ISSN: 1204-5357

All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.

Effects of Convenience Online Shopping and Satisfaction on Repeat-Purchase Intention among Students of Higher Institutions in Indonesia

Nuryakin*

Marketing Program, Diponegoro University, Semarang and Master of Management, the Muhammadiyah University of Yogyakarta, Indonesia

Naili Farida

Faculty of Business and Economics, Diponegoro University, Semarang, Indonesia

*Corresponding Author:
Nuryakin
Marketing Program, Diponegoro University Semarang and Master of Management the Muhammadiyah University of Yogyakarta, Indonesia
Tel:
+628569985299
Email: [email protected]

Visit for more related articles at Journal of Internet Banking and Commerce

Abstract

The purpose of the research is to empirically study the students perceptions towards facilitation in online shopping on particular products online. The research design used quantitative approach through research instrument. The unit of analysis in this study was Indonesian students who have done online shopping. The data were gathered through face to face distribution by the researcher. Purposive sampling was used to collect sample of this research. The total respondents under this study were 212 who were students of five Universities in Surakarta area, i.e. Health Polytechnic of Surakarta, Muhammadiyah University of Surakarta, Sebelas Maret University of Surakarta, Unggulan Polytechnic of Sragen, and AUB Economics College of Surakarta. This research indicated that all dimensions of convenience in online shopping (access convenience, information convenience and transaction convenience) have a positive effect towards consumer’s satisfaction. These empirical research findings have also shown the significant positive effect of the consumer’s satisfaction towards repeatpurchase intention. This research has also given theoretical contribution towards Fishbein and Ajzen theory which is also known as reasoned-action theory.

Keywords

Online Shopping; Access Convenience; Information Convenience; Transaction Convenience; Customer’s Satisfaction; Repeat-Purchase Intention

Introduction

It cannot be denied that for the past 10 years, the internet growth in Indonesia has been significantly increasing. It can be seen from the number of users, penetration, and also from connection quality viewpoints. The fact is also supported with the widespread use of various mobile devices by different levels of society in Indonesia. A study published by Indonesian Internet Service Providers Association (APJJI) indicated the behaviors of Indonesian internet users in 2012 could be observed from internet usage penetration in the Indonesian urban area which reached 24.23% [1]. The number means an outstanding potential, when, in fact, is compared with the total population of Indonesian people which reaches 260 million. The number is also categorized as a massive number when it is compared to the internet penetration in the neighboring countries of Indonesia, as : Vietnam about 47.3 million people, Philippines 47.13 million people, Thailand 38 million people, Malaysia 20.62 million people and Singapore 4.65 million people [2].

Pentina, Amialchuk [3], investigate the impact of global economy which came for the emerging of economy recession has caused in increasingly challenges from the retailers towards the consumers to save money through the empowerment model of selling goods, creating goods as commodity, the existence of fragmented market, and competitiveness intensification. Moreover, Pentina, Amialchuk [3], have also explained that online retailers have unique strategy and opportunity in taking the main role within the global market by providing free locations; information rich retail services that enable them in managing consumers.

On the other perspective, long term condition and trend in the world business are on the stage of economy shifting from goods and services and the emerging expansion from economy information and electronic business. The two model of business becoming the e-service concept, a service provider via electronic network, such as internet [4]. Moreover, this e-service advantage model has become a capability of competitiveness differentiation.

The studies on online shopping have been conducted [5-8]. A research finding from Gehrt, Rajan [9] found three identified segments in appraising online shopping behaviors, i.e. singularity value, competitive price, and business reputation. Quality price offered and reputation is a dominant segment in online shopping behavior. Jiang and Rosenbloom [7] explain that after consumers’ satisfaction with the online shopping behaviors, they tend to conduct repeated purchasing intention. Furthermore, Jiang and Rosenbloom [7] elaborated that satisfied consumers will tend to compare the price perception.

Gehrt, Rajan [9] has revealed several consumer orientations on online shopping behaviors. They are mostly caused by the websites and attribute ratings, demography factor, and consumer’s occupation. Xu and Paulins [8] explained that consumers have positive attitude towards online shopping for the clothing product type. Al-hawari and Mouakket [10] explained the antecedent of consumer’s behavior in facilitating and adopting network in online shopping behaviors.

The purpose of the research is to empirically study the student’s perceptions towards facilitation in online shopping on particular products online. Furthermore, this research also aims to contribution and evidence for reasoned-action theory, individual attitude is antecedent as a intention determinant in carrying actions, and viewed as predictor of the behaviors [11]. This study attempts to investigate the relationship between convenience in online shopping with three dimensions (search convenience, transaction convenience, and access convenience) which are developed in Jiang, Yang [12] study in influencing online purchasing satisfaction toward affecting repeat purchasing intention.

Theoretical Background and Hypothesis Development

Consumer Perception in Online Shopping

A consumer approach towards purchasing action is known as shopping orientation [9]. The basic assumption of shopping orientation is that consumers often utilize various different approaches in conducting a shopping behavior. Pentina, Amialchuk [3] stated that sensory, cognitive, pragmatic, and relational online experiences are types of new experiences of online shopping in the form of interactive or involvement. Furthermore, online shopping experience is the consumer’s involvement with the online shops, friends, and other buyers via online shops. According to Sabiote, Frías [13] study, found out that the perceived quality in a service has an important role in the consumer purchasing decision.

The study on services for the past 20 years have been done in the field of offline service quality, taking the consumer’s satisfaction as the key result of the service quality and determinant factor in the organization long term performance [14]. Furthermore, the same study has also mentioned way of consumer in appraising online service quality.

The various study have explained different works which attempt to identify the most exact dimension to measure the online service quality. From those various studies on service quality, the scale mostly used was from Parasuraman, Zeithaml [14] which is also known as E-S-Qual. Those dimensions consist of four related dimensions, they are: efficiency, fulfillment, system availability, and privacy. However, one of the most determining factor is system service by facilitating internet that potentially offers some crucial information. Furthermore, in the studies of tourism service providers often include all information on information they offer, include those irrelevances, that instead, bring more difficulties for tourists in decision making.

Several previous studies have also tested service quality on distribution channel [15] and its effect on internet service quality by developing an e-SQ (e-Service Quality) scale. In the study, e-Service Quality is defined as how far the website in facilitating effective and efficient purchasing for consumers. Study Chang and Wang [16] showed that e-service quality perceived by the consumers gives effects on consumer’s satisfaction value and then affects consumer’s loyalty. In addition, the research also revealed that the consumers have high satisfaction value with stronger relationship between consumer’s satisfaction and loyalty, yet, perceived low in the satisfaction value. Kim and Eom [17] concluded that a site design of a web plays a pivotal role in reaching internet users’ satisfaction.

Repeated-Purchase Intention

Repeat purchase intention is determined by various important variable (antecedent), for example inertia and satisfaction [18], hedonic value and utilitarian value [19], and perceived justice and satisfaction [20]. Repeated-purchase intention has become an important attention for the organization in improving their product selling value [21].

Kuo [18] explained that repurchasing intention as a process of how far the consumer’s willingness in purchasing similar products or services, simple, objective, and predictor which can be observed from the future purchasing behaviors. Consumer’s intention in repurchasing is very important in success business profitability. Reichheld and Sasser [22] indicated that 5 percent of improvement on consumer’s retention can increase the profit up to 25-85 percent and the cost to attract new customers is about fivefold than defending old customers.

Some service organizations have tried maximally in defending consumers due to the higher competition and cost in defending the existing customers. Several other researchers found that determinant factors in repeated purchasing can be understood through investigation towards customers’ behavior to change brand [23]. Furthermore, Bansal, Taylor [23] offered a PPM (pushing, attracting, and tethering) approach which is a migration model to investigate a customer’s service provider with the customers’ behavior who move to other products or services.

Purchasing intention in the context of online shopping has been studied by [24]. In addition, Park and Stoel [24] stated that either internal, e.g. brand closeness, previous shopping experience, external, e.g. information on website, or information searching can improve the consumer’s intention in shopping or repurchasing via internet which usually leads to the stage of purchasing decision making. Shim and Drake [25] explain the previous experience in shopping via internet, trust in shopping via internet, and attitude towards shopping in the internet positively affect the purchasing intention through internet. Consumers with previous experience in shopping via internet and their attitude trust towards shopping intention in internet give huge influence than consumers with low experience in shopping via internet.

Consumer’s Satisfaction

Many studies on consumer’s satisfaction have been investigated on the various contexts and analysis units (e.g. [6,26-30]). Consumer’s satisfaction can be determined by organization flexibility and organization strength that will create a cognitive legitimacy and eventually end on the consumer’s satisfaction [31]. However, Pentina, Amialchuk [3] found that the role of experience support in online shopping such as sensory, cognitive, pragmatic, and relational as the new form of online shopping behaviors. Furthermore, Pentina, Amialchuk [3] also explained the consumer’s involvement and their friends and other consumers in online shopping have also affected the consumer’s satisfaction. The study has also revealed that the role of mediation from the browser satisfaction in improving selling and service channel of online shopping.

