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By Group: 05
Exaggeration in
fake vs authentic
online reviews
for luxury and
budget hotels
*****
Our team
Jahid Khan
Rahat
ID: 2123021047
Md.
Munirruzzaman
ID: 2123021043
Md. Muzammel
Haque
ID: 2123021041
Mehedi Hanan
ID: 2123021008
Md. Asifur
Rahaman
ID: 21230210263
Shahjalal Mia
ID: 2123021049
Research Design
 It can answer the research
questons & control the
variance
 A Research Design is simply a
structural framework /Blue
print / Plan of various research
methods as well as techniques
that are utilized by a
researcher.
Md. Muzammel Haque
ID: 2123021041
Research Design
Md. Muzammel Haque
ID: 2123021041
Research Design type = Exploratory
 Research process is flexible & unstructured
 Sample is small & non- representive
 Analysis of primary data is qualitative
 Findings are tentative
 Research methods are informal
Md. Muzammel Haque
ID: 2123021041
Research Design
 Developed & examined a
research model
 Factor analysis was adopted &
Regression analysis
 This study also offered areas worthy of more research efforts
from perspectives of practitioners & researchers
Md. Muzammel Haque
ID: 2123021041
Research Design
 Practical implications: to find out the ways of
increasing consumers’ booking intentions in the
specific hotel contexts.
 A major theoretical contribution of this paper is its
comprehensiveness in examining features of review content
as well as its source simultaneously.
 online reviews as a marketing tool
Md. Muzammel Haque
ID: 2123021041
Elements of Research Design
The method applied for analyzing collected details
Type of research methodology
Accurate purpose statement
Probable objections for research
Techniques to be implemented for collecting and analyzing research
Timeline
Measurement of analysis
Settings for the research study
Md. Muzammel Haque
ID: 2123021041
2
6 3
5 4
Six 6
features
of online
reviews
content
usefulness reviewer expertise
Comprehensiveness
interrelationships among
features of online reviews
timeliness
Valence
(negative and positive)
volume
Findings 6 content + 1 source
Md. Muzammel Haque
ID: 2123021041
Data Sources
Primary data Secondary data
Mehedi Hanan
ID: 2123021008
Secondary Data
Data Collection platforms: Agoda.com,
Expedia.com, and Hotels.com.
Data collection period- six months
Participants-134
Mehedi Hanan
ID: 2123021008
A Sampling plan is a detailed outline of which
measurements will be taken at what times, which
materials, in what manner, and by whom.
Sample planning
Md. Asifur Rahaman
ID: 21230210263
Sample selection process
1. Identify the Target population:
five popular Asian destinations—
● Bangkok,
● Hong Kong,
● Kuala Lumpur,
● Singapore, and
● Tokyo.
1. Select a sampling frame:
Authentic reviews of three online platforms:
● Agoda.com,
● Expedia.com, and
● Hotels.com
Reviews are posted only by bona fide travelers who had paid and actually stayed in a given hotel.
Md. Asifur Rahaman
ID: 21230210263
Sample selection process
3. Specify the sampling technique:
Used snowballing sample selection technique-
Set eligibility criteria to select samples. here
● Regular readers or contributors on
review websites.
● Must have had travel experience
within the last year.
● The study disseminated
○ offline and
○ online word-of-mouth.
Snowballing sample selection technique
Md. Asifur Rahaman
ID: 21230210263
Sample selection process
4. Determine the sample size:
Selection from each country
● 10 hotels (5 luxury + 5 budget).
● For each hotel, 40 entries (20 positive + 20
negative)
400 authentic reviews uniformly distributed across
● Hotel category—luxury and budget—and
● Review polarity—positive and negative.
