main disciplinary domains: consumer behavior/marketing, organizational behavior/human resource management, strategic management, operations management, and finance/economic/law/accounting. Articles of topics that did not fit any main discipline (e.g., research methodology, education, tourism, literature reviews, food and beverage, and entrepreneurship) were sorted into the category “others”. Of 1,459 articles reviewed, the majority fell into the consumer behavior/marketing discipline (652 articles; 44.69%), followed by organizational behavior/human resource management (280 articles; 19.19%), and strategic management (191 articles; 13.09%). To a lesser extent, articles could be placed into finance/economics/law/accounting (102 articles; 6.99%), or operations management (86 articles; 5.89%). 145 articles were summarized in the “others” category (9.94%). Within each of the disciplines, counts of the key words associated with the main focus of the studies were used to identify the primary trends and research themes. We will discuss the most prominent ones in the following paragraphs. Table 2 provides a complete overview of all trends by discipline, the distribution and count, as well as exemplary citations.

Overview of research trends per discipline.

The major research trends within the consumer behavior/marketing discipline focused on the customer experience (e.g., eWOM, social influences, emotions, and customer satisfaction; 29%), followed by online content (e.g., online reviews, online ratings, social media; 14%), brand and branding issues (e.g., brand love, brand personality, authenticity; 7%), and co-creation (e.g., customer-centricity, user generated content; 7%).

Research in the organizational behavior/ human resource management discipline focused on employee job attitudes and participation (e.g., engagement, innovative and creative behaviors, OCB; 29%), talent, recruiting, and retention management (e.g., job crafting, mentoring, training, selection; 18%), employee well-being (e.g., work-family conflict, work-life balance, burnout, bullying; 16%), and leadership (e.g., ethical, transformational, authentic leadership; 16%).

Strategic management articles examined the impact of firm-level policies, strategies, and practices (e.g., green practices, management strategies, transparency, and accountability; 18%), innovation, intellectual capital, and knowledge (e.g., knowledge sharing, collaboration, product, service, process innovations; 17%), performance management (e.g., profitability, survival, profit chain; 17%), and CSR (e.g., different strategies, influences of CSR on brand equity and reputation; 11%).

Finance/Economics/Law/Accounting articles centered on performance (e.g., efficiency, financial performance matrices and assessments, economic growth, revenue; 32%), governance (e.g., M&A, investments, ownership; 23%), risk (e.g., policy uncertainty, credit risk, risk management; 10%), and local and community impact (e.g., market structure, local environment, discrimination; 10%).

Finally, operations management articles highlighted trends such as revenue management (e.g., pricing, forecasting, modeling, rate conditions, discounting; 34%), technology (e.g., robotics, logistic robots, blockchain, key-less technology; 13%), supply chain, distribution, and procurement (e.g., lean techniques, supplier relationships, transparency; 11%), and sustainability (e.g., waste and water management, carbon footprint, packaging; 9%).

4. Study 2: Review & categorization of trade literature

The goal of Study 2 was to gauge the sentiment of hospitality practitioners and identify what they believe to be the most important topics related to the industry. In general, the expectation is that the topics covered in the hospitality trade literature represent either current needs or expected future needs within the industry. Given the fast turnaround for publication, in comparison to the academic literature, discussed topics may be more time-sensitive and driven by recent development.

4.1. Procedure & samples

To assess topic areas of interest to practitioners, we followed the same process described in the academic literature review and conducted a systematic review of three of the most widely circulated trade publications: Hotel Magazine , Hotels , and Hotel Business . As with the academic literature review, we examined the time period from January 2018 to September 2020, the most recently available issues at the time of writing. It should be noted that while hotels are the featured focus of these outlets, they include content that considers many other industry segments (e.g., food and beverage, OTAs, cruise, etc.).

As before, two coders independently evaluated 1,365 articles and classified each according to content areas discussed. It is important to note that content areas used to code these trade publications were not mutually exclusive, as articles regularly discussed multiple topics (average of 2.06 topics per article). Interrater reliability was calculated using Cohen’s Kappa (k = 0.75, p < .001), indicating substantial agreement between coders ( Landis & Koch, 1977 ).

