Winda Victoria Pebriani
Bogor Agricultural University, Indonesia
E-mail: windavictoria@gmail.com
Ujang Sumarwan
Bogor Agricultural University, Indonesia
E-mail: usumarwan@apps.ipb.ac.id
Mega Simanjuntak
Bogor Agricultural University, Indonesia
E-mail: mega_juntak@apps.ipb.ac.id
Submission: 13/07/2013
Accept: 02/03/2018
ABSTRACT
The objective of this
research was to analyze the effect of lifestyle, perception, satisfaction, and
preference on the online re-purchase intention. The data are collected from 218
women consumers who have bought Muslim clothing through e-commerce (Hijup) and
social network (Instagram) at least two times in the last three months. The
data are analyzed using t-test and Structural Equation Modelling (SEM). The
result of this research indicates that lifestyle has a significant effect on
perception, perception has an effect on satisfaction, satisfaction has an
effect on preference, and preference has an effect on re-purchase intention.
Meanwhile, satisfaction has no significant effect on re-purchase intention in
both models.
Keywords: lifestyle, online repurchase
intention, perception, preference,
satisfaction
1. INTRODUCTION
A
rapidly growing human civilization is also followed by a rapid development of
information technology. The current rapid technological development is caused
by the presence of internet. Based on Directorate General of Tax (2014)
Indonesia is the world’s largest market of e-commerce. Indonesia is also the
world’s largest contributor of internet attack accounting for 38 percent,
followed by China with 33 percent, USA with 6,9 percent, Taiwan with 2,5
percent, Turkey 2,4 percent, and other countries. One of the many products sold
online is clothing product. Based on the
Statistics Indonesia or BPS (2010), the Muslim population in 2010 is recorded
amounting to 207,2 million people (87,18 percent). That percentage figure is
the highest in terms of religion embraced in Indonesia. Accordingly, Muslim
clothing has a big market potential in Indonesia.
Hijup.com,
Hijabenka, and Fashion Valet Indonesia are the examples of Muslim clothing
e-commerce platforms conducting business in Indonesia. In addition to
e-commerce, the online sale of Muslim clothing is also conducted a lot in
social network like Facebook, Twitter, and Instagram. Facebook and Instagram,
in Asia especially Indonesia, become the popular and effective social network
to open an online shop. The intense competition between e-commerce platforms
and social-network-based online shops such as in Facebook and Instagram makes
the players in this business compete to gain new consumers and maintain the
existing consumers.
Along with the
rapid development of information technology, currently there is a change of
trend in shopping due to the lifestyle change and the increasing online
activities. Mowen and Minor (2002) state that lifestyle is associated with how
people spend their money and how they allocate time upon the products they
consume. Lifestyle can be categorized into price oriented, network oriented,
and time oriented (KIM et al, 2000).
Lifestyle has an effect on perception in online shopping (Mohamed et al, 2014). Perception has a positve effect on online
re-purchase intention (LIN; LU, 2000; CHAO et al, 2008; RAMAYAH; IGNATIUS, 2005; LINGLING; XUESONG,
2014). Perception after online shopping has an effect on satisfaction in online
shopping (MOHAMED et al,
2014).
Figure 1:
Conceptual framework
In online
environment, the overall satisfaction in online media will make the consumers
to reuse that media online (BHATTACHERJEE, 2001). Satisfaction has a positive
effect on online re-purchase interest (SIYAMTINAH; HENDAR, 2015; CURTIS et al, 2011; KYAUK; CHAIPOOPIRUTANA, 2014). Satisfaction
affects the brand preference (JAMAL; GOODE, 2001) and channel preference
(DEVARAJ et al, 2002).
Consumer preference is the choice of liking and disliking done by a person upon
the products (goods and services) consumed (SUMARWAN et al, 2011; YOSINI, 2011). The evaluation on the choice is
based on the shopping experience. Shopping experience influences consumer
intention to re-purchase a product, in other words preference can influence
re-purchase intention. Preference affects re-purchase intention (OVERBEE; LEE,
2006; MOHAMED et al, 2014).
