New vs traditional lodging providers : impact of attribute perceptions on booking intentions of P2P accomodation rentals

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Nathalie Monge De Andreis Student nº: 10998519

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1 Statement of Originality ... 1

2 Abstract ... 2

3 Introduction ... 3

4 Theoretical Framework ... 6

4.1 The Sharing Economy & The Lodging Industry ... 6

4.1.1 Components of the Share Accommodations Space ... 7

4.1.2 Importance of the Sharing Economy ... 9

4.2 The New Landscape ... 11

4.2.1 Economic Impact ... 11

4.2.2 Social Impact ... 12

4.2.3 Political Impact ... 12

4.3 Attribute Perceptions by the Lodging Consumer ... 14

4.4 Thesis’ Conceptual Model ... 16

4.4.1 Independent Variables ... 16

4.4.2 Dependent Variable ... 17

4.4.3 Moderators ... 17

4.4.4 Market Choice ... 18

4.4.5 Hypothesis 1: Social Interaction ... 19

4.4.6 Hypothesis 2: Price Attractiveness ... 20

4.4.7 Hypothesis 3: Sustainability ... 21

4.4.8 Hypothesis 4: Experience Authenticity ... 22

4.4.9 Hypothesis 5: Reliability... 22

4.4.10 Hypothesis 6: Booking Ease ... 23

4.4.11 Hypothesis 7: Location Convenience ... 24

5 Methodology ... 28

5.1 Research Procedure & Data Collection ... 28

5.1.1 Target Population & Resulting Sample ... 29

5.1.2 Measurement of Variables ... 30

5.1.3 Statistical Analysis ... 35

5.1.4 Strengths & Limitations ... 41

6 Findings & Discussion... 43

6.1 Future Research ... 45

7 Addendums ... 47

7.1 Demographics of Sample ... 47

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I, Nathalie Monge De Andreis, wrote this document and take full responsibility for its content. I declare that the text and the work presented in this thesis is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business at the University of Amsterdam is responsible solely for the supervision of the work’s completion, not for its content.

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BSTRACT

Given the exponential growth of sharing economy options in the accommodation sector, gaining a better understanding of the drivers of consumer booking intention is strategically important to providers of peer-to-peer (P2P) rentals, as well as their competitors. Based on survey data (N=90) from avid travelers in the author’s network, this study investigated whether consumers’ perceptions of key attributes extracted from the academic literature impacted their booking intention of urban P2P rentals. Furthermore, it posed the question of whether or not the influence of these elements on booking intention could be swayed by how travelers’ perceived these same attributes at urban hotels.

The results indicated that the concepts of sustainability and reliability impacted travelers’ booking intention for leisure purposes, but discarded the popular attributes of social interaction, price attractiveness, experience authenticity, booking ease, location

convenience, and hipness. Also, traveler perceptions of sustainability and reliability at hotels did not influence the described relationship between these perceived attributes at urban P2P rentals and booking intention. The implications of these findings for both industry professionals and scholars are discussed and recommendations for future research are offered.

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NTRODUCTION

The fundamental question addressed in this study revolves around consumer choice criteria within the new lodging context of shared accommodations. More precisely, it aims to find what key attributes influence travelers’ booking intention of urban peer to peer rentals and whether this influence is swayed by their perception of these same attributes at urban hotels.

The sharing economy is a rapidly growing sector (Belk, 2014; Eckhardt & Bardhi, 2015; Heo, 2016; Martin, 2016; Möhlmann, 2015; Richard & Cleveland, 2016; Sigala, 2014; Stors & Kagermeier, 2015; Tussyadiah, 2015; Zervas et al., 2016) that has changed the way people travel (Heo, 2016) while disrupting the status quo, threatening established companies and existing business models (Belk, 2014; Cusumano, 2015; Eckhardt & Bardhi, 2015; Guttentag, 2015; Martin, 2016; Möhlmann, 2015; Richard & Cleveland, 2016; Richardson, 2015; Sigala, 2014; Tussyadiah & Zach, 2015; Zervas et al., 2016). In lodging, this

significant disrupter has fostered a rapid expansion of the informal or unregulated accommodation sector (Guttentag, 2015; Tussyadiah & Zach, 2015) exponentially increasing room capacity (Richard & Cleveland, 2016) around the world.

As expressed by Zervas et al. (2016), the rise of the sharing economy has come along with a host of open research questions. Guttentag (2015), Heo (2016), Martin, (2016), and Sigala (2014) echo this sentiment by pointing out the lack of research in the field and the urgent need for further studies. Moreover, Möhlmann (2015) states that the current academic work on the sharing economy does not explicitly differentiate between various industries whereas

Heo (2016) expresses that researchers in tourism have paid little attention to the impact of this relatively new phenomenon on the tourism landscape.

This work’s focus on the lodging industry addresses the described literature gap by making advances in the understanding of one of the many forms of the sharing economy. More specifically, by looking at attributes influencing consumer choice it responds to Stors & Kagermeier (2015)’s plea to uncover expectations that lie behind the offer and use of share

accommodation.

In hospitality marketing and management, identifying accommodation attributes that influence potential guests’ choice is key to achieve optimal hotel development decisions (Dolnicar & Otter, 2003) as well as attract and retain customers (Tussyadiah & Zach, 2015). This is a topic of growing importance in this new space (Hamari et al., 2015) since

exploring perceived competitive advantages of P2P accommodation rentals in comparison to hotels can provide both with better managerial direction (Tussyadiah & Zach, 2015) by aiding them to assess their competitive position, pinpoint their leverage points, and respond accordingly.

While the current literature shines some light as to the possible attributes affecting consumers’ intentions towards share accommodations, it is surrounded by ambivalent explanations and fails to fully capture what compels tourists to make an actual booking. This is confirmed by Tussyadiah & Zach (2015) which states that knowledge on the dimensions used to evaluate share accommodations is extremely limited. This thesis work is thus among the first to explore the consumption criteria of lodging guests faced with sharing economy options.

Similarly to Zervas et al. (2016), this study also contributes to the expanding literature on the switch between offline and online markets, as sharing economy platforms have provided

technology that enable informal accommodations with niche inventory to effectively sell their products online at a level that competes with the traditional lodging industry. Finally, by focusing on urban properties and measuring booking intention this research provides new and targeted insights that equip lodging providers with important information for the design of pointed strategies and the improvement of their marketing action.

In the coming pages, a look into the academic literature on the sharing economy as it relates to the lodging industry sets the stage for this thesis’ research. From the writings, an

exploratory analysis of traditional and share accommodations key attributes is used to draw the work’s conceptual model and hypotheses. This is followed by an explanation of the study’s methodology – procedure, data collection, strengths, and limitations. A final

discussion of the findings offers conclusions regarding the tested hypotheses and the study’s contributions. To close, avenues for future research are recommended.

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HEORETICAL

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This section presents a review of scholarly literature on the sharing economy framed within a lodging industry context. The analysis is used to draw the hypotheses for this thesis study.

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While sharing is considered a phenomenon as old as humankind, the rise of the internet and Web 2.0 has allowed its practice to evolve with a previously unknown dynamism and scale that poses unforeseeable ultimate consequences (Belk, 2014; Stors & Kagermeier, 2015). These developing transformations and their ample applications are collectively understood as the sharing economy— also referred to as collaborative consumption, the peer economy, and even the gig economy.

In further explaining the sharing economy, Heo (2016) brings up the Oxford Dictionary definition: “An economic system in which assets or services are shared between private individuals, either for free or for a fee, typically by means of the Internet.” Yet, there is currently no uniformly accepted or concise definition of the sharing economy in its

various evolving contexts. Furthermore, Eckhardt & Bardhi (2015) argue that “sharing” is a misleading term for market-mediated environments and that, instead, the phenomenon should be referred to as “access economy”, since consumers engaging in these platforms are after utilitarian, rather than social, value.

Nevertheless, this paper adheres to the generally accepted term, sharing economy, since the label of sharing is weighty and flighty enough to capture the breadth and depth of these ‘new’ configurations of economic activity (Richardson, 2015).

4.1.1 COMPONENTS OF THE SHARE ACCOMMODATIONS SPACE

Rather than select one of the many definitions offered by scholars such as Belk (2014),

Cusumano (2015), Hamari et al. (2015), Martin (2016), Rea (2016), and Richardson (2015), this work explores the primary components of these sharing economy models for a lodging industry application. Hereby, this section offers a detailed look at the role of the internet, communities, P2P platform creators and users, and access in the world of share accommodations.

4.1.1.1 Internet sharing

As already mentioned, the internet has played a central role in the development of the sharing economy. It facilitates the easy constitution of online-based communities and networks for little transaction costs (Möhlmann, 2015) and simplifies sharing of both physical and nonphysical goods and services (Hamari et al., 2015) by connecting a diverse array of potential consumers and producers (Richardson, 2015). In other words, internet technologies have allowed real-life sharing to move online and, by connecting people at a larger scale, they have created a new “economy” featuring an explosion of sharing websites.

4.1.1.2 Community creation

Another known and necessary component for sharing economy companies is fostering community participation (Richardson, 2015) and creating strong networks. By

leveraging social media and Web 2.0 technologies, companies can encourage interaction and user-generated content (Sigala, 2014). This generates proximities between strangers, thereby fostering participation (Richardson, 2015) and the ability for

economy platforms act merely as economical-technological coordination providers (Hamari et al., 2015), an active community or network is necessary for exchanges to occur.

4.1.1.3 Evolving player ecosystem

Sharing economy platforms originated as peer-to-peer (P2P) or consumer-to-consumer (C2C) networks. While most sharing economy ventures are facilitated by digital platforms created by firms (Rea, 2016), the service providers and the clients leveraging these platforms are peers —that is to say, they are (theoretically) interchangeable (Richardson, 2015).

However, as established business players enter the sharing economy space, platforms aim to move beyond their intermediary role, and new ventures continuously appear, the space has evolved beyond it’s pure intermediary roots to include newer business-to-consumer (B2C) commercial ventures (e.g. Avis Group’s ZipCar). Belk (2014) terms these B2C enterprises faux sharing or pseudo-sharing and they are outside the scope of this study.

It is noteworthy to mention that within a lodging context the involvement of professional management companies taking on groups of properties inside P2P networks is part of a natural evolution. Hence, it is inevitable for P2P and B2C transactions to eventually converge or cohabitate within various sharing economy platforms.

4.1.1.4 Access products

The products exchanged via sharing economy platforms tend to differ from those typically offered by commercial providers. One of these differences is that they are access-based (Richardson, 2015). In other words, rather than selling ownership of a product, sharing platforms present temporary access-rights to a product or service (Daunorienė et al., 2015). By renting short-term access to underutilized products that people would otherwise need to buy, such as holiday homes, cars or tools, the sharing economy also reflects the broader “servitization” trend (Cusumano, 2015).

While shared accommodations are often considered alternative travel goods (Sigala, 2014) given their level of individuality, authenticity and local experience (Rea, 2016), the access-based nature of the lodging industry has turned it into fertile ground for growth in this new space.

4.1.2 IMPORTANCE OF THE SHARING ECONOMY

The importance of the sharing economy is precisely apparent in the above mentioned rapid growth (Belk, 2014) and the unprecedented scale at which businesses leveraging the sharing economy have emerged (Martin, 2016; Tussyadiah, 2015). Several reasons are attributed with fueling this massive growth, including the paradigm shift from company-centric value creation to value co-creation with consumers (Heo, 2016), technological advances such as social networking tools and software-as-a-service, payment systems, economic crises, low barriers of entry for sharing economy companies (Sigala, 2014), the large size of the market which appeals to diverse socioeconomic profiles (Möhlmann, 2015), loss of consumer interest in ownership for self-definition, urbanization (Belk, 2014), and the virality of the model (Möhlmann, 2015; Sigala, 2014).

In line with this growth story, today’s sharing economy lodging firms include a variety of platforms such as Airbnb, 9flats, HouseTrip, HomeAway®, FlipKey® by TripAdvisor, HomeExchange.com™, Villas.com, Roomorama, Onefinestay, Homestay, Wimdu, CouchSurfing, and CampInMyGarden.com. These companies act as matchmakers connecting potential guests with individuals holding underused assets (Tussyadiah, 2015) ranging from spare rooms and vacation homes to couches and gardens.

The centerpiece of the lodging sharing economy is AirBnB. Started in 2008, this platform has facilitated tens of millions of short-term accommodation bookings (Zervas

et al., 2015). It is the largest marketplace platform in the accommodations space

(Guttentag, 2015) and, to offer some perspective on its scale, it has very quickly built up a greater choice of rooms in terms of location, price and amenities, than many global hotel chains (Richardson, 2015). So, aside from the myriad of business opportunities opened by the sharing economy, the exponential growth opportunities that platform dynamics and network effects offer P2P networks has also threatened established companies (Cusumano, 2015).

Share accommodations have also exponentially increased room capacity, a dynamic fueled by strong consumer demand, the abundance of underutilized spare rooms and homes in the marketplace, and the access-based nature of the rental transactions (Richard & Cleveland, 2016). There is no doubt: the sharing economy has changed the way people travel and is of great significance to the traditional tourism industry (Heo, 2016).

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The sharing economy creates a mix of positive and negative impacts (Martin, 2016) and blurs the boundaries between consumers and service providers, and (in tourism

destinations) the ones between local residents and business entities (Hamari et al., 2015; Heo, 2016). Given the rapid rise of share accommodation businesses or platforms, it is vital to understand their effect on the lodging industry environment and its stakeholders. Although the full impact of the sharing economy is still under study, the below analysis describes its economic, social, and political effects as mentioned in the current academic discourse.

4.2.1 ECONOMIC IMPACT

Consistent with the growth of the sharing economy and the outburst of sharing accommodation firms described above, Martin (2016) recognizes its potential for economic value creation and commercial opportunity. Local residents are able to

leverage their homes to earn additional income and local businesses can benefit from the economic push of increased traffic (Guttentag, 2015).

On the other hand, the sharing economy may: cause a surge in the price of housing and rental properties for local residents (Guttentag, 2015), establish illegal and unregulated markets (Martin, 2016) which compete unfairly and take potential guests away from hotels (Tussyadiah & Zach, 2015), and promote tax avoidance (Martin, 2016) which affects local government funding.

For traditional accommodation providers, the new and evolving competitive landscape generated by the sharing economy is threatening to the point that Cusumano (2015)

predicts that unless they adapt and capitalize on their unique advantages they will become diminished versions of what they used to be.

4.2.2 SOCIAL IMPACT

Amongst its benefits, the sharing economy is credited with creating social value, empowering individuals, enabling ‘sharing’ practices (Martin, 2016), and offering consumers cost savings and valuable alternatives to traditional accommodations (Tussyadiah, 2015).

