To Airbnb or not to Airbnb: Does Airbnb feel safer than hotels during a pandemic?

Abstract

Airbnb was able to recover faster than hotels from the downturn caused by the COVID-19 pandemic. This research note examines whether Airbnb’s success resulted from tourists feeling safer in Airbnbs due to their greater opportunities for social distancing. Nearly 9500 U.S. adults were surveyed between March 2020 and July 2021, and asked the degree to which they would be concerned about staying in a hotel or Airbnb, within the context of the pandemic. Very similar levels of concern were associated with both lodging types, even as this concern decreased as the pandemic unfolded. The similar levels of concern towards hotels and Airbnbs suggest that other factors better explain Airbnb’s comparatively rapid recovery from the pandemic. Implications and suggestions for future research are discussed.

1. Introduction and background

In the very early days of the COVID-19 pandemic, many people questioned whether the global health crisis would spell doom for Airbnb. For example, a New York magazine headline asked, “Will the coronavirus kill Airbnb?” (Feldman, 2020); a Wired headline questioned, “Is this the end of Airbnb?” (Temperton, 2020); and a Bloomberg headline wondered, “Can Airbnb survive Coronavirus?” (O’Sullivan, 2020). In the academic literature, Dolnicar and Zare (2020) claimed the pandemic had “disrupted the disruptor,” and they predicted the pandemic would permanently push away many of Airbnb’s most profitable hosts. Despite Airbnb’s meteoric rise over the prior decade, a dramatic decline suddenly appeared realistic – tourism had plummeted, future tourists seemed unlikely to choose peer-to-peer rentals with uncertain cleaning standards, and hosts would need to transition their units into long-term rentals to stay afloat.

As expected, Airbnb indeed suffered significant setbacks during the initial COVID-19 outbreak in the spring of 2020. However, as the pandemic progressed, Airbnb was able to rebound much more quickly than hotels. For example, a joint analysis by the hotel analytics firm STR and the Airbnb analytics firm AirDNA, looking at 27 global markets in the summer of 2020, found that the pandemic’s impacts on hotel performance were far more severe than on Airbnb performance (Sanford and DuBois, 2020). In its most recent week of data, for instance, the report noted that hotel revenue per available room (RevPAR) was down 64.8% year-over-year, whereas Airbnb RevPAR was down just 4.5%. Likewise, a more recent analysis by Dogru et al. (2023) concluded that Airbnb entire home listings, which represent the bulk of its properties, overall were not adversely affected by the pandemic, whereas the pandemic had a significant negative effect on hotels. Medeiros et al. (2022), in their analysis of the Nordic and American markets, similarly confirmed Airbnb was far more resilient than hotels during the pandemic. In fact, Airbnb even launched itself as a public company in early December 2020, and earned record revenue in 2021 (Rana, 2022).

One possible explanation for Airbnb’s swift recovery is theoretically rooted in the concept of risk (Williams and Baláž, 2015). Risk is inherent in – and often especially pronounced in – tourism, due to the many uncertainties that characterize travel in unfamiliar environments. Substantial literature has demonstrated that risk perceptions can directly influence tourists’ decision making (e.g., Le and Arcodia, 2018), including regarding Airbnb (Yi et al., 2020). Inadequate cleanliness represents a risk tourists face throughout their travels, and confidence in cleanliness is an especially important dimension of lodging choice (Mody et al., 2022, Sohrabi et al., 2012). Cleanliness also is one factor by which consumers may distinguish between hotels and Airbnbs (Guttentag and Smith, 2017).

During the pandemic, hygiene predictably became even more important for guests of both hotels (Yu et al., 2021) and Airbnbs (Shen and Wilkoff, 2020), as the perceived risk associated with tourism lodging increased (Lee and Deale, 2021). Many lodging companies responded by establishing and publicizing new cleaning processes; for example, Hilton established a “CleanStay” program that was co-branded with Lysol, Marriott launched a “Global Cleanliness Council” and a “Commitment to Clean” program, and Airbnb introduced an “Enhanced Clean” program. Some analysts felt consumers’ increased focus on hygiene could benefit hotels over Airbnb, as hotels employ professional cleaning staff, use industrial-grade cleaning products, and can more easily establish standard cleaning protocols (Glusac, 2020). Indeed, Ozdemir et al. (2021) argued that hotels should tout their professionally-cleaned rooms to highlight their value proposition vis-à-vis Airbnb during the pandemic.

However, as the science regarding the COVID-19 virus increasingly revealed that it spread primarily via respiratory droplets, rather than surface contamination, the social distancing afforded by Airbnbs seemed to offer a safer environment than hotels. Due to their hallways and lobbies, hotels simply could not match the protective isolation offered by many Airbnbs. As one medical director stated in a summer 2020 media story about travel safety when asked whether Airbnbs or hotels were safer: “I think an Airbnb or a condo would be best. A lot of hotels are really taking steps to mitigate risk … [but] it’s indoor with strangers” (Lin-Fisher, 2020). Bresciani et al. (2021) found support for this notion in experimental research that determined the desire for physical distance during the pandemic made people prefer Airbnbs over hotels.

Given the contrasting notions about attitudes towards Airbnb and hotel hygiene during the pandemic, the purpose of this study was to examine whether, within the context of the pandemic, travelers felt more concern towards staying in hotels or Airbnbs. The present study builds on other research on this topic by drawing on the attitudes of nearly 10,000 Americans over the course of the first 16 months of the pandemic. Although Airbnb is examined specifically, the company can be viewed as representative of the broader peer-to-peer short-term rental sector, including companies such as VRBO as well.

2. Methods

A repeated cross-sectional online survey of adults in the U.S. was undertaken. The survey commenced in mid-March 2020, around the very beginning of the pandemic in the U.S., and concluded in early July 2021, by which time all U.S. adults had ready access to vaccines and life had largely returned to normal (prior to the arrival of variants like Delta and Omicron). The survey was distributed twice per week during the first several months, and then reduced to once per week because it was felt that the pandemic environment was no longer evolving as rapidly as it had been at the very beginning of the pandemic. Respondents could only complete the survey one time. The survey was conducted via Mechanical Turk, which has been widely used in tourism research. The primary survey questions of interest for this study were answered by 9489 respondents – 51.8% were male, the average age was 38.8, 76.1% were White, 69.3% had at least a college education, and 65.6% were employed full-time.

The survey instrument (see Appendix A) took approximately four minutes to complete and included questions primarily focused on travel intentions and concerns, as related to the pandemic. Of particular relevance, various items asked respondents, “Considering the Coronavirus, how concerned would you be about…”, with separate items for “staying in a hotel” and “staying in an Airbnb.” These items were answered with a six-point Likert scale that ranged from “Very unconcerned” to “Very concerned.” The use of a six-point scale avoided the possibility that a midpoint would be interpreted in varying ways (Nadler et al., 2015), and six-point scales also are more likely than four- or five-point scales to produce a normal distribution of responses (Leung, 2011). The data were analyzed with paired sample t-tests to identify differences between perceptions of hotels and Airbnbs. In addition, the difference between concerns towards Airbnb and hotels was computed and used as the dependent variable in an ordinary least squares multiple regression that examined the impact of several variables on this difference. These variables included demographic variables – age, gender, ethnicity (dummy coded as White and non-White), and education (dummy coded based on having earned a college/university degree) – together with fear of the Coronavirus (measured on a six-point Likert scale ranging from “Very unfearful” to “Very fearful”) and likelihood of taking an overnight leisure trip within the following six months (measured on a six-point Likert scale ranging from “Extremely unlikely” to “Extremely likely”).

3. Findings

The concern with which respondents viewed hotels and Airbnbs was very similar throughout the course of the study. Using the scale that ranged from 1 = “Very unconcerned” to 6 = “Very concerned,” the average degree of concern associated with hotels was 4.06 (SD=1.51) and the average degree of concern associated with Airbnbs was 4.09 (SD=1.52). While these levels of concern fluctuated throughout the course of the pandemic, they fluctuated in tandem, as can be observed in Fig. 1, which plots the average levels of concern at two-week intervals. Concerns regarding the beach also were included in Fig. 1 as an indicator of face validity, to demonstrate that respondents were thoughtfully considering the various survey items and not simply stating identical levels of concern towards everything.

Fig. 1.

Levels of concern during the pandemic (1 =“Very unconcerned,” 6 =“Very concerned”).

To statistically test the comparative levels of concern towards hotels and Airbnbs, the time period of study was divided into eight periods of 60 days, and paired sample t-tests were performed within each period. The results, as presented in Table 1, show the perceived concern towards hotels and Airbnbs remained similar throughout the different stages of the pandemic. In only one of the eight time periods was the difference between the two lodgings found to be statistically significant, and yet even during that period this statistical significance was driven by the large n value, as the average level of concern only differed by 0.1 on a six-point scale. Moreover, it should be noted that, although concerns regarding hotels and Airbnbs diminished over time, both remained fairly high throughout the study. The scale’s midpoint was 3.5, and this neutral level of concern only was reached in the final period of measurement, after vaccinations had become readily available to all American adults.

Table 1.

Levels of concern associated with staying in a hotel and Airbnb (1 =“Very unconcerned,” 6 =“Very concerned”).

	Hotel	Airbnb
Period	M (SD)	M (SD)	t-test	n
Mar 17 - May 15, 2020	4.48 (1.41)	4.50 (1.41)	t2694 = 1.02, p = .31	2695
May 16 - Jul 14, 2020	4.07 (1.47)	4.17 (1.52)	t1687 = 4.00, p < .01	1688
Jul 15 - Sep 12, 2020	4.08 (1.43)	4.15 (1.43)	t804 = 1.78, p = .08	805
Sep 13 - Nov 11, 2020	4.00 (1.44)	4.01 (1.44)	t899 = 0.38, p = .71	900
Nov 12, 2020 - Jan 10, 2021	4.10 (1.46)	4.05 (1.49)	t798 = 1.39, p = .17	799
Jan 11 - Mar 11–2021	3.81 (1.56)	3.80 (1.56)	t899 = 0.18, p = .86	900
Mar 12 - May 10, 2021	3.60 (1.54)	3.62 (1.55)	t800 = 0.53, p = .60	801
May 11 - Jul 7, 2021	3.50 (1.59)	3.50 (1.56)	t900 = 0.18, p = .86	901

To explore the potential influence of various predictor variables on the difference in concerns towards Airbnb and hotels, a multiple regression analysis was undertaken, with the difference in concerns towards Airbnb and hotels serving as the dependent variable. The regression model exhibited no issues related to multicollinearity, as per the variance inflation factors and tolerance values, nor autocorrelation, as per the Durbin-Watson test. The adjusted R ² value indicated that the model only explained 0.5% of the variance, which was likely somewhat reflective of the very limited difference between the Airbnb and hotel concerns. Nevertheless, the model was found to have significant fit (F _{6, 9390} =9.46, p < .01), and several of the individual coefficients were found to be statistically significant, as can be seen in Table 2. In particular, age was found to be the most influential variable, with older age being associated with an increase in comparative concerns towards Airbnb. Being male and being non-White likewise were linked to increased comparative concerns about Airbnb. On the other hand, having a university education and having increased fear of the Coronavirus were associated with increased comparative concerns about hotels.

Table 2.

Results of the multiple regression analysis.

	B	S.E.	β	t	Sig.
(Constant)	0.00	0.05
Age	0.01	0.00	0.06	5.57	< 0.01
Gender	0.06	0.02	0.03	2.52	0.01
Ethnicity	0.06	0.03	0.03	2.45	0.01
Education	-0.05	0.02	-0.02	-2.28	0.02
Leisure trip intention	0.01	0.01	0.01	0.88	0.38
Coronavirus fear	-0.03	0.01	-0.04	-3.41	< 0.01

