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Users can also verify their email addresses and phone numbers with Airbnb (the actual addresses and numbers are hidden), and link their Facebook and LinkedIn accounts to their Airbnb profiles to demonstrate an online presence (see FIGURE 2). As it is customary for both parties to leave a short review of the experience after the stay, these profiles are then accompanied by past reviews the user has accumulated from other hosts and guests.
As previously discussed in the introduction, Airbnb was selected as a suitable case study because of its global dominance in P2P accommodation and because P2P accommodation is arguably the sector of the sharing economy most contingent on trust. The case study was
approached through a framework of four Airbnb-specific research sub-questions:
1. Why do users use Airbnb instead of traditional accommodation and/or other P2P
2. What are the most commonly perceived risks of using Airbnb?
3. Which elements of Airbnb profiles or listings do users find most important in
4. What are the mechanisms by which Airbnb engenders trust among its users?
These sub-questions comprised a framework for the research design, which is presented in the next chapter.
4 Research design
4.1 Exploratory purpose The sharing economy is a relatively new social movement, and has only recently gained mainstream traction; academic work regarding various aspects of the sharing economy comprises a nascent, growing field (see APPENDIX A.1). The purpose of this research is thus exploratory, designed to investigate and generate a new level of comprehension about unknown aspects of a relatively new phenomenon (Teddlie & Tashakkori 2009). Hypotheses will not be generated nor tested; instead, this investigation will endeavor to build a conceptual foundation of critical insight to inform future research. To that end, this research utilizes inductive analysis, which entails the discovery and analysis of patterns, categories, and themes within the data, arguing from the particular to the general (Patton 2002). Inductive, exploratory research processes are particularly effective when coupled with a qualitative methodology.
4.2 Qualitative methodology This research employs a qualitative methodology in order to gain critical insight on the multidimensional topic of trust in the sharing economy. Yin (2011: 135, 98) contends a fundamental objective of qualitative research is to “depict a complex social world from a participant’s perspective,” and that “understanding the nuances and patterns of social behavior only results from studying specific situations and people, complemented by attending carefully to specific contextual conditions.” A qualitative methodology is thus extremely appropriate for the study of trust among users of Airbnb, as the engendering and continued growth of trust is personal, contextual, culturally-mediated, and inherently social. The interpretive case study – “a qualitative approach in which the investigator explores a real-life, contemporary bounded system (a case) over time, through detailed, in-depth data collection involving multiple sources of information” (Creswell 2013: 97) – is particularly suitable for the exploratory, inductive nature of the research, as it is an effective way to research an area in which few previous studies have been conducted (Benbasat et al. 1987). The case study is constructed through an interpretive approach, effectively attempting to understand and analyze phenomena through accessing participants’ context-specific perceptions (Orlikowski & Baroudi 1991).
4.3 Data collection The case study is composed of two types of qualitative data: in-depth, open-ended interviews and broad document review, as multiple methods of data collection provide robust support for the conclusions via triangulation (Benbasat et al. 1987). As qualitative research is most effective by means of an iterative process (Kelly 2006), the case study was constructed through a continual cycling between theory and data (Eisenhardt 1989, Walsham 1995, Tracy 2013).
4.3.1 Document review The research entailed an extensive investigation of relevant documents in order to develop contextual insight on Airbnb, the bounded system. The researcher initially explored the Airbnb website and company documentation as a user in order to become familiarized with patterns of user behavior, emergent user experience, and website-specific norms and functions.
This exploration was supplemented by an examination of relevant documents, defined by Walsham (2006: 323) to include “press, media, and other publications of the sectoral context of organizations being studied.” The researcher reviewed an extensive amount of relevant press, following the development of the sharing economy from the years 2010 to mid-2013 to develop an approximate arc of traction within mainstream society, and to investigate perceptions of the sharing economy from a wide range of perspectives, including those of social innovators, entrepreneurs, authors, journalists, venture capitalists, and other various stakeholders. Through this process of document review, the researcher concluded that although there is ample extant and available knowledge on the opinions and ideas of thought leaders regarding trust in the sharing economy, there is a conspicuous lack of user perspective – the perceptions, constructions, and first-hand behavioral accounts of the people that actually use these websites.
It thus seemed most advantageous for this research to explore the user perspective regarding trust in the sharing economy.
The relevant press review was augmented by an investigation of a variety of other sectoral content and media. The research encompasses blog posts from several Airbnb users about their experiences, various recorded TED talks from thought leaders in the space, prominent technology and entrepreneurship blogs, the following of sector-specific online magazines Shareable and OuiShare, and attendance at the two-day sharing economy-focused LeWeb 2013 technology conference in London. This process provided a foundation upon which to design the empirical core of the research: the interviews.
4.3.2 Interviews Interviews are often the primary data source of interpretive case studies (Walsham 1995).
As this case study is most concerned with users’ perceptions of trust within the Airbnb platform, it accordingly makes use of eleven semi-structured interviews with a diverse sample of participants. The qualitative methodology is best suited for purposive sampling, in which participants are selected in a deliberate manner in order to yield the most relevant and plentiful data (Yin 2011). The central criteria most commonly advised for purposive sampling is value of information (Patton 2002) and diversity of perspectives (King & Horrocks 2010). To this end, the participants selected, five males and six females, represent seven different nationalities, have as little as 1 instance of Airbnb experience to as many as 15, and span an age range of 23 to 62, although most participants are clustered in the 23-30 range in order to maintain an accurate representation of the Airbnb user population. The main recruiting channel was through the global Startup Weekend Facebook network. Through broadcasting a message to this network – worldwide travelers and early adopters of technology – the researcher was able to compose a diverse sample of participants with relevant and interesting Airbnb experience. The number of cases was directly determined by the sufficiency of data acquired (Kelly 2006).
The objective of the interviews was to elicit rich and contextual qualitative data through open-ended questions, and to utilize the opportunity to interact with the participants and pose follow-up or divergent questions if necessary. Each interview was between 15 and 45 minutes in length, contingent on the proclivity of the participant to elaborate during their responses. The participants were made aware that while certain excerpts from their interview transcripts may be published in this research, these excerpts would not be associated with any personally identifiable information.
As the participant group is geographically diverse, four interviews were conducted in person and seven over Skype, a voice-over-IP service with both audio and video capabilities.
Both in-person and Skype interviews were recorded with the software program Camtasia 2 in order to compile precise transcripts of what was said in each interview, and to be able to engage with the transcripts within various conceptual frameworks during analysis. The general list of interview questions and a sample anonymized interview transcript can be found in APPENDIX A.2 and A.3.
4.4 Data analysis The analysis of qualitative data is not a precise science, rather, it is an intuitive and creative process of inductive reasoning, theorizing, and interpreting (Basit 2003). The objective of data analysis is to identify the categories, relationships, and assumptions that comprise the participant’s perceptions both in general and on the topic in particular (McCracken 1988). The analysis is comprised of a subjective classification process – applying codes to significant phrases – and subsequently identifying themes or patterns (Hsieh & Shannon 2011). The coding process is the core of the analytic process, as the cognitive act of coding data prompts critical conceptual organization (Ely et al. 1991). While analysis and interpretation might in some sense distill or reduce the volume of data, the implementation of such analysis should also “value add” to the emergent story (Madden 2010), elucidating existing situations and recurrent themes.
The research utilized Dedoose, a web-based quantitative and qualitative data analysis software program, to code the interview transcripts. The transcripts were loaded into the program and a hierarchical code system was applied to generate emergent patterns among the participant responses. The full list of codes can be found in APPENDIX A.4.
The coded transcripts were linked to chains of ‘descriptors,’ such as age, gender, nationality, frequency of Airbnb use, and percentage of accommodations booked with Airbnb. In this way, the data could be manipulated in different ways, and various associations between specific codes and descriptors could be teased out. Coded excerpts could also be filtered in a hierarchical fashion, aggregating similar responses to varying degrees.
The final iteration of the hierarchically coded data was then exported to a document format, and the resulting report of coded material was further distilled and analyzed for emergent themes with regard to the research sub-questions of the case study.
4.5 Limiting considerations The first consideration to address regarding this research is that of the in-depth nature of the generated qualitative data, but the limited scope of generalizability (Patton 2002). However, as research of an exploratory nature, the goal is not to confirm hypotheses or corroborate causal conclusions, but to provide a conceptual foundation of insight upon which other research and other preliminary hypotheses might be developed. Furthermore, the research has qualities conducive for “naturalistic” generalization, or presenting findings in a way that a reader normally experiences and understands them (Gomm et al. 2000). Thus, while this research may not be statistically generalizable, it is of value as a foundation for future research, and can be intuitively interpreted by readers.
The limiting phenomenon of self-selection must also be considered. Because participants were recruited from respondents to a general posting, it can be argued that the study attracted a certain type of participant. Yet access to this particular sample can simultaneously be considered a strength of the research. As the goal of qualitative research is to elicit in-depth, informationrich experiences, focusing on this demographic – active on the Internet, early adopter of technology, and capable of travel – highlights the most relevant and informative users of P2P services such as Airbnb.
It is thus reasonable to conclude, despite these considerations, that the research was successful in addressing the research sub-questions and generating critical insight on the subject matter. The following chapter will present a discussion of the results of the research.
experience with Airbnb, both in instances of use and in total percentage of accommodations booked with Airbnb.
The interview questions were derived from the four research sub-questions, and responses were iteratively coded into hierarchical code sets. Twelve emergent themes were identified with respect to the research sub-questions. In the following sections, each of these themes will be examined in further detail.1 Theme 10, “the more information, the better,” is discussed in Section 6.
5.1 Reasons for using Airbnb To contextualize trust within the Airbnb setting, the research investigated users’ motivations for using the website. Each participant remarked on different reasons for using Airbnb; their responses are comprised by two practical themes, value for money and flexibility, and one non-practical theme, cultural experience.
5.1.1 Value for money In discussing why they had used Airbnb instead of traditional accommodation or another P2P service, most participants immediately referred to a sense of extracting more value at less cost from the Airbnb accommodation experience. This ‘value’ manifested itself in the ability to secure a better venue for a lower price, but also in the “extra” services that many Airbnb stays provided. P2 described Airbnb hosts’ proclivity to go above and beyond, detailing positive
experiences with hosts’ generosity:
Most cases, my experience has been that you get a lot of value for the money you pay for, and there are also things that I’ve gotten through Airbnb that I wouldn’t have gotten through a hotel, ever – everything from items, such as people having an umbrella at the apartment, or guidebooks, and saying it’s okay to use them, to things like surprises, like when we were in France, the person that was renting the apartment had bought randomly wine and cheeses for us.