Md. Asifur Rahaman
ID: 21230210263
Sample selection process
5. Execute the sampling plan:
● Collect data for six months
● 134 participants
○ aged 21–25 years: 40,
○ aged 26–35 years: 64,
○ aged 36–45 years: 30;
○ educational background: minimally
undergraduate students;
○ gender: 63 females, 71 males
Md. Asifur Rahaman
ID: 21230210263
Reviews acknowledged criteria
 English comprising meaningful titles
 Latter being at least 150 characters in length
 Reviews must have been posted as recently
Jahid Khan Rahat
ID: 2123021047
Software
 SPSS
 Typeform
Tool
 Table
 Line chart
Data analysis tool
Jahid Khan Rahat
ID: 2123021047
40
309
45
6
 50% luxury and 50% budget
 Required 6 months to collect data
 ANOVA is calculated as sample size is
above 30
 Critical value calculated form t table
Reviews collection criteria
 Hypothesis evaluate based on P and F value
Jahid Khan Rahat
ID: 2123021047
Measurement
Treated as
negative
Treated as
Positive
Dataset
Luxury
Positive
Fake Authentic
Negative
Fake Authentic
Budget
Positive
Fake Authentic
Negative
Fake
Authentic
Sample reviews in the dataset
Jahid Khan Rahat
ID: 2123021047
Review analysis
 Adjectives (e.g., awesome, awful)
Shahjalal Mia
ID: 2123021049
 Adverbs (e.g., beautifully, horribly)
 Nouns (e.g., hotel, room)
 Verbs (e.g., visited, stayed)
Descriptive Statistical Analysis
Shahjalal Mia
ID: 2123021049
Presentation
Shahjalal Mia
ID: 2123021049
Discussion
Four key findings of the paper
First, with a finer-grained
conceptualization of exaggeration
in reviews compared with previous
works
Second, this paper found that the
contextual idiosyncrasy created by
crossing hotel category
Third, the paper empirically
confirms that individuals
Fourth, the paper found that
humans strengthen their online
information processing vigilance
under disconfirmatory contexts.
Md. Munirruzzaman
ID: 2123021043
Theoretical contributions
Exaggeration should be measured in not only descriptions but also titles
of reviews.
This paper busts the myth that fake reviews are always more exaggerated than
authentic ones.
Finally, the paper contributes to the online review literature by looking into both
review writers and review readers in conjunction.
Md. Munirruzzaman
ID: 2123021043
Limitations and further research
direction
The paper should be viewed in light of a few limitations that future
research should address
Md. Munirruzzaman
ID: 2123021043
Exaggeration in fake vs authentic online reviews for luxury and budget hotels

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Exaggeration in fake vs authentic online reviews for luxury and budget hotels

  • 1. By Group: 05 Exaggeration in fake vs authentic online reviews for luxury and budget hotels *****
  • 2. Our team Jahid Khan Rahat ID: 2123021047 Md. Munirruzzaman ID: 2123021043 Md. Muzammel Haque ID: 2123021041 Mehedi Hanan ID: 2123021008 Md. Asifur Rahaman ID: 21230210263 Shahjalal Mia ID: 2123021049
  • 3. Research Design  It can answer the research questons & control the variance  A Research Design is simply a structural framework /Blue print / Plan of various research methods as well as techniques that are utilized by a researcher. Md. Muzammel Haque ID: 2123021041
  • 4. Research Design Md. Muzammel Haque ID: 2123021041
  • 5. Research Design type = Exploratory  Research process is flexible & unstructured  Sample is small & non- representive  Analysis of primary data is qualitative  Findings are tentative  Research methods are informal Md. Muzammel Haque ID: 2123021041
  • 6. Research Design  Developed & examined a research model  Factor analysis was adopted & Regression analysis  This study also offered areas worthy of more research efforts from perspectives of practitioners & researchers Md. Muzammel Haque ID: 2123021041
  • 7. Research Design  Practical implications: to find out the ways of increasing consumers’ booking intentions in the specific hotel contexts.  A major theoretical contribution of this paper is its comprehensiveness in examining features of review content as well as its source simultaneously.  online reviews as a marketing tool Md. Muzammel Haque ID: 2123021041
  • 8. Elements of Research Design The method applied for analyzing collected details Type of research methodology Accurate purpose statement Probable objections for research Techniques to be implemented for collecting and analyzing research Timeline Measurement of analysis Settings for the research study Md. Muzammel Haque ID: 2123021041
