The Ascent of the Sharing Frugality PDF

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The Ascent of the Sharing Frugality –
Assessing the Influence of Host and Guest on the Online
Hotel Business of Airbnb
1
Abstract
The study for this article was designed to examine the differentiation of influence in Airbnb's
business model, as demonstrated by valuation models for the two additional datasets. The main
objective of the article was to study and quantify the qualification models for hosts and guests of
Airbnb. The objective was to clearly indicate the value of the qualification and the funds for the
daily salary of guest comments. Two separate linear regression models related to the guest and
guests were included in the research context.
Among the 30478 observations of the public data set, only credible estimates of 22155 subjects
are available. For example, the remaining observations 8323 in the multiple regression
evaluation models were considered missing. The re-estimated linear regression model for public
dataset was evaluated asRS=0.005P0.594NB1.23RT1.048B+96.24. The estimation or
prediction percentage did not increase with the removal of room type and the final model was
found to be statistically significant (F = 113.82, p < 0.05). The estimated linear equation of the
final model with survey data wasSAT=2.09CA+0.81SP+1.88, where wish for continuing
with Airbnb (CA) (t = 3.62, p < 0.05) and span of association with Airbnb (SP) (t = 3.95, p <
0.05) were found to significantly estimate the satisfaction level of the owners.
The conclusion of this article was that the most successful way to avoid the last minute
cancellation and improvement of the customer base is to use the new information technology for
advertising and millions of travelers through the available to reach the link. The study can serve
as a guide for future online travel agents to move to an acceptable number of users. Future
analysis to measure the impact of having alternative facilities, more than one Airbnb property
nearby has not been evaluated.
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Table of Contents
Abstract.......................................................................................................................................................................................2
Table of Figures.......................................................................................................................................................................7
Question 1:Business Objective..........................................................................................................................................8
Online Marketing................................................................................................................................................................8
About Airbnb........................................................................................................................................................................9
Research Aim.....................................................................................................................................................................10
Question 2:Depiction of Datasets..................................................................................................................................11
Public Dataset with Guest Reviews..........................................................................................................................11
Survey Dataset with Host Ratings.............................................................................................................................13
Question 3:Descriptive Summary of the Datasets..................................................................................................16
Public Dataset with Guest Reviews..........................................................................................................................16
Survey Dataset with Host Ratings.............................................................................................................................18
Question 4:Experimental Design...................................................................................................................................23
Appropriateness of Regression Model....................................................................................................................23
Assumptions of the Regression Model....................................................................................................................23
Regression Model with Guest Dataset.....................................................................................................................24
Regression Model with Host Dataset.......................................................................................................................25
Question 5: Discussion.......................................................................................................................................................27
Conclusion...............................................................................................................................................................................27
Limitations..............................................................................................................................................................................28
Suggestions for Future Analysis.....................................................................................................................................29
References...............................................................................................................................................................................30
Appendix:.................................................................................................................................................................................33
Introduction.......................................................................................................................................................................33
Data Depiction..................................................................................................................................................................34
Regression Models..........................................................................................................................................................35
Appendices..............................................................................................................................................................................36
Responses of the Survey...............................................................................................................................................46
Public Dataset...................................................................................................................................................................48
3
Table of Figures
Figure 1: Neighborhood of Guest Houses in Public Dataset...................................................................................8
Figure 2: Airbnb Room types from Guest data............................................................................................................8
Figure 3: Gender Distribution of Hosts..........................................................................................................................9
Figure 4: Location of the Guest Houses as per the Hosts......................................................................................10
Figure 5: Education Qualification of Hosts.................................................................................................................10
Figure 6: Number of Reviews by the Guests..............................................................................................................12
Figure 7: Property Type by Guests................................................................................................................................12
Figure 8: Number of Beds from Guest Feedback.....................................................................................................13
Figure 9: Distribution of Price paid Guests................................................................................................................13
Figure 10: Monthly Income Level of Hosts.................................................................................................................14
Figure 11: Duration of Association of Hosts with Airbnb....................................................................................14
Figure 12: Hosts View on Profitability of Airbnb.....................................................................................................15
Figure 13: Number of Hosts Want to Continue with aIRBNB.............................................................................16
Figure 14: Rent Charged by the Hosts..........................................................................................................................16
Figure 15: Satisfaction Scores of Hosts........................................................................................................................17
4
Question 1:Business Objective
Online Marketing
The research question of the article was framed to explore the differentiating impact on the
business model of Airbnb as illustrated by the estimation models for the two complementary data
sets.The scholar investigated: Whether there was an analogous trend in ranking of
satisfaction levels by hosts and guests for facilities obtained.The two complementary data
sets of Airbnb, collected from five provinces in the United States were used for the purpose of
the study.
