Sharing economy and incumbents' pricing strategy: The impact of Airbnb on the hospitality industry

https://doi.org/10.1016/j.ijpe.2019.03.023Get rights and content

Highlights

  • We study how sharing economy (SE) influences incumbents' price responses.

  • We study how these incumbents' price responses depend on the type of incumbents.

  • We address these questions in the hospitality industry.

  • Low/medium-end hotels set lower prices where SE is stronger only for weekend offer.

  • High-end hotels set higher prices where SE is stronger.

Abstract

In this paper, we examine how the emergence of sharing economy platforms influences incumbents' price responses. Grounding on the literature on price reactions to new entrants and on the unique characteristics of the sharing economy, we argue that the effect of the penetration of the sharing economy on incumbents' prices is not straightforward, and actually depends on the type of incumbents as well as certain product/service offer characteristics. Indeed, relying on a large sample of hotel price offerings from the Italian market, we find that the effect of the growing relevance of the sharing economy (exemplified by Airbnb) on incumbents' prices depends on the type of incumbents (low/medium-end versus high-end hotels) as well as on the accommodation period (weekend versus weekdays), and thus on the type of consumers looking for accommodation. Specifically, low/medium-end incumbents set lower prices in geographical areas where sharing economy has a higher penetration, but this occurs only for weekend accommodation search. In contrast, high-end incumbents tend to set higher prices in geographical areas where sharing economy has a higher penetration, irrespective of the accommodation period. We discuss the important implications of our findings for incumbents, sharing economy platforms, consumers, and policy makers.

Introduction

The recent surge of peer-to-peer platforms has enabled people to collaboratively share and make use of underutilized resources on a massive scale upon payment, giving rise to a new phenomenon commonly referred to as sharing economy (Sundararajan, 2016, Zervas et al., 2017; Jiang and Tian, 2018, Tian and Jiang, 2018). This implies that under sharing economy each consumer can become a product/service provider by exploiting the ownership of certain underutilized resources. Important examples of platforms enabling the sharing economy include Airbnb and Couchsurf in the hospitality industry, Uber, Lyft, Blablacar in the car transportation industry, Mobypark in the parking sector, Borrow my doggy in the domestic animals' market, Lufax in the financial sector (Jiang and Tian, 2018). By activating product/service provision from underutilized resources owned by a plethora of geographically distributed individuals, sharing economy platforms have emerged as an alternative channel to access goods and services traditionally provided by long-established industries, such as car transportation service, hospitality, etc., (Sundararajan, 2016). In fact, this unique and novel characteristic of exploiting underutilized resources owned by a large multitude of geographically distributed individuals translates into very competitive prices offered in sharing economy platforms, thus making them extremely insidious threats to cope with for traditional incumbents operating in these industries (Zervas et al., 2017). The reason is twofold. First, the underutilized capacity relates to resources generally purchased by individuals for other scopes (e.g., private usage/consumption), thus implying that the related costs (e.g., costs such as property taxes, mortgage, maintenance, cleaning, etc., for hospitality providers on Airbnb) are almost entirely covered within those scopes and, at any time, any excess of this capacity can be made available by these individuals on sharing economy platforms with near-zero additional costs to the simple purpose of generating extra-income (Benkler, 2004, Zervas et al., 2017, Blal et al., 2018). Second, the sharing economy reduces barriers to entry as any resource owner can supply his/her resource by simply leveraging on platform services. In turn, very low entry barriers attract a plethora of geographically distributed resource-owners, thus naturally including also providers with very low opportunity cost (i.e., individuals accepting very low extra-income for their shareable resources), which further pushes prices downward. In contrast, incumbents of traditional businesses (e.g., hotels) cannot leverage on such a huge and geographically distributed underutilized resources, and, more importantly, their resources have been acquired for the specific business scope. Therefore, when pricing their product/services they have to take into account all costs involved in the business operations to ensure adequate profitability and maximize the returns of their investments (Einav et al., 2016). This different feature of the sharing economy is likely to impact especially on industries facing high variability in customers' demand, as the newcomers can scale to meet demand more dynamically, given it is easier to adapt the supply when relying on a multitude of small underutilized and geographically distributed resources (Blal et al., 2018).

In particular, the hospitality industry offers all the characteristics required to make peer-to-peer platforms successful, and thus a real threat for the business of traditional firms (e.g., hotels). Indeed, the resources (houses/rooms/beds) are largely available in many geographical areas and, in light of the above arguments, the cost (and thus the minimum affordable price) to offer them in the market is, in general, lower than that of incumbents. Moreover, the financial crisis has increased taxation on properties, unemployment and wealth erosion, which, on the one hand, have jointly induced resource owners (e.g., landlords) to look for additional economic returns from their properties, and, on the other hand, travelers to look for less expensive accommodation solutions. Finally, the transactions between resource providers and travelers can easily be managed online due to the rise of digital peer-to-peer platforms (Constantinides et al., 2018, Rolland et al., 2018; Roma et al. 2018), mimicking already consolidated online travel agents (e.g., Booking.com or Priceline.com).

While the issue of incumbents' reactions to new entries, especially those related to pricing, has been largely studied across many industries in the extant economics and management literature (Bain, 1951, Bresnahan and Reiss, 1991, Frank and Salkever, 1997, Thomas, 1999, Yamawaki, 2002, Ward et al., 2002, Simon, 2005, Goldsbee and Syverson, 2008, Prince and Simon, 2015), the novelty of the sharing economy players highlighted above makes them totally different from traditional new entrants (e.g., a new hotel company entering in the hospitality industry or a new taxi company entering in the car transportation service industry). Indeed, taking advantage of underutilized small resources owned by a multitude of geographically distributed individuals, sharing economy platforms enable the provision of a huge variety of product and/or service solutions differing in terms of hard and soft characteristics as price, geographic location, quality and ability to match a large customers' needs combination (Wang and Nicolau, 2017, Zervas et al., 2017). As a result, the entrance of a sharing economy player is likely to generate a much more disruptive effect on incumbents than traditional new entrants would be able to do (Bower and Christensen, 1995), due to the fact that the latter can hardly count on the same massive capacity offered, the same capillary diffusion, the same offer variety and the same competitive prices enabled by the former. In turn, the greater competitive threat entailed by the growth of sharing economy players should in principle generate neater and more articulated strategic pricing responses of incumbents, which is important to unravel in order to advance theoretical understanding on the competitive strategic interactions determined by new unconventional and disruptive economy models as well as to support pricing decisions of different parties (incumbents, sharing economy players, consumers) facing the sharing economy wave.

Therefore, in this paper, we aim to contribute to the literature on incumbents' pricing reactions to new entries as well as to the nascent literature on the sharing economy by examining how the presence of sharing economy players influences incumbents' price responses and how these price responses depend on the type of incumbents as well as certain product/service offer characteristics. We address these important research questions in the context of the hospitality industry because pricing is one of the most important competitive weapons in this industry, given its intrinsic characteristics. Moreover, there is broad consensus on the fact that the hospitality industry can be considered as exemplificative of the disruptive effect of the sharing economy (Blal et al., 2018).

Specifically, given the absolute prominence of Airbnb as a sharing economy player in this industry, we examine how hotels' pricing strategy is influenced by the growing penetration of Airbnb. We advance that the manner in which the competitive threat exerted by this sharing economy player affects incumbents' pricing decisions is definitely not straightforward. Indeed, relying on data related to Airbnb as well as on a large sample of hotel price offerings (more than 35,000 price offerings from around 2000 hotels) retrieved from the popular hotel booking platform Booking.com in the Italian market, we argue and find that incumbents' price reactions are not uniform. Rather, they vary according to the type of incumbent, the targeted market as well as some offer characteristics. Specifically, in line with classical literature on new entries (e.g., Thomas, 1999, Goldsbee and Syverson, 2008) as well as some initial studies on sharing economy (Hajibaba and Dolnicar, 2017, Zervas et al., 2017), hotels targeting low/medium consumer segments (i.e., 1–3 star hotels) tend to set lower prices in cities where sharing economy (i.e., Airbnb) has a higher penetration and thus represents a more relevant threat, as compared with cities where sharing economy (i.e., Airbnb) has lower penetration. However, in this case we add the novel evidence that this price-lowering effect occurs only for specific types of service offers, i.e., those related to weekend accommodation rather than those related to working days accommodation. This is because, by enabling very competitive prices, sharing economy players in the hospitality industry have emerged as an appealing alternative especially for price-sensitive consumers. Therefore, they tend to be competitors especially for consumers traveling for vacation purposes (leisure travelers), rather than for consumers who travel due to job/business reasons (business travelers) and thus are usually less price-sensitive. More interestingly, we argue and find a positive effect of sharing economy (Airbnb) penetration on prices of hotels serving high-end consumers (i.e., 4–5 star category hotels). That is, these hotels tend to set higher prices in cities where sharing economy attracts more demand and thus represents a more relevant threat to incumbents, and they do it irrespective of the type of service offer (weekend or weekdays accommodation). This apparently counter-intuitive result suggests that the high-end hotels prefer setting higher prices in geographical areas where there is a larger penetration of sharing economy. This is because the greater downward pressure on prices coming from Airbnb implies that high-end hotels should reduce the price of their best deals to the extent that it would be an inconsistent strategy with their higher service quality and thus would be negatively perceived by their core segment (i.e., high-end consumers). Therefore, high-end hotels tend to tilt away from any possible competition with a dangerous and unconventional competitor for more price-conscious consumers, and concentrate more on their core segment. As a consequence, they will try to signal more their higher service quality by limiting the practice of offering best deals (e.g., applying a lower discount on the standard rate or using it less frequently) in areas where Airbnb's penetration is stronger, thus resulting in higher prices in these areas. Overall, our findings suggest that the sharing economy has an impact on the pricing decisions of both types of incumbents, but in a different manner.

The remainder of the paper unfolds as follows. In Section 2 we provide the background of the sharing economy in the hospitality industry. In Section 3 we develop our theoretical arguments and formulate our hypotheses grounding on the relevant literature on incumbents' pricing reactions to new entries, fine-tuned to the sharing economy context. In Section 4 we discuss data and variables employed in this study. In Section 5 we present and discuss our findings and a robustness check. Finally, in Section 6 we conclude providing important implications and tracing avenues for future research.

Section snippets

The background of the sharing economy in the hospitality industry

The hospitality industry is recognized by many sources as the industry where the sharing economy is having the biggest impact, with Airbnb being by far the major sharing economy player in this industry (Blal et al., 2018, Guttentag, 2015, Guttentag and Smith, 2017). In particular, this peer-to-peer platform, founded less than 10 years ago, allows people across the globe to lease or rent short-term lodging and provide travel experiences, especially for consumers who travel for vacation purposes (

Theory on incumbents' pricing reactions to new entries

A large body of literature in economics and management has traditionally investigated how incumbents react to entry threats and actual entries into a market, with considerable emphasis on pricing decisions. As intuition may suggest, most of these studies have demonstrated that prices generally fall in the face of increased competition due to new entries (Bain, 1951, Bresnahan and Reiss, 1991, Goldsbee and Syverson, 2008, Prince and Simon, 2015, Thomas, 1999, Yamawaki, 2002, Windle and Dresner,

Data & variables

To study how sharing economy affects hotel pricing decisions depending on the type of hotel (i.e., the star category) and the period of the accommodation search (weekend or working days), we considered two scenarios: 1) a couple of users looking for an accommodation in Italy during the first weekend of June 2018 (June 1st-June 3rd), which also includes the Italian Republic celebration (June 2nd); 2) a traveler in search of a two-nights accommodation in working days period, and specifically from

Main results

Due to the cross-sectional nature of our full sample, for each scenario (weekend and weekdays trips) we performed robust OLS regression models for the two subsamples of 1–3 star hotels and 4–5 star hotels, respectively, as well as for the full sample. In Table 4 we report the results of the regression models for the weekend trip scenario (which mainly captures the case of accommodation search for short vacation purposes), whereas Table 5 presents the same results for the weekdays trip scenario

Discussion and conclusion

In this paper, we have investigated incumbents' pricing reactions to the growing presence of a novel and disruptive phenomenon, namely the sharing economy. We have discussed the importance to investigate the impact of sharing economy players (e.g., Airbnb, Uber, etc …) on incumbents' business, in light of the fact that, as compared with traditional new entrants, these new players can enable extremely competitive prices and ensure a more capillary diffusion of products/services by relying on

Acknowledgements

The authors would like to thank the Guest Editors of the Special Issue “Innsbruck 2018” and the three anonymous reviewers for their valuable and insightful comments, which helped improve the paper significantly.

References (66)

  • P. Roma et al.

    Price dispersion, competition, and the role of online travel agents: evidence from business routes in the Italian airline market

    Transport. Res. E Logist. Transport. Rev.

    (2014)
  • P. Roma et al.

    Revenue models, in-app purchase, and the app performance: Evidence from the Apple's App Store and Google Play

    Electronic Commerce Research and Applications

    (2016)
  • P. Roma et al.

    The role of the distribution platform in price formation of paid apps

    Decision Support Systems

    (2016)
  • L.A. Thomas

    Incumbent firms' response to entry: price, advertising, and new product introduction

    Int. J. Ind. Organ.

    (1999)
  • R. Torres

    Linkages between tourism and agriculture in Mexico

    Ann. Tourism Res.

    (2003)
  • D. Wang et al.

    Price determinants of sharing economy based accommodation rental: a study of listings from 33 cities on Airbnb.com

    Int. J. Hosp. Manag.

    (2017)
  • R. Windle et al.

    Competitive responses to low cost carrier entry

    Transport. Res. E Logist. Transport. Rev.

    (1999)
  • H. Yamawaki

    Price reactions to new competition: a study from US luxury car market, 1986-1997

    Int. J. Ind. Organ.

    (2002)
  • J. Bain

    Relation of profit rate to industry concentration

    Q. J. Econ.

    (1951)
  • Y. Benkler

    Sharing nicely: on shareable goods and the emergence of sharing as a modality of economic production

    Yale Law J.

    (2004)
  • J. Bower et al.

    Disruptive technologies: catching the wave

    Harv. Bus. Rev.

    (1995)
  • T. Bresnahan et al.

    Entry and competition in concentrated markets

    J. Political Econ.

    (1991)
  • Business Insider

    Airbnb CEO Speaks on Disrupting Hotel Industry

    (2017)
  • R.R. Caves et al.

    From entry barriers to mobility barriers: conjectural decisions and contrived deterrence to new competition

    Q. J. Econ.

    (1977)
  • Y. Chen et al.

    Price-increasing competition

    Rand J. Econ.

    (2008)
  • R.R. Chen et al.

    Opaque distribution channels for competing service providers: posted Price versus Name-Your-Own Price mechanisms

    Oper. Res.

    (2014)
  • P. Constantinides et al.

    Introduction – platforms and infrastructures in the digital age

    Inf. Syst. Res.

    (2018)
  • M.A. Cusumano

    How traditional firms must compete in the sharing economy

    Commun. ACM

    (2015)
  • J. de Figueiredo et al.

    Churn, baby, churn: strategic dynamics among dominant and fringe firms in a segmented industry

    Manag. Sci.

    (2007)
  • A. Dixit

    The role of investment in entry deterrence

    Econ. J.

    (1980)
  • T. Dogru et al.

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

    Boston Hospit. Rev.

    (2017)
  • L. Einav et al.

    Peer-to-peer markets

    Ann. Rev. Econ.

    (2016)
  • R. Frank et al.

    Generic entry and the pricing of pharmaceuticals

    J. Econ. Manag. Strategy

    (1997)
  • Cited by (0)

    View full text