The effect of perceived waiting time on customer's satisfaction: A focus on fast food restaurant

Abstract

Past research reveals that perceived waiting time was found to influence customer satisfaction and post-purchase behaviour. However, the present study aims to examine the effect of perceived waiting time on customer satisfaction in the context of fast food restaurant in Malaysia. In this study, simple random sampling method was employed and a total of 384 questionnaires were distributed. Consequently, 205 usable responses were successfully collected, representing 53% response rate. The data were analysed using SPSS software including descriptive analysis, reliability and validity test, factor analysis and correlation analysis. The result reveals that perceived waiting time significantly influence customer satisfaction towards fast food restaurants. Theoretically, this study confirmed the effects of perceived waiting time on customer satisfaction in the context of fast food restaurant. Practically, these findings are invaluable to fast food operators to improve the quality of their service delivery.

Full text

Int. J Sup. Chain. Mgt Vol. 7, No. 5, October 2018
259
The Effect of Perceived Waiting Time on
Customer’s Satisfaction: A Focus on Fast Food
Restaurant
Johanudin Lahap1, Rabiatul Iylia Azlan2, Khairil Anuar Bahri3, Noraslinda Mohd Said4,
Dahlan Abdullah5 & Razlan Adli Zain6
Faculty of Hotel & Tourism Management, University Teknologi MARA, Penang Campus,
13500, Malaysia.
1johanudin785@ppinang.uitm.edu.my
2iylia116@gmail.com
3khairil777@ppinang.uitm.edu.my
4noraslinda698@ppinang.uitm.edu.my
5dahla707@ppinang.uitm.edu.my
6razlan75@tganu.uitm.edu.my
Abstract - Past research reveals that perceived waiting
time was found to influence customer satisfaction and
post-purchase behaviour. However, the present study
aims to examine the effect of perceived waiting time on
customer satisfaction in the context of fast food
restaurant in Malaysia. In this study, simple random
sampling method was employed and a total of 384
questionnaires were distributed. Consequently, 205
usable responses were successfully collected,
representing 53% response rate. The data were analysed
using SPSS software including descriptive analysis,
reliability and validity test, factor analysis and
correlation analysis. The result reveals that perceived
waiting time significantly influence customer satisfaction
towards fast food restaurants. Theoretically, this study
confirmed the effects of perceived waiting time on
customer satisfaction in the context of fast food
restaurant. Practically, these findings are invaluable to
fast food operators to improve the quality of their
service delivery.
Keywords: Perceived waiting time, Customer
satisfaction, Fast food restaurant.
1. Introduction
The foodservice industry is one of the most lucrative
industries in Malaysia, the revenue of foodservice
industry is forecasted to increase due to growing
disposable income and acceptance of fast food
restaurant among Malaysian [1]. There are different
types of food service operation such as hotel’s
restaurant, cafeteria, takeaways, canteens and function
rooms. Each foodservice operation carries different
types of service and concept. For example, fine dining
restaurant offer distinguish service, whilst fast food
restaurant in general deal with time and speed for
service [2]. Some fast food restaurant is categorized as
quick service restaurant, but not all of them fast food.
Speed in service, inexpensive food and simple décor
are examples of the quick service restaurants [3]. In
addition, some types of fast food restaurant provide
drive-thru, delivery, and take out services [4].
Minimum preparation time and serving the food is the
main feature of fast food restaurant [5]. According to
Abdullah et. al., [1] fast food restaurant has become a
popular choice of eatery because it served ready to eat
food, and it was acknowledged that time is very
important to busy customers. In addition, they added
that the main factors that attract customer to purchase
fast food due to food safety, speed in delivery and the
taste of the food. Working schedule and limited time
to prepare meals at home is also one of the major
influence in shaping consumer's eating lifestyles
today, and this is the case of Malaysia [6]. Davis and
Heineke [7] assert that in general families opt to rely
on quick service restaurant, because of the
convenience, comfort and time.
Davis and Heineke [7] in their study have found that
customers are a bit intolerable during lunch time
because that duration of time is not sufficient as
compared to dinner time. Besides that, customers in a
restaurant that is disgruntle about waiting time may
complaint about the food even the food is tasty.
Therefore, it can be suggested that, waiting time was
known to impacting customer judgment and buying
decision [8]. This contend that choosing fast food
restaurant could be the best choice for customer to
avoid waiting time. Lee and Lambert [9] opined that
customer have different tolerable waiting time, as
some people may feel that 5 minutes is long and
others will find it ‘just okay”. They added that human
perception on waiting time is subjective, because it is
literally based on personal experience, background
and value. Notwithstanding, it can be concluded that
customer’s perception of waiting times in the fast
food restaurants varies in different situations.
2. Literature Review
Waiting to be served or waiting for numbers to be
called in private or public counter service is part of
everyday routine and it can be distressing. Waiting
time can be defined as unoccupied time, pre-process
waits, uncertain waits, unexplained waits, unfair
waits, solo waits and group waits [9]. Bielen and
Demoulin [10] asserted that waiting time in many
______________________________________________________________
International Journal of Supply Chain Management
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Int. J Sup. Chain. Mgt Vol. 7, No. 5, October 2018
260
circumstances gives problems to service providers and
it can get intense if the demand for a service is high.
The act of waiting is always regarded as a negative
experience, because of its economic and physical
costs, in addition, delay worsen the waiting time,
when customers have high expectation about the
service [11] [12]. Customers in a restaurant who are
unhappy waiting to be seated may complain about the
quality of the food even though the food is delicious
[7]. Waiting lines have been associated to reduce
service evaluation, negative perception of service
quality and reduce satisfaction, having to wait for
some amount of time for a service to be delivered
creates negative implication to a first-time customer
[13]. According to Wu, Lu and Ge [14] consumer’s
evaluation towards the service is a key factor. Besides
that, customers have a different tolerable waiting time
as Lee & Lambert [9] suggested that human
perception of waiting time is subjective. Customers
who are dissatisfied with a service will be less likely
to return in the future [7]. Alsumait [15] proposed that
study on waiting time were found to influence the
profit and sustainability of fast food operation and it is
a detrimental issue for many food service providers.
2.1 Perceived Waiting Time
The duration of waiting time for a service is called
perceived waiting time [16]. According Palawatta
[17], perceived waiting time depends on factors such
as; whether the customer is occupied or not, are they
in the waiting stage, are they anxious or not, do the
wait is certain or not, does the reason for the wait is
explained or not, whether the customer is alone or not,
and finally does the effort of waiting gives them
value. Time is considered as one of the scarce
resources that should be cautiously spent, because
time is money, or time is business, both customer and
provider value time as an important aspect
(perishable) to be productive (input = output) [16].
The ‘perceived duration of the waiting time’ is how
individuals perceive and feel about the time before
and after the service [12].
When customers have to wait for a long time, their
perception about that overall ‘service experience’
might be influenced and the ‘perceive wait’ differs
from one place to another or one individual to another
according to level of service provided [15] [17] [7].
Lee and Lambert [9] study reported that customers
feel that ‘expected reasonable waiting time’ was
longer than ‘perceived waiting time’ and this
impacting customer satisfaction. Luo, Liberatore,
Nydick, Chung and Sloane [18] supported that
contention by asserting that perceived and actual
waiting times depends on different types of waiting
lines in various food service outlets.
2.2 Customer Satisfaction
Customer satisfaction is one of the most important
antecedent towards the success of hospitality and
tourism. According to Dudovskiy [19] satisfaction is
a result from comparing a product or service
perceived performance in relation to his or her
expectations. Customer satisfaction is known to be
the most important element in business, because when
the customer is satisfied they are not only bring profit
to business but they become repeat customer [20]. To
support that argument, Sze (2006) coined that
customers are the source of profit to organization. In
addition, Davis & Heineke [7] stated that customer
loyalty is the manifestation of customer satisfaction,
thus, it will be demonstrated through repeat visitation
and loyalty is a key determinant for service
organization to survive. In other words, customers
who are dissatisfied will be less likely to return in the
future [7]. The degree of satisfaction can be measured
through the number of repeat customer [21].
Customer satisfaction, leads to various effects and it
was known to be one of the indicator of a company’s
profit. If a customer waiting time is longer than
expected, their level of satisfaction was found to
decline [22] [23]. Nonetheless, service provider
should put a priority to reduce customer’s waiting
time [24]. High level of customer satisfaction was
known to create repeat customers [25]. The study on
customer satisfaction, service perception and actual
service delivery is well established by [26] [27] [28]
study.
2.3 Fast food
Nowadays, fast foods restaurant become a popular
place to dine in Malaysia and people incline to buy
fast food because of convenient and time saving.
According to Sumaedi and Yarmen [8] fast food is
characterised as food that is prepared in a short period
of time. Besides that, several choices of food that is
produced in a standardize-line and specialize products
is also called fast food (for example Subway, Sushi
King). There are many types of fast food restaurant
that sells fried chicken, hamburger, fries and pizzas
that can be found in in Malaysia. According to
Quoquab and Abu Dardak [29] fast food restaurant is
the world fastest growing business, because it is
quick, priced reasonably and readily available
alternate to home cooked food. A & W was the first
fast food restaurant established in Malaysia which
begin their operation in Jalan Tunku Abdul Rahman
back in 1961 [30].
3.0 Methodology
The target sample for this study focused on people
who has the experience patronizing the fast food
restaurants in Malaysia. The researcher employed a
survey questionnaire to collect the required data for
the study. The questions used in this study were
adapted from Davis and Heineke [7] and Tsaur and
Lin [31]. Simple random sampling method was
employed and 384 questionnaires were sent. As a
result, 205 responses were successfully collected
which represents 53% response rate. In this study,

Int. J Sup. Chain. Mgt Vol. 7, No. 5, October 2018
261
waiting time was measured as independent variable
and customer satisfaction was examined as dependent
variable, representing part of a more complex research
framework.
3.1 Calculation of sample size
Formula than being used to determine the sample size is (Z-score) ²
x standard deviation x (1-standard deviation) / (margin of error) ²
Sample Size = (Z-score) ² x Std Dev x (1-StdDev) / (margin of
error)
Sample size = (1.96²) x 0.5 x (1- 0.5) / 0.05²
Sample size = (1.96²) x 0.5 x 0.5 / 0.05² Sample size = 3.8416 x
0.25 / 0.0025 Sample size = 0.9604 / 0.0025 Sample size = 384.16
Sample size adjusted with the population of 31 240 187
Sample size adjusted = (Sample Size) / 1 + [(Sample Size – 1) /
population
= 384.16 / 1 + [(384.16-1) / 31 240 187]
=384.16
4. Findings
4.1 Gender
For the analysis, 205 responses were successfully
collected. 173 of them were completed by female
respondents, representing 84.4% of total respondents.
While male respondents represent only 15.6% (32
responses). From the result, it shows that the
percentages of female respondents are dominating the
samples. The distribution of respondents by gender is
presented in table 4.1.
Gender
Total
Female
Male
Count
173
32
205
Percentage
84.4%
15.6%
100%
Table 4.1: Respondents’ gender
4.2 Age
It was found that the highest respondents’ age range is
17 to 20 years old that represent 109 (53.0%) of the
total sample. Respondent from the age 21 years old to
24 years old is the second highest respondent (36.0%).
The third in rank is respondent from 25 to 28 years
old which has 11 respondents (5.0%). The remaining
respondents are a range from 29 to 32 years old, 33
years old to 36 years old and 37 years old to 40 years
old that represent 63.0%, 1.4 % and 1.0%
respectively. Table 4.2 below shows the age range of
the respondents.
Table 4.2: Respondent’s Age
Age Range
Frequency
Percentage (%)
17- 20
109
53.0
21- 24
74
36.0
25- 28
11
5.0
29 - 32
6
3.0
33 - 36
3
1.4
37 - 40
2
1.0
4.3 Race
In this analysis, it was found that the highest
respondents are Malay represent 199 (97%) of the
total sample. Chinese respondents are the second
highest respondent, which is 3(1.46%) followed by
Indian respondents is 2 (0.97%). The reason why
Malays respondents tops the charts is due the higher
acceptance of them patronizing fast food restaurant
and responding to the questionnaire. Table 4.3 depict
the age range of the respondents.
Table 4.3: respondents’ race
Race
Total
Percentage (%)
Malay
199
97.0
Chinese
3
1.46
Indian
2
0.97
others
1
0.57
Total
205
100
4.4 Education level
In this analysis, it was found that college students
recorded the highest number which represent 137
people (66.8%). Graduates represent 15.6% and post
graduate students registers 9.8% respondents.
Secondary school and others represent 1.5% and 6.3%
respectively. Table 4.4 below depicts the education
level of the respondents.
Table 4.4: respondents’ education level
Education level
Total
Percentage (%)
Secondary School
3
1.5
College
137
66.8
Post Graduate
20
9.8
Graduate
32
15.6
Others
13
6.3
Total
205
100.0
4.5 Reliability and Validity Test
Reliability refers to the extent to which a scale
produces consistent result if the measurements are
made repeatedly. The type of reliability analysis used
to analyze reliability in this research is the Cronbach
Alpha Coefficient. Cronbach’s alpha is designed by
Lee Cronbach to measure the internal consistency and
the stability of the research items and expressed as a
number between 0 and 1 [32]. Internal consistency
describes the extent to which all the items in a test
measure the same concept or construct and hence it is
connected to the inter-relatedness of the items within
the test. It should be determined before a test can be
employed for researcher examination purposes to
measure validity. There are different reports about the
acceptable values of alpha, ranging from 0.7 to 0.95.
However, a low value of alpha could be due to a low
number of questions, poor inter-relatedness between
items or heterogeneous construct [32]. Reliability that
less than 0.6 is generally acceptable, but the reliability
that over 0.8 is even better [33]. Table 4.5 below
depicts the result of the reliability test.
Table 4.5: Reliability of measure of the variability
Section
No of Item
Cronbach’s Alpha
B
9
0.736
C
5
0.769

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262
Section B consist of 9 items in this study achieved a
reliability of 0.736. While section C consists of 5
items in this study achieved a reliability of 0.769. So,
it shows that all the items are above 0.6. The results
and the overall variables item is acceptable.
4. 6 Chi-Square Tests
The Chi Square statistic is commonly used for testing
relationship between categorical variable. It is also
known as test for goodness-of-fit and test of
independence. The most important of the chi square
testing is researcher could use the statistical methods
that did not depend on the normal distribution to
interpret the findings [34]. Cross tabulation presents
the distribution of two categorical variables
simultaneously, with the intersections of the
categories of the variables appearing in the cells of the
table. Descriptive analysis about time expectation and
fast food preference is presented below.
Table 4.6: Fast food preferences*time expectations cross tabulation.
Table 4.7: Chi-Square test result of fast food
preferences*time expectations
4.7 Interpretation of Result Analysis
: No relationship between fast food preferences and
time expectation.
1: Some relationship between fast food preferences
and time expectation.
Based on the results, since the p-value (0.000) <0.05,
therefore, null hypothesis is rejected. This research
concludes that there is enough evidence to suggest
that there is a positive correlation between food
preferences and time expectation.
4.8 Mean and Standard Deviation
4.8.1 Waiting Time
Descriptive analysis in Table 4.8 provides information
about waiting time towards customer’s satisfaction in
fast foods restaurants. The analyzed revealed that the
highest mean score on Likert’s Scale of 1 to 5 is “the
customer do not mind waiting as long as they know
why” that scored is 3.77 (SD= 1.005). It shows that,
most of the customers agreed that “they are willing to
wait if they know the reason why”. The second
highest score is statement related to “I do not mind
waiting if I see things happening” scored 3.54 (SD=
0.957). I do not mind waiting as long as I know for
how long, with the mean of 3.48 (SD= 0.942). Then,
the statement of “if I see a queue I go elsewhere” has
mean of 3.40 (SD= 0.958). I do not feel like spending
after long waiting, has a mean of 3.37 (SD=1.024).
The lowest mean score is 3.31 (SD= 0.693) that
represent a statement of “a good meal but a long wait
is a bad experience” has lowest mean score which
is3.10 (SD = 1.109).
Table 4.8: Descriptive analysis about waiting time towards
customer’s satisfaction in fast food restaurants
Statement
N
Mean
S.D
I do not mind waiting if I see things
happening
205
3.54
0.957
I do not mind waiting as long as I
know why
205
3.77
1.005
I do not mind waiting as long as I
know for how long
205
3.48
0.942
a good meal but a long wait is not a
bad experience
205
3.10
1.109
if I see a queue I will stay
205
3.40
0.958
I feel like spending after I have been
waiting.
205
3.18
1.019
How satisfied are you with the
amount of time that you waited in
line?
205
3.39
1.030
4.9 Customer’s Satisfaction
Descriptive analysis in Table 4.9 shows 5 questions
regarding customer satisfaction. The question asked
about the satisfaction in fast food restaurant been
attend by them. The outcomes revealed that the
highest mean score is on statement on “the
consideration that the fast food restaurants always
maintain its service” with mean of 3.61 (SD=0.915).
The second highest mean statement is “I am satisfied
with the service provided by the staff of the fast food
restaurants with a mean of 3.53 (SD=0.808). They
also agree that the staffs are very kind and can solve
the customers’ problem well and rapidly (Mean, 3.49,
SD=0.889). Other than that, they also agree that “the
fast food service has exceeded their highest
expectation (mean 3.38, SD=0.767). The statement of
the fast food restaurant is among the best, has the
lowest score of 3.339 (SD=0.819).

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Table 4.9: Descriptive analysis about customer’s satisfaction in fast
foods restaurants
Statement
N
Mean
S.D
I am satisfied with the service provided by
the staff of the fast food restaurants.
205
3.53
0.808
The fast food service has exceeded my
highest expectation.
205
3.38
0.767
The staffs are very kind and can solve the
customers’ problem well and rapidly.
205
3.49
0.889
The fast food restaurants always maintain
its service.
205
3.61
0.915
The fast food restaurant is among the best.
205
3.39
0.819
4.10 Principles Component Analysis
In this research ‘factor analysis’ was employed, in
order to reduce the number of item [35]. The aim of
Principle component analysis is to find the
significance of each question. The technique relies on
the correlation between the large number of items by
looking at the correlation and the inter-correlation to
group items. The most important of the factor
analysis in this research study is to examine the
structure or relationship between variables. The
analysis is focused on 14 questions that representing
two dimensions which are waiting times (9 questions)
and customer satisfaction (5 questions). It was
essential for multivariate analysis to be conducted in
this research to explore the most significant among
the questions and Principle Component Analysis was
seen as the most suitable multivariate method to be
employed in this analysis. Factor loadings that is
generally considered to be meaningful when it
exceeds 0.30 or 0.40 [36].
4.11 Waiting Time
Based on the data analysis, the Kaiser-Meyer-Olkin
Measure of the sampling Adequacy value of 0.796
exceeded the recommended values of 0.6 by Hair,
Black, Babin and Anderson [37]. Therefore, it is
statistically significant. It shows that there is a high
degree of interrelationship between the questions
within the scope of waiting times. Referring to table
4.10, these 9 components account for 100% of the
explained variance with the first factor explained
41.794% of the variance (Table 4.10).
Table 4.10: Extraction method of principal component
analysis.
Component
Eigenvalues
% of
Variance
Cumulative %
1
3.761
41.794
41.794
2
1.133
12.586
54.380
3
1.002
11.135
65.515
4
0.877
9.748
75.263
5
0.778
8.646
83.909
6
0.539
5.984
89.893
7
0.372
4.135
94.028
8
0.316
3.506
97.534
9
0.222
2.466
100.000
Kaiser-Meyer-Olkin Measure of the sampling Adequacy
= 0.796
Referring to Table 4.11, the highest factor loading is
the respondent stated that they do not feel like
spending after they have been waiting (0.718). The
second highest is the respondent stated that the
amount of time that they satisfied waited in line
(0.682). They do not mind waiting as long as they
know why (0.857). The factor loading of they do not
mind waiting if they see things happening (0.805).
The time they expect to wait upon entering the line in
fast food restaurants (0.710). They do not mind
waiting as long as they know for how long (0.702). A
good meal but a long wait is a bad experience for
them (0.688). They see a queue they will go
elsewhere (0.533). Lastly, the fast food restaurants
they prefer most (0.740).
Table 4.11: The result of Varimax rotated factor matrix for the
waiting times
Waiting Time
Factor Loading
How much time do you expect to wait
upon entering the line?
0.706
I do not mind waiting if I see things
happening
0.805
I do not mind waiting as long as I know
why
0.857
I do not mind waiting as long as I know for
how long
0.765
a good meal but a long wait is not a bad
experience
0.688
if I see a queue I will stay
0.533
I feel like spending after I have been
waiting.
0.718
How satisfied are you with the amount of
time that you waited in line?
0.682
4.12 Customer’s Satisfaction
Based on the result presented in Table 4.12, the
Kaiser-Meyer-Olkin Measure of the sampling
Adequacy value of 0.730 exceeded the recommended
values of 0.6 by Hair, Black, Babin and Anderson
[37]. Therefore, it is statistically significant. It shows
that there is a high degree of interrelationship between
the questions within the scope of customer
satisfaction. Referring to table 4.12, these 5
components account for 100% of the explained
variance with the first factor explained 52.117% of the
variance.
Table 4.12: Extraction method of principal component
analysis of customer’s satisfaction
Eigenvalues
% of Variance
Cumulative %
1
2.606
52.117
52.117
2
1.045
20.900
73.017
3
0.571
11.413
84.430
4
0.396
7.913
92.344
5
0.383
7.656
100.000
Kaiser-Meyer-Olkin Measure of the sampling Adequacy =
0.730
Based on the result of data analysis presented in Table
4.13, the highest factor loading is respondents stated
that the fast food restaurant is among the best to them
(0.891). Besides that, the respondents also reported
that the fast food restaurants always maintain its
service. (0.828), the service provided by the staff of

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264
the fast food restaurants. (0.864) and factor loading
for the staffs are very kind and can solve the
customers’ problem well and rapidly is (0.677).
Lastly, they agree that the fast food service has
exceeded their highest expectation. (0.787).
Table 4.13: The result of varimax rotated factor matrix for the
customer satisfaction
Customer’s Satisfaction
Factor
Loading
I am satisfied with the service provided by the staff
of the fast food restaurants.
0.864
The fast food service has exceeded my highest
expectation.
0.787
The staffs are very kind and can solve the
customers’ problem well and rapidly.
0.677
The fast food restaurants always maintain its
service.
0.828
The fast food restaurant is among the best.
0.891
4.13 Pearson Correlations
Based on the result in Table 4.14, it is shown that the
Pearson correlation between waiting times and
customer satisfaction show the value of r = 0.292 >
value of p =0.05. It is shown that both variables have
weak positive linear relationship.
Table 4.14: Correlation between waiting time and customer’s
satisfaction
Waiting
Times
Customer
Satisfaction
Waiting
Time
Pearson Correlation
1
.292**
Sig. (2-tailed)
.000
N
205
205
Customer
Satisfaction
Pearson Correlation
.292**
1
Sig. (2-tailed)
.000
N
205
205
**. Correlation is significant at the 0.01 level (2-tailed).
5. Delimitation, Limitation and Recommendation
In this study, it was found that time and money is the
main constraints, as this research is conducted in 6
months where, the budget for this study was found to
be scarce. Therefore, in the future, the researchers
may find bigger fund to support this study turn it into
a bigger scale fully funded research. Limitation that
occurs in this study involves the response of
respondent, as the number of questionnaires via email
were send to almost 1000 people, however, the
response is adequate enough to cater the sampling
chosen to this study. It can be proposed that, the fast
food operator in Malaysia should give more
consideration to improve the speed of their service, by
improving employee skills, knowledge and aptitude.
It was also important to food service operator to
improve the existing technology and durability of
their machine, as failure in the line of service means
delay. Once a service is delayed, dissatisfaction
among customer will occur. Delay also occur due to
employee inefficiency, failed to follow procedure,
communication breakdown and external factor
(supplier, repair, maintenance etc.).
6. Discussion and Conclusion
Surprisingly, the present study revealed that,
perceived waiting time has a positive relationship
with customer satisfaction towards fast food
restaurant. Since this finding is not consistent with
most of the previous studies, further investigation is
recommended to find the role of contextual variables
that might influence the relationship. For instance, in
Malaysia, people are willing to que to get good food
from well-known restaurants. The longer the que
which translated to longer waiting time, the more the
intention of curious customers to patronize the
restaurant. Psychologically, this phenomenon is
known as bandwagon effect. Generally, in Malaysia,
customers are willing to sacrifice their time to get
good food. One of the factors contributed to this is the
influence of electronic word-of-mouth [38]. This
research has finally achieved its goal and contributed
to the existing body of knowledge about the role of
perceived waiting time on customer satisfaction in fast
food restaurants. The relationship between waiting
times and customer satisfaction in fast food
restaurants has been the focal point to many
researchers in fast food industry. To sum up, it is
hoped that this research will contribute to the body of
knowledge and make a significance impact to the fast
food operators, specifically in Malaysia. The present
study did not examine the roles of mediator or
moderator variables that might influence the findings.
Therefore, future researchers may integrate their
findings from this study with factors that might have
significant influence to customer buying behavior
towards patronizing or revisiting fast food restaurant.
THIS RESEARCH IS SPONSORED BY THE MINISTRY OF
HIGHER EDUCATION (MOHE) – FUNDAMENTAL
RESEARCH GRANT (FRGS) 600-RMI/FRGS 5/3 (45/2015).
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