Introduction
Airbnb has offered alternative, creative, and unique
places to stay in various cities since its founding in
2007 (Airbnb Newsroom, n.d.). It has also provided
guests with a more authentic way of connecting with a
city. Airbnb, originally known as Airbed & Breakfast,
began when Brian Chesky and Joe Gebbia invited
three guests to stay in their San Francisco home in
October 2007 (Airbnb Newsroom, n.d.). In March 2008,
Airbed and Breakfast officially became a business, and
they launched the website in August of 2008 (Airbnb
Newsroom, n.d.). In March 2009, Airbnb became the
new name of the company and expanded its selection
to apartments, homes, and vacation rentals (Airbnb
Newsroom, n.d.). Today, Airbnb is one of the most
popular booking apps, allowing guests to select their
most important preferences such as city, type of
accommodation, neighborhood, price range, and more.
Multiple external factors impact the operation of Airbnb
and its ability to maximize its profits. To know these
factors, one must look at them through the PESTLE
Analysis. The PESTLE Analysis is a framework that
analyzes how political, economic, social, technological,
legal, and environmental factors affect an organization
(Makos, 2024). The first of these factors is political
factors. The policy and regulations in each city, country,
and state regarding short-term rentals can vary. Some
are stricter than others, and some do not allow for
short-term rentals (Makos, 2024). According to Makos
(2024), external stakeholders (such as policymakers
and people who are considered locals). Another factor
that affects Airbnb is economic factors. Inflation, global
economic conditions (including tourism), and the
housing market can heavily influence the performance
of Airbnb.
Another factor is the social factor. Social trends and
cultural shifts during a time can play a role in the
performance of Airbnb (Makos, 2024). After COVID-19,
remote work was rising in popularity and created a new
normal (Pabilonia & Redmond, 2024). With the rise of
remote work, it can affect Airbnb’s success because a
person will no longer have to travel to another state,
city, or country and need lodging. They can stay home
and work. In addition, safety and health became a huge
importance during COVID-19, which further drove the
popularity of remote work. Another factor is the
technological factor. Technology is constantly
advancing, and cybersecurity risks have grown with
technology (Makos, 2024). If Airbnb does not stay on
top of the current technological advancements, then it
has the potential to hurt the company.
Legal factors can also affect Airbnb’s performance.
Airbnb operates in a highly regulated industry and
must comply with local laws in every city, state, and
country (Makos, 2024). In some high tourism areas
where short-term rentals are restricted or banned,
Airbnb’s ability to operate and grow may be limited. For
example, cities such as New York have strict rules,
requiring hosts to be physically present during a
guest’s stay and limiting the short-term rentals to no
more than two guests (Harper, 2024). Failure to comply
with these regulations can prevent Airbnb from doing
business in key tourist destinations. Environmental
factors also play a role. As climate change awareness
grows, so does the demand for sustainable travel. This
could lead to reduced travel overall, as people choose
to limit their trips to reduce their environmental impact.
While the local communities, governing bodies, guests,
shareholders, and employees are important
stakeholders, the most important stakeholder is the
host of the Airbnb location (Airbnb, 2020). This is
because without them, Airbnb would not be able to
make a profit from the rental listings. When considering
the host, the question should be asked about what
factors affect the host’s listing(s) and why? Of course,
the factors from the PESTLE analysis will affect the
host, but are there additional factors that can affect
them, such as geographical area, the type of listing
offered, price, etc.?
To understand the factors affecting the Airbnb hosts,
an analysis was conducted using secondary data from
Airbnb bookings in New York during 2019. This year
was chosen because it reflects a period before the
COVID-19 pandemic, which significantly impacted
travel and work patterns due to concerns of health and
safety. The rise of remote work and public safety during
the pandemic could distort the data, so using 2019 data