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The current generation has seen a major increase in usage of restaurants which has given birth to applications which let the consumers rate the restaurants on a scale of 1 to 5. This rating is letting the other consumers to know where they are putting their money. This sudden increase in the Restaurant industry and due to the availability of ratings of the restaurants consumers buying behavior has been affected in a tremendous way. This paper aims at analyzing the role of consumer reviews on the buying behavior of consumers, the perception of the consumers on various review platforms and to study a qualitative impact of consumer reviews on restaurants.
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Volume-04 ISSN: 2455-3085 (Online)
Issue-02 RESEARCH REVIEW International Journal of Multidisciplinary
February -2019 www.rrjournals.com [UGC Listed Journal]
RRIJM 2015, All Rights Reserved 532 | P a g e
A study on Impact of Consumer Reviews on Consumer Behavior with reference to
Restaurants in Bengaluru
*1Akash Goyal, 2Rahul Bhagtani, 3Udei Pratap Singh & 4Prof Natchimuthu N
1,2,3Student, Christ University, Bengaluru, Karnataka (India)
4Professor, Christ University, Bengaluru, Karnataka (India)
ARTICLE DETAILS
ABSTRACT
Article History
Published Online: 20 February 2019
The current generation has seen a major increase in usage of restaurants which has given
birth to applications which let the consumers rate the restaurants on a scale of 1 to 5. This
rating is letting the other consumers to know where they are putting their money. This
sudden increase in the Restaurant industry and due to the availability of ratings of the
restaurants consumers buying behavior has been affected in a tremendous way. This paper
aims at analyzing the role of consumer reviews on the buying behavior of consumers, the
perception of the consumers on various review platforms and to study a qualitative impact of
consumer reviews on restaurants.
Keywords
Consumer ratings, Consumer
behaviour, Online review platform
*Corresponding Author
Email: akashkhs171[at]gmail.com
1. Introduction
As Social media usage is growing rapidly, the restaurant
industry has also seen a significant growth and impact of social
media on consumers in terms of usage and reliability. The very
fact that social media is giving people a platform to voice their
opinions in terms of restaurant experience, proves the point
that the world is going through a major shift in selection of a
restaurant by consumers. The impact of consumer feedback
and reviews are rising significantly especially in the restaurant
business. Restaurants are hiring people and spending a lot of
money to take care of the same. Expenditure done on this
purpose is not considered to be an expense but rather to be an
investment in the long run. Food delivery applications like
Zomato which lists restaurants and let the consumers rate the
restaurants as per their experience are changing the market for
the restaurant industry. This study aims at understanding
whether or not the reviews and feedbacks given by consumers
make a significant impact on the buying behavior of other
consumers with reference to restaurants in Bengaluru.
2. Literature Review
Online Reviews
The consumer review plays a significant role in influencing
the purchasing behavior of consumers. There are many
studies done by various scholars on the impact of reviews on
consumer buying behavior. To decide quickly and the best
product with various options and competition, consumers rely
on various reviews such as ratings, description, picture
reviews, additional reviews, which allows consumers to take a
quick decision in a short time. (Zan Mo, 2015). Social media
allows consumers to investigate, label and criticise which
impacts other consumers (Elisabeta Ioanas, 2014). Along with
the online reviews, brand reputation, restaurant atmosphere,
and brand character plays a significant role to bring positive
feedbacks and reviews which impact the consumers behaviour
((Tung-Ju Wu & Wu, 2015). The online reviews include many
attributes which have different implications in consumer
behaviour. Attributes such as Food quality, service quality,
price and many other attributes has a different implications
(Reviews) in consumer buying decision (Gunden, 2017). The
studies have consistently found that the characteristics of
online reviews (i.e., star ratings, review richness, and valence
of reviews) (Beverley A.Sparks, 2011) and of review providers
(i.e., identity disclosure and level of expertise) (Ivar
E.Vermeulen, 2009) have positive influences on purchase
decision.
Word of Mouth Marketing
Word of Mouth marketing (WOM) has come up
tremendously in the recent ages. There are many researches
done on the same to analyse the impact of word of mouth
marketing on the sales of restaurants. Consumer nowadays
largely consider online reviews as a form of E-WOM
(Electronic Word of Mouth) in decision making process. Online
reviews enable people to obtain trustworthy and credible
information as compared to information provided by marketers
which might be viewed with scepticism and possible disbelief.
(Juan Luis Nicolau, 2015). E-WOM is more influential than
traditional WOM, which than extends far beyond from the
members of physical communities (Anish Parikh, 2014)
3. Objective
1. To analyze the role of consumer reviews on buying
behavior of consumers with reference to restaurants.
2. To study the perception of consumers on various
review platforms
3. To study the factors that influence restaurant
selection by consumers.
4. Data and methodology
This study takes both quantitative and qualitative
approach to address the proposed research questions. The
main purpose of the paper is to examine how consumer
reviews influence the buying behavior of consumers with
reference to restaurants and to study the ranking of various
Volume-04, Issue-02, February-2019 RESEARCH REVIEW International Journal of Multidisciplinary
RRIJM 2015, All Rights Reserved 533 | Page
consumer reviews platform and ranking of various factors of
restaurant which affects the selection of a restaurant.
The target population for this paper were the residents of
Bengaluru who have visited restaurants and also who check
reviews for restaurant selection. The online survey was created
in Google Forms and the forms were forwarded. The survey
received 288 responses.
For the purpose of data analysis, SPSS was used to
analyze the data. For checking the validity of the responses
collected, Cronbach’s coefficient alpha was used. This paper
used frequency tables to analyze the responses and then
further ahead Crosstabs is used on the responses.
5. Results and inferences
5.1 Reliability test results
The overall value of Cronbach’s alpha for this study was
calculated and it was 0.91 and hence it was considered
reliable.
5.2 Frequency Tables
Table 1: Frequency of Respondents on the basis of frequency of dining at a restaurant
Frequency
Percent
Cumulative Percent
Valid
Last week
205
71.2
71.2
Last month
58
20.1
91.3
3 months ago,
10
3.5
94.8
6 months ago,
5
1.7
96.5
More than a year ago
3
1.0
97.6
I haven't been at a restaurant
7
2.4
100.0
Total
288
100.0
The aim was to find how many consumers had dined in
restaurants in a certain stipulated time period. The results establish the fact that a lot of people regularly dine in
restaurants which can be confirmed from Table1.
Table 2: Frequency of Respondents on the basis of checking reviews before dining
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
Yes
177
61.5
61.5
61.5
No
111
38.5
38.5
100.0
Total
288
100.0
100.0
The aim was to find the number of respondents who check
reviews before dining in a restaurant.
The results establish the fact that a majority of people
(61.5%) check online reviews before dining at restaurants,
whereas 38.5% do not check reviews before dining at
restaurants.
Table 3: Frequency of Respondents on the basis of frequency of checking review
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
Sometimes
34
11.8
19.2
19.2
Half of the time
27
9.4
15.3
34.5
Most of the time
89
30.9
50.3
84.7
Always
27
9.4
15.3
100.0
Total
177
61.5
100.0
Missing
System
111
38.5
Total
288
100.0
The aim was to identify how frequently the respondents
check reviews before dining.
The results suggested that majority of the
respondents check reviews most of the time before
dining in a restaurant.
Hence it implies that reviews are significant for
consumers and restaurants.
Table 4: Frequency of Respondents on the basis of trusting other dinner’s reviews
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
Neutral
62
21.5
35.0
35.0
Agree
99
34.4
55.9
91.0
Volume-04, Issue-02, February-2019 RESEARCH REVIEW International Journal of Multidisciplinary
RRIJM 2015, All Rights Reserved 534 | Page
Strongly Agree
16
5.6
9.0
100.0
Total
177
61.5
100.0
Missing
System
111
38.5
Total
288
100.0
The aim was to find the level of trust which consumers
tend to show on the reviews provided by other consumers in
terms of dining in restaurants. Five options were given to the
respondents to choose from a) Strongly Agree b) Agree c)
Neutral d) Disagree and e) Strongly Disagree. It was found that
all the respondents agreed or strongly agreed to trusting other
consumer reviews as we can see on Table 4.
This establishes the fact that people do rely and trust other
consumer reviews before dining at a restaurant.
Table 5.1:Frequency of Checking Reviews and Age
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Data-Do you check reviews
Yes
10
161
2
4
177
No
15
79
5
12
111
Total
25
240
7
16
288
Table 5.2:Chi-Square Test on checking reviews and age.
Value
df
Pearson Chi-Square
20.240a
3
.000
Null Hypothesis (H0) No Significant impact of age on
responses to “Do you check reviews?”.
The Significance of Pearson Chi-Square gives a P
value of .0001i.e. less than 5% which indicates there
is some significant impact of Age on Checking
Reviews (Table 5.2.)
Therefore, it can be implied that age does influence
on Checking Reviews.
Therefore, Null Hypothesis was rejected.
Table 6.1:Frequency of Trusting other dinner’s Reviews and Residential Status
Count
Resident
Total
Yes
No
I trust other diner's reviews about
restaurants
Neutral
20
42
62
Agree
11
88
99
Strongly Agree
5
11
16
Total
36
141
177
Table 6.2:Chi-Square Test on Trusting other dinner’s Reviews and Residential status.
Value
df
Pearson Chi-Square
11.815a
2
.003
Null Hypothesis (H0) There is no significant impact of being
a permanent resident and responses to “I trust other diner's
reviews about restaurants”.