In contrast, the availability and affordability of housing and rental properties for locals can be negatively impacted, neighborhoods may encounter increased noise and safety concerns (Guttentag, 2015), and P2P accommodation providers may face unclear

liabilities and risks in terms of legality (Richardson, 2015). Also, the informal economy featured on sharing economy platforms transfers risk to consumers (Martin, 2016) generating uncertainty in terms of safety, legitimacy, and quality (Richard & Cleveland, 2016).

4.2.3 POLITICAL IMPACT

Policy and regulation have failed to keep up with the birth and evolution of sharing economy platforms, fueling considerable resistance regarding the legality and taxation of P2P rentals (Guttentag, 2015) and perpetuating the negative social and economic impacts noted above.

For most in the traditional lodging industry, sharing economy platforms are fostering a rapid expansion of the informal and illegal tourism accommodation sector (Guttentag, 2015; Tussyadiah & Zach, 2015). By evading taxes and operating in a concealed or

unregulated manner (Guttentag, 2015; Heo, 2016), these new firms are believed to have gained unfair advantages which allow them to offer a more competitive price value (Richard & Cleveland, 2016). Hence, legal hotel operators are pressuring municipalities to level the playing field (Cusumano, 2015) by enforcing hotel or bed and breakfast regulations on the short-term rental services offered by the sharing economy (Belk, 2014).

Local governments are also contending sharing economy firms that encourage illegal short-term rentals, dodge taxes, and/or offer inadequate tourist accommodations (Richard & Cleveland, 2016) which do not satisfy health and safety standards or submit to

applicable inspections (Guttentag, 2015). However, it is still questionable whether share economy platforms –most of which are set up as intermediaries with little or no control over the content displayed, distributed, exchanged, or coordinated on their websites- should actually be held responsible for the goods being exchanged through them by their users (Hamari et al., 2015). Furthermore, certain jurisdictions are actually welcoming share accommodations as a way to expand tourism’s potential benefits. For example, those with short tourism seasons or insufficient lodging capacity perceive share rentals as a solution to demand spikes which allows them to host major events (Guttentag, 2015) without having to build additional infrastructure.

The different governmental attitudes described evidence how the full effects of the share economy on destinations remains unknown and may vary depending on context. As a result, it appears that the legal battles with share accommodation providers are just commencing and that the regulatory environment will likely remain quite fluid for years to come (Guttentag, 2015).

To conclude, the newness of the rapidly growing share accommodations sector opens up an opportunity to further study the economic, social, and political impact on its various stakeholders. Yet, for practical purposes, this thesis will focus on the lodging consumer in an attempt to aid market orientation strategies as a way to generate value and business sustainability.

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As stated in this paper’s introduction, the lodging industry is fully aware of the importance of understanding guests’ choice criteria and seeking to provide amenities accordingly (Yavas & Babakus, 2005; Zhang et al., 2011). Also, as the P2P phenomenon continues to grow and influence the way people experience, consume, and produce accommodations (Sigala, 2014), it is important for hoteliers and share accommodation providers to identify the attributes valued by P2P guests and compare and contrast them with attributes valued by hotel guests (Tussyadiah & Zach, 2015).

So far, top hotel attributes that have been recognized in the literature as motivators of consumer behavior include: convenience of location, service quality, reputation,

friendliness of staff, price, room cleanliness, value for money (Dolnicar & Otter, 2003), comfortable bed, and other conveniences such as airport shuttle service, parking, breakfast, and in-room services (Tussyadiah & Zach, 2015).

When it comes to P2P platforms in general, consumer motivating features explored by scholars are multifaceted and include topics of sustainability, enjoyment, (Hamari et al., 2015), utility, trust, familiarity, service quality, community belonging (Möhlmann, 2015), and economic gains or cost savings (Eckhardt & Bardhi, 2015; Hamari et al., 2015;

Möhlmann, 2015). Considering P2P accommodations specifically, attributes identified in the literature as most appealing center around economic benefits or cost-savings

(Guttentag, 2015; Möhlmann 2015; Richardson, 2015; Sigala, 2014; Stors & Kagermeier, 2015; Tussyadiah 2015; Tussyadiah & Zach, 2015), sustainability (Sigala, 2014;

Tussyadiah 2015; Tussyadiah & Zach, 2015), hospitality of the hosts (Stors &

Kagermeier, 2015; Tussyadiah & Zach, 2015), neighborhood location and local businesses (Richardson, 2015; Stors & Kagermeier, 2015; Tussyadiah & Zach, 2015), provision of an authentic lodging experience (Guttentag, 2015; Sigala, 2014; Tussyadiah 2015), social interaction with new people and locals (Stors & Kagermeier, 2015; Tussyadiah 2015), and household amenities (Guttentag, 2015).

Although there is certain overlap on the attributes valued by guests of traditional and new accommodation providers, hotels’ main advantages seem to be factual and related to amenities and services, while more emotional attributes are appreciated by P2P

consumers. An example of this is clear on the way P2P guests highlight the importance of human interactions and intimacy with hosts and locals, beyond hotel attributes such as staff recognition, friendliness, or attentiveness. (Tussyadiah & Zach, 2015)

In terms of factors that deter the use of P2P rentals Guttentag (2015) refers to service quality, staff friendliness, brand reputation, and security, while Tussyadiah (2015)

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In line with this research’s scope, namely to measure the effect of relevant lodging attributes on the booking intention of urban P2P rentals, this section describes the conceptual model in detail.

4.4.1 INDEPENDENT VARIABLES

The above literature review yielded eight relevant attributes for consumers of P2P accommodations that are used as this study’s independent variables –social interaction (Guttentag, 2015; Hamari et al., 2015; Heo, 2016; Richardson, 2015; Stors &

Kagermeier, 2015; Tussyadiah, 2015), price attractiveness (Daunorienė et al., 2015;

Eckhardt & Bardhi, 2015; Guttentag, 2015; Hamari et al., 2015; Heo, 2016; Martin, 2016; Möhlmann, 2015; Richard & Cleveland, 2016; Sigala, 2014; Stors & Kagermeier, 2015; Tussyadiah, 2015), sustainability (Hamari et al., 2015; Martin, 2016; Möhlmann, 2015; Stors and Kagermeier, 2015; Tussyadiah, 2015), experience authenticity

(Guttentag, 2015; Rea, 2016; Richard & Cleveland, 2016; Sigala, 2014; Stors &

Kagermeier, 2015), reliability (Belk, 2014; Guttentag, 2015; Möhlmann, 2015; Richard & Cleveland, 2016; Richardson, 2015; Zervas et al., 2015), booking ease (Cusumano, 2015; Guttentag, 2015; Stors & Kagermeier, 2015; Tussyadiah, 2015), location convenience (Stors & Kagermeier, 2015; Tussyadiah & Zach, 2015), and hipness (Möhlmann, 2015; Stors & Kagermeier, 2015; Tussyadiah, 2015). These variables correspond with the most commonly cited lodging attributes mentioned in the sharing economy academic writings.

4.4.2 DEPENDENT VARIABLE

Booking intention, is defined as the likelihood that a potential visitor will book (Tsao et

al., 2015). It was chosen as the dependent variable of this study in order to address the entire consumer population (users and non-users of shared accommodations). This choice contrasts with current share economy research, which measures attributes in terms of satisfaction, motivation for usage, and repurchase intention (Hamari et al., 2015; Möhlmann, 2015; Stors and Kagermeier, 2015; Tussyadiah, 2015; Tussyadiah & Zach, 2015). Booking intention is also more practical as it addresses the possible attitude-behavior gap described by Hamari et al. (2015), where people express good feelings towards sharing economy products but do not necessarily translate this attitude into action.

4.4.3 MODERATORS

Given the consumer behavior phenomenon of coherent arbitrariness (Ariely et al., 2003), hotel attribute perceptions are included as potential moderators for the relationship between P2P attribute perceptions and booking intentions. According to Ariely et al. (2003), consumer valuations are largely arbitrary, but once a valuation has been made, subsequent valuations are likely to be scaled appropriately relative to the first. Since hotels are the natural anchor or first valuation for lodging products, one can hypothesize that, even if P2P rentals are different from hotels, potential guests will value the latter relative to the former. Hence, for P2P rentals travelers’ perception of hotel attributes may impact the relationship between the perception of these same attributes and booking intentions.

4.4.4 MARKET CHOICE

To avoid gross generalizations that may diminish the applied usefulness of this study, the author chose to focus on urban properties. This shall produce finer and more helpful insights for industry practitioners.

Furthermore, as noted by Davidson & Infranca (2016) the scale, proximity, amenities, and specialization of city life are what enables sharing economy firms to flourish. The critical mass of providers and consumers who are sufficiently close to each other or to other amenities are what has allowed P2P platforms to work, fostering the ability to rent spare rooms and apartments while finding value in the beneficial spillovers from

proximity.

This is not to say that the phenomenon does not exist in secondary and tertiary markets. As Mark Woodworth, President of PKF Hospitality Research, states, hotel owners and operators outside of main destinations may be immune for now, but they are not likely to ignore the threat of share economy platforms when the next down cycle hits the industry, especially those differentiating and competing on price (Mayock, 2015). At that time, generalized strong competitive responses from hotels, including legal action, can be expected to hit share accommodation companies.

4.4.5 HYPOTHESIS 1:SOCIAL INTERACTION

Given the sociable personality of most P2P guests, social interaction is an important element of the visitor experience (Stors & Kagermeier, 2015) and a major motivating factor for usage (Tussyadiah, 2015). The quality of this interaction with the host and the ability to meet new people or make new friends is particularly relevant for leisure guests (Heo, 2016; Stors & Kagermeier, 2015; Tussyadiah, 2015) who enjoy gaining inside knowledge about the city or undertaking activities with locals (Stors & Kagermeier, 2015). Nevertheless, the image of the welcoming P2P host can be a fallacy (Richardson, 2015) and the renter may be completely absent at the time of the rental (Guttentag, 2015) limiting the visitor’s social interaction to a third party handling formalities, such as supplying the keys (Stors & Kagermeier, 2015). To the extent that the reciprocity implied by peer-to-peer exchanges proves illusory (Richardson, 2015), the essential role played by enjoyment and interaction on alternative accommodations may negatively influence usage intention (Hamari et al., 2015).

To sum up, even though the literature on shared accommodations remains unclear about the degree to which travelers still perceive the existence of social interaction on the evolving offerings (Guttentag, 2015; Hamari et al., 2015; Richardson, 2015; Stors & Kagermeier, 2015), the attribute has been identified as a relevant variable for travelers (Heo, 2016; Stors & Kagermeier, 2015; Tussyadiah, 2015). This leads to the first hypothesis: (H1a) Perceived social interaction positively influences booking intention of

urban share accommodations, and (H1b) the relationship between perceived social interaction and booking intention of urban share accommodations is moderated by perceived social interaction at urban hotels.

4.4.6 HYPOTHESIS 2:PRICE ATTRACTIVENESS

Price is a key factor in hotel purchase decisions (Dolnicar & Otter, 2003; Richard & Cleveland, 2016) and economic benefits seem to also significantly impact behavioral intentions towards sharing economy products (Hamari et al., 2015). Stors & Kagermeier (2015) expresses the notion that the monetary dimension plays an important role when choosing share economy accommodations, while Eckhardt & Bardhi (2015)believes that lower costs are one of consumer’s main interests. Furthermore, Möhlmann (2015)’s

study on Airbnb found that cost savings have a significant and positive effect on guest satisfaction.

Despite the indications on finances as a motivator for P2P rentals, it appears they are less relevant than expected (Stors & Kagermeier, 2015). The market of the sharing economy in the travel industry consists of more educated consumers with higher income

(Tussyadiah, 2015) who are no more economical or thrifty than non-users (Stors & Kagermeier, 2015). Furthermore, the sporadic and unstandardized nature of P2P transactions may increase non-monetary costs such as stress or efforts in search, coordination, and risk-reduction (Hamari et al., 2015; Sigala, 2014). All this suggests that P2P rentals offer guests more than the sum of a low cost solution (Tussyadiah, 2015) resulting from lower overhead (Daunorienė et al., 2015) and tax/regulation avoidance (Guttentag, 2015; Heo, 2016; Martin, 2016; Richard & Cleveland, 2016).

As evidenced, researchers argue whether or not price is the main motivator driving booking intentions of P2P rentals; yet they mostly agree that it is a key factor (Eckhardt & Bardhi, 2015; Guttentag, 2015; Möhlmann, 2015; Richard & Cleveland, 2016; Stors & Kagermeier, 2015; Tussyadiah, 2015). Thus, price attractiveness or price/value is the

second attribute to be tested on this study: (H2a) Perceived price attractiveness positively

influences booking intention of urban share accommodations, and (H2b) the relationship between perceived price attractiveness and booking intention of urban share

accommodations is moderated by perceived price attractiveness at urban hotels.

4.4.7 HYPOTHESIS 3:SUSTAINABILITY

For consumers with a greater preference towards environmentally-friendly consumption, the sharing economy offers a sustainable alternative that employs excess capacity leading to a more efficient use of resources (Martin, 2016; Möhlmann, 2015; Tussyadiah, 2015). While Tussyadiah (2015) confirms sustainability or responsible travel as a driver for the use of P2P accommodation, it is worth noting that this is achieved by influencing

consumer attitude rather than behavioral intention. This parallels results from Hamari et

al. (2015) which concluded that, in the case of the sharing economy platform Sharetribe, perceived sustainability was not directly associated with participation unless attitude translated it into behavioral intentions.

In spite of the fact that a direct link has not been established between sustainability of share accommodations and consumer behavior, the confirmed influence of this third attribute on consumer attitude (Tussyadiah, 2015) permits the following hypothesis:

(H3a) Perceived sustainability positively influences booking intention of urban share accommodations, and (H3b) the relationship between perceived sustainability and booking intention of urban share accommodations is moderated by perceived sustainability at urban hotels.

4.4.8 HYPOTHESIS 4:EXPERIENCE AUTHENTICITY

Authenticity, or the ability to experience a destination as a local, plays a major role in consumers’ choice of share accommodations (Stors & Kagermeier, 2015). By booking a local residence, P2P guests get to stay in a home away from home that is possibly located in a ‘non-toursity’ area and offers unique facilities and design (Guttentag, 2015; Rea, 2016;

Richard & Cleveland, 2016; Sigala, 2014; Stors & Kagermeier, 2015).

Given that the unique and authentic residential feel of P2P rentals is considered an important choice driver (Stors & Kagermeier, 2015), the next hypothesis is postulated:

(H4a) Perceived experience authenticity positively influences booking intention of urban share accommodations, and (H4b) the relationship between perceived experience

authenticity and booking intention of urban share accommodations is moderated by perceived experience authenticity at urban hotels.

4.4.9 HYPOTHESIS 5:RELIABILITY

Risk plays a major role in hotel selection decisions (Dolnicar & Otter, 2003) and information asymmetries that arise from loosely-regulated P2P marketplaces can make trust building especially difficult (Zervas et al., 2015). Reliability issues currently associated with P2P accommodations comprise quality levels and consistency as well as safety and security concerns (Guttentag, 2015; Richard & Cleveland, 2016), both

important choice factors (Möhlmann, 2015; Richard & Cleveland, 2016; Zhang et al., 2011).

Since the institutional structures that ensure reliability to both guests and hosts are bypassed in P2P marketplaces, trust needs to be built through technology (Richardson,

2015). Although ratings tend to be overwhelmingly positive and are unlikely to reflect true product quality, online reviews are still a significant driver of consumer behavior (Zervas et al., 2015). Thus, reputation systems, fostering communication between hosts and guests, and user profiles are methods that help nurture this trust (Belk, 2014;

Guttentag, 2015). Yet, this is not enough for some tourists who will still prefer the more predictable experience of staying in traditional accommodations (Guttentag, 2015). In any case, given the relevance of quality and safety to lodging consumers (Guttentag, 2015; Möhlmann, 2015; Richard & Cleveland, 2016; Zhang et al., 2011) and the

necessity to create trustworthy P2P platform environments (Richardson, 2015), reliability is at the core of our fifth hypothesis: (H5a) Perceived reliability positively influences

booking intention of urban share accommodations, and (H5b) the relationship between perceived reliability and booking intention of urban share accommodations is moderated by perceived reliability at urban hotels.

4.4.10 HYPOTHESIS 6:BOOKING EASE

The typical booking process of share accommodations does not offer real time

confirmations, which is the general standard for hotels. Tussyadiah (2015) explains that consumers will not participate in collaborative consumption if they find the technology systems too complex or inefficient; however, not all potential guests view the extended booking process of shared accommodations as a weakness.

Further research, messaging, and coordination often precedes the reservation of share accommodations. Although this additional time and effort hampers consumers’ ability to set definitive travel plans (Cusumano, 2015; Guttentag, 2015), some visitors find the

communication with the hosts to be a great advantage and the platforms informative and easy to use (Stors & Kagermeier, 2015).

Since booking ease can affect usage (Tussyadiah, 2015), this is the sixth attribute to be tried. Its potential effects on booking intention are echoed in the hypothesis: (H6a)

Perceived booking ease positively influences booking intention of urban share accommodations, and (H6b) the relationship between perceived booking ease and booking intention of urban share accommodations is moderated by perceived booking ease at urban hotels.

4.4.11 HYPOTHESIS 7:LOCATION CONVENIENCE

In the lodging industry, a convenient location is an important determinant of room price and a key source of competitive advantage (Zhang et al., 2011). This remains true for share accommodations where location is highly relevant and sometimes the decisive factor for selecting them over hotels (Stors & Kagermeier, 2015). Nevertheless, the definition of convenient location seems to vary between guests who stayed at hotels and those who stayed at share accommodations.

After hotel stays, guests describe a properties’ proximity to attractions or facilities (i.e., downtown, airport) to be the most relevant, while they pay attention to the neighborhoods where P2P rental spaces are located (quiet, within short walking distances to local

restaurants and shops, within minutes by bus to downtown) (Tussyadiah & Zach, 2015). Although there is no further information on the origin of these differences, a convenient location prevails in the discussion of important lodging attributes (Stors & Kagermeier, 2015; Tussyadiah & Zach, 2015; Zhang et al., 2011). It follows that: (H7a) Perceived

location convenience positively influences booking intention of urban share

accommodations, and (H7b) the relationship between perceived location convenience and booking intention of urban share accommodations is moderated by perceived location convenience at urban hotels.

4.4.12 HYPOTHESIS 8:HIPNESS

Personal innovativeness traits often drive consumers towards share accommodations as a way to expand their horizon, try new things, or follow a trend (Möhlmann, 2015; Stors & Kagermeier, 2015; Tussyadiah, 2015). In other words, the newness of the share

accommodation space attracts trend-seeking consumers.

Although hipness is mentioned sparingly in the literature, the academic literature on shared accommodations is so limited that the attribute still warrants exploration: (H8a)

Perceived hipness positively influences booking intention of share accommodations, and (H8b) the relationship between perceived hipness and booking intention of share

Having drafted the hypotheses, Figures 1 and 2 summarize the developed conceptual model on determinants of booking intention for urban peer to peer accommodation rentals. They illustrate the influence of the eight key accommodation attributes on booking

intention and the moderating effect of the perception of these same attributes in hotels.

FIGURE 1:CONCEPTUAL MODEL -IMPACT OF PERCEIVED ATTRIBUTES ON BOOKING INTE NTION

Booking Intention of Share Accommodations Experience Authenticity of Share Accomm. Social Interaction of Share Accommodations Price Attractiveness of Share Accommodations Sustainability of Share Accommodations Reliability of Share Accommodations Booking Ease of Share Accommodations Location Convenience of Share Accommodations Hipness of Share Accommodations H1a H2a H3a H4a H5a H6a H7a H8a

FIGURE 2:CONCEPTUAL MODEL –MODERATION EFFECT OF HOTEL ATT RIBUTE PERCEPTI ONS

Attribute Perception for Share Accommodations

Attribute Perception for Hotels Booking Intention of Share Accommodations Attributes: 4 Experience Authenticity Au 1 Social Interaction 2 Price Attractiveness 3 Sustainability 5 Reliability 6 Booking Ease Ea 7 Location Convenience 8 Hipness Hb

5 M

ETHODOLOGY

Given that the theoretical resources available to aid the development of data sampling and analysis approaches on the sharing economy are limited (Martin, 2016), the research procedure and data collection described below relied on a variety of resources that were adapted based on researcher judgement.

5.1 R

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The research procedure chosen for this study involved an exploratory analysis to identify accommodation attributes possibly affecting booking intentions for P2P rentals followed by a survey to evaluate travelers’ perceptions on these topics.

A list of eight key elements emerged from the sharing economy academic literature corresponding to social interaction, price attractiveness, sustainability, experience

authenticity, reliability, booking ease, location convenience, and hipness. A questionnaire was then used to measure these variables along with the dependable variable, booking intention. The questionnaire to capture travelers’ perceptions also included questions to explain respondents’ travel characteristics and demographic variables.

To lure in a more internet-savvy population, which was more likely to be familiar with P2P rental platforms, an online collection platform was chosen; Qualtrics research software was used to develop the survey. To further expand the sample reach, the questionnaire was presented in English and Spanish. Finally, it got distributed via

LinkedIn, Facebook, and email communications between November 27, 2016 and January 15, 2017.

5.1.1 TARGET POPULATION &RESULTING SAMPLE

This study’s target population was urban travelers (refer to section 4.4.4) who booked at least 2 overnight stays in the past 12 months (criteria used by Yavas & Babakus, 2005) and who had awareness about P2P rental websites (this included users and non-users). From the 170 potential respondents who accessed the online survey, 112 belonged to the described target population. The following questions were asked at the beginning of the survey to qualify these respondents and make sure that they could offer informed

answers: How many trips with overnight stays did you take in the last 12 months? Do you tend to stay at urban destinations/cities when you travel? Do you know what a peer-to-peer rental website is (e.g. Airbnb, Homeaway) or are you familiar with this type of accommodation websites?

The final sample comprised responses from 90 urban travelers (response rate 53%) from which 51% were female and 46% were male. The sample population had a mean age of 38 years old (SDage=10, age-range: 16-63) and was highly educated, with a large majority holding university and professional degrees (90%). A bias towards western travelers emerged within the results, particularly concentrated in Costa Rica (43%), the United States (20%), and the European Union (14%). Amongst this group of avid travelers (Mtrips=9.6 trips with overnight stays taken in the past year, SDtrips=8.8, number of trips range: 2-40, substantial positive skewness=1.6, kurtosis=1.9), 42.2% reported staying at a P2P rental within the last 12 months. Their nightly budget for urban stays stood at a mean of €130 (SDbudget=€61, budget-range: €5-€331). Finally, the sample population included a large percentage of hospitality industry professionals (20%). See section 7.1.

While an incentive for participation was offered to capture responses beyond the author’s network (participants were informed that they had the chance to win a €100 gift card for an Internet store), the survey resulted in a non-probability sample. Aside from this limitation, the quality of the respondents in terms of relevance is very high given the qualifying questions and the resulting traveler statistics described above.

5.1.2 MEASUREMENT OF VARIABLES

The accommodation attributes and booking intentions of travelers were measured as described below and responses were recorded following a five-point Likert-type scale from (1) strongly disagree to (5) strongly agree.

5.1.2.1 Social Interaction

Given the newness of this concept in the academic literature and the lack of multiple item scales, a single question was used to measure social interaction, which refers to guests’ opportunities to relate and spend quality time with other individuals such as hotel staff, rental hosts, locals, and tourists. The inquiry, adapted from Tussyadiah (2015) is: opportunity to have meaningful interactions with others.

5.1.2.2 Price Attractiveness

To measure price attractiveness, or perceived economic benefits derived from lower prices and cost savings, the following queries were adapted from Tussyadiah (2015),

Hamari et al. (2015), and Möhlmann (2015): money savings, lower travel costs, higher quality for less money, high satisfaction for price, and financial benefits. This scale has high reliability when applied to both P2P (α=.832) and hotels (α=.806). For both cases, the corrected item-total correlations indicated that all the items have a good correlation

with the score of the scale and none of the items would substantially affect the reliability if they were deleted.

5.1.2.3 Sustainability

Sustainability, which in this context concerns consumers’ worries about their

environmental and social impact (overconsumption, and inefficient use of natural and human resources), was assessed by asking about: lower consumption of natural resources, energy efficiency, socially responsible travel, environmentally-friendly travel, and opportunity to support the local economy. The questions were also derived from Tussyadiah (2015), Hamari et al. (2015), and Möhlmann (2015) and the scale yields high reliability for a P2P (α=.817) and a hotel (α=.874) context. The corrected item-total correlations indicated that all the items have a good correlation with the score of the scale with the exception of “support the local economy” (.285) measured for P2P rentals. None of the items would substantially affect the reliability if they were deleted.

5.1.2.4 Authentic Experience

A guest’s opportunity to have a more ‘local’ experience by participating and discovering the culture and traditions of their destination in a real, non-staged or “touristy” way, is what this text refers to as experience authenticity. Based on

Tussyadiah (2015), this concept was measured using two dimensions: opportunity to get to know locals, and access to insider’s tips on local attractions. This scale has high reliability (α=.844) within a P2P setting. Also, the corrected item-total correlations indicated that both items have a good correlation with the score of the scale. On the other hand, the scale is not reliable for hotel measurements.

5.1.2.5 Reliability

When selecting a lodging option online, guests expect a certain level of quality and safety standards that they may not assess in person which means they must trust the information provided on the web. This expectation and its fulfillment is what this study has termed as reliability. Since reliability was not measured in the reviewed literature and the share accommodations space revolves around the internet, the author adapted the questions from the field of information systems, more specifically from Chang & King (2005): the information about the accommodations is reliable, and the information on the accommodations is verifiable. Since the literature mentions trust-building as a reliability tool (Belk, 2014; Guttentag, 2015; Möhlmann, 2015; Richardson, 2015; Zervas et al., 2015), these questions were complemented by adapting Yim et al. (2008)’s measurement of service firms trust: you are confident about the quality of the

accommodations, the services provided are reliable and professional, overall, you can confidently rely on the services of these lodging providers. The resulting reliability scale has high reliability when applied to both P2P (α=.891) and hotels (α=.893). For both applications, the corrected item-total correlations indicate that all the selected items have a good correlation with the score of the scale and none of the items would substantially affect the reliability if they were deleted.

5.1.2.6 Booking Ease

Booking ease refers to the efficiency and simplicity of the consumer-facing aspects of the reservation process. As booking a room is essentially purchasing it, and in the absence of a booking ease measurement, this independent variable was evaluated by adapting Pavlou & Fygenson (2006)’s perceived ease of purchasing variable. The

questions were: easy to purchase online and easy to learn how to purchase online. This scale has high reliability when measuring P2P rentals (α=.858) and hotels (α=.877). In both cases, the corrected item-total correlations indicated that the items have a good correlation with the score of the scale.

5.1.2.7 Location Convenience

Location convenience is relative to guests’ expectations on what they wish to

accomplish or experience. It can be defined in terms of proximity and ease of access to where they want to be or other location characteristics that allow them to fulfill their goals. Results by Tussyadiah & Zach (2015) show that convenience is a subjective term when it comes to lodging locations; thus, a simple question was used to measure this attribute: likely to have a convenient location. Since the P2P literature reviewed did not offer a measurement for location convenience, this evaluation was modeled after Hua et al. (2009).

5.1.2.8 Hipness

In line with this research’s goals, the level at which a concept is perceived as novel and trendy denotes its hipness. To assess the level of hipness at hotels and P2P rentals, the following was asked: the accommodations are trendy, the accommodations are modern, and the accommodations have an urban-feel. These questions are based on marketing research evaluations from Zhu & Meyer-Levy (2009). Applied to P2P rentals, the hipness scale has high reliability (α=.858). The corrected item-total correlations indicated that all the items have a good correlation with the score of the scale and none of the items would substantially affect the reliability if they were deleted. The scale is also reliable when applied to hotels (α=.799) and the corrected item-total correlations

indicate that all the selected items have a good correlation with the score of the scale. However, the Cronbach’s Alpha would be affected if “Hotels are trendy” (.679) or “Hotels are modern” (.655) were deleted.

5.1.2.9 Booking Intention

Similarly to Sparks & Browning (2011), booking intention or likelihood to make a reservation was measured using a single item: it is very likely that I will book a room or apartment at a peer-to-peer rental (such as Airbnb, HomeAway, or 9Flats) if it is

available in a location that I am traveling to. The question was asked twice adding the purpose of travel at the end (for business/for leisure) to address the jumbled

correspondence of hotel choice attributes for business and leisure travelers revealed in

5.1.3 STATISTICAL ANALYSIS

After testing the various measurements for reliability, running a factor analysis, and computing scale means, the author ran a correlation analysis mainly to measure the strength of the relationship between the independent variables and booking intention (DV). As illustrated in Table 1, this investigation revealed that experience authenticity and booking ease had no significant correlation with booking intention for both leisure and business travel. Furthermore, location and hipness were only correlated to booking intention when traveling for leisure purposes. All other variables presented a positive correlation to booking intentions.

M SD 1. Booking Intention - Business 2.47 1.33

2. Booking Intention - Leisure 3.78 1.15 0.46**

3. Social Interaction 3.52 0.98 0.25* 0.24* 4. Price Attractiveness 3.80 0.71 0.32** 0.44** 0.26* (.83) 5. Sustainability 3.14 0.68 0.33** 0.45** 0.44** 0.37** (.82) 6. Experience Authenticity 3.68 0.82 0.19 0.18 0.56** 0.27* 0.41** (.84) 7. Reliability 3.42 0.80 0.26* 0.53** 0.27* 0.67** 0.46** 0.36** (.89) 8. Booking Ease 4.26 0.75 0.04 0.20 0.10 0.34** 0.10 0.15 0.42** (.83) 9. Location Convenience 3.86 0.83 0.10 0.33** 0.14 0.48** 0.16 0.31** 0.46** 0.39** 10. Hipness 3.78 0.76 0.19 0.41** 0.38** 0.33** 0.41** 0.37** 0.46** 0.39** 0.47** (.86) **

Correlation is significant at the 0.01 level (2-tailed).

*

Correlation is significant at the 0.05 level (2-tailed). Variables

Table 1: Means, Standard Deviations, Correlations

-5 6 7 8 9 10 -1 2 3 4

-Next, multiple regression analyses were performed to investigate the potential for the remaining independent variables to predict travelers’ booking intentions for leisure and business travel respectively. The first model was statistically significant F(8,81)=6.19; p<.001 and explained 37.9% of variance in booking intention for leisure travel. Yet, only two out of the eight predictor variables were statistically significant, sustainability

(β=.236, p<.05) and reliability (β=.307, p<.05). The second model analyzed explained 17.2% of the variance F(8,80)=2.08; p<.05; however, none of the predictors had statistical significance.

Table 2: Regression Models of Booking Intention

R B SE t

Booking Intention for Leisure Travel 0.62 0.38 ***

Social Interaction 0.07 0.13 0.06 0.49 Price Attractiveness 0.17 0.20 0.10 0.82 Sustainability 0.40 0.19 0.24 * 2.12 Experience Authenticity -0.23 0.16 -0.16 -1.44 Reliability 0.44 0.19 0.31 * 2.28 Booking Ease -0.11 0.16 -0.07 -0.70 Location Convenience 0.14 0.16 0.10 0.89 Hipness 0.24 0.18 0.16 1.36

Booking Intention for Business Travel 0.42 0.17 *

Social Interaction 0.12 0.18 0.09 0.64 Price Attractiveness 0.50 0.28 0.27 1.83 Sustainability 0.39 0.25 0.20 1.53 Experience Authenticity 0.00 0.22 0.00 -0.02 Reliability 0.00 0.26 0.00 0.00 Booking Ease -0.11 0.21 -0.06 -0.52 Location Convenience -0.10 0.21 -0.07 -0.49 Hipness 0.07 0.24 0.04 0.31 Statistical significance: * p<.05; ***p<.001 R2 β

Given the unexpected results from the regression analyses, the parameters from the original models were reduced to check for potential overfitting. The items that showed no correlation to the dependable variable were omitted. Hence, for leisure travel, the eight original predictors were reduced to the following six: social interaction, price

attractiveness, sustainability, reliability, location convenience, and hipness. This yielded a statistically significant model F(6,83)=7.78; p<.001 that explained 36% of variance in booking intention for leisure travel. Again, only sustainability (β=.225, p<.05) and reliability (β=.263, p<.05) proved to be statistically significant. For business travel, the new model incorporated four predictors of booking intention: social interaction, price attractiveness, sustainability, and reliability. Similar to the original model, this one explained a mere 16.6% of the variance F(4,84)=4.17; p<.01 and none of the predictors had statistical significance.

Table 3: Regression Models of Booking Intention

R B SE t

Booking Intention for Leisure Travel 0.6 0.36 ***

Social Interaction -0.02 0.12 -0.02 -0.17 Price Attractiveness 0.18 0.20 0.11 0.91 Sustainability 0.38 0.18 0.23 * 2.06 Reliability 0.38 0.19 0.26 * 2.01 Location Convenience 0.08 0.15 0.06 0.53 Hipness 0.21 0.17 0.14 1.20

Booking Intention for Business Travel 0.41 0.17 **

Social Interaction 0.12 0.15 0.09 0.81 Price Attractiveness 0.45 0.26 0.24 1.76 Sustainability 0.43 0.24 0.22 1.81 Reliability -0.05 0.24 -0.03 -0.21 Statistical significance: * p<.05; **p<.01; ***p<.001 R2 β

With these results, one last test was performed to rule out the overfitting theory. It included the top three attributes that correlated to booking intentions for leisure travel: reliability, sustainability, and price attractiveness. The model was statistically significant F(3,86)=14.77;p<.001 and it explained 34% of variance in booking intention. Once again, the only predictors that were statistically significant were sustainability (β=.247, p<.05) and reliability (β=.325, p<.05).

To conclude, the results from the regression models partially proved hypotheses: (H3a)

Perceived sustainability positively influences booking intention of urban share

accommodations, and (H5a) Perceived reliability positively influences booking intention of urban share accommodations, applied only to travelers visiting cities for leisure

purposes. Conversely, the following hypotheses were discarded: (H1a) Perceived social

interaction positively influences booking intention of urban share accommodations, (H1b) The relationship between perceived social interaction and booking intention of urban share accommodations is moderated by perceived social interaction at urban hotels, (H2a) Perceived price attractiveness positively influences booking intention of urban share accommodations, (H2b) The relationship between perceived price attractiveness and booking intention of urban share accommodations is moderated by perceived price attractiveness at urban hotels, (H4a) Perceived experience authenticity positively influences booking intention of urban share accommodations, (H4b) The relationship between perceived experience authenticity and booking intention of urban share accommodations is moderated by perceived experience authenticity at urban hotels, (H6a) Perceived booking ease positively influences booking intention of urban share accommodations, (H6b) The relationship between perceived booking ease and

booking intention of urban share accommodations is moderated by perceived booking ease at urban hotels, (H7a) Perceived location convenience positively influences booking intention of urban share accommodations, (H7b) The relationship between perceived location convenience and booking intention of urban share accommodations is

moderated by perceived location convenience at urban hotels, (H8a) Perceived hipness positively influences booking intention of share accommodations, and (H8b) The

relationship between perceived hipness and booking intention of share accommodations is moderated by perceived hipness at hotels.

Moving on to the final stage in this investigation, the author ran moderation analyses to test the influence of the two remaining variables, sustainability and reliability, on the booking intentions of urban P2P rentals when travelers visited for leisure. Contrary to the original hypotheses, the perceived sustainability and reliability of urban hotels by travelers’ in the sample population showed no statistically significant influence on the relationship between the perception of these variables at urban P2P rentals and their booking intentions. In other words, the following hypotheses were not proved: (H3b)

The relationship between perceived sustainability and booking intention of urban share accommodations is moderated by perceived sustainability at urban hotels, and (H5b) The relationship between perceived reliability and booking intention of urban share

5.1.4 STRENGTHS &LIMITATIONS

Once again, due to the recent emergence of the topic of shared economy accommodations in academic research, the knowledge on the dimensions used by potential guests as choice criteria is extremely limited. By studying the effect of popular attributes on booking intention, this research opened up a new and more targeted area of exploration. It also contributed to the goal set by Tussyadiah and Zach (2015) of identifying the attributes that guests may consider important or, based on the results, attributes that do not really affect booking intention. This information allows accommodation providers to make informed decisions regarding how to adapt or market their offers to fit with

consumer expectations.

Table 4: Moderation Analyses

Coefficient SE t p

Perceived Sustainability

Intercept i1 1.10 1.69 0.65 4.46

Sustainability of P2P rentals (X) a1 0.94 0.50 1.88 1.94 Sustainability of hotels (M) a2 0.09 0.52 0.17 1.12 Sustainability of P2P x Sustainability of hotels (XM) a3 -0.06 0.15 -0.39 0.24

Perceived Reliability

Intercept i2 -0.23 2.41 -0.09 0.93

Reliability of P2P rentals (X) b1 1.46 0.74 1.97 0.05 Reliability of hotels (M) b2 0.30 0.55 0.55 0.59 Reliability of P2P x Reliability of hotels (XM) b3 -0.16 0.17 -0.93 0.35

R2=.2031 F(3,86)=7.3076; p<.001

R2=.2972

On the other hand, the methodology applied for this research has limitations and further studies will be necessary in order to gain a more comprehensive understanding of the topic. First, important academic discourse from around the globe may have been

excluded from this study, given that the literature review was based on English language material. Second, the proposed scales need to be tested further and may benefit from future revisions. Third, although the sample of highly educated urban travelers fits with the profile of P2P guests presented by Tussyadiah (2015), the researched population has important biases regarding geography and occupational characteristics. Replication studies would need to engage a broader audience in order to both attain conclusive generalizations and produce finer insights in which relevant variables are controlled for. Factors such as accommodations quality standards, for example, could extend

researchers’ examination of choice criteria. Finally, future studies may go beyond booking intentions by using experimental designs or longitudinal studies to test actual behavior.

6 F

INDINGS

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ISCUSSION

Results from this research indicate that, when visiting urban destinations for leisure,

travelers’ perceived sustainability and reliability positively influence their intention to book peer-to-peer accommodations (H3a and H5a partially proved).

Although the predictive value of perceived sustainability on booking intentions is relatively small, it aligns with the perception that the sharing economy engages sustainably-minded consumers (Hamari et al., 2015; Martin, 2016; Möhlmann, 2015; Tussyadiah, 2015). Similarly, the positive influence of perceived reliability on booking intentions is in line with the literature and was expected given its association with vital choice factors such as quality, consistency, safety, and security (Guttentag, 2015; Möhlmann, 2015; Richard & Cleveland, 2016; Zhang et al., 2011).

Conversely, the lack of predictability that resulted from the other tested attributes (H1a, H2a, H4a, H6a, H7a and H8a rejected) suggests further support for the nascent state of the share economy research and the lack of knowledge regarding consumer choice criteria for shared accommodations (Heo, 2016; Martin, 2016; Sigala, 2014; Tussyadiah and Zach, 2015).

While these results can lead one to speculate that the concepts currently studied simply have no value in predicting the booking intention of shared rentals, a more plausible explanation is that these dimensions have a broader scope than the market and population of this study. In other words, the general characteristics of the sharing economy space may not directly apply to the context of urban share accommodations and highly educated avid travelers. Therefore, even when the results of the study failed to appropriately answer the proposed

research question, they are still insightful to both industry practitioners and academics, particularly regarding the importance of context and segmentation when it comes to lodging attributes impacting consumer behavior.

For instance, the results suggest that lodging providers should take care when following popular concepts discussed in the sharing economy literature, as they may not be relevant to their target market or specific situation. Also, when relying on existing research, it is

advisable to test the applicability of any initiative to attract or retain potential P2P customers before making any major investment. In the case of large P2P platforms, such as Airbnb, the results make an argument to consider more in-depth customer segmentation strategies. This is especially true for platforms trying to lure in profitable business travelers; which, based on our results, seem to be less in tune with key constructs typically associated with the sharing economy than leisure travelers.

When it comes to hospitality researchers, the study brought to light the need to pinpoint whether or not global predictors of peer-to-peer booking intentions actually exist. Likewise, academics must figure out what controls or segmentations need to be in place in order to produce quality results.

When it comes to the second part of the proposed theory, although most of the dimensions were discarded due to lack of booking intention predictability (H1b, H2b, H4b, H6b, H7b and H8b rejected) the author was able to perform moderation analyses for the sustainability and reliability variables. Once again, the unexpected results disproved the proposed

hypotheses (H3b, and H5b rejected). Nevertheless, given the limited number of predictors tested and the possible geographic and customer segmentation issues raised above, it would

be hasty to conclude that travelers’ perceptions of hotels have no effect on their perceptions of peer-to-peer rentals as they relate to booking intention. To rephrase, even if in the mind of educated urban travelers P2P rentals prove to be alternative travel goods, as suggested by

Sigala (2014), the question of whether hotels are competitive products that affect consumer behavior regarding P2P rentals remains open.

To conclude, this study is an example of the ample grounds that need to be covered when it comes to understanding the dynamic phenomenon of share accommodations. While in one end this research contributed by revealing sustainability and reliability as key attributes influencing travelers’ intention to book urban P2P rentals, on the other, it evidenced the large amount of unknowns and the complexity surrounding this practical topic.

6.1 F

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As mentioned throughout this paper, the relatively new and evolving concept of share accommodations provides abundant opportunities for scholarly research. In agreement with the author’s findings, for example, a broader study on the topic of attributes that affect booking intentions of P2P rentals would allow researchers to segment and control variables like accommodations geography and quality standards, as well as consumer demographics. The resulting information would have great strategic relevance to industry practitioners especially in terms of marketing and product design.

Testing actual behavior with longitudinal studies and experimental designs is also an interesting avenue to explore the attribute subject and it would contribute enormously to the limited knowledge on how consumers’ evaluate share accommodations highlighted by

hypotheses, studying consumers’ mental associations and interactions between traditional and shared accommodations could offer valuable insights regarding competitive

dynamics.

Beyond this, and as suggested by Heo (2016), Möhlmann (2015), Sigala (2014), and

Tussyadiah (2015), future research needs to examine factors motivating both sellers and buyers to participate in the space. Tourism researchers have also suggested: profiling travelers (Guttentag, 2015; Sigala, 2014), learning about the value and benefits that various stakeholders perceive from shared accommodations, (Sigala, 2014) and investigating the economic, socio-cultural, and environmental impact of this new

businesses on the destinations in which they operate (Sigala, 2014; Heo, 2016; Guttentag, 2015), as well as their impact on the tourism industry and accommodation sector

(Guttentag, 2015; Heo, 2016). Finally, studying the success factors and sustainability of traditional business models and the ways in which they can effectively re-define their strategy to generate value is also important (Möhlmann, 2015; Sigala, 2014).

In terms of technical knowledge, Sigala (2014) mentioned the need to investigate how websites should be effectively designed to support P2P transactions, while Möhlmann (2015) raises the question about the importance of different listing information in selecting a particular rental (e.g. price, location, amenities, pictures, reviews, etc.).

In short, as the sharing economy continues to expand and transform the market there will be no shortage of topics to examine in order to, in the words of Zervas et al. (2016), “fully