Research Design done by Robbie Li in 2021 under Dr. Prudence Carter

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Robbie Li
Professor Prudence Carter
SOC 2210
Airbnb and Perceived Neighborhood Safety:
A Research Blueprint to Expand Criminology Theory in the Wake of Short-term Vacation Rental
I. Introduction and Study Significance
Short-term vacation rentals, recently popularized by brands like Airbnb and Vrbo, have
become a major component of modern social life. In 2020, on the Airbnb platform alone, there
were over 4 million people sharing homes in approximately 100,000 cities across the world
(Airbnb Inc, 2020). However, the popularity of home sharing does not belie its reported
negative externalities on the local community. Anecdotes abound in public media that
neighbors of Airbnb are now demanding further regulation to address their concerns of
community safety. For instance, one neighbor in Niagara Falls, NY complained that she had to
install “ring bells all over the place” and “got a pistol permit” as a result of seeing Airbnb guests
in her neighborhood (Hallikaar, 2021). Closer to home in Barrington, RI, neighbors recently
organized to impose a zoning rule that would outlaw an Airbnb rental operated by the Rhode
Island School of Design (Amaral, 2021). As short-term vacation rental platforms continue to
reach more zip codes across the world, the tension amongst the host, her neighbors, the
platform, and local government, will likely become more and more pressing. This growing
tension is worth examining not only because it has implications for how local governments
might regulate short-term vacation rentals to ensure a sense of community safety, but also
because it provides a touchpoint through which we can investigate how something as

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fundamental as feeling safe in one’s own neighborhood is being shaped by the new
phenomenon of short-term vacation rentals operated by members of the community.
II. Background and Literature Review
While there is not any precedent research specifically examining non-hosting Airbnb
neighbors’ conceptualization of neighborhood safety, there exists relevant literature that has
informed the design of this study. Such literature can be divided into three categories: Airbnb’s
impact on community safety; non-hosting residents’ attitudes towards Airbnb; and factors
affecting residents’ perception of neighborhood safety.
II.1 Airbnb’s Impact on Community Safety
The study of Airbnb’s impact on community safety is a nascent research field where
extant literature almost ubiquitously utilizes quantitative methods; consequently, the proposed
qualitative study examining neighbors’ attitudes regarding safety will add to the depth of our
understanding. The first study on Airbnb’s impact on community safety was published only in
2018 (Xu et al, 2018), where researchers used a geographically weighted regression analysis to
find a statistically significant positive correlation between Airbnb listing density and levels of
criminal activity across 67 counties in Florida. Since, other quantitative studies have ensued,
though utilizing different analytical methods and sampling different geographic regions.
Findings, however, have been consistent. For instance, a 2021 study, using compiled longitudinal
data for Airbnb listings as well as 911 call data to perform Difference-in-Difference analysis,
concluded that Airbnb listings lead to more neighborhood crime in later years in the Boston
area (Ke et al, 2021). These quantitative studies establish the premise of the current research,

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that Airbnb might have a negative effect on community safety. This premise motivates the
current research to investigate community sentiments around Airbnb-impacted neighborhoods.
II.2 Non-hosting Residents’ Attitudes of Airbnb
Research on the residents' attitudes of Airbnb has expanded greatly in recent years to
contradict dominant media portrayals that equate Airbnb presence with endless nuisance and
unhappy neighbors. Contrary to the dominant narrative that neighbors generally disdain Airbnb,
researchers have found that neighbors of Airbnb generally hold positive opinions about the
platform (Mody 2020), and that there exist mediating factors that could further lead to
community support for the platform, including a sense of agency in collective decision-making
around regulating Airbnb (Mody 2020), prior experience as a guest on the platform (Suess et al
2021), and emotional solidarity with the guests (Suess et al 2020). Here, the three factors
identified by prior research present potential areas for the current study to probe. While these
factors contribute to a positive imagination of the platform, it remains to be ascertained
whether and how they also affect neighbors’ perception of community safety.
II.3 Factors Affecting Resident Perception of Neighborhood Safety
The study of residents’ perception of community safety stems from criminology where
theories and conceptualizations are robust. Criminology researchers have mainly utilized three
theoretical constructs to explain the determinants of residents’ perception of neighborhood
safety: a) broken windows theory (Kelling and Wilso, 1982; Baba and Austin, 1989; Pitner et al
2012), which postulates that physical and social incivilities such as abandoned lots or noisy
neighbors may lead to perceived danger; b) collective efficacy (Sampson and Raudenbush, 1999;
Baba and Austin, 1989; Pitner et al, 2012), which suggests that community members feel safer

