Category: Sharing Economy

Airbnb and the Hotel Industry: The Past, Present, and Future of Sales, Marketing, Branding, and Revenue Management

October 31st, 2018 in Business Practices, Fall 2018, Hotels, Marketing, Sharing Economy, Technology, Trends 0 comments

By Makarand Mody and Monica Gomez

For a long time, the hotel industry did not consider Airbnb a threat. Both the industry and Airbnb claimed they were serving different markets and had different underlying business models. Over the years, as Airbnb become more successful and grown to being larger than the companies in the hotel industry, the rhetoric has changed. The hotel industry began to realize they had something to worry about.

A stage of denial was followed by the American Hotel & Lodging Association (AH&LA) attacking Airbnb by sponsoring research to demonstrate its negative impacts on the economy and lobbying governments to impose taxes and regulations on homesharing. The association is arguing for a level playing field between homesharing and hotels (and rightly so). The next stage of this battle involves competition and integration. Not only are hotels looking to add homesharing-like attributes and experiences to their properties, to more effectively compete with Airbnb, but are also looking to tap into the platform-based business model that underlies Airbnb’s success.

 

The Past: How does Airbnb impact the hotel industry?

Airbnb’s disruption of the hotel industry is significant, both existentially and economically. A recent study by Dogru, Mody, and Suess (2018) found that a 1% growth in Airbnb supply across 10 key hotel markets in the U.S. between 2008 and 2017 caused hotel RevPAR to decease 0.02% across all segments. While these numbers may not appear substantial at first, given that Airbnb supply grew by over 100% year-on-year over this ten year period means that the “real” decrease in RevPAR was 2%, across hotel segments. Surprisingly, it was not just the economy but also the luxury hotel segment that was hard hit by Airbnb supply increases, experiencing a 4% real decline in RevPAR. The impact of Airbnb on ADR and occupancy was less severe. In Boston, RevPAR has decreased 2.5%, on average, over the last ten years due to Airbnb supply increases. In 2016 alone, this 2.5% decrease in RevPAR amounted to $5.8 million in revenue lost by hotels to Airbnb. Brands that felt the impact the most were those in the midscale and luxury segments, with a decrease in RevPAR of 4.3% and 2.3% respectively. These supply increases are also fueling Airbnb taking an increasing share of the accommodation market pie. For example, in New York City, Airbnb comprised 9.7% of accommodation demand, equaling approximately 8,000 rooms per night in Q1 2016 (Lane & Woodworth, 2016). As a whole, Airbnb’s accommodated demand made up nearly 3% of all traditional hotel demand in Q12016.

Buoyed by a growth rate of over 100% year on year, Airbnb now has over 4 million listings, with the U.S. being its largest market. The company also has significant room to grow in other countries, particularly emerging markets in Africa and India. The company has run into some competition in China, with local rivals Tujia and Xiaozhu. Also, within the U.S., the good news is that Airbnb will not grow at 100% indefinitely and will eventually plateau as it reaches a saturation point (Ting, 2017a). In view of this, the company has turned to alternative strategies to continue to increase supply. It is now targeting property developers to turn entire buildings into potential Airbnb units, through its newest hotel-like brand, Niido. Currently, there are two Airbnb branded Niido buildings in Nashville, TN and Orlando, FL with over 300 units each and Airbnb plans to have as many as 14 home-sharing properties by 2020 (Zaleski, 2018). Niido works by encouraging tenants to list their units on Airbnb, with Airbnb and Niido taking 25% of the revenue generated.  Airbnb has also clearly evolved from its original premise of “targeting a different market” to attracting segments traditionally targeted by hotels, such as the leisure family market, business travelers, and the upscale traveler, as evidenced through its latest offering, Airbnb Plus. These homes have been verified for quality, comfort, design, maintenance, and the amenities they offer. They also have easy check in, premium internet access, and fully equipped kitchens. Their hosts are typically rated 4.8+, and go above and beyond for their guests. Through Airbnb Experiences, travelers can partake in everything from the great outdoors—hiking and surfing—to “hidden” concerts and food and wine tours.  In addition to these products, Airbnb has also “created” its own segments of travelers: novelty and experience seekers who are looking for unique and unconventional accommodation like yurts, treehouses, and boats, all things that a traditional hotel company cannot provide.

 

The Present: Understanding what consumers want lies at the heart of the battle between hotels and Airbnb

There are larger societal trends that are impacting what consumers seek travel, and we think this has implications for the Airbnb and hotel dynamic. These trends include:

  • A shift to a “new luxury”—seeking out unique, authentic experiences that serve as a launchpad for self-actualization—fueled by an increased wealth gap in the United States.
  • An increased mobility, particularly among previously under-represented groups in the United States (the black travel movement, for example) and the global traveler (more Indian and Chinese international travelers than ever before).
  • The changing nature of brand loyalty: from long-term relationships to consumers’ needs for instant gratification and personalization.
  • Changing nature of “ownership”: In a post-consumerist society, the emphasis on “access-based consumption” has put a spotlight on wellness and well-being, beyond materialism.
  • A co-everything world where work, play, and life blend into one seamless mosaic: Technology has changed the way we live our lives, and how we are connected to work, to each other and to the things that drive us. An upcoming 5G world and the IOT is only likely to accelerate the pace of change. Take LiveZoku (https://livezoku.com/), for example: is it a residence? A hotel? A WeWork? A space for the local community? A thriving food and beverage destination? It’s all of these things.

What do these trends mean? They require marketers and experience designers to re-think what the travel experience means to the customer. The notion of the experience economy was created by Pine and Gilmore in 1998, and included four dimensions: escapism, education, entertainment, and esthetic. Leveraging one, or ideally, more of these dimensions creates memorable experiences for customers, which in turn results in brand loyalty. This dynamic has been fairly well-established in the academic literature. However, Airbnb has changed the game for the experience economy by emphasizing the sharing lifestyle and a sense of community, cleverly incorporating the above highlighted trends into its communications with customers. Because of Airbnb popularity and success, six new dimensions have been incorporated into the experience economy, in the context of the travel experience: personalization, communitas, localness, hospitableness, serendipity, and ethical consumerism, as was presented by Mody in 2016.

Interestingly, in a recent study by Mody and colleagues (Mody, Suess, & Lehto, 2017), the researchers found that Airbnb outperformed hotels on all the dimensions of this new, expanded, accommodation experiencescape. Airbnb outperforms hotels in the personalization dimension because of its wide array of homes and locations, enabling genuine micro-segmentation and the “perfect match” between guest and host (Dolnicar, 2018). Moreover, no one home is similar to another, giving customers a unique experience every time, enhancing the serendipity associated with an Airbnb stay. Airbnb elevates the sense of community that consumers seek, particularly when sharing space with other travelers and/or with the host, and allows consumers unparalleled access to “the local”—that café or cute little store that only locals know about. However, there are areas where hotels hold their own. For example, the pathways between these dimensions and memorability were just as strong for hotels as for Airbnb, emphasizing the need for hotels to engage customers by leveraging the “right” dimensions for the brand—dimensions that align with the brand’s mission, story, and personality.

One such dimension where hotels perform just as well as Airbnb is hospitableness, as confirmed in a study by Mody, Suess, and Lehto (2018). More “investor units” on the Airbnb platform means that the host is often not present when guests arrive to the home; moreover, all communication is done electronically and with someone who “manages” the Airbnb unit and doesn’t necessarily own or live in it. In turn, hotels that leverage the human factor—the welcome of a friendly check-in agent, the helpfulness of the concierge,  the warm greeting and genuine interaction between guest and food and beverage staff—create more positive emotions, which subsequently lead to higher brand loyalty. It is imperative that hotel brands really think about the high-tech, high touch experience they are looking to provide, particularly in the golden age of brand proliferation that we live in.

 

From a non-experience standpoint, regulation is another bone of contention that merits close inspection. After years of denying that Airbnb was a competitor, in 2016, the American Hotel & Lodging Association first began an extensive lobbying effort for the imposition of taxes and regulations on Airbnb that level the playing field. Over the last couple of years, the voices of the hotel lobby and other community groups have translated into governments taking some action, in the U.S. and abroad. However, in a study of regulation across 12 European and American cities, Nieuwland and van Melik (2018) found that governments have been fairly lenient towards short-term rentals with little to no (meaningful) regulations thus far. Moreover, regulations have been designed to alleviate the negative externalities of Airbnb on neighborhoods and communities rather than to level the playing field between Airbnb and hotels. Another challenge with regulating the peer to peer economy has been enforcement. In New York City, under the Multiple Dwelling law, it is illegal for a unit to be rented out for less than 30 days unless the owner is present in the unit at the time the guest is renting. However, it is still possible to find “entire homes” on Airbnb in New York City, even though, in principle, these typically include homes where the host is not present during the guest’s stay. Moreover, Nieuwland and van Melik (2018) and Hajibaba and Dolnicar (2017) have found that regulations tend to be very similar across cities, without accounting for the specificities of a particular location, which makes the process perfunctory and superficial. There also remains the danger of over-regulating Airbnb, given that there is still very little knowledge about effective ways of regulating these innovations in the sharing economy, thus stifling their potential. Avoid over-regulation is critical, since Airbnb has significant welfare effects in the economy. In addition to stimulating travel to previously inaccessible markets, Airbnb also creates customer surplus (Farronato & Fradkin, 2018), an important economic value measure. Moreover, other research has suggested that the average resident is not as negative towards the Airbnb as media rhetoric might suggest (Mody, Suess, & Dogru, 2018). The need for a data-driven approach to Airbnb regulation remains paramount.