Analysis-
The Significance of Pearson Chi-Square gives a P
value of .003 i.e. less than 5% which indicates there is
some significant impact of being a resident on “I trust
other diner’s reviews”. (Table 6.2.)
Therefore, it can be implied that being a resident does
influence consumers perception on trusting other
diner reviews information.
Therefore, Null Hypothesis was rejected.
Table 7:Frequency Food Quality Ranking and Age.
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Ranking [Food Quality]
Most Important
6
101
2
2
111
Important
1
13
0
0
14
Neutral
1
4
0
0
5
Volume-04, Issue-02, February-2019 RESEARCH REVIEW International Journal of Multidisciplinary
RRIJM 2015, All Rights Reserved 535 | Page
Less Important
0
7
0
1
8
Least Important
2
36
0
1
39
Total
10
161
2
4
177
The aim was to find the significance of Food Quality factor
for a consumer before deciding to dine at a restaurant: -
It suggests that among all the factors given, food
quality was considered and preferred as the most
important factor by consumers while selecting a
restaurant.
Table 8:Frequency Service Quality Ranking and Age.
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Ranking [Service Quality]
Most Important
0
6
0
1
7
Important
2
79
1
2
84
Neutral
4
43
0
1
48
Less Important
2
30
1
0
33
Least Important
2
3
0
0
5
Total
10
161
2
4
177
The aim was to find the significance of Service Quality
factor for a consumer before deciding to dine at a restaurant: -
It suggests that among all the factors given, service
quality was considered and preferred as an important
factor by a consumer but not as much as food quality
while choosing a restaurant.
Table 9:Frequency Atmosphere Ranking and Age.
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Ranking [Atmosphere]
Most Important
0
14
0
0
14
Important
3
25
1
1
30
Neutral
5
83
1
2
91
Less Important
1
29
0
0
30
Least Important
1
10
0
1
12
Total
10
161
2
4
177
The aim was to find the significance of Atmosphere
(Ambience) factor for a consumer before deciding to dine at a
restaurant: -
It suggests that atmosphere was neither considered
important nor not-important while choosing a
restaurant by a consumer.
Table 10:Frequency Number of Online Reviews Ranking and Age.
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Ranking [Number of Online
Reviews]
Most Important
2
16
0
1
19
Important
3
23
0
0
26
Neutral
0
14
0
0
14
Less Important
1
54
1
2
58
Least Important
4
54
1
1
60
Total
10
161
2
4
177
The aim was to find the significance of Number of reviews
as a factor for a consumer before deciding to dine at a
restaurant: -
It suggests that number of online reviews do not play
a significant role among all the factors before dining.
Volume-04, Issue-02, February-2019 RESEARCH REVIEW International Journal of Multidisciplinary
RRIJM 2015, All Rights Reserved 536 | Page
Table 11:Frequency of overall Restaurant Rating Ranking and Age.
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Ranking [Overall Restaurant
Ratings]
Most Important
2
24
0
0
26
Important
1
21
0
1
23
Neutral
0
17
1
1
19
Less Important
6
41
0
1
48
Least Important
1
58
1
1
61
Total
10
161
2
4
177
The aim was to find the significance of Overall Restaurant
Rating as a factor for a consumer before deciding to dine at a
restaurant: -
It suggests that number of Overall Restaurant Rating
does not play a significant role among all the factors
before dining.
Table 12:Frequency of Word of Mouth Rating and Age.
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Rating [Word of Mouth]
No Usage
1
13
0
0
14
Very Low
1
17
1
0
19
Low
3
18
1
0
22
Neutral
1
18
0
0
19
High
1
40
0
2
43
Very High
3
55
0
2
60
Total
10
161
2
4
177
The aim was to find the impact of Word of Mouth as a
factor for influencing a consumer to visit a restaurant.
It suggests that Word of Mouth was an important
consideration for any restaurant as many people rely
on word of mouth and prefer it above other modes of
media.
Hence it implies that even though there are so many
modes of online and offline reviews, Word of Mouth
was still more relied upon.
Table 13:Frequency of Food Application Rating and Age.
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Rating [Food Applications]
No Usage
0
8
0
1
9
Very Low
1
19
1
0
21
Low
0
14
0
0
14
Neutral
2
38
0
1
41
High
3
39
1
1
44
Very High
4
43
0
1
48
Total
10
161
2
4
177
The aim was to find the impact of Food Applications as a
factor for influencing a consumer to visit a restaurant.
It suggested that Food Application was an important
consideration for any restaurant. It implies that many
respondents check food applications and rely highly
on food application before making a decision to visit a
restaurant.
Table 14:Frequency of Online Platform Rating and Age.
