M-Commerce Service and Application to Enhance Repurchase

Intention

Anis R. Amna and Supangat

Department of Informatics Engineering, University of 17 Agustus 1945 Surabaya, Jln. Semolowaru No. 45, Surabaya,

Indonesia

Keywords: Retail M-Commerce Service and Application, Consumer’s Purchase Intention, Stimulus Theoretical

Framework

Abstract: Rapid development of M-Commerce application (M-Commerce apps) and highly competitive market

encourage business to create innovative applications. Development of E-Marketplace in Indonesia increase

competition among business due to application benefits in enhancing bonding between existing customers

and the new one. In order to ensure repurchasing intention from customers, M-Commerce apps should be able

to satisfy particular needs and to enhance customers shopping experience. This study aims to evaluate the M-

Commerce application to enhance repurchasing intention using the apps. The data will be collected from 100

users and analysed using Partial Least Square – Structural Equation Modeling (SEM-PLS). The result shows

that application features drive customer to perceive ease of use, while perceived of ease of use (PEoU) and

information security are important factors to motivate users to use the mobile apps for repurchasing products.

1 INTRODUCTION

Vast growth of internet and mobile device penetration

in Indonesia make this country become the largest e-

commerce market in South East Asia (Priansa, 2016).

Whilst E-Commerce channels are continually

growing, nearly 75% of those transactions come

through mobile devices (Social and Hootsuite, 2018).

The large population of mobile users drives

massive development of online shopping technology,

business model, and ecosystems through mobile

applications. Customer loyalty program such as

rewards, gamifications, and advertisement through

the applications considered very important features to

create customers’ online behaviours (Hsu and Chen,

2018). This result is in line with previous studies that

revealed the importance of gamifications and rewards

for enhancing customers’ intention to install mobile

apps (Hwang and Choi, 2019) and strengthen

customers commitment to consume products

continuously (Leclercq, Hammedi and Poncin, 2018).

In Indonesia, retail stores are one of the most

affected business sector influenced with the

situations. The growth of online shopping channel

such as Lazada, Tokopedia, and Bukalapak truly

inspire small-medium business to broaden their

business digitally. In addition, enormous supports

from government and potential benefits from M-

Commerce apps motivate them for joining E-

Commerce apps to develop their own program. Most

of SMEs’ retail believe that adopting M-Commerce

apps is a key for business to retain their relationship

with customers through providing rewards, sharing

their shopping experiences, and yield particular

services as users need anytime anywhere (Iyer,

Davari and Mukherjee, 2018; Wang, Ou and Chen,

2019).

However, even though m-commerce apps is

considerably beneficial for both retailer and

customers, but highly investment and lack of

customers responses make this application need to

evaluated to make sure that customers are willing to

use application continuously (Onn Lee and Soon

Wong, 2016). Thus, this study will focus on

investigating what factors influence people to use M-

Commerce apps, if the apps can motivate users to

repurchase products using the channel, and whether

customer is willing to use M-Commerce apps

continuously.

R. Amna, A. and Supangat, .

M-Commerce Service and Application to Enhance Repurchase Intention.

DOI: 10.5220/0008433105150519

In Proceedings of the 2nd International Conference on Inclusive Business in the Changing World (ICIB 2019), pages 515-519

ISBN: 978-989-758-408-4

515

2 LITERATURE REVIEW

M-Commerce apps concepts and development of

internet technology bring enormous impact to Retail

Small Medium Enterprise (SME’s). While in the past

people have bigger trust to brick-and-mortar shop,

recently they tend to shop online through their fingers

(Hew et al., 2016).

M-Commerce apps users are continuously

increase and have significant impact to business

performance since the apps offering people new

experience on shopping and browsing information

quickly. Digital service delivery channel, E-Payment,

and gamification are some attractive services for

customers. However, study from (McLean, Al-

Nabhani and Wilson, 2018) showed that instead of

utilitarian factors of technology, enjoyment and

screen size of mobile apps are also influence users to

continue using m-commerce apps in the future.

Another studies had performed to analyse

customer behaviour during mobile applications

usage. Some factors related to the use of technology

framework, such as Technology Acceptance Model

(TAM), Unified Theory of Acceptance and Use of

Technology (UTAUT) have been developed to

respond customer behaviour within online

environment (Taherdoost, 2018).

Structural Equation Modelling (SEM) through its

Partial Least Square (PLS) is a good method for

testing prediction-oriented goal as well as to provide

evaluation procedure for complex model structures

(Carlson et al., 2017). PLS enable users to construct

reflective and formative models, conduct concurrent

analysis and develop hypothesis as well as investigate

the relationship between variables in the same time

(Hair Jr et al., 2016). In marketing research, PLS-

SEM considered as very supportive method for

assessing the success of certain target constructs as

well as for estimating, monitoring, and benchmarking

particular key drivers of the model (Hair, Ringle and

Sarstedt, 2011).

3 METHODOLOGY

First, a research model based on Stimulus Theoretical

Framework (Lai, 2016) with context as an additional

latent factor is constructed (figure 1). The additional

dimension is included because it considered having

correlation with customer loyalty and their intention

for repurchasing products.

Afterwards, a set of close answer questionnaire

was given to 150 of M-Commerce users and it

succeed to collect 66.67% respond rate (100 data). To

measure the repurchasing intention using M-

Commerce apps, the five Likert-scale was used to

represent degree of answers, start from 1 that

represents strongly disagree to 5 that represents

strongly agree.

Figure 1: The Research Model

Dimensions and indicators that are used to

construct the model are listed as follow:

Table 1: Dimensions, Indicators, and Instrument Items

Dimensions

Indicators

Instrument

Items

Context (Con)

Advantages

Con11

Good Idea

Con12

Information Quality

Feat11

Features (Feat)

Service Benefits

Feat12

Convenience

Feat13

Easy to Use

Feat14

Security (Sec)

Information

Security

Sec11

Data Privacy

Guarantee

Sec12

Perceived of

Usefulness

Fast Response

PoU1

(PoU)

Real Time

PoU2

Perceived Ease

Efficiency

PEoU1

of Use (PEoU)

Customers’

Satisfactions

PEoU2

Repurchasing

Continuity

RI1

Intention (RI)

Commitment

RI2

In order to obtain influential factors on

repurchasing intention, following hypotheses were

constructed:

H1: Context of information (Con) affects

positively to perceived of usefulness (PoU)

H2: Context of information (Con) affects

positively to perceived ease of use (PEoU)

H3: M-Commerce features (Feat) affects

positively to perceived of usefulness (PoU)

H4: M-Commerce features (Feat) affects

positively to perceived ease of use (PEoU)

ICIB 2019 - The 2nd International Conference on Inclusive Business in the Changing World

516

H5: M-Commerce data and information security

(Sec) affects positively to perceived of usefulness

(PoU)

H6: M-Commerce data and information security

(Sec) affects positively to perceived ease of use

(PEoU)

H7: M-Commerce data and information security

(Sec) affects positively to repurchasing intention (RI)

H8: Perceived ease of use (PEoU) affects

positively to perceived of usefulness (PoU)

H9: Perceived ease of use (PEoU) affects

positively to repurchasing intention (RI)

H10: Perceived of usefulness (PoU) effects

positively to repurchasing intention (RI)

The data were analysed using Partial Least Square

software after it passed reliability analysis to ensure

model sufficiency. Composite reliability score in this

research is more than or equal to 0.7 and Cronbach

Alpha value should be more than 0.7 (Larasati,

Widyawan and Santosa, 2017).

Our surveys get feedback from 100 M-Commerce

apps users, where 50% of them are women and 35.3%

are men. Regarding to the age, users who are willing

to response dominantly ranging from 36 to 40

(35.3%) followed by age around 31 to 35 that

represent 23.5% respondents. Among 100 users,

94.1% of them has experience to shop online using

M-Commerce apps from Bukalapak (41.2%) and

Shopee (35.3%).

4 RESULT AND DISCUSSION

Before deciding influential factors of repurchasing

intention behaviour, sets of reliability and validity

testing have been conducted. To obtain a valid model,

loading factor of AVE for each latent variable should

be above 0.5 (Ghozali, 2014). Table 2 show that the

value of each latent variable is above 0.5, so each

variable indicates qualified for the model.

Table 2: Latent Variable AVE Value

Dimension

AVE

Context (Con)

0.776

Features (Feat)

0.687

Security (Sec)

0.890

Perceived Ease of Use (PEoU)

0.609

Perceived of Usefulness (PoU)

0.770

Repurchasing Intention (RI)

0.788

In order to measure reliability, composite

reliability and Cronbach’s alpha value should be

above 0.7 for explanatory research (Hair, Ringle and

Sarstedt, 2011). Table 3 shows that composite

reliability of each latent variable is above 0.7. That

means that in terms of composite reliability test, all

dimension in the model is reliable. However, the

value of PEoU’s Cronbach’s alpha is below 0.7.

Therefore, PEoU is not reliable to the model.

Table 3: Composite Reliability of Each Latent Variable

Dimension

Cronbach's

Alpha

Composite

Reliability

Context (Con)

0.712

0.874

Features (Feat)

0.846

0.897

Security (Sec)

0.877

0.942

Perceived Ease of Use

(PEoU)

0.574

0.754

Perceived of Usefulness

(PoU)

0.701

0.870

Repurchasing Intention (RI)

0.736

0.881

Structural model testing was conducted to

investigate latent variables relationship in the model.

It is started by calculating t-value of lanes coefficient

and T-value by using two-tailed test. By comparing

the value of lanes coefficient and T-Value, we can

conclude whether the hypothesis among the lines

were accepted or rejected. Minimum value of

accepted T-Value according to t-table is 1.96. So, t-

value below 1.96 will be rejected.

Table 4: Lanes’s Coefficient, T-value, and Hypothesis

Explanation of Each Latent Variable

Lanes

Lanes' Coef.

T-Val

Explanation

Con → PoU

0,102

0,610

Insignificant

Con → PEoU

0,251

1,623

Insignificant

PoU →

Repurchasing

Intention

0,117

1,135

Insignificant

PEoU→

Repurchasing

Intention

0,333

3,394

Significant

PEoU → PoU

0,248

1,999

Significant

Feat → PoU

-0,051

0,331

Insignificant

Feat → PEoU

0,277

1,984

Significant

Security → PoU

0,369

2,898

Significant

Security →

PEoU

0,207

1,390

Insignificant

M-Commerce Service and Application to Enhance Repurchase Intention

517

Security →

Repurchasing

Intention

0,396

3,132

Significant

From the table 4 it is shown that repurchasing

intention behaviour is influenced significantly by

perceived of ease of use (PEoU), while in the same

time perceived of ease of use (PEoU) and information

security as well as data privacy guarantee also trigger

user to believe that the apps is useful. Meanwhile,

user perception about application simplicity is closely

related to information quality, service, convenience,

and easiness that should be represented in the

features.

To evaluate the validity of structural model,

variance of endogenous latent variables’ should be

high depends on particular research discipline. For

customer behaviour study, high level of variance is

represented by R-square >= 0.2. In this research,

endogenous latent variables that should meet the R-

square requirement are Perceived of Usefulness

(PoU), Perceived of Ease of Use (PoU), and

Repurchasing Intention. The result from table 5

shows that R-square value of each endogenous latent

variable is above 0.2, therefore the model is sufficient

to show customer behaviour.

Table 5: R

value of Endogenous Latent Variable

Endogenous Variable

R-Square

Perceived of Ease of Use (PEoU)

0,419

Perceived of Usefulness (PoU)

0,342

Intention to Repurchase

0,521

Finally, acceptance of the proposed hypothesis

will be analysis since the structural model testing

showed good result. For doing so, each lanes of

dimension will be represented by hypothesis and T-

value then the decision will be made by comparing T-

value to t-table using two-tailed test at significance

level of 0.05 (t-value >=1.96, p-value <=0.05).

Table 6: Hypothesis testing and conclusions

Lanes

Hypo-

tesis

T-Value

P-Value

Explanation

Con -> PoU

0,61

0,542

Hypotesis was

rejected

Con ->

PEoU

1,623

0,105

Hypotesis was

rejected

PoU ->

Intention to

Repurchase

1,135

0,257

Hypotesis was

rejected

PEoU ->

Intention to

Repurchase

3,394

0,001

Hypotesis was

accepted

PEoU ->

PoU

1,999

0,046

Hypotesis was

accepted

Feat -> PoU

0,331

0,741

Hypotesis was

rejected

Feat ->

PEoU

1,984

0,047

Hypotesis was

accepted

Security ->

PoU

2,898

0,004

Hypotesis was

accepted

Security -

>PEoU

1,39

0,165

Hypotesis was

rejected

Security ->

Intention to

Repurchase

H10

3,132

0,002

Hypotesis was

accepted

5 CONCLUSION

To conclude, this study aims to understand influential

factors on M-Commerce use in customer’s

repurchasing intention. In order to achieve the

objectives, a research model based on Stimulus

Theoretical Framework and Technology Acceptance

Model is developed. The result showed that perceived

of ease of use (PEoU) and security factors were

dominantly control user repurchasing behaviours,

while perceived ease of use and security factors were

also lead to usefulness perception on the M-

Commerce apps.

While M-Commerce apps is closely related to E-

Payment, this research find that security plays

significant impact on user willingness to use the apps

and repurchasing intention. Thus, this finding is

important for further development of M-Commerce

apps since improvement on data privacy guarantee

and information security will increase customers’

trust therefore will rise the number of M-Commerce

users. The finding is similar to prior studies (Jahangir

and Begum, 2013; Lai, 2016; Chong et al., 2018) that

mentioned M-Commerce security as an important

factor for customer decision making and adaptation.

In terms of M-Commerce features, convenience

and information quality are prominent for

repurchasing intention. In this research, this situation

occurs because particular knowledge is essential for

purchasing certain products. This finding is similar

with the finding from previous studies (Kassim et al.,

2012; Lai, 2016). However, the reliability test found

that PEoU’s value is unreliable, thus the hypothesis

acceptance related to PEoU should be further

analysed to find out whether this phenomenon only

happened in specific M-Commerce retail applications

or in general apps.

ICIB 2019 - The 2nd International Conference on Inclusive Business in the Changing World

518

ACKNOWLEDGEMENTS

The authors would like to acknowledge the Research

and Community Service of University of 17 Agustus

1945 Surabaya and Arrayana Honey for the financial

and data support in conducting the research.

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