Rina Indrayani , Ashrul Adi Muhammad | http://devotion.greenvest.co.id
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VARIABLES THAT AFFECT CUSTOMER SATISFACTION
OF ONLINE FOOD DELIVERY SERVICE USERS
Rina Indrayani
1
, Ashrul Adi Muhammad
2
12
Industrial Engineering, Bandung College of Technology, Indonesia
[email protected]
1
ashrul.nasution@gmail.com
2
KEYWORDS
Model Development,
Online Food Delivery
Service, E-Servqual,
SEM-PLS
ABSTRACT
Improving the quality of service is the most important thing for service
companies, as is the case with PT. Gojek Indonesia as one of the online-based
service provider companies, customer satisfaction is very important to know the
level of satisfaction and quality of service to customers. The development of
electronic service quality in online-based service providers was carried out by
distributing questionnaires to 385 respondents to determine the effect of electronic
service quality on the satisfaction of consumers who use it, as well as finding
proposals for improvements in electronic services based on the right dimensions
of e-servqual. In improving the quality of online-based food delivery services, the
development of an E-Service Quality (E-Servqual) model was carried out which
was built using the Structural Equation Modeling-Partial Least Square (SEM-PLS)
method in the form of 10 dimensions of electronic service quality, namely ease of
use, website design, customization, responsiveness, assurance assurance,
reliability, tangible, emphaty, price, and customer value. The results of the study
found that the dimensions that accommodate the quality of electronic services for
online food delivery services are variables of customer value, reliability,
assurance, emphaty, website design, tangible, responsiveness, and price, but there
is 1 variable that does not have a significant effect on satisfaction consumers i.e.
variable prices. While the results of simultaneous testing, all variables formed in
the final model have a significant effect on consumer satisfaction, so that the
development of the e-servqual model in services online-based food delivery
services are declared optimal.
INTRODUCTION
The food delivery industry is currently very popular in Indonesia. Food is a daily
necessity and everyone has different ways of getting the food they want (Prasetyo et al.,
2021). At this time, one of the ways a person gets the desired food is to make a delivery
purchase of food. Delivery is mostly done by busy people until they don't have time to
prepare food (Aprilia Dwi Putri, 2017).
In an effort to meet the need for food delivery services, it is currently facilitated by
the development of information technology that provides online food delivery services such
as e-commerce (Ilham, 2018). With the existence of services in the form of e-commerce that
can be precisely enjoyed by customers, all services desired by customers can be immediately
followed up. So that a company will be able to provide the best service for customers
(Irmawati, Dewi Irmawati, 2011).
Servicequality is the most important thing for service companies, because service
quality describes the company's ability to meet customer expectations based on customer
satisfaction (Indrayani 2021). Such is the case with PT. Gojek Indonesia as one of the
online-based service provider companies, customer satisfaction is very important to know
the level of satisfaction and quality of service to customers (Adnyana and Suprapti 2018) .
In a data found in several restaurants providing fast food and beverages in the
Bandung city area, the turnover and total orders obtained by some of these restaurants for 7
consecutive days through Gofood orders were lower compared to the turnover and total
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e-ISSN: 2797-6068 and p-ISSN: 2777-0915
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orders obtained through Grabfood orders (food delivery service providers on the Grab
application) (Pradnyaswari & Aksari, 2020). The following is a table of data on the total
orders of W restaurants as fast food providers (Chetan Panse, Sharma, & Dorji, 2019):
Table 1
Restaurant W 7-Day Order Data
Order Online
Gofood
Grabfood
13 orders
16 orders
11 orders
15 orders
12 orders
17 orders
12 orders
16 orders
15 orders
18 orders
18 orders
20 orders
17 orders
21 orderss
The data table above is the total order of restaurant Was a fast food provider
restaurant with a relatively expensive food menu price range at a price range of around
Rp.85,000 to Rp.200,000, - per portion. Data on the turnover of restaurant X as a fast food
drink provider restaurant will be presented in the following table:
Tabel 2
Data omzet 7 hari restoran X
Tanggal
Omzet
Gofood
Grabfood
24/12/19
Rp.7.980.000
Rp.11.004.000
25/12/19
Rp.8.103.000
Rp.12.030.000
26/12/19
Rp.7.242.000
Rp.9.211.000
27/12/19
Rp.9.821.000
Rp.9.872.000
28/12/19
Rp.10.826.000
Rp.12.063.000
29/12/19
Rp.10.253.000
Rp.10.748.000
30/12/19
Rp.10.113.000
Rp.10.537.000
Total
Rp.64.338.000
Rp.75.465.000
The table above is data on the turnover of restaurant X as a fast food drink provider
restaurant with a relatively expensive price range of the beverage menu offered, which is
around Rp.28,000 to Rp.34,000 per cup. In these tables, it can be seen that sales based on the
number of cups of drinks and total food orders in these restaurants are more placed orders
using the service Grabfood is compared to Gofood services, so the turnover obtained by
restaurants has also experienced a considerable difference (Suhartanto, Helmi Ali, Tan,
Sjahroeddin, & Kusdibyo, 2019).
