Factors Affecting e-Commerce Adoption on Micro,

Small and Medium Enterprises in Medan City

Nurlinda

, Wardayani

and Iskandar Muda

Department

of Accounting, Politeknik Negeri Medan, Medan, Indonesia

Department of Management, STIM SUKMA, Medan, Indonesia

Faculty Economic and Business, Universitas Sumatera Utara, Medan, Indonesia

Keywords: Organizational Readiness, Technological Readiness, External Environment, E-Commerce.

Abstract: This study aims to see whether organizational readiness, technological readiness and external environment

affect the adoption of e-Commerce on micro, small, and medium enterprises in the city of Medan. This

research is a quantitative research with primary data and using questionnaires sent online to the respondents.

The sample is the target population analyzed by using multiple linear regression. The results of the data testing

showed that the organizational readiness variables did not affect the adoption of e-commerce on MSMEs, but

for the technology readiness variables the test results showed that this variable had a positive and significant

effect on the adoption of e-commerce on MSMEs, but for external environmental variables the results of

testing shows that there is a positive influence of this variable on the adoption of e-commerce on MSMEs,

but the effect is not significant.

1 INTRODUCTION

E-Commerce is a potential digital economy that has

potential growth opportunities in Indonesia. Based on

data e-Marketer which states that the number of

internet users in Indonesia every year continues to

grow.The data of Internet user since 2013 has been

recorded as 72.8 million and continues to increase in

2016 to 102.8, and in 2017, internet users in Indonesia

in the preceding to 112.6 million. Bank Indonesia

estimates from the data of significant internet users

there are 24.7 million people who shop online with

the estimated transaction value in 2018 reached 144

trillion. The importance of e-Commerce is not only

seen from the ease, efficiency of time, effort and cost

becomes the main value especially for Micro, Small

and Medium Enterprises (

MSMEs). The data of

MSMEs in Indonesia shows that 8.7 million is a big

potential for the economic sector. Improving e-

commerce users is inseparable from behavioral

changes from offline shopping to online. This change

in consumer behavior is evident from the annual

report released by We Are Social which shows in

2017 the percentage of Indonesian citizens buying

online by 41% increased by 15% compared to 2016

which was only 26%. Survey from Indonesia's

shopback recently released a recent research that

provides an overview of the predicted e-commerce

trends will occur throughout the year 2018 namely, 1)

shopping behavior patterns shifted to online, 2)

delivery services on the same day so the main choice,

3) installers move to lapak, 4) online shopping more

desirable because of the many promos offered, 5) the

growth of mobile wallet increasingly, 6) online ticket

sales increased.

Micro Small Medium Enterprises (MSMEs) are

an important economic sector in competitive

economic development even in Indonesia livelihoods

depend on this sector. The micro, small and medium

enterprises are concentrated in several business

sectors such as trade, food, processed food, textiles

and garments, wood and wood products, and also the

production of minerals and metals and culinary.

Culinary a few years later entered into one of the sub-

Nurlinda, ., Wardayani, . and Muda, I.

Factors Affecting e-Commerce Adoption on Micro, Small and Medium Enterprises in Medan City.

DOI: 10.5220/0010072313011311

In Proceedings of the International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches (ICOSTEERR 2018) - Research in Industry 4.0, pages

1301-1311

ISBN: 978-989-758-449-7

1301

sector of creative industries in Indonesia so that

Indonesia embraces the 15 subsectors of creative

industries (Nurrohmah and Alfanur, 2016). These

SMEs move in competitive conditions and

uncertainty and influenced macroeconomic (Hapsari,

2014) plus a bad business environment because the

risk of loss is higher than big business. The general

problems faced by MSMEs are financial and non-

financial (Urata and Kawai, 2000) in addition to these

problems (Urata and Kawai, 2000) mention that the

implementation of laws and regulations related to

SMEs, including taxation issues that have not yet

adequate. There are still discrepancies in the facilities

provided by the government compared to the needs of

SMEs, as well as the lack of linkage between SMEs

themselves or between SMEs with larger industries

become the problems faced by MSMEs.

Research conducted by(Rahayu and Day, 2015)

found that perceived benefits, technological

readiness, owner innovation, Information and

Technology (IT) owners and owners IT experience

are the decisive factors that influence Indonesian

SMEs in adopting e-commerce, further (Rahayu and

Day, 2017) found that SMEs at higher levels of

experience from e-commerce adoption experience

benefited greater e-commerce than those at other

adoption rates. A different focus is seen in the

research (Nurrohmah and Alfanur, 2016) who found

three factors in e-commerce adoption of SMEs

Fashion in Bandung consisting of technological

readiness factor, external factor of company and

internal factor of company. Further ((Nurrohmah and

Alfanur, 2016), (Magdalena, 2017), (Kabanda and

Brown, 2017) found that technological readiness

factors were influential, further research (Magdalena,

2017) also found a typical food business entrepreneur

as an alternative factor of the highest weight. Several

studies have been conducted to examine the factors

that influence e-Commerce adoption such as

perceived barriers, good support (management

support), organizational readiness, and competitors’

pressures. (Lim, Baharudin and Low, 2017), (Iqbal

and Astuti, 2013) find competitive pressure affecting

e-commerce adoption of MSMEs. Other studies have

found that organizational readiness influences e-

commerce adoption(Lim, Baharudin and Low, 2017)

but ((Iqbal and Astuti, 2013), but (Hanum and

Sinarasri, 2017)research found that organization

readiness has no effect. Other research shows that

perceived barriers factors show no effect on e-

commerce(Lim, Baharudin and Low, 2017), but

perceived benefits (Iqbal and Astuti, 2013) positively

affect the adoption of e-commerce in MSMEs. Factor

management support affects e-commerce adoption of

MSMEs (Lim, Baharudin and Low, 2017), while

Family business's strategic orientations have a

moderate influence between external pressure,

organizational readiness and perceived benefits

(Iqbal and Astuti, 2013).

Based on this background, the formulation of this

research problem is whether there is a positive

influence on 1) organizational readiness, 2)

technological readiness and 3) the external

environment partially towards the adoption of e-

commerce in SMEs in Medan city. The purpose of

this study to determine whether the organization's

readiness, technological readiness, external

environment positively affect the adoption of e-

commerce on MSMEs.

2 LITERATURE REVIEW

2.1 Adoption of Electronic Commerce

(e-Commerce)

According to (www.depkop.go.id) e-Commerce is a

business activity that uses the internet as part of the

whole or part of a business transaction. Transactions

with suppliers through the internet, advertising

through the internet, transactions with consumers via

the internet via the Internet, and others-commerce is

a transaction of buying and selling goods and services

by using the internet and providing a means to

conduct transactions involving goods or services

between two or more parties using electronic and

techniques devices

.(Nurrohmah and Alfanur, 2016).

E-commerce is a process of buying and selling

products or services through electronic data

transmission using the internet and world wide

web(Li and Xie, 2012). E-commerce is a dynamic set

of technologies, using applications and business

processes that connect companies, consumers and

certain communities through electronic transactions

in the trading of goods, services and information

electronically (Yulimar, 2010).

Factors that drive e-Commerce (Nurrohmah and

Alfanur, 2016), consist of 1) Environmental

perspective, consisting of a socio-cultural

environment, corporate strategy, external pressure,

benefits; 2) Perspective of company, consisting of

company size and company structure; 3)

Technological perspective of IT Infrastructure,

Internet, Company technical strength, IT capability

and IT adoption, government support. Factors

affecting SMEs in adopting e-commerce in

developing countries are as follows (a) Perceived e-

readiness, including awareness, human resources,

ICOSTEERR 2018 - International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches

1302

business resources (business resources), technology

resources, commitment (commitment) and

government (government). b). Perceivedexternal e-

readiness includes: government readiness, market

forces readiness, industry support (supporting

industries). Research (Morteza, Daniel & Jose, 2011)

in (Hanum and Sinarasri, 2017) states that e-

commerce should be tailored to the company, where

this conformity refers to the extent to which e-

commerce complies with technological, cultural, pre-

existing to the company.

2.2 Micro Small and Medium

Enterprises (MSME)

Understanding of MSMEs according to (Law No. 20,

2008) concerning micro, small and medium

enterprises (MSMEs), states that micro-enterprises

are productive businesses owned by individuals or

individuals and / or individual business entities, while

small businesses are productive economic enterprises

that stand alone. individual is not a subsidiary, not a

branch of the company owned, and is not a direct or

indirect part of a medium or large-scale business, and

a medium-sized business is a productive economic

enterprise that is independent, carried out by an

individual not a subsidiary, not a branch of the

company owned, and not a direct or indirect part of a

small business or large business. SMEs in terms of

turnover have criteria, 1) micro businesses have a

maximum asset of 50 million and a maximum

turnover of 300 million; 2) small businesses have

assets greater than 50 million to 500 million and

turnover greater than 300 million to 2.5 M; and 3)

medium-sized businesses have assets greater than 500

million to 10 M and turnover of large from 2.5 M - 50

Research conducted by (Urata and Kawai, 2000)

states that the inhibiting factor of MSMEs consists of

financial factors and non-financial factors. Urata

further explained about financial factors which

consist of: 1) lack of compatibility between available

funds that can be accessed by SMEs, 2) the absence

of a systematic approach in SME funding, 3) high

transaction costs, caused by sufficient credit

procedures complicated so that it takes a lot of time

while the amount of credit disbursed is small, 4) lack

of access to formal funding sources, both caused by

the absence of remote banks and the unavailability of

adequate information, 5) credit interest for investment

and working capital is quite high, 6) many SMEs are

not yet bankable, both due to the lack of transparent

financial management and lack of managerial and

financial capabilities related to non-financial factors

regarding organizational management problems,

consisting of: 1) lack of knowledge of production

technology and quality control caused by the lack of

opportunities to keep up with technological

developments, as well as lack of education and

training, 2) lack of marketing knowledge due to

limited information accessible to SMEs regarding the

market, in addition to the limited ability of SMEs to

provide products / services that are in line with market

desires, 3) limited human resources due to lack of

resources to develop Human Resources, 4) lack of

understanding of finance and accounting.

2.3 Organizational Readiness

Organizational readiness is one of the factors that

influence the adoption of e-commerce by the

company (Hanum and Sinarasri, 2017). According to

Hoffer (2002) in (Nelson and Shaw, 2003)mentions

that organizational readiness is intended to attribute

firm-level attributes from organizations that estimate

overall company readiness in innovation diffusion.

Further (Chwelos, Benbasat and Dexter, 2000) states

that organizational readiness is a measure of the

adequacy of the company's experience in IT and the

financial resources to adopt. (Chwelos, 2000)

explains that IT experience encompasses not only the

level of technological expertise within the

organization but also includes the level of

management's understanding of IT usage and the use

of IT support to achieve organizational goals, while

for financial resources it represents the availability of

organizational capital for IT investments.

Companies that will adopt e-commerce require

technology readiness in addition must also consider

the size of the company. Zhu et al, 2006 in (Hanum

and Sinarasri, 2017) states that the technology

infrastructure must be tailored to the system and

technical capabilities of the business to be able to

support e-commerce. Absolute technological

infrastructure must be owned by companies that will

implement e-commerce consists of technology

infrastructure and information technology personnel

(Zhu and Kraemer, 2005), while other determining

factors that play a role in the implementation of e-

commerce in the organization is firm size (firm size).

The size of the company is related to the company's

ability to prepare resources that support the adoption

of e-commerce consisting of financial and human

resources (Oliveira and Martins, 2010), thus it can be

said that the larger the size of the company the greater

the company's ability to prepare the necessary

resources in the adoption of e-commerce (Hanum and

Sinarasri, 2017). Further (Hanum and Sinarasri,

Factors Affecting e-Commerce Adoption on Micro, Small and Medium Enterprises in Medan City

1303

2017) mentioned that the better the managerial

understanding of the relative advantages of e-

commerce adoption will make the company allocate

some resources, such as managerial, financial and

technological resources.

2.4 Technology Readiness

Factor technology consists of several indicators, such

as perceived benefits, conformance, and costs that

affect the adoption of e-commerce technology

(Hanum and Sinarasri, 2017). Research (Oliveira and

Martins, 2010) finds that the perceived benefit is the

level of profit earned that will be obtained for

companies. They further argue that the application of

technology is so expensive that it becomes an

obstacle factor in the technological readiness of the

organization this is in line with (Hanum and Sinarasri,

2017) also mentions that in the implementation of e-

commerce in Indonesia the cost factor in the

application of technology is also quite instrumental,

and (Premkumar & Robert, 1999 in (Jannah and

Rahayu, 2015) mentioned below usually low cost

technology will accelerate the adoption and

implementation of technology in the organization .

2.5 External Environment

The external environment factor is a factor consisting

of several aspects such as consumer pressure /

supplier, competitive pressure affecting the company

in adopting e-commerce (Hanum and Sinarasri,

2017). According to Provan (1980) in (Chwelos,

Benbasat and Dexter, 2000) external encouragement

includes influences arising from several sources in the

competitive environment around the organization

consisting of competitive impetus, industry impetus

and the impetus of a trading partner's influence. One

of the external factors considered by companies in

adopting IT is the presence of competitors (Sarosa

and Zowghi, 2003). Another pressure that plays a role

in e-commerce adoption is the pressure from business

associates that the higher the pressure of business

associates the possibility of companies adopting high

e-commerce in the company's efforts to maintain their

competitive position (Duan, Deng and Corbitt, 2012).

The higher pressure from competitors will force the

company to adopt e-commerce (Hanum and Sinarasri,

2017) but with higher competition it will show the

benefits of e-commerce adoption (Zhu and Kraemer,

2005). Other external factors that play a role are

government support and technology providers

(Hanum and Sinarasri, 2017).

2.6 Organizational Readiness and

e-Commerce Adoption

Organizational readiness on e-commerce adoption is

explained using the Framework Technology

Organization and environment (TOE Framework)

theory adopted from Tornatzky and Fleisher (1990) in

(Oliveira and Martins, 2010). This theory considers

that the decision to use technological innovation is

based on organizational factors, external environment

and technological characteristics (Huy, et al., 2012)

in (Nurhadi, 2015). The results of the study (Hanum

and Sinarasri, 2017) found that organizational effects

negatively to e-commerce adoption, while the results

(Oliveira and Martins, 2010), (Duan, Deng and

Corbitt, 2012) found that organizational readiness

factors and management support were a significant

facilitator for e-commerce adoption. Research

(Rahayu and Day, 2017)found that e-commerce

adoption is beneficial to higher SMEs. Based on the

above explanation, the hypothesis for this research is

as follows:

H1: There is a positive influence of organizational

readiness on e-commerce adoption

2.7 Technological Readiness and

e-Commerce Adoption

The adoption of an innovation is called diffusion and

is tied to the theory of diffusion of innovation.

Diffusion is a process whereby an innovation is

adopted by an organization (Hashim, 2007)).

According to (Rogers, 1995)there are four factors that

influence the adoption of an innovation by the

organization: (1) innovation itself, (2) the

communication channel used to disseminate

innovation, (3) time, and (4) where the place of

innovation was introduced . Use of technology is

needed in order to adopt e-commerce.

Research conducted by (Hanum and Sinarasri,

2017) found that technology has an effect on the

adoption of UMKM e-commerce. The results

(Oliveira and Martins, 2010) found that the

technological readiness factor was a significant

facilitator for e-commerce adoption, and further

stated that technological readiness included

professional attachments, user skills and e-business

skills. Based on the above explanation then

hypothesis 2 is as follows:

H2: there is a positive effect of technology

readiness on e-commerce adoption

ICOSTEERR 2018 - International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches

1304

2.8 External Environment and

Adoption of e-Commerce

External environmental factors are factors that consist

of several aspects such as customer / supplier

pressure, competitor pressure that affects the

company in adopting e-commerce(Hanum and

Sinarasri, 2017). In competitive environments around

the organization are competitive encouragement,

industry encouragement and the influence of trading

partners (Provan, 1980) in (Chwelos, Benbasat and

Dexter, 2000). Competitors are an important element

in the external factors that companies consider in

adopting IT (Sarosa and Zowghi, 2003). Based on the

research (Duan, Deng and Corbitt, 2012), (Yulimar,

2008), (Yulimar, 2010)found that the external

environment has a positive relationship on the

adoption of e-commerce while (Hanum and Sinarasri,

2017) found environmental factors positively e-

commerce adoption. Based on the above explanation,

the third hypothesis can be arranged as follows:

H3: there is a positive effect of the external

environment on e-commerce adoption

3 RESEARCH METHODOLOGY

This research is a quantitative research that uses

primary data in the form of distributing

questionnaires to e-commerce actors. Data were

collected using an online questionnaire of the 200

respondents consisting of small business actors,

micro and medium enterprises, the questionnaire

returned only 31. This study will use multiple linear

regression tests to answer the proposed hypothesis.

3.1 Conceptual Framework

The conceptual framework of this study looks as

follows which consists of three independent variables

(VI) and one dependent variable (VD) consisting of

organizational readiness (VI 1), technological

readiness (VI 2) and external environment (VI 3) and

adoption e-commerce (VD). The concept framework

is shown in Figure 1 below:

Figure 1: Concept framework

Note’s:

X1 : Organizational Readiness

X2 : Information Technology readiness

X3: External environment

Y : e-Commerce Adoption

3.2 Population and Sample

The population in the research is all micro business

and small business in Medan city that use e-

commerce, the sample is the target population

obtained from the whole questionnaire distributed

online.

Data were collected using an online questionnaire

Of the 200 respondents consisting of small business

actors, micro and medium enterprises, the

questionnaire returned only 31 respondents.

3.3 Research Variable

The variable of this research consists of one

dependent variable that is performance variable of

UMKM, one mediation variable that is adoption of e-

Commerce and 3 independent variable that is,

organizational readiness, readiness of information

technology, and external motivation.

3.4 Variable Operational Definition

3.4.1 e-Commerce Adoption

E-commerce adoption is all business activity or

business done on-line by using internet-based

information technology. E-Commerce adoption

variables are formed by nine indicators consisting of

1) Support of all organizational elements, 2) Resource

adequacy, 3) Availability of facilities and

infrastructure 4) Information technology, 5) External

party encouragement, 6) E-Commerce facilitates

access to information , 7) E-Commerce can improve

ITR

(X2

EE

(X3)

e‐

Com

OR(X

Factors Affecting e-Commerce Adoption on Micro, Small and Medium Enterprises in Medan City

1305

business performance, 8) E-Commerce can improve

the quality and speed of service to business partners,

9) E-Commerce can improve cost efficiency, E-

Commerce is superior to conventional-based trading

(Nuvriasari, 2012)

3.4.2 Organizational Readiness

Organizational readiness variables use indicators

from (Nuvriasari, 2012) by modifying the question

instruments of 4 indicators consisting of, 1)

availability of financial resources, 2) readiness to

accept risks from e-commerce utilization, 3)

leadership commitment, 4) awareness of acceptance

of change and development of information

technology.

3.4.3 Variable Technological Readiness

The technological readiness variable uses

modifications of four indicators developed by

(Nuvriasari, 2012) consisting of, 1) HR capabilities

and skills, 2) availability of information technology

tools (computers and internet networks); 3)

availability of e-commerce support programs and

systems software, website), 4) Compatibility between

benefits and costs in the application of e-commerce.

3.4.4 External Environment

The external environment variable is an

encouragement that comes from outside the company

which is the reason for the company in adopting e-

commerce. For this variable we use a modified

indicator of (Nuvriasari, 2012)) consisting of, 1)

Encouragement and demand from the consumer, 2)

Suppliers' encouragement and demand, 3)

Encouragement and demands of business

development, 4) Government encouragement, 5)

Encouragement and competitive pressure demands.

3.5 Data Analysis Method

This study will use multiple linear regression tests to

answer the proposed hypothesis. The data will be

processed using SPSS. From the model that has been

prepared, then this research will yield good parameter

value with the fulfillment of classical assumption of

multiple regression test. The classical assumption test

is validity test, reliability, normality, multicolinearity

and heteroscedasticity.

4 DISCUSSION AND RESULT

All the question instruments proposed in this research

questionnaire have been tested for validity and

reliability. Testing of validity and reliability is

necessary considering the type of research data is

primary with a questionnaire. Test the validity of data

is done by comparing the value of r arithmetic with r

table for alpha 5% and df = n-2 ie 0.335. The r value

of the table in this study for "n" is 31 (df: 31-2 = 29)

and P = 0.05 is 0.335 so this value will be used as

comparison with the calculated r value obtained from

the processing using SPSS. Based on the validity test

results found there are some items of the statement

are not valid, thus the item is discarded. From the

external environmental variables of 5 points 1

statement is not valid so it is not used in this research

while from 9 items of e-commerce adoption variable

4 items statement is invalid and not included in the

discussion of this research. For organizational

readiness variables and technological readiness all

statements are valid.

After all invalid statements are discarded

then the validity test is validated so that the whole

item valid statement, indicated by one-way count r is

greater than r table i.e. for sample 31 with alpha 5%

is 0.335. After testing the validity, the next step is to

test the reliability of data that is by looking at the

value of reliability coefficient greater than the value

of cronbach's alpha 0.6. According to (Santoso,

2001), if the alpha count is greater than the alpha table

with a positive value then the research instrument can

be called reliable. The results of validity and

reliability can be seen in tables 1 and 2 below:

Table 1: Validity Test

Variables

Indicator

Count

Tabl

Remark

Organization

al readiness

KO1 0.746

0.35

5 Vali

KO2 0.722

0.35

5 Vali

KO3 0.582

0.35

5 Vali

KO4 0.413

0.35

5 Vali

Technologica

l readiness

KT1 0.530

0.35

5 Vali

KT2 0.650

0.35

5 Vali

KT3 0.598

0.35

5 Vali

KT4 0.466

0.35

5 Vali

ICOSTEERR 2018 - International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches

1306

Eksternal

environment

LE1 0.715

0.35

5 Vali

LE2 0.659

0.35

5 Vali

LE4 0.670

0.35

5 Vali

LE5 0.627

0.35

5 Vali

E-Commerce

Adoption

AE2 0.689

0.35

5 Vali

AE3 0.775

0.35

5 Vali

AE4 0.741

0.35

5 Vali

AE5 0.492

0.35

5 Vali

AE9 0.640

0.35

5 Vali

Source: research results 2018 (data processed)

Table 2: Reliability Test

Variables

Coefficient

Reliabilit

y limits Remarks

Organizationa

l readiness 0.789 0,60 Reliable

Technological

readiness 0.752 0,60 Reliable

Externals

environment 0.827 0,60 Reliable

E-Commerce

Ado

tion 0.844 0,60 Reliable

Source: research results 2018 (data processed)

4.1 Classical Assumption Testing

Classic assumption testing is needed to see if the data

is biased if regression testing is performed. Classical

assumption testing is needed to determine an

econometrically acceptable regression model. These

classical assumptions consist of normality testing,

heterocedasticity testing and multicollinearity testing.

4.2 Normality Testing

Kolmogorof Smirnov test was used to test the

normality of the data. In this test the data are said to

be normally distributed if the Kolmogorov Smirnov

value has a probability greater than 0.05 (Santoso,

2001). The test results showed that the data has a

normal distribution where the value of Kolmogorov

Smirnov is 0.882 with a significance level of 0.509.

Level of significance 0.509> 0.05 then it can be

concluded normal distributed data. Normally

distributed data will spread on the side of the diagonal

line on the P.Plot graph. The normality test graph can

be seen in the following figure.

Figure 2: Normality Testing

Normally distributed data can be used for conclusion

because the data has spread with characteristic

resembling the population represented.

4.3 Heterocedasticity Testing

Based on the test results shown in Figure 3 below,

which is adapted from the SPSS output can be

concluded that the data in this study is free from

symptoms of heterokedastisitas because the plot

diagram seen in the test does not show a certain

pattern but is random. Groups of data indicated to

have heterokedastisity character will form a certain

pattern such as centered at a certain point or form a

pattern that has certain characteristics, which in

testing this research model is not found it, meaning

that the variation error is not too large so that the

regression is quite reliable Triton, (2006). These

particular points are randomly distributed, do not

form a certain clear pattern, and are spread either

above or below the number 0 on the Y axis.

Figure 3: Heteroscedasticity testing

Factors Affecting e-Commerce Adoption on Micro, Small and Medium Enterprises in Medan City

1307

4.4 Multicolinearity Testing

Multicolinearity may arise if independent variables

are correlated with each other, so multicolinearity can

only occur in multiple regression. This resulted in a

change in the sign of the regression coefficient and

resulted in large fluctuations in the regression result.

The change in the sign of this regression coefficient

can lead to errors in interpreting the relationship

between variables so that the presence of this

multicolinearity should be tested (Levin and Rubin,

1998). This test is conducted to ensure that the

independent variables in this study are not mutually

correlated. Measurements are often used to measure

whether there are correlated variables using Variance

Inflation Factor (VIF) test or detection devices.

Where VIF values are not more than 10 and tolerance

values is not less than 0.1.

Table 3: Multicolinearity Testing

Variables

Collinearit

Statistics

Tolerance VIF

Organizational readiness 0.423 2.364

Technolo

ical readiness 0.456 2.194

Externals environment 0.703 1.422

Source: research results 2018 (data processed)

Table 3 shows that from the independent variable

the VIF value is not more than 10 and the tolerance

value is not less than 0.1. So it can be concluded in

this regression model there is no multicollinearity

problem.

4.5 Results of Data Analysis

4.5.1 Hypothesis Testing with t test

After testing the classical assumption and obtained

the conclusion that the model can be used to perform

multiple regression analysis, and then the next step is

to test the hypothesis.Hypotheses to be tested are

Effect of organizational readiness, technological

readiness, and external environment against the

adoption of e-commerce. Summary of hypothesis

testing results can be seen in table 4 below.

Table 4: Summary of Hypothesis testing

Model

Unstandardi

zed

Coefficients

Standardi

zed

Coefficie

nts

Sig

Std.

Erro

Beta

(Constant)

Organizatio

nal

readiness

Technologi

cal

readiness

Externals

environmen

.334 .334

1.00

.32

.289 .191 .280 1.50

.14

.362 .173 .373 2.08

.04

.221 .123 .259 1.80

.08

Source: research results 2018 (data processed)

Table 5: Anova Test

Mod

Squar

Adjuste

d R

Square

1 0.779 0.606 0.563 13.8

Source: research results 2018 (data processed)

To see the influence of each independent variable

partially to the decision to vote, it can be seen t

arithmetic and significance of the value of t

arithmetic. If the significance value of t arithmetic is

smaller than 0.05 then it can be stated that there is a

significant influence of these variables on e-

Commerce Adoption with 95% confidence level or

alpha 5%. In this study t test is used to test whether

the hypothesis used in this study is accepted or not by

knowing whether the independent variables

individually affect the dependent variable. The

method in the determination of t table using 5%

significant level provisions, with n-k (in this study df

= 31-4 = 27), so that obtained t table value of 1.703 is

presented in table 6 as follows:

Table 6: The value of t arithmetic

Variables

count

table

Signifi

cance

Hypoth

esis

Organization

al readiness

1.509

1.70

0.143

Not

Proven

Technologica

l readiness

2.087

1.70

0.047

Proven

Externals

environment

1.803

1.70

0.083

Proven

Source: research results 2018 (data processed)

ICOSTEERR 2018 - International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches

1308

Based on the above table, the results of the

research can be used to answer the hypothesis as

follows:

Hypothesis 1: There is positive influence of

organizational readiness to e-commerce adoption,

hence hypothesis of t value is positive but t arithmetic

<from t table that is 1.509 <1.703 it can be concluded

there is no influence of organizational readiness

towards e-commerce adoption. When viewed from

the table significance is indicated by a significance

value of 0.143 greater than alpha 0.05, which states

no significant effect. The results of this study are in

line with (Iqbal and Astuti, 2013), (Hanum and

Sinarasri, 2017).

Hypothesis 2: There is a positive effect of

technology readiness on e-commerce adoption, hence

this research show value t count> t table that is 2,087>

1,703 hence can be concluded to accept hypothesis,

there is a positive influence of technology readiness

to e-commerce and the effectof this significant

variable seen in the column of significance of 0.047

is smaller than alpha 0.05 thus expressed significant

effect. The results of this study are in line with

(Nurrohmah and Alfanur, 2016), (Noerlina and

Hiererra, 2013), (Magdalena, 2017), (Kabanda and

Brown, 2017).

Hypothesis 3: There is a positive influence of the

external environment on e-commerce, so this research

shows the value of t count> t table that is 1.803>

1.703, thereby can be concluded there is positive

influence of external environment to e-commerce.

This positive influence is not significantly visible

from the significance column of 0.083 greater than

0.05 thus not significant. The results of this study are

in line with (Provan, 1980) in ((Chwelos, Benbasat

and Dexter, 2000), (Yulimar, 2010), (Yulimar, 2008),

(Duan, Deng and Corbitt, 2012).

Submission of one-way hypothesis can be

analyzed partially from the value of significance

where the value of significance is below 0.05, it can

be stated that partially each independent variable has

a positive effect on the level of 5% alpha. From the

table above can be explained that all independent

variables are positive but organizational readiness

variable has a t value smaller than t table, so reject

hypothesis H1 i.e. no effect of organizational

readiness on e-Commerce adoption, while the

variables of technology readiness and external

environment variables influence against e-commerce.

However, from the significance of only technology

readiness variables that has a positive and significant

effect.

4.6 Result of Regression Equation

To facilitate the reading of results and interpretation

of regression analysis then used the form of equation.

Equation or model contains the constants and

regression coefficients obtained from the data

processing that has been done previously. Regression

equations that have been formulated then with the

help of data processing program, the processing so

that the final equation obtained as follows:

Y = 0.334 + 0.289 organizational readiness +

0.362 Technological readiness + 0.221 external

environment + e

In this regression model, the listed constant value

of 0.334 can be interpreted if the independent

variables in the model are assumed to be equal to

zero, the average variable outside the fixed model will

increase the choice decision by 0334 times.

The value of the regression coefficient β1, 0.289 in

this study can be interpreted that the organizational

readiness variable (VI 1) is positive but does not

affect the adoption of e-commerce (Y). This shows

that every variable of organizational readiness has

increased by one time, and then the adoption of e-

commerce will not increase.

The value of regression coefficient β2 equal to

0.362 in this research can be interpreted that

technological readiness variable (VI 2) have positive

and significant influence to decision of adoption of e-

commerce (Y). This shows that when technology

readiness has increased one time, the adoption of e-

commerce will also increase by 0, 362 times.

The value of the regression coefficient β3 of 0.221

in this study can be interpreted that the external

environment variable (VI 2) has a positive but not

significant effect on e-commerce adoption decision

(Y). This shows that when the external environment

has increased one time, the adoption of e-commerce

will also increase by 0.221 times.

From the above equation can be seen that the

coefficient of the variable of technology readiness

and positive external environment gives the meaning

that the higher the readiness of the organization, the

readiness of technology and the external environment

will be higher Adoption E-Commerce. However, for

organizational readiness variable that has t value <of

t table shows there is no influence of organizational

readiness towards e-commerce adoption.

Factors Affecting e-Commerce Adoption on Micro, Small and Medium Enterprises in Medan City

1309

4.7 Determination Coefficient Analysis

(R2)

The value of R in essence to measure how big the

relationship between independent variables with

dependent variables. Based on the test results

obtained R value of 0.779, this indicates that the

variable of organizational readiness, technological

readiness and external environment have a strong

influence on the adoption of e-commerce. While the

value of R square (R2) or coefficient value of

determination in essence measure how far the ability

of the model in explaining the variation of the

dependent variable. R2 value is between zero and

one. The small value of R2 means that the ability of

independent variables to explain variations in

dependent variables is very limited. A value close to

one means that independent variables provide almost

all the information needed to predict variations of

dependent variables. Generally, R2 for cross-data

(crossection) is relatively low because of the large

variation between each observation, while for the

series data (time series) usually have a high

coefficient of determination. The underlying

weakness of using R2 is the bias against the

independent number of variables included in the

model. Each of the additions of one independent

variable, then R2 must increase, regardless of whether

the variable has significant effect on dependent

variable. Therefore, some researchers recommend

using an adjusted R2 value at the time of evaluation

(Ghozali, 2016)

The magnitude of the coefficient of determination

(R2) is 0.606 (60.6%). So, it can be said (R2) that

60.6% dependent variable that is e-commerce

adoption on model can be explained by independent

variable that is organizational readiness (VI 1),

technological readiness (VI 2) and external

environment (VI3), while the rest equal to 39, 4% is

influenced by other variables outside the model.

The results of the coefficient of determination

analysis can be seen in table 7 below:

Table 7: Results of Determination Coefficient Analysis

Mod

el R

Squa

Adjuste

d R

uare

Std.

Error of

the

Estimate

Durbin-

Watson

1 .77

.606 .563 .60676 2.190

Source: research results 2018 (data processed)

Partially organizational readiness has no

significant effect on E-commerce adoption, this

means that the higher organizational readiness does

not contribute significantly to the adoption of e-

commerce. Technological readiness variables

significantly influence the adoption of e-commerce,

this means the higher the readiness of technology, the

stronger the adoption of e-commerce. For external

environmental variables showing a positive but not

significant impact, it can be interpreted that the higher

the external environmental pressure will contribute to

the adoption of e-commerce adoption but this

contribution is not significant.

5 CONCLUSIONS

This study examines whether organizational

readiness, technological readiness, external

environment has a positive effect on e-commerce

adoption. Based on the testing of direction and the

discussion of the results of the research on the use of

e-commerce adoption, it can be concluded that

partially only organizational readiness variable is

positive but the positive value t count is smaller than

t table so it can be said there is no effect of

organizational readiness on adoption e-commerce,

another finding of this variable is a significant

significance greater than 5% alpha which states that

there is no significant effect of organizational

readiness variable on e-commerce adoption. For

technological readiness variables there is a positive

and significant influence on e-commerce adoption.

While for external environment variable there is

positive influence but not significant.

This research was conducted in a short time and

the respondent was limited to Medan city area with

the level of online questionnaire is quite low,

therefore for the next researcher can choose the

questionnaire directly so that it will improve the

return of questionnaire and the obtained sample can

be bigger. Although these three independent variables

are able to answer and represent the factors that

support e-commerce adoption, it would be better if

the next researcher can see other variables such as

taking into account internal factors, as well as

examining the inhibiting factors of e-Commerce

adoption.

REFERENCES

Chwelos, P., Benbasat, I. and Dexter, A. S. (2000)

Empirical Test of an EDI Adoption Model Empirical

Test of an EDI Adoption Model, Information Systems

ICOSTEERR 2018 - International Conference of Science, Technology, Engineering, Environmental and Ramiﬁcation Researches

1310

Research.

Duan, X., Deng, H. and Corbitt, B. (2012) ‘Evaluating the

critical determinants for adopting e-market in

Australian small-and-medium sized enterprises’,

Management Research Review, 35(3–4), pp. 289–308.

doi: 10.1108/01409171211210172.

Ghozali, I. (2016) Aplikasi Analisis Multivariate Dengan

Program IBM SPSS 23. VIII. Semarang: Badan

Penerbit Universitas Diponegoro.

Hanum, A. N. and Sinarasri, A. (2017) ‘Analisis faktor-

faktor yang mempengaruhi adopsi e commerce dan

pengaruhnya terhadap kinerja umkm (studi kasus

umkm di wilayah kota semarang)’, Maksimum, Vol.

1(No. 1), pp. 1–15.

Hashim, J. (2007) ‘Information Communication

Technology ( ICT ) Adoption Among SME Owners in

Malaysia’, 2(2), pp. 221–240.

Iqbal, M. and Astuti, R. D. (2013) Analisis Faktor Yang

Memperngaruhi Pengadopsian E-Commerce Pada

UMKM Khususnya Bisnis Keluarga.

Jannah, M. and Rahayu, S. (2015) ‘Pengaruh Partisipasi

Penganggaran terhadap Kinerja Manajerial SKPD

dengan Kejelasan Sasaran Anggaran , Komitmen

Tujuan Anggaran , Keadilan Distributif dan

Pengawasan Internal sebagai Variabel Intervening’,

Jurnal Perspektif Pembiayaan dan Pembangunan

Daerah, 3(2), pp. 69–90.

Kabanda, S. and Brown, I. (2017) ‘A structuration analysis

of Small and Medium Enterprise (SME) adoption of

E-Commerce: The case of Tanzania’, Telematics and

Informatics, 34(4), pp. 118–132. doi:

10.1016/j.tele.2017.01.002.

Li, P. and Xie, W. (2012) ‘A strategic framework for

determining e-commerce adoption’, Journal of

Technology Management in China, 7(1), pp. 22–35.

doi: 10.1108/17468771211207321.

Lim, S. C., Baharudin, A. S. and Low, R. Q. (2017)

‘Factors Influence SMEs in Malaysia to Adopt e-

Commerce: Moderating Roles of Perceived Strategic

Value’, Journal of Engineering and Applied Sciences,

12(6), pp. 1566–1574.

Magdalena, H. (2017) ‘Strategi Memanfaatkan E-

Commerce Dalam Memasarkan Makanan Khas

Bangka ( Studi Kasus : Aneka Citra Snack ) The

Strategy of Exploiting E-Commerce in The Marketing

Of Bangka Peculiar Food ( Case Study : Aneka Citra

Snack )’, Cogito Smart Journal, VOL. 3(NO. 2/DEC

2017), pp. 286–298.

Nelson, M. L. and Shaw, M. J. (2003) ‘The Adoption and

Diffusion of Interorganizational System Standards and

Process Innovations’, MIS Quarterly Special Issue

Workshop on: Standard Making: A Critical Research

Frontier for Information Systems, pp. 258–301.

Noerlina and Hiererra, S. E. (2013) ‘Penilaian Pemanfaat

Teknologi E-Business Pada Industri UMKM’,

ComTech, 4(9), pp. 1216–1224.

Nurhadi (2015) Anteseden Penggunaan E-Commerce:

Pengaruhnya Terhadap Manajemen Pengetahuan dan

Kinerja Organisasi. Universitas Brawijaya.

Nurrohmah, A. and Alfanur, F. (2016) ‘Adopsi E-

Commerce Pada Usaha Mikro Dan Kecil Di Bandung

( Studi Kasus Subsektor Fesyen ) Adoption of E-

Commerce on Micro and Small Enterprise in Bandung

( Fashion Subsector Case Study )’, in e-Proceeding of

Management, pp. 1120–1127.

Nuvriasari, A. (2012) ‘Peran Dukungan Organisasional,

Kompetensi Teknologi dan Lingkungan Eksternal

Dalam Rangka Mendorong Pengadopsian E-

Commerce Pada usaha Kecil Menengah’, Jurnal

Siasat Bisnis, Vol. 16(2), pp. 205–217.

Oliveira, T. and Martins, M. F. (2010) ‘Understanding e-

business adoption across industries in European

countries’, Industrial Management and Data Systems,

110(9), pp. 1337–1354. doi:

10.1108/02635571011087428.

Rahayu, R. and Day, J. (2015) ‘Determinant Factors of E-

commerce Adoption by SMEs in Developing Country:

Evidence from Indonesia’, Procedia - Social and

Behavioral Sciences. Elsevier B.V., 195, pp. 142–150.

doi: 10.1016/j.sbspro.2015.06.423.

Rahayu, R. and Day, J. (2017) ‘E-commerce adoption by

SMEs in developing countries: evidence from

Indonesia’, Eurasian Business Review. Springer

International Publishing, 7(1), pp. 25–41. doi:

10.1007/s40821-016-0044-6.

Rogers, E. M. (1995) Diffusion of Innovations. Fourth Edi.

New York: The Free Press.

Sarosa, S. and Zowghi, D. (2003) ‘Strategy for Adopting

Information Technology for SMEs: Experience in

Adopting Email within an Indonesian Furniture

Company’, Electronic Journal of Information Systems

Evaluation, 6(2), pp. 165–176.

Urata, S. and Kawai, H. (2000) ‘The determinants of the

location of Foreign Direct Investment by Japanese

small and medium size enterprises’, Small Business

Economics, 15, pp. 79–103.

Yulimar, V. A. (2008) ‘Analisis Faktor-Faktor Yang

Mempegaruhi Pengadopsian Electronic Commerce

Dan Pengaruhnya Terhadap Kinerja Perusahaan (Studi

Pada Perusahaan Kecil dan Menengah Di Indonesia)’,

in Seminar Nasional Aplikasi Sains dan Teknologi

2008, pp. 118–128.

Yulimar, V. A. (2010) Analisis Faktor-Faktor Yang

Mempengaruhi Pengadopsian Electronic Commerce

Dan Pengaruhnya Terhadap Kinerja Perusahaan (

Studi Pada Perusahaan Kecil Dan Menengah Di

Indonesia ).

Zhu, K. and Kraemer, K. L. (2005) ‘Post-adoption

variations in usage and value of e-business by

organizations: Cross-country evidence from the retail

industry’, Information Systems Research, 16(1), pp.

61–84. doi: 10.1287/isre.1050.0045.

Factors Affecting e-Commerce Adoption on Micro, Small and Medium Enterprises in Medan City

1311