4. Discussion and conclusion

This study’s findings demonstrate that Americans were concerned about the prospect of staying in both hotels and Airbnbs during the pandemic, and it was not until vaccines were readily available that this concern abated to neutral levels. Moreover, Americans generally viewed hotels and Airbnbs as similarly risky throughout the first sixteen months of the pandemic. Even as people learned more about the virus’s respiratory transmission, became more accustomed to living in a pandemic, and received vaccinations – all of which precipitated decreased concerns towards different activities – the levels of concern directed towards hotels and Airbnbs remained remarkably similar, even if lower than before. Of the limited differences that were detected, being older, male, and White increased comparative concerns towards Airbnb, and greater education and fear about the virus increased comparative concerns towards hotels. Nonetheless, these variables did not explain much of the variance detected.

The concerns Americans expressed towards staying in both hotels and Airbnbs during the pandemic presumably are reflective of the increased attention tourists placed on hygiene during the pandemic (Shen and Wilkoff, 2020, Yu et al., 2021). These concerns, therefore, justify the efforts lodging companies made to intensify their cleaning activities and publicize these efforts, and the concerns underscore the high levels of perceived tourism risk that defined the pandemic (Lee and Deale, 2021). The lack of major differences between Americans’ concerns regarding hotels and Airbnbs diverges from findings by Guttentag and Smith (2017) and Bresciani et al. (2021) that revealed more pronounced distinctions between how tourists viewed Airbnbs and hotels. Nevertheless, the results align with Mody et al.’s (2022) findings that tourists’ decision-making regarding Airbnb and hotels involves similar levels of importance placed on different lodging attributes. The present study’s findings suggest that the advantages that Airbnbs and hotels each offered during the pandemic – hotels having more professional and standardized cleaning processes, and Airbnbs offering more social distancing – may have cancelled each other out, even as Americans tended to view both forms of tourism lodging as somewhat concerning. Moreover, it seems likely that the unique environment of elevated perceived risk produced by the pandemic (Lee and Deale, 2021) may have flattened some of the perceived distinctions between Airbnbs and hotels, as all tourism lodging experiences came to be seen as risky endeavors.

The finding that increased fear towards the virus was associated with greater comparative concern towards hotels aligns with the notion that Airbnb may have benefited from hygiene concerns. Nonetheless, as mentioned, the associated model provided very limited predictive power, and age was the variable most highly associated with divergent concerns towards Airbnb and hotels. The importance of age is likely reflective of generational differences in Airbnb attitudes, as younger people have been shown to hold more positive attitudes towards peer-to-peer rental platforms and their underlying ethos (Del Chiappa et al., 2021). Consequently, this study’s findings suggest hygiene should not be viewed as the primary reason why Airbnb was able to rebound much more quickly from the pandemic than hotels, and the company’s success must instead be attributed to other possible factors. These alternative explanations likely revolve around how the broader return of tourism was characterized by travel patterns that happened to align closely with Airbnb’s primary markets – leisure (rather than business or group) travel; longer trip durations; and visits to beaches, lakes, mountains, and other smaller communities where short-term rentals are often disproportionately prevalent (Oliver, 2020).

Looking forward, the findings suggest that hotels’ inability to provide social distancing does not seem to have hindered their recovery from the pandemic. Hotels, therefore, presumably will continue to recover as broader tourism patterns increasingly return to normal, such as with multitudes of business travelers descending upon major cities for short stays. Therefore, as an unexpected consequence of the pandemic, perhaps the more significant long-term threat to hotels’ recovery is the possibility that some meaningful portion of business travel will be permanently replaced by the videoconferencing technologies such as Zoom that so many people became accustomed to using. This study’s findings also highlight the ongoing convergence between hotels and Airbnbs (Guttentag and Smith, 2017), and thereby underscore the importance for each to continue emphasizing its value proposition to distinguish itself from the other.