Several concepts on consumer’s satisfaction have also experienced changes in the last few decades [32]. Consumer’s satisfaction, in the study, is defined in different perspectives. Consumer’s satisfaction concept has been accepted by many in very wide scope of research, although satisfaction is an effective response followed by experience and expectation confirmed with involving cognitive process [33]. Furthermore, it is explained that consumer’s satisfaction is an evaluation on service performance; the consumer compares output with their expectation before purchasing or consuming.

Consumer’s satisfaction in carrying transaction is classified as consumers’ evaluation on their experience and reaction towards particular product in transacting or reacting on service [33]. Meanwhile, other researchers viewed two different concepts towards consumer’s satisfaction [34]. According to them, when a more specific satisfaction in conducting transaction was asked, the consumers tended to give comments on certain event in transaction service (for instance, certain employee’s action). Conversely, the consumers tended to give comment on general impression and experience with company (like company’s honesty) when they were asked on the overall satisfaction. Satisfaction in transaction is a psychological reaction that product or service provider consumer should be oriented on particular long term performance [33].

Service quality, consumer’s satisfaction, and consumer’s intention become crucial factors for the success of a business [21]. Various studies have been done in testing the role of consumer’s satisfaction and consumer’s loyalty (e.g. [18,26,28(p.19),35]). Those studies underlined the importance of satisfaction concept and consumer’s value that give effect towards consumer’s behavior in the future time (consumer’s loyalty). Nagy and Kacmar [31] stated that one of the positive and negative attributes related to the satisfaction level still needs to be explored. Furthermore, consumer’s satisfaction is explained as the one’s good feeling resulted from comparing related product, service, or experience of a business with the hope the product or service gives experience beyond expectation.

Convenience in Online Shopping

A study in online shopping facilitation has explained that comfort is a concept in the consumer’s purchasing [12]. SERVCON measurement developed in the context of offline shopping does not apply unique aspect approach of online shopping comfort since the online retailers utilize internet as the shopping platform. Various previous literatures have proven the online service quality concept by identifying some dimensions of service comfort like unique feature with dimension like facilitation in interactivities usage, information browsing, information in depth and richness, and security [14]. Unfortunately, though service comfort strategy for the success of online retailers is pivotal, researchers have only given little portion in their empirical studies which proved the important dimension of online shopping comfort and in depth related features.

In the study developed by Oliver [33], explained that a marketer tends to require satisfaction concept as an evaluation with cognitive attribute basis but as the emotional response towards product during accessing a service. Also, basically, the current competition is taking place at the augmentation product level. Augmentation product leads the marketers to look at the users’ consumption system: ways of users in conducting duties to get and use the pertinent product and service.

With the increasing number of e-commerce usage in fulfilling the service need and value, now it shifts to the virtual world [36]. Different dimensions in measuring online shopping facilitation have been reviewed by many researchers, which mostly aimed to develop measurement scale based on the media developed. Jiang and Rosenbloom [7] stated that product/service selling process in e-commerce which generally consists of pre selling service, (information mode, product development, and comparison offering) transaction (trade and finance), physical order fulfillment, and post selling service. The selling process is focused on the physical and virtual activities and challenges in fulfilling the consumer’s expectation in every single stage of shopping process.

This research adopted online shopping facilitation dimension which has been developed by several previous researchers. The three dimensions are access convenience, information search convenience, and transaction convenience.

Hypothesis Development

The Relationship between Online Shopping Convenience and Consumer’s Satisfaction

A study from Pentina, Amialchuk [3] concluded that the existence of retailers as inside the stores and online shopping experience with the sensory, cognitive, pragmatic, and relational approaches are new types of online shopping experience (interactive/involvement). Further, Pentina, Amialchuk [3] explained that the consumer’s involvement with online shops, friends, and other buyers through direct meeting have become a determinant factor in affecting the consumer’s attitude. The role of searching satisfaction mediation in improving selling and traffic during online shopping is also pivotal for the company.

Another study from Then and Then and DeLong [37] reported that the information access through website will become a useful source in the market where probably the consumer has no access to the retail stores. Meanwhile, Johnson, Lennon [38] mentioned that although there are only 19 percent of today’s internet users are from big cities with population less than 50.000, consumers from low class society will tend to choose online shopping as the number of choices for small retail community is getting lower. Consumers tend to do online shopping for they assume that it is profitable, simple, compatible, and low risk. Based on the above elaborations, the hypothesis can be drawn as follows:

H1: Access Convenience Positively Affects the Consumer’ Satisfaction

Another study developed by Jiang, Yang [12] concluded that consumers require comfort in their variation organization to carry out shopping. Even though, online shopping comfort is one of the main factors considered by the consumer in accessing online retailer websites, many previous researches which assessed on e-commerce which was treated in building comfort as one of the predictor variables, like consumer service and trust, that give effect on result variable, such as consumer’s satisfaction and attitude intention [31].

A study on the online shopping role was done by Xu and Paulins [8] who found that the elements which encourage the consumers to repurchase online clothing product include web page design, navigation facilitation, information searching, and security warranty. In addition, the online buyers’ growth is bigger than the internet users’ growth which indicated that the internet users require comfort in online shopping. Based on the above explanations, the hypothesis can be drawn as follows:

H2: Information Searching Convenience Positively Affects the Consumer’s Satisfaction

The consumer’s concern on payment security and its relation with attitude towards shopping in internet have been investigated deeper by [39]. Overall, the respondents involved in the research felt comfort in using internet to have online shopping during the previous six months. In addition, [39] have also observed the relation between attitude towards internet shopping and the concern on the online payment security. Consumers with positive attitude towards online shopping seem to less concern about the payment security.

A study on perception towards online shopping conducted by [8] outlined the role of students’ behavior in using internet combined with the market strength currently growing and the possibility in developing consumer’s loyalty is interesting to be studied on the consumer group and their behavior intention in online shopping. Meanwhile, [38] argued that the consumer’s knowledge and experience affect their decision to buy goods online, the amount of money spent during the online purchasing has motivated retailers to understand consumer’s shopping habit and desire. Those elaborations above have led to the following hypothesis:

H3: Transaction Convenience Positively Affects Consumer’s Satisfaction

The relationship of consumer’s satisfaction and Repeated-Purchasing Intention

A study done by Ryu, Han [19] showed that the hedonism and utilitarian values significantly affect consumer’s satisfaction and towards repeated-purchasing behavior intention as well. Further, Ryu, Han [19] concluded that the consumer’s satisfaction and intention give bigger effect rather than the hedonism value. This research has also confirmed that the consumer’s satisfaction plays as the partial mediator of the relationship between hedonism/utilitarian and purchasing behavior intention.

Consumer’s satisfaction relation with the repurchasing intensity on the different respondent coverage has been studied by many researchers as Wang and Po-Lo [21] who found that service quality, customer value, and customer satisfaction own powerful relationship towards purchasing intention within the telecommunication industry area. Moreover, Wang and Po-Lo [21] also explained the importance of organization to focus on the satisfaction and attention towards their consumers.

Consumer’s perception and satisfaction are the bases for the competitive excellence and value creation perceived by the consumers [31]. In fact, the essence of the consumer’s value creation within the new organization development contexts is defined by consumer’s perception and satisfaction [40]. The company should understand how the organization plays an important role in their ability to manage consumer’s perception and satisfaction level in order to create value and guarantee the consumer’s satisfaction.

Those previous researches explained above have led to the following hypothesis:

H4: Consumer’s Satisfaction Positively Affects Consumer’s Repeated Purchasing Intensity

Method

Research Design and Unit Analysis

This research employed quantitative research by developing reliable and valid research instrument on online shopping comfort as perceived by the consumers. The unit analysis of this research was Indonesian students who have ever done online shopping. The students came from five colleges in Surakarta region, they are: Health Polytechnic of Surakarta, Muhammadiyah University of Surakarta, Sebelas Maret University, Unggulan Polytechnic of Sragen, and AUB Economics College of Surakarta.

Operational Definition and Scale Measurement

Operational definition of each variable is explained as follows:

Facilitation in online shopping: Online shopping convenience is an identification of several comfort service of unique feature for online shopping which indicates several materials include in online service quality, like usage convenience, interactivities, information searching, information in depth and richness, and security [14]. This research developed dimension and indicator of the online shopping convenience which reflective indicator:

a. Access convenience, with access time flexibility, site searching convenience, and access place flexibility indicators.

b. Search convenience, with interesting web design quality, information searching convenience, and product searching speed indicators.

c. Transaction convenience, with payment convenience, payment access flexibility, and assurance in payment indicators.

Consumer’s satisfaction: Consumer’s satisfaction is defined as consumers’ evaluation on their experiences and reactions towards certain products during transaction and reaction on services [33]. Indicators of consumer’s satisfaction consist of: Satisfaction on product price, satisfaction on goods quality, satisfaction on the suitability of the information with the goods received.

Repeat-purchase Intention: Kuo, Hu [18] stated that repeated purchasing intention is an effort done by the consumers in how far they are willing to repurchase the same product or service in the future. Indicators of repeated purchasing intention include: repeated purchasing for the similar product, giving product reference to other people, using the same site in conducting repeated purchasing.

All the variables in this research, i.e. online shopping convenience construct, consumer’s satisfaction, and repeat-purchase intention, were measured with questionnaire by using likert-scale with answer scale 1–7. The scale represented the rating from ‘strongly disagree’ to ‘strongly agree’.

Research Sample

The sample in this research was the students in five colleges in the Surakarta, namely: Health Polytechnic of Surakarta, Muhammadiyah University of Surakarta, Sebelas Maret University, Unggulan Polytechnic of Sragen, and AUB Economics College of Surakarta. Total respondents were as many as 212 Students.

The data were gathered through face to face distribution by the researcher.

Purposive sampling was used to collect sample of this research. According to Sekaran [41], the method was used on the basis of certain considerations and goals of a researcher. In this research, the researcher considered the respondents who have at least 3 times conducted online product shopping.

Screening and Data Analysis

Screening and validation of research instrument: Data screening test on the first stage of data processing in this research were carried out in two steps, data normality and data outlier checking. The total respondents under this study was 212 who were students of five colleges in Surakarta area, i.e. Health Polytechnic of Surakarta, Surakarta Muhammadiyah University, Sebelas Maret University, Unggulan Polytechnic of Sragen, and AUB Economics College of Surakarta. Based on the survey distributed, 197 questionnaires were filled completely. 15 questionnaires did not meet the qualification. However, 23 questionnaires were considered as outlier during the data processing, thus, they must be dropped from the research sample. At last, the total remaining sample of this research was 174 respondents.

Hypothesis test in this research using Structural Equation Modeling (SEM) on AMOS 21 program. Indicators that create construct by observing parameters which resulted in goodness of fit. Model measurement would employ convergent validity to test those indicators, whether valid or not in measuring what should be measured. Estimation likelihood maximum technique was used in this research. Next, we assessed the questionnaire item by applying confirmatory factor analysis to test the construct relation with the indicator based on the developed theory, while, cronbach alpha (Cronbach’s α) was used to test reliability.

Confirmatory factor analysis test result showed the value for loading factor in each question item was >0.5, which can be concluded that all the question items were valid.

Meanwhile, cronbach alpha (α) value for each construct was >0.6, which explains that all constructs were reliable [42].

The research concluded that the indicators can be explained to measure construct.

Results

The hypotheses testing in this research using Structural Equation Modeling (SEM) analysis with AMOS program. The Structural Equation Modeling (SEM) test result on full model can be seen in Figure 1. Table 1 explained the assumption test result in Structural Equation Modeling (SEM) development. Confirmatory test of full model exposed fit model which means complied with goodness of fit criteria. Model structure was used to draw research causality models with structural relationship. The test result showed the goodness of fit was Chi-Square=121.302. The probability=0.004, TLI=0.962, GFI=0.922, AGFI=0.887, and RMSEA=0.052. Although the cut off value of Chi-Square and probability value have not met the required cut-off yet, however, the TLI, GFI, AGFI, and RMSEA values have already met the required cut off [43]. It indicates that the research model is fit and meets the standard criteria.

Reflective scale names and items (measured on 1 – 7 point Likert-scale indicating the extent to which respondent agrees with following statements) Cronbach alpha(α) Standardized Factor Loading
Access Convenience
Access time flexibility 0.660 0.810
Site searching convenience 0.756 0.703
Access place flexibility 0.724 0.738
Information Convenience
Interesting web design quality 0.712 0.820
Information searching convenience 0.808 0.725
Product searching speed 0.726 0.796
Transaction Convenience
Convenience in payment 0.801 0.800
Payment access flexibility 0.738 0.889
Assurance in payment 0.833 0.748
Customer Satisfaction
Satisfaction on product price 0.761 0.741
Satisfaction of goods quality 0.670 0.758
Satisfaction on the suitability of the information with the goods received 0.749 0.734
Repeat-purchase Intention
Repeated purchasing for the similar product 0.843 0.850
Giving product reference to other people 0.842 0.846
Using the same site in conducting repeated purchasing 0.836 0.859

Table 1: Scale item for measures.

Figure

Figure 1: Full model convenience in online shopping, customer’s satisfaction and repeat purchase intention.

Table 2 indicated that standardized path coefficients of the relationship between access convenience, information convenience, transaction convenience on customer’s satisfaction and repeat purchase intention. Furthermore, the result was shown in Table 1 which 4 hypotheses. Meanwhile, the path analysis test result on each construct can be seen in the following table.

Hypothesis Structural path Standardized path coefficients t value Prob. Result
H1 access convenience → customer’s satisfaction 0.236 2.367 0.018 Significant
H2 information convenience → customer’s satisfaction 0.212 2.611 0.009 Significant
H3 transaction convenience → customer’s satisfaction 0.317 4.511 0.000 Significant
H4 customer’s satisfaction → repeat-purchase intention 0.943 7.399 0.000 Significant

Table 2: Structural parameter estimates: Path analysis model (n=174).

Relationship between Convenience Online Shopping on Customer’s Satisfaction

The result of hypothesis 1 explains that the relationship between access convenience on consumer’s satisfaction was shown with t value and probability values which positive and significant relationship. The structural path findings indicated that there was a significant and positive relationship between the access convenience on customer’s satisfaction (t=2.367>1.96) with significance value (0.018<0.05). Thus, hypothesis 1 is accepted.

This study is support the research by Pentina, Amialchuk [3] who concluded that the consumer’s involvement with online shopping, reference and other buyers have become a crucial determinant factor in affecting the consumer’s attitude. The role of searching satisfaction mediation in toward selling and traffic of online shopping is also crucial for the organization.

Another study which supported this research result was Then and DeLong [37] who found information access on website will become useful sources for the online retail shops. Meanwhile, Johnson, Lennon [38] in his research viewed consumers as profitable, simple, compatible, and low risk things when conducting access on online shopping model.

The verification result for hypothesis 2 revealed the relationship between information convenience with consumer’s satisfaction as seen from t value and probabilities values which indicated positive and significant relationship. The structural path findings indicated that there was a significant and positive relationship between the information convenience on customer’s satisfaction (t=2.611>1.96) with significant value (0.009<0.05). Therefore, hypothesis 2 is accepted.

The empirical result of this study is in line with the research finding from Jiang, Yang [12] who concluded that customers need convenience in their variation organization for shopping. Meanwhile, another researcher found that online shopping convenience as one of the main factors considered by the consumers in accessing online website [31].

A study on the role of online shopping conducted by Xu and Paulins [8] was also in line with this research finding which found that the booster elements for consumers to buy online clothing product include web page design, navigation and information searching convenience, and security warranty. Consumers will tend to find detailed information on product they are going to buy.

The verification result for hypothesis 3 found the relation between transaction convenience with the consumer’s satisfaction as seen in t value and probability values which indicated the positive and significant relationship. The structural path findings indicated that there was a significant and positive relationship between the transaction convenience on customer’s satisfaction (t=4.511>1.96) with significant value (0.000<0.05). Thus, hypothesis 3 is accepted.

This research finding supports the previous study on perception study towards online shopping done by Xu and Paulins [8] who found the students’ behavior role in using internet which is combined with current growing market strength. Furthermore, it elaborated the importance for other researchers in developing consumer’s loyalty on consumer group and their behavior intention in online shopping.

Relationship between Customer’s Satisfaction on Repeat-Purchase Intention

The verification result for hypothesis four found the relationship between customer’s satisfaction on repeat-purchase intention as seen from t value and probability values which indicated positive and significant relationship. The structural path findings indicated that there was a significant and positive relationship between the customer’s satisfaction on repeat-purchase intention (t=7.399>1.96) with significant value (0.000<0.05). Hypothesis 4 is accepted.

This research result support the previous research by Ryu, Han [19] with the result that hedonism and utilitarian values give influence on the customer’s satisfaction and repeated purchasing. Another research is also in line with this study which revealed the relationship between customer’s satisfaction and repeated-purchasing intent [21].

