JRSSEM 2022, Vol. 02, No. 4, 445 - 465
E-ISSN: 2807 - 6311, P-ISSN: 2807 - 6494
EFFECT OF SME’S E-READINESS AND ONLINE FOOD
DELIVERY APPS ADOPTION TOWARD BUSINESS
PERFORMANCE
Reyna Nadhya Ulhaq
Management Science Graduate School Bogor Agricultural University Bogor, Indonesia
*
e-mail: reynanadhya@gmail.com
*Correspondence: reynanadhya@gmail.com
Submitted
: 07
th
November 2022
Revised
: 17
th
November 2022
Accepted
: 23
th
November 2022
Abstract: Malaysia and Indonesia, in this case, have several similarities including the non-optimal
performance of SMEs and the potential of online food delivery to improve SME performance. Al-
Bakrie and Katsioloudes (2015) stated that one of the most important factors in influencing the
impact of e-commerce-adoption was readiness. The purpose of this study was to understand and
compare e-readiness factors that influence online food delivery apps adoption and to understand
the effects of online food delivery apps adoption on SME's performance between Malaysia and
Indonesia. The number of samples used in this study amounted to 70 respondents. Research using
SEM PLS as a data processing tool. The findings showed that the factors that influence the level of
e-commerce-adoption in Indonesia are commitment, market forces, supporting industries e-
readiness, and online food delivery apps adoption while in Malaysia only market forces has a
significant effect on online food delivery apps adoption. In both countries, online food delivery
apps adoption is positively and significantly influential to SME’s performance with a relatively equal
significance value.
Keywords: e-adoption, e-readiness, food retailing, online food delivery, SME
Reyna Nadhya Ulhaq | 446
INTRODUCTION
Micro Small and Medium Enterprise
(SME) has played an essential role in the
ASEAN economy, but the performance has
not been optimum (Iqbal & Rahman, 2015)
stated that SMEs played an essential role in
facilitating ASEAN growth because SMEs
contributed to economic growth, total
employment, export, and GDP. The role of
SMEs was not only for ASEAN but also for
individual countries such as Indonesia and
Malaysia. However, in recent years the
growth of SME contributions has been
fluctuating, as shown in Figure 1. The
growth rate of SME’s contribution to GDP
did not show a significant growth rate,
indicating that SME’s performance has not
optimum.
Figure 1. Growth of Contribution SME to GDP in Malaysia and Indonesia
Source: (Menengah, 2018; NESDC, 2019)
E-commerce is an opportunity for
SMEs to improve their performance. The
development of internet technology has
changed people's behavior, especially
shopping behavior. People choose to shop
through e-commerce with convenience
and flexibility (Eroglu, 2014). Besides
finding the desired item more quickly, e-
commerce also made consumers find
information and easily compare various
products and prices (Butler & Peppard,
1998). Shopping for goods or services via
the internet (e-commerce) has been
accepted on the broader community and
has become a popular way (Bourlakis et al.,
2008). (Thomsen R., 2019) stated that
21.55% of the world's population began to
purchase through e-commerce and is
expected to grow in line with the growth of
world internet users. Not only globally, but
the high number of internet users was also
seen in ASEAN countries, as shown by Table
1. Indonesia, the Philippines, Vietnam,
Thailand, and Malaysia were the five
countries with the most significant number
of internet users in ASEAN. The level of
internet penetration in five countries
reached more than 60% of the country's
population, which was above the world
internet penetration's level. Whereas, in
that five countries, the enormous
penetration of e-commerce consumers is in
Indonesia, Thailand, and Malaysia. The
large penetration's number on e-
0
5
10
15
2014 2015 2016 2017 2018
The Growth of GDP
contribution (%)
Year
Malaysia Indonesia
447 | Effect of Sme’s E-Readiness and Online Food Delivery Apps Adoption Toward Business
Performance
commerce's market indicated the sizeable
potential opportunities that SMEs can
access to increase their performance.
Several published studies have investigated
how e-commerce has affected SME's
performance by increased sales (Abebe,
2014; Thomsen R., 2019), improved
international sales (Eduardsen, 2018), and
improved promotion of the brand and
corporate image (Jahanshahi et al., 2013).
(Turban et al., 2007) stated that e-
commerce allowed businesses to increase
their competitiveness, reduce time and
distance barriers, save costs, open new
markets and help small businesses
compete globally.
Table 1. Internet user in ASEAN country 2019
Country
Penetration
% Population
Penetration user in
e-commerce market
Indonesia
65 %
90 %
Philippines
64 %
75 %
Vietnam
61 %
78 %
Thailand
69 %
85 %
Malaysia
83 %
80 %
Source: (Datareportal, 2019)
One of the fast-growing e-commerce
was ride-hailing. Ride-hailing is a
transportation service provider using a
platform or apps to connect drivers with
consumers and is supported by GPS
systems (International Transportation
Forum 2018). The total gross merchandise
value of ride-hailing in ASEAN countries
has been growing and projected to
snowball until 2025, as shown in Figure 2.
Figure 2. The growth of ride-hailing Gross Merchandise Value
Source: (Google and Temasek, 2019)
Data displayed by (Google and
Temasek, 2019) divided ride-hailing
services into two, namely online
transportation and online food delivery.
Reyna Nadhya Ulhaq | 448
The data from (Google and Temasek, 2019)
also stated that the growth of online food
delivery services had increased significanty,
as shown in Figure 3.
Figure 3. The growth of Online tranpors and Online food delivery Gross Merchandise Value
Source: (Google and Temasek, 2019)
Online food delivery has provided the
customer with many benefits. Several
benefits of adopting online food delivery
were many promotions, many drivers who
help deliver the food, and supported
features that can provide information
about menus, prices, and business location
(Suryadi & Ilyas, 2018). Moreover,
customers can also read testimonials that it
is essential to influence customer purchase
behavior (Nasiruddin & Hashim, 2015).
Lembaga Demografi Universitas Indonesia
(2018) stated that the adoption of online
food delivery services by SMEs can increase
the transaction volume of the food retailing
sector. Especially food and beverage have a
unique role in advancing the economy
because it is related to human life (Pfitzer
& Krishnaswamy, 2007). The demand for
this sector will also continue to increase
along with the increasing number of
people.
1. Problem Statement
Malaysia and Indonesia, in this case,
have a similar problem there was SME’s
performance has not optimal. Malaysia and
Indonesia also have similar opportunities to
solve that problem. The potential of e-
commerce market share and gross
merchandise value of online food delivery
was projected to snowball. Optimization of
online food delivery apps adoption by food
retailing SMEs in Indonesia and Malaysia is
expected can increase SME’s performance.
(Al-Bakri & Katsioloudes, 2015) stated that
one of the most critical factors influencing
the impact of e-commerce-adoption was e-
readiness. In order to increase SME’s
performance through online food delivery
adoption as expected, further studies are
needed to examine the effect of e-
readiness to e-adoption and e-adoption on
business performance.
However, it was still difficult to find
0
5
10
15
20
25
2015 2019 2025
GMV ($B)
Online Transport Online Food Delivery
449 | Effect of Sme’s E-Readiness and Online Food Delivery Apps Adoption Toward Business
Performance
literature specifically discussing e-readiness
in online food delivery apps adoption from
the SME's perspective. (Marunung DY,
2019) examined the technology readiness
of online transportation services from the
driver's perspective. (Munandar & Munthe,
2019) examined technology readiness in
online transportation from the consumer's
perspective. Related to the limited e-
readiness theory on adopting online food
delivery apps from the MSMEs' view, the e-
readiness theory from (Molla & Licker,
2005), namely the Perceived e-readiness
Model (PERM) was chosen to be used in
this study. The consideration of choosing
the PERM theory in this study is because
the PERM theory is designed according to
the conditions of MSMEs in developing
countries. In addition, the theory also has
complex sub-variables. Therefore, it is
necessary to discuss more deeply e
readiness from the perspective of MSMEs
and the use of PERM theory in adopting e-
commerce type online food-delivery apps.
A comparative study was conducted to
understand the causal processes involved
in the case (Pickvance, 2005).
The problems in this study are:
1. How does the effect of e-readiness on
online food delivery apps adoption?
2. How does online food delivery apps
adoption affect SME’s performance?
2. Research Objectives
Based on the problem that has been
described, the objectives of this study are:
1. Analyze the effect of e-readiness on
online food delivery apps adoption
2. Analyze the effect of e-adoption on SME
performance
3. Benefit of Research
Hopefully, the results of this study can
be helpful 1) For online food delivery
service providers to see what aspects of e-
readiness affect SMEs' online food delivery
apps adoption, so companies can use them
as a basis for reaching more partners. 2) For
SMEs, this research will be used as a
reference to prepare the critical e-readiness
aspect to get higher performance. 3) For
academics, this research can be a new
reference about the hypothesis, adoption
PERM theory in online food delivery apps
adoption's case, and e readiness from
SME's perspective.
4. Scope of The Research
This study limited to 70 samples of
SMEs in the food retailer sector in
Indonesia and Malaysia. The scope of the
study is to investigate the influence of e-
readiness on online food delivery apps
adoption and the effect of e-commerce-
adoption on SME’s performance.
MATERIALS AND METHODS
Type and Source of Data
The data used in this study are
quantitative and qualitative. The data
sources in this study are primary data and
secondary data. Primary data is carried out
using a questionnaire, while secondary
data is taken from references such as the
internet, annual reports, books, and related
journals that support this research.
Sampling Methode
The population in this study is food
Reyna Nadhya Ulhaq | 450
retailing SMEs in Indonesia and Malaysia.
Sampling in this study used a
nonprobability sampling method, namely
nonrandom sampling, where each member
does not have the same opportunity to be
selected as a sample. Researchers used a
purposive sampling technique, namely
filtering samples with specific criteria. The
samples were taken in this study were 70
samples from the two countries, 35 SME
respondents in Indonesia and 35 SME
respondents in Malaysia. The number of
respondents met the requirement for
samples to be processed using SEM-PLS.
The samples used in SEM-PLS ranged from
30 - 100 (Hussein, 2015). In PLS-SEM,
analysis is processed using bootstrap or
random multiplication. Hence the
assumption of normality will not be a
problem for PLS.
Data Processing and Analyzing Methode
Structural Equation Modelling (SEM)
was one of the statistical analysis
techniques, which combines two different
statistical methods, namely factor analysis
and simultaneous equation models
(Ghozali, 2014). The variables seen in SEM
are latent variables and manifest variables.
The latent variables consist of exogenous
and endogenous variables. Exogenous
constructs are independent variables, while
endogenous constructs are dependent
variables. The manifest variable or indicator
variable is manifested in the form of a six
Likert- scale question. This study used
quantitative data analysis, a measurement
used in a study that can be calculated with
specific units or expressed by numbers. This
analysis includes data processing,
organizing data, and finding results.
Partial Least Squares (PLS) analysis was
a multivariate statistical technique that
compares multiple dependent variables
and multiple independent variables
(Abdillah W, 2015). The purpose of PLS is to
predict the effect of variable X on Y and
explain the theoretical relationship
between the two variables. This analysis can
simultaneously test measurement models
while testing structural models. The
measurement model is used to test the
validity and reliability, while the structural
model is used to test causality (hypothesis
testing).
The research model of this study aims
to examine the effect of e-readiness (x) on
online food delivery apps adoption (y1) and
to examine the effect of online food
delivery apps adoption (y1) on SMEs
performance (y2).
The first test identified the effect of e-
readiness (x) on online food delivery apps
adoption (y1). E-readiness theory used in
this model refers to Molla and Licker
Theory, dividing readiness into nine
variables. E-readiness (x) in this model
becomes an exogenous variable, while the
online food delivery apps adoption
becomes an endogenous variable. The
second test, testing the effect of online
food delivery apps adoption (y1) on SME's
performance (y2). Online food delivery
apps adoption becomes an exogenous
variable, while the SMEs performance (y2)
is an endogenous variable.
.
451 | Effect of Sme’s E-Readiness and Online Food Delivery Apps Adoption Toward Business
Performance
Figure 4. Research Model
RESULTS AND DISCUSSION
1. Result
This study processed the data using
descriptive analysis and SEM PLS.
Descriptive analysis was used to explain the
characteristics of respondents in Indonesia
and Malaysia. The results of the descriptive
analysis are expected to provide
supporting insights related to this research.
Data processing using SEM PLS was used to
answer the objectives of this study.
2. Respondent Characteristics
This research was conducted in two
countries, namely Indonesia and Malaysia.
The object of this research was a food
retailing SME. The total number of samples
from the two countries was 70 SMEs,
consisting of 35 Indonesian SMEs and 35
Malaysian SMEs. The characteristics of the
research respondents are explained in
Table 5.
Table 2. Respondent Characteristics
Indonesia
Malaysia
Age
20-30
83%
54%
Reyna Nadhya Ulhaq | 452
31-40
09%
29%
41-50
06%
17%
51-60
03%
Gender
Female
43%
40%
Male
57%
60%
length be a
businessman
<1
31%
17%
1 to 10
63%
57%
> 10
06%
26%
Based on Table 5 there are slight
differences between Indonesian and
Malaysian respondents. Compared with
Malaysia, Indonesia has more respondents
aged 20-30 years old. Otherwise, Malaysia
has more respondents aged 30 years old
and over. Male respondents dominated
both Indonesian and Malaysian
respondents. Most Indonesian and
Malaysian respondents have business
experience from one until ten years.
Indonesian respondent excels in business
experiences for less than one year, while
Malaysia in business experience for more
than ten years.
Table 6 shows the characteristics of
SMEs in this study. The number of short-
lived SMEs in Indonesia is higher than in
Malaysia, the longer age in Malaysia is
higher than in Indonesia. Meanwhile, if
viewed from the average sales, the number
of buyers and turnover, SME in Malaysia is
higher than in Indonesia.
Table 3. SME Characteristics
Indonesia
Malaysia
length of business
0 - 1 year
31%
14%
1- 4 year
49%
29%
4-8 year
11%
11%
more than 8
9%
46%
Average of sales
0 – 200 pcs
91%
49%
201– 400 pcs
3%
31%
More than 400 pcs
6%
20%
Average of buyers
0-100 people
89%
23%
100-200 people
9%
29%
200-300 people
-
26%
300 – 400 people
-
6%
More than 400
3 %
17%
Average of
omzet
0 - $ 1.514,23
83%
20%
$ 1.514,23 - $ 3.028,614
12%
9%
$ 3028,614 -$ 4.542,704
3%
23%
$ 4.542,704 - $6.056,93
6%
453 | Effect of Sme’s E-Readiness and Online Food Delivery Apps Adoption Toward Business
Performance
More than $6.056,93
3%
43%
Using a e
commerce
Yes
77%
60%
No
23%
40%
3. Research Indicators
The same indicators or questions
are given to Indonesia and Malaysia.
Indicators are variables used to explain or
measure a latent variable. The magnitude
of the correlation between the indicator
and its latent construct is called the loading
factor. Indicators with a high loading factor
have a higher contribution to explain the
latent variables. On the other hand,
indicators with low loading factors have a
weak contribution to explaining the latent
variables. In most references, a loading
factor value of 0.50 or more is considered
to have strong enough validation to explain
latent variables (Hair, 1998); (Ghozali,
2014).
Figure 5. Final Indonesia’s research model
Reyna Nadhya Ulhaq | 454
Figure 6. Final Malaysia’s research model
In the case of the Malaysian model,
nine indicators were eliminated. The
indicators of awareness variable (x1) have
been eliminated, namely x1.1, x1.2, x1.3,
x1.4, x1.5, and x1.7. Technological resource
variable (x3) has been eliminated on
indicators x3.1, x3.2. The business resource
variable (x4) has been eliminated, namely
the indicators x4.4 and x4.5. The indicators
x5.1 and x5.5 has been eliminated from The
Commitment variable (x5). The indicator
x7.2 has been eliminated from the
Government e-readiness variable (x7).
Supporting industries (x9) have been
eliminated indicators on the x9.3 indicator.
The elimination of indicators produces the
final model, as shown in Figure 8 and Figure
9. So, the indicators used in this study have
fulfilled the convergent validity
requirements.
a. Discriminant Validity
Discriminant validity is an analysis to
see whether indicators can reflect latent
variables or not. The AVE rate value of the
latent variable set can be used to analyze
discriminant validity. The minimum
standard AVE rate should be higher than
0.5. In the final model of Indonesia and
Malaysia, all AVE rate values for each latent
indicator were > 0.5, meaning that all
indicators can reflect latent variables. AVE
root values were higher than any
correlation between variables so that the
comparison criteria for AVE root values with
correlation values between latent variables
have also been fulfilled.
455 | Effect of Sme’s E-Readiness and Online Food Delivery Apps Adoption Toward Business
Performance
Table 4. AVE and AVE root Value
Variable
Indonesia
Malaysia
AVE
Squar
e root
AVE
Discrimina
nt Validity
AVE
Squa
re
root
AVE
Discrimina
nt Validity
Awareness
1,000
1,000
valid
1,00
0
1,000
valid
Human Resources
0,833
0,913
valid
0,61
0
0,781
valid
Business Resources
0,835
0,914
valid
1,00
0
1,000
valid
Technological
Resources
0,536
0,732
valid
0,69
5
0,834
valid
Commitment
0,644
0,802
valid
0,53
8
0,733
valid
Governance
0,555
0,745
valid
0,52
3
0,723
valid
Market Forces
1,000
1,000
valid
1,00
0
1,000
valid
Goverment
0,567
0,753
valid
0,65
8
0,811
valid
Supporting
Industries
0,669
0,818
valid
0,78
3
0,885
valid
Online Food
Delivery Apps
Adoption
0,953
0,976
valid
0,92
0
0,959
valid
SME’s Performance
0,753
0,868
valid
0,84
3
0,918
valid
b. Composite Realibility
Constructions are declared reliable
if the composite reliability value of each
latent variable is above 0.60. Table 8
showed that all the composite reliability
values were above 0.6, which means that
the construction in this study has fulfilled
the reliability requirements, as shown in
Table 8.
Table 5. Composit Realibility Value
Variable
Indonesia
Malaysia
Compos
it
Realibilit
y
Compos
it
Realibilit
y
Reyna Nadhya Ulhaq | 456
Realibilit
y
Realibilit
y
Awareness
1,000
realiabel
1,000
realiabel
Human resources
0,952
realiabel
0,610
realiabel
Business resources
0,938
realiabel
1,000
realiabel
Technological resources
0,851
realiabel
0,871
realiabel
Commitment
0,900
realiabel
0,822
realiabel
Governance
0,880
realiabel
0,868
realiabel
Market forces
1,000
realiabel
1,000
realiabel
Goverment
0,863
realiabel
0,882
realiabel
Supporting industries
0,858
realiabel
0,878
realiabel
Online food delivery apps adoption
0,992
realiabel
0,986
realiabel
Sme’s performance
0,901
realiabel
0,955
realiabel
Discussion
From the results of hypothesis testing
and descriptive analysis, there awere
several similarities and differences between
food retailing SMEs in Indonesia and
Malaysia as shown in Table 10. The
following was a discussion about the
comparison of the results of descriptive
analysis and the hypothesis testing.
Regarding the age of business in both
countries, Indonesia has many SMEs with
short-lived and few MSMEs with long-lived.
That means that many new entrants enter
the food retailing industry, but few survive
over time. Meanwhile, in Malaysia, there are
more long-lived SMEs than short-lived
SMEs. That means few new entrants into
the food retailing industry, but they can
survive last longer. Indonesia and Malaysia
both have food business licenses. However,
the application of food business licenses in
Malaysia is more stringent than in
Indonesia. The licensing is one of the
barriers for food retailing SMEs to enter and
leave the food retailing industry. Indonesia
has lower barriers than Malaysia, so SMEs
can quickly enter the food retailing
industry.
Table 6. Resuts Comparation
Indicators
Comparation
Indonesia
Malaysia
Age
Dominated by young people
and a few older ones
The number of young
people is almost
proportional to the older
age
Pbusiness experience
Dominated by 1-10 years of
business experience, most of
the rest are <1 year.
Dominated by 1-10 years
of business experience, and
most of the rest more than
10 years.
457 | Effect of Sme’s E-Readiness and Online Food Delivery Apps Adoption Toward Business
Performance
Lenght of business
Short business life
dominates. Only a few are
older
Shorter business life is less
than extended business life
Average of sales,
buyers and omzet
The majority of businesses
have lower sales, buyers and
turnover
The number of sales,
number of purchases and
turnover varies, but tends
to be higher.
The effect of POER
variable on Online
food delivery Apps
adoption
Has a significant effect on
the commitment variable
Has no significant effect
The effect of PEER
variable on Online
food delivery Apps
adoption
Has a significant effect on
market forces and
supporting
industriesvariable
Has a significant effect on
the market forces variable
The effect of Online
food delivery apps
adoption on SME
performance
Has a significant effect
Has a significant effect
One of the impacts of the above
conditions is that business competition in
Indonesia is higher than Malaysia. The level
of competition in Malaysia was lower than
in Indonesia, which makes Malaysian SMEs
have a higher average sales, number of
buyers, and turnover than in Indonesia.
SMEs in Malaysia tend to have longer
lives and higher incomes than Indonesian
businesses. That illustrates that SMEs in
Malaysia were more promising and
sustainable. However, high incomes and
business sustainability make some SMEs in
Malaysia satisfied with the current income
and do not apply an online food delivery
app to their business goal. That contradicts
(Yusgiantoro et al., 2020) research, which
states that income and length of business
can support e-commerce adoption. She
stated that the higher income and the
longer of business create the higher ability
of business owners to develop their
business with e-commerce.
1. Effect of E-Readiness on e commerce-
adoption
This study used the PERM theory by
(Molla & Licker, 2005). Where the e-
readiness variable was classified into 2
groub, namely Perceived Organization E-
readiness (POER) and Perceived External E-
readiness (PEER). POER variables consist of
awareness, human resources, technological
resources, business resources,
commitment, and governance. Meanwhile,
the variables belonging to the PEER group
are government e-readiness, market forces,
and supporting industries.
The test of the effect of e-readiness on
online food delivery apps shows different
results between Indonesia and Malaysia.
Several POER variables affect online food
delivery apps adoption in Indonesia. These
results were strengthened by previous
research that stated that organizational
readiness factors affected e-commerce
Reyna Nadhya Ulhaq | 458
adoption (Lim et al., 2017). On the other
hand, in Malaysia, the POER variable did not
affect online food delivery apps adoption.
Research (Hanum & Sinarasri, 2018),
(Ningtyas & Sunarko, 2015), which stated
that organizational readiness did not affect
e-commerce adoption, strengthens the
results of the study in Malaysia’s case.
Regarding the POER factor in
Indonesia and Malaysia, the test results
show that resource factors (human
resources, technology resources, and
business resources) and governance factors
did not significantly affect online food
delivery apps adoption. Previous research
used PERM theory to investigate website
adoption, e-procurement adoption, and
others that require higher technology than
the resources used by online food delivery
apps adoption. In website or e-
procurement adoption, specific resources
are needed. So, the higher resources will
affect the level of technology adoption. In
contrast to the resources and governance
used by online food delivery apps, nearly
every business already owns and can
operate one. Which research results show
that resources and governance do not
significantly affect the adoption of online
food delivery apps.
Awareness does not significantly
influence online food delivery apps
adoption in Indonesia and Malaysia.
Awareness includes the benefits and
opportunities of online food delivery apps
and the weakness and threats of adopting
online food delivery apps. Each SME has
different views about the weaknesses,
opportunities, threats, and benefits of
adopting online food delivery apps. In
addition, they also have different actions to
responding their views. Due to
considerations of advantages and
disadvantages, higher awareness of SMEs
did not necessarily affect the adoption of
online food delivery apps. The results of
this study contradicted research conducted
by (Nurunnisha & Dalimunthe, 2018), who
stated that awareness was one of the
factors that influenced the adoption of
technology.
The hypothesis analysis showed a
different result in the POER's variable,
commitment. The commitment
significantly affects online food delivery
apps in Malaysia but does not in Indonesia.
Several SMEs in Malaysia adopted online
food delivery apps as their marketing
strategies. However, not all SMEs adopted
online food delivery apps smoothly. Some
of them were constrained by technical
problemsThe problems include not
agreeing with the cooperation contract and
the lack of services and responses from
online food delivery apps companies. While
in Indonesia, the commitment had a
positive effect on online food delivery apps
adoption. Higher competition has made
food retailing SMEs in Indonesia strategize
to survive in the food retailing industry.
Every SME had different commitments in
each marketing strategy according to their
priority. One alternative marketing strategy
was the adoption of online food delivery
apps. SMEs committed to making online
food delivery apps as a marketing strategy
will fight and optimize sales through online
food delivery apps. These efforts include
participating in various promotions,
integrating with e-banking and e-money,
and others. So the higher commitment will
influence their adoption rate of online food
459 | Effect of Sme’s E-Readiness and Online Food Delivery Apps Adoption Toward Business
Performance
delivery apps. (Molla & Licker, 2005) and
(Ali & Alrayes, 2014) state that
commitment is the most influential factor
contributing to technology adoption, so
businesses must support technology
adoption in their vision and provide
leadership to implement that vision.
In contrast to the POER variable test
where Malaysia and Indonesia showed
different results, a PEER variable affects
online food delivery apps adoption both in
Indonesia and in Malaysia. These results
were strengthened by the research of
(Duan et al., 2012), (Yulimar VA., 2006),
(Ningtyas & Sunarko, 2015), which stated
that the external environment significantly
influences e-commerce adoption.
The variable affecting e-commerce
adoption both in Indonesia and Malaysia
was market forces. The various
conveniences provided by the online food
delivery apps to consumers seem to have
led to ordering requests through online
food delivery apps. Request from the
customer has forced SMEs to adopt online
food delivery apps. Consumer demand for
purchases through online food delivery
applications made SME realize that they
have market opportunities on online food
delivery apps. (Aghaunor & Fotoh, 2006)
stated that market readiness affected
business actors' beliefs about whether or
not an online market exists. The results of
this study were supported by (Molla &
Licker, 2005) and (Aghaunor & Fotoh,
2006), which stated that market forces
influence the adoption of online food
delivery applications.
Besides market forces variable,
supporting industries also influenced
online food delivery apps adoption in
Indonesia. Supporting industry, in this case,
includes online food delivery apps
companies telecommunications companies
that provide internet services, and financial
institution companies that provide support
services for the adoption of online food
delivery apps. The higher support from
supporting industries impacts SMEs'
adoption of online food delivery apps.
Different results were obtained from the
case of Malaysia, where the supporting
industry has no influence on the extent of
online food delivery apps adoption by
Malaysian SMEs. The results study in
Malaysia was supported by (Rahayu & Day,
2015), who stated that the industry did not
influence the adoption of online food
delivery apps.
As for the Government variable, in the
case of the two countries, it did not
significantly affect online food delivery
apps adoption. That was supported by
research (Palacios, 2003) (Aghaunor &
Fotoh, 2006), and also (Rahayu & Day,
2015).
2. Effect of Online food delivery Apps
adoption to SME performers
Based on the evaluation of the
hypothesis, in both countries, online food
delivery apps adoption has a positive and
significant effect on SMEs' performance.
The results of these studies were supported
by previous research, namely
(Suriyapperuma et al., 2015), (Wu et al.,
2003) (Ramdansyah & Taufik, 2017), which
stated that the performance of SME was
positively and significantly affected by the
application of E-commerce. Likewise,
research conducted by (Opreana &
Vinerean, 2015), (Ivanauskiene et al., 2015),
Reyna Nadhya Ulhaq | 460
and (Mokhtar, 2015) stated that the
application of e-commerce could affect
business performance.
CONCLUSIONS
Based on the result of SEM analysis. In
both Indonesia and Malaysia, it was evident
that several variables of e-readiness affect
online food delivery apps adoption. In
Indonesia, e-readiness variables that affect
online food delivery apps adoption include
commitment, market forces, and
supporting industries. Malaysia has fewer
e-readiness variables affecting online food
delivery apps adoption, namely market
forces.
In both countries, the test stated a
positive influence of online food delivery
apps adoption on SME's performance.
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