 

The Future: Competing with the sharing economy requires re-thinking the brand and the experience

While regulation is outside the control of the hotel industry, the brand and the customer experience are not. We contend that these are the areas where hotel companies’ efforts need to be focused. Hotels need to re-think the brand promise, both for the parent brand as well as individual brands in the portfolio, and how it defines and shapes the guest experience. Recent research by Mody and Hanks (2018) indicates that while Airbnb leverages the authenticity of the travel experience—by enabling local experiences that provide a sense of self and sense of place, hotel brands that are perceived as being authentic—original, genuine, and sincere—can generate higher brand loyalty. Thus, while it’s hard to compete with homesharing in terms of experiential authenticity, brand authenticity is a pillar on which hotels can build a strong foundation for loyal brand relationships. This is particularly important because while Airbnb promotes experiential authenticity as a key reason to use the brand, most travelers tend to stay with the brand for much more functional requirements, such as space and price (Chen & Xie, 2017; Dogru & Pekin, 2017)

There is no one definition for or manifestation of an “authentic” brand. It’s a perception, a feeling that consumers have about what you stand for. An authentic brand has at its core the brand promise, an authentic value proposition that gives consumers a raison d’etre for associating with the brand. However, what an authentic brand does require is effective storytelling. A brand is perceived to be authentic, if it has an authentic story that feeds it. Brand stories can come from many sources: a brand’s values, personality, heritage, uniqueness, or its quest and purpose. What is important is telling compelling and coherent stories across the brand’s various touchpoints to engage consumers at a visceral, emotional level. Taking off industry blinders, and looking for inspiration outside the hotel industry, is critical. Tom’s Shoes is an excellent example of leveraging its quest—One for One—in creating a compelling brand story. As another example, in an industry typically focused on the in-store, “physical” experience, Burberry has set the gold standard for authentic, digitally-led and emotive storytelling, by looking within and leveraging over 150 years of history (Watch the YouTube Video here). In this vein, we think that Fairfield Inn and Suites’ return to “where it all began”—the Marriott family’s Fairfield Farm in the Blue Ridge Mountains of Virginia— to craft the brand experience of the future, from a design and communications standpoint, is an excellent example of leveraging authenticity and crafting a compelling brand promise (Ting, 2017b).

Another idea that lies at the heat of the brand promise is what we call the experiential value proposition, or EVP. For the longest time, hotel marketers have relied on the guest room as the primary source of value for the guest. But think about the last time you traveled. Was it the prospect of the hotel room that got you excited about your trip? Or was it everything that the hotel enables you to do – the experience outside the guestroom? From experiencing art and music in the lobby to its proximity to the must-do craft beer garden, hotel marketers must realize that it’s the complete package—what’s inside and outside the room—that customers use as cues for making  their decision to choose an accommodation. We call this proposition offered by the hotel—what’s inside and outside the guest room, enclosed within an experience of hospitableness and a connection to humanity—its EVP. We present the EVP in Figure 1.  The EVP mirrors the value paradigm of the modern traveler, something that must be reflected in the hotel brand’s sales, marketing and pricing and revenue management efforts. Thinking about a brand through the lens of the EVP paradigm has the power to re-orient the customer’s mindset from one of price-shopping to experience-shopping.

 Figure 1. The Experiential Value Proposition Framework

How does a hotel marketer apply the EVP paradigm? Its application can open up many avenues. Hotels can start by rethinking the design of their primary digital channels, led by the website by adding more rich, vivid content that goes beyond the guestroom, in order to better integrate aspects of the wider hotel and local experience. The Standard Hotels serves as an excellent example (http://www.standardhotels.com/) Its website feels more like a local lifestyle and culture magazine than a digital media property “selling” a hotel room. The website’s rich images and stories draw the visitor into wanting to learn more about what the brand has to offer. While not every hotel can or would want to go the Standard way, since the brand has its own distinct voice and personality, there is a case to be made for going beyond static images of beds in guestrooms, which tend to blend into one indistinguishable whole after a point, particularly on OTA websites. When was the last time the image of a hotel bed excited you to want to stay there? Yet, when you look at the imagery put out by most hotels, this is what marketers still focus on.

Placing an emphasis on humanity and providing a sense of hospitableness can also enhance a brand’s EVP. Instead of technology replacing the human connection, the industry needs to look for ways in which technology can actually free up employees so that they can spend their time crafting more personal and unique experiences, delighting guests instead of performing routine transactions. Moreover, if the human connection is what people seek out when traveling with Airbnb, why is it that hotel confirmation emails still get sent out by automated systems that highlight the “facelessness” of the hotel entity. Why not use that as an opportunity to truly welcome the guest; a simple touch such as a welcome letter from the GM with his/her photo, or that of an employee who is “assigned” as “your personal host” during your stay can go a long way in emulating the human connection that the sharing economy enables.

The design of the hotel’s public spaces can be used to enhance the guest’s experience of “communitas”. Ian Schrager would agree (Schaal, 2017). After all, with much of Airbnb’s supply being dominated by investor units that provide little or no host contact, what better an opportunity for hotel brands to show that they are the original connectors of human beings? Sheraton has been wise in incorporating some of these communal elements into its brand makeover by introducing productivity tables and studio spaces and a day-time coffee bar that transforms into a bar at night. In terms of another design element, Airbnb’s attractiveness to family and group travelers can be offset by offering connecting and/or multiple rooms for one price, with other experience value-adds thrown in (as with the Marriott family room connecting rooms package.

Finally, the role of the loyalty program cannot be emphasized enough. Loyalty programs must move beyond programmatic levels to being able to leverage data from guest history, social media, and other marketing data sources, powered by predictive analytics, to personalize and individualize the guest experience of the brand. In an age of instant gratification, the loyalty program has to be gamified to unlock value-adds and offer creative bundling.

At the level of the hotel company, beyond the individual brand, the hotel industry has started participating in the home sharing business and is increasingly looking to integrate these platform business models. For example, while Accor purchased Onefinestay, Marriott has teamed up with Hostmaker to create Tribute Portfolio Homes, a partnership that was recently expanded to four European cities (Fox, 2018). From an organic brand development standpoint, Accor’s newest Jo & Joe brand mimics the sharing economy within the confines of a traditional hotel space. Other, more innovative and bold ways of integrating the sharing economy ethos into a hotel could include offering an “Airbnb floor”, an antithesis to the club floor, one that would not offer housekeeping and other hotel services and thus be offered at a lower price. With hotel brands becoming “branded marketplaces” for accommodation and not just hotel rooms, perhaps there is merit in listing hotel rooms on alternative accommodation platforms. HomeAway is already adding hotels to its platform through the Expedia Affiliate Network, while Airbnb is making a push for bed-and-breakfasts and boutique hotels. Homesharing providers hope that by adding these options to their listings, they will fulfill their goal of being “for everyone”, while allowing independent and boutique hotels to reap the benefits of branded distribution at a lower cost than traditional OTA brands.

In sum, hotels must adopt a sales, marketing, and revenue management approach that is both strategic and tactical.

At a strategic level, hotel brands need to re-think their story, and how they portray and fulfill their authenticity and brand promises. At a tactical level, it’s the experience and value beyond the guestroom that must be factored into what is presented to current and potential guests, what they are charged for it, and how it is leverage to create “memorable memories” that lead to higher net promotor scores and brand loyalty. We present a graphical summary of the past, present, and future of Airbnb vs. hotels in Figure 2.

Figure 2. Summarizing the past, present and future of Airbnb vs. hotels


PDF Version Available Here


References
Chen, Y., & Xie, K. (2017). Consumer valuation of Airbnb listings: a hedonic pricing approach. International Journal of Contemporary Hospitality Management, 29(9), 2405–2424. http://doi.org/10.1108/IJCHM-10-2016-0606
Dogru, T., Mody, M., & Suess, C. (2018). Adding evidence to the debate: Quantifying Airbnb’s disruptive impact on ten key hotel markets.
Dogru, T., & Pekin, O. (2017). What do guests value most in Airbnb accommodations? An application of the hedonic pricing approach. Boston Hospitality Review.
Dolnicar, S. (2018). Unique Features of Peer-to-Peer Accommodation Networks. In S. Dolnicar (Ed.), Peer-to-Peer Accommodation Networks: Pushing the boundaries (pp. 1–14). Oxford: Goodfellow Publishers Ltd.
Farronato, C., & Fradkin, A. (2018). The Welfare Effects of Peer Entry in the Accommodation Market: The Case of Airbnb.
Fox, J. (2018). Marriott expands homesharing program in Europe. Hotel Management. Retrieved from https://www.hotelmanagement.net/own/marriott-expands-homesharing-program-to-3-european-cities
Hajibaba, H., & Dolnicar, S. (2017). Regulatory Reactions Around the World. In S. Dolnicar (Ed.), Peer-to-Peer Accommodation Networks: Pushing the boundaries (pp. 120–136). Oxford: Goodfellow Publishers Ltd.
Lane, J., & Woodworth, M. (2016). The Sharing Economy Checks In: An Analysis of Airbnb in the United States. Retrieved from http://www.cbrehotels.com/EN/Research/Pages/An-Analysis-of-Airbnb-in-the-United-States.aspx
Mody, M. A., Suess, C., & Lehto, X. (2017). The accommodation experiencescape: a comparative assessment of hotels and Airbnb. International Journal of Contemporary Hospitality Management, 29(9), 2377–2404. http://doi.org/10.1108/IJCHM-09-2016-0501
Mody, M., & Hanks, L. (2018). Parallel pathways to brand loyalty: Mapping the consequences of authentic consumption experiences for hotels and Airbnb.
Mody, M., Suess, C., & Dogru, T. (2018). Not in my backyard? Is the anti-Airbnb discourse truly warranted? Annals of Tourism Research. http://doi.org/10.1016/j.annals.2018.05.004
Mody, M., Suess, C., & Lehto, X. (2018). Going back to its roots : Can hospitableness provide hotels competitive advantage over the sharing economy ? International Journal of Hospitality Management. http://doi.org/10.1016/j.ijhm.2018.05.017
Nieuwland, S., & van Melik, R. (2018). Regulating Airbnb: how cities deal with perceived negative externalities of short-term rentals. Current Issues in Tourism, 0(0), 1–15. http://doi.org/10.1080/13683500.2018.1504899
Schaal, D. (2017). Ian Schrager Calls Out Hotel Industry’s Airbnb Strategy as Misguided. Skift. Retrieved from https://skift.com/2017/12/08/ian-schrager-calls-out-hotel-industrys-airbnb-strategy-as-misguided/
Ting, D. (2017a). Airbnb Growth Story Has a Plot Twist — A Saturation Point. Skift. Retrieved from https://skift.com/2017/11/15/airbnb-growth-story-has-a-plot-twist-a-saturation-point/
Ting, D. (2017b). Marriott and Choice Take Varied Approaches to Reviving Classic Midscale Brands. Skift.
Zaleski, O. (2018). Airbnb and Niido to Open as Many as 14 Home-Sharing Apartment Complexes by 2020. Retrieved from https://www.bloomberg.com/news/articles/2018-08-14/airbnb-and-niido-to-open-as-many-as-14-home-sharing-apartment-complexes-by-2020

Makarand Mody, Ph.D. has a varied industry background. He has worked with Hyatt Hotels Corporation in Mumbai as a Trainer and as a Quality Analyst with India’s erstwhile premier airline, Kingfisher Airlines. His most recent experience has been in the market research industry, where he worked as a qualitative research specialist with India’s leading provider of market research and insights, IMRB International. Makarand’s research is based on different aspects of marketing and consumer behavior within the hospitality and tourism industries. He is published in leading journals in the field, including the International Journal of Contemporary Hospitality Management, Tourism Management Perspectives, Tourism Analysis and the International Journal of Tourism Anthropology. His work involves the extensive use of inter and cross-disciplinary perspectives to understand hospitality and tourism phenomena. Makarand also serves as reviewer for several leading journals in the field. In fall 2015, he joined the faculty at the Boston University School of Hospitality Administration (SHA). He received his Ph.D. in Hospitality Management from Purdue University, and also holds a Master’s degree from the University of Strathclyde in Scotland.

 

Monica Gomez is a graduate student in the School of Hospitality Administration at Boston University. She received her Bachelor’s degree in Tourism, Recreation, and Sport Management from the University of Florida and has held previous internship positions in hotel operations and event management. She is a member of the Hospitality Sales and Marketing International Association and is interested in hotel revenue management.

The hotel industry’s Achilles Heel? Quantifying the negative impacts of Airbnb on Boston’s hotel performance

October 5th, 2017 in Fall 2017, Finance, Hotels, Sharing Economy 2 comments

Photo by Michael Ivins/Boston Red Sox/Getty Images

By Tarik Dogru, PhD, Makarand Mody, PhD, Courtney Suess, PhD

Airbnb is the largest firm in the sharing economy marketplace, with about 3 million listings, including entire homes, shared rooms, and private rooms—more than the world’s largest three hotel chains combined (IHG, Marriott, Hilton, 2.58 M listings). It has hosted about 50 million guests in 5 years, 30 million of whom were hosted in 2015 alone (Airbnb Summer Travel Report, 2015). Furthermore, Airbnb is valued at around $31 billion. Due to its meteoric rise in popularity and, more importantly, its uncalculated potential impact, it has been in the center of discussions in the world of hospitality and beyond. Specifically, Airbnb might negatively affect the hotel industry if visitors were to shift their demand from hotels to Airbnb accommodations. However, it is not clear whether Airbnb is taking a part from the existing pie or increasing the size of the pie itself.

The increasing number of Airbnb listings might also have undesirable effects on the residential housing market. Homeowners might simply turn their properties into Airbnb listings if they believe they could make more money, which may exacerbate already existing housing problems in cities (Lee, 2016). Furthermore, Airbnb could have an adverse impact on the residents’ quality of life because of nuisances caused by visitors.

The course and the magnitude of these impacts, however, do not go beyond speculation, with the exception of some empirical evidence on the economic impacts supporting both proponents and critics of Airbnb. The results from the most comprehensive study analyzing the effects of Airbnb on the hotel industry showed that a 1% increase in Airbnb listings decreases hotel revenue by 0.04% (Zervas, Proserpio, & Byers, 2016). However, a recent study conducted by STR reported that Airbnb listings did not affect hotel demand and revenues (Haywood, Mayock, Freitag, Owoo, & Fiorilla, 2017). As such, the jury is still out on this issue.

While there are limited studies from which to draw definite conclusions about the effects of Airbnb on the hotel industry, Airbnb founder Brian Chesky claims that the company does not directly compete with the hotel industry because Airbnb guests are not typical hotel customers, but rather those who would have stayed with friends and family during the regular course of their travels (Intelligence, 2017). Although Airbnb argues that it brings new visitors to the markets and that 70% of its listings are outside of hotel districts, a report by Morgan Stanley indicates that about 42% and 36% of Airbnb guests switched from hotels and bed and breakfasts, respectively, whereas only 31% of Airbnb guests are those who would have stayed with friends and family (Intelligence, 2017), thus countering Mr. Chesky’s claims. Furthermore, a recent study conducted in Los Angeles showed that more than 60% of the properties listed on Airbnb are solely used for commercial purposes and are thus excluded from the residential real estate market (Lee, 2016). According to a recent report by CBRE, revenue generated by hosts renting two or more units was about $1.8 billion, and hosts renting ten or more units generated $175 million in 13 major US markets in 2016 (CBRE, 2017).

Airbnb is considered to be one of the major competitors of the traditional lodging industry, considering its market share, value, and potential economic impacts. In a recent study, we analyzed whether Airbnb directly competes with hotels in Boston (see Dogru, Mody, & Suess, 2017). We simply compared Airbnb dynamics with those of the hotel market, including supply, demand, occupancy, ADR, RevPAR, and market share. This study was descriptive in nature mainly due to the unavailability of data and was thus limited in its ability to draw a conclusion about the causal effects of Airbnb on hotels in Boston. We have now obtained a comprehensive dataset that allows us to analyze the effects of Airbnb on hotels. Therefore, we examine the extent to which Airbnb supply affects hotel room revenues (RevPAR), average daily rate (ADR), and occupancy rates (OCC) in the Boston hotel market for the period between July 2008 and June 2017.

Airbnb and Hotel Data          

In our analyses, we consider Airbnb an alternative accommodations company to analyze the effects of Airbnb supply on hotels. The cumulative number of listings created (including entire homes and private and shared rooms) since the introduction of Airbnb constitutes Airbnb supply (hereafter referred to as “total cumulative listings”). Further, we also measure the cumulative number of listings created (including entire homes and private and shared rooms) since the introduction of Airbnb that were active within the past twelve months. That is, an Airbnb unit must have been rented at least once within the past twelve months to be included in our alternative measure of Airbnb supply (referred to hereafter as “active cumulative listings”).

The Airbnb data were obtained from Airdna, a company that provides data and analytics to entrepreneurs, investors, and academic researchers. Hotel data, inclusive of hotels within the Boston metropolitan statistical area (MSA), were provided by Smith Travel Research (STR). The Airbnb data also includes listings from MSA. Put simply, the Airbnb supply and Boston hotel market goes beyond the city of Boston and comprise hotels from the “Greater Boston” area.

Airbnb host Jennifer Lawrence offers a pull-out couch with nearby toiletries that she rents in the living room of her Somerville home on July 12, 2014. Photo source: Boston Globe.

Airbnb host Jennifer Lawrence offers a pull-out couch with nearby toiletries that she rents in the living room of her Somerville home on July 12, 2014. Photo source: Boston Globe.

Column 1 (i.e., All Listings) of Table 1 presents the cumulative total number of listings (i.e., Airbnb supply) as of June 2017, including entire homes, private rooms, and shared rooms, created from the introduction of Airbnb in Boston in July 2008. Column 5 of Table 1 presents the cumulative total Airbnb listings as of June 2017 that were created since the introduction of the Airbnb and were still active within the past 12 months. As the data shows, 16,160 out of 28,957 listings created were still active as of June 2017. Airbnb supply has increased dramatically from 4 units in July 2008 to 28,957units in June 2017. The extreme increase in Airbnb supply is due to the superior flexibility in adding existing residential properties in the market. Indeed, this gives an unfair advantage to Airbnb in competing against the hotel industry because adding a new hotel to the market might take several years.

Table 1. Total number of listings created from the introduction of Airbnb as of June 2017
Total cumulative listings Active cumulative listings*
Year All Listings (1) Entire Home

(2)

Private Room

(3)

Shared Room (4) All Active Listings (5) Entire Home (6) Private Room (7) Shared Room (8)
2008  4  2  2  –  3  2  1  –
2009  59  34  25  –  43  25  18  –
2010  169  90  79  –  119  60  59  –
2011  371  177  189  5  252  118  130  4
2012  861  432  414  15  526  265  253  8
2013  2,214  1,082  1,094  38  1,221  601  604  16
2014  6,295  3,162  3,009  124  2,673  1,372  1,267  34
2015  14,392  7,126  6,882  384  6,202  3,214  2,883  105
2016  23,981  11,890  11,389  702  13,980  7,149  6,498  333
2017  28,957  14,288  13,798  834  16,160  8,152  7,593  395
*Listings with at least one booking within the past 12 months as of June 2017

In addition to the total number of Airbnb listings, it is also important to see the extent to which entire homes, private rooms, and shared rooms constitute the total Airbnb supply. Columns 2, 3, and 4 of Table 1 present cumulative Airbnb supply for entire homes, private rooms, and shared rooms, while Columns 6,7, and 8 present respective figures for our alternative metric of Airbnb supply, active cumulative listings.

To put these figures in perspective, we present the percentages of the supply of entire homes, private rooms, and shared rooms since the introduction of Airbnb in Table 2. Entire home listings comprised the majority of the total listings in Airbnb in most years. While the number of shared rooms appears to be negligible, the supply of private rooms constitutes the second largest Airbnb supply in the market.

Table 2. The percentage of entire home, private room, and shared room listings in Airbnb
Total cumulative listings Active cumulative listings*
Year Entire Home Private Room Shared Room Entire Home Private Room Shared Room
2008 50% 50% 0.0% 66.6% 33.3% 0.0%
2009 57.6% 42.3% 0.0% 58.1% 41.8% 0.0%
2010 53.2% 46.7% 0.0% 50.4% 49.6% 0.0%
2011 47.7% 50.1% 1.3% 46.8% 51.5% 1.6%
2012 50.2% 48.1% 1.7% 50.3% 48.1% 1.5%
2013 48.8% 49.4% 1.7% 49.2% 49.4% 1.3%
2014 50.2% 47.8% 1.9% 51.3% 47.4% 1.2%
2015 49.5% 47.8% 2.6% 51.8% 46.4% 1.7%
2016 49.5% 47.4% 2.9% 51.1% 46.4% 2.4%
2017 49.3% 47.6% 2.89% 50.4% 46.9% 2.4%
*Listings with at least one booking within the past 12 months as of June 2017

 

While the number of listings has reached a striking level within a relatively short period of time, the speed at which new properties are added to the market is even more striking. Figure 1 presents the year-over-year change in Airbnb supply that has remained active within the past 12 months in Boston. Accordingly, the number of total listings that were still active as of June 2017 has increased dramatically by more than 100% each year. The ability to add existing residential properties to the market as part of the Airbnb property supply increases the potential for adverse effects on hotels. As an accommodations platform, Airbnb offers properties that are alternatives to hotels but does not play by the same rules as hoteliers. Adding properties with a pace of 100% increase every year makes hotels vulnerable to the adverse economic effects of Airbnb. Therefore, we further examined the extent to which Airbnb affects the key performance metrics for the hotel industry in Boston.

Figure 1. Year over year change in Airbnb supply

The percentages shown are the year-over-year supply changes in All active listings

The effects of Airbnb on Hotel RevPAR, ADR, and OCC

We utilized a panel data fixed effect regression technique to examine the effects of Airbnb supply on hotel revenues. Similar to the methodology employed in Zervas et al. (2016), we treated Airbnb supply as a variable intervention in time against hotel data in Boston. In particular, this technique allows for the analysis of Airbnb’s effects on hotel revenues by comparing differences in hotel revenues before and after Airbnb’s entry in Boston. We examine the effects of Airbnb supply on hotel room revenues using two measures of Airbnb supply. First, we use cumulative total Airbnb listings that were created since the introduction of Airbnb. Second, we use cumulative total Airbnb listings that were created since the introduction of Airbnb and were still active within 12 months prior to June 2017. We consider an Airbnb listing active if the unit had been booked at least once within the prior 12 months. We also include a number of control variables that might potentially affect hotel room revenues regardless of Airbnb’s entry in these markets. Specifically, we control for the effects of hotel room supply, number of employees in the hospitality sector, population, unemployment rate, and number of airport arrivals in Boston. Table 3 presents the results from the DD regression for the effects of Airbnb supply, both total and active Airbnb supply, on hotel RevPAR, ADR, and OCC.

Table 3. The effects of Airbnb on Hotel Performances in Boston
  Total Airbnb Supply Active Airbnb Supply
RevPAR ADR OCC RevPAR ADR OCC
Log Airbnb Supply -0.025a

(-4.64)

-0.019a

(-4.30)

-0.003c

(-1.67)

-0.027a

(-4.70)

-0.022a

(-4.86)

-0.002

(-1.22)

Log Hotel Supply -2.32a

(-5.75)

0.03

(0.09)

-1.55a

(-9.34)

-2.26a

(-5.66)

0.04 (0.13) -1.52a

(-9.23)

Log Population 1.98c

(1.70)

-0.96

(-1.01)

1.93a (4.00) 1.86

(1.59)

-1.10

(-1.18)

1.93a (3.99)
Log Hospitality Employees 2.13a

(4.91)

1.50a (4.28) 0.41b (2.30) 2.12a

(4.95)

1.61a (4.69) 0.35b (1.98)
Log Airport Arrivals 0.63a

(3.63)

0.26c (1.85) 0.25a (3.53) 0.64a

(3.71)

0.27c (1.95) 0.25a (3.53)
Unemployment Rate -0.05

(-0.04)

-0.74

(-0.81)

0.49

(1.05)

-0.02

(-0.02)

-0.52

(-0.58)

0.38

(0.83)

Constant -39.26a

(-2.84)

0.01

(0.00)

-24.71a

(-4.35)

-37.73a

(-2.74)

1.09 (0.10) -24.45a

(-4.29)

Adjusted R-Square 0.97 0.91 0.97 0.97 0.91 0.97
t-statistics are in parenthesis. a, b, and c denote 1%, 5%, and 10% statistical significance levels, respectively.

The results show that hotel RevPAR, ADR, and OCC were negatively affected by Airbnb. Specifically, a 1% increase in Airbnb supply decreases hotel RevPAR by 0.025% and ADR by 0.02%. These effects might be seen as marginal if Airbnb supply was increasing at only a 1% level. However, our data showed that Airbnb has been increasing more than 100% year-over-year. Thus, a 100% increase in Airbnb supply (as has been the case consistently since 2008) decreases hotel RevPAR by around 2.5%.

We further examined the effects of active Airbnb supply on hotel RevPAR because some of the existing listings might have been inactive and hence might not necessarily affect hotels. Nevertheless, the findings were similar to those of all Airbnb supply. That is, a 100% increase in Airbnb supply decreases hotel RevPAR by 2.7%.

In addition to the examination of Airbnb’s effect on overall Boston hotel market, we also analyzed the effects of Airbnb on the various hotel class segments. The results show that each class segment is negatively impacted by Airbnb. Specifically, a 1% increase in Airbnb decreases hotel RevPAR by 0.015%, 0.043%, 0.021%, 0.024%, 0.032%, and 0.034% in the economy, midscale, upscale, upper upscale, luxury, and independent hotel categories, respectively. Again, these effects might be considered minimal if Airbnb supply was increasing at only a 1% level, but Airbnb supply has been increasing by over 100% year-over-year. Therefore, a 100% increase in Airbnb supply (as has been the case consistently since 2008) decreases hotel RevPAR by 1.5%, 4.3%, 2.1%, 2.4%, 3.2%, and 3.4% in the economy, midscale, upscale, upper upscale, luxury, and independent hotel categories, respectively. Surprisingly and as opposed to the expectations, Airbnb seems to affect luxury hotels more than it affects economy-scale hotels. While midscale hotel room revenues are the most affected by Airbnb, independent hotel room revenues also receive a major hit from Airbnb.

Table 4. The effects of Airbnb on Hotel Performances in Boston: Scales
Economy Mid Upscale Upper Upscale Luxury Independent
Log Airbnb Supply -0.015b

(-2.36)

-0.043a

(-5.61)

-0.021a

(-3.47)

-0.024a

(-3.66)

-0.032a

(-3.68)

-0.034a

(-5.28)

Log Hotel Supply -4.12a

(-8.65)

-1.43b

(-2.62)

-1.67a

(-4.00)

-1.75a

(-3.76)

-3.71a

(-6.02)

-2.64a

(-5.78)

Log Population 2.38c

(1.71)

-0.04

(-0.03)

2.10c

(1.71)

-0.55

(-0.40)

1.32 (0.73) 2.38c

(1.78)

Log Hospitality Employees 2.51a

(4.92)

2.12a

(3.62)

1.59a

(3.54)

2.38a

(4.76)

2.40a (3.62) 2.43a

(4.97)

Log Airport Arrivals -0.82a

(-3.98)

0.37

(1.58)

0.51a

(2.81)

0.95a

(4.67)

0.76a (2.83) 0.67a

(3.38)

Unemployment Rate -3.28b

(-2.44)

-0.01 (0.00) -1.46

(-1.24)

1.10

(0.84)

-2.74

(-1.57)

1.14

(0.88)

Constant -0.61

(-0.04)

-8.01a

(-2.93)

-41.94a

(-2.91)

-6.31

(-0.39)

-11.26

(-0.53)

-47.14a

(-3.00)

Adjusted R-Square 0.95 0.95 0.96 0.96 0.95 0.97
t-statistics are in parenthesis. a, b, and c denote 1%, 5%, and 10% statistical significance levels, respectively.

Discussion and Conclusions

The results from the analyses on the effects of Airbnb on hotel room revenues showed that Airbnb significantly affects hotel room revenues. These effects are not only statistically but also economically significant. For example, in Boston, the 2.5% decrease in RevPAR would amount to a decrease of approximately $4.00 in RevPAR in 2016, given a 100% increase in Airbnb supply in Boston. Based on these results, the economic impact in terms of a loss of total hotel revenues would be $5.8 million in 2016 alone in Boston. The effects of Airbnb on hotel room revenues also influence tax revenues. That is, revenues lost by hotels are likely to reduce tax revenues for cities and local governments. The economic impacts of Airbnb might be better observed once the sharing economy market is regulated. Therefore, future studies are necessary to analyze the tax implications of Airbnb listings.

Nevertheless, Airbnb has become a major phenomenon as an alternative platform for potential hotel guests. Moreover, while Airbnb may provide economic benefits to consumers, it may also offer social benefits (Dogru & Pekin, 2017). Also, Airbnb accommodations may provide substantial economic and social benefits to the city of Boston if these listings are used to accommodate additional tourists. During peak seasons or in the cases of mega-events like the Olympics, the availability of supplementary Airbnb rentals may be more beneficial than building hotels that will later not be utilized at optimal levels (Dogru, 2016).

The sharing economy phenomenon and the economic, social, and technological changes fueling its growth have challenged the hotel industry to rethink its experiential value proposition to the customer (Mody, Suess, & Lehto, 2017). Therefore, traditional hotels should create more opportunities for unique experiences, post more photos of the hotel and guest rooms, provide a family friendly environment, and offer activities for families. In particular, hotel firms might offer alternative packages to attract Airbnb guests, especially when operating at lower occupancies.

This study was an overall investigation of Boston hotel market at the MSA level. Further analyses are necessary to investigate the effects of Airbnb at neighborhood and property levels. Also, additional analysis is required to determine the extent to which Airbnb’s effects on asset-heavy REITs or franchising and management companies vary. Most importantly, overall economic and social impacts of Airbnb on the greater economy (e.g.tax revenues and residents’ quality of life) need to be examined. Therefore, further investigations are necessary to measure the economic and social impacts of Airbnb.

Summary of key findings

  • Airbnb supply has increased dramatically and consistently by over 100% each year, between 2008 and 2017. The majority of this supply has been entire home listings. The flexibility and ease of adding new supply, owing to the lack of government regulation, gives Airbnb an unfair advantage in competing against the hotel industry, because adding a new hotel to the market might take several years.
  • Using a difference in difference (DD) regression analysis, and controlling for a variety of hotel demand and revenue drivers, we found that a 1% increase in Airbnb supply decreases hotel RevPAR by 0.025% and ADR by 0.02%. Thus, a 100% increase in Airbnb supply (as has been the case consistently since 2008) decreases hotel RevPAR by around 2.5%. The effects of “active” Airbnb supply on hotel revenue are higher (2.7% decrease in RevPAR).
  • Similarly, a 100% increase in Airbnb supply (as has been the case consistently since 2008) decreases hotel RevPAR by between 1.5% and 4.3% across the various hotel class segments. While the impact is most pronounced for midscale hotels (4.3%), somewhat surprisingly, luxury hotels have also taken a significant hit (3.2% decrease in RevPAR).
  • The loss in RevPAR has significant economic implications for the hotel industry. For example, the 2.5% decrease in RevPAR in 2016 alone would amount to a total loss in hotel revenues of $5.8 million in Boston and, consequently, a loss of taxation for city and state governments. Over time, at a 100% increase in Airbnb supply every year, these losses add up, and their resulting impacts on other economic vitality indicators for the industry, such as employment rate, and social impact indicators can be significant and must be examined in future research.

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Dogru Headshot

Tarik Dogru earned his Ph.D. in Hospitality Management from University of South Carolina, and holds Master’s degree in Business Administration from Zonguldak Karaelmas University in Turkey.Prior to joining the Boston University School of Hospitality Administration faculty, he was an adjunct faculty at University of South Carolina (2013-2016) and research assistant at Ahi Evran University (2009-2012) in Turkey. He has taught a variety of courses, including Economics, Finance, Accounting, Hospitality, and Tourism in business and hospitality schools. He is a Certified Hospitality Educator (CHE) and holds Certification in Hotel Industry Analytics (CHIA) from American Hotel & Lodging Educational Institute. Tarik’s research interests span a wide range of topics in hospitality finance, corporate finance, behavioral finance, real estate investment trusts (REITs), hotel investments, tourism economics, and climate change.

 

Mody
Makarand Mody, Ph.D. has a varied industry background. He has worked with Hyatt Hotels Corporation in Mumbai as a Trainer and as a Quality Analyst with India’s erstwhile premier airline, Kingfisher Airlines. His most recent experience has been in the market research industry, where he worked as a qualitative research specialist with India’s leading provider of market research and insights, IMRB International. Makarand’s research is based on different aspects of marketing and consumer behavior within the hospitality and tourism industries. He is published in leading journals in the field, including the International Journal of Contemporary Hospitality Management, Tourism Management Perspectives, Tourism Analysis and the International Journal of Tourism Anthropology. His work involves the extensive use of inter and cross-disciplinary perspectives to understand hospitality and tourism phenomena. Makarand also serves as reviewer for several leading journals in the field. In fall 2015, he joined the faculty at the Boston University School of Hospitality Administration (SHA). He received his Ph.D. in Hospitality Management from Purdue University, and also holds a Master’s degree from the University of Strathclyde in Scotland.

 

Suess Raeis New

Courtney Raeisinafchi, Ph.D spent 6 years designing and developing hotels and restaurants with Jordan Mozer and Associates, Ltd., an architecture firm based in Chicago, IL, after completing a bachelors degree at the School of the Art Institute of Chicago where she studied architecture. Some notable projects she was involved in includes Marriott’s Renaissance Hotel, Times Square and Hotel 57 in Manhattan, NY; both hotels have received the International Hotel , Motel and Restaurant Society’s Golden Key Awards for Best hotel design. While drafting new proposals for hospitality projects for Jordan Mozer and Associates in Southeast Asia, she began a masters degree, studying hospitality administration, at the University of Nevada, Las Vegas (UNLV) in Singapore. After graduating, she continued to complete her doctoral degree in Hospitality Administration at UNLV in Las Vegas and studied towards a second masters degree in architecture at UNLV’s School of Architecture. Courtney joined the Boston University School of Hospitality Administration in 2013, where taught the Design and Development Class as well as Lodging Operations and Technology. In 2017, she joined Texas A&M University Department of Recreation, Parks and Tourism Sciences as an Assistant Professor. She is an active quantitative researcher on the topics of hospitality development and built environments, as well as design and atmospherics impacts on consumer behavior.

References
  • CBRE. (2017). Hosts with Multiple Units – A Key Driver of Airbnb Growth. Retrieved from https://www.ahla.com/sites/default/files/CBRE_AirbnbStudy_2017.pdf
  • Dogru, T. (2016). Development of the Hotel Industry in China: Mega-Events, Opportunities, and Challenges. E-review of Tourism Research, 13.
  • Dogru, T., Mody, M., & Suess, C. (2017). Comparing apples and oranges? Examining the impacts of Airbnb on hotel performance in Boston. Boston Hospitality Review, 5(2).
  • Dogru, T., & Pekin, O. (2017). What do guests value most in Airbnb accommodations? An application of the hedonic pricing approach. 2017, 5(2).
  • Haywood, J., Mayock, P., Freitag, J., Owoo, K. A., & Fiorilla, B. (2017). Airbnb & Hotel Performance: An analysis of proprietary data in 13 global markets. Retrieved from http://www.str.com/Media/Default/Research/STR_AirbnbHotelPerformance.pdf
  • Intelligence, B. (Producer). (2017). Airbnb CEO speaks on disrupting hotel industry. Retrieved from http://www.businessinsider.com/airbnb-ceo-speaks-on-disrupting-hotel-industry-2017-3
  • Lee, D. (2016). How Airbnb Short-Term Rentals Exacerbate Los Angeles’s Affordable Housing Crisis: Analysis and Policy Recommendations. Harvard Law and Policy Review, 10, 229-253.
  • Mody, M., Suess, C., & Lehto, X. (2017). The Accommodations Experiencescape: A Comparative Assessment of Hotels and Airbnb. International Journal of Contemporary Hospitality Management.
  • Zervas, G., Proserpio, D., & Byers, J. W. (2016). The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry. Journal of Marketing Research, Research In-Press. doi:http://dx.doi.org/10.1509/jmr.15.0204

Comparing apples and oranges? Examining the impacts of Airbnb on hotel performance in Boston

June 7th, 2017 in Hotels, Sharing Economy, Spring 2017, Trends, Uncategorized 1 comment

Left: Boston-area Airbnb hosts prepares her spare room for rent Right: A suite at the Godfrey Hotel, a recent addition to Boston's hotel offerings. Photo Sources: Getty Images

Left: Boston-area Airbnb hosts prepares her spare room for rent Right: A suite at the Godfrey Hotel, a recent addition to Boston’s hotel offerings. Photo Sources: Getty Images

By Tarik Dogru, Makarand Mody, and Courtney Suess

If you are in the hotel industry, chances are that Airbnb has come up in conversation at some point or another. The sharing economy phenomenon and the economic, social, and technological changes fueling its growth have challenged the hotel industry to rethink its experiential value proposition to the customer (Mody, Suess, & Lehto, in press). Airbnb founder and CEO Brian Chesky tweeted that “Airbnb hosted more than 2 million guests in the past New Year’s Eve,” and that with the last round of financing, which was $1 billion, Airbnb is now valued at $31 billion (Yurieff, 2017). As a result, Airbnb has been at the core of discussions in the world of hospitality and beyond, mainly due to its potential and uncalculated impacts. On one hand, Airbnb might have positive economic impacts on hospitality and tourism institutions, such as restaurants, bars, and other area attractions, through increases in income and job creations. On the other hand, potential adverse economic impacts of Airbnb cannot be overlooked: Airbnb might negatively affect the hotel industry, if visitors were to shift their demand from hotels to Airbnb accommodations. However, it is not yet clear whether Airbnb is taking a share of the existing hotel industry pie or increasing the size of the overall accommodations industry.

LOS ANGELES, CA - NOVEMBER 17: Airbnb founder/CEO Brian Chesky speaks onstage at "Introducing Trips" Reveal at Airbnb Open LA on November 17, 2016 in Los Angeles, California. (Photo by Stefanie Keenan/Getty Images for Airbnb)

Brian Chesky, Airbnb CEO and founder, tweeted that “Airbnb hosted more than 2 million guests in the past New Year’s Eve”. Photo Source: Getty Images. Photo by Stefanie Keenan/Getty Images for Airbnb

The results from the most comprehensive study analyzing the effects of Airbnb on the hotel industry showed that a 1% increase in Airbnb listings decreases hotel revenue by 0.05% (Zervas, Proserpio, & Byers, 2016). Thus, although negative effects on hotel revenues by way of Airbnb were reported in this study, the magnitude of these effects was small in the given location of Texas. On the other hand, a study conducted in Korea showed that Airbnb does not affect hotel revenues at all (Choi, Jung, Ryu, Do Kim, & Yoon, 2015). A recent study conducted by Smith Travel Research (STR) in 13 global markets reported that Airbnb listings did not affect hotel demand and revenues (Haywood, Mayock, Freitag, Owoo, & Fiorilla, 2017).

While there are limited studies from which to draw definitive conclusions on the effects of Airbnb on the hotel industry, according to Mr. Chesky, Airbnb does not directly compete with the hotel industry. He claims that Airbnb guests are not typical hotel customers, but rather those who would have stayed with friends and family (Intelligence, 2017). Although Airbnb argues that it brings new visitors to destinations and that 70% of its listings are outside of hotel districts, a report by Morgan Stanley indicates that about 42% and 36% of Airbnb guests switched from hotels and bed and breakfasts respectively, whereas only 31% of Airbnb guests represent those who would have stayed with friends and family (Intelligence, 2017). Furthermore, a recent study conducted in Los Angeles showed that more than 60% of the properties listed on Airbnb are solely used for commercial purposes and thus are excluded from the residential real estate market (Lee, 2016). According to a recent report by CBRE, revenue generated by hosts renting out two or more units was about $1.8 billion, and hosts renting out ten or more units generated $175 million in 13 major US markets in 2016 (CBRE, 2017). Despite this massive amount of generated revenue, the hosts are generally not paying taxes on their properties.

While there seems to be free-riders on the market that take advantage of the sharing economy platforms like Airbnb by listing multiple properties, based on the current knowledge, it is still not clear whether Airbnb has an adverse effect on the hotel industry. The present study compares the hotel industry and Airbnb in terms of key performance metrics, including occupancy, ADR, and RevPAR, to determine whether and how Airbnb affects the hotel industry in Boston. Boston is a strong hotel market, but italso has a considerable and growing Airbnb supply, so it provides an excellent context for our analysis.

In our analyses, we treated Airbnb as an accommodation firm to analyze whether it is directly competing with hotels in Boston. Accordingly, the number of Airbnb units listed and the number of units rented (including entire homes and private and shared rooms) multiplied by the number of days in a specified time period constitute Airbnb supply and demand figures, respectively. Occupancy, ADR, and RevPAR were calculated following the same methodology used to calculate these statistics in hotel industry. The Airbnb and hotel data were provided by Airdna and STR, respectively. We analyzed data for the period between January 2015 and September 2016.

ANALYSIS

Comparing changes in supply and demand

Tables 1 and 2 present the supply, demand, and revenue statistics for Airbnb and hotels in the city of Boston during the analysis period.

Table 1. Airbnb Supply and Demand

Period Airbnb Supply % Change in Supply Airbnb Demand % Change in Demand
Jan-15 79,110 N/A 575 N/A
Feb-15 85,890 8.6 4,506 683.7
Mar-15 91,710 6.8 7,811 73.3
Apr-15 106,380 16.0 18,733 139.8
May-15 114,330 7.5 30,547 63.1
Jun-15 123,180 7.7 38,545 26.2
Jul-15 122,670 -0.4 51,378 33.3
Aug-15 119,580 -2.5 37,555 -26.9
Sep-15 128,730 7.7 51,757 37.8
Oct-15 142,470 10.7 41,011 -20.8
Nov-15 363,660 155.3 76,451 86.4
Dec-15 383,880 5.6 65,064 -14.9
Jan-16 380,910 -0.8 73,300 12.7
Feb-16 375,480 -1.4 101,409 38.3
Mar-16 372,540 -0.8 112,501 10.9
Apr-16 373,050 0.1 134,951 20.0
May-16 374,970 0.5 137,347 1.8
Jun-16 378,870 1.0 147,947 7.7
Jul-16 385,260 1.7 148,473 0.4
Aug-16 385,620 0.1 123,588 -16.8
Sep-16 390,270 1.2 107,690 -12.9

Table 2. Hotel Supply and Demand

Period Hotel Supply % Change in Supply Hotel Demand % Change in Demand
Jan-15  1,588,843  N/A  896,065  N/A
Feb-15  1,436,512 -9.6  901,459 0.6
Mar-15  1,598,701 11.3  1,200,426 33.2
Apr-15  1,550,910 -3.0  1,216,283 1.3
May-15  1,605,304 3.5  1,328,932 9.3
Jun-15  1,558,800 -2.9  1,357,872 2.2
Jul-15  1,610,760 3.3  1,413,521 4.1
Aug-15  1,616,278 0.3  1,393,622 -1.4
Sep-15  1,564,170 -3.2  1,335,976 -4.1
Oct-15  1,616,340 3.3  1,394,364 4.4
Nov-15  1,564,170 -3.2  1,105,292 -20.7
Dec-15  1,616,309 3.3  906,619 -18.0
Jan-16  1,632,367 1.0  909,132 0.3
Feb-16  1,482,796 -9.2  895,546 -1.5
Mar-16  1,646,410 11.0  1,150,937 28.5
Apr-16  1,593,300 -3.2  1,273,368 10.6
May-16  1,650,409 3.6  1,303,974 2.4
Jun-16  1,603,050 -2.9  1,366,553 4.8
Jul-16  1,656,392 3.3  1,406,893 3.0
Aug-16  1,667,955 0.7  1,403,774 -0.2
Sep-16  1,622,130 -2.7  1,347,565 -4.0

The number of Airbnb listings has increased dramatically from 79,110 in January 2015 to 390,270 in September 2016. While the highest growth in hotel room supply was about 11% month-over-month (in March 2016), Airbnb supply experienced a phenomenal growth rate of 155% (in November 2015). Extraordinary changes in hotel room supply might be due to renovations and the completions of ongoing projects in the pipeline. However, the extreme supply shocks in the case of Airbnb are due to the greater flexibility of adding or removing existing residential properties in the market.

Changes in demand were greater than the changes in supply for both Airbnb and the hotel industry. Yet overall trends indicate that Airbnb experienced greater increases in demand as compared to the increases in the demand for hotel rooms. For example, Airbnb demand increased by 684%, 140%, and 33% in February, April, and July 2015 respectively, whereas hotel demand only increased by 0.6%, 1.3%, and 4.1% during these months. Although the changes in demand for Airbnb and the hotel industry during the analysis period were, for most part, in the same direction (albeit to varying degrees), there were some anomalies where the changes occurred in the opposite direction. For example, in September and November 2015, while hotel demand decreased by around 4% and 21% respectively, the demand for Airbnb accommodations increased by about 38% and 86% respectively. Also, demand for Airbnb accommodations decreased by 21% in October 2015, whereas hotel demand increased by 4% during the same period.

Comparing Occupancy, ADR, and RevPAR

Tables 3 and 4 shows occupancy, ADR, and RevPAR statistics for Airbnb and hotels in the city of Boston during the analysis period.

Table 3. Airbnb OCC-ADR-RevPAR

Period Airbnb Occupancy Airbnb

ADR

Airbnb RevPAR
Jan-15 0.70 $158.86  $1.15
Feb-15 5.20 $133.05  $6.98
Mar-15 8.50 $153.44  $13.07
Apr-15 17.6 $161.00  $28.35
May-15 26.7 $134.61  $35.97
Jun-15 31.3 $186.51  $58.36
Jul-15 41.9 $180.12  $75.44
Aug-15 31.4 $142.24  $44.67
Sep-15 40.2 $183.34  $73.71
Oct-15 28.8 $171.78  $49.45
Nov-15 21.0 $151.97  $31.95
Dec-15 16.9 $149.88  $25.40
Jan-16 19.2 $142.60  $27.44
Feb-16 27.0 $160.89  $43.45
Mar-16 30.2 $156.35  $47.22
Apr-16 36.2 $158.33  $57.27
May-16 36.6 $160.96  $58.96
Jun-16 39.0 $187.26  $73.13
Jul-16 38.5 $176.45  $68.00
Aug-16 32.0 $145.23  $46.55
Sep-16 27.6 $159.41  $43.99

Table 4. Hotel OCC-ADR-RevPAR

Period Hotel Occupancy Hotel

ADR

Hotel RevPAR
Jan-15 56.4 $142.74 $80.50
Feb-15 62.8 $144.29 $90.55
Mar-15 75.1 $170.58 $128.08
Apr-15 78.4 $188.01 $147.44
May-15 82.8 $205.62 $170.22
Jun-15 87.1 $206.68 $180.04
Jul-15 87.8 $200.44 $175.90
Aug-15 86.2 $193.64 $166.96
Sep-15 85.4 $209.00 $178.51
Oct-15 86.3 $220.10 $189.87
Nov-15 70.7 $183.17 $129.43
Dec-15 56.1 $147.97 $83.00
Jan-16 55.7 $146.43 $81.55
Feb-16 60.4 $146.65 $88.57
Mar-16 69.9 $171.94 $120.20
Apr-16 79.9 $201.51 $161.04
May-16 79.0 $207.29 $163.78
Jun-16 85.2 $212.35 $181.02
Jul-16 84.9 $199.52 $169.47
Aug-16 84.2 $198.45 $167.02
Sep-16 83.1 $219.26 $182.15

Hotel occupancy rates decreased to 83% in September 2016 from 85% in the same period of the previous year, whereas Airbnb’s occupancy has seen a greater decrease from 40% to 28% in the same period. In February 2015, Airbnb’s occupancy was around 5% and reached about 28% in September 2016. While Airbnb experienced a dramatic increase in occupancy growth throughout the analysis period, these gains did not seem to affect the hotel industry’s occupancy rates.

Although hotel ADR was generally greater than that of Airbnb, Airbnb’s ADR figures were greater than hotel ADR in three months (January 2015, December 2015, and February 2016). Hotel ADR was $209 in September 2015 and increased to about $219 in September 2016. Despite the lower occupancy in hotels in September 2016 as compared to the same time in the previous year (September 2015), the RevPAR was comparatively higher even after correcting for inflation. (Note: The RevPAR increased from $75.17 to $75.58 based on 1982=100 prices.) A clear trend can be observed in hotel ADR and RevPAR figures through 2015, and this trend seemed to persist in 2016 in terms of the month-over-month growth rates. However, Airbnb ADR and RevPAR seemed to fluctuate throughout 2015 and do not seem to follow a seasonal movement. Indeed, supply and demand dynamics may have caused the changes in Airbnb ADR and RevPAR, where the equilibrium price is set within the Airbnb market. However, the lack of revenue management practices by Airbnb hosts might also have contributed to these fluctuations in ADR and RevPAR.

Boston Change in supply Airbnb vs Hotels

Change in demand Airbnb vs Hotels Boston Change in occupancy Airbnb vs Hotels Boston

Figure 4

Change in RevPAR Airbnb vs Hotels Boston Boston Hotel Perforamnce Trends 2005-2016 12 years

Hotel performance before and after the arrival of Airbnb

We further analyzed the hotel industry trends for Boston during last 12 years (presented in Table 5), both before and after Airbnb’s entry into the market, to determine whether Airbnb has an effect on hotel supply, demand, and revenue dynamics. The hotel room supply has continued to grow, which suggests that hotel industry seem to continue to grow despite the rise of the Airbnb. The hotel industry’s occupancy saw its lowest point in 2009 and reached over 85% in 2015. Although hotel occupancy experienced a few declines year over year, these decreases appear to be due to supply shocks. For example, in 2016, occupancy decreased by about 2.7%; however, supply growth was around 3.7%. That is, the decline cannot be entirely attributed to the growth in Airbnb. Despite the declines in occupancy, both ADR and RevPAR have continued to increase without a decline after the crisis period and around the arrival of Airbnb onto the scene (2008-2009), and reached their peak in September 2016.

Table 5. Historical Hotel Dynamics

Period Supply Demand Occupancy ADR RevPAR
Sep-05 1418370 1092599 77.0  $143.85  $110.81
Sep-06 1460070 1095808 75.1  $152.20  $114.23
Sep-07 1472790 1164487 79.1  $165.97  $131.23
Sep-08 1492830 1105819 74.1  $171.52  $127.06
Sep-09 1504560 1091371 72.5  $143.20  $103.88
Sep-10 1512540 1176147 77.8  $155.26  $120.73
Sep-11 1512810 1225707 81.0  $162.31  $131.51
Sep-12 1528290 1208011 79.0  $170.08  $134.43
Sep-13 1538100 1251193 81.3  $180.20  $146.58
Sep-14 1537860 1306622 85.0  $202.38  $171.95
Sep-15 1564170 1335976 85.4  $209.00  $178.51
Sep-16 1622130 1347565 83.1  $219.26  $182.15

So, has Airbnb impacted hotel performance in Boston? The data suggests “no”!

Hotels were able to sell more rooms over the last 12 years—that is, more people stayed in hotels in 2016 compared to previous years, despite the demand that was captured by Airbnb. Although it is not clear whether the excess demand in the overall accommodations market was created solely because of Airbnb, the additional demand, at least to some extent, could have been accommodated by hotels in Boston. Hotels in the city have, on average, around 83% occupancy. Thus, for example, if the Airbnb guests were to be captured by the hotels in Boston, the average hotel occupancy would have been around 90% in September 2016. However, considering the fact that Airbnb’s ADR was lower than that of hotels ($159 vs. $219), hotels would probably have captured the Airbnb demand within this lower Airbnb price range. It should also be noted that, historically, the hotel occupancy in the Boston market has fluctuated between 74 and 85%. With this in mind, Airbnb does not seem to whip from the hotel industry’s market share, but rather seems to have created new demand. Although correlation does not indicate causation, the correlation coefficients between hotel and Airbnb supply, demand, revenue, occupancy, ADR, and RevPAR (presented in Table 6) also suggest that Airbnb does not seem to adversely affect the hotel industry in Boston.

Table 6. Correlations

Hotel Supply Hotel Demand Hotel Occupancy Hotel ADR Hotel RevPAR
Airbnb Supply 0.386
Airbnb Demand 0.289
Airbnb Occupancy 0.716
Airbnb ADR 0.494
Airbnb RevPAR 0.358

Nevertheless, as Table 7 indicates, Airbnb has been able to increase its market share quite remarkably. In particular, Airbnb’s market share in terms of supply has increased from about 5% in January 2015 to about 19% of the overall accommodation market (i.e., available room nights) in September 2016. Theoretically, the Airbnb supply can be as large as the residential real estate market in a location. However, it takes a few years to develop a hotel and thus boost the hotel room supply in the market, so comparing the market share in terms of supply is less than ideal. Airbnb’s market share in terms of demand also shows significant growth, from less than 0.1% in January 2015 to more than 7% in September 2016. Despite Airbnb’s penetration into the market in terms of supply and demand, Airbnb’s market share in terms of revenues was only around 5.5% in September 2016. The lower market share in revenues is likely due to lower prices compared to those of hotels and the lack of revenue management practices by the Airbnb hosts. While a 5.5% market share in terms of revenue is considerable for a start-up like Airbnb, it should be highlighted that Airbnb seems to have created new demand by increasing the market size. We estimated approximately $15 million in tax obligations based on the revenues generated by Airbnb during 2015-2016, which is similar to the figures found in the recent CBRE report.

Table 7. Airbnb Market Share

Period Airbnb Market Share (Supply) Airbnb Market Share (Demand) Airbnb Market Share (Revenue)
Jan-15 4.74% 0.06% 0.07%
Feb-15 5.64% 0.50% 0.46%
Mar-15 5.43% 0.65% 0.58%
Apr-15 6.42% 1.52% 1.30%
May-15 6.65% 2.25% 1.48%
Jun-15 7.32% 2.76% 2.50%
Jul-15 7.08% 3.51% 3.16%
Aug-15 6.89% 2.62% 1.94%
Sep-15 7.60% 3.73% 3.29%
Oct-15 8.10% 2.86% 2.24%
Nov-15 18.86% 6.47% 5.43%
Dec-15 19.19% 6.70% 6.78%
Jan-16 18.92% 7.46% 7.28%
Feb-16 20.21% 10.17% 11.05%
Mar-16 18.45% 8.90% 8.16%
Apr-16 18.97% 9.58% 7.69%
May-16 18.51% 9.53% 7.56%
Jun-16 19.12% 9.77% 8.72%
Jul-16 18.87% 9.55% 8.54%
Aug-16 18.78% 8.09% 6.05%
Sep-16 19.39% 7.40% 5.49%

While it is still not clear from our analysis whether the increase in overall demand was caused by Airbnb or other economic factors, the descriptive analyses presented in this study suggest that Airbnb does not seem to be competing directly with the hotel industry. However, this was an investigation of the overall hotel market with limited Airbnb data; further analysis is required to determine within-hotel industry effects (e.g. midscale, economy, luxury) and whether Airbnb has a greater impact on asset heavy hotel-REITs or asset-light hotel management and franchising companies (Dogru, 2017a).

With 242 rooms, the Godfrey Hotel is one of many recent additions to Boston’s hotel market. Photo by Pat Greenhouse/The Boston Globe via Getty Images.

Airbnb accommodations may provide substantial financial, economic, and social benefits to the city of Boston if the listings drive additional tourists to the city, which seems to be the case as suggested by our analyses. These benefits include but are not limited to generating additional tax revenues for cities and local governments, especially to neighborhoods not traditionally visited by guests staying within the hotel-dominated areas (Tussyadiah & Pesonen, 2016), and additional income for hosts, which would cause a surge in per capita income. Furthermore, during peak seasons or in the cases of mega-events like the Olympics, the availability of supplementary Airbnb rentals may be more beneficial than building hotels that will later not be utilized at optimal levels (Dogru, 2016, 2017b).

However, the positive economic impacts may not sufficiently compensate for the potential decline in residents’ quality of life. Airbnb could have an adverse impact on the quality of life of local residents in neighborhoods that contain Airbnb offerings because of nuisances and disruptions caused by visitors. Also, the increasing number of Airbnb listings might have undesirable effects on the residential housing market. Homeowners might simply turn their properties into Airbnbs if they believe they can make more money, which may exacerbate preexisting housing problems in metropolitan cities (Lee, 2016). There is little empirical evidence on the economic or social impacts of Airbnb to support either the proponents or the critics of Airbnb. Thus, the course and the magnitude of these impacts do not go beyond speculation for the time being. Moreover, the economic impacts of Airbnb might be better observed once the sharing economy market is regulated. Therefore, further investigations are necessary to measure the economic and social impacts of Airbnb.

Summary of key findings

  • Airbnb supply experienced more extraordinary “supply shocks” due to flexibility in adding inventory in Boston. Hotel supply displayed a marginal increase over the analysis period.
  • Airbnb experienced greater increases in demand as compared to the increases in the demand for hotel rooms, mirroring the trends in supply growth for the start-up.
  • While Airbnb experienced a dramatic increase in occupancy growth throughout the analysis period, these gains did not seem to adversely impact the hotel industry’s occupancy rates, or either hotel ADR and RevPAR growth rates.
  • Hotel ADR and RevPAR have continued to grow following the arrival of Airbnb onto the accommodation scene, continuing their pre-Airbnb growth momentum.
  • Key performance metrics for Airbnb and hotels indicate a strong positive correlation, suggesting that Airbnb demand is potentially different from hotel demand (i.e., they target different customer segments), and thus, Airbnb’s negative economic impacts on the hotel industry are, at best, marginal.
  • Future research should supplement economic analyses with the profiling of customer segments across the hotel industry and Airbnb and should also examine the social impacts of the sharing economy.


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Dogru Headshot
Tarik Dogru earned his Ph.D. in Hospitality Management from University of South Carolina, and holds Master’s degree in Business Administration from Zonguldak Karaelmas University in Turkey.Prior to joining the Boston University School of Hospitality Administration faculty, he was an adjunct faculty at University of South Carolina (2013-2016) and research assistant at Ahi Evran University (2009-2012) in Turkey. He has taught a variety of courses, including Economics, Finance, Accounting, Hospitality, and Tourism in business and hospitality schools. He is a Certified Hospitality Educator (CHE) and holds Certification in Hotel Industry Analytics (CHIA) from American Hotel & Lodging Educational Institute. Tarik’s research interests span a wide range of topics in hospitality finance, corporate finance, behavioral finance, real estate investment trusts (REITs), hotel investments, tourism economics, and climate change.

 

Mody
Makarand Mody, Ph.D. has a varied industry background. He has worked with Hyatt Hotels Corporation in Mumbai as a Trainer and as a Quality Analyst with India’s erstwhile premier airline, Kingfisher Airlines. His most recent experience has been in the market research industry, where he worked as a qualitative research specialist with India’s leading provider of market research and insights, IMRB International. Makarand’s research is based on different aspects of marketing and consumer behavior within the hospitality and tourism industries. He is published in leading journals in the field, including the International Journal of Contemporary Hospitality Management, Tourism Management Perspectives, Tourism Analysis and the International Journal of Tourism Anthropology. His work involves the extensive use of inter and cross-disciplinary perspectives to understand hospitality and tourism phenomena. Makarand also serves as reviewer for several leading journals in the field. In fall 2015, he joined the faculty at the Boston University School of Hospitality Administration (SHA). He received his Ph.D. in Hospitality Management from Purdue University, and also holds a Master’s degree from the University of Strathclyde in Scotland.

 

Suess Raeis New

Courtney Raeisinafchi, Ph.D spent 6 years designing and developing hotels and restaurants with Jordan Mozer and Associates, Ltd., an architecture firm based in Chicago, IL, after completing a bachelors degree at the School of the Art Institute of Chicago where she studied architecture. Some notable projects she was involved in includes Marriott’s Renaissance Hotel, Times Square and Hotel 57 in Manhattan, NY; both hotels have received the International Hotel , Motel and Restaurant Society’s Golden Key Awards for Best hotel design. While drafting new proposals for hospitality projects for Jordan Mozer and Associates in Southeast Asia, she began a masters degree, studying hospitality administration, at the University of Nevada, Las Vegas (UNLV) in Singapore. After graduating, she continued to complete her doctoral degree in Hospitality Administration at UNLV in Las Vegas and studied towards a second masters degree in architecture at UNLV’s School of Architecture. Courtney joined the Boston University School of Hospitality Administration in 2013. She teaches the Design and Development Class as well as Lodging Operations and Technology. She is an active quantitative researcher on the topics of hospitality development and built environments, as well as design and atmospherics impacts on consumer behavior.

 


References
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