The electronic marketplace is a new business field created by the development of the Internet,
with more than a billion potential clients. The common economy is a sustainable economic
system built around the sharing of private resources (Alizadeh, Farid, and Sarkar, 2018). This
relatively new system is based primarily on information technology, allowing people and other
non-profit organizations and non-profit organizations to do things, knowledge and amenities in
the facility. In addition to renting a broker, Airbnb is also a social network that allows users to
share their experience and travel related benefits (Biega, Gummadi, and Weikum, 2018). The
survey was conducted on a web-based study published on the Tableau page.
About Airbnb
The shared economy is a sustainable economic system based on the distribution of private assets.
This relatively new system is mainly based on information technologies that allow individuals
and other commercial and non-profit organizations to exchange surplus capacities in the field of
goods, knowledge and services. Since trust and security are key factors in the sharing of private
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assets, the value of these assets is increased by exchanging only information about them
(Filippas, and Horton, 2017; Jung et al., 2016). The purpose of this research is to explore the
structure of Airbnb users and some of the pros and cons of this type of e-business. Data from this
study were processed using descriptive statistics.
The socio-economic phenomenon of tourism is based on the needs of people to change their
temporary residence. The current modern concept of tourism makes important changes in the
development of tourism and tourism (Zekanovic-Korona, and Grzunov, 2014). Modern and
sophisticated technologies have better communication and an important role on the Internet.
Eleven years ago, Airbnb started as one of the participants in the general economy. This includes
expatriates such as Uber and Lyft. These companies offer a wide range of Internet platforms and
applications that create new ways for people to share goods and services with unimaginable
extensions. They also function as virtual tampons, reducing transaction costs and weakening
systems that would otherwise be too burdensome. Therefore, there is enormous potential for
consumer benefits by promoting the consumption of community assets such as cars and
condominiums that are costly to buy, but which are often not yet met because their owners
cannot use them. Although these companies were still in the early stages, they grew fast and their
joint sales were rated highly.
But there are three things in common. Firstly, they are based on the last technological advances
to meet the needs of older consumers. This cannot be done sooner. Secondly, there are a wide
range of established industries, which are primarily biased by the division of the economy as a
new capacity to offer innovative alternatives. Third, they work in inter-cellular jurisdictions
because there are new and fundamentally different things that cannot be expected after the
adoption of the government regulations.The two major stakeholders of these models are
6
customers (guests) and employees (hosts) of the system. The synchronization of the two
stakeholders is very essential for these models to be successful. The satisfaction of guests with
amenities provided by hosts, and, facilities as well as support rendered by Airbnb management to
the hosts play deciding roles in the expansion of the business model.
Research Aim
The paper's main goal was to investigate and quantify the estimation models for the hosts of
Airbnb and the guests. The aim was to explicitly specify the significance of the rankings and
facilities on the daily wages from the reviews of the guests. The data set 1 for guests of the
random selected 30479 reviews written by guests was used as the reference to identify the
sustainability of the Airbnb model based on guest rankings. The datasets were complimentary
from the angle of the business model stakeholders. Customers' reviews and hosts appraisal of the
facilities of the model was used as two complementing factors in the sustainability model of
Airbnb. The article contains five stages of exploration. First, the pre-processing and data
description was provided for detail description to see Airbnb's data. Secondly, a descriptive
summary of each of the data sets has been provided. The third step was the estimation model
construction with both the data sets. Two separate linear regression models referenced to the host
and the guests have been taken in the amount of the investigation.
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Question 2:Depiction of Datasets
Public Dataset with Guest Reviews
The objective of this research is to present the possible criteria to evaluate the structure of the
content, to provide information on the continent, internal and external impulses, and the
flexibility and availability of the Airbnb database. The first database was collected from tableau
website containing public datasets (Airbnb, 2015). The first dataset contained information about
review ranking and cost of accommodation per night at Airbnb guesthouses. Information of
30479 feedbacks from guests was identified in the obtained public dataset. Data was available
under 10 variables (Edelman, and Luca, 2014). The neighborhood, property type, room type
were the three string variables with categorical information. Neighborhood contained
information on 5 different cities of United States with Airbnb accommodations. Property type
was the type of facilities available in the Airbnb guesthouses. 20 different facility categories
were present in the collected data (Edelman, and Luca, 2014). Three room types were "entire
home", "private room", and "shared room". Information was collected from 189 unique zip
codes, where the available number of rooms in Airbnb properties ranged between one and
eleven.This database was particularly selected as it reflected the satisfaction level of the guests
in five US cities, where the scholar wanted to conduct the research.
The second data generated from the survey response presented the views and satisfaction level of
the hosts with the present Airbnb support and payment system. The questions were aimed to
collect maximum possible information about the relation of hosts and Airbnb management.
Significant number of extreme outliers was observed in the data. Number of reviews greater than
242 for a particular guest house was seen to be an extreme outlier observation. Price of a
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