  • 9. 2 6 3 5 4 Six 6 features of online reviews content usefulness reviewer expertise Comprehensiveness interrelationships among features of online reviews timeliness Valence (negative and positive) volume Findings 6 content + 1 source Md. Muzammel Haque ID: 2123021041
  • 10. Data Sources Primary data Secondary data Mehedi Hanan ID: 2123021008
  • 11. Secondary Data Data Collection platforms: Agoda.com, Expedia.com, and Hotels.com. Data collection period- six months Participants-134 Mehedi Hanan ID: 2123021008
  • 12. A Sampling plan is a detailed outline of which measurements will be taken at what times, which materials, in what manner, and by whom. Sample planning Md. Asifur Rahaman ID: 21230210263
  • 13. Sample selection process 1. Identify the Target population: five popular Asian destinations— ● Bangkok, ● Hong Kong, ● Kuala Lumpur, ● Singapore, and ● Tokyo. 1. Select a sampling frame: Authentic reviews of three online platforms: ● Agoda.com, ● Expedia.com, and ● Hotels.com Reviews are posted only by bona fide travelers who had paid and actually stayed in a given hotel. Md. Asifur Rahaman ID: 21230210263
  • 14. Sample selection process 3. Specify the sampling technique: Used snowballing sample selection technique- Set eligibility criteria to select samples. here ● Regular readers or contributors on review websites. ● Must have had travel experience within the last year. ● The study disseminated ○ offline and ○ online word-of-mouth. Snowballing sample selection technique Md. Asifur Rahaman ID: 21230210263
  • 15. Sample selection process 4. Determine the sample size: Selection from each country ● 10 hotels (5 luxury + 5 budget). ● For each hotel, 40 entries (20 positive + 20 negative) 400 authentic reviews uniformly distributed across ● Hotel category—luxury and budget—and ● Review polarity—positive and negative. Md. Asifur Rahaman ID: 21230210263
  • 16. Sample selection process 5. Execute the sampling plan: ● Collect data for six months ● 134 participants ○ aged 21–25 years: 40, ○ aged 26–35 years: 64, ○ aged 36–45 years: 30; ○ educational background: minimally undergraduate students; ○ gender: 63 females, 71 males Md. Asifur Rahaman ID: 21230210263
  • 17. Reviews acknowledged criteria  English comprising meaningful titles  Latter being at least 150 characters in length  Reviews must have been posted as recently Jahid Khan Rahat ID: 2123021047
  • 18. Software  SPSS  Typeform Tool  Table  Line chart Data analysis tool Jahid Khan Rahat ID: 2123021047
  • 19. 40 309 45 6  50% luxury and 50% budget  Required 6 months to collect data  ANOVA is calculated as sample size is above 30  Critical value calculated form t table Reviews collection criteria  Hypothesis evaluate based on P and F value Jahid Khan Rahat ID: 2123021047
  • 21. Dataset Luxury Positive Fake Authentic Negative Fake Authentic Budget Positive Fake Authentic Negative Fake Authentic Sample reviews in the dataset Jahid Khan Rahat ID: 2123021047
  • 22. Review analysis  Adjectives (e.g., awesome, awful) Shahjalal Mia ID: 2123021049  Adverbs (e.g., beautifully, horribly)  Nouns (e.g., hotel, room)  Verbs (e.g., visited, stayed)
  • 25. Discussion Four key findings of the paper First, with a finer-grained conceptualization of exaggeration in reviews compared with previous works Second, this paper found that the contextual idiosyncrasy created by crossing hotel category Third, the paper empirically confirms that individuals Fourth, the paper found that humans strengthen their online information processing vigilance under disconfirmatory contexts. Md. Munirruzzaman ID: 2123021043
  • 26. Theoretical contributions Exaggeration should be measured in not only descriptions but also titles of reviews. This paper busts the myth that fake reviews are always more exaggerated than authentic ones. Finally, the paper contributes to the online review literature by looking into both review writers and review readers in conjunction. Md. Munirruzzaman ID: 2123021043
  • 27. Limitations and further research direction The paper should be viewed in light of a few limitations that future research should address Md. Munirruzzaman ID: 2123021043