This study sheds important light on consumer attitudes towards hotels and Airbnbs, but also entails various limitations which should be taken into account and which highlight avenues for future research. This study only involved U.S. respondents, and the findings may have differed in other geographic areas with different cultures, economies, or lodging profiles. Also, the data collection concluded in the summer of 2021, meaning it encompassed a significant portion of the pandemic, but as future variants unfortunately have prolonged the pandemic it would be interesting to know how concerns towards hotels and Airbnbs continued to evolve. Finally, this study did not examine what aspects of staying in a hotel or an Airbnb were seen as most concerning, and likewise it did not assess the effectiveness of the lodging companies’ various efforts to assuage pandemic fears with new cleaning protocols. Future research could examine such concerns, and perhaps better reveal what factors influenced individuals to view either Airbnbs or hotels as more concerning. Subsequent research exploring this topic will be helpful not only during a pandemic, but at all times, as hygiene and cleanliness will surely remain key drivers of tourism lodging choice.

Declaration of Competing Interest

None.

Appendix A. Survey instrument

• 1.How many overnight trips have you taken in the past 6 months?
• 2.How fearful are you about the Coronavirus?

  Very unfearful (1) - Very fearful (6)

• 3.Have you or someone close to you been diagnosed with the Coronavirus?
• 4.Due to the Coronavirus, have you cancelled or postponed a trip that had already been booked?

  If more than one trip was cancelled/postponed, please think only about the most recent trip. (Q5-8)

• 5.Who made the decision to cancel/postpone the trip?

  Me / Someone else in my travel party (e.g., spouse) / My employer / Conference/event was cancelled

• 6.What type of trip was cancelled/postponed?

  Leisure/vacation / Business (non-conference) / Conference/event / Visiting friends/relatives (4)

• 7.Was the destination within the U.S. / Canada or overseas?
• 8.How were you planning to get to the destination?

  Via car / Via airplane / Cruise

• 9.How likely are you to take the following types of overnight trips within the next 6 months?

  Extremely unlikely (1) - Extremely likely (6)

  Leisure/vacation

  Business (non-conference)

  Conference/event

  Visiting friends/relatives

  Within U.S. / Canada

  Overseas

  Via car

  Via airplane

  Cruise

• 10.To demonstrate your care in answering this survey, please mark "Somewhat agree".

  Strongly disagree (1) - Strongly agree (6)

• 11.Are you delaying booking future travel due to the Coronavirus?
• 12.Considering the Coronavirus, how concerned would you be about.

  Very unconcerned (1) - Very concerned (6)

  Visiting Italy

  Visiting Iceland

  Visiting South Carolina

  Eating at a restaurant

  Riding in a taxi/Uber

  Going to Disney World

  Taking a cruise

  Attending a Broadway show

  Attending a major indoor sporting event

  Hiking in a national park

  Staying in a hotel

  Staying in an Airbnb

  Going to the beach

  Receiving restaurant delivery

• 13.Due to the Coronavirus, one can find significant travel discounts on airfare, hotels, cruises, etc. How likely are you to take advantage of such discounts to take a trip you would not have otherwise taken?

  Very unlikely (1) - Very likely (6)

  On you next trip for leisure/vacation (not to visit family/friends)… (Q14-15)

• 14.How many hours would you consider driving?
• 15.How important would the following be as you select a destination for that leisure/vacation trip?

  Very unimportant (1) - Very important (6)

  Good deals and/or value

  Lots of outdoor attractions/activities

  Strong safety measures at hotels, restaurants, etc.

  Low local infection rates

  Confidence in local response to the pandemic

• 16.How satisfied are you with the U.S. federal government's response to the Coronavirus?

  Very dissatisfied (1) - Very satisfied (6)

• 17.Please indicate how well the following statements describe you.

  Not at all (1) - Very much (4)

  I prefer to visit places that have not been discovered, especially before hotels and restaurants are built.

  I am actively involved in a rigorous physical fitness program.

  I have more energy than most persons my age.

  I make decisions quickly and easily.

• 18.US State or Territory where you live:
• 19.What is your age?
• 20.What is your gender?
• 21.Do you think of yourself as:

  Democrat / Republican / Libertarian / Independent / Other

• 22.Choose the ethnicity that best describes you:
• 23.Please indicate your highest level of education:
• 24.Which of the following best describes your current employment status:
• 25.Please provide any additional comments you may have in the space below: