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The Influence of Information, System Quality, and Service Quality on Customer
Satisfaction and Loyalty in Online Shopping
(Study on online shopping Customer in Forum Jual Beli/FJB Kaskus.us
Malang Region)
Wheny Khristianto*1, Imam Suyadi2, Kertahadi2
1Business Adminstration Department, FISIP, Lampung University, Indonesia
2Business Administration Department, Brawijaya University, Indonesia
-----------------------------------------------------------------------------------------------------------
ABSTRACT
Most business try their best to continually satisfy their customer, because customer
satisfactio n se ems to be an importa nt baro me ter of cu stomer’s intenti ons and has been
regarded as an important antecedent of loyalty.The exponential increases in online
shopping and the rapid growth in the number of retailers selling online cause customer
satisfaction and loyalty become main focus, because they are difficult to be predicted.
Relationship between buyer and seller only through a website as a media which support
online business. In recent electronic commerce research, the measures of information
quality, system quality, service quality, customer satisfaction and loyalty are important to
know website’s performance.
The purpose of this research are to know and to analyze: 1) information quality
influence on customer satisfaction in online shopping, 2) system quality influence on
customer satisfaction in online shopping, 3) service quality influence on customer
satisfaction in online shopping, 4) customer satisfaction influence on customer loyalty in
online shopping, and 5) service quality influence on customer loyalty in online shopping.
A set of empirical data including 82 questionnaires were collected from online
shopping customer in Malang who use FJB Kaskus.us as online shopping media and to
test estimates in the research model. The finding of this research indicate that
information quality, service quality were found influence and significant on customer
satisfaction, customer satisfaction and service qual ity were found influence and
significant on customer loyalty, but system quality was not significant on customer
satisfaction.
KEYWORDS: information quality, system quality, service quality, customer satisfaction,
customer loyalty, online shopping.
INTRODUCTION
Customer satisfaction and loyalty are elements that determine the successful of
market concept implementation. In bisnis, customer satisfaction is essential. It is a strong
media to predict customer retention, customer loyalty and product repurchase (Smith and
Albaum, 2010). A simple logic derived from businessman is when customer feels satisfied;
there must be something better come for future business (Irawan, 2003). Customer
satisfaction occurs as customer expectation can be met by the service giver. According to
Anderson and Lehman (1994), high performance service is the one that can satisfy the
customer need or may exceed their expectation in short. In other words, this satisfaction
occurs when expectation equals to delivery or the fact received by customer.
Customer satisfaction is created originally from detail, something routine and is
started far before good and service produced. It is appropriate with survey result of
Temporal & Trout (TARP) in 2001 that exposure some causes of why company loses its
market. Those causes are: customer move to other place or die (4%), customer shift to
competitor brand (5%), customer search for more competitive price (9%), poor handling of
complain (68%) (Poeradisastra, 2010). Those data indicate that actually customers are not
easily persuaded and not too emphasize on the price, they rather need good attention.
Through online business, individual may see favorable good or service product first
through website used by the seller as promotion media. These methods also make the
customer smarter since they have more information about the product and more alternative
places to buy such product. Customer satisfaction and loyalty is a very expensive thing to
maintain by every e-commerce company in global market that full of competition.
Customer satisfaction and loyalty concept in online business become a hot issue discussed
in electronic bases business. Different from customer satisfaction and loyalty concept of
tradisional business that has examined and discussed clearly and broadly, customer
satisfaction and loyalty concept within e-commerce is still in early stage of research (Swaid
and Wigand, 2007).
In Indonesia, e-commerce transaction value is still less than US$ 20 millions in
1996 up to 1999. However in 2009, e-commerce achievement is really uplifting. It is
revealed by Sharing Vision Telemathic Research Institution in 2010, that e-commerce
transaction value in Indonesia has reached Rp. 35 trillion, or equals to US$ 3.4 billions
(http: www.detik.com/, accessed in December 11th 2010). Based on The Economist report
in early 2011, Indonesia is the biggest global network market, with internet business
condition undergoes more rapid development compared to 4 year before beca use of mobile
internet, laptop, and tablet computer (Kompas, June 17th 2011).
Basically, online customer has high satisfaction, it is proved by research finding
released by Direct Newsletter in 2002 that 80% online customer has high satisfaction and
aim to repurchase within 2 months, 90% online customer will recommend the cite where
they buy product or service to others (Diana, 2009). Other evidence is research finding
done by Communication and Information Ministry in 2011 towards 1280 e-commerce
companies in various big cities in Indonesia also indicate that 7% respondent feel very
satisfied when doing shopping via internet, 44% respondent feel satisfied, 46% respondent
feel so so, and only 3% responden state their dissatisfaction (Kompas, June 17th 2011).
However, attracting customer attention in internet and give satisfaction and create loyalty
to customer are not easy job. A portal that provide online shopping facility needs
creativity, intelligence, a lot of time and energy in order to compete with ten, hundreds
even thousands of other virtual shop or online shop in internet (Rizka, 2010). Portal online
shopping is not only rely on service quality since the customer also need any matters cause
their satisfaction (Kuo, 2005), such as information and system quality in online shopping.
METHODS
This study uses survey method. The research population is online shopping
customers in FJB Kaskus within Malang region, which are active and frequently do online
shopping in FJB Kaskus. Sample collection technique in this study is systematic random
sampling with total of 82 respondents participated in this study. Data collection relied on
questionnaire given to respondents. Measuring scale used in questionnaire is semantic
differential scale and Partial Least Square (PLS)-based SEM analysis of variance for data
analysis.
RESULT AND DISCUSSION
1. Evaluation of Construct Measurement Model
This measurement model specifies the relationship between latent variable with
indicator or manifest variable. PLS employs principle component analysis method in
analyzing construct measurement model. This method is one of methods within
confirmatory factor analysis (CFA), namely factor analysis technique used to measure
factor quantity and loading variable score. Loading factor score is described at Table 1
follow.
Tabel 1. Loading Factor
Original
Sample (O)
Sample
Mean (M)
Standard
Deviation
(STDEV)
Standard
Error
(STERR)
T Statistics
(|O/STERR|)
X1.1
0,783
0.775
0.054
0.054
14.438
X1.2
0,759
0.749
0.049
0.049
15.209
X1.3
0,738
0.739
0.058
0.056
12.819
X1.4
0,680
0.685
0.062
0.062
11.027
X1.5
0,751
0.752
0.049
0.049
15.367
X1.6
0,782
0.785
0.037
0.037
21.045
X1.7
0,619
0.614
0.067
0.067
9.253
X1.8
0,687
0.682
0.076
0.076
9.0814
X1.9
0,699
0.699
0.064
0.064
10.991
X2.1
0,768
0.759
0.063
0.063
12.209
X2.2
0,670
0.667
0.078
0.078
8.571
X2.3
0,763
0.763
0.044
0.044
17.479
X2.4
0,718
0.709
0.051
0.051
14.046
X2.5
0,777
0.774
0.039
0.039
19.436
X2.6
0,608
0.805
0.036
0.036
22.468
X2.7
0,731
0.726
0.054
0.054
13.583
X2.8
0,689
0.687
0.055
0.055
12.542
X2.9
0,681
0.633
0.062
0.062
10.209
X2.10
0,715
0.705
0.063
0.063
11.326
X2.11
0,623
0.626
0.062
0.062
10.011
X2.12
0,722
0.719
0.055
0.055
13.172
X3.1
0,801
0.792
0.045
0.047
17.152
X3.2
0,830
0.817
0.042
0.042
19.731
X3.3
0,808
0.804
0.043
0.043
19.001
X3.4
0,727
0.724
0.059
0.059
12.321
X3.5
0,761
0.763
0.055
0.055
13.895
X3.6
0,804
0.802
0.031
0.031
25.982
X3.7
0,779
0.766
0.058
0.058
13.391
X3.8
0,632
0.633
0.069
0.069
9.159
X3.9
0,657
0.667
0.063
0.063
10.427
Y1.1
0,842
0.847
0.049
0.049
17.336
Y1.2
0,892
0.892
0.030
0.030
29.496
Y1.3
0,843
0.843
0.041
0.041
20.496
Y2.1
0,817
0.818
0.053
0.053
15.392
Y2.2
0,855
0.853
0.028
0.028
30.237
Y2.3
0,920
0.918
0.017
0.017
55.534
Source: Research Data Processed, 2011.
(i) Convergent Validity
Convergent validity test in PLS with reflective indicator is assessed based on
loading factor (between item score/component score correlation with construct or variable
score) that measure the construct or variable. Information quality variable (consist of item
X1.1 , X1.2, …, X1 .9), Syste m q ua lity variable (co nsist of i tem X2.1, X2.2, …, X2 .12),
Servic e q ua lity varia ble ( consist of item X3.1 , X3. 2,…X3 .9), custo mer s atisfac tion variable
(consist of Y1.1, Y1.2, Y1.3) and customer loyalty variable (consist of item Y2.1, Y2.1,
Y2.3) in table 16 indicates that loading factor score for each item is > 0.6 with tstatistic> tta ble
(1.99). It indicates that all items in information quality used in the research is valid and has
fulfilled convergent validity.
(ii) Discriminant validity
Discriminant validity from measurement model with reflective indicator is assessed
based on cross loading measurement with construct. Cross loading is worth to assess
whether construct has sufficient discriminant validity, namely by comparing indicator
correlation of a variable with correlation of that indicator with other variable.
Tabel 2. Cross Loading
Information
Quality
Sistem
Quality
Service
Quality
Customer
Satisfaction
Customer
Loyalty
X1.1
0.783
0.529
0.448
0.459
0.431
X1.2
0.759
0.522
0.414
0.524
0.557
X1.3
0.738
0.531
0.428
0.418
0.369
X1.4
0.679
0.446
0.414
0.494
0.412
X1.5
0.751
0.451
0.275
0.393
0.509
X1.6
0.782
0.519
0.523
0.571
0.496
X1.7
0.619
0.454
0.414
0.267
0.302
X1.8
0.687
0.513
0.431
0.366
0.373
X1.9
0.699
0.584
0.517
0.429
0.456
X2.1
0.567
0.768
0.573
0.474
0.540
X2.2
0.496
0.768
0.573
0,474
0,540
X2.3
0.594
0.763
0.606
0.554
0.528
X2.4
0.623
0.718
0.516
0.443
0.513
X2.5
0.485
0.777
0.658
0.512
0.553
X2.6
0.611
0.808
0.595
0.495
0.458
X2.7
0.485
0.731
0.525
0.467
0.487
X2.8
0.488
0.689
0.510
0.334
0.494
X2.9
0.405
0.631
0.445
0.363
0.411
X2.10
0.489
0.715
0.649
0.415
0.457
X2.11
0.339
0.623
0.603
0.464
0.497
X2.12
0.414
0.722
0.700
0.470
0.482
X1.1
0.396
0.637
0.801
0.472
0.349
X1.2
0.378
0.639
0.830
0.461
0.346
X1.3
0.358
0.586
0.808
0.459
0.409
X1.4
0.435
0.596
0.727
0.597
0.409
X1.5
0.368
0.581
0.761
0.568
0.514
X1.6
0.585
0.656
0.804
0.582
0.612
X1.7
0.365
0.561
0.779
0.416
0.303
X1.8
0.437
0.482
0.632
0.525
0.457
X1.9
0.617
0.612
0.657
0.484
0.610
Y1.1
0.539
0.641
0.643
0.842
0.633
Y1.2
0.578
0.557
0.611
0.892
0.660
Y1.3
0.475
0.430
0.499
0.843
0.588
Y2.1
0.497
0.547
0.504
0.614
0.817
Y2.2
0.538
0.591
0.542
0.605
0.854
Y2.3
0,545
0,624
0,544
0,678
0,918
Source: Research Data Processed, 2011.
From Tabel 2 above, it is suggested that for item X1..X1.9 has higher correlation
value compared with correlation value of items at other variables. Correlation value at
X2.1..X2.12 has higher value compared with correlation value of items at other variables.
Item X3.1...X3.9 has also gain higher correlation value compared with correlation value of
items at other variables, item Y1.1...Y1.3 has higher correlation value compared with
correlation value of items at other variables, and Y2.1..Y2.3 has also higher correlation
value compared with correlation value of items at other variables. These results indicated
that latent variables have predicted indicators at its own block better than indicator to other
blocks. Based on this analysis, it could be interpreted that those items has meet
discriminant validity and therefore asserted as valid.
(iii) Composite Reliability
Subsequent testing is reliability testing. Reliability variable measured by using
composite reliability, where variable would be said reliable if it have composite reliability
> 0,7. Composite reliability value of this study is shown in Table 3 as follows.
Tabel 3. Composite Reliability
Variable
Composite
Reliability
Information Quality
0,908
Sistem Quality
0,928
Service Quality
0,924
Customer Satisfaction
0.894
Customer Loyalty
0.899
Source: Ouput SmartPLS
Output of SmartPLS at Table 3 above has shown that overall variables has
composite reliability > 0,7. Based on the data above, it is proved that all variable used in
this study is reliable.
2. Structural Model Evaluation
Structural model was tested by looking at the explained variance percentage that is
by looking at R-square of latent dependent variable and by using Stone-Geisses Q-square
test measures for predictive relevance and goodness of fit (GoF). Result of R-square value
could be seen from Table 4 below.
Tabel 4. R-Square
Variable
R-Square
Customer Satisfaction
0.540
Customer Loyalty
0,559
Source: Output SmartPLS
At Table 4 it is known that R-square at customer satisfaction variable is 0,540.
This is showing that information quality, system quality and service quality variables has
contributed to customer satisfaction variable accounted for 54% while the remaining 46% is
contribution from other variables not examined in here. R-square value of customer loyalty
variable is 0,559. This is showing that customer satisfaction variable has giving
contribution toward customer loyalty variable as 55,9% while the remaining 44, 1% is
contribution from service quality variable.
(i) Q-Square predictive relevance
For testing or measuring value toward predictive relevance is using Q square with
mathematical equation as follows:
Q2=1 - (1-R12)(1-R22)… (1 -Rp2)
In this study, R12 value is R-square value from customer satisfaction variable, while R22 is
R-square value from customer loyalty variable. Based on the above equation, Q -square
value in this study is:
Q2=1 - (1-0,540289)(1-0,559232) = 0,797
Q-square value obtained is 0,797 and showing that observation value gained by model and
its parameter estimation is moderate, since Q-square value is almost 1. This result could
also being interpreted that model has been able to explain about customer loyalty
phenomenon for 79,7%, while the rest of it (20,1%) is explained by other variable that
didn ’t compos e the e xamin ed mode l.
(ii) GoF
Based on the output obtained using SmartPLS, we could get Communality value,
R2, with each average as shown in Table 5.
Tabel 5. Communality and R-Square
Variable
Communality
Average Value
of
Communality
R-
Square
Average Value
of R-Square
Information Quality
0,523
0,621
System Quality
0,519
Service Quality
0,575
Customer Satisfaction
739
0,540
0,55
Customer Loyalty
0,750
0,560
Source: Output SmartPLS
Table 5 above has described communality average value and R2 average value. Both
numbers could be put into equation with result as follows.
GoF =
55,0621,0 x
GoF =
342,0
GoF = 0,584
According to the calculation above, GoF value is 0,584. This means that model in this
study is in accord with index value requirement that is 0 < GoF < 1.
3. Hypothetical Testing Result
Hypothetical testing was conducted by using Bootstrapping method developed by
Geisser & Stone. Bootstrap is a re-sampling method that gives solution toward study with
small sample amount. Statistical testing was done by comparing t-statistic with t-table
value of 1,99 (significance at 0,05). Relationship between variable would be significant if
t-statistic > t-table value therefore subsequent analysis could be done. This method
determination has allowed free distributed data, thus it would not needed normal
distribution assumption.
Bootstrapping result after the use of SmartPLS software (see appendices) has
showed coefficient result of each lane with cross loading value and R-square value for each
item. For coefficient value of each lane is presented in Table 6 follow.
Tabel 6. Path Coefficients (Mean, STDEV, T -Values)
Original
Sample
(O)
Sample
Mean (M)
Standard
Deviation
(STDEV)
Standard
Error
(STERR)
T Statistic
(|O/STERR|)
Information Quality
Customer Satisfaction
0,306
0,315
0,110
0,110
2,775
System Quality
Customer Satisfaction
0,069
0,096
0,166
0,166
0,416
Service Quality
Customer Satisfaction
0,447
0,423
0,129
0,129
3,481
Customer Satisfaction
Customer Loyalty
0,588
0,577
0,104
0,104
5,629
Service Quality
Customer Loyalty
0,211
0,220
0,091
0,091
2,309
Source: output SmartPLS, 2011
Based on the Table 6 above, interpretation from hypothetical testing result toward
five variables in this study is described as follows:
Based on the Table 6 above, interpretation from hypothetical testing result toward five
variables in this study is described as follows:
a. First hypothesis: information quality has effect toward customer satisfaction.
Calculation result has showed that path coefficient value of 0,306 and t-statistic >
t-table value (2,775 > 1,99). This showed that information quality has significant effect
toward customer satisfaction. Relationship between both variable is uni-directive that
means higher information quality would brought higher customer satisfaction in doing
online shopping. According to this result, hypothesis that suggests information quality has
effect toward customer satisfaction in doing online shopping is therefore accepted.
b. Second hypothesis: system quality has effect toward customer satisfaction.
Result of calculation has showed that path coefficient value is 0,069 and t-statistic
< t-table (0,416 < 1,99). This is showing that system quality has insignificant effect toward
customer satisfaction. Relationship between both of this variable is uni-directive that
means higher system quality would bring higher customer satisfaction in conducting online
shopping. According to this result, thus hypothesis that said system quality has effect
toward customer satisfaction in doing online shopping is accepted.
c. Third hypothesis: service quality has effect toward customer satisfaction.
Calculation result has showed that path coefficient value is 0,447 and t-statistic > t-
table (3,481 > 1,99). This is showing that service quality has significant effect toward
customer satisfaction. Both variable relationships are uni-directive that means higher
service quality would bring higher customer satisfaction in conducting online shopping.
Based on this result, this hypothesis that said service quality has effect toward customer
satisfaction in doing online shopping is accepted.
d. Fourth hypothesis: customer satisfaction has effect toward customer loyalty.
Result of calculation has showed that path coefficient value is 0,588 and t-statistic
> t-table (5,629 > 1,99). This is showing that customer satisfaction has significant effect
toward customer loyalty. Relationship between both of this variable is uni-directive that
means higher customer satisfaction would bring higher customer loyalty in conducting
online shopping. Based on this result, hypothesis that said customer satisfaction has effect
toward customer loyalty in conducting online shopping is accepted.
e. Fifth hypothesis: service quality has effect toward customer loyalty.
Calculation has showed that path coefficient value is 0,211 and t-statistic > t-table
(2,309 > 1,99). This showed that service quality has significant effect toward customer
loyalty. Relationship between both variables is uni-directive that means higher service
quality would bring higher customer loyalty in conducting online shopping. Based on this
result, hypothesis that said service quality has effect toward customer loyalty in conducting
online shopping is accepted.
Interpretation description of hypothetical test results above could be summed up in
Table 7 and describe graphically in Figure 2.
Tabel 7. Summary of Hypothetical Testing Result
Hypothesis
Varible Influence
Result
Ho
1
Information Quality
Customer Satisfaction
Significant
Not accepted
2
System Quality
Customer Satisfaction
Not Significant
Accepted
3
Service Quality
Customer Satisfaction
Significant
Not accepted
4
Customer Satisfaction
Customer Loyalty
Significant
Not accepted
5
Service Quality
Customer Loyalty
Significant
Not accepted
DISCUSSION
More detailed discussion from hypothesis obtained in this study might be explained
as follows.
1. Effect of Information Quality toward Customer Satisfaction
Result of our study has showed that information quality provided in FJB Kaskus
website has direct, positive and significant effect toward customer satisfaction in
conducting online shopping. This finding has supported study conduct by Seddon and
Kiew (1994), in which information quality as having positive and significant effect toward
satisfaction of customer that use interface-based system. This result also gives support to
study conduct by Magerhands (2006), where information quality is one of the main
antecedent that affecting satisfaction while conducting e-Commerce transaction.
Customer satisfaction might be felt by customer conducting online shopping since
shopping could be done practically everywhere and anytime, and it ha s lower cost in
accessing information (Elliot and Fowell, 2000). Shang et al., (2005) argues that online
shopping has give extrinsic advantage toward customer by wider product option,
competitive price and easy access on information. This would give advant age and
satisfaction for customer that wants to buy product in a quick way (impulsive buyers).
Result of study conduct ed by Ya ng (2 007) is also in a ccord with t his s tud y’ s res ul ts
that is information quality would affects online satisfaction of consumers. Moreover, Yang
(2007) explained that when customer is interacting using a portal or a website, customer
would emphasize his/her attention toward information quality exist within the portal or
website. This is the reason why information quality has major effect toward customer
satisfaction. For customer or buyers that purchase using online system, information is
needed to found out the existence of a product, how much does it cost in the market. More
than that , c ustomer co uld c ompar e p roduct’ s p rice, qu alit y and brand from several different
places.
Result obtained from this study has strengthened assertion by Turban and Gehrke
(2000) that for online-base business, information quality within the website could function
as customer appeals. This study also strengthened Janda, et al. (2000) and Szymanski and
Hise (2000) that said information quality is one of the main factors that affecting customer
satisfaction in shopping using internet-based media. Result of this study has conflicting
result with Radityo and Zulaikha (2007) study that concludes information quality has no
effect toward user satisfaction.
Lohse and Spiller (1999) has contends that there is difference in features delivery
of retail shop that has physical nature with online shop. This could cause difference in
customer satisfaction. Though online shop has giving information about physical product
sold but due to technical limitation such as picture quality, it could not give the same
satisfaction with one that obtained if customers seeing the product in retail shop. However,
this study has give evidence that information presentation speed of new products, easiness
in accessing information for sold products, accurate price information for sold products,
variety of products displayed, description clarity of products offered, regularity of
description writing format of displayed products at the website, matching color
composition displayed on the website, and appropriate product picture with product
description is several things that could create customer satisfaction in conducting online
shopping at FJB Kaskus.
Based on result in this study, information quality provided at FJB Kaskus website
has direct, positive and significant effect, thus, higher information quality at FJB Kaskus
website would cause higher customer satisfaction to conduct online shopping in that
website. Since its significant effect, information quality variable is one important variable
that need to consider by online shopping customer in order to meet his/her satisfaction in
conducting online shopping.
2. Effect of System Quality toward Customer Satisfaction
If we were discussing about system quality for electronic based business regarding
customer satisfaction, an important aspect in it is customer relation with system that
supporting online shopping. Jarvenpaa and Todd (1997) argue that system quality is
generally discussing about what felt by consumers while conducting online shopping.
Result of this study has showed that system quality positive but insignificant effect tow ard
online shopping customer of FJB Kaskus. This finding is not similar with finding from
study of Seddon and Kiew (1994), where system quality has positive and significant effect
toward satisfaction of interface-based system users. But this finding is quite similar with
result of Schaupp et al. (2009) where system quality showed insignificant effect toward
satisfaction of e-commerce website users. Other than that, result of this study is quite
similar with study conducted by Yang (2007) and Radityo and Zul aikha (2007).
Regarded system quality variable that has insignificant effect toward customer
satisfaction, Yang (2007) has argued that when customer conduct online shopping
transaction, the main concern goes to information quality and service quality gain by
customer compared with system quality. This proved that customer is less care about
system quality. Reality that technology advance applied to e-commerce portal or websites
could reduce hardware and software system cost also increase system quality so that it
could be better accessed and making the particular portal or website become faster in
delivering response during interaction with customer. However, it, according to Yang
(2007), has been perceived differently by online shopping customers, since there is
tendency of customer to not complicating system quality issue while they were doing online
shopping.
Reason described by Yang (2007) above is matched with the reality felt by some
customer of online shopping at FJB Kaskus as our respondent. Their perception about
system quality existed in FJB Kaskus is highly different. When responden have fast internet
connection, responden would tend to say that processing online shopping access at FJB
Kaskus such as in loading process, data search speed and moving process from one page to
another page at FJB Kaskus can be categorized as fast or very fast. However, for customers
that have slow internet connection, they would give different answers. Other than that,
some respondent feel that they cannot give accurate assessment toward system quality,
since respondent has no standard in determining system quality.
Schaupp et al. (2009) also explained why system quality has insignificant effect
toward customer satisfaction. This is because, for customer, the important things for them
are to be able to do transaction and transaction they conduct is succeeded. They do not care
about system quality, like easy access in using the system while conducting online
shopping through e-commerce. Customer position as user could be the reason why they
didn ’t ca re, beca use ba si cally customer d idn’t underst and detailed syste m q ualit y, like typ e
of se rver u sed, d ataba se cap acity availab le so that there can ’t be o verload , and others.
These kind of things is only known by company, web master or web developer that
responsible toward website system performance of online shopping provider.
Reason being describe by Schaupp et al. (2009) is in agreement with the existing
reality for online shopping respondent at FJB Kaskus. Most of the ti me Kaskus party
conduct maintenance toward database system therefore thread or comments that sent by
customers regarding bought products were missing. When database overload is occurring at
Kaskus, it might lead to missing thread from seller and thus it would need longer time to
recovery database and while they were at it, customer cannot found the products or doing
transa ction. Howe ve r, t hose e vents didn’ t ma ke cus to mer stop their p reference i n
conducting online transaction at FJB Kaskus, since for customers the most important thing
is that they would be able to do online shopping eventually.
Other reality felt by online shopping customer at FJB Kaskus, that FJB Kaskus side
is not yet fully identified trusted and untrusted seller. Other that still occurri ng at FJB
Kaskus is fraud modus. However, with system quality condition and existing events that
occurs at FJB Kaskus has insignificant effect for customer to keep doing online shopping at
FJB Kaskus.
Based on this finding it means that for respondent of online shopping customer at
FJB Kaskus, system quality variable owned by FJB Kaskus is not an important variable for
creating customer satisfaction. Different result with prior study was possible by the
existence of different view toward system quality. At developed countries with higher
competition of online shopping facility offered by various vendor or portals, it have made
customer become more sensitive toward system quality given by particular e-commerce
company. However, for customers in developing countries and underdeveloped countries,
issue of system quality is not yet a sensitive issue. Other than that, it is highly possible for
online shopping customer at FJB Kaskus to not paying attention toward system quality
since there are other thing that functions as appeals for Kaskus.us website generally, that is
as the biggest online community media in Indonesia that offers several sub forums other
FJB and various features within it.
3. Effects of Service Quality toward Customer Satisfaction
Result of this study showed that service quality offers at FJB Kaskus website has
positive and significant effects toward customer satisfaction in doing online shopping.
This finding is supporting study conduct by Yang (2007), where service quality has
positive and significant effect toward online shopping customer satisfaction. In fact,
service quality has become one aspects that being centre of attention while doing online
shopping. Other study supporting this finding is one that conducts by de Oliveira (2007).
Aberg and Shahmehri (2000) have argued that sustainable improvement regarding offered
service by e-commerce web would bring high effect at customer satisfaction level.
Result gained in this study has also strengthen facts that said by Mappatompo
(2005) that service quality has close relationship with customer satisfaction, since service
quality gives encouragement for customer to get a real and strong relationship with the
co mpany in ord er to unders ta nding custo mer’s expectatio n. This is in accord with theor y
said by Wyckok in Lovelock (1988) in Tjiptono (2000) that service quality is superiority
degree expected and control toward that supe riority in meeti ng customer ’s dema nd . This
result also gives support toward theory said by Zeithaml et al. (1990), that c ustomer
satisfaction is customer perception from service experience given.
Based on this finding and the above explanation, it brought the means that higher
quality of service at FJB Kaskus website would create higher customer satisfaction to do
online shopping at the website. Since its significant effect, therefore service quality
variable has become an important variable to consider by online shopping customer to meet
his/her need in doing online shopping.
4. Effects of Customer Satisfaction toward Customer Loyalty
Result of this study has showed finding that customer satisfaction has direct and
significant effect toward customer loyalty in doing online shopping at FJB Kaskus. This
findin g is suppo rting Mager ha nds’s study (20 06), whe re t he re i s rela ti onship between
service qualities with customer loyalty in online shopping. Other study that gives support
toward this result is study conducted by Yang (2007).
Result of this study also gives support to Siat opinion (1997) in Harun that said
loyal customer is satisfied customer. Finding in this study also strengthened Selnes ’s
argument (1993) that customer loyalty is a function of customer satisfaction, where
satisfied customer would come and tell others about the service he/she received.
Satisfaction felt by customer could create customer loyalty. This support Jonas and Sasser
(1995) that customer loyalty is an endogen variable caused by satisfaction.
Similarity of result with prior study conducted by Magerhands (2006) and Yang
(2007) means that customer satisfaction variable is highly considered variable for online
shopping customer at FJB Kaskus in creating loyal attitude for online shopping activities
within the website. Higher satisfaction own by FJB Kaskus online shopping customer
means greater customer loyalty in doing online shopping at FJB Kaskus.
5. Effects of Service Quality toward Customer Loyalty
In this study we found that service quality has positive and significant effect
toward customer loyalty in doing online shopping. This result is in accord with prior study
conducted by Gefen (2000) that is for online-based environment, though there is no direct
human service provider, service quality has considerable effect in creating customer
loyalty. Prior results from empirical study by de Oliviera (2007) are also in accord with
result of this study. De Oliviera (2007) found a strong relationship between service
qualities with customer loyalty in electronic-based service.
Based on the above results, it is could be said that higher service quality in FJB
Kaskus would bring higher customer loyalty in doing online shopping at FJB Kaskus. Since
its significant effect, therefore service quality variable has become an important variable to
consider by respondent in improving loyalty of online shopping at FJB Kaskus. Generally,
service quality would create customer loyalty (Gefen, 2000). But according to de Oliviera
(2007), specific for electronic-based services, it would need harder efforts to create
customer loyalty compared with traditional service quality.
CONCLUSION
Based on hypothetical testing, analysis result and result discussion, conclusion of this study
might be summed as follows:
1. There is direct and significant effect between information quality toward customer
satisfaction in doing online shopping at FJB Kaskus. This has proved that online
shopping customer at FJB Kaskus with different education background, with age
ranging from 20-30 year would bring focus or his/her attention toward information
quality exist in FJB Kaskus website. This is shown with positive answers of
respondent. Online shopping customer condition that already accustomed in using
internet with many purposes could make them understand which information is
effective, interesting, accurate and which is not within context of human computer
interface, particularly when doing online shopping.
2. There is indirect and insignificant effect between system quality with customer
satisfaction in doing online shopping at FJB Kaskus. This is an interesting matter to
review, since though respondent has already accustomed in doing interaction with
computer, doing online shopping has not making system quality become a variable
that need to consider. Although in reality most respondent would give positive
answers, but when they were doing online shopping there is tendency not to care
about system quality of FJB Kaskus. Another thing that might be the cause of
system quality ignorance is respondent position as user, as online shopping
customer, and not as one that understand about system such as web developer and
web programmer. Other than that, responden characteristic that bear different
background is saying that it is possible if there is only a few of them that do pay
attention and understand about system quality when they do online shopping.
3. There is direct and significant effect between service quality with customer
satisfaction in doing online shopping at FJB Kaskus. Service quality existence in
online shopping context has become something that should be considered by
customer. This is reflected from respondent customer that tends to give positive
assessment. Though service existence at FJB Kaskus is mostly intangible, its
existence has direct effect toward customer satisfaction while doing online
shopping.
4. There is direct and significant effect of customer satisfaction variable toward
customer loyalty in doing online shopping at FJB Kaskus. This showed that online
shopping customer satisfaction at FJB Kaskus has impact toward hope fulfillment,
needs fulfillment and belief that doing online shopping at FJB Kaskus is the right
option to do. The next stage, the impact would make customer have interest in
recommend FJB Kaskus to other people, has interest in re-buying and loyal to do
online shopping at FJB Kaskus. This is proved by positive ten dency o f respondent ’s
answers.
5. There is direct and significant effect between service quality with customer loyalty
in doing online shopping at FJB Kaskus. The existence of intangible human service
provider was replaced by electronic based service which is not face-to-face in
nature, but through website media, does not make service quality not needed. Based
on posit ive tende ncy of responde nt’s answer s, it co ul d be seen that qualif ied
service is highly needed because when customer is doing online shopping, they
would be at blind condition in not knowing with who they were doing transaction
with, didn ’t k no w about threat r egard ing co nfide ntialit y and a ctual tra nsactio n that
was conducted also minimum direct attention. When customer was doing online
shopping and found a qualified service, this would bring impact toward creation of
customer loyalty in doing online shopping through the related website or portal.
REFERENCES
Anderson, F., and Lehman. 1994. Consumer Satisfaction, Market Share and
Profitability F inding from Sweden. Jurnal of Marketing, Vol. 58, p. 53 – 66.
New York.
Cheung, C.M.K, and Lee, M.O.K. 2005. Research Framework for Consumer
Satisfaction with Internet Shopping. Spronts: Working Papers on Information
Systems, 5(26). http://sprout.a isnet.org/5-26..
de Oliveira, R.C. 2007. Evidences from Link Between Quality and Loyality in e-
Service: An Empirical Study. Rivista Electronica Sistemas & Gestao 2 (2) 1-15.
Diana, A. 2009. Mengenal E-Business. Penerbit Andi. Yogyakarta.
Ferdinand, A. 2002. Structura l Equation Modeling Dala m Penelitian Manajemen . Balai
Penerbit Universitas Diponegoro, Semarang.
Gefen, D. 2002. Customer Loya lity in E-Commerce. Jurnal of The Association for
Information Systems (Volume 3) 27 – 51.
Harun. H. 2006. Analisis Faktor – Faktor Yang Mempengaruhi Kepua san Pelanggan
Untuk Meningkatkan Loyalitas Pelanggan Produk Telkom Flexi (Studi Kasus
PT. Telekomunkasi Indonesia Kota Semara ng). Master Tesis. Program Sarjana,
Universitas Dipenogoro. Semarang.
Indrakusuma, J. dan Ellitan, L. 2008. Analisis Multi Atribut Yang Mempengaruhi
Preferensi Bela nja Online Produk Tiket Pesawat Di Kalangan Mahasiswa
UKWMS. The 2nd Conference UKWMS, 6 September, Surabaya.
Irawan, H.D. 2003. 10 P rinsip Kepuasan Pelanggan. PT. Elex Media Komputindo.
Penerbit Gramedia, Jakarta.
Japa rianto, E., P opp y, L., Khomariya h, N.A., …. -. Analisa Kualitas Layanan Sebagai
Pengukur Loyalita s Pelanggan Hotel Majapahit Surabaya Dengan P emasaran
Relasional Sebaga i Varia be Intervening. Jurusan Manajemen Perhotelan,
Fakultas Ekonomi, Universitas Kristen Petra.
Janda, S., Trocchia, P.J, Gwinner, K.P. 2002. Consumer Perceptions of Internet Reta il
Sernice Qua lity. International Journal of Service Industry Management (13:5),
pp. 412 – 431.
Jogiyanto, H.M, Abdillah, W. 2009. Konsep dan Aplikasi PLS (Partial Least Squa res)
Untuk Penelitian Empiris. Edisi Pertama, Penerbit BPFE, Yogyakarta.
Kuo, T., Lu, I., Huang, C., & Wu, G. 2005, Measuring Users' Perceived P ortal Service
Quality: An Empirical Study. Total Quality Management & Business
Excellence, Volume. 16, No. 3, pp. 309-320.
Magerhans, A. 2006. Consumer Satisfaction in Electronic Commerce – A Survey
Concerning the German Online Bookshop Trade. International Federation of
Scholary Association of Management (IFSAM) VIIIth World Congress. Sept,
28-30. Berlin.
Poeradisastro, T. 2010. Layanan Mengesankan vs. Layanan Menyebalkan. Majalah
SWA No. 21/XXVI/4-13 Oktober.
Riduan, dan Kuncoro, E.A. 2007. Cara Menggunakan Dan memakai analisis Jalur
(Path Analysis). Penerbit Alfabeta, Bandung.
Schaupp, L.C, Belanger, F, Fan, W. 2009. Examining The Success of Websites Beyond
E-Commerce: An Extension of The IS Success Model. The Journal of Computer
Information Systems. Volume 49, No.4, pp. 42-52, ProQuest Computing
Singarimbun, M., dan Effendi, S. 2006. Metode Penelitian Survei. Pustaka LP3ES.
Jakarta.
Smith, S.M. and Albaum, G.S. 2010. Measuring Respondent Informa tion: Attitudes,
Satisfaction, Loyalty, and Behavior. An Introduction to Marketing Research.
Swaid, S.I., and Wigand, R.T. 2007. Key Dimensions of E-Commerce Service Quality
and Its Relationship to Satisfaction and Loyality. 20th Bled eConference
eMergence: Merging and Emrging Technoligies, Processes, and Institutions,
June 4- 6. Bled, Slovenia.
.Symanski, D. M., and Hise, R. T. 2000. e-Satisfaction: An Initial Examination. Journal
of Retailing (76:3), pp. 309 – 322.
Tjiptono, F. 2000. Manajemen Pemasaran Jasa. Penerbit Balai Pustaka, Jakarta.
Vinzi, V.E., Trichera, L., and Amato, S. PLS Path Modelling: From Foundations to Recent
Developments and Open Issues for Model Asessment and Improvement. Handbook
of Partial Least Squares: Concepts, Methods, and Application (V. Esposito Vinzi,
et al. (edition)). Springer Handbooks of Computational Statistic. Springer-Verlag,
Berlin-Heidelberg.
Xiao, Li and Dasgupta, Subhasish. 2002. Measurement of User Satisfaction with Web-
Based Information System: An Empirical Study. Eighth American Conference
on Information Systems.
Yang, Hao-erl. 2007. Assesing The Effects of e-Quality and e-Satisfaction on Website
Loyalty. International Journal of mathematics and Computer in Simulation, Issue
3, Vol. 1.
Appendix
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X2. 3
X2. 4
X2. 5
X2. 6
X2.7
X2. 8
X2. 1
Y1.
Y1.
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