｢정보시스템연구｣ 제17권 제4호

한국정보시스템학회

2008년 12월, pp. 261～279

A Study on Searching for the Factors Affecting Customer Loyalty in B2C E-Commerce from An IS Success Perspective*

* 본 연구는 울산대학교 교내연구비 지원에 의하여 연구되었음.

** 울산대학교, 경영학부 부교수(교신저자), ypark@mail.ulsan.ac.kr

*** 신라대학교, 경영정보학과 교수, yemoon@silla.ac.kr

Yong-Tae Park**․Yong-Eun Moon***

			<목 차>
Ⅰ. Introduction Ⅱ. Literature Review 2.1 Information and system quality in B2C e-commerce 2.2 Service quality 2.3 Customer perception, attitude, and behavior: shopping experience, satisfaction, and customer loyalty Ⅲ. Methodology 3.1 Data collection 3.2 Operationalization of research variables 3.3 Reliability and validity analysis of the research instrument				Ⅳ. Data Analysis and Findings 4.1 Confirmatory factor analysis 4.2 Correlation matrix of constructs 4.3 Goodness-of-fit of the research model 4.4 Testing research hypotheses Ⅴ. Discussion and Implications of the Research Findings Ⅵ. Conclusion References Abstract

Ⅰ. Introduction

Due to it's unique characteristics, the rules governing the market mechanisms in B2C e-commerce are quite different from those in the traditional business. That is, the way customers contact e-commerce stores and business transactions are conducted are somewhat unique in B2C e-commerce than that of traditional business. Therefore, whether they like them or not, e-commerce stores  must learn to live by these new mechanisms to survive, grow, and thrive in this new business environment (Oliver, 2000).

	A Study on Searching for the Factors Affecting Customer Loyalty in B2C E-Commerce from An IS Success Perspective

｢정보시스템연구｣ 제17권 제4호, 2008년 12월

Despite the downturn of dot-com companies at the turn of the new millennium and the pessimistic outlook on e-commerce thereafter, the growth in e-commerce is expected to continue to exceed that of traditional markets (Kearns, 2005). Furthermore, considering the increasing Internet penetration rates around the world and the increase in the average amount that Internet users spend online, it can be said that the consumer demand for online goods and services is still maintaining it's momentum. This fact is well supported by a report from eMarketer estimating that the U.S. e-commerce sales(excluding travel) will reach $146 billion in 2008, up 14.3% over 2007 (eMarketer, 2008). In Europe, the size of e-commerce market grew to $133 billion in 2006 and is expected to reach $407 billion by 2011 (Anonymous, 2008). Furthermore, online retail accounted for only about 2% of total retail sales value in 2004 (U.S. Cencsus Bureau, 2006). Thus, B2C firms can still capitalize on the unique, nearly untapped opportunities offered by e-commerce should they develop a solid understanding of what factors are affecting customer loyalty and how they are related to each other, and thereby develop effective business strategies accordingly. In other words, to be successful, B2C e-commerce stores must have a better understanding of the perceptions, attitudes, and buying behavior of diverse customer groups because understanding what influences customer attitudes and behavior can be a major determinant of a success for B2C e-commerce.

It has been a widely accepted notion that the primary enabler of e-commerce is information systems that innovated the way business transactions are conducted (Burger, 2001; Teresko, 2001). Information systems, especially the Internet,  redefined the scope of the retail market for consumer products and services in e-commerce. Thus, the success factors of B2C e-commerce must be sought from an information systems perspective, among other things. However, little research has been conducted on e-commerce success from an information systems perspective.  Therefore, this study attempts to identify the factors affecting the success of B2C e-commerce from an IS success perspective. It then proposes a structural model of B2C e-commerce success factors and investigates how they are related to each other. Specifically, this study addresses the following research question: of what are the B2C e-commerce success factors from an IS success perspective and how they are related to customer loyalty?

Ⅱ. Literature Review

Previous research on success of B2C e-commerce has been conducted in various perspectives(Kim, 2008; Kim and Kwak, 2004; Kwon et al., 2006; Suh and Jung, 2008). Kim(2008) found that both commerce function and web design function influenced the trust and familiarity of e-commerce stores and they then affected customer satisfaction. Kim and Kwak(2004) showed that institution-based trust, perceived usefulness,  and trusting beliefs affected the customer participating intention in Internet auction. Gefen(2000) reported that web site familiarity and trust had effects on the customer's intention to purchase in B2C e-commerce. Kho and Choi(2005) also showed that customer trust and web site familiarity were important factors to retain customer loyalty in Internet shopping mall. Torkzadeh and Dhillion(2002) found that such factors as vendor trust, product choice, product value, customer relation, and shopping convenience influenced the success of B2C e-commerce.

Although the primary enabler of e-commerce is information systems that innovate the way business transactions are conducted (Burger, 2001; Teresko, 2001), little research has been conducted on B2C e-commerce from an IS success perspective, as described in previous research above. In addition, customers’perception, experience, and their attitudes toward B2C e-commerce stores can influence their buying behaviors. Therefore, a solid understanding of how IS success factors influence customer perceptions, experience, attitudes, and behaviors can be a necessary condition for success in B2C e-commerce. In other words, identifying and understanding the various factors affecting customer perception and attitudes that influence their buying behavior can help e-commerce stores respond more effectively to customer needs and wants. This can eventually lead to their success (increased customer loyalty in this study) in B2C e-commerce.

2.1 Information and system quality in B2C e-commerce

IS success models (DeLone and McLean 1992, 2003; Seddon 1997) postulate that information quality and system quality are associated with net benefits, through user satisfaction and use. An empirical study (Seddon and Kiew, 1994) found that higher levels of information and system quality were associated with higher levels of net benefits. The Internet is the primary means of contact and communication between customers and e-commerce stores for business transactions in B2C e-commerce, as customers mainly obtain information about products and services provided by e-tailers from their web sites. Liang and Lai (2002) found that the quality of web site design and the quality of information contained on the web site affected consumer choice that in turn, influenced shoppers’ current and future purchases.

Angehrn (1997) asserted that providing information was the basic goal of a web site. Well-designed shopping mall web sites must provide background information regarding the company, product and/or service information, and non-commercial information to strengthen the relationship with customers (Huizingh, 2000). Liu and Arnett  (2000) also found that information quality of web sites was highly related to customer satisfaction.

Thus, it can be inferred that by providing high quality information about the products and services, e-commerce stores can positively influence customers’ perception of their shopping experience with them and help customers develop favorable attitudes toward the e-store. That is, e-commerce stores can not only make customers’ shopping experiences more convenient and pleasant, but also in turn, generate positive customer attitudes toward them by providing accurate, relevant, complete, current, and consistent information about the products and services they offer. These positive attitudes can, in turn, lead to enhanced overall customer satisfaction that can result in greater customer loyalty (Bruhn and Grund, 2000).

By the same token, a high level of system quality such as system flexibility, ease of use, ease of navigation of the web site, response time, availability, and reliability of the web site, can make customers’ shopping experience more enjoyable and give satisfaction to customers  (Jarvenpaa and Todd, 1997). This, in turn, can lead to more positive customer attitudes and subsequently result in favorable customer behavior toward Internet shopping malls(Liu and Arnett, 2000). Thus, we hypothesize:

H1: Information quality of B2C e-commerce web site will positively affect the perceived satisfaction of customer.

H2: System quality of B2C e-commerce web site will positively affect the perceived satisfaction of customer.

2.2 Service quality

Researchers (Wilkin and Hewitt, 1999; Kettinger et al., 1995) assert that service quality be included as a success measure in determining the effectiveness of information systems, since the role of the IS department is not only a provider of information systems, but also a provider of ongoing services once information systems are put in place. Others have (Moad, 1989; Rockart, 1982) argued that the quality of IS department services, as perceived by their users, is a key indicator of IS success. This argument is well supported by the fact that DeLone and McLean (2003) added the service quality construct to their original IS success model since the role of service provider of IT function is critical for the success of information systems. The revised IS success model of DeLone and McLean (2003) postulates that by providing a higher quality of customer service, organizations can expect to enhance the satisfaction of information system users and in turn, obtain more net benefits. Therefore, by applying the basic ideas of DeLone and McLean' model, it can be inferred that B2C e-commerce stores can positively affect their customers’ attitudes and customer satisfaction by providing a higher quality of customer services, both online and off-line. Empirical evidence has also shown that the quality of customer service in e-commerce is highly related to customer satisfaction (Liu and Arnett, 2000).

The cycle of business transactions in B2C e-commerce consists of contacts, transaction (buying products/services), and after-sale services. Thus, service quality can be a factor that influences customers to form their perception and attitudes toward B2C e-commerce stores and must be included in studies investigating the success of B2C e-commerce in IS success perspective. Jarvenpaa and Todd (1997) found customer service as one of the salient factors in a consumer-centered view of Internet shopping. Customers feel that web sites of B2C e-commerce are not designed to be responsive to customers’needs, especially for customer service (Jarvenpaa and Todd, 1997). This implies that many customers of B2C e-commerce are not satisfied with the quality of service they get from these stores and thus, it should be considered as an important factor in studies of B2C e-commerce success. So, it can be inferred that a higher quality of customer service can be associated with more enjoyable customer shopping experiences as well as more positive customer perception and attitudes toward e-commerce stores.

Shostack (1997) asserts that when a customer buys a tangible product (e.g. a laptop computer) he or she also buys a (intangible) service. For example, when a customer buys a laptop computer at an Internet store he or she also buys a delivery and/or warranty service. Later, he or she might need such after-sale services as technical support from the e-store. Furthermore, customers might need some additional services, such as exchange, return or refund of merchandise. Thus, a high level of service quality provided by an e-commerce store both online and off-line can be a reinforcer that can favorably influence customer perception and attitude toward the Internet store. In other words, customer service quality can be related to customer loyalty (or retention of customer) directly and indirectly, through behavioral intentions such, as saying positive things about the e-commerce store to others, recommending the company or product and/or service to others, or becoming a repeat customer (Zeithaml et al., 1996; Boulding et al., 1993; Parasuraman et al., 1991). Thus, we hypothesize:

H3: Service quality of B2C e-commerce web site will positively affect the perceived satisfaction of customer.

2.3 Customer perception, attitude, and behavior: shopping experience, satisfaction, and customer loyalty

Fishbein and Ajzen (1975, p 216) define an attitude as a person’s general feeling of favorableness or unfavorableness toward some stimuli objects. Their definition of attitude implies a strong link between attitude and behavior. The traditional view of social psychology has been that any stimulus object comes to elicit an attitude that mediates or determines responses to the object (Fishbein and Ajzen, 1975). Furthermore, a person's attitude toward an object is a function of his beliefs about the object's attributes and his evaluation of those attributes (Fishbein and Ajzen 1975, p. 253). Thus, it can be postulated that customers’ attitude deriving from their perceived customer shopping experience is a function of the stimuli objects of Internet store, such as information quality and system quality, as well as service quality. Customer shopping experience can influence overall customer satisfaction. Furthermore, customer shopping experience and customer satisfaction influence behavior; customer loyalty in this study (Bruhn and Grung, 2000). Researchers contend (Baker et al., 1992, Woodside and Trappey, 1992) that shopping experience consists of various attributes such as convenience, satisfaction, and store atmosphere and they are important determinants of patronage behavior. In this study, customer's shopping experience and satisfaction were used interchangeably. Thus, we hypothesize:

H4: Customer’s perceived satisfaction (shopping experience) will positively affect customer loyalty.

Based on the literature review above and the relationships between the constructs identified in the various literatures regarding factors affecting customer perception, attitudes, and behavior in the B2C e-commerce, this study proposes a framework of factors affecting customer loyalty in B2C e-commerce as presented in <Figure 1>.

<Figure 1> A Framework of Factors Affecting Customer Loyalty in B2C e-Commerce

Ⅲ. Methodology

This study used a survey for data collection   and a majority of question items was adopted and modified from existing studies. A structural equation modeling(SEM) approach was used for the examination of the proposed research model and research hypotheses.

3.1 Data collection

A survey questionnaire was distributed to 300 sophomore, junior, and senior students with B2C e-commerce shopping experiences in college of social sciences, college of human ecology, and college of business from five different universities. Since the survey questionnaire was distributed during class, all the copies of the questionnaire were collected. Among the 300 responses, 273 were turned out to be valid.

The demographic statistics of the respondents is summarized in <Table 1>. Among the respondents, 58% of them was female and 42% was male. The majority of respondents(65%) was business major.

<Table 1> The Demographic Statistics of the Study Sample

Respondