eWoM in Hospitality: Survey, Analysis, and Findings Report

This report analyzes the impact of Electronic Word of Mouth (eWoM) within the hospitality industry, specifically focusing on hotels in the UAE. The study utilizes survey data collected from five-star hotels to assess eWoM indicators, including the influence of online reviews, customer satisfaction, and brand image. The report outlines the methodology, including data collection, analysis using correlation, regression, and ANOVA, and discusses key findings. The analysis explores relationships between factors such as management level, annual revenue, and organizational culture, and their impact on customer perception. Key findings include that annual revenue significantly impacts responses related to finance and costs, while the number of employees and organizational ownership have less impact on responses. The report concludes with insights into the importance of eWoM and its relationship with online platforms like TripAdvisor, emphasizing the need for businesses to utilize technology for growth.

EWOM in the
Hospitality Industries

The Team
Mohamad Issa
1006234
MARNAN AL NAJAR
1036950
Fatema Mohammed
1073300
Akram Younis
1024392
Owais Al Dayeh
1075015

Agenda Brief understanding of word of mouth and Hospitality survey
details.
Introduction01
Background and Impacts of Electronic word of mouth.
Theoretical Background02
Representation of Hospitality survey results.
Data Table03
Report Conclusion
Conclusion05
Achieved results are evaluated.
Discussion of Results04

Introduction

1
Timeline Style
Word of
mouth is a
strategy used
in marketing.
It has proved
to be
successful for
most of the
organizations.
Word of
mouth
is a reflection
of customers’
experience.
In the social
media addicted
world, nearly
62 percent of
consumers
consult the
online review &
information
prior to any
purchase or
service.
4.3.2.
Word of
mouth
requires
people's
interest to get
involved in
talking about
it.

Hospitality Survey Details
Selection of Hotels Data Collection
& survey
Data
analysis
Result
Evaluation
4.
Results are evaluated
using p-value and
statistical significance
1.
The top hotels of UAE
are investigated.
 Numerical data is collected from the local hotels (5-star or more) to assess eWoM indicators in the hospitality industry of
UAE.
 The five hotels considered hotels are:
 Intercontinental Abu Dhabi
 Fairmont Bab Al Bahr
 Khalidya Palace Rahyann by Rotana
 Anantara Mangroves
 The St. Regis Abu Dhabi
2.
Data collection from
local hotels and the
survey sample size is
50 individuals.
Determining
Conclusion
3.
Data analysis is
performed using
correlation, regression
and ANNOVA methods.
5.
Concluding the results
of the survey.

Theoretical Background

Identified Facts
1
2
3
4
 For any business to flourish knowledge management (KM) is required.
 Follow the indicators of successful KM initiatives.
You can simply impress your audience and add a unique zing and
appeal to your Presentations.
Content Here
4
5  The TripAdvisor has a relationship between the total reviews and comparative ranking given to the hotel.
 Thus, the positive and negative results have direct impact on the number of reviews on a hotel’s
TripAdvisor rating.
 The elasticity of eWoM is extremely higher for the reviews posted by the
TripAdvisor.
 E-WOM, E-WOM variables, brand image, customer trust and customer satisfaction have high influence
on the intention to buy the service.
 The primary aspects noticed in hotels/restaurants include-Quality of food and their service, which leave
good/bad impact on the customers and allow the WOM to take place.
 Cost and atmosphere have no impact for creating word of mouth.

Data Table

Data Table
The data table for eWoM in Hospitality survey is represented below.

Data Table
Data and Reliability is represented below.
. Business Rules and Responsibilities
BR1 BR2 BR3 BR4 BR5 BR6 BR7 Sum
3 5 5 4 4 4 5 30
4 5 5 4 4 4 5 31
4 5 5 5 5 4 5 33
4 3 4 5 3 3 3 25
5 5 4 4 4 5 4 31
5 5 4 4 4 5 4 31
5 5 4 4 4 5 3 30
5 5 5 5 4 5 3 32
3 4 5 3 3 3 2 23
3 3 2 5 3 3 3 22
4 3 2 4 2 5 3 23
5 4 4 4 5 4 3 29
5 4 4 4 5 4 4 30
5 4 4 4 5 3 3 28
3 4 3 3 4 4 5 26
3 2 4 4 5 5 4 27
4 3 3 3 4 2 3 22
3 2 4 4 5 5 3 26
4 3 4 3 3 4 4 25
4 3 2 4 4 5 5 27
4 4 3 3 3 4 2 23
5 3 2 4 4 5 5 28
4 5 4 5 4 5 5 32
3 5 4 4 3 4 4 27
3 5 5 4 4 4 5 30
4 5 5 4 4 4 5 31
4 5 5 5 5 4 5 33
4 3 4 5 3 3 3 25
5 5 4 4 4 5 4 31
5 5 4 4 4 5 4 31
5 5 4 4 4 5 3 30
3 4 3 3 4 4 5 26
4 3 3 3 4 2 3 22
3 2 4 4 5 5 3 26
4 3 4 3 3 4 4 25
4 3 2 4 4 5 5 27
4 4 3 3 3 4 2 23
5 3 2 4 4 5 5 28
4 5 4 5 4 5 5 32
3 5 4 4 3 4 4 27
3 3 2 5 3 3 3 22
4 3 2 4 2 5 3 23
5 4 4 4 5 4 3 29
5 4 4 4 5 4 4 30
5 4 4 4 5 3 3 28
3 4 3 3 4 4 5 26
3 2 4 4 5 5 4 27
4 3 3 3 4 2 3 22
3 2 4 4 5 5 3 26
4 3 3 3 4 2 3 22

Data Table
Finance and Cost
Finance and costs
FC1 FC2 FC3 FC4 FC5 FC6 Sum
2 5 3 4 5 4 23
3 5 3 5 3 4 23
5 4 4 2 1 3 19
5 4 1 4 1 3 18
3 4 4 3 4 4 22
3 4 4 3 5 4 23
5 5 4 4 5 4 27
5 5 3 4 5 5 27
4 5 3 5 3 2 22
2 4 4 2 1 4 17
3 4 1 4 1 4 17
3 3 5 4 4 5 24
4 2 5 3 4 5 23
5 3 5 3 5 3 24
4 5 4 4 2 1 20
4 5 4 1 4 1 19
3 3 4 4 3 4 21
3 3 4 4 3 5 22
5 5 4 3 4 5 26
5 5 4 4 5 5 28
5 5 3 4 5 3 25
4 5 3 5 3 3 23
2 4 4 2 1 4 17
3 4 1 4 1 5 18
3 4 4 3 5 4 23
5 5 4 4 5 4 27
5 5 3 4 5 5 27
4 5 3 5 3 2 22
2 4 4 2 1 4 17
3 4 1 4 1 4 17
3 3 5 4 4 5 24
4 2 5 3 4 5 23
5 3 5 3 5 3 24
3 3 4 4 3 4 21
3 3 4 4 3 5 22
5 5 4 3 4 5 26
5 5 4 4 5 5 28
5 5 3 4 5 3 25
4 5 3 5 3 3 23
5 5 4 4 5 4 27
5 5 3 4 5 5 27
4 5 3 5 3 2 22
3 3 4 4 3 5 22
5 5 4 3 4 5 26
5 5 4 4 5 5 28
5 5 3 4 5 3 25
4 5 3 5 3 3 23
2 4 4 2 1 4 17
3 4 1 4 1 5 18
4 5 4 1 4 1 19