According to the
above empirical review, this research focused on the relationship between
lifestyle, perception, preference, satisfaction, and re-purchase intention as
shown in Figure 1. This research aimed to analyze the difference of lifestyle,
perception, satisfaction, preference, and re-purchase intention in web-based
Muslim Clothing e-commerce and social network, analyze the effect of lifestyle,
perception, satisfaction, and preference on re-purchase intention in web-based
Muslim Clothing e-commerce and social network, and formulate managerial
implication in web-based Muslim clothing e-commerce and social network.
2. RESEARCH METHOD
This
research was conducted from October to December 2016 using online sampling. The
online questionnaire was created using Google Docs. Respondents of this
research amounted to 218 people who are female consumers who have done online
shopping through web-based e-commerce and social network at least two times in
the last three months. The web-based e-commerce in this research refers to
hijup.com and the social network studied is Instagram. The statistic analysis
used is t-test and Structural Equation Modelling (SEM). SEM is utilized to
analyze the effect of lifestyle, perception, satisfaction, and preference on
online re-purchase intention. Meanwhile, t-test is used to identify the
difference of variables in both the media studied. The data obtained are
processed using Microsoft Excel 2013, SPSS version 23.0, and LISREL 8.70.
Table 1: Research variables and indicators
Latent variables |
Definition of operational variables |
Indicator variables |
Lifestyle (X1) |
The way a person spends
her money and time. |
Time-oriented lifestyle (X1.1) Network-oriented lifestyle (X1.2) Price-oriented lifestyle (X1.3) |
Perception (X2) |
A condition in which an individual uses a technology
in doing her activities and is considered pleasant for herself. |
Access (X2.1) Search (X2.2) Evaluation (X2.3) Transaction (X2.4) Delivery (X2.5) After-purchase (X2.6) |
Customer Satisfaction (X3) |
The reflection of customer’s feeling about
experience in online shopping. |
Shopping experience satisfaction (X3.1) Satisfaction on the service received (X3.2) Shopping decision (X3.3) |
Preference (X4) |
The choice of liking or disliking by a person on the
media used. The preference of media in this research is divided into two,
namely e-commerce and social network. |
This media is the main choice in online shopping (X4.1) This media is more favored in online shopping (X4.2) |
Re-purchase Intention (Y1) |
The willingness of customer (who has bought at least
once) to re-purchase. |
Intend to continue the purchase (Y1.1) Keep making purchases (Y1.2) Regularly make purchases (Y1.3) |
Source: Modifikasi dari Jiang et al,(2012) dan (MOHAMED et al , 2014).
This research consisted of two types of variable,
namely latent variable and indicator variable. There were 5 latent variables
which were measured using an instrument of questionnaire containing questions
about indicators of those variables, in order to examine the hypotheses. The
exogenous latent variables of this research were lifestyle (X1), while
the endogenous latent variables were perception (X2), customer
satisfaction (X3), preference (X4), and re-purchase
intention (Y1). The instrument used in this research was the
modification of the instruments used in Jiang et al, (2012) and Mohamed et
al, (2014). The measurement scale applied was Likert scale with
five points, in which 1 meant strongly disagree and 5 meant strongly agree.
3. RESULT AND DISCUSSION
Respondents
of this research are dominated by women aged 25 to 34 years old with the
percentage of 64.7 percent. The age of 25 to 34 year-old indicates that the
respondents have been having a job and are probably married. Based on the
consumer’s age distribution, online shopping is mostly done by the consumer
aged 25 to 34 years old who are called as Generation Y which according to
Stiady (2011) is the largest group of social media user. Generation Y or
millennial generation is the generation born between 1980s to early 2000s. The
older the consumer’s age, the less they do online shopping.