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when they feel a sense of agency in deciding community matters; and c) territoriality (Brown et
al, 2004; Pitner et al, 2012), which proposes that residents’ sense of pride and identification
with the neighborhood may lead to perception of community safety. However, little scholarship
has been produced to incorporate into criminology theory the recent development in
short-term vacation rental services such as Airbnb, which motivates the present study.
III. Research Questions
Given the theoretical gaps discussed in the prior section, the researcher seeks to use the
proposed research to answer this overarching theoretical question: To what extent do the
classical criminology theories around perceived community safety need to be modified and
expanded to account for the new dynamics and contexts brought forth by short-term vacation
rentals such as Airbnb? If modification of such theories are warranted, then how?
In practice, the theoretical question is approached with the following, more fleshed-out,
empirical questions:
1. Which of the three theoretical constructs from criminology (broken window
theory, collective efficacy, and territoriality) possess the most explanatory power
when accounting for non-hosting Airbnb’s perceived community safety in a study
of two neighborhoods in a medium-sized city? Why?
2. Are there new constructs to be discovered and added to the literature?
3. How do these factors vary between urban and suburban neighborhoods?

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IV. Methods
IV.1 Study Population
This study will focus on the experiences and perspectives of Airbnb neighbors in two
communities: Downtown Providence and Wayland. While both neighborhoods are located in
Providence, RI, they are distinct in that one is urban whilst the other is suburban. Urban in
nature, Downtown Providence hosts robust commercial entities such as restaurants, malls, bars,
and a public transportation hub (Kennedy Plaza). On the other hand, Wayland exhibits
attributes of a suburban and family-oriented neighborhood. With only a limited strip for
business, most of the neighborhood real estate is dedicated to residential use. Conducting
research at these two sites will enable the researcher to collect data regarding research
question #3: how do non-hosting Airbnb neighbors' perception of community safety vary across
urban and suburban neighborhoods?
In addition to the geographic constraints set above, key informants will be screened
based on two additional criteria: 1) they must be aware of Airbnb activities within the
neighborhood; 2) they themselves must not currently rent out rooms or entire homes through
Airbnb or any other similar platforms. Here, it is important for key informants to be non-hosting
Airbnb neighbors rather than hosts, because neighbors are the ones bearing the negative
externalities of the platform without any monetary gains. Yet they are also in the majority
compared to Airbnb hosts when it comes to intra-neighborhood decision-making. Thus, they
possess the unique position and power to influence the regulation of short-term vacation
rentals like Airbnb. That’s why the present research is laser-focused on Airbnb neighbors.

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IV.2 Sampling Strategies and Tactics
Sampling will be guided by the philosophy of sampling for range (Weiss, 1994, 23-24),
which ensures a significant variation in participants' perspectives and experiences, hence
enabling a more comprehensive inquiry. For this research in particular, key informants will be
recruited to maximize range along the following axes:
● Neighbors with different existing beliefs of Airbnb's impact on community safety: those
who feel safe with having Airbnb in their communities and those who don’t;
● Neighbors of different ages: 18 to 30, 30 to 60, 60 and above;
● Neighbors who’ve lived in the neighborhood for varying lengths of time: <1 year; 1-5
years; 5+ years;
● Neighbors with different family structures: those who live with children vs. those who
don't.
● Neighbors of different racial-ethnic backgrounds: Asian, Black, Hispanic, and White;
● Neighbors with different levels of prior engagement with the Airbnb platform: those
who've used the platform as a guest vs. those who have not;
Because the research follows “sampling for range” as its strategy, it needs a robust set of
tactics to ensure enough participants are recruited. Unfortunate for the researcher, Airbnb does
not publish the specific addresses of the listings, nor is there such a database publicly available.
Therefore, gaining entry into the field is one of the biggest challenges for this study. In response,
the researcher has considered the following three tactics, and hereby propose that the
combination of all three tactics will propel the project forward. The three tactics include:
1) Leveraging Airbnb Hosts

