THE EFFECT OF LIFESTYLE, PERCEPTION, SATISFACTION, AND PREFERENCE ON THE ONLINE RE-PURCHASE INTENTION

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

3.1. Profile Respondent

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..

3.2. Online Shopping Behaviour

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.

3.3. T-Test Analysis Based on Shopping Media

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.

3.4. Overall Model Fit

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

3.5. Measurement Model 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)

3.6. The Contribution of Indicator on the Latent Variable

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 SEM model of hijup.com, online shopping decision indicator is the major contributor to the customer satisfaction. It is because consumers feel that their decision is right in online shopping in hijup.com. On the other hand, in the SEM model of Instagram, the pleasure of online shopping is the main contributor to the customer satisfaction. It indicates the pleasure felt by consumers when the products they bought are satisfactory.

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.

3.7. The Relationship of Lifestyle and Perception (H1)

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

3.8. The Relationship of Perception and Customer Satisfaction (H2)

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

3.9. The Relationship of Perception and Re-purchase Intention (H3)

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.

3.10. The Relationship of Customer Satisfaction and Preference (H4)

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.

3.11. The Relationship of Customer Satisfaction and Re-purchase Intention (H5)

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.

3.12. The Relationship of Preference and Re-purchase Intention (H6)

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.

3.13. Managerial Implications

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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