building repurchase intention through online and …

xvii

BUILDING REPURCHASE INTENTION THROUGH ONLINE

AND MOBILE SERVICE QUALITY MEDIATED BY

SATISFACTION : AN EMPIRICAL STUDY

By:

Fransiska Roseline Setiawan Putri

015201400039

A Skripsi presented to the

Faculty of Business President University

In partial requirements for

Bachelor Degree in Business Administration

January 2018

xviii

PANEL OF EXAMINERS

APPROVAL SHEET

The Panel of Examiners declare that the skripsi entitled ―BUILDING

REPURCHASE INTENTION THROUGH ONLINE AND MOBILE SERVICE

QUALITY MEDIATED BY SATISFACTION : AN EMPIRICAL STUDY‖ that

was submitted by Fransiska Roseline Setiawan Putri majoring in Business

Administration from the Faculty of Business was assessed and approved to have

pass the Oral Examinations on January 2018

Dr. Ir. Farida Komalasari, M. Si.

Chair- Panel of Examiner

Adhi Setyo Santoso, ST,MBA

Examiner I

Suresh Kumar, ST, M.Si.

Examiner II

xix

CONSENT FOR INTELLECTUAL PROPERTY RIGHT

Title of

Skripsi :

BUILDING REPURCHASE INTENTION THROUGH ONLINE

AND MOBILE SERVICE QUALITY MEDIATED BY

SATISFACTION : AN EMPIRICAL STUDY

1. The Author hereby assigns to President University the copyright to the

Contribution named above whereby the University shall have the exlusive

right to publish the Contribution and translations of it wholly or in part

throughout the world during the full term of copyright including renewals

and extensions and all subsidiary rights.

2. The Author retains the right to re-publish the preprint version of the

Contribution without charge and subject only to notifying the University

of the intent to do so and to ensuring that the publication by the University

is properly credited and that the relevant copyright notice is repeated

verbatim.

3. The Author retains moral and all proprietary rights other than copyright,

such as patent and trademark rights to any process or procedure decribed

in the Contribution.

4. The Author guarantees that the Contribution is original, has not been

published previously, is not under consideration for publication elsewhere

and that any necessary permission to quote or reproduce illustrations from

xx

another source has been obtained (a copy of any such permission should

be sent with this form).

5. The Author guarantees that the Contribution containts no violation of any

existing copyright or other third-party right or material of an obscene,

indecent, libellous or otherwise unlawful nature and will indemnify the

University against all claims arising from any breach of this warranty.

6. The Author declares that any named person as co-author of the

Contribution is aware of this agreement and has also agreed to the above

warranties.

Name : Fransiska Roseline Setiawan Putri

Date : January 10, 2018

Signature :

xxi

ACKNOWLEDGEMENT

First and foremost I would like to express my gratitude to God for every blessings

He gave to me during this 3,5 years study, 8 months internship, and 4 months of

skripsi. It was not always an easy moment yet it helps me grow to be a better

person. Thank You for making this whole journey exciting and become a new

ground for bigger faith to face new phase of life ahead. Second, I would like to

thank my parents : Iwan Setiawan and Rany Ekawati for guiding, protecting, and

providing me with all the best supports since I born until now. Thank you son

much for giving your biggest love and support.

Third, I would like to thank my dearest friends : Fanni Agmeka and Felecia.

Thank you for letting me join your car to campus, and letting me rest in your

room in the gap of next class. They you for always being diligent. Thank you for

inspiring me.

Fourth, I would thank all lecturers in President University especially my skripsi

adviser : Mr. Suresh Kumar. Thank you for all your patience and clear guidance in

revising my skripsi. Thank you fo all lecturers who have inspired me and guide

me to learn better.

Cikarang, Indonesia, 10 January 2018

xxii

Fransiska Roseline Setiawan Putri

TABLE OF CONTENTS

CHAPTER I - INTRODUCTION ....................................................................... 1

1.1 Background ................................................................................................... 1

1.2 Significance of the Study .............................................................................. 5

1.3 Limitation ...................................................................................................... 6

1.4 Organization of Skripsi ................................................................................. 6

CHAPTER II- LITERATURE REVIEW........................................................... 7

2.1 Repurchase Intention ..................................................................................... 7

2.1.1 Definition of Repurchase intention. .................................................... 7

2.1.2 Measurement of Repurchase Intention .............................................. 7

2.1.3 Influencial factors of Repurchase Intention ....................................... 7

2.2 Satisfaction .................................................................................................... 8

2.2.1 Definition of Satisfaction ...................................................................... 8

2.2.2 Measurement of Customers Satisfaction ............................................ 9

2.2.3 Influencial Factors of Customers Satisfaction ................................... 9

2.3 Perceived Channel Integration .................................................................... 10

2.3.1 Definition of Perceived Channel Integration ................................... 10

2.3.2 Measurement of Perceived Channel Integration ............................. 11

2.3.3 Factors influenced by Perceived Channel Integration .................... 12

2.4. Mobile and Website Service Quality .......................................................... 13

2.4.1 Definition of Online Service Quality ................................................. 13

2.4.2 Definition of Mobile Service Quality................................................. 14

2.4.3 Measurement of Online Service Quality........................................... 15

2.4.4 Factors affected by Online Service Quality ...................................... 16

2.5. Research Gap .............................................................................................. 17

CHAPTER III - RESEARCH METHOD ......................................................... 20

3.2 Theoretical Framework ............................................................................... 20

Figure 3.1 Theoretical Framework .................................................................... 20

3.3 Hypothesis .............................................................................................. 20

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3.4 Operational definitions of variables ............................................................ 21

Table 3.1 Instruments of Questionnaire ............................................................ 21

3.5 Instrument .................................................................................................... 21

3.6 Sampling ...................................................................................................... 22

3.7 Data Gathering ............................................................................................ 22

Data collection method ................................................................................ 22

3.8 Data Analysis .............................................................................................. 23

1. Validity...................................................................................................... 23

2. Reliability.................................................................................................. 23

3. Descriptive Analysis................................................................................. 23

4 Inferential Analysis: Structural Equation Modelling ........................... 24

a. Model Fit................................................................................................... 24

e. Hypothesis Testing ................................................................................... 27

CHAPTER IV - RESULT AND DISCUSSION ............................................... 28

4.1 Validity and Reliability ............................................................................... 28

4.2 Respondents Profile ..................................................................................... 29

4.3 Descriptive Analysis.................................................................................... 30

4.3.1 Website Service Quality ....................................................................... 30

4.3.2 Mobile Service Quality ......................................................................... 33

4.3.3 Channel Integration .............................................................................. 36

4.3.4 Customer Satisfaction ........................................................................... 37

4.3.5 Repurchase Intention ............................................................................ 39

4.4 Inferential Analysis ..................................................................................... 40

4.4.1 Model Fit.............................................................................................. 40

Appendix 4j Model Fit Summary .................................................................. 40

4.4.2 Square Multiple Correlation- R2 ....................................................... 41

Appendix 4k Squared Multiple Correlation .................................................. 41

4.4.3 Mediation Analysis – Direct –Indirect Effect ................................... 42

4.4.4 Hypothesis Testing .............................................................................. 43

(2) Hypothesis 2: Channel Integration influences Customer Satisfaction 43

(3) Hypothesis 3: Mobile Service Quality influences Customer

Satisfaction .................................................................................................... 44

xxiv

(4) Hypothesis 4: Channel Integration influences Website Service Quality

44

(5) Hypothesis 5: Channel Integration influences Mobile Service Quality

44

(6) Hypothesis 6: Customer Satisfaction influences Repurchase Intention

44

4.5 Discussion ................................................................................................... 45

CHAPTER V - CONCLUSION ......................................................................... 50

5.1 Hypothesis Answers .................................................................................... 50

5.2 Future Recommendation ............................................................................. 50

REFERENCES .................................................................................................... 52

xxv

LIST OF APPENDICES

Appendice 1 – The Online Questionnaire ......................................................... 62

Appendice 2 – Data Tabulation ......................................................................... 73

Appendice 3a KMO and Bartlett's Test ............................................................. 81

Appendice 3b Communalities ........................................................................... 82

Appendice 3c Total Variance Explained ........................................................... 83

Appendice 3d Rotated Component Matrix ........................................................ 83

Appendice 3e Reliability Statistics of ―Website Service Quality‖ ................... 84

Appendice 3f Reliability Statistics of ―Mobile Service Quality‖ ...................... 84

Appendice 3g Reliability Statistics of ―Channel Integration‖........................... 84

Appendice 3h Reliability Statistics of ―Customer Satisfaction‖ ....................... 84

Appendice 3i Reliability Statistics of ―Repurchase Intention‖ ......................... 85

Appendice 3j Model Fit Result ......................................................................... 85

Appendice 3k Squared Multiple Correlation ..................................................... 87

Appendix 3l Direct & Indirect Testing .............................................................. 87

Appendice 3m Hypothesis testing ..................................................................... 90

Appendice 3n Amos Diagram ........................................................................... 92

xxvi

LIST OF TABLES

Table 3.1 Instruments of the Questionnaire ...................................................... 93

Table 4.2 Respondents by Age Demography .................................................... 97

Table 4.3 Respondents by Average Value of Transaction ................................ 97

Table 4.4 Website Service Quality Data Summary ........................................... 98

Table 4.5 Mobile Service Quality Data Summary ............................................ 99

Table 4.6 Channel Integration Data Summary .................................................. 99

Table 4.7 Customer Satisfaction Data Summary ............................................ 100

Table 4.8 Repurchase Intention Data Summary .............................................. 100

xxvii

LIST OF FIGURES

Figure 3.1 Theoretical Framework .................................................................. 101

Figure 4.1 Respondents by Age Demography................................................. 101

Figure 4.2 Respondents by Average Value of Transaction ............................. 102

xxviii

ABSTRACT

Purpose

The purpose of this paper is to examine the impact of channel integration between

website service quality and mobile service quality towards repurchase intention

through customer satisfaction as its mediating role in the context of ecommerce

Elevenia.co.id‘s customers in Greater Jakarta area.

Design/methodology approach

An online questionnaire consists of 33 items measurement was distributed to 300

Elevenia.co.id‘s customers through social media. There are 171 valid responds

from respondents who made purchase in Elevenia.co.id, domicile in Greater

Jakarta area, and in the group age between 18 -45 years old. The validity and

reliability test was done using construct validity and factor analysis. Data is then

further analyzed using Sturctural Equation Modelling to find out the relationships

among variables in the model proposed.

Findings

Analysis revealed that channel integration does not have any influence to the

repurchase intention through customer satisfaction, but customer satisfaction

influences the repurchase intention. It appears that channel integration, however,

has impact to both mobile and service quality. It also found that the website

service quality influences repurchase intention through customer satisfaction,

xxix

whereas the mobile service quality does not influence the repurchase intention

through customer satisfaction.

Keywords : Website Service Quality, Mobile Service Quality, Channel

Integration, Customer Satisfaction. Repurchase Intention, E-commerce,

Elevenia.co.id

1

CHAPTER I

INTRODUCTION

1.1 Background

The phenomenon of Online Commerce or Electronic Commerce (e-Commerce)

has affected various aspect of consumer‘s buying pattern. E-Commerce makes

customer feels easier in finding information, comparing price, enabling remote

transactions, and offering lower costs as it often has lower operational costs

(Khurana, 2017). These benefits somehow could not be found in traditional brick

and mortar store. Though the traditional store has its own advantages, the growth

of Online Commerce is still often being blamed for the failure of some brick and

mortar stores (Jetta, 2017).

The Retail Apocalypse as stated by Thompson (2017)shows that the biggest factor

of this failure is the Online Shopping behaviour. People just purchase more stuff

online than they had before. Furthermore, he added that mobile commerce has

shown tremendous growth from 2 to 20% since the year 2010 in U.S. Different

story occurs in China which is entitled by Forbes as ―the first mobile commerce

nation‖. China has gained more mobile commerce sales rather than the online

sales from personal desktop on 2016. A total of 66% of digital sales derived from

mobile on 2016 remarks a unique achievement for the mobile commerce in China

(Evans, 2017).

2

Despite U.S and China are still in number 1 and 2 in the rank of most attractive

online commerce market, the South East Asia market is expected to emerge and

hold $200 billion of digital sales by the year 2025 (Kinasih, 2016). According to a

report by Google in cooperation with Temasek ‘e-conomy SEA: Unlocking the

$200 billion digital opportunity in Southeast Asia’, Indonesia will be the largest

sales holder of $46 billion by 2025. The hike of middle class population, internet

users, and accretion of tier 2/3 cities are some critical factors in this growth

(Tegos, 2016). Indonesia will not only experience the online sales from PC but

also from mobile commerce as it has 65 million (26% of total citizens) active

smartphone users in 2016 ("Smartphone Rakyat Indonesia-Ristekdikti", 2017). In

total, Indonesia is expected to hold 52% online market share in South East Asia

by 2025 with its 132.000.000 people (51.8% from total population) with internet

access (Widiartanto, 2016) ("Indonesia to Take 52% Share of SE Asia E-

Commerce Market by 2025", 2016).

Indonesia‘s online market potential has also being noticed by big players of

commerce such as Alibaba and JD.com. The two players now dominated

Indonesia market through Lazada, Tokopedia, and JD.id (Indra, 2017). Besides

the three players, there are also some other local players such as Elevenia,

Blibli.com, etc. Each has different characteristics and some act as B2B, B2C, or

even C2C. All of these ecommerce players have come up with the mobile

application which costs are not cheap from the ground foundation, great planning,

and eminent talents during the scheming and technical skills (Mehra, 2014). The

cost for building mobile application could costs up to USD$ 7 billion in a year

according to data from Google (Pratama, 2016).

3

Reckoning the increase number of online commerce players and the cost of

building such mobile environment, it is critical to sustain in the competitive

market. One way to survive is how e-commerce could gain repetitive buyers.

There are some factors contributed to the re-purchase intention in online customer

behaviour such as e-word of mouth (Jalilvan & Samiei, 2012), trust (Ling, Chai,

& Piew, 2010), perceived usefulness and enjoyment (Chiu, Chang, Cheng, &

Fang, 2008), etc. Other factor considered as important for the repurchase intention

is satisfaction. While a few study proves that perceived channel integration of

online site and mobile commerce have strong influence to the repurchase

intention, the role of satisfaction to increase the repurchase intention has been

widely assessed in various study. Satisfaction has been addressed as the

antecedents of repurchase behaviour. The past purchase experience builds overall

customer satisfaction that is used on the intention of making repeat purchase.

Value obtained from past experience is very important in building satisfaction (H.

Li & Hong, 2013; Blut, 2016; Ding, Hu, & Sheng, 2011).

While satisfaction has been proven to positively influences the purchase intention,

the antecendents of satisfaction should also be analyzed for better understanding

in building purchase intention. One of the most important factors in building

satisfaction is E-commerce Service Quality (Mohamad, Salim & Ismail; 2015).

Most studies have analyzed that the website or online service quality positively

influences customer satisfaction (Sharma & Lijuan, 2015). Reckoning the trend

happened in Indonesia of the mobile commerce and online retailer site, the service

quality is not only scoping website but also to the mobile apps service quality,

especially since the cost of building it is not cheap (Yang et al., 2017). According

4

to a study conducted by (Yang et al., 2017) in China to 217 respondents of a

famous etailers, both online and mobile apps service quality positively influence

the customer satisfaction. Aside from service quality, this paper evaluates the role

of channel integration to the repurchase intention. A study conducted in China

involving 317 customers of famous e-retailers found that the integration among

these mobile and online retail has a positive relationship towards customer

satisfaction (Yang et al., 2017). The scope of integration addresses data

integration, consistency of information, integrated promotion, integrated product

and pricing, and integrated customer service (Frasquet & Miquel, 2017; Hyun-

Hwa & Kim, 2010; Yang et al , 2017; Song, Zhang, Chen, & Huang, 2009).

Researcher decided to choose Elevenia as the subject of this study due to its

declining month-to month website traffic and mobile apps users on 2017. On

November 2017, there are 9,300,000 visits occur to Elevenia while on January

2018, there is only 5,200,000 visits occur ("Elevenia.co.id Analytics - Market

Share Stats & Traffic Ranking", 2018). The decline of re-visit could means

the decline in repurchase intention due to a lot of factors such as less promotion,

bad e-service quality, etc. Similarly, in the mobile apps, there is a steep decline in

mobile apps users especially on the year 2018. Elevenia app usage rank on daily

basis is declining from 800,006 usage to 106,339 usages from 1 January to 5

February or 86% of base daily usage (elevenia- Jual Beli Online App Ranking and

Market Share Stats in Google Play Store., 2018). This also indicates less re-visir

of customers to the apps, which could led to decline in repurchase intention. There

is no evidence if channel integration among the two channels are important in

5

customers‘ perspective to drive their repurchase intention, subsequently, this

research is conducted to find out about it.

Hence, this research tries to identify does any influence occurs from Mobile Apps

service quality to customer satisfaction? Does any influence occurs from Website

Service Quality to Customer Satisfaction? As both Mobile Apps and Website

Service Quality represent the particular e-commerce service quality, researcher

tries to also seek does any influence occurs from the channel integration towards

the Customer Satisfaction? Also, does channel integration influence the Mobile

Apps Service Quality and Website Service Quality? Last, researcher tries to

answer the question: does there is any influence occurs from Customer

Satisfaction to the Repurchase Intention?

The objectives of this research are to assess the importance of service quality from

both mobile and online commerce to the repurchase intention through satisfaction.

The impact of channel integration to the repurchase intention through satisfaction

is also assessed in this paper.

1.2 Significance of the Study

This study gives insight for multi-channel retailers in Indonesia of the role carried

by the service quality of online and mobile commerce to the repurchase intention

through customers‘ satisfaction, and bring-on the channel integration as the new

assessed variable that not much being evaluated in previous study.

For students and researchers, this research provides insight of how website and

mobile commerce service quality together with the channel integration influence

6

repurchase intention through Indonesia‘s customer satisfaction. This insight

enriches the literature related with the digitalization of retail in Indonesia.

1.3 Limitation

This study only involved the millennials respondents age 18 – 45 years old due to

their massive contributions to current online market. The geographical boundary

is also set in which respondents come from various areas in Greater Jakarta as

they are also major contributors of online sales (Herlinda, 2017).

1.4 Organization of Skripsi

The skripsi is divided into five chapters. The first chapter gives the background of

the study consists of the problem identification, research questions, objectives and

its significance. Afterwards, a literature review from previous studies is presended

in chapter two, together with the explanation of each variables used in the study :

definitions, construct measurement, and factors which are influential to the

varable. The theoretical framework, hypotheses, and methodology used in the

research is explained on chapter three. Chapter four describes the result and

discussion based on the validity and reliability test, data distribution in descriptive

analysis, and inferential analysis, followed by discussion of it. Subsequently, the

final chapter gives conclusion of hypothesis testing and recommendation for

future study.

7

CHAPTER II

LITERATURE REVIEW

2.1 Repurchase Intention

2.1.1 Definition of Repurchase intention.

Repurchase intention behavior inclines to be more preferable than purchase

intention as it represents purchase continuation in the future (Mohlepour, Wong,

Pham, & Aulia, 2017). It is defined as personal assessment whether to repurchase

a particular product or service from the same company after considering current

situation and problem (Toni, Eberle, Larentis, & Milan, 2017). More specifically,

online repurchase intentions reflects the customer‘s personal likelihood to make a

repurchase behavior on specific ecommerce (Razak, Marimuthu, & Mamat,

2014).

2.1.2 Measurement of Repurchase Intention

This study measures ‗repurchase intention‘ with three constructs based on study

by Matute, Polo-Redondo, & Utrillas (2016) with three questions: (1) If I could, I

would like to continue using Elevenia.co.id to purchase products, (2) It is likely

that I will continue purchasing products from Elevenia.co.id in the future, (3) I

intend to continue purchasing products from Elevenia.co.id in the future.

2.1.3 Influencial factors of Repurchase Intention

Satisfaction has a positive influences to the repurchase intention according to a

study done by Lin & Lekhawipat (2014) to 204 online shoppers in China.

Similarly, the meta analysis study collecting various online service quality studies

8

in past 15 years (2000-2014) also indicates that online service quality influences

repurchase intention through satisfaction as the mediating role (Blut, Chowdhry,

Mittal, & Brock, 2015).

2.2 Satisfaction

2.2.1 Definition of Satisfaction

Kotler defines satisfaction as customer‘s positive feelings (pleasure) or negative

feelings (disappointment) towards certain products based on his/her expectation.

Expectation could be influenced by several factors: companies‘ promise, word of

mouth, etc. (Srivastava, 2011). Customer Satisfaction in online cum-mobile

environment is modelled as transaction specific satisfaction and cumulative

transaction by (Yang et al., 2017) to prevent misunderstanding and inadequate

explanation of behavioural responses. The transaction specific satisfaction reflects

the customer‘s assessment towards the service encounter at a specific point

whereas the cumulative satisfaction measure the satisfaction of overall purchase

experience, and beneficial in maintaining retail-buyer relationship. The

transaction specific satisfaction is important in measuring if there is any changes

of performance occurs and how customer might perceive and react towards it

while the cumulative satisfaction reflects the relationship of retailer and shopper

(Yang et al., 2017).

According to Urvashi Tandon, Ravi Kiran (2015), Customer Satisfaction has an

important role to nurturing old customer and acquainting new customers.

Customer Satisfaction is also acknowledged as an essential determinant for an e-

shopper to make a repurchase or not (Urvashi Tandon, Ravi Kiran, 2015).

Satisfaction is also seen as an affective condition related to emotional attributes

9

towards specific transaction experience, that describe how a retailer could meet

customer‘s past expectation (Kim, Xu, & Koh, 2004). Similarly, Frasquet &

Miquel (2017) on their research related to channel integration of online and

offline store highlight satisfaction as affective response of customer towards

his/her shopping experience. Hence this research paper defines Satisfaction as the

emotional attribute related with past shopping experience that plays a major role

in retaining old customers and bringing in new customers, while also reflects how

a retailer maintain their relationship with buyers.

2.2.2 Measurement of Customers Satisfaction

This study measures customer satisfaction using four constructs : (1) I like to

purchase products from Elevenia.co.id.(Chiu, Chang, Cheng, & Fang, 2009), (2) I

am pleased with the experience of purchasing products from Elevenia.co.id (Jun,

Yang, & Kim, 2004; O. Pappas, G. Pateli, N. Giannakos, & Chrissikopoulos,

2014), (3) I think purchasing products from Elevenia.co.id.is a good idea (Zboja

& Voorhees, 2006), and (4) Overall, I am satisfied with the experience of

purchasing products from Elevenia.co.id(San Martín & Camarero, 2009; Urvashi

Tandon, Ravi Kiran, 2015).

2.2.3 Influencial Factors of Customers Satisfaction

Yang et al., (2017) also did a study to 317 respondents of famous Chinese

ecommerce also found the same findings of how customer satisfaction being

influenced by online service quality. However, this study also found that the

channel integration among mobile and website service quality influences the

customer satisfaction as well. Furthermore, customer satisfaction is addressed as

vital in retaining customers as it drives repurchase intention according to a study

10

in China towards 204 online buyers (Lin & Lekhawipat, 2014). The same findings

occurs according to a study in Thailand, which specifically address customer

satisfaction towards pricing, website information, responsibility, assurance, and

empathy are positively influence the purchase intention (Jiradilok, Malisuwan,

Madan, & Sivaraks, 2014).

Ding, Hu, & Sheng (2011) conducted study with 311 undergraduate and graduate

students as the respondents in United States also found out that customer

satisfaction is influenced by online service quality, just like customer loyalty is

influenced by online service quality.

2.3 Perceived Channel Integration

2.3.1 Definition of Perceived Channel Integration

Channel integration is defined as all effort to manage various retail channels

which aim to provide customer a consistent shopping experience all across

reciprocal channels (Frasquet & Miquel, 2017). Similarly, Piotrowicz &

Cuthbertson (2014) defines channel integration as customer expectation of a

harmonious, consistent, amalgamated service and experience in every retail

channel. Customers would prefer to have seamless experience across channels:

traditional store, online, and mobile—based on their preferences and condition.

Channel Integration could also be defined as the synergy level of coordination

among firm‘s objectives, design, and transmission of its channels to provide

distinctive benefit to its customers (Cao & Li, 2015). As the mobile channels

emerged as one new ecommerce channel, the firm now should involve this

channel in the integration process.

11

While its impact of channel integration in offline and online environment has been

widely assessed, the impact of mobile & website integration in the solely

ecommerce platform has not been widely examined. In the context of this study,

retailers define perceived channel integration as the consistent customer‘s

experience related with the data integration, information consistency, pricing,

customer service, and promotion. The dimensions used were based on recent

study of online and mobile environment by Yang et al., (2017) combined with

some essential attributes of channel integration which also be founded in online

platform which are integrated branding and promotion (Görsch, 2002; Oh et al.,

2012), integrated product and pricing (Oh et al., 2012), and integrated customer

service (Oh et al., 2012),

2.3.2 Measurement of Perceived Channel Integration

There are five dimensions being used in this study based on research by Yang et

al., (2017) about channel integration between online & mobile service quality and

other study from Frasquet & Miquel (2017), Cao & Li (2015), Hyun-Hwa & Kim

(2010), Oh et al. (2012), and Bendoly, Blocher, Bretthauer, Krishnan, &

Venkataramanan (2005). The first dimension is ‗data integration‘ which is

measured by statement ―Elevenia.com effectively integrates data from its online

and mobile channels (Yang et al., 2017)‖. The second dimension is ‗information

consistency‘ which is measured with ―3. Elevenia.com pulls together

information that used to come from its online and mobile channels.(Yang et al.,

2017)‖. Thirdly, dimension ‗integrated promotion‘ is measured by the construct

―Elevenia.com align advertising and promotion across online and mobile channels

(Cao & Li, 2015; Frasquet & Miquel, 2017; Hyun-Hwa & Kim, 2010;Bendoly,

12

Blocher, Bretthauer, Krishnan, & Venkataramanan, 2005)‖. The next dimension is

‗integrated product and pricing‘ which is measured by construct ―Elevenia.co.id

has a consistent product prices in online and mobile channels (Oh et al.,

2012)(Frasquet & Miquel, 2017)(Hyun-Hwa & Kim, 2010)‖ and the last

dimension is ―integrated customer service‖ which is measured by ―Elevenia.com

provides an interactive access to customer service assistant in online and mobile

channels (Oh et al., 2012)‖.

2.3.3 Factors influenced by Perceived Channel Integration

The latest study conducted by Yang et al., (2017) to 317 customers of mobile and

website 360buy.com in China address the channel integration of mobile and

website, and how its impact on customer‘s satisfaction and purchase intention.

The study of 360buy.com by Yang et al., (2017) that defined the variable as level

of data integration, information consistency, and overall coherence of mobile and

website channels found that perceived integration contributed positive impact to

customer‘s satisfaction and purchase intention. The study of channel integration

was first done in the brick and mortar to the website. Study done by Pentina &

Hasty (2009) to 50 multichannel retailers in found that retailers with higher level

of inter-channel coordination will have higher online sales rather than those who

are not. The next study from Cao & Li (2015) to 91 publicly trade retail firms in

U.S reveals that the cross channel integration of online and offline channels

contributed to overall firm‘s sales growth. While the perceived channel

integration were accessed in 562 retail firms in Singapore by Oh et al. (2012)

contributed to the retailer‘s overall competence and performance. They also

suggest 28 items to comprehensively measure the integration consists of

13

promotion, information technology management, product and pricing, order

fulfilment, and customer service. Besides, their finding underlines the importance

of information system‘s competence in integrated data among channels.

2.4. Mobile and Website Service Quality

2.4.1 Definition of Online Service Quality

The concept of service quality was first popularized by Parasuraman (1985) as the

difference between the customer‘s expectations toward service quality and the

perceived service real performance. The theory usually called as SERVQUAL

measured by five dimensions: reliability, responsiveness, assurance, empathy, and

tangibility. As the industry of commerce expand to electronic commerce, the

model than being reinvented to be E-SERVQUAL which is defined as the level of

how a website provides an effective and efficient shopping experience,

transaction, and delivery of goods (Parasuraman, Zeithaml, & Malhotra, 2005).

Ever since, a lot of studies examined the proper dimensions to measure e-service

quality, which comply with all aspects involved on it. Li Tan and Xie (2002)

proposed the same dimensions as Parasuraman‘s model to assess a web based

service quality in overseas customers of e-commerce and found that the

dimensions and construct of service quality has to be modified. His hypotheses of

information quality and integration of digital & traditional communication

resulted in the high correlation of information quality to customer‘s satisfaction.

Integration of digital & traditional communication appears not so fit in the

statistics model, and tangibility as not much relevant in measuring e-service

quality(Y. N. Li, Tan, & Xie, 2002). New dimensions proposed information

quality and web assistance are proven correlated to customer satisfaction. This

14

concept aligned with findings of Blut, Chowdhry, Mittal, & Brock (2015) that

address four critical dimensions of e-service quality: website design (consist of

information quality, website aesthetics, purchase process, website convenience,

product selection, merchandise availability, price offerings, website

personalization, and system availability), fulfilment (timeliness of delivery, order

accuracy, delivery condition), customer service (service level and return), and

security/privacy. Using meta-analysis, Blut, Chowdhry, Mittal, & Brock (2015)

combined other studies from Parasuraman, Zeithaml, & Malhotra (2005) and

other researchers in gathering sixteen constructs in the study.

2.4.2 Definition of Mobile Service Quality

In the online-cum-mobile environment, e-service quality should be assessed from

both channels of mobile and desktop. The mobile channel covers mobile apps,

while the desktop offers solely online website (Fieldnation, 2016). In Indonesia,

mobile app is predicted to contributed higher revenue compared to desktop

website and mobile website in the year 2017 yet the desktop and mobile website

are also considered as important as they are predicted to contribute nearly 33%

and 30% of total e-commerce revenue (Vyas, 2017). Hence, e-service quality

should also measure the second channels of e-commerce which are the mobile

commerce channels. Combined together, online service quality and mobile service

quality could be defined as consumers‘ evaluations of reliability, promptness,

assurance, and personalisation of service quality in the online and mobile

shopping channels, successively (Yang et al., 2017).

Finally, this research defines online service quality as the overall customer‘s

evaluation of the website and mobile channels performance compared to their

15

initial expectations using underlying dimensions of reliability, responsiveness,

assurance, personalization (reinvented dimension of empathy), information

quality, system quality, purchase process, fulfilment, customer service, and

security.

2.4.3 Measurement of Online Service Quality

This study measures Online & Mobile Service Quality using 9 dimensions which

are combination of SERVQUAL dimensions by Parasuraman, Zeithaml, &

Malhotra (2005) and other study from Kim, Xu, & Koh (2004) and Blut, (2016).

Dimension ―tangibility‖ from SERVQUAL is not being used as it is not much

relevant with online service quality (Li et al., 2002). The first dimension used is

‗reliability‘ with construct ―The ecommerce desktop/mobile platform provides

dependable services (Yang et al., 2017). Dimension Reliability is defined as the

ability of e-mail systems and website to provide accurate information and perform

the promised service (Li et al., 2002). Secondly, dimension ‗responsiveness‘ is

measured with construct ―The ecommerce desktop/mobile platform provides

prompt services (Yang et al., 2017)‖. Thirdly, dimension ―assurance‖ is measured

with construct ―The ecommerce desktop/mobile platform provides professional

services (Yang et al., 2017)‖. The fourth dimension is ―empathy‖ which is

measured by the statement ―The ecommerce desktop/mobile platform addresses

my specific needs‖ (Kim et al., 2004). Fifth, dimension ―information quality‖ is

measured with construct ―The ecommerce desktop/mobile platform has

information relevant to my needs (Kim et al., 2004)‖. This dimension

―information quality‖ is an addition to original SERVQUAL as this dimension

specifically address attributes of information contained in E-mails or websites.

16

The sixth dimension is ―purchase process‖ which is measured with construct ―The

ecommerce desktop/mobile platform has no difficulties in payment process (Blut,

2016)‖. The seventh dimension is ‗customer service‘, measured by ―The

ecommerce desktop/mobile platform offers a customer good service (Blut,

2016)‖. The last dimension is security which is measured by ―I feel safe in my

transactions with the ecommerce desktop/mobile platform (Blut, 2016)‖

2.4.4 Factors affected by Online Service Quality

According to study by (Jun, Yang, & Kim, 2012) to 268 online buyers in USA,

online service quality positively influences customer satisfaction. In this study,

factors being assessed were reliability/prompt responses, access, ease of use,

attentiveness, security, and credibility. Similarly, study conducted by (Yang et al.,

2017) to 317 online buyers of famous etailers in China found that website service

quality contributed to transaction specific satisfaction and cumulative satisfaction.

More specifically, the study concluded that the mobile service quality contributed

greater impact to satisfaction compared to website service quality. This highlight

the importance for retailers to put consideration of the service quality provided by

its mobile commerce channels as it is important to customer‘s satisfaction.

Reliability, responsiveness, assurance, and personalization are the dimensions

being used by (Yang et al., 2017).

The last meta analysis study in USA also found that four dimensions of online

service quality: website design, fulfillment, customer service, and security has a

direct influence towards overall customer satisfaction (Blut, Chowdhry, Mittal, &

Brock, 2015).

17

2.5. Research Gap

Previous study has analyzed the role of channel integration of mobile & online

service quality to repurchase intention using the mediating role of satisfaction

(Yang et al., 2017). However, the research was done in China, using solely 4

dimensions of service quality: reliability, responsiveness, assurance, and

personalization. Yang et al., (2017) also divides the ‗customer satisfaction‘ to two

sub-dimensions: ‗transaction specific satisfaction‘ and ‗overall satisfaction‘ while

in this study, ‗customer satisfaction‘ is not divided to two sub-dimensions but

only as overall. Yang et al., (2017) also used structural equation modelling in their

research, with object of 360buy.com in China. Hence, the first gaps occurs from

this research are the dimensions used in measuring service quality and customer

satisfaction (Yang et al., 2017). The Chinese ecommerce market is considered as

more mature than Indonesia on 2017, Indonesia is having 1,8% of retail

transaction happened online while China has 9,8% of retail transaction happened

online (Iskandar, 2018). In the mobile transaction, Indonesia is having 33% of

total online transaction happened from smartphone on 2017, while China already

reached 66% of transaction happened online (Evans M. , 2017). Hence, it is likely

that Indonesia will also reach China‘s position 5-8 years from now.

Other study has also measured the role of channel integration but mostly in the

case of online and offline store integration (Frasquet & Miquel, 2017; Cao & Li,

2015; ;Bendoly et al., 2005; Hyun-Hwa & Kim, 2010; Oh et al., 2012). Frasquet

& Miquel (2017) analyze the role of channel integration across 761 multichannel

retailers in apparel sectors through questionnaires developed from previous study.

The MCI (Multi Channel Integration) appears to have two dimensions: reciprocity

18

and coordination. Study was done through EQS 6.1 program. In addition, the

main goal of study done by Frasquet & Miquel (2017) is to see the impact of MCI

to customer loyalty through mediating role of customer satisfaction. Hence, the

next difference is in the dimension used in assessing the channel integration, the

subject of the study which is apparel retailers in Spain and United Kingdom, also

the object of the study which is multi channel integration in context of online and

offline retailer and its impact to customer loyalty.

Other study done by Cao & Li (2015) also focus on physical and online store

cross channel integration with its impact to sales growth, using grounded theory

and panel regression approach. Bendoly et al., (2005) decided to focus on

customer retention which is aligned with current study of repurchase intention,

but still in context of offline and online retail. Also the study from Oh et al.,

(2012) focus on the channel integration through IT in integrating retailers‘

activities and environmental dynamism become the moderating variable to

effectiveness of firms‘ performance in 172 firms in Singapore. Hence, the gap

occurs between current research and research done by Cao & Li (2015) is the

subject of the study which is 71 publicly U.S retail firms, the object of the study

which is the cross channel integration through IT and its impact to sales growth.

To conclude, there are some research gaps from current study to previous studies.

First, the most distinct approach is that this research‘s focus on mobile application

and website service quality in defining the channel integration, not the physical

and the online store. This might be similar with research from Yang et al (2017)

but using different dimensions with previous study or could be proclaimed as

theoretical gap. While Yang et al., (2017) only use the reliability, responsiveness,

19

assurance, and personalization based on Parasuraman et al. (2005) without

―tangible‖, current study expand the dimensions used based on previous e-service

quality study from (Blut, 2016; Kim et al., 2004;Li et al., 2002) which are

―fulfillment‖, ―customer service‖, and ―security‖ as they are important elements

related with service quality of online retailer. The second difference is in

mediating variable ―customer satisfaction‖ which is measured as four items of

overall satisfaction based on study by (O. Pappas et al., 2014; Urvashi Tandon,

Ravi Kiran, 2015) rather than ―transaction specific satisfaction‖ and ―overall

satisfaction‖ in (Yang et al., 2017). Current study also focus on ―repurchase

intention‖ through mediating role of ―customer satisfaction‖, while previous study

focus on sales growth (Cao & Li, 2015), purchase decision (Bendoly et al., 2005),

firm‘s overall performance (Oh et al., 2012), and customer loyalty (Frasquet &

Miquel, 2017). The next difference is in the methodology used which is Structural

Equation Modelling through Amos, unlike previous study which use EQS 6.1

(Frasquet & Miquel, 2017) and grounded theory and panel regression (Cao & Li,

2015). Last, current study analyze Indonesia market perspective using

Elevenia.co.id as the object reckoning it is one of the most famous ecommerce in

Indonesia with declining number of monthly traffic visits and has been sold to

other company due to tight competition issue (Wardani, 2017; "Elevenia.co.id

December 2017 Overview", 2017) or could be proclaimed as an empirical gap.

20

CHAPTER III

RESEARCH METHOD

This research is conducted through a quantitative method to analyze bigger

amount of samples. Measurement items were adapted from past study with pre-

test perception test. This is a conclusive research which gives insight of cause and

effect relationship in measuring the effect of independent variable to the

dependent variable (research-methodology.net).

3.2 Theoretical Framework

Figure 3.1 Theoretical Framework

3.3 Hypothesis

H1: Website Service Quality influences Customer Satisfaction

H2: Channel Integration influences Customer Satisfaction

H3: Mobile Service Quality influences Customer Satisfaction

H4: Channel Integration influences Website Service Quality

H5: Channel Integration influences Mobile Service Quality

H6: Customer Satisfaction influences Repurchase Intention

21

3.4 Operational definitions of variables

Table 3.1 Instruments of Questionnaire

Channel Integration is the exogenous which influences Online Service Quality,

Mobile Service Quality, and Customer Satisfaction is the mediating variable

towards Purchase Intention. Online Service Quality and Mobile Service Quality

serve as endogenous towards Channel Integration, while it also influences the

Customer Satisfaction. Customer Satisfaction is the mediating variable to the

Repurchase Intention.

3.5 Instrument

The research instrument used in this study is online questionnaire using 7 points

of Likert scale. Respondents were asked to describe their opinion regarding

particular statements from very disagree (point 1) until very agree (point 7). The

interpretation of each scale: (1) Strongly Disagree, (2) Disagree, (3) Somewhat

Disagree, (4) Undecided, (5) Somewhat Agree, (6) Agree, (7) strongly Agree

(Beshai, Branco, Dobson, & Dobson, 2013). Hence, 7 points Likert Scale measure

their level of agreement towards questionnaire statement (Vagias, 2006). A

Questionnaire is presented in both English and Indonesian language using Google

Form, targeting everyone around 18-45 years old, and have experienced purchase

transaction in Elevenia.co.id.

22

3.6 Sampling

Researcher choose respondents between age 18-45 years old due to its major

contribution to ecommerce sales(―2015, Belanja Online Tumbuh Dua Kali Lipat –

VIVA,‖ 2015). Researcher uses a non-probability sampling technique, under

purposive sampling. The criteria defines only respondents who were in the age

demography between 18 – 45 years old who live in Greater Jakarta area with

previous purchase experience with Elevenia Website (Desktop) and Mobile Apps

who can submit full responses of the questionnaire. In total, questionnaires were

distributed to 300 people, but resulted in 171 acceptable responds according to

purposive sampling. The amount of 300 respondents were chosen to get the

proper sample size for SEM of minimum 1. The sample size is considered

acceptable for conducting Structural Equation Modelling (Wang, 2012).

Researcher target those who have made transactions in Elevenia.co.id through its

followers of social media account.

3.7 Data Gathering

Data collection method

An online survey was spreaded through social media, email, and messenger

application. The questionnaires were spreaded to 300 people with total 171 valid

responses within 7 weeks from 16 October – 5 December 2017.

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3.8 Data Analysis

1. Validity

Construct validity is used to measure if the statements in the questionnaires are

valid and if the respondents have similar understanding of the questionnaires

(William Zikmund, 2009). The validity is measured under 5 criteria:

1. Barlett test significant must have bigger value than 0.05.

2. MSA or Anti Image value must have bigger value than 0.5.

3. Total variance explained must have bigger value than 60%.

4. Rotated component matrix value must have bigger value than 0.55.

5. Measure of Sampling Adequate (known as KMO in SPSS) must have

bigger value than 0.5.

6. Communalities must have bigger value than 0.5.

2. Reliability

Reliability test is used to measure the consistency of respondents‘ answers

throughout the instruments (Heffner, 2014).The reliability is tested using

Cronbach coefficient alpha, typically used in testing multipoint-scaled items like

likert scale. The Cronbach‘s coefficient alpha must be in the range of 0.6 to be

acknowledged as reliable (Hair, Black, Babin, & Anderson, 2010).

3. Descriptive Analysis

The descriptive analysis shows the summary of data distribution represented in

percentage from each question statements in the questionnaire (sydney.edu.au,

2017). Data is presented in frequency table and description summary in chapter

24

IV. Researcher describes the majority of respondents‘ answer and draws a

conclusion based on it. However, this conclusion still further needs to be accessed

altogether in inferential analysis, to draw a final conclusion of the research. This

analysis helps researcher in gaining beneficial information based on the data

gathered.

4 Inferential Analysis: Structural Equation Modelling

SPSS Amos 24th version is used in hypothesis testing. The goodness of fit among

all dimensions in a variable is tested to understand the relationship among all

variables under Structural Equation Modelling (SEM). SEM initially is a

combination of factor analysis to test the validity/reliability and the multiple

regression in hypothesis testing. Hypothesis testing must be done after model is

indicated as fit.There are some criterias to indicates the Model Fit of data in SEM

which consists of Goodness of Fit (GFI and AGFI), CMIN, Model Comparison

(TLI, NFI, and CFI), Root Mean Square (RMSEA) (Schumacker & Lomax,

2010).

a. Model Fit

Model Fit is used to test whether the sample variance-covariance fit with the

Structural Equation Model proposed. The common criteria in Model Fit are Chi

Square, Goodness of Fit (GFI), the adjusted goodness-of-fit index (AGFI), and the

root-mean-square residual index (RMSEA)

(1) Goodness of fit indices (GFI)

GFI is measure how the data is fit enough with result we expect from

actual population (Glen, 2014). The value of GFI should be in the range of

25

0 - 1. Value which is above 0,9 or closer to 1 is considered as better result,

indicates that the model has a good suitability (Hendry, 2013).

(2) Adjusted Goodness of Fit Index (AGFI)

AGFI comes from the development of GFI, this criteria has been adapted

with ratio from degree of freedom (Ghozali & Fuad, 2008). AGFI will be

accepted only if it has greater value than 0.90 (Hendry, 2013).

(3) Chi- Square

Significance values are expected from this test is ≥ 0.05 to indicate that

the null hypothesis is accepted (Hendry, 2013). Chi-Square measures

degrees of freedom between the observed and inserted variance-covariance

matrices.

(4) CMIN/DF

The CMIN/DF value is accepted only when it passes criteria of in range of

2 until 5 (Murhadi & Sem, n.d.).

(5) Root mean square error of approximation (RMSEA)

The RMSEA value seeks to fix the tendency of chi-square value to rejecct

big amount of samples. Value of RMSEA of 0.05 <RMSEA <0.08 is

considered as having goodness of fit (Hendry, 2013).

26

Other than the previous Model Fit measurement, there are three other indices

to compare the proposed model with the independence (null) model: IFI, TLI,

and CFI

(1) Comparative Fit Index (CFI)

CFI value represents the fit of the target model to the independent variable

wherein both are assumed uncorrelated (Moss, 2016). The value of CFI

should be >0.90.

(2) Incremental fit index (IFI)

Values which is greater than 0.90 are acceptable. IFI compares the

suitability of incremental model tested with the hypothesis model.

(3) Tucker Lewis index (TLI)

Just like IFI, TLI values which is greater than 0.95 are acceptable. TLI

compares the null model against the new proposed model (Schumacker &

Lomax, 2010).

c. Squared Multiple Correlations – R2

The result of squared multiple correlations in Amos Output described the total

variance of dependent variable explained by the independent variable in this

model (―What‘s a good value for R-squared?,‖ 2017). The value of R2

is in the

range of 0-1, and the value which is closer to 1 is better since it describes that the

model explained higher percentage of variance.

27

d. Mediation Analysis - Direct & Indirect Testing

The direct effect describes the part of the effect which is not mediated by the

predicted mediating variable in the model while the indirect effect describes the

part of the effect which is mediated by the predicted variable in the model

(Vansteelandt, n.d.). The result of this mediation analysis is presented in the

Direct Indirect result on chapter IV.

e. Hypothesis Testing

Afterwards, the hypothesis testing is conducted. There are three values interpreted

in this analysis which are ‗estimates‘, ‗critical ratio‘ (C.R), and p value.

‗Estimates‘ shows the relationship of variables. Critical ratio (C.R) also known as

T-Test refers to the strength of the relationship, accepted when it is greater than

absolute value of 1,96. The P-Value tests the significance of the hypotheses which

is accepted when its value is greater than 0, 05. All of these values are found in

―Regression Weight‖ table on Table 4.8 in Appendices.

28

CHAPTER IV

RESULT AND DISCUSSION

4.1 Validity and Reliability

Appendix 4a – 4i Validity & Reliability Result

The measurement items of each variables were gathered from past studies related

with dimensions used. A pretest was done by asking panel of persons to explain

their perception about the questionnaire, to measure the validity of content being

used. The panel of persons chosen in this study consists of 6 persons who are

familiar with ecommerce repurchase transaction, and 3 of them were also

practicioners of e-commerce (Omnichannel Sales Manager, Brand Commerce of

an Ecommerce, and Regional Omnichannel Project Manager). This is aligned with

concept of pretest to measure validity of content (Zikmund W. G., 2002).

The validity is measured using construct validity. During the validity test, there

are five measurement items deleted due to its invalid result in Rotated Component

Matrix. Items deleted were related with assurance (WAS3), purchase process or

fulfilment (WPP6), customer service (WCS7), and security (WSE8) in Website

Service Quality. One more item deleted is related with integrated customer

service (CIS5) in Channel Integration. After the five invalid items deleted, the

data was proven valid with KMO & Barlett test significant value 0,000 or lower

than 0.05 as the prerequisite. All MSA or Anti Image value is ranging in 0.925 –

29

0.970 which is higher than minimum value of 0.50. The total variance explained

was 82,129% (greater than 60%), and all Rotated Component Matrix are greater

than 0.52.

The reliability test was done using Cronbach Alpha which should be greater than

0.6. Variable Website Service Quality has 0.903 as the value of Cronbach Alpha,

followed by Mobile Service Quality with value of 0.958, Channel Integration with

value of 0.907, Customer Satisfaction with value of 0.946, and repurchase

intention with value of 0.945. Hence, all variables are proven reliable.

4.2 Respondents Profile

In total, there are 246 respondents who filled in the online questionnaires.

However, there are only 171 valid responses based on the purposive sampling‘s

criteria. These respondents are those who have made purchase in Elevenia.co.id

Mobile and Desktop App, and suit the age criteria. According to (Fan et al., 2016)

and (Tabachnick, Fidell, & Osterlind, 2001), the sample size of 100 – 200 is

permissible for Structural Equation Modelling.

Table 4.2 Respondents by Age Demography

Majority of these respondents were 21 – 30 years old (53%), followed by 35%

respondents in the age of 18-20 years old, 7% in the age of 31-40 years old, and

5% in the age of 41 – 45 years old.

30

Table 4.3 Respondents by Average Value of Transaction

In the average value of transaction, 61% of respondents usually have average

value of transaction between Rp 100,000 – Rp 500,000, followed by 23% who

have average value of transaction below Rp 100,000, and 7% who have among Rp

500,000 – Rp 1,000,000 average value of transaction, and 4% and 3% who have

average value of transaction in Rp 1,000,000 – Rp 2,000,000 and above Rp

2,000,000.

4.3 Descriptive Analysis

4.3.1 Website Service Quality

(1) Reliability - Website Elevenia.co.id provides dependable services

Table 4.4 Website Service Quality Data Summary

There are 76% respondents agree with the statement, with majority of them is in

scale number 4 ―Somewhat Agree‖ (36%), followed by ―Agree‖ (26%), and

―Strongly Agree ―(14%). While on the opposite judgment, there are only 6% who

disagree with the statement, and 16% choose ―Undecided‖. Hence, the reliability

of Elevenia.co.id website is assessed as quite dependable based on customers‘

perspective since 76% of them agree with the statement.

(2) Responsiveness - Website Elevenia.co.id provides prompt services

31


There are 75% respondents who are in ―Agree‖ section with 33% choose

―Somewhat Agree‖, 29% choose ―Agree‖, and 13% choose ―Strongly Agree‖.

Hence, leaving 8% of respondents who disagree, and 17% choose ―Undecided‖.

Most customers (75%) assessed the service quality of website Elevenia.co.id has

been prompt and responsive, and only 24% who are disagree and undecided

towards the statement.

(3) Assurance - Website Elevenia.co.id provides professional services


There are 80% of respondents who choose agree with breakdown of ―34%‖

choose ―Somewhat Agree‖, 30% choose ―Agree‖, and 15% choose ―Strongly

Agree; whereas there are 8% respondents who choose disagree and 12%

―Undecided‖. Hence, most of customers (80%) agree that the assurance as

represented in website Elevenia.co.id provides professional services.

(4) Personalization- Website Elevenia.co.id addresses my specific needs


There are 65% respondents who choose agree with 24% in ―Somewhat Agree‖,

30% in ―Agree‖ and 12% in ―Strongly Agree. It leaves 12% customers who are

disagree and 22% undecided. Hence, there are still majority of customers agree

that website Elevenia.co.id could personalize its services by addressing

customers‘ specific needs.

(5) Information Quality - Website Elevenia.co.id has relevant information

regarding product

32


There are 68% of respondents agree with the statement. Most of them choose

―Somewhat Agree‖ (26%), followed by ―Agree‖ (27%), and ―Strongly Agree‖

(15%). The rest of them choose disagree (13%) and undecided (19%). Hence, still

majority of customers represented by 68% of them agree that the information

quality of website Elevenia.co.id is relevant.

(6) Fulfilment- Website Elevenia.co.id has no difficulties in payment process


Most of the respondents agree with the statement (73%). 25% of them choose


While there are 9% disagree with the statement and 18% undecided. Hence, still

majority of customers (73%) agree that there is no difficulties in website

Elevenia.co.id payment process.

(7) Customer Service - The ecommerce website offers a customer service


Most of the respondents (77%) agree with the statement with 33% choose

―Somewhat Agree‖, 30% choose ―Agree‖, and 15% choose ―Strongly Agree‖,

whereas there are 8% who disagree with the statement and 15% undecided.

Hence, majority of customers (77%) agree or aware that website Elevenia.co.id

provides a customer service.

(8) Security - I feel safe in my transactions with the ecommerce website platform


33

There are 71% of respondents choose agree with 25% in ―Somewhat Disagree‖,

There are 25% customers in ―Somewhat Agree‖, 29% of customers ―Agree‖ with

the statement and 16% in strongly agree. While there are 10% who are disagree

and 19% undecided. Hence, there are majority of 70% customers agree that they

feel safe with their transactions in website Elevenia.co.id.

4.3.2 Mobile Service Quality

(1) Reliability - Mobile Elevenia.co.id provides dependable services

Table 4.5 Mobile Service Quality Data Summary

There are 72% respondents agree with the statement, with majority of them is in

scale number 4 ―Agree‖ (36%), followed by ― Somewhat Agree‖ (26%), and

―Strongly Agree ―(11%). While on the opposite judgment, there are only 8% who

disagree with the statement, and 20% choose ―Undecided‖. Hence, majority of

customers 72% agree with statement that the mobile apps of Elevenia.co.id

provides a dependable service.

(2) Responsiveness - Mobile Elevenia.co.id provides prompt services


There are 75% respondents who are in ―Agree‖ section with 32% choose


Hence, leaving 9% of respondents who disagree, and 16% choose ―Undecided‖.

The Majority 75% of customers still agree with the statement that mobile apps of

Elevenia.co.id provides prompt and responsive service to customers.

(3) Assurance – Mobile Elevenia.co.id provides professional services

34


There are 74% of respondents who choose agree with breakdown of ―35%‖

choose ―Agree‖, 27% choose ― Somewhat Agree‖, and 12% choose ―Strongly

Agree; whereas there are 8% respondents who choose disagree and 18%

―Undecided‖. Hence, majority 74% of customers agree with professionalism

services provided by Mobile Apps of Elevenia.co.id.

(4) Personalization- Mobile Elevenia.co.id addresses my specific needs


There are 71% respondents who choose agree with 30% in ―Agree‖, 29% in

―Somewhat Agree‖ and 12% in ―Strongly Agree. It leaves 11% customers who

are disagree and 18% undecided. Hence, majority of 71% customers still agree

with statement that mobile Elevenia.co.id personalized its services by addressing

customers specific needs.

(5) Information Quality - Mobile Elevenia.co.id has relevant information

regarding product


There are 75% of respondents agree with the statement. Most of them choose

―Somewhat Agree‖ (27%), followed by ―Agree‖ (18%), and ―Strongly Agree‖

(12%). The rest of them choose disagree (7%) and undecided (18%). Hence, most

of customers (75%) agree that the product information in mobile Elevenia.co.id is

relevant enough.

35

(6) Fulfilment- Mobile Elevenia.co.id has no difficulties in payment process


Most of the respondents agree with the statement (72%). 27% of them choose


While there are 9% disagree with the statement and 19% undecided. Hence,

majority (72%) of customers agree that there is no difficulties in the payment

process of Mobile Elevenia.co.id.

(7) Customer Service - The ecommerce mobile offers a customer service


Most of the respondents (70%) agree with the statement with 27% choose

―Somewhat Agree‖, 27% choose ―Agree‖, and 15% choose ―Strongly Agree‖,

whereas there are 9% who disagree with the statement and 21% undecided.

Hence, majority 70% of customers agree that there is customer service provided

in Mobile Elevenia.co.id.

(8) Security - I feel safe in my transactions with the ecommerce mobile platform


There are 74% of respondents choose agree with 32% in ―Somewhat Disagree‖,

30% in ―Agree‖, and 13% in strongly agree, while there are 6% who are disagree

and 19% undecided. Hence, majority 74% of customers feel safe in their

transaction in the mobile platform of Elevenia.co.id.

36

4.3.3 Channel Integration

(1) Elevenia.co.id effectively integrates data from its website and mobile apps

Table 4.6 Channel Integration Data Summary

As shown on Table 4.5, most of the respondents choose agree with 36% in

―Agree‖, 26% in ―Somewhat Agree‖, and 11% in ―Strongly Agree‖. There are 8%

of respondents who disagree and 19% undecided. Hence, 73% of customers agree

that the integration of data from website and mobile apps in Elevenia.co.id is

effective.

(2) Elevenia.co.id pulls together information that used to come from its website

and mobile channels


Table 4.5 shows that 76% of respondents agree with the statement with 42%

choose ―Somewhat Agree‖, 27% choose ―Agree‖, and 7% choose ―Strongly

Agree‖, while there are 6% who are disagree and 18% undecided. Hence, majority

of customers agree that Elevenia.co.id pulls together data from both website and

mobile channels.

(3) Elevenia.co.id align advertising and promotion across online and mobile

channels


There are 74% of respondents choose agree with 33% in ―Agree‖, 26% in

―Somewhat Agree‖, and 15% in ―Strongly Agree‖. While there are 8% who are

disagree with the statement and 15% undecided. Hence, majority 74% of

37

customers agree about the integration across channels promotion in

Elevenia.co.id.

(4) Elevenia.co.id has a consistent product prices in website and mobile apps


There are 77% of respondents who choose agree, with 32% in ―Somewhat

Agree‖, 29% in ―Agree‖, and 16% choose ―Strongly Agree‖. Hence leaving 8%

respondents who are disagree and 15% undecided. Majority 77% of customers

agree about the consistency of product‘s prices across website and mobile

channels.

(5) Elevenia.co.id provides an interactive access to customer service assistant in

website and mobile channels.


As shown in Table 4.5, most of respondents choose agree with 26% in

―Somewhat Agree‖, 26% in ―Agree‖, and 19% in ―Strongly Agree‖. While there

are 8% who choose disagree with the statement and 21% undecided. Hence,

majority 71% of customers agree that there is consistent customer service

assistant in its website and mobile channels.

4.3.4 Customer Satisfaction

(1) I like to purchase products from Elevenia.co.id

Table 4.7 Customer Satisfaction Data Summary

38

In the customer satisfaction, the number of respondents who choose agree towards

the statement are generally decrease compared with previous variables. There are

64% of respondents agree with breakdown of 27% who choose ―Agree‖, 26%

who choose ―Somewhat Agree‖, and 10% who choose ―Strongly Agree‖. While

there are 14% who choose disagree and 22% undecided. Hence, majority 64% of

customers agree that they like to purchase products in Elevenia.co.id.

(2) I am pleased with the experience of purchasing products from Elevenia.co.id


There are 70% of respondents agree with breakdown of 34% who choose

―Somewhat Agree‖, 22% who choose ―Agree‖, and 15% who choose ―Strongly

Agree‖. While there are 11% who choose disagree and 19% undecided. Hence,

majority 70% of customers agree that their previous purchase experience in

Elevenia.co.id is pleasing for them.

(3) I think purchasing products from Elevenia.co.id.is a good idea


In this third statement of customer satisfaction, 68% of respondents agree with the

statement while there are 9% who are disagree, and 23% undecided. Hence,

majority 68% of customers agree that it is a good idea to purchase product from

Elevenia.co.id.

(4) Overall, I am satisfied with the experience of purchasing products from

Elevenia.co.id


39

In this last statement of customer satisfaction, there are 71% of respondents agree

with the statement with majority of 32% in ―Somewhat Agree‖, 24% in ―Agree‖,

and 15% in ―Strongly Agree‖. While there are 9% of respondents disagree with

the statements and 19% undecided. Hence, most of customers (71%) satisfied

with their purchase experience in Elevenia.co.id.

4.3.5 Repurchase Intention

(1) If I could, I would like to continue using Elevenia.co.id to purchase products

Table 4.8 Repurchase Intention Data Summary

The first statement of repurchase intention indicates 67% of respondents agree

with breakdown of 29% in ―Somewhat Agree‖, 21% in ―Agree‖, and 16% in

―Strongly Agree‖. While in the opposite judgment there are 15% of respondents

who are disagree and 19% undecided. Hence, most of customers (67%) would like

to continue purchase product from Elevenia.co.id.

(6) It is likely that I will continue purchasing products from Elevenia.co.id in the

future


The second statement of repurchase intention shows that there are 61% of

respondents agree with breakdown of 26% in ―Somewhat Agree‖, 25% in

―Agree‖, and 9% in ―Strongly Agree‖. While there are 18% of respondents

disagree and 22% undecided towards the statement.

(4) I intend to continue purchasing products from Elevenia.co.id in the future


40

The last statement has the lessen number of respondents who choose agree though

it is still majority (59%) with breakdown of 23% in ―Somewhat Agree‖, 29% in

―Agree‖, and 12% in ―Strongly Agree‖. Hence there are 19% of respondents who

are disagree and 22% undecided towards the statement. Majority 59% of

customers still agree to do repurchase in Elevenia.co.id.

4.4 Inferential Analysis

4.4.1 Model Fit

Appendix 4j Model Fit Summary

Using structural equation modelling, the inferential analysis is conducted through

IBM SPSS Amos 22. Figure 4.3 shows the model in Amos testing which involves

the 5 variables: Website Service Quality (WSQ), Mobile Service Quality (MSQ),

Channel Integration (CI), Customer Satisfaction (SAT), and Repurchase Intention

(RPI). Before Hypothesis testing is conducted, the model fit tests is conducted to

make sure that variance-covariance of the sample is fit with the Structural

Equation Model proposed. Altogether, the model passes four out of seven criteria

of Model Fit and Model Comparison. The CMIN Value shows number of 2,042

which passes criteria of greater or equal to 0,05 ( ). Also the result of Chi-

Square shows value of P = 0,000 which passes the requirement. The value of IFI

(0,946) and CFI (0,946) are accepted as they are greater than minimum value of

0.9. The RMSEA (Root Mean Square Error of Approximation) also shows value

of 0,078 which is acceptable since the criteria is (0,05 < RMSEA < 0,08). There

are some criterion which are not accepted such as GFI (0.816), AGFI (0.774), and

41

TLI (0.939) which is lower than the acceptable values (0.9 for GFI and AGFI and

0.95 for TLI). However, the model is still considered as fit as it passes four

criterion out of seven criterion.

4.4.2 Square Multiple Correlation- R2

Appendix 4k Squared Multiple Correlation

Appendix 4k describes the squared multiple correlation from each variable. It

represents how much variance from a dependent variable can be explained by the

independent variable which is 1 - the unexplained variance. The value of squared

multiple correlation range from 0-1, the closer it is to 1, the better the result is.

The result shows that the squared multiple correlation of Mobile Service Quality

is 79.2% which means that there are 79.2% of the variance in Mobile Service

Quality can be explained by the independent variable in this study which is

Channel Integration. While the rest 20.8% of Mobile Service Quality variance

cannot be explained by the independent variable, must be explained from other

factors.

The Website Service Quality has 76.7% variable explained from its predictors,

leaving 23,3% variance explained from other factors. The customer satisfaction

has 74.6% variance explained from its predictors (mobile service quality, website

service quality, and channel integration) while the rest 25.4% should be explained

by other factors not in this study. Last, the variable of Repurchase Intention has

42

68.9% of variance explained in this study, leaving the rest 31.1% unexplained.

Hypothesis 1: Website Service Quality influences Customer Satisfaction

4.4.3 Mediation Analysis – Direct –Indirect Effect

Appendix 4l Direct and Indirect Effect Table

The result of direct effect of Channel Integration on Mobile Service Quality is 0,869.

This is in addition to any indirect effect that Channel Integration may have on Mobile

Service Quality. Whereas direct effect of Channel Integration to Website Service Quality

is 0,852. This is interpreted as whenever the Channel Integration goes up by 1, the

Website Service Quality goes up by 0,852 while the Mobile Service Quality goes up by

0,869 in addition to any indirect effect that may occurs.

The Website Service Quality shows a direct effect to customer satisfaction by 0,443,

while it has no direct effect to other variables. Customer Satisfaction only has a direct

effect to repurchase intention by 0,940 which is the biggest among all direct effect. It has

no effect towards other variables. Last, repurchase intention as the Z variable does not

have any direct effect to other variables

Moving on to the indirect effects, channel integration shows indirect (mediated) effect on

Customer Satisfaction by 0,534, which means the mediating role either website service

quality and mobile service quality could mediate the effect of Channel Integration to

Customer Satisfaction. Channel Integration also has an indirect effect on Repurchase

43

Intention by 0,843. This means that the mediating role of Customer Satisfaction could

mediate the effect of Channel Integration to repurchase intention.

The Mobile Service Quality has indirect effect of 0,170 to Repurchase Intention which

means it is mediated by the Customer Satisfaction. Also, Website Service Quality has

indirect effect to Repurchase intention by 0,416 which is also mediated by the Customer

Satisfaction.

4.4.4 Hypothesis Testing

(1) Hypothesis 1: Website Service Quality influences Customer Satisfaction

Appendix 4m Regression Weight

The ‗Estimates‘ value shows 0.443 which interpreted as whenever Website

Service Quality increase by 1, the customer satisfaction will increase by 0.443.

The C.R Value shows number of 3,356 which is accepted and the p-value is

proven significance (***). Hence, the first hypothesis is proven accepted.

(2) Hypothesis 2: Channel Integration influences Customer Satisfaction


The second hypothesis is proven not accepted, described by value of C.R is 1.92

which is lower than requirement of 1.96. The p-value also shows not significant

(0.55). Though the estimates value shows number of 0.33, the second hypothesis

not accepted because the C.R and P-Value are not suitable with the acceptance

criteria.

44

(3) Hypothesis 3: Mobile Service Quality influences Customer Satisfaction


Similar to the second hypothesis, the third hypothesis is also not accepted since

the C.R value of it is 1.377 (below the minimum value of 1.96). The P-Value is

also not significant (0.169).

(4) Hypothesis 4: Channel Integration influences Website Service Quality


The fourth hypothesis is accepted with estimates value of 0.852 which is

interpreted as whenever the Channel Integration goes up by 1, the value of

Website Service Quality will increase by 0.852. The p-value is accepted (***) and

the C.R value is 13.786 which is far greater than requirement of 1.96.

(5) Hypothesis 5: Channel Integration influences Mobile Service Quality


The fifth hypothesis is also accepted with ‗estimates‘ value of 0.896, C.R value of

13.875, and p-value which is significance. The ‗estimates‘ is interpreted as

whenever the Channel Integration increase by 1, the mobile service quality will

increase by 0,896.

(6) Hypothesis 6: Customer Satisfaction influences Repurchase Intention


The sixth hypothesis is also accepted with ‗estimates‘ value of 0.940 which is

interpreted as whenever the Customer Satisfaction value increase by 1, the value

of Repurchase Intention will increase by 0,94. The C.R value shows number of

45

12,725 which is far greater than minimum requirement of 1.96 with p-value which

shows significance (***).

4.5 Discussion

This study seeks to enrich the literature of how the mobile service quality

influences the customer satisfaction, altogether with the widely studied website

service quality. The mobile service quality found in the famous ecommerce

mobile apps has been addressed as important based on study by (Yang et al.,

2017) in China using 360buy.com as the research object. However, this study

found that the Mobile Service Quality is found not significance or having no

relationship with customer satisfaction. Though this is contrary towards previous

study, there is some logical explanations behind as the desktop website is still the

most favorable in Indonesian customers‘ perspective in terms of online shopping

(Agung, 2017; Elfira, 2017). Though data recorded that Indonesia is the fastest

growing mobile commerce country, this big data might be irrelevant in context of

Elevenia.co.id because it recorded the success story of Transportation Service

Apps such as Go-Jek, Uber, Grab mobile apps too which are very dominant in

Indonesia market (Nylander, 2017).

While there is no positive influence of mobile service quality to customer

satisfaction, there is a positive influence of website service quality to customer

satisfaction. This result is suitable with similar previous studies from Lee & Lin

(2005), Blut et al., (2015), Collier & Bienstock (2006), (Ding et al., 2011).

Altogether, each dimension in website service quality assessed in this study:

reliability, responsiveness, assurance, personalization, information quality,

46

customer service, and security are importance in maintaining the customer

satisfaction.

Other main purpose of this study is to find how channel integration could

influence both website and mobile service quality, as well as the customer

satisfaction. This variable is proven supported towards Website and Mobile

Service Quality, while it is not influential to the customer satisfaction. However,

as shown in Appendix L, the channel integration is indirectly influential to

customer satisfaction as it is mediated by the website service quality. This might

be occurs as Indonesia customers still likely to purchase through solely one mean

of desktop website rather than the mobile apps, which makes them not really

focusing on how integration between channels affect their customer satisfaction

(Elfira, 2017). This result is similar with previous study in China that Channel

Integration affects customer satisfaction indirectly through website service quality

(Yang et al., 2017). The difference is that in this research, mobile service quality

is not influential to the customer satisfaction while Yang et al. (2017) found that

the mobile service quality is directly influential towards the customer satisfaction

in China.

In order to justify the result of current study, researcher conducted a mini

qualitative study on 405 bFebruary 2018 involving seven respondents to find out

their preferences, either to do online transaction in Elevenia website or mobile

apps. The result shows that there are four respondents who prefer desktop website

for purchase transaction while three who choose mobile apps. Apparently, there

are some attributes involved in their decision such as (1) type of products want to

47

be purchased (3) occupation (4) major daily activity (4) features in smartphone or

desktop being used. Clearly, this could be the next object for future study.

The elucidation of the interview result is as below:

There are four respondents who prefer to do purchase transaction in website pc

with some reasons : (1) with bigger display in PC, they want to prevent any

misspell in writing the shipping address, reading the product information, etc.

Especially when they want to purchase what they perceived as ―luxury products‖

which need detailed and clear product information. One respondent admit that she

often ―add to cart‖ in the mobile apps or mobile website, then continue with

payment and shipping details on the desktop website. Therefore, she did the

product research, comparison, and chose the product in the mobile and continue

with transaction on the desktop website. (2) error in connection once happened

with one respondent who do purchase in mobile apps of Elevenia.co.id. The

respondent found that the transaction is failed while his bank account has already

being deducted since he is using autodebet credit card as payment option. Hence,

he need to contact the customer service and do clarification about it (3) they are

frequently using PC to do their work, and they access ecommerce during their

leisure time or when they are bored. The time when the respondents do online

transaction is between 11 AM – 1 PM and 5-7 PM. This is actually similar with a

research done by Shopback on 2016 that most Indonesians do online purchase

transaction on working hours (Widiartanto, 2016). One other interesting point is

that all of these respondents who prefer desktop website are employees in the age

of 23-33 years old.

48

On the other hand, there are three respondents who prefer to do purchase in

mobile apps. They have ever purchased cheap to expensive products like mobile

phone. There are several reasons revealed (1) Convenience. Mobile is with them

everytime, they can browse and check products, do purchase transaction ehenever

they want. These customers do not always use laptop everyday. Their occupation

varies from housewive, student, and a worker (2) Beside, the mobile apps service

quality are getting better and product information is getting clearer. Elevenia.co.id

is generally improving its mobile apps service quality like the payment method,

navigation, and other user interface features (3) their smartphone also could

accommodate good shopping experience and research. For example, with

capability to have more than one tab or bigger ram, customer can do research in

the browser while on the same time opening the ecommerce apps and do price

checking/comparisons in various ecommerce apps/site. Hence, this smartphone

already have the capability similar with what desktop can do. Especially for the

smartphone who has bigger screen size, the reason of not purchasing in mobile

due to inconvenience in reading product information is not essential.

Based on the interview researchers conclude that there are some factors involved

in respondents preferences in choosing the channel : (1) type of products want to

be purchased. The more luxury it is, the more tendency of them to use the desktop

website to prevent any fault in wring shipping address, credit card number, and

other payment options. Also, they could read product information clearly in

bigger screen size (2) their most frequent device used in their activity. The

employee who used to work with laptop tend to use desktop on their leisure time

to do purchase transaction, while the housewives and students mostly use

49

smartphone to do purchase transactions, (3) the type of smartphone and PC they

have, is it sophisticated enough to support convenient mobile apps or desktop

website seamless shopping experience?

Lastly, hypothesis sixth which claims that there is a positive relationship between

the customer satisfaction towards the repurchase intention is accepted. This is

supported by a lot of studies overseas (Ding et al., 2011; Jiradilok, Malisuwan,

Madan, & Sivaraks, 2014; Yang et al., 2017; Blut, 2016; Fang, Chiu, & Wang,

2011). Hence, it is very important for ecommerce to find every effort to maintain

its customer satisfaction to always maintain its customers‘ repurchase intention

since the ecommerce who could maintain its repurchase intention will be able to

sustain in competition.

50

CHAPTER V

CONCLUSION

5.1 Hypothesis Answers

H1: Website Service Quality influences Customer Satisfaction is accepted

H2: Channel Integration influences Customer Satisfaction is rejected

H3: Mobile Service Quality influences Customer Satisfaction is rejected

H4: Channel Integration influences Website Service Quality is accepted

H5: Channel Integration influences Mobile Service Quality is accepted

H6: Customer Satisfaction influences Repurchase Intention is accepted

5.2 Future Recommendation

Researcher recommends e-commerce in Indonesia to focus on improving the

website service quality to correspondently maintain customer satisfaction and

repurchase intention. E-commerce should also start understand the important of

integration between each channels it has, especially by the time Mobile

Commerce in Indonesia getting bigger attention. At the moment, mobile might not

become the main channel used in online shopping, but as the smartphone and

internet penetration rises in Indonesia, it is significant to prepare the integration of

the channels starting from now.

For future study, it is important to address ‗mobile focused‘ ecommerce such as

Shopee and Salestock in terms of Mobile Commerce Service Quality. These e-

51

commerce players commit to focus on Mobile Apps which makes the research

more focus and respondents must be familiar with the mobile platform (Putri,

2015; Pratama, 2016).

Also, based on the mini qualitative study conducted by researcher, there are some

more findings could become object of study such as the impact of customers age

and occupation to the channel preferences, or the impact of type of products they

want to purchase with the channel preferences. Is it true that millennials are not

hesitate to do mobile apps transaction while the generation X still having problem

with the risk acceptance? Is it true that most of housewives do online transaction

in mobile while the employees choose to use desktop website on their working

hours?

While for future study that want to focus on Channel Integration of online and

mobile apps, researcher would recommend to use Tokopedia and Lazada as the

object since both e-commerce focus on both desktop website and mobile apps,

with stabile traffic for the past eight months (ecommerceIQ, 2017). These

ecommerce also have high customers database and consider as the stringest in

Indonesia market (Freischlad, 2017). They have highest traffic with rank #12 and

#9 among websites in Indonesia (Tokopedia.com Analytics - Market Share Stats

&amp, 2018) (Lazada.co.id Analytics - Market Share Stats s &, 2018)In their

good reputation, it is important if channel integrations really plays major role on

the success story.

52

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62

APPENDICES

Appendice 1 – The Online Questionnaire

18 – 20 tahun

21 – 30 tahun

31 – 40 tahun

41 – 45 tahun

73

Appendice 2 – Data Tabulation

Website Service Quality Mobile Service Quality

WR

EL1

WR

ES2

W

AS

3

W

EM

4

WI

Q5

W

PP

6

W

CS

7

W

SE

8

MR

EL

1

MR

ES2

M

AS

3

ME

M4

MI

Q5

M

PP

6

M

CS

7

M

SE

8

7 6 6 5 6 7 7 7 6 6 6 7 7 7 7 7

5 5 5 5 5 5 6 4 5 5 5 5 5 5 5 4

6 6 6 5 6 3 6 3 6 6 6 6 6 6 6 6

3 3 3 3 3 3 3 4 4 3 3 4 3 4 3 4

6 6 6 6 5 6 6 6 6 6 6 6 6 6 6 6

6 6 6 6 5 5 5 5 6 5 5 5 5 5 5 5

6 5 5 5 6 5 6 5 5 5 6 5 6 4 3 5

5 5 6 7 5 7 7 5 5 5 5 7 6 6 6 6

6 6 5 6 6 6 5 6 6 6 6 6 6 6 6 6

4 4 4 4 4 4 4 4 4 5 5 4 4 3 4 5

6 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4

4 4 4 5 5 4 5 4 5 5 5 6 5 5 6 5

7 7 7 6 6 5 6 6 7 7 6 6 6 6 6 6

5 6 5 4 6 5 6 6 5 6 4 5 6 6 5 5

5 4 4 5 3 4 4 4 4 5 4 3 4 4 4 5

5 6 6 6 6 6 6 6 5 6 7 6 6 6 6 7

7 7 7 6 7 7 6 7 7 7 7 7 7 7 7 7

7 6 7 6 7 6 6 7 6 7 7 6 6 7 6 6

4 4 5 5 3 4 6 3 6 6 6 5 5 4 5 5

5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4

4 5 6 6 6 7 4 6 6 6 7 7 4 7 4 5

5 4 5 6 6 6 5 5 6 3 6 6 5 4 5 6

5 4 5 5 6 4 5 6 5 5 6 6 6 6 6 6

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

3 5 4 4 3 5 3 1 2 2 2 2 2 2 1 1

7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7

4 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4

5 5 2 2 2 4 1 2 3 3 2 2 2 2 2 4

6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4

6 6 6 7 6 5 6 7 5 4 5 4 6 5 6 6

5 4 5 4 4 3 5 4 4 5 4 5 5 4 5 5

6 5 5 4 5 7 7 5 5 5 6 6 6 7 7 5

4 4 3 4 3 5 5 4 4 5 3 4 5 4 4 4

6 6 7 6 6 6 7 6 7 6 6 7 7 7 6 7

4 4 5 4 4 4 4 4 4 4 4 4 4 4 4 4

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

4 3 3 3 3 3 5 7 1 1 1 1 2 2 2 3

7 6 6 4 4 5 6 7 6 6 4 6 6 6 5 7

5 5 5 4 4 4 4 5 5 5 5 5 5 5 5 5

74

6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5

2 3 3 2 2 3 3 3 2 2 2 2 3 3 2 2

6 6 6 5 4 7 6 6 6 6 6 4 6 7 6 6

5 6 6 6 6 3 3 3 5 6 6 6 5 5 3 3

4 4 4 4 4 4 4 6 4 6 6 4 4 4 4 4

6 5 6 4 5 5 6 5 6 6 6 6 6 5 6 6

6 5 5 5 5 5 6 6 6 4 5 4 4 6 4 6

5 6 5 6 5 5 5 5 5 6 6 6 5 5 5 5

7 7 6 6 6 7 7 7 7 7 6 6 6 7 7 7

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

6 6 6 4 6 7 7 6 6 6 6 6 6 7 7 6

7 6 5 5 4 5 6 5 6 5 6 5 6 6 6 5

7 7 7 7 7 5 5 5 7 7 6 6 6 6 5 6

7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7

6 6 6 5 5 6 5 5 5 6 6 5 5 6 5 5

4 4 4 3 3 5 4 4 4 4 4 4 4 4 4 4

6 6 7 7 7 7 7 7 6 7 6 6 6 6 7 7

5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5

5 5 6 6 6 7 7 5 6 5 6 5 6 7 7 5

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

4 5 5 6 4 3 6 3 6 7 5 5 5 2 3 5

4 5 5 3 4 5 5 5 6 6 6 6 6 6 6 6

4 5 4 5 5 5 4 4 4 5 4 3 5 5 5 5

4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4

4 5 4 5 6 6 6 6 4 5 4 5 6 6 6 6

5 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6

4 4 4 2 4 4 4 4 4 4 4 4 4 2 3 4

6 6 7 6 7 6 5 5 6 6 7 7 6 7 6 5

5 5 4 6 7 7 6 7 5 5 6 6 6 6 5 5

5 5 4 3 3 5 5 5 5 5 4 3 5 5 5 5

4 4 4 4 4 4 4 5 3 4 4 3 4 4 3 4

5 6 6 7 6 7 5 6 5 7 5 6 6 5 7 5

7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7

4 4 4 5 4 4 4 4 4 4 4 4 4 4 4 4

5 3 6 5 5 2 5 6 3 3 2 2 6 4 2 4

4 7 3 4 4 4 6 4 4 5 6 6 5 3 3 5

6 6 6 6 6 6 6 6 5 6 6 6 6 5 6 6

6 5 5 5 6 5 5 5 5 5 5 5 5 5 5 5

7 7 7 6 7 7 5 6 6 6 6 7 7 6 7 7

3 3 4 6 5 2 1 3 2 5 2 3 2 5 4 4

6 6 6 5 6 6 5 4 6 5 5 5 5 5 5 4

5 5 5 6 7 6 6 6 6 2 5 6 6 6 6 6

6 6 6 4 5 4 5 6 4 5 4 5 5 5 5 5

75

7 7 7 7 7 7 6 7 6 5 7 7 7 7 7 7

5 5 5 6 4 5 6 6 5 5 5 5 6 6 6 6

5 5 5 5 6 6 5 5 6 6 6 5 5 5 6 5

5 5 6 6 7 6 5 6 5 5 6 6 5 6 5 5

4 5 5 5 5 5 5 6 6 6 6 6 6 6 5 6

7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7

3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 3

5 5 5 4 6 6 5 5 4 5 5 5 6 6 4 5

5 5 6 3 4 6 7 7 6 5 7 6 7 7 7 7

2 2 2 2 2 2 2 2 3 2 2 2 2 3 1 1

4 5 5 4 5 4 4 4 5 6 6 4 4 4 4 4

5 4 6 5 3 7 6 5 5 6 6 5 6 7 5 6

4 4 4 4 4 4 4 6 6 6 6 5 6 5 5 6

4 4 5 3 3 5 4 4 4 4 4 3 4 4 4 4

5 5 6 7 6 2 6 3 6 2 5 3 5 2 7 6

7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7

6 6 6 6 4 6 6 6 5 6 6 6 5 6 6 6

4 3 3 4 3 4 3 4 4 3 4 4 3 5 5 4

5 6 6 6 5 5 6 5 6 5 5 6 5 5 6 6

4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4

6 5 5 5 5 5 5 5 6 5 5 5 5 5 5 5

5 5 5 4 5 5 5 5 5 5 5 6 5 5 5 5

7 7 7 7 6 6 6 5 6 5 7 7 7 7 7 5

6 6 6 6 6 6 6 7 6 6 6 6 6 6 6 6

3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3

7 7 7 7 7 6 6 6 7 6 7 6 6 6 6 6

4 4 4 4 4 4 4 3 4 4 3 4 5 3 4 4

6 6 5 5 6 6 6 4 6 5 5 5 5 6 5 6

5 5 5 6 5 5 5 6 5 5 5 5 6 5 5 6

5 5 5 5 5 6 6 5 6 5 4 5 5 5 4 5

5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5

5 5 4 4 5 5 5 5 5 5 5 5 5 5 5 5

5 5 6 6 4 6 5 7 3 4 4 5 6 5 5 6

5 5 6 4 7 7 5 4 6 4 6 4 5 4 6 4

6 5 5 6 5 6 6 5 7 6 6 5 5 6 5 5

5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4

5 4 5 4 4 4 4 5 4 5 5 5 5 5 4 5

1 2 3 2 3 4 3 5 3 3 3 3 4 3 4 4

6 7 6 6 7 7 5 6 7 7 7 7 7 5 6 7

7 7 7 6 7 7 7 7 7 7 7 7 6 7 6 5

7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7

7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7

6 6 6 5 5 6 5 6 6 6 6 6 6 6 5 5

76

4 4 5 4 5 4 4 4 6 5 5 4 5 5 6 4

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

4 4 5 5 5 6 5 6 5 5 5 5 5 5 5 5

6 6 7 2 3 6 7 6 6 6 6 7 6 6 7 6

5 6 6 4 4 5 7 6 4 4 4 4 4 4 4 4

5 6 5 6 5 6 5 6 6 4 6 5 7 5 6 5

5 6 5 6 6 5 4 6 6 6 6 5 6 6 4 6

5 5 5 6 6 7 6 7 6 6 5 6 7 7 7 7

5 5 6 4 3 4 5 4 4 5 5 4 4 4 4 5

2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

7 7 7 7 7 7 7 7 6 6 6 7 7 7 7 7

2 5 5 2 2 5 7 3 5 5 5 5 3 5 7 5

7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6

6 6 5 6 6 6 6 6 6 6 6 6 6 6 6 6

5 5 5 6 5 5 5 6 5 6 5 6 5 6 5 5

4 4 5 3 4 4 5 4 6 6 5 3 4 5 5 6

5 5 7 6 6 4 4 4 4 6 6 5 6 5 4 4

5 5 5 5 5 5 5 5 5 5 5 5 6 5 5 6

6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5

5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

6 6 7 7 6 7 6 7 7 6 7 6 7 6 7 6

5 5 5 5 5 6 5 5 5 5 5 5 6 5 5 5

5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5

4 3 3 4 4 4 3 4 4 4 3 4 3 4 4 3

5 5 5 6 5 7 6 4 4 5 5 6 6 6 6 6

6 6 6 5 5 5 5 6 6 6 6 6 6 6 6 6

6 6 5 4 6 5 6 5 6 6 5 6 5 4 6 5

5 5 4 5 5 4 5 5 5 5 5 5 4 5 5 5

7 7 7 2 7 7 7 7 7 7 7 7 7 7 7 7

5 5 5 5 5 5 6 6 3 3 4 4 5 5 4 4

4 3 3 3 3 3 5 4 3 4 5 3 4 3 4 3

6 5 5 4 4 6 5 6 6 5 6 6 5 7 6 6

5 5 6 4 4 7 7 3 4 4 5 4 4 4 5 4

6 6 6 5 5 6 5 5 6 6 6 5 6 5 5 5

5 4 5 3 4 5 6 4 5 4 4 5 5 5 4 6

6 6 6 6 6 6 6 7 5 6 5 6 6 6 6 6

5 6 6 6 7 6 7 5 4 3 4 5 5 5 4 5

5 5 5 5 5 5 5 4 5 5 4 4 4 4 4 4

5 4 6 4 6 6 4 6 6 5 6 6 6 7 4 6

5 4 5 4 6 3 5 3 5 4 6 6 4 3 5 3

7 7 7 7 7 4 5 5 5 6 6 5 7 6 6 5

5 6 5 4 4 6 5 6 6 6 5 4 6 4 5 5

6 7 5 6 6 7 5 6 6 6 5 5 6 7 6 6

77

6 6 6 6 5 6 5 7 6 7 7 5 6 5 6 7

5 5 6 5 5 7 5 5 5 5 5 5 5 6 5 5

5 4 6 5 5 6 4 5 5 4 6 5 4 4 3 4

Channel Integration Customer Satisfaction

Repurchase

Intention

CDI

1

CIC

2

CIPR

3

CIPP

4 CICS

5

SAT

1

SAT

2

SAT

3

SAT

4

RPI

1

RPI

2

RPI

3

6 6 7 7 7 6 6 6 6 5 5 6

5 5 5 5 5 4 3 3 3 4 4 4

6 6 6 3 6 5 5 5 5 3 5 3

3 4 4 4 3 3 3 3 3 3 4 3

6 5 6 6 6 6 6 6 6 6 6 6

5 5 5 5 5 5 5 5 5 5 5 5

4 5 5 5 5 5 5 4 4 3 5 5

6 6 7 7 6 6 7 6 5 7 7 6

6 6 5 6 6 6 6 7 7 7 6 6

4 4 4 4 4 4 4 4 4 4 4 4

5 5 5 5 5 5 5 5 6 5 4 4

4 4 3 4 4 4 5 4 4 5 5 4

7 6 6 6 7 6 6 7 7 6 6 6

6 5 6 5 7 3 5 6 4 5 6 5

3 4 5 5 4 4 3 4 4 4 3 4

6 6 6 6 6 6 6 6 6 7 5 6

6 6 7 7 7 7 7 7 7 7 6 7

7 6 7 7 6 6 7 7 7 7 6 6

5 5 6 5 5 5 5 5 5 6 6 6

4 4 4 4 4 5 5 5 5 4 5 5

2 4 5 1 3 2 6 4 5 3 3 3

5 5 6 6 6 4 5 5 5 4 5 4

6 6 6 6 6 4 5 5 5 4 4 4

6 6 6 6 6 6 6 6 6 6 5 6

3 3 2 2 1 1 1 1 1 1 1 1

7 7 7 7 7 7 7 7 7 7 7 7

4 4 4 4 4 4 4 4 4 4 4 4

2 2 2 5 3 3 3 2 3 1 1 1

7 7 7 7 7 7 7 7 7 7 7 7

4 5 5 6 4 6 5 6 5 6 6 5

5 5 5 5 5 5 5 5 4 5 5 4

5 4 5 5 6 5 5 4 5 5 5 4

4 5 4 4 4 5 4 5 4 4 4 3

6 5 6 6 6 6 6 6 7 6 6 7

4 4 4 4 4 5 5 4 5 4 4 4

78

6 6 7 7 7 7 7 7 7 7 6 6

4 4 1 2 3 1 1 1 1 1 1 1

6 5 6 7 4 5 7 6 5 7 6 6

5 6 6 5 5 4 5 4 5 5 5 4

5 5 5 5 5 5 5 5 5 5 6 6

2 3 1 2 2 1 2 2 2 3 2 2

6 5 5 5 6 6 6 6 6 6 5 5

6 5 5 5 5 6 5 6 5 5 5 6

6 6 6 5 4 4 5 6 4 6 6 4

6 6 7 7 6 5 4 5 5 5 4 4

4 5 5 5 4 6 6 6 6 6 5 5

6 5 5 6 6 5 5 5 6 5 6 5

5 5 4 6 7 5 6 5 6 5 5 5

6 6 6 6 6 6 6 6 6 6 6 6

6 6 7 7 7 4 4 5 5 5 2 2

6 6 6 6 6 5 4 6 6 6 5 6

6 6 5 7 7 7 7 7 7 7 6 7

7 7 7 7 7 7 7 7 7 7 7 7

6 6 6 6 6 6 6 6 6 6 6 6

4 4 4 4 4 4 4 4 4 4 4 4

6 5 5 6 6 4 7 7 6 6 7 7

5 5 5 5 5 5 5 5 5 5 5 5

6 5 4 6 7 6 7 7 6 5 3 3

6 6 6 6 6 6 6 6 6 6 6 6

5 4 6 6 6 6 5 4 5 5 6 5

6 6 6 1 5 4 4 4 4 3 3 3

5 5 5 3 4 5 4 4 5 5 4 5

4 4 4 4 4 4 4 4 4 4 4 4

4 4 5 6 5 4 5 4 6 5 4 4

6 6 6 6 6 4 5 5 5 4 4 4

4 4 4 5 4 4 5 4 4 5 4 5

6 4 5 5 7 6 6 6 7 6 6 6

5 5 5 5 6 5 5 6 5 6 5 5

5 5 5 5 5 4 5 4 5 5 4 4

4 4 4 4 4 3 3 3 2 3 3 3

6 6 7 5 4 6 4 7 6 5 7 5

7 7 7 7 7 7 7 7 7 6 6 7

4 4 4 4 4 4 4 4 4 4 4 4

2 3 6 5 5 6 5 5 4 6 6 7

4 5 5 5 4 3 3 2 2 2 2 2

5 6 6 6 6 5 5 6 6 6 5 5

5 5 5 5 5 5 6 5 4 4 5 4

6 6 7 6 7 6 7 6 7 7 5 5

79

2 4 3 3 3 3 4 4 6 4 6 6

6 6 6 6 6 4 4 4 4 4 4 4

7 7 7 7 4 6 6 6 6 5 5 5

4 4 4 4 5 5 5 5 5 5 6 6

6 6 7 7 7 5 7 7 7 7 5 5

5 5 6 5 5 3 3 3 3 3 1 2

6 5 5 5 5 4 5 5 5 5 4 4

5 5 6 5 6 5 5 5 6 6 5 5

6 6 6 6 6 6 6 6 6 6 6 6

7 7 7 7 7 7 7 7 7 7 7 7

3 3 3 5 4 3 3 4 3 2 2 2

6 5 5 5 5 6 5 5 5 5 5 5

7 6 6 3 6 3 3 4 4 3 3 3

3 2 3 1 3 3 2 3 3 4 3 3

4 4 4 4 4 4 6 6 4 3 1 1

5 5 6 6 5 3 4 5 5 5 4 4

5 6 4 5 5 4 4 5 5 4 5 6

4 6 6 6 4 3 6 4 5 4 5 5

6 4 6 6 3 6 4 6 2 2 4 3

7 7 7 7 7 7 7 7 7 7 7 7

6 5 6 5 5 5 5 5 5 5 4 4

3 4 2 3 4 4 4 3 5 5 5 3

5 5 5 5 5 6 6 6 6 6 6 6

4 4 4 4 4 4 4 4 4 4 4 4

5 5 5 5 5 5 5 5 5 5 5 5

5 5 5 5 5 6 6 5 6 5 5 4

7 7 6 6 7 7 7 6 7 7 6 7

6 6 6 5 6 6 6 6 6 6 6 6

4 4 4 4 4 3 3 3 3 3 3 3

6 6 7 7 7 6 6 6 6 7 6 6

4 4 3 3 4 4 3 4 4 4 4 4

6 5 6 5 6 6 4 6 5 5 6 4

5 5 5 5 5 5 5 5 5 5 5 5

6 5 6 5 5 6 6 6 6 6 5 6

5 5 5 5 5 5 5 5 5 5 4 4

5 5 5 5 5 5 5 5 5 5 5 5

5 5 3 7 6 4 6 5 5 4 5 5

5 5 6 6 7 3 4 4 4 4 3 3

6 5 6 6 7 5 6 5 5 5 5 5

4 4 4 4 4 4 4 4 4 3 2 2

5 5 5 5 5 5 5 5 5 5 5 5

3 3 3 4 3 2 3 3 4 3 3 3

5 5 6 5 6 7 7 7 7 7 6 7

80

4 4 4 7 7 4 4 4 5 7 6 6

7 6 7 6 7 6 6 6 6 6 7 7

7 6 7 6 7 6 6 6 6 6 7 7

6 5 6 6 6 6 5 6 6 6 6 5

5 5 4 6 7 4 5 4 5 4 3 3

6 6 6 6 6 6 6 6 6 6 6 6

5 5 4 6 5 4 4 4 4 4 3 3

6 6 7 6 7 7 7 7 7 7 7 7

5 6 6 7 6 5 6 6 7 5 4 4

6 5 5 4 6 6 5 6 5 5 6 5

6 5 5 6 5 5 5 6 6 6 5 6

7 6 4 7 7 6 7 7 7 7 7 7

4 5 4 5 4 5 4 5 4 5 4 5

2 2 2 2 2 2 2 2 2 2 2 2

6 7 6 7 7 7 7 7 7 7 7 7

5 5 5 5 5 4 5 3 4 1 1 3

7 7 7 7 7 7 7 7 7 7 7 7

6 6 6 6 6 6 6 6 6 5 3 2

5 5 6 5 5 6 5 6 5 6 5 5

3 3 4 3 4 6 5 4 4 3 2 3

5 5 5 5 3 4 3 3 4 4 4 4

5 5 5 5 5 5 5 6 6 5 4 5

6 5 6 6 6 7 7 7 7 7 7 7

6 6 6 6 6 6 6 6 6 6 6 6

7 7 7 6 7 7 6 7 7 7 7 6

5 5 5 4 4 4 4 4 5 4 4 4

5 5 5 5 5 5 5 5 5 4 4 4

4 4 4 4 4 4 4 4 3 4 3 5

6 6 6 6 6 6 4 4 5 4 4 5

6 6 6 5 6 6 6 6 6 6 6 6

6 5 5 4 4 6 5 5 5 5 4 5

5 5 6 5 5 5 5 5 5 5 6 6

7 7 7 7 7 7 7 7 7 1 1 1

5 5 5 5 5 5 5 5 5 5 5 5

4 3 4 4 3 3 5 4 3 3 4 6

4 4 3 4 5 5 5 5 5 6 6 6

5 5 6 7 6 4 5 4 5 5 5 4

6 5 7 5 5 6 5 5 6 6 5 5

6 5 6 5 5 3 4 4 4 3 3 3

6 6 6 6 6 5 5 5 5 5 5 5

5 5 5 6 6 6 5 5 6 7 6 6

4 4 4 4 4 3 4 5 4 4 4 3

6 5 6 7 4 5 6 6 6 6 5 6

81

4 5 4 6 6 3 4 4 4 4 3 4

6 6 7 7 7 5 5 5 5 7 6 6

7 6 6 6 5 5 6 5 5 5 6 5

6 5 4 6 6 5 5 7 6 7 6 6

7 5 6 6 4 5 7 5 4 6 5 7

5 5 6 5 5 4 4 4 5 5 4 4

4 5 4 4 5 4 4 5 6 5 4 6

Appendice 4a KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. ,958

Bartlett's Test of Sphericity Approx. Chi-Square 4345,670

Df 253

Sig. ,000

Source : IBM SPSS ver 22 Output

Appendice 4b Communalities

Initial Extraction

WREL1 1,000 ,796

WRES2 1,000 ,802

WEM4 1,000 ,858

WIQ5 1,000 ,836

MREL1 1,000 ,813

MRES2 1,000 ,737

MAS3 1,000 ,810

MEM4 1,000 ,821

MIQ5 1,000 ,827

MPP6 1,000 ,771

MCS7 1,000 ,773

MSE8 1,000 ,771

CDI1 1,000 ,844

CIC2 1,000 ,849

CIPR3 1,000 ,806

82

CIPP4 1,000 ,723

SAT1 1,000 ,822

SAT2 1,000 ,861

SAT3 1,000 ,861

SAT4 1,000 ,848

RPI1 1,000 ,866

RPI2 1,000 ,911

RPI3 1,000 ,898

Extraction Method: Principal Component

Analysis.


Appendice 4c Total Variance Explained

Componen

t

Initial Eigenvalues

Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

Total

% of

Varianc

e

Cumulativ

e % Total

% of

Varianc

e

Cumulativ

e % Total

% of

Varianc

e

Cumulativ

e %

1 15,02

1

65,308 65,308 15,02

1

65,308 65,308 6,46

2

28,095 28,095

2 1,740 7,564 72,872 1,740 7,564 72,872 4,22

2

18,356 46,451

3 ,842 3,663 76,534 ,842 3,663 76,534 3,52

5

15,328 61,779

4 ,754 3,278 79,813 ,754 3,278 79,813 2,47

8

10,774 72,553

5 ,547 2,376 82,189 ,547 2,376 82,189 2,21

6

9,636 82,189

6 ,505 2,194 84,383

7 ,431 1,875 86,258

8 ,395 1,717 87,975

9 ,364 1,583 89,558

10 ,284 1,233 90,791

11 ,272 1,184 91,975

12 ,243 1,056 93,031

13 ,225 ,980 94,011

83

14 ,202 ,878 94,889

15 ,181 ,787 95,676

16 ,163 ,710 96,386

17 ,152 ,662 97,048

18 ,146 ,635 97,683

19 ,136 ,593 98,276

20 ,109 ,475 98,751

21 ,107 ,467 99,218

22 ,093 ,402 99,620

23 ,087 ,380 100,000

Extraction Method: Principal Component Analysis.


Appendice 4d Rotated Component Matrix

Component

1 2 3 4 5

WREL1 ,526

WRES2 ,546

WEM4 ,711

WIQ5 ,710

MREL1 ,745

MRES2 ,754

MAS3 ,778

MEM4 ,763

MIQ5 ,673

MPP6 ,770

MCS7 ,741

MSE8 ,724

CDI1 ,698

CIC2 ,734

CIPR3 ,718

CIPP4 ,643

SAT1 ,568

SAT2 ,617

SAT3 ,532

SAT4 ,534 ,525

84

RPI1 ,785

RPI2 ,876

RPI3 ,872

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.a

a. Rotation converged in 7 iterations.


Appendice 4e Reliability Statistics of “Website Service Quality”

Cronbach's Alpha N of Items

,903 4


Appendice 4f Reliability Statistics of “Mobile Service Quality”


,958 8


Appendice 4g Reliability Statistics of “Channel Integration”


,907 4


Appendice 4h Reliability Statistics of “Customer Satisfaction”


,946 4


85

Appendice 4i Reliability Statistics of “Repurchase Intention”


,945 3


Appendice 4j Model Fit Result

Indicators Cut Off Value Result Evaluation

Chi Square ≤ 0.05 0 Significant

CMIN/DF 2 < CMIN < 5 2.042 Good Fit

GFI ≥ 0.9 0.816 Not Fit

AGFI ≥ 0.9 0.774 Not Fit

RMSEA 0.05 ≤ RMSEA

≤ 0.08

0.078 Good Fit

CFI CFI ≥ 0.9 0.946 Good Fit

TLI TLI ≥ 0.9 0.939 Good Fit

IFI IFI ≥ 0.9 0.946 Good Fit

Source : IBM AMOS ver 22 Output

CMIN

Model NPAR CMIN DF P CMIN/DF

Default model 52 457.329 224 .000 2.042

Saturated model 276 .000 0

Independence model 23 4574.389 253 .000 18.081

RMR, GFI

Model RMR GFI AGFI PGFI

Default model .079 .816 .774 .662

Saturated model .000 1.000

Independence model 1.001 .099 .018 .091

Baseline Comparisons

Model NFI

Delta1

RFI

rho1

IFI

Delta2

TLI

rho2 CFI

Default model .900 .887 .946 .939 .946

Saturated model 1.000

1.000

1.000

86

Model NFI

Delta1

RFI

rho1

IFI

Delta2

TLI

rho2 CFI

Independence model .000 .000 .000 .000 .000

Model RMSEA LO 90 HI 90 PCLOSE

Default model .078 .068 .089 .000

Independence model .317 .309 .325 .000

87

Appendice 4k Squared Multiple Correlation

Squared Multiple Correlations: (Group number 1 - Default model)

Estimate

MSQ

.792

WSQ

.767

SAT

.746

RPI

.689

RPI3

.864

RPI2

.871

RPI1

.821

SAT4

.820

SAT3

.870

SAT2

.795

SAT1

.773

MSE8

.749

MCS7

.735

MPP6

.696

MIQ5

.789

MEM4

.788

MAS3

.764

MRES2

.647

MREL1

.766

WIQ5

.661

WEM4

.558

WRES2

.788

WREL1

.804

CIPP4

.562

CIPR3

.720

CIC2

.789

CDI1

.808


Appendix 4l Direct & Indirect Testing

Direct Effects (Group number 1 - Default model)

CI MSQ WSQ SAT RPI

MSQ .869 .000 .000 .000 .000

88

WSQ .852 .000 .000 .000 .000

SAT .362 .181 .443 .000 .000

RPI .000 .000 .000 .940 .000

RPI3 .000 .000 .000 .000 1.059

RPI2 .000 .000 .000 .000 1.047

RPI1 .000 .000 .000 .000 1.000

SAT4 .000 .000 .000 1.012 .000

SAT3 .000 .000 .000 1.044 .000

SAT2 .000 .000 .000 .982 .000

SAT1 .000 .000 .000 1.000 .000

MSE8 .000 .975 .000 .000 .000

MCS7 .000 1.068 .000 .000 .000

MPP6 .000 1.021 .000 .000 .000

MIQ5 .000 1.000 .000 .000 .000

MEM4 .000 1.071 .000 .000 .000

MAS3 .000 1.038 .000 .000 .000

MRES2 .000 .937 .000 .000 .000

MREL1 .000 1.000 .000 .000 .000

WIQ5 .000 .000 1.009 .000 .000

WEM4 .000 .000 .936 .000 .000

WRES2 .000 .000 .974 .000 .000

WREL1 .000 .000 1.000 .000 .000

CIPP4 .898 .000 .000 .000 .000

CIPR3 1.004 .000 .000 .000 .000

CIC2 .837 .000 .000 .000 .000

89

CDI1 1.000 .000 .000 .000 .000

Indirect Effects (Group number 1 - Default model)

CI MSQ WSQ SAT RPI

MSQ .000 .000 .000 .000 .000

WSQ .000 .000 .000 .000 .000

SAT .534 .000 .000 .000 .000

RPI .843 .170 .416 .000 .000

RPI3 .893 .180 .441 .996 .000

RPI2 .882 .178 .435 .984 .000

RPI1 .843 .170 .416 .940 .000

SAT4 .908 .183 .448 .000 .000

SAT3 .936 .189 .462 .000 .000

SAT2 .880 .178 .435 .000 .000

SAT1 .896 .181 .443 .000 .000

MSE8 .848 .000 .000 .000 .000

MCS7 .928 .000 .000 .000 .000

MPP6 .888 .000 .000 .000 .000

MIQ5 .869 .000 .000 .000 .000

MEM4 .931 .000 .000 .000 .000

MAS3 .902 .000 .000 .000 .000

MRES2 .815 .000 .000 .000 .000

MREL1 .869 .000 .000 .000 .000

WIQ5 .860 .000 .000 .000 .000

WEM4 .797 .000 .000 .000 .000

WRES2 .830 .000 .000 .000 .000

90

Appendice 4m Hypothesis testing

Estimate S.E. C.R. P Label

WSQ <--- CI .852 .062 13.786 *** par_7

MSQ <--- CI .869 .063 13.875 *** par_15

SAT <--- CI .362 .188 1.922 .055 par_19

SAT <--- WSQ .443 .132 3.356 *** par_20

SAT <--- MSQ .181 .131 1.377 .169 par_21

RPI <--- SAT .940 .074 12.725 *** par_24

CDI1 <--- CI 1.000

CIC2 <--- CI .837 .048 17.483 *** par_1

CIPR3 <--- CI 1.004 .064 15.804 *** par_2

CIPP4 <--- CI .898 .072 12.486 *** par_3

WREL1 <--- WSQ 1.000

WRES2 <--- WSQ .974 .057 16.944 *** par_4

WEM4 <--- WSQ .936 .077 12.216 *** par_5

WIQ5 <--- WSQ 1.009 .071 14.184 *** par_6

MREL1 <--- MSQ 1.000

WREL1 .852 .000 .000 .000 .000

CIPP4 .000 .000 .000 .000 .000

CIPR3 .000 .000 .000 .000 .000

CIC2 .000 .000 .000 .000 .000

CDI1 .000 .000 .000 .000 .000


Regression Weights: (Group number 1 - Default model)

91

Estimate S.E. C.R. P Label

MRES2 <--- MSQ .937 .068 13.831 *** par_8

MAS3 <--- MSQ 1.038 .064 16.256 *** par_9

MEM4 <--- MSQ 1.071 .064 16.793 *** par_10

MIQ5 <--- MSQ 1.000 .059 16.815 *** par_11

MPP6 <--- MSQ 1.021 .069 14.790 *** par_12

MCS7 <--- MSQ 1.068 .068 15.606 *** par_13

MSE8 <--- MSQ .975 .061 15.906 *** par_14

SAT1 <--- SAT 1.000

SAT2 <--- SAT .982 .058 17.034 *** par_16

SAT3 <--- SAT 1.044 .055 18.886 *** par_17

SAT4 <--- SAT 1.012 .057 17.629 *** par_18

RPI1 <--- RPI 1.000

RPI2 <--- RPI 1.047 .051 20.375 *** par_22

RPI3 <--- RPI 1.059 .053 20.168 *** par_23


92

Appendice 4n Amos Diagram


93

TABLES

Table 3.1 Instruments of the Questionnaire

Website Service Quality

No. Dimensions Construct

1. Reliability –

WREL1

The ecommerce desktop platform provides

dependable services(Yang et al., 2017)

2. Responsiveness –

WRES2


prompt services(Yang et al., 2017)

3. Assurance –

WAS3


professional services(Yang et al., 2017)

4. Empathy – is

reinvented to

Personalization –

WEM 4

The ecommerce desktop platform addresses my

specific needs

5. Information

Quality – WIQ5

The ecommerce desktop platform has

information relevant to my needs(Kim et al.,

2004)

6. Purchase

Process/Fulfilment

– WPP6

The ecommerce desktop platform has no

difficulties in payment process (Blut, 2016)

7. Customer Service

– WCS7

The ecommerce desktop platform offers a

customer service (Blut, 2016)

94

8. Security – WSE8 I feel safe in my transactions with the

ecommerce desktop platform (Blut, 2016)

Source : Constructed by researcher

Mobile Service Quality

No. Dimensions Sub Dimensions and Construct

1. Reliability –

MREL1

The ecommerce mobile platform provides

dependable services(Yang et al., 2017)

2. Responsiveness –

MRES2


prompt services(Yang et al., 2017)

3. Assurance –

MAS3


professional services(Yang et al., 2017)

4. Empathy – is

reinvented to

Personalization –

MEM 4

The ecommerce mobile platform addresses my

specific needs

5. Information

Quality – MIQ5

The ecommerce desktop/mobile platform has

information relevant to my needs(Kim et al.,

2004)

6. Purchase

Process/Fulfilment

– MPP6

The ecommerce mobile platform has no

difficulties in payment process (Blut, 2016)

7. Customer Service The ecommerce mobile platform offers a

95

– MCS7 customer service (Blut, 2016)

8. Security – MSEC8 I feel safe in my transactions with the

ecommerce mobile platform(Blut, 2016)


Channel Integration

No.

Dimensions

Construct

1 Data Integration- CDI1

Elevenia.com effectively integrates data

from its online and mobile channels(Yang et

al., 2017)

2 Information Consistency -

CIC2

Elevenia.com pulls together information that

used to come from its online and mobile

channels.(Yang et al., 2017)

3 Integrated promotion -

CIPR3

Elevenia.com align advertising and

promotion across online and mobile

channels (Cao & Li, 2015)(Frasquet &

Miquel, 2017); (Hyun-Hwa & Kim,

2010)(Bendoly et al., 2005)

4 Integrated Product and

Pricing - CIPP4

Elevenia.com has a consistent product prices

in online and mobile channels (Oh et al.,

96

2012)(Frasquet & Miquel, 2017)(Hyun-Hwa

& Kim, 2010)

5 Integrated Customer Service

- CICS5

Elevenia.com provides an interactive access

to customer service assistant in online and

mobile channels(Oh et al., 2012)


Customer Satisfaction

No. Construct Author

1 I like to purchase products from

Elevenia.co.id.

(Fang et al., 2011)

2 I am pleased with the experience of

purchasing products from Elevenia.co.id.

(Fang et al., 2011; Kim

et al., 2004)

3 I think purchasing products from

Elevenia.co.id.is a good idea.

(Fang et al., 2011;

Zboja & Voorhees,

2006)

4 Overall, I am satisfied with the experience of

purchasing products from Elevenia.co.id.

(Fang et al., 2011; Kim

et al., 2004; San Martín

& Camarero, 2009;

Zboja & Voorhees,

2006)


97

Repurchase Intention

No. Construct Author

1 If I could, I would like to continue using

Elevenia.co.id to purchase products.

(Fang, Chiu, & Wang,

2011; Chiu et al., 2009)

2 It is likely that I will continue purchasing

products from Elevenia.co.id in the future.


2011; Chiu et al., 2009)

3 I intend to continue purchasing products

from Elevenia.co.id in the future.


2011; Chiu et al., 2009)


Table 4.2 Respondents by Age Demography

Age Group Number of Respondents Percentage

18 - 20 years old 60 35%

21 - 30 years old 90 53%

31 - 40 years old 12 7%

41 - 45 years old 9 5%

TOTAL 171 100%

Source : Constructed by researcher based on respondents data

Table 4.3 Respondents by Average Value of Transaction

Average Value of

Transaction

Number of

Respondents

Percentage

< Rp 100,000 43 25%

Rp 100,000 - Rp 500,000 105 61%

Rp 500,000 - Rp

1,000,000

12 7%

Rp 1,000,000 - Rp 6 4%

98

2,000,000

> Rp 2,000,000 5 3%

TOTAL 171 100%



Website Service Quality

N

o. 1 2 3 4 5 6 7

TO

TA

L

1

Reliability- Website Elevenia.co.id Provides

Dependable Services 1 4 5 31 61 45 24 171

Percentage

1

%

2

%

3

%

18

%

36

%

26

%

14

%

100

%

2

Responsiveness - Website Elevenia.co.id

provides prompt services 0 3 10 29 57 49 23 171

Percentage

0

%

2

%

6

%

17

%

33

%

29

%

13

%

100

%

3

Assurance - Website Elevenia.co.id provides

professional services 0 3 11 21 58 52 26 171

Percentage

0

%

2

%

6

%

12

%

34

%

30

%

15

%

100

%

4

Personalization- Website Elevenia.co.id

addresses my specific needs 0 9 12 38 41 51 20 171

Percentage

0

%

5

%

7

%

22

%

24

%

30

%

12

%

100

%

5

Information QualityWebsite Elevenia.co.id has

relevant information regarding product 0 5 17 32 45 46 26 171

Percentage

0

%

3

%

10

%

19

%

26

%

27

%

15

%

100

%

6

Fulfillment- Website Elevenia.co.id has no

difficulties in payment process 0 5 11 31 43 47 34 171

Percentage

0

%

3

%

6

%

18

%

25

%

27

%

20

%

100

%

7

Customer Service - The ecommerce website

offers a customer service 2 2 9 26 56 51 25 171

Percentage

1

%

1

%

5

%

15

%

33

%

30

%

15

%

100

%

8

Security - I feel safe in my transactions with the

ecommerce website platform 1 3 13 33 43 50 28 171

Percentage

1

%

2

%

8

%

19

%

25

%

29

%

16

%

100

%

99


Mobile Service Quality

N

o. 1 2 3 4 5 6 7

Tot

al

1 Reliability- Mobile Elevenia.co.id Provides Dependable Services 1 4 9 34 44 61 18 171

Percentage

1

%

2

%

5

%

20

%

26

%

36

%

11

%

100

%

2 Responsiveness - Mobile Elevenia.co.id provides prompt

services 1 6 9 27 54 55 19 171

Percentage

1

%

4

%

5

%

16

%

32

%

32

%

11

%

100

%

3 Assurance - Mobile Elevenia.co.id provides professional

services 1 7 6 30 46 60 21 171

Percentage

1

%

4

%

4

%

18

%

27

%

35

%

12

%

100

%

4 Personalization- Mobile Elevenia.co.id addresses my specific

needs 1 6

1

1 31 49 52 21 171

Percentage

1

%

4

%

6

%

18

%

29

%

30

%

12

%

100

%

5 Information Quality - Mobile Elevenia.co.id has relevant

information regarding product 0 6 6 30 46 62 21 171

Percentage

0

%

4

%

4

%

18

%

27

%

36

%

12

%

100

%

6 Fulfillment- Mobile Elevenia.co.id has no difficulties in payment

process 0 7 9 32 47 47 29 171

Percentage

0

%

4

%

5

%

19

%

27

%

27

%

17

%

100

%

7 Customer Service - The ecommerce mobile platform offers a

customer service 2 5 9 36 46 47 26 171

Percentage

1

%

3

%

5

%

21

%

27

%

27

%

15

%

100

%

8 Security - I feel safe in my transactions with the ecommerce

mobile platform 2 2 7 33 54 51 22 171

Percentage

1

%

1

%

4

%

19

%

32

%

30

%

13

%

100

%


Channel Integration

1 2 3 4 5 6 7

Tot

al

1

Elevenia.co.id effectively integrates data from its website and

mobile apps 0 6 8 32 45 61 19 171

Percentage

0

%

4

%

5

%

19

%

26

%

36

%

11

%

100

%

2

Elevenia.co.id pulls together information that used to come from its

online and mobile channels 0 3 7 31 72 46 12 171

Percentage

0

%

2

%

4

%

18

%

42

%

27

%

7

%

100

%

3

Elevenia.co.id align advertising and promotion across online and

mobile channels 2 4 8 31 44 56 26 171

Percentage

1

%

2

%

5

%

18

%

26

%

33

%

15

%

100

%

4

Elevenia.co.id has a consistent product prices in website and mobile

apps 3 4 7 25 55 49 28 171

Percentage

2

%

2

%

4

%

15

%

32

%

29

%

16

%

100

%

5

Elevenia.com provides an interactive access to customer service

assistant in website 1 2

1

0 36 44 45 33 171

Percentage

1

%

1

%

6

%

21

%

26

%

26

%

19

%

100

%

100


Customer Satisfaction

1 2 3 4 5 6 7

Tot

al

I like to purchase products from Elevenia.co.id 3 3 18 38 45 47 17

Percentage

2

%

2

%

11

%

22

%

26

%

27

%

10

%

100

%

I am pleased with the experience of purchasing products from

Elevenia.co.id 2 3 13 33 58 37 25 171

Percentage

1

%

2

% 8%

19

%

34

%

22

%

15

%

100

%

I think purchasing products from Elevenia.co.id.is a good idea 2 4 10 39 47 44 25 171

Percentage

1

%

2

% 6%

23

%

27

%

26

%

15

%

100

%

Overall, I am satisfied with the experience of purchasing products

from Elevenia.co.id 2 5 9 33 55 41 26 171

1

%

3

% 5%

19

%

32

%

24

%

15

%

100

%


Repurchase Intention

1 2 3 4 5 6 7

Tot

al

1

If I could, I would like to continue using Elevenia.co.id to

purchase products 5 4 16 32 50 36 28 171

Percentage

3

%

2

% 9%

19

%

29

%

21

%

16

%

100

%

2

It is likely that I will continue purchasing products from

Elevenia.co.id in the future 7 7 16 37 45 43 16 171

Percentage

4

%

4

% 9%

22

%

26

%

25

% 9%

100

%

3

I intend to continue purchasing products from Elevenia.co.id in

the future 5 8 20 37 40 40 21 171

Percentage

3

%

5

%

12

%

22

%

23

%

23

%

12

%

100

%

Source : Constructed by researcher based on survey result

101

FIGURES

Figure 3.1 Theoretical Framework

Figure 4.1 Respondents by Age Demography


60

90

12 9

0

10

20

30

40

50

60

70

80

90

100

15 - 20 tahun 21 - 30 tahun 31 - 40 tahun 41 - 45 tahun18 - 20 tahun 21-30 tahun 31 - 40 tahun 41-45 tahun 18 - 20 tahun

Online Service

Quality

Channel

Integration

Mobile Service

Quality

Customer

Satisfaction

Repurchase

Intention

H1

H2

H3

H1

H4

H5

H6

102

Figure 4.2 Respondents by Average Value of Transaction


43

105

12 6 5

0

20

40

60

80

100

120

< Rp 100,000 Rp 100,000 - Rp500,000

Rp 500,000 - Rp1,000,000

Rp 1,000,000 -Rp 2,000,000

> Rp 2,000,000

building repurchase intention through online and …

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