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To establish research partnerships with the elusive Airbnb neighbors, the researcher may
consider contacting Airbnb hosts first. Anyone can directly message Airbnb hosts on the
platform, and Airbnb hosts are incentivized to answer inquiries in a timely manner (Response
rate and response time of the hosts are displayed at the bottom of any Airbnb listing as
advertisement for the host’s attentiveness and helpfulness). Therefore, the researcher can
reach out to Airbnb hosts online and explain the research context in order to kickstart the
participant recruitment process -- the host might be able to introduce the researcher to the
neighbors. If the host were not able or willing to connect the researcher directly with her
neighbors, then the researcher could ask for the exact location of the listing and conduct a site
visit to establish direct contact with the neighbors.
2) Gaining entry through neighborhood associations and crime watch
Another way to gain entrée into the neighborhood is through contacting neighborhood
associations and showing up to their meetings. Both Downtown Providence and Wayland have
neighborhood associations, which meet monthly to discuss matters concerning the respective
communities. These meetings could serve as entry points for the researcher, where he might
develop relationships with community leaders who would have a wide network of contacts
eligible for the study. It is also possible that the researcher may even find eligible participants
directly at the association meetings.
3) Direct Recruitment Online
Finally, direct recruitment should also be considered. Online recruitment channels may
include Facebook, where the researcher can post in specific Facebook groups such as
“Providence, but On Facebook” which has over four thousand group members. Postings on

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forums such as Providence subreddit might also lead to research participants, although the
researcher has found in preliminary study that Reddit posts elicit more comments than
sign-ups. What’s more, the researcher might find success in neighborhood forums hosted by
Nextdoor. Users of Nextdoor sign up for the platform by verifying their identities including their
zip code. Therefore, Nextdoor users for the Wayland and Downtown Providence forums already
satisfy the geographic constraints specified in the study population, leading to a higher chance
of yielding eligible participants.
The purpose of the aforementioned recruitment tactics is not to gather the entire set of
study cases, but rather establish a starting point from which the researcher will conduct
snowball sampling. Once entry into the field is established through one of the aforementioned
tactics, the researcher will then ask the participants to help him identify other informants who
may be open to research. The ask for assistance will be standardized as part of the interview
protocol. As a result of snowball sampling, study recruitment will be greatly expedited.
IV.3 Sample Size
Sampling will conclude when saturation is achieved (Small, 2007). This research will not
operate with a target number of participants, but rather, be guided by a constant interrogation
from the researcher to himself: does the additional data I have collected add to the theoretical
understanding of Airbnb neighbors’ conceptualization of community safety? Based on the
distinct characteristics of the participant on the dimensions I have sampled along, can I
accurately predict the ways that the informant will talk about Airbnb in relation to community
safety? If so, saturation will have been achieved, and the data collection phase of the research
may end. Otherwise, more participants need to be recruited for the study.

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IV.4 Interview Protocol and Instrument
The study will rely primarily on semi-structured interviews because the research
concerns neighbors’ mental models around community safety, which can best be probed
through guided conversation. Specifically, the researcher will conduct in-depth semi-structured
interviews with key informants, with the aim of each interview spanning about 1 hour.
Interviews will take the format of 1-on-1 conversations to allow participants to develop ideas
independently. Considering COVID guidelines, all interviews will be conducted virtually through
Zoom. Upon participant consent, the researcher will record the meeting as material for analysis.
This is not to say observation-based ethnography does not have a place in this research.
In fact, much observation was done in preparation for the development of this research
blueprint. In order to select Downtown Providence and Wayland as research sites, the
researcher visited all neighborhoods in the Providence municipality. This process allowed the
researcher to obtain rich contextual understandings of different neighborhoods’ idiosyncrasies
in Providence, which are relevant for Research Question #3. Furthermore, during the data
collection phase, the researcher will conduct additional ethnography by attending and
observing neighborhood association meetings.
Nonetheless, the most direct way for the researcher to collect relevant data is through
interviews. As a protocol, the interview will consist of the following steps: introduction,
informed consent, interview questions and follow-ups, snowball sampling, and finally, a short
demographics survey which will assist the researcher to sample for range. A sample interview
instrument outlining the questions and follow-ups is listed below:
General context:

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● How long have you lived in the neighborhood (Wayland/Downtown Providence)?
● How long have you known of the existence of Airbnb in your neighborhood?
● How did you find out about the existence of Airbnb in your neighborhood?
Areas of Research:
● What’s your general impression of your neighborhood’s safety level?
○ To what extent has it changed since you realized that there are Airbnbs near
where you live?
○ How do you determine if your neighborhood is safe or unsafe?
● How often do you see physical or social incivilities in your neighborhood?
○ How would you describe the recent trends in this aspect?
○ How much of these incivilities do you think is due to Airbnb?
○ To what extent does seeing physical and social incivilities make you feel safe or
unsafe? Why?
● How often do you participate in community discussion or other similar engagements?
○ How much of that is related to Airbnb?
○ To what extent does participating in community engagement make you feel safe
or unsafe? Why?
● To what extent do you identify with the neighborhood, feeling as if you belong and you
want to work for the betterment of the community?
○ To what extent has this changed since you've noticed the existence of Airbnbs in
your neighborhood?

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○ To what extent does participating in community engagement make you feel safe
or unsafe? Why?
● To what extent do you interact with Airbnb guests in your neighborhood?
○ What is your opinion about them?
○ To what extent does interacting with Airbnb guests make you feel safe or unsafe?
IV.5 Data Analysis and Analytical Steps
Qualitative data analysis will be facilitated through content analysis performed on the
transcribed interviews and the researcher-produced field notes. After each key informant
interview, which is conducted over Zoom, a transcript will be automatically generated thanks to
the videoconferencing platform. To ensure accuracy, however, the researcher will manually go
through the recording and its transcript to correct any mistakes. Field notes will also be
produced by the researcher after each attendance of the neighborhood association meetings.
Both the interview transcripts and the field notes will be uploaded to NVivo to perform content
analysis.
The coding of qualitative data will follow a flexible coding protocol (Deterding and
Waters, 2021). To start, the researcher will index the data according to a provisional list of codes
informed by the existing frameworks discussed in the literature review. These codes have also
been embedded as probing areas in the interview instrument to facilitate analysis. After the first
pass of indexing, the researcher will then apply axial coding to develop analytical codes that are
more descriptive. For instance, where the prior index has identified “broken window theory” for
a section of text, axial coding will list out specific sub-themes for sentences and paragraphs

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based on collected data, such as “unauthorized parking,” “noise concerns,” and “public
drunkenness.”
To start generating meaning from the coded data, the researcher will utilize specific
analytical steps to address each of the empirical questions listed in this research blueprint. To
answer the first research question regarding the variegated explanatory powers of the existing
constructs of criminology theory, the researcher will note the frequencies of codes for each of
the criminology constructs and report an ordered list. To understand why neighbors relied on
one construct more than another to make sense of community safety, the researcher will locate
the relevant sections in the transcript and conduct both clustering and factoring. To answer the
second research question regarding additional constructs to consider, the researcher will first
cluster together any new analytical codes beyond codes from the provisional list, and then note
any patterns and themes. New codes will likely emerge from this analytical process to formulate
new theoretical constructs from the bottom up. Finally, to answer the final research question
about how the relevance of these factors might differ across communities, the researcher will
rely on the comparing and contrasting of data collected from the two sites. Where possible, the
researcher will compare across sites the cases that are similar in demographics, revealing the
location effect on informants’ conceptual model.
V. Reflections on the Evolution of Research Methods
While there are many ways my research project has evolved over time, I’d like to focus
on two aspects: research scope and interview questions, which go hand-in-hand. When I first
started the research process, I knew I wanted to study the neighborhood dynamics in the
context of Airbnb but wasn’t sure exactly what neighborhood dynamics should encapsulate. Nor

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did I have a theoretical anchoring for my empirical research; I did not know what theory I could
contribute to. However, through reading news reports about Airbnb neighbors’ concerns for
community safety as well as combing through the extant literature, my scope became much
more defined. Finally, I arrived at an approach similar akin to the Extended Case Method, where
I seek to put criminology theory into a new context and examine its relevance and validity.
Because my research scope grew more defined, my interview questions also became
more focused. Prior, I was asking big and broad questions about how the neighborhood has
changed, hoping that the participant would volunteer information about their interactions with
Airbnb. I would also ask about their perceptions of how the platform impacted community
dynamics, without providing a clear aspect such as my current focus on perceived safety. My
questions used to be big and vague, and thus not very productive. Thanks to a narrower
research focus, now my questions are much more specific. I relied heavily on the theoretical
constructs found in the literature to structure my empirical questions, which were then
operationalized as interview questions.
If I had more time to develop this research, I would reach out to Makarand Mody of
Boston University and Courtney Suess of Texas A&M University, whose works are at the cutting
edge of scholarship concerning Airbnb neighbors. Their works heavily shaped how I conceived
of the project and designed the research methods. Specifically, one of the dimensions I
proposed to consider while sampling for range is whether the neighbor has had prior
experience on the Airbnb platform as a guest, which is an idea discussed in Suess’ research
(2021). I would have loved to get their feedback on the framing of my research question.
Outside of gaining researchers’ feedback, I would have liked to contact local politicians for

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further contexts on Airbnb regulation. In 2019, Providence started regulating short-term rentals
(List, 2019); therefore, the issue of short-term vacation rentals is a familiar issue to the political
circle in Providence. I suspect by talking to legislators, I would be able to further calibrate my
research scope so that I produce insights that are indeed relevant to policymaking.
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