According to (Felicia, 2016) the dimensions of the e-service quality model are seen
from two perspectives, namely the company perspective in the form of ease of use (ease of
use for customers to use the website), website design (website which is well designed and
visually appealing), reliability (consistency of performance and web reliability), system
availability (correct technical function of the website), privacy (security and protection of
[ Variables that Affect Customer Satisfaction of Online Food
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customer information), responsiveness (handling problems and effective returns via the
internet), emphaty (individual care and attention given to customers through electronic
channels) and perspectives from customers in the form of experiences about the company
through previous customers), as well as trust (customer trust by providing fast and
information-rich service) (Suhartanto et al., 2019).
In previous research according to (Berlianto, 2017) that the five dimensions of
electronic service quality, namely ease of use, e-scape, responsiveness, customization and
assurance used did not have a positive effect on satisfaction, while electronic satisfaction
affects electronic trust, then electronic trust has no perception of behavioral loyalty. In a
study conducted by (Setiawan & Septiani, 2018) on customers who use Grab transportation
modes in South Tangerang, it shows that the quality of electronic services partially affects
consumer satisfaction, and trust electronics partially have a significant effect on customer
satisfaction, the quality of electronic services and electronic trust simultaneously have a
significant effect on customer satisfaction (Saad, 2020). Meanwhile, research according to
(Hanifa, Trianto, and Hendrich 2019) shows that price, service quality and customer value
simultaneously affect Gojek's customer satisfaction, then customer price and value partially
affect the Gojek customer satisfaction.
Gofood services on the Gojek application have spread throughout Indonesia. One of
the keys to success that supports customer satisfaction in this company is the existence of a
good quality of electronic service (Oh, 1999). The purpose of this study is to optimally
analyze and develop an e-servqual model on online food delivery services. This study aims to
determine the effect of electronic service quality on the satisfaction of consumers who use it,
as well as find proposals for improvements in electronic services based on the right
dimensions of e-servqual. The limitation used in this study is that data collection carried out
on restaurant customers who use Gofood services is only collected at a few restaurants in the
city of Bandung.
METHOD RESEARCH
In the implementation of this research, several stages were carried out starting from the
beginning of the implementation to the end of the research implementation, the steps of the
research were as follows:
1. Preliminary survey, researchers monitor the latest developments or field facts that occur
in the service system and consumer satisfaction with the electronic services provided.
2. Identification of problems based on the results of the survey, researchers look for the
negative impact of the situation that is occurring directly in the service system.
Researchers identified the service system and consumer satisfaction that was the object of
the study as part of the scope of the course of food delivery services in the service
system and the extent of its effect on consumers.
3. The purpose of the study, from the existing subject matter, is expected that researchers
can analyze and develop an e-servqual model on online food delivery services optimally.
4. Study of literature, to determine and find the right method to apply to the existing
problem. In this study using the SEM-PLS analysis method, because it can provide
absolute results.
5. Determination of samples, based on the methods and studies of the literature that have
been decided, then samples or variables that correspond to the available literature can be
determined.
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6. Preparation of questionnaires, as a tool for collecting data on the object under study in
accordance with a predetermined sample.
7. Data collection, after knowing the subject matter that occurred, the researcher held a
questionnaire to users of the online food delivery service application needed in order to
find solutions to existing problems.
8. Data processing, problem-solving processes or data analysis are carried out in
accordance with the provisions of the service system that occurs, the series of processes
are implied in the sub-Chapter Data Processing and Analysis Methods.
9. Descriptive analysis, describing or describing the data that has been collected as it is
without intending to make generally accepted or generalized conclusions that include an
analysis of the characteristics of respondents consisting of gender, age, occupation,
monthly income and frequency of use of services.
10. Instrument tests, carried out to find out whether the composed instruments are really a
good result or not.
a. Data validity testing, used to find out whether the data that has been collected is valid
or not. If it is invalid, then some invalid data needs to be selected.
b. Data reliability testing, used to find out whether the data that has been collected is
reliable or not. If not, then some unreliable data needs to be selected.
11. Sem-PLS processing with smartpls program, used to create Structural Equation Modeling
Partial Least Square using SmartPLS software.
12. Evaluation of the Outer Model, used to determine the validity and reliability of indicators
that measure latent constructs.
13. Evaluation of the Inner Model, carried out to test the relationship between the latent
constructs.
14. Goodness of Fit, after the results are obtained, a comparison is made. If the results of
goodness of fit are appropriate, then this study is worth moving to the next stage. And if
not, then a modification of the model is carried out.
15. Test the hypothesis, in order to find out whether the hypothesis proposed in this study is
appropriate or not.
16. Analysis and Discussion, after conducting data analysis in the context of solving
problems, the results of data analysis are obtained and further discussion of the results of
the data analysis is carried out to gain an understanding of the results of data analysis.
17. Conclusions and Suggestions, after the understanding of the results of data analysis is
reached, then the researcher makes a final conclusion or decision making related to the
acceptance of the analysis results and positive research results that can be used as advice
by researchers as material for consideration by companies providing online food delivery
services to make policies.
RESULT AND DISCUSSION
The results of the data collection will be tested for validity and reliability tests. Validity
testing is used to find out all feasible statements and can be used for further analysis.
Reliability testing is used to measure the extent to which questionnaires can be used, trusted,
and relied upon in research. The validity test in this study is perason's correlation product
moment which is analyzed using the SPSS program.
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Table 3 Validity test results
Variable
Question Items
r count
r table
Status
Ease of use
(X
1
)
X
1.1
0.394**
0.0999
Valid
X
1.2
0.740**
0.0999
Valid
X
1.3
0.799**
0.0999
Valid
X
1.4
0.835**
0.0999
Valid
Website
Design (X
2
)
X
2.1
0,923**
0,0999
Valid
X
2.2
0,933**
0,0999
Valid
X
2.3
0,892**
0,0999
Valid
Custom
(X
3
)
X
3.1
0,787**
0,0999
Valid
X
3.2
0,857**
0,0999
Valid
X
3.3
0,778**
0,0999
Valid
Responsive
(X
4
)
X
4.1
0,867**
0,0999
Valid
X
4.2
0,920**
0,0999
Valid
X
4.3
0,890**
0,0999
Valid
Assurance
(X
5
)
X
5.1
0,799**
0,0999
Valid
X
5.2
0,829**
0,0999
Valid
X
5.3
0,721**
0,0999
Valid
X
5.4
0,830**
0,0999
Valid
Tangible
(X
6
)
X
6.1
0,840**
0,0999
Valid
X
6.2
0,833**
0,0999
Valid
X
6.3
0,781**
0,0999
Valid
Reliability
(X
7
)
X
7.1
0,855**
0,0999
Valid
X
7.2
0,885**
0,0999
Valid
X
7.3
0,868**
0,0999
Valid
Emphaty
(X
8
)
X
8.1
0,778**
0,0999
Valid
X
8.2
0,869**
0,0999
Valid
X
8.3
0,757**
0,0999
Valid
Price
(X
9
)
X
9.1
0,812**
0,0999
Valid
X
9.2
0,644**
0,0999
Valid
X
9.3
0,583**
0,0999
Valid
X
9.4
0,787**
0,0999
Valid
Customer Value
(X
10
)
X
10.1
0,675**
0,0999
Valid
X
10.2
0,817**
0,0999
Valid
X
10.3
0,760**
0,0999
Valid
X
10.4
0,718**
0,0999
Valid
Consumer Satisfaction
(Y)
Y
1
0,794**
0,0999
Valid
Y
2
0,750**
0,0999
Valid
Y
3
0,815**
0,0999
Valid
Referring to the results of the resulting validity test is produced that the entire
instrument on the entire variables X and Y consisting of several statement items produces a
calculated value of r > r of the table. So, it can be concluded that all instruments in this study
are declared valid. Reliability test in this study using Cronbach's Alpha technique. This test
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can be said to be reliable if Cronbach's Alpha is worth more than 0.60. The following is a
table of reliability test results obtained:
Tabel 4. Reliability Test Results
Variable
Cronbach’s
Alpha
Minimum
Value
Status
Ease of use
0,660
0,60
Reliable
Website Design
0,896
0,60
Reliable
Customization
0,734
0,60
Reliable
Responsiveness
0,871
0,60
Reliable
Assurance
0,802
0,60
Reliable
Tangible
0,733
0,60
Reliable
Reliability
0,838
0,60
Reliable
Emphaty
0,701
0,60
Reliable
Price
0,626
0,60
Reliable
Customer Value
0,707
0,60
Reliable
Customer Satisfaction
0,687
0,60
Reliable
It can be seen in the table that the value of Cronbach's Alpha of all variables has a
value greater than 0.60, so it can be concluded that all variable instruments in the
questionnaire used in this study were declared reliable as measuring instruments. Overall, the
SEM-PLS model formed in the structural and measurement model in this study is as follows:
Figure 2. Early SEM-PLS models
The evaluation of the measurement model consists of three stages of testing, namely
Convergent Validity, Discriminant Validity, and Composite Reliability. Here are the results
of the Goodness of Fit measurement model test:
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1. Convergent Validity Test
Validity testing for reflective indicators can be carried out using the correlation
between the indicator's score and its constructive score. Measurements with reflective
indicators show that there is a change in an indicator in a construct if other indicators in
the same construct change. The following is the output of the calculation results using
SmartPLS software:
Figure 3. Initial SEM-PLS model loading factor output
Based on the output in the table and figure, it can be seen that the value of the
outer loading or loading factor indicator against the latent variable does not all have a
value greater than 0.7. So that indicators whose value is less than 0.7 need to be
eliminated in order to meet convergent validity.
Figure 4. Final SEM-PLS model loading factor output
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In the output of the table and figure, it can be seen that the outer loading value or
loading factor of the latent variable with the indicator entirely having a value greater than
0.7. So that the indicators used in this study have met the requirements of convergent
validity.
2. Discriminant Validity or Discriminant Validity Test
In reflective indicators, it is necessary to test the validity of discriminants, where
an indicator is said to meet the validity of discriminants if the cross-loading value of the
indicator against the variable is greater than other variables, and can also be seen based on
the value of the AVE (Average Variance Extracted) which must have a value of > 0.5.
Table 5. Cross loading and AVE output
Score
AVE
X2.1
0,820
0,750
X2.2
0,784
X2.3
0,981
X4.1
0,848
0,758
X4.2
0,878
X4.3
0,887
X5.1
0,780
0,687
X5.2
0,823
X5.4
0,880
X6.1
0,888
0,831
X6.2
0,935
X7.1
0,859
0,726
X7.2
0,860
X7.3
0,838
X8.1
0,801
0,626
X8.2
0,703
X8.3
0,861
X9.1
0,742
0,755
X9.4
0,980
X10.1
0,770
0,644
X10.2
0,819
X10.3
0,816
Y1
0,802
0,581
Y2
0,766
Y3
0,718
It can be seen that the cross-loading value of all indicators that make up each
variable in this study has met the validity of the discriminant. And it is also proven in the
AVE value obtained in each variable, where the values are greater than 0.5. So, it can
be concluded that the indicators and variables used in this study have met the
requirements for discriminant validity.
3. Composite Reliability or Composite Reliability Test
Composite reliability is expressed as good if it has a > value of 0.7, and also has a
cronbach's alpha value > 0.7.
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Table 6. Latent variable reliability test results
Variabel
Cronbach's
Alpha
Composite
Reliability
Status
Website Design (X2)
0,883
0,899
Reliable
Responsiveness (X4)
0,841
0,904
Reliable
Assurance (X5)
0,783
0,868
Reliable
Tangible (X6)
0,800
0,908
Reliable
Reliability (X7)
0,812
0,888
Reliable
Emphaty (X8)
0,711
0,833
Reliable
Price (X9)
0,744
0,858
Reliable
Customer Value (X10)
0,724
0,844
Reliable
Customer Satisfaction (Y)
0,702
0,806
Reliable
All latent variables measured in this study have values of cronbach's alpha and
composite reliability greater than 0.7. So that all the latent variables are declared reliable.
Tests on inner models or structural models are carried out to test the relationship between
latent constructs. There are several stages of testing for structural models, namely
measuring the value of the R-Square (R2) and Q-square (Q2) test results, here are the
results of the Goodness of Fit structural model test:
1. R-Square Testing (R2)
The R-square value on the endogenous construct is used to measure how much
influence a particular independent latent variable has on the dependent latent variable.
From the processed R2 data using SmartPLS software, it was obtained:
Table 7. The calculation output of the value of R2
R Square
R Square Adjusted
Kepuasan Konsumen
0,762
0,757
The R-square value of 0.67 is included in the strong category, so the Rvalue 2
obtained in this study is also included in the strong category with an R value of 2 greater
than 0.67, which is 0.762 or 76.2%, which means that the ability of independent
variables can explain almost all the information needed to predict the variation in the
consumer satisfaction variable of 76.2% while the other 23.8% is explained by other
variables not discussed in this study.
2. Q-Square Testing (Q2)
This test is carried out to determine the predictability with the Blinfolding
procedure. Here's the Q2 test output using SmartPLS software:
Table 8. Output calculation of the value of Q2
SSO
SSE
Q² (=1-SSE/SSO)
Satisfaction User
1.155,000
679,379
0,412
If Q- square value obtained 0.35 then it is included in the large category. The Q2
value obtained in this study was 0.412, the value is certainly greater than 0.35.
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This shows that all independent variables have a good level of prediction of
consumer satisfaction. The final SEM model was obtained after modifications based on
the validity, reliability, and goodness of fit of the model processed in the study, which can
be seen in the following figure:
Figure 5. Final SEM-PLS model
After the SEM model is declared fit, then hypothesis testing can be carried out.
The hypothesis test aims to determine whether the modified e-servqual model has a
significant effect between independent variables and dependent variables partially or
simultaneously.
3. T Test (Partial)
The T test is used to partially test the effect of independent variables on dependent
variables. With the value of df = 383, the table T-value of 1.966 is obtained, then the path
coefficient score indicated by the T-count value must be greater than 1.966. Partial
hypothesis testing with the SEM-PLS method is carried out with a bootstrapping
procedure with the help of SmartPLS software, and the following are the results of the
calculation of the hypothesis test of research data, where a significant value can be seen
of a T-count value greater than 1,966.
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Table 9. Partial hypothesis testing
Influence
Inner
Weight
T-table
T-count
Information
H1.2
0,177
1,966
4,873
Significant
H1.4
0,245
1,966
2,878
Significant
H1.5
0,258
1,966
5,358
Significant
H1.6
0,132
1,966
2,969
Significant
H1.7
0,463
1,966
6,472
Significant
H1.8
0,262
1,966
5,186
Significant
H1.9
-0,033
1,966
0,815
Not Signifikan
H1.10
0,520
1,966
9,693
Significant
4. F Test (Simultaneous)
The F test is used to determine whether the modeling developed has a
simultaneous influence of independent variables on dependent variables or not. To obtain
the value of F-Calculate or F-statistics requires the help of SPSS software with the
ANOVA procedure. Here are the results of testing the H1.1s hypothesis:
Determining the degree of significance by:
α = 0,05 , df1 = 9 – 1 = 8 , df2 = 385 – 9 = 376
F-table = 1,963
Table 10. Simultaneous hypothesis testing
ANOVAa
Model
Sum of Squares
df
Mean
Square
F
Sig.
1 Regression
539,929
8
67,491
126,766
,000b
Residual
200,717
377
,532
Total
740,645
385
a. Dependent Variable: Y
b. Predictors: (Constant), X10, X2, X8, X9, X5, X6, X7, X4
The table shows the results of the F-count test value (126,766) > the F-table
(1,963). Based on the comparison of these values, the variables of website design,
responsiveness, assurance, tangible, reliability, emphaty, price, and customer value
simultaneously accommodate the quality of electronic services in increasing satisfactionn
consumers.
CONCLUSION
Based on the research that has been carried out, it can be concluded that the e-
servqual model produced after the analysis process using the SEM-PLS analysis technique
obtained dimensions that affect and accommodate consumer satisfaction, namely variables of
customer value, reliability, assurance, emphaty, website design, tangible, responsiveness, and
price. With variables that do not have a significant effect, namely the price variable, and
the variable that has the most significant effect on consumer satisfaction, namely the
customer value variable, this happens because the customer value is the tradeoff between the
customer's perception of the quality received from the costs that have been incurred by the
customer.
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