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Rating [Online Platforms]
No Usage
0
10
1
2
13
Very Low
1
14
0
0
15
Volume-04, Issue-02, February-2019 RESEARCH REVIEW International Journal of Multidisciplinary
RRIJM 2015, All Rights Reserved 537 | Page
Low
2
33
1
0
36
Neutral
3
54
0
2
59
High
2
35
0
0
37
Very High
2
15
0
0
17
Total
10
161
2
4
177
The aim was to find the impact of Online Platforms as a
factor for influencing a consumer to visit a restaurant.
Online Platform here includes Restaurant websites,
Social media platforms (Facebook, Instagram).
It suggests that Online platform stands in a neutral
position where some consumers gets influenced by
the ratings and reviews whereas some do not get
influenced.
It also implies that even though it is a neutral factor,
many respondents do consider it as an important
factor.
Table 15:Frequency of Food Blogs and Vlogs Rating and Age.
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Rating [Food Blogs and Vlogs]
No Usage
1
34
0
3
38
Very Low
0
26
2
0
28
Low
4
42
0
0
46
Neutral
1
31
0
1
33
High
2
17
0
0
19
Very High
2
11
0
0
13
Total
10
161
2
4
177
The aim was to find the impact of Food Blogs and Vlogs
as a factor for influencing a consumer to visit a restaurant.
It suggests that Food Blogs and Vlogs do not
significantly influence the consumers.
It also implies that consumers don’t really visit Food
Blogs and Vlogs currently to rely on the restaurant
information and reviews as compared to other modes
of media.
Table 16:Frequency of Newspaper Review Usage Rating and Age.
Count
Age
Total
Less Than 18
18 to 24
25 to 34
34 and beyond
Rating [Newspaper
Reviews]
No Usage
5
69
1
2
77
Very Low
3
37
0
0
40
Low
0
15
1
0
16
Neutral
0
17
0
0
17
High
1
15
0
1
17
Very High
1
8
0
1
10
Total
10
161
2
4
177
The aim was to find the impact of Newspaper Reviews as a
factor for influencing a consumer to visit a restaurant.
It suggests that Newspaper reviews are considered
not very important by most of the respondents.
6. Limitations of the study
1. This study does not analyze the impact of food prices
on consumers.
2. The study was limited only to Bangalore City.
7. Conclusion
It was found that restaurant consumers rely heavily on
reviews and then take decisions on dining based on these
reviews. Our analysis yields that majority of people check
reviews before selecting a restaurant.
The results suggested that majority of respondents
frequently check reviews. It was also found 56% respondents
trust other consumer reviews before dining in at restaurants.
The study found that there is no significant impact of age
on the frequency of checking reviews. The study also found
that a significant impact of Age existed on checking reviews. It
was also found that there is no significant impact between of
age on trusting other diner’s reviews.
The study concluded that there is no significant impact
ofresident in frequency of checking reviews. It was found there
is some significant impact of being a resident and trusting other
diner reviews.
It was found that there is no significant impact of being a
resident and checking online reviews.
Volume-04, Issue-02, February-2019 RESEARCH REVIEW International Journal of Multidisciplinary
RRIJM 2015, All Rights Reserved 538 | Page
It was found that consumer ranked food quality as most
important before dining in at a restaurant followed by Service
Quality where consumer ranked it important, followed by
Atmosphere. The respondents rated Number of online reviews
and Overall restaurant ratings as least important factor as
compared to other attributes.
It was found that Word of mouth has the highest rating and
was the most preferred medium by consumers before selecting
a restaurant followed by Food Applications. Whereas online
platforms have found to have a neutral impact on selecting a
restaurant. Food Blogs and Vlogs were found to have a very
low rating in terms of usage. Respondents rated Newspaper
Reviews as the least important.
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... From 1980 to till to date, the sales of the restaurant industry have increased drastically from US$42.8 billion to US$536.7 billion (approx.), which is more than 10 times (Goyal et al., 2019). Extant hospitality research has facilitated in getting comprehensive understanding of the factors that lead to of customers' satisfaction with hotels/cafeterias/restaurants (Ivkov et al., 2018). ...
... Extant hospitality research has facilitated in getting comprehensive understanding of the factors that lead to of customers' satisfaction with hotels/cafeterias/restaurants (Ivkov et al., 2018). In some of these studies, researchers have focused extensively on the customers' dining behavior, because food is a vital element to comprehend one's society or culture (Goyal et al., 2019;Konuk, 2019;Ryu & Han, 2010;Zhang et al., 2019), while other researchers have been interested in identifying the important service dimensions of restaurant, which include menu, cleanliness, style, price, ambience, location (Prendergast & Man, 2002), chef, service staff, and atmosphere (Emir, 2016). These service dimensions determine the dining behavior and revisit intention of the clientele. ...
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