The ones
ages 45 to 54 years old rarely do online shopping probably due to the lack of
information regarding online shopping media or their tendency of liking offline
shopping by coming directly to the stores. Most of the respondents have the
income of more than Rp 3.000.000. It shows that the respondents with such level
of income have the ability (money) to do online shopping. It can be concluded
that most of the respondents are upper middle or capable consumer..
This
research also observed online shopping behavior of consumer shopping in
hijup.com and Instagram-based online shops. The online shopping behavior
includes monthly online shopping expenditure, the last expenditure of online
shopping, the last time of online shopping, time used to go online in a day,
and products that are usually bought online. The data are presented in Table 2.
Based on this research, the majority of the
respondents, with the percentage of 43,6 percent, spend less than Rp 500.000
per month for online shopping. Meanwhile, the ones who spend between Rp 500.000
and Rp 1.000.000 per month for online shopping are 38,9 percent of total
respondents. The remaining are respondents who spend between Rp 1.000.001 - Rp
2.000.000 per month for online shopping (7,8 percent), between Rp 2.000.001 and
Rp 3.000.000 per month for online shopping (4,1 percent), and between Rp 3.000.001
and Rp 5.000.000 per month for online shopping (0,5 percent). The other 4,1
percent spend more than Rp 5.000.000 per month for online shopping.
Table 2: Consumer’s online
shopping behavior
|
Online shopping behavior |
Amount (n) |
Percentage (%) |
Monthly online shopping
expenditure |
|
|
|
|
<Rp 500.000,00 |
95 |
43,6 |
|
Rp 500.000,00 - Rp 1.000.000,00 |
87 |
38,9 |
|
Rp 1.000.001,00 - Rp 2.000.000,00 |
17 |
4,1 |
|
Rp 2.000.001,00 - Rp 3.000.000,00 |
9 |
7,8 |
|
Rp 3.000.001,00 - Rp 5.000.000,00 |
2 |
0,5 |
|
>Rp 5.000.000,00 |
8 |
4,1 |
The last expenditure of online shopping |
|||
|
<100.000,00 |
14 |
6,4 |
|
Rp 100.001,00 - Rp 300.000,00 |
84 |
38,5 |
|
Rp 300.001,00 - Rp 500.000,00 |
71 |
32,6 |
|
Rp 500.001,00 - Rp 1.000.000,00 |
30 |
13,8 |
|
>Rp 1.000.000,00 |
19 |
8,7 |
The last time of online shopping |
|||
|
< last week |
119 |
54,6 |
|
Last 1-2 month(s) |
14 |
6,4 |
|
Last 1-2 week(s) |
55 |
25,2 |
|
Last 2-3 months |
3 |
1,4 |
|
Last 2-4 weeks |
27 |
12,4 |
Time used to go online in a day |
|||
|
1-2 hour(s)/day |
31 |
14,2 |
|
2-3 hours/day |
47 |
21,5 |
|
3-4 hours/day |
49 |
22,5 |
|
4-5 hours/day |
23 |
10,6 |
|
5-6 hours/day |
23 |
10,6 |
|
> 6 hours/day |
45 |
20,6 |
Products that are usually bought online (answer can be more than one) |
|||
|
Blouse |
160 |
31,5 |
|
Pants |
72 |
14,2 |
|
Dress |
78 |
15,4 |
|
Shirts |
44 |
8,7 |
|
Veil |
154 |
30,3 |
In this research, 39 percent of the respondents have
the last expenditure of online shopping of between Rp 100.001 and Rp 300.000
(Table 2). Judging from the last expenditure of online shopping, nearly most of
the consumers spend more than Rp 100.000 the last time they did online
shopping. Most of the respondents, which is 54,6 percent, have the last time of
online shopping of less than the last week. The last time of online shopping
for 25,2 percent of the respondents is between the last 1 to 2 week(s) from the
time of questionnaire filling. Meanwhile, 12,4 percent and 6,4 percent of the
respondents have the last time of online shopping of between the last 2 to 4
weeks and between the lasr 1 to 2 month(s) respectively. The res tof the
respondents (1,4 percent) have the last time of online shopping of between the
last 2 to 3 months.
Based on this research, the time used by most of the
respondents to do online routine in a day is quite varied. There is no
domination in the length of time use for daily online routine because the
busyness of the respondents studied is quite diverse. Most of the respondents
do online shopping to buy blouse and veil.
The
test of H1 to H6 hypotheses made use of independent t-test in which all
dimension scores and variable scores were transformed into the scale of 0 to
100 to see the index comparison between dimension and variable. It is carried
out because the number of question for each dimension and variable is
different. Table 3 reveals that the dimension of price-oriented lifestyle has p
< 0,05. It indicates that there is a difference in the dimension of
price-oriented lifestyle. The average value of Instagram (4,65) is higher than
hijup.com (4,36). It means that the respondents consider that the price offered
by the Instagram-based online shop is better than the price offered by
hijup.com.
In terms of perception variable, there is a real
difference in dimension between hijup.com and Instagram, namely evaluation,
transaction, delivery, and after-purchase dimension due to the value of p <
0,05. Perception in terms of evaluation shows the information provided by
hijup.com and Instagram. Based on the average value, the evaluation in
hijup.com has a higher value than Instagram. It shows that the respondents
regard that the information provided by hijup.com is better than the
information provided by Instagram.
Transaction in hijup.com is considered to be more
convenient than in Instagram according to the average value of transaction
dimension of hijup.com (4,79) which is higher than the value of Instagram (4,51).
The delivery done by hijup.com is considered to be better than the delivery
done by Instagram-based online shops, based on the average value of delivery
dimension. The delivery encompasses the aspect of suitability, quality of
goods, and delivery timeliness. It proves that hijup.com always maintain its
good quality control and stock availability. In terms of re-purchase aspect,
respondents think that Instagram is more flexible than hijup.com.
Table 3: The result of
independent T-Test
Variable |
Dimension |
hijup.com |
Instagram |
T-test between media |
||
Average |
SD |
Average |
SD |
|||
Lifestyle |
Time-oriented |
4,33 |
0,80 |
4,40 |
0,77 |
0,080 |
Network-oriented |
4,73 |
0,73 |
4,70 |
0,70 |
0,745 |
|
Price-oriented |
4,36 |
0,85 |
4,65 |
0,72 |
0,000** |
|
Perception |
Access |
4,76 |
0,68 |
4,70 |
0,73 |
0,373 |
Search |
4,54 |
0,82 |
4,44 |
0,88 |
0,530 |
|
Evaluation |
4,73 |
0,73 |
4,09 |
1,09 |
0,000** |
|
|
Transaction |
4,79 |
0,69 |
4,51 |
0,90 |
0,000** |
|
Delivery |
4,75 |
0,68 |
4,50 |
0,84 |
0,000** |
|
After-purchase |
4,45 |
0,70 |
4,54 |
0,58 |
0,009** |
Customer satisfaction |
Online shopping experience satisfaction |
3,87 |
0,76 |
3,70 |
0,83 |
0,036* |
The pleasure of online shopping |
3,93 |
0,73 |
3,87 |
0,79 |
0,415 |
|
|
Online shopping decision |
3,76 |
0,81 |
3,71 |
0,85 |
0,528 |
Preference |
This media is the main choice in online shopping |
3,19 |
0,92 |
3,56 |
0,91 |
0,000** |
|
This media is more favored in online shopping |
3,08 |
0,95 |
3,52 |
0,95 |
0,000** |
Re-purchase intention |
Intend to continue purchase |
3,34 |
0,87 |
3,67 |
0,86 |
0,000** |
Keep on making purchases |
3,20 |
0,86 |
3,55 |
0,91 |
0,000** |
|
Regularly make purchases |
2,99 |
0,90 |
3,40 |
0,91 |
0,000** |
Note: *significant at p < 0.05, **
significant at p < 0,01
In terms of satisfaction variable, the dimension of
shopping experience satisfaction in hijup.com is better than in Instagram. It
is probably because of the products sold by hijup.com are of good quality and
are as advertised. The average values of dimensions of preference variable are
higher in Instagram compared to the values in hijup.com. It indicates that
respondents favor online shopping in Instagram more than in hijup.com. There is
a real difference in re-purchase intention variable, namely in the three
dimensions. Based on the average value, respondents think they intend to do
re-purchase in Instagram rather than in hijup.com. On the other hand, there is
no real difference in the access and search dimension.
One
of the weaknesses of SEM model is that it is sensitive to the large number of
sample which will tend to generate a high chi-square value which causes the
model to not having goodness of fit. Therefore, SEM provides the alternative
use of other goodness of fit indicator. The Root Mean Square Error of
Approximation (RMSEA) is an index that can be used to compensate the chi-aquare
statistic in a large sample. Based on the analysis, the values of RMSEA
obtained are 0,036 (hijup.com) and 0,031 (Instagram) which mean that the model
is acceptable. The value of Goodness of Fit Index (GFI) is used to show how
capable a model is to explain the data variance. Based on the analysis result,
the value of GFI obtained is 0,90. It follows the good-fit criteria because of
the value of GFI ≥ 0,90 so that the model is categorized as fit model. The
Adjusted Goodness of Fit Index (AGFI) is similar to the GFI but it adjusts the
effect of degree of freedom on the model. The measurement of AGFI in both
models can be considered as marginal fit because of the value of 0,8 < AGFI
< 0,90. The values of AGFI acquired are 0,85 (hijup.com) and 0,86
(Instagram).
The use of other criteria of Goodness of Fit, namely
GFI, CFI, NFI, NNFI, IFI and RFI, generates the value of > 0,90 which means
that the model generated is a good fit. The other measurement criteria of
Goodness of Fit called RMR also generates the value of ≤ 0,1 which means that
the model is a good fit. Because most of the criteria give a conclusion that
the model is a good fit, therefore the hypothesis testing can be conducted. It
also signifies that the data obtained from the questionnaire have been able to
answer the developed theories. The measurement model fit indexes can be seen in
Table 4.
Table 4: Measurement Model Fit Indices
Goodness-of-Fit |
Cut-off-Value |
Result |
Information |
|
hijup.com |
Instagram |
|||
RMR (Root Mean Square Residual) |
< 0,05 atau < 0,1 |
0,036 |
0,031 |
Good fit |
RMSEA (Root Mean square Error of
Approximation) |
< 0,08 |
0,068 |
0,064 |
Good fit |
GFI (Goodness of Fit) |
> 0,90 |
0,90 |
0,90 |
Good fit |
AGFI (Adjusted Goodness of Fit
Index) |
> 0,90 |
0,85 |
0,86 |
Marginal fit |
CFI (Comparative Fit Index) |
> 0,90 |
0,99 |
0,99 |
Good fit |
NFI (Normed Fit Index) |
> 0,90 |
0,98 |
0,98 |
Good fit |
NNFI (Non-Normed Fit Index) |
> 0,90 |
0,98 |
0,98 |
Good fit |
IFI (Incremental Fit Index) |
> 0,90 |
0,99 |
0,99 |
Good fit |
RFI (Relative Fit Index) |
> 0,90 |
0,97 |
0,97 |
Good fit |
Measurement
model fit criteria is measured based on the validity of each indicator variable
on its latent variable. An indicator variable is said to be valid if it has the
value of standardized loading factor higher than the tolerated loading factor
limit, which is ≥ 0,50 and has the t-value of above 1,96 (WIJANTO,
2008). Table 5 reveals that the loading factor value of each indicator meets
the validity requirements as shown by the value of standardized loading factor
of ≥ 0,5 and t-value of above 1,96 (significant). Figure 2 portrays the results
of measurement of both SEM models
Table 5: Loading factor values of indicators in each SEM model
Latent variabel |
Indicator variables |
Loading factor |
||
hijup.com |
Instagram |
|||
Lifestyle (X1) |
Time-oriented lifestyle (X1.1) |
0,55 |
0,64 |
|
Network-oriented lifestyle (X1.2) |
0,78 |
0,69 |
||
Price-oriented lifestyle (X1.3) |
0,74 |
0,92 |
||
Perception (X2) |
Access (X2.1) |
0,86 |
0,83 |
|
Search (X2.2) |
0,87 |
0,87 |
||
Evaluation (X2.3) |
0,87 |
0,72 |
||
Transaction (X2.4) |
0,89 |
0,79 |
||
Delivery (X2.5) |
0,91 |
0,85 |
||
After-purchase (X2.6) |
0,70 |
0,54 |
||
Customer satisfaction (X3) |
Online shopping experience satisfaction (X3.1) |
0,88 |
0,91 |
|
The pleasure of online shopping (X3.2) |
0,88 |
0,95 |
||
Online shopping decision (X3.3) |
0,90 |
0,90 |
||
Preference (X4) |
This media is the main choice in online shopping (X4.1) |
0,90 |
0,94 |
|
This media is more favored in online shopping (X4.2) |
0,90 |
0,92 |
||
Re-purchase intention (Y1) |
Intend to continue purchase (Y1.1) |
0,93 |
0,92 |
|
Keep on making purchases (Y1.2) |
0,91 |
0,96 |
||
Regularly make purchases (Y1.3) |
0,89 |
0,82 |
||
Note : If the value of Standardized Loading Factor (SLF) ≥ 0,5, the
indicator variable has a good validity
Figure 2: The output of SEM
measurement model of hijup.com and Instagram
Note: * significant at the significance level of 5% (calculated t-value is greater than 1,96)
The relationship between indicator variable and its
latent variable is equal to the loading factor value of the variable on its
forming variable. The highest loading factor value indicates that the indicator
variable is the factor that contributes the most to the forming of latent
variable. The higher the loading factor value, the greater the contribution of
an indicator variable to the forming of latent variable.
In the SEM model of hijup.com, network-oriented
lifestyle indicator is the indicator which contributes the most to the
online-shopping-related lifestyle. Consumers who have network-oriented
lifestyle mean that they spend every day with internet, for example working by
using internet and receiving huge number of e-mail each day. In online shopping
in hijup.com, orientation on internet network is indeed a very important thing
compared to the other indicator. It is different with the SEM model of
Instagram in which price-oriented lifestyle owns the highest contribution on
the lifestyle variable. The respondents feel that in shopping in Instagram,
price is the first priority. It is possible because the price in Instagram are
cheaper and more diverse from various sellers. Such price-oriented lifestyle
refers to the cheaper price of products offered in internet (MOHAMED et al, 2014).
In SEM model of hijup.com, the delivery indicator
holds the largest contribution on perception. It indicates that respondents
feel comfortable when the goods the bought have a little possibility of damage
or defect, are according to their expectation, and delivered in a timely
manner. It is possible because hijup.com has a stringent quality control and an
updated stocks according to its website. The products delivered must be
declared to be not damaged and according to the online shop’s website (MISHRA;
MATHEW, 2013).
In the SEM model of Instagram, the search indicator
has the top contribution. It indicates that the respondents feel comfortable
when they search the products they desire. Instagram owns hashtag facility so
that it facilitates consumers to look for products from various sellers and
they can choose the products as desired. The convenience in searching holds the
largest portion of total variance, centralized on the user-friendly website,
various choice of search, and the fast process of finding the desired product (JIANG et al, 2012).
In the
In the SEM model of hijup.com, the indicator of this
media is the main choice and more favored in online shopping have the equal
contribution on preference. Meanwhile, in the SEM model of Instagram, the
indicator of this media is the main choice has a higher contribution on
preference than the indicator of this media is more favored in online shopping.
It indicates that the respondents prefer Instagram because Instagram is chosen
as the main choice in online shopping. It also indicates that respondents
prefer Instagram to hijup.com to buy Muslim clothing’s.
In the SEM model of hijup.com, the indicator of intend
to continue purchase is the highest of all indicators of re-purchase intention.
It shows that consumers only have the intention to re-purchase someday.
Meanwhile, in the SEM model of Instagram, the indicator of keep making
purchases is the highest of all indicators of re-purchase intention. It
indicates that the re-purchase intention to keep making purchases exists in
Instagram. Based on that comparison, Instagram is more favored than hijup.com
to do a re-purchase.
A Table 6 and
Table 7 show the causal relationship between variables. The relationship
between lifestyle (X1) and perception (X2) variable have the calculated t-value
> 1,96, which are 12,86 (hijup.com) and 10,98 (Instagram). It means that
lifestyle significantly affects perception variable. It is in line with the
research conducted by Mohamed et al, (2014) which states that lifestyle has an effect on
perception.
Tabel 6. Hypotheses testing
of the SEM model of hijup.com
Causal relationship |
Path coefficient |
|t-value| |
Information |
|||
Lifestyle (X1) à Perception (X2) |
0,89 |
12,86 |
Significant |
|||
Perception
(X2) à Customer satisfaction (X3) |
0,77 |
12,05 |
Significant |
|||
Customer
satisfaction (X3) à Preference (X4) |
0,74 |
11,29 |
Significant |
|||
Perception
(X2) à Re-purchase intention (Y) |
0,07 |
1,01 |
Not significant |
|||
Customer
satisfaction (X3) à Re-purchase intention (Y) |
0,01 |
0,07 |
Not significant |
|||
Preference (X4) à Re-purchase intention (Y) |
0,83 |
10,24 |
Significant |
|||
The
relationship between perception (X2) and customer satisfaction (X3) variable
have the calculated t-value > 1,96, which are 12,05 (hijup.com) and 12,61
(Instagram). It means that perception has a significant effect on customer
satisfaction variable. The more positive consumer perception on a media, the
more satisfied the consumer is. It is in accordance with the research undertaken by Mohamed et al, (2014) which states
that perception has an effect on customer satisfaction. Customer
satisfaction reflects the level of positive feeling felt by the customer towards the service providers
and it is important for the service providers to understand customer perception
on their service (PRATMININGSIH et
al, 2013).
Tabel 7: Hypotheses testing
of the SEM model of Instagram
Causal relationship |
Path coefficient |
|t-value| |
Information |
||
Lifestyle (X1) à Perception (X2) |
0,80 |
10,98 |
Significant |
||
Perception (X2) à Customer satisfaction (X3) |
0,80 |
12,61 |
Significant |
||
Customer satisfaction (X3) à Preference (X4) |
0,79 |
14,28 |
Significant |
||
Perception (X2) à Re-purchase intention (Y) |
0,17 |
2,10 |
Significant |
||
Customer satisfaction (X3) à Re-purchase intention (Y) |
0,10 |
0,90 |
Not significant |
||
Preference (X4) à Re-purchase intention (Y) |
0,61 |
7,05 |
Significant |
||
In
Instagram model, perception variable has an effect on re-purchase intention. It
is in accordance with the study carried out by Jiang et al, (2012) and Chao et al,
(2008). It indicates that the more positive the view on Instagram, the more
increased the intention to buy in Instagram is. On the contrary with the
measurement result of the SEM model of Instagram, perception has no significant
effect on re-purchase intention in the SEM model of hijup.com, which is aligned
with the research conducted by Liat and Wuan (2014) in the University of Malaysia which reveals
that convenience perception has no significant effect on online re-purchase
intention. The respondent’s view regarding convenience on Instagram and
hijup.com is different. It perhaps due to the feedback from Instagram which is usually
faster than hijup.com or web-based e-commerce. In addition, in terms of
transaction of order, payment, and complaint, online shops utilize messenger
(chatting) applications, such as Whatsapp and Line which enables an immediate
response from the sellers. Such convenience felt by the customers towards the
online shops generates the re-purchase intention.
In both SEM model of hijup.com and Instagram, customer
satisfaction variable has a positive effect on preference variable, based on
the calculated t-value > 1,96. Thus, the more satisfied the consumer is, the
higher the preference to use the media for online shopping. It is in line with
the research undertaken by Jamal and Good (2001) and Devaraj et al, (2002) which declares that satisfaction has an effect on
consumer preference.
In both SEM models, customer satisfaction variable has no
significant effect on re-purchase intention. It is from the calculated t-value
< 1,96. It indicates that respondents’ satisfaction in online shopping in
both hijup.com and Instagram has an effect on re-purchase. It indicates that
respondents’ satisfaction has no effect on re-purchase intention. It is in line
with the research carried out by Akhter (2010) which proclaims that
satisfaction has no direct effect on re-purchase.
The relationships between preference and re-purchase intention
have the calculated t-value > 1,96, which are 10,24 (hijup.com) and 7,05
(Instagram) which mean that preference has a significant effect on re-purchase
intention variable. It indicates that the more consumers favor the media used,
the more increased their re-purchase intention in the media used. It is aligned
with the research done by Mohamed, Hussein, Zamzuri and Haghshenas
(2014) which states that preference has an effect on re-purchase intention.
Consumer preference on internet retailer is an important component to acativate
and strengthen the behaviour intention (OVERBEE; LEE, 2006).
Hellier et al, (2003) finds out the
relationship between brand preference and re-purchase intention.
The demographic segmentation of both online shopping
media of Muslim clothing is women with an age ranging between 25 to 34 years
old and have the income of more than Rp 5.000.000 per month. The psychographic
segmentation of Muslim clothing is addressed for women with price-oriented and
network-oriented lifestyle.
The targeted consumer of both online shopping media of
Muslim clothing is teen and adult aged group with a quite high income and
categorized as upper middle society. Consumers of Instagram put more emphasis
on price-oriented lifestyle which means that cheap price is what they pay
attention to when they want to do online shopping. On the other hand, consumers
of web-based media put more emphasis on network-oriented lifestyle because they
feel more comfortable with the user interface and user experience of the
website.
The positioning of both online shopping media of Muslim
clothing is shopping media which prioritize customer convenience and offer a
practical use. Online shopping is shopping activity which enable the seller and
buyer to not directly meet. Therefore, there needs to be a service enhancement
in both the media especially in terms of
after-purchase so that the customers will have no regret to do online shopping
and have a re-purchase intention in that media.
4. CONCLUSION
The result of t-test revelas that there is a difference
in the dimension of price-oriented lifestyle, perception upon evaluation,
transaction, delivery, and after-purchase, online shopping experience
satisfaction, and all dimensions in preference and re-purchase intention. The
results of analysis on hijup.com show that lifestyle has a significant effect
on perception and perception has no effect on re-purchase intention. Customer
satisfaction has no effect on re-purchase intention. Consumer preference
variable has an effect on re-purchase intention.
The results of analysis on Instagram indicate that
lifestyle has a significant effect on perception and perception has an effect
on customer satisfaction. Customer satisfaction has no effect on re-purchase
intention which means that customers who are satisfied in shopping Muslim
clothings in Instagram-based online shops do not always do re-purchase there.
Consumer oreference variable has an effect on re-purchase intention, which
means that consumers who like to buy Muslim clothings in Instagram-based online
shops tend to do re-purchase.
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