4.2. Results

Analysis of the text allowed us to define a set of overarching trend categories (see Table 3 for complete overview). Of these 34 trend categories, five (each > 10%), namely technology (e.g., AI, mobile applications, and blockchain; 22%), consumer segments/preferences (e.g. segmentation, guest expectations and experiences; 14%), corporate portfolios (e.g., diversification, expansion; 12%), employee management (e.g., training, education, compensation; 12%) as well as travel and tourism (e.g. travel habits, regional analysis; 11%) accounted for the majority of topics (>70%). Our analysis was based on trade publications with a largely set format, containing designated sections for topics such as food and beverage and design. As such, these categories may be overrepresented in this analysis.

Overview of trade publication trends.

In comparing the results of the academic literature review and the review of trade publications, we see that most interests between academics and practitioners do align. Both groups place considerable emphasis on each of the disciplinary foci, namely, consumer behavior/marketing, organizational behavior/human resource management, strategic management, finance/economics/law/accounting, and operations management. However, and most notably, practitioners seem to place a much greater emphasis on technology than academics, as this is by far the most discussed topic in trade publications.

5. Study 3: Assessment of short- & long-term trends by academics and hospitality industry professionals

The goals of Study 3 were to: (a) gauge what hospitality academics and practitioners believe to be the major trends impacting the industry in both the short-term (1 to 3 years) and long-term (4–10 years); (b) identify any significant differences between these perspectives; and (c) assess the general level of economic optimism regarding the hospitality industry over both the short- and long-term. The need to distinguish one to three year trends from longer term trends in part reflects a desire to mitigate respondents’ expected emphasis on the COVID-19 pandemic; it is hoped that this distinction will allow for the separation of long-term trends from those that may be pandemic-specific. Furthermore, perceptions about economic outlook may differ based on stakeholder status and if so, may offer some explanation for any differences that may be identified.

5.1. Data and measures

Sample : Data for this study was collected via an online survey. As the survey was designed to reach both academic researchers and hospitality practitioners, respondents were drawn from several sources. To gain insight into academia’s perceptions of hospitality industry trends, a survey was sent to the editorial review board members of seven journals: Cornell Hospitality Quarterly , International Journal of Contemporary Hospitality Management , International Journal of Hospitality Management , Journal of Hospitality and Tourism Research , Tourism Management , Annals of Tourism Research , and Journal of Sustainable Tourism . The latter two journals were included to broaden the sample of hospitality scholars and include those who conduct tourism research that informs hospitality management practice. In total, 67 completed responses were received. To gain insight into hospitality practitioners’ perceptions of industry trends, a survey was sent to hospitality school alumni from ESSEC Business School in Paris, France, Cornell University’s School of Hotel Administration (and members of the Advisory Boards of the School’s Centers and Institutes), and Florida State University. In total, 235 completed responses were received. Respondents fell into one of three primary groups: (1) academic (22.2%), (2) current or former hospitality industry practitioner (51.0%), and (3) other (26.8%); the “other” category was largely made up of individuals who supply services to the hospitality industry (e.g., consultant). Overall, the respondents were 62.7% male; 15.2% age 18–34, 44.9% age 35–54, 39.9% age 55 and older; 72.6% White, 14.2% Asian or Pacific Islander, 6.6% Hispanic or Latino, 1.0%% Black or African American, 4.6% Other Racial/Ethnic Identification.

Academic respondents were 36.5% Full Professor (tenured/tenure track), 22.2% Associate Professor (tenured/tenure track), 4.8% Assistant Professor (tenured/tenure track), 1.6% Clinical Professor (non-tenure track), 4.8% Adjunct Professor (non-tenure track), 12.7% Senior Lecturer, 11.1% Lecturer, 6.3% Emeritus Professor (retired). Hospitality practitioner respondents were 27.9% Executive/C-Level Management, 30.5% Administrative (e.g. GM, Restaurant Manager, Department Manager, Assistant Manager, etc.), 12.3% Sales and Marketing, 8.4% Data Analytics, 7.1% Revenue Management, 5.8% Hospitality Operations (e.g. Front Desk Agent, Guest Room Attendant, Guest Service Agent, etc.), 4.5% Human Resources, 3.2% Technology (e.g. System Operator, IT Specialist, etc.). See Fig. 1 for the respective details.

Academic and practitioner positions held by respondents.

In total, respondents were from 42 countries (plus Hong Kong), with 64.5% from the United States. See Fig. 2 for the respective details.

Top 20 countries of respondents.

Measures : The overriding aim of the survey was to identify both short-term (1–3 years) and long-term (4–10 years) trends in the hospitality industry. To help ensure that respondents were prepared to think about these issues separately, the survey began with the following text:

“For the first few questions, we ask that you think about what are the most important 1) short-term trends (current environment through the next 3 years) and 2) long-term trends (4 to 10 years into the future) impacting the hospitality industry separately .”

Respondents were first asked to list “the five most important trends impacting the hospitality industry in the current environment through the next 3 years ”, and their “prediction for the economic health of the hospitality industry in the current environment through the next 3 years ”. Respondents were then asked to list “the five most important trends impacting the hospitality industry over the longer term ( i.e. 4 to 10 years in the future) ”, and their “prediction for the economic health of the hospitality industry over the longer term ( i.e. 4 to 10 years in the future) ”. 1 Additionally, we included two measures that in the context of the pandemic may influence an individual’s disposition and perceptions about what may be important. The first measure included two questions that asked about the economic impact that COVID-19 may have had on respondents: (a) “How has the COVID-19 pandemic impacted your employment status in 2020”, and (b) “How has the COVID-19 pandemic impacted your total household income in 2020?” Response choice alternatives for the first item ranged were: temporarily furloughed, job eliminated, pay reduced without reduction in hours, pay reduced with deduction in hours, accepted buyout package/early retirement, and no change to employment status. Response choice alternatives for the second item were: increased significantly, decreased significantly, and no change in household income related to COVID-19 pandemic.

The second measure assessed the respondents’ general level of optimism and pessimism using the 10-item Life Orientation Test, developed and validated by Scheier, Carver, and Bridges (1994) . A principle components analysis (Varimax rotation, Eigenvalues > 1) revealed three significant factors. Reliability analysis, however, found that only one component achieved a Cronbach’s Alpha level of 0.7 or higher (i.e., 0.717). Specifically, this factor was comprised of three items associated with pessimism: (a) I hardly ever expect things to go my way; (b) If something can go wrong for me, it will; and (c) I rarely count on good things happening to me. Further analyses using median-based groupings on the expected trends and industry economic health indicators, however, revealed very few statistically significant differences (and as a result, very little additional insight). As a result, it appears that respondents’ general level of pessimism has little impact on their perceptions of hospitality trends.

5.2. Analyses and results

Personal Economic Impact of the COVID-19 Pandemic : In contrast to the non-significant findings associated with an individual’s pessimism, there were significant differences in the personal economic impact of the COVID-19 pandemic across the two industry stakeholder groups. Specifically, academic respondents were much less likely to be negatively impacted economically as a result of COVID-19 than were hospitality industry practitioners. Almost 80% of academic respondents (79.7%) indicated that they experienced no change to their employment status as a result of the pandemic. That number dropped to 35.1% for hospitality practitioner respondents (see Fig. 3 ). Similarly, 25% of academic respondents indicated that their household income had dropped significantly because of the pandemic, whereas 61% of hospitality practitioners saw a significant drop in household income (see Fig. 4 ). As such, any differences across the stakeholder groups may be explained in part by the personal economic impact of COVID-19.

Impact of COVID-19 on employment status.

Impact of COVID-19 on 2020 household income.

Expected Industry Health Over the Short- and Long-term : Despite differing levels of economic harm caused by COVID-19 on academics and practitioners, the projected health of the industry in the short- and long-term was remarkably similar among the groups (see Fig. 5 ). That, however, does not mean that there was general agreement in the outlook. Regarding their short-term outlook, both groups of respondents were almost evenly divided as to whether they were optimistic or pessimistic about the future (see Fig. 5 ).

Level of economic optimism for the hospitality industry over the next 3 years Fig. 5 (continued): Level of economic optimism for the hospitality industry over the next 3 years.

Regarding their long-term outlook, however, 75% or more of respondents (regardless of group) were somewhat or very optimistic about the economic health of the hospitality industry (see Fig. 6 ). Moreover, there were no statistically significant differences between the mean levels of economic optimism for any group.

Level of economic optimism for the hospitality industry over the next 4 to 10 years Fig. 6 (continued): Level of economic optimism for the hospitality industry over the next 4 to 10 years.

In sum, we did not observe any salient differences across the industry stakeholder groups regarding perceptions about pessimism and expected industry health. However, the personal economic impact of COVID-19 may explain, at least in part, differences across the stakeholder groups regarding the nature and perceived importance of future industry trends (although we do not make any major claims about the theoretical relevance of this finding).

Most Important Trends Impacting the Hospitality Industry : Respondents were asked to list the five most important trends impacting the hospitality over the short-term (i.e., “current environment through the next 3 years”) and the longer-term (i.e., “4 to 10 years in the future”). To assess the trends proposed by respondents, two independent coders read through all trends collected, and based upon this review developed a mutually agreed upon coding structure. Each coder, working separately, assigned codes to each trend. Codes were then compared for consistency, resulting in an initial agreement rate of 85%. Discrepancies were discussed and resolved for all divergent codes.

Respondents’ perceptions of the most important short- and long-term trends for both hospitality academics and practitioners combined are displayed in Fig. 7 . For the short-term, the most cited topics included: 1) sanitation, cleanliness, and health; 2) demand, supply, and revenue; 3) technology; 4) COVID-19; 5) travel policies and issues, 6) economic and competitive issues; 7) employee well-being; and 8) consumer confidence/sentiment. A similar list emerged for the longer-term priorities, though the relative importance of some topics changed: 1) demand, supply, and revenue; 2) technology; 3) economic and competitive issues; 4) travel policies and issues; 5) sanitation, cleanliness, and health; 6) environmental and sustainability issues; 7) employee well-being; and 8) customer and guest issues.

Expected hospitality trends (all respondents).

The most obvious initial takeaway from examining differences in anticipated short- and long-term trends is the significant and expected decline in pandemic related issues in the longer term. In fact, all significant declining trends have an obvious relationship to concerns over health, safety, and disease prevention. Another major takeaway is the comparatively low perceived importance of environmental and sustainability concerns in the short- versus the long-term (where these concerns rose significantly).

To examine differences by type of respondent, short- and long-term trends were distinguished by academic, hospitality industry, and other employment groups (see Fig. 8 , Fig. 9 , Fig. 10 , respectively). Fig. 8 shows the expected short- and long-term trends for academic respondents. Unlike the aggregate trends shown in Fig. 7 , the pandemic did not alter the top two expected trends; they are the same for both the short- and long-term: (a) technology and (b) demand, supply, and revenue. Moreover, environmental and sustainability mentions rise significantly over the long-term, becoming the third most important expected trend. Pandemic related issues become much less prominent in the longer term, with the highest ranked issue being sanitation (ranked number nine).

Expected hospitality trends (academic).

Expected hospitality trends (hotel industry practitioner).

Expected hospitality trends (other).

Fig. 9 shows the expected short- and long-term trends for hospitality industry respondents. The pattern of responses was similar to those of the academic respondents. The most important trend for hospitality industry respondents is supply and demand/revenue in both the short- and long-term. Technology is similarly important, ranking third in the short-term and second in the long-term. Unlike academic respondents, however, while environmental/sustainability rises significantly over the long-term, it did not reach the top five trends (rising to number seven). Additionally, branding rises significantly in importance over the longer term, becoming the tenth most mentioned long-term trend; by contrast, only 4.3% of academics mentioned branding, making it the twenty-third most mentioned long-term trend.

Fig. 10 shows the expected short- and long-term trends for respondents in the other category (primarily industry supplier) respondents. After examining both the academic and hospitality industry data, it is evident that respondents in this group tend to see trends in the industry differently. For example, technology never rises to the top three trends in either the short- or long-term. Moreover, no trends showed statistically significant increases in importance over the longer term, whereas numerous trends showed significant declines from the short to the long-term. It is possible that these differences are in part, impacted by the diverse nature of respondents’ involvement with and stakeholder position associated with the hospitality industry (e.g., supplier, consultant).

Because one aim of this investigation is to gauge the differences in perspectives between academics and hospitality industry practitioners, Fig. 11 , Fig. 12 provide direct comparisons between expected hospitality trends for these two groups. Examining both the short-term trends ( Fig. 11 ) and long-term trends ( Fig. 12 ) reveals that academics are much more likely to believe that technology related trends are important; this occurs despite technology being a top three trend for both academics and hospitality practitioners. Similarly, academic respondents are much more likely to believe that environmental/sustainability issues represent an important trend; in this case, however, this represents a large difference in the relative perception of this issue as an important trend by the two groups. Environmental/sustainability issues are the ninth most mentioned short-term trend for academics whereas they are the eighteenth most mentioned trend for hospitality industry practitioners. While the perception of this issue becomes significantly more important in the long-term for both groups, it is much more frequently mentioned by academics. Specifically, it is the third most mentioned long-term trend for academics, and the seventh most mentioned trend for hospitality industry practitioners. Another often mentioned trend where academics and practitioners differed significantly is food and beverage in the short-term. In terms of most mentioned short-term trends, the issue is similar for both academics and practitioners (seventh vs. tenth respectively). But in terms of percentage of respondents, almost twice as many academic respondents mentioned the issue compared to hospitality industry practitioners (28.4% vs. 14.3% respectively).

Expected hospitality trends current to 3 years (academic vs practitioner).

Expected hospitality trends 4 to 10 years (academic vs practitioner).

Additionally, academic researchers were more likely to mention innovation as a short-term trend (11.9%) while only 3.0% of hospitality industry practitioners did. By contrast, 13.6% of hospitality industry practitioners mentioned cost control as a short-term industry trend, while only 4.5% of academic respondents mentioned this issue as a priority.

6. Conclusions

Taken together, the results from studies 1, 2, and 3 provide important insights for both academic researchers and practitioners in the hospitality industry. Perhaps the most obvious and expected finding is that COVID-19 has pushed safety, and disease prevention issues to the forefront in the short-term. Moreover, although the importance of these issues appears to decrease over the longer term, given the significant and yet-to-be discovered implications of the current pandemic, we expect continued attention will be given to sanitation, cleanliness, and related issues.

However, our findings also suggest that future research should continue to focus on the topics that were important prior to the COVID-19 pandemic. First, and perhaps reinforced by the pandemic, technology-related issues remain at or near the top for both academics and practitioners in both the short- and long-term. Interestingly, despite technology being much more widely discussed in hospitality trade publications than in the hospitality academic literature prior to the pandemic, academic respondents were significantly more likely to mention technology as an important short- and long-term issue than were hospitality practitioner respondents, making it the most mentioned trend for both time frames. Why trade journals focus more on technology yet academics mention technology more is not possible to determine from this study (particularly given the structured formats and editorial calendars of trade publications), but it does point to a general alignment on the importance of technology between academics and practitioners.

Our review of the recently published hospitality research indicates several opportunities to extend the current body of knowledge about the roles and relevance of technology. For example, several studies have demonstrated positive effects associated with interactive- (e.g., Morosan & DeFranco, 2019 ) and AI-based technologies (e.g., Pillai & Sivathanu, 2020 ) that have been introduced to enhance or improve the consumer experience. These findings point to the need to consider the relative and/or differential influence of emerging technologies for customer satisfaction, loyalty, engagement, and related outcomes. Moreover, Cho, Bonn, Susskind, and Giunipero’s (2018) study on the supplier relationships in the independent restaurant segment demonstrated that information technology may be an important moderator of the relationship between a restaurant’s supplier dependence and market responsiveness. The results from this study suggests that further consideration is needed to examine the multi-level influences associated with technology (e.g. individual/customer versus unit/restaurant), as well as the extent to which technology may be an antecedent, mediator, and/or moderator within technology-embedded frameworks.

Another topic in which hospitality academics and practitioners agreed was the importance of supply, demand, and revenue issues for both the short- and long-term. Interestingly, while the academic literature provides some coverage of these topics (typically under disciplines related to finance/economics/law/accounting and operations management ), the total number of studies in this area was relatively small given its recognized importance by both academics and practitioners. Similarly, the trade literature devoted little space to supply and demand issues (see Table 3 ). However, given the significant economic impact of the COVID-19 pandemic, the need for additional research into issues related to supply, demand, and revenue optimization, at least for the foreseeable future, appears well-justified. For example, studies in this domain have examined the use and applicability of predictive forecasting (e.g., Arbelo, Arbelo-Pérez, & Pérez-Gómez, 2018 ) and revenue management practices (e.g., Noone, Enz, & Canina, 2019 ) within and across industry segments. In addition, studies have demonstrated support for a wide array of individual (e.g., gender; Choi, Joe, & Mattila, 2018 ) and contextual (e.g., rate conditions; Arenoe & van der Rest, 2020 ) factors that may influence both individual- (e.g., consumer price evaluations) and aggregate-level outcomes (e.g., hotel pricing strategies). Thus, and similar to research on technology, we encourage future studies to examine the relative importance of key demand characteristics (e.g., customers’ willingness to pay), as well as explore the relevance of contingencies that may influence the efficacy and utility of demand, supply, and revenue management practices (e.g., distribution channel management).

Another noteworthy finding was the perceived relevance of environmental/sustainability. This issue is widely considered to be important across all industries ( unglobalcompact.org 2020 ), which is consistent with our finding that 41.8% of academic researchers mentioned environmental/sustainability issues as important over the longer term (making it the third most mentioned trend). However, our findings also indicated that this topic has received comparably much lower attention in the academic literature (i.e., 3.7% of all published articles), which is reflected by the dispersed treatment of this topic across multiple disciplines and stakeholder groups (e.g., strategic management, operations management, consumer behavior, etc.) By contrast, 6.4% of trade industry articles covered sustainability issues pre-pandemic. Yet while 19.5% of hospitality practitioners mentioned this issue as an important longer-term trend, it falls to seventh place behind financial and operational issues. Based on these findings, it appears there is a need for multi- and cross-disciplinary studies to extend our understanding about the roles and relevance of environmental and sustainability issues, especially policies, programs, and systems that can be linked to business outcomes that resonate with priorities expressed by industry practitioners (e.g. demand, supply, and revenue).

One noteworthy point of divergence between academics and practitioners is the perceived importance of trends and priorities associated with branding. While branding topics have been widely addressed in both the academic and trade literatures, this topic was seldom mentioned by academic respondents as a short- or longer-term priority. In contrast, 16.9% of hospitality industry practitioners mentioned branding as an important long-term trend. This difference may reflect the general tendency of internal stakeholders (i.e. industry practitioners) to focus more on immediate and tangible concerns versus external stakeholders (i.e., industry-focused academics) who may focus more on more longer-term and broader priorities ( Khan, 2019 , King et al., 2011 , Vong, 2017 , Wenzel et al., 2020 ). We see similar divergence—with likely similar causes—with several other less mentioned trends, such as innovation, differentiation, and cost control.

These findings point to additional opportunities for hospitality academic researchers to address gaps in the literature on topics believed to be important by both academia and practitioners. Moreover, the findings reinforce the need for academic researchers to carefully consider and integrate managerial relevance with academic rigor to their investigations. In this way, academic researchers can better assist the hospitality industry—which has suffered greatly from the pandemic—to recover more quickly and thrive in the long term.

CRediT authorship contribution statement

Lerzan Aksoy: Data curation, Conceptualization, Supervision, Writing – original draft, Writing – review & editing. Sunmee Choi: Methodology, Formal analysis, Data curation, Conceptualization, Writing – review & editing, Writing – original draft. Tarik Dogru: Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing. Timothy Keiningham: Writing – review & editing, Writing – original draft, Visualization, Methodology, Formal analysis, Data curation, Conceptualization. Melanie Lorenz: Conceptualization, Data curation, Formal analysis, Methodology, Validation, Writing – original draft, Writing – review & editing. Dan Rubin: Methodology, Formal analysis, Data curation, Conceptualization, Writing – review & editing, Writing – original draft, Visualization, Validation, Software. J. Bruce Tracey: .

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Biographies

Lerzan Aksoy's research interests are in service research, including customer satisfaction, employee satisfaction, innovation and social innovation, its relationship to loyalty, firm performance and societal wellbeing. A prolific writer, Professor Aksoy has co-authored or edited five books. Her most recent book, The Wallet Allocation Rule, is a New York Times and USA Today bestseller. Professor Aksoy's research has received more than a dozen prestigious scientific awards, including the Marketing Science Institute/H. Paul Root Award from the Journal of Marketing, Citations of Excellence “Top 50” Award and Robert Johnston Outstanding Paper Award (3 times) from the Journal of Service Management. Her articles have been published in top tier journals such as the Journal of Marketing, Journal of Marketing Research, Marketing Science, Journal of Academy of Marketing Science, Journal of Interactive Marketing, Harvard Business Review, MIT Sloan Management Review, Journal of Service Research and Journal of Service Management. She is associate editor for the Journal of Service Research and was selected “Best Reviewer of the Year” among the editorial review board members of both the Journal of Service Research and Journal of Service Management. Dr. Aksoy served as co-chair of AMA SERVSIG (American Marketing Association - Service Special Interest Group) and worked with Filene Research Institute doing research with credit unions. She currently serves on the Board of Trustees of Marketing Edge, is a member of the Academic Council of the AMA and serves as the academic partner for the American Innovation Index. She has also been featured in media including CNN, CNBC and publications such as The Wall Street Journal, BrandWeek and Harvard Business Online. Professor Aksoy is a keynote speaker at academic and industry conferences. She has provided executive training and consulting to credit unions and companies including Sony, Ford, Pfizer, Nielsen and L'Oreal.

Sunmee Choi is Dean of College of Business and Management at VinUniversity in Hanoi, Vietnam, while taking a three-year leave of absence from School of Business at Yonsei University in Seoul, Korea. The areas of her research interest include service operations management, revenue management, demand-forecasting methods, distribution channel management, and customer experience management. Her work has been published in journals such as Journal of Business Research, Journal of Service Management, Cornell Hospitality Quarterly, Journal of Hospitality and Tourism Research, International Journal of Hospitality Management, Journal of Marketing Theory and Practice, Journal of Revenue and Pricing Management, and Journal of Hospitality and Tourism Marketing. Sunmee received her M.S. and Ph.D. from the School of Hotel Administration at Cornell University.

Tarik Dogru earned his doctorate in hospitality management from the University of South Carolina and MBA from Zonguldak Karaelmas University, Turkey. Prior to joining the faculty of the FSU Dedman College of Hospitality, Dr. Dogru served as an assistant professor at Boston University (2016-18), an adjunct faculty member at the University of South Carolina (2013-16), and a research assistant at Ahi Evran University, Turkey (2009-12). He has taught a variety of courses in business and hospitality schools at undergraduate and graduate levels. The range of Dr. Dogru’s research interests spans topics in hospitality finance, corporate finance, behavioral finance, real estate investment, hotel investments, sharing economy, tourism economics, climate change, and block chain technology. Dr. Dogru is a highly productive researcher who publishes in many prestigious hospitality and tourism journals — Tourism Management, Annals of Tourism Research, Journal of Travel Research, International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management, Cornell Hospitality Quarterly, Tourism Analysis, International Journal of Tourism Research, and Journal of Hospitality and Tourism Insights. He serves on the editorial board of Tourism Economics and Tourism Analysis and as a reviewer for several academic journals.

Timothy Keiningham, is the J. Donald Kennedy Endowed Chair in E-Commerce. He received the American Marketing Association’s Christopher Lovelock Career Contributions to the Services Discipline Award for teaching, research, and service that has had the greatest long-term impact on the development of the services discipline. This is the highest award presented in the field of service marketing. Dr. Keiningham was named one of the Top 50 Undergraduate Business Professors by Poets & Quants. He is author of the NY Times bestseller The Wallet Allocation Rule and author/editor of eight other books on customer loyalty. His research has been accepted in top-tier journals in marketing (e.g., Journal of Marketing, Journal of Marketing Research, Marketing Science, Journal of the Academy of Marketing Science), strategy (e.g., Harvard Business Review and MIT Sloan Management Review) and service management (e.g., Journal of Service Research, and Journal of Service Management). His research has received several awards. Dr. Keiningham’s work aims to bridge the gap between leading scientific research and management best practices. To advance management practice and inform his scientific research, he serves as chief strategy and client officer at Rockbridge Associates. Prior to joining Rockbridge, he worked for seventeen years in senior officer positions at Ipsos (the world’s 3rd largest market research firm); the last seven years he served as Global Chief Strategy Officer and EVP at Ipsos Loyalty. Dr. Keiningham received a BA from Kentucky Wesleyan College, an MBA from Vanderbilt University, and a PhD from Staffordshire University (UK).

Melanie Lorenz is an experienced Assistant Professor. A native of Germany, she has worked in banking and consulting. She then decided to become an academic, and earned her PhD in Marketing from the University of Alabama in 2016. She has been an Assistant Professor at the University of Toledo. Her focus is in International Business and Marketing; her research has been published in the Journal of World Business, International Marketing Review, and Academy of Management Learning and Education, among others.

Dan Rubin is assistant professor of marketing at St. John’s University, Peter J. Tobin School of Business. His research focusing on consumer behavior has been published in top-tier journals including the Journal of Consumer Psychology, Journal of Business Research, and Journal of Consumer Marketing. Dr. Rubin received his PhD from Baruch College.

J. Bruce Tracey is the Kenneth and Marjorie Blanchard Professor of Human Resource Management at Cornell University's Nolan School of Hotel Administration, where he has taught courses in human resources and organizational management for undergraduate, graduate, and professional audiences throughout North America, Europe, the Middle East, Africa, and Asia. Professor Tracey's research considers a wide range of topics that examine the effectiveness of HR policies, practices, and systems. His work has been published in diverse outlets such as the Journal of Applied Psychology, Journal of Management, University of Pennsylvania Journal of Labor and Employment Law, and the Cornell Hospitality Quarterly, where he is currently serving in his second term as Editor. Sponsors for Professor Tracey's research and consulting include Four Seasons Hotels and Resorts, Hilton Worldwide, and Marriott International, and he has been cited in the New York Times, Bloomberg, Forbes, USA Today, Fast Company, among other popular press outlets.

☆ Author order is alphabetical. All authors contributed equally.

1 While we initially considered asking respondents to rank-order pre-defined categories and trends based on our academic and practitioner literature review, we decided that the results would not have been able to reflect the unprecedented turbulence in the industry that COVID-19 has created. Thus, open ended questions, while more difficult to code, will provide more in-depth insights.

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