Nagy and Kacmar [31] have claimed that the consumer’s satisfaction is the basis of competitive advantage and value creation perceived by the customers. Moreover, a view from [40] have confirmed the research findings here which explained the importance of an organization in managing consumer’s perception and satisfaction categories in order to create value and guarantee the customer’s satisfaction.

Managerial Implications

These research findings have empirical study that all dimensions of online shopping convenience e.g. access convenience, information convenience, and transaction convenience, has a positive effects on customer’s satisfaction during online purchasing. It indicates that the consumers, in overall, demand convenience in conducting online transaction.

This research has indicated that convenience access characterized by time flexibility in accessing information, site searching facilitation, place flexibility in accessing information have given positive influence for customer’s satisfaction. It indicates the importance for online retailers in providing complete information and easiness in accessing.

Information convenience gives positive effect towards customer’s satisfaction. It is indicates that interesting web design quality, information searching facilitation, and product searching speed have become important parts in information availability for customers that it is important for online retailers to create complete information for product offered to the customers. Online shopping retailers also need to pay attention on the easiness in online transaction like facilitation in payment, payment access flexibility, and payment assurance that enable to enhance the customer’s satisfaction.

Future research agenda will need to assess further on the direct effect of access convenience, information convenience, and transaction convenience towards repeat-purchase intention. Furthermore, another approach needs to be developed such as the combination between qualitative and quantitative approach (mixmethods).

This research has also verified the theory from Ajzen and Fishbein [44] which is commonly known as reasoned-action theory. Consumer’s attitude in conducting online shopping in this study is determined by several factors. The factors include access convenience, information convenience, transaction convenience and individual’s satisfaction as the consumers’ determinants in behaving and conducting direct actions of their behaviors.

References

  1. APJJI (2012) Profil Internet Indonesia.
  2. http://www.statista.com/statistics/265153/number-of-internet-users-in-the-asia-pacific-region/
  3. Pentina I, Amialchuk A, Taylor DG (2011) Exploring effects of online shopping experiences on browser satisfaction and e-tail performance. International Journal of Retail & Distribution Management 39: 742-758.
  4. Rust R (2001) The rise of e-service. Journal of Service Research 3: 283-5.
  5. Ballester ED, Espallardo MH (2008) Building online brands through brand alliances in internet. European Journal of Marketing 42: 954-976.
  6. Ho CF, Wu WH (1999) Antecedents of Customer Satisfaction on the Internet An Empirical Study of Online Shopping. Proceedings of the 32nd Hawaii International Conference on System Sciences.
  7. Jiang P, Rosenbloom B (2005) Customer intention to return online price perception, attribute-level performance, and satisfaction unfolding over time. European Journal of Marketing 39: 150-174.
  8. Xu Y, Paulins VA (2005) College students’ attitudes toward shopping online for apparel products. Journal of Fashion Marketing and Management 9: 420-433.
  9. Gehrt KC (2012) Emergence of online shopping in India shopping orientation segments. International Journal of Retail & Distribution Management 40: 742-758.
  10. Al-hawari MA, Mouakket S (2012) Do offline factors trigger customers’ appetite for online continual usage. Asia Pacific Journal of Marketing and Logistics 24: 640-657.
  11. Ajzen I, Fishbein M (1980) Understanding Attitudes and Predicting Social Behavior. Prentice-Hall, Englewood Cliffs.
  12. Jiang L, Yang Z, Jun M (2013) Measuring consumer perceptions of online shopping convenience. Journal of Service Management 24: 191-214.
  13. Sabiote CM, Frías DM, Castañeda JA (2012) The moderating effect of uncertainty-avoidance on overall perceived value of a service purchased online. Internet Research 22: 180-198.
  14. Parasuraman A, Zeithaml A, Malhotra A (2005) E-S-QUAL: a multiple-item scale for assessing electronic service quality. Journal of Service Research 7: 213.
  15. Zeithaml VA, Parasuraman, Malhotra A (2001) A conceptual framework for understanding e-service quality: implications for future research and managerial practice. Marketing Science Institute, Cambridge pp: 01-115.
  16. Chang HH, Wang HW (2011) The moderating effect of customer perceived value on online shopping behaviour. Emerald Group Publishing Limited 35: 333-359.
  17. Kim EB, Eom SB (2002) Designing effective cyber store user interface. Industrial Management & Data Systems 102: 241-51.
  18. Kuo YF, Hu TL, Yang SC (2012) Effects of inertia and satisfaction in female online shoppers on repeat-purchase intention. Managing Service Quality 23: 168-187.
  19. Ryu K (2010) Relationships among hedonic and utilitarian values, satisfaction and behavioral intentions in the fast-casual restaurant industry. International Journal of Contemporary Hospitality Management Decision 22: 416-432.
  20. Teo TSH, Lim VKG (2001) The Effects of perceived justice satisfaction and behavioural intention the case of computer purchase. International Journal of Retail & Distribution Management 29: 109-124.
  21. Wang Y, Po-Lo P (2002) Service quality, customer satisfaction and behavior intention. Journal international entrepreneur.
  22. Reichheld FF, Sasser J (1990) Zero defections: quality comes. Harvard Business Review of Industrial Organization 68: 105-111.
  23. Bansal HS, Taylor SF, James Y (2005) Migrating to new service providers: toward a unifying framework of consumers’ switching behaviors. Journal of the Academy of Marketing Science 33: 96-115.
  24. Park JH, Stoel L (2002) Apparel shopping on the Internet: Information availability on US apparel merchant Web sites. Journal of Fashion Marketing and Management pp: 158-176.
  25. Shim S, Drake MF (1990) Customer intention to purchase apparel by mail order: Beliefs, attitude, and decision process variables. Clothing and Textiles Research Journal 9: 18-26.
  26. Bowen JT, Chen SL (2001) The relationship between customer loyalty and customer satisfaction. International Journal of Contemporary Hospitality Management Decision 13: 213-217.
  27. Brunner TA, Stocklin M, Opwis K (2008) Satisfaction, image and loyalty new versus experienced customers. European Journal of Marketing 42: 1095-1105.
  28. Donio J, Massari P, Passiante G (2006) Customer satisfaction and loyalty in a digital environment an empirical test. Journal of Consumer Marketing 23: 445-457.
  29. Eggert A, Ulaga W (2002) Customer percerved value a substitute. Journal of Business & Industrial Marketing.
  30. Host V, Knie-Andersen M (2004) Modeling customer satisfaction in mortgage credit companies. The International Journal of Bank Marketing 22: 26-42.
  31. Nagy BG, Kacmar KM (2013) Increasing customer satisfaction in the new venture context. Journal of Research in Marketing and Entrepreneurship 15: 143-159.
  32. Johnson M (2001) Customer satisfaction. International Encyclopedia of the Social & Behavioral Sciences pp: 3198-3202.
  33. Oliver RL (1997) Satisfaction: A Behavioral Perspective on the Consumer. McGraw-Hill, New York.
  34. Bitner MJ, Hubbert AR (1994) Encounter satisfaction versus overall satisfaction versus quality: the customer’s voice. Service Quality: New Directions in Theory and Practice, Sage Publications, London.
  35. Kandampully J, Suhartanto D (2000) Customer loyalty in the hotel industry the role of customer satisfaction and image. International Journal of Contemporary Hospitality Management Decision 12: 346-351.
  36. Cristobal E, Flavian C, Guinalıu M (2007) Perceived e-service quality (PeSQ). Managing Service Quality 17: 317-340.
  37. Then NK, DeLong MR (1999) Apparel shopping on the web. Journal of Family and Consumer Sciences 91: 65-68.
  38. Johnson KKP (2005) Clothing and Textiles Research. An application of Rogers’ innovation model: use of the internet to purchase apparel, food, and home furnishing products by small community consumers. Journal of Fashion Marketing and Management 9: 420-433.
  39. Kwon K, Lee J (2003) Concerns about payment security of Internet purchases: a perspective on current on-line shoppers. Clothing and Textiles Research Journal 21: 174-184.
  40. Hills GE, LaForge RW (1992) Research at the marketing interface to advance entrepreneurship theory. Entrepreneurship Theory & Practice 17: 33-59.
  41. Sekaran U (2010) Research Methods for Business. New York: John Wiley & Son, Inc.
  42. Nunnally JC, Berstein IH (1994) Psychometric Theory. McGraw-Hill Series in Psychology, New York.
  43. Ghozali I (2011) Structural Equation Modelling. Semarang: BP Udip.
  44. Ajzen I, Fishbein M (1980) Understanding Attitudes and Predicting Social Behavior. Prentice-Hall, Englewood Cliffs.
https://wowcappadocia.com
https://cappadocia-hotels.com
https://caruscappadocia.com
https://brothersballoon.com
https://balloon-rides.net

https://paperio-live.com

Replica watches

https://agario.red

https://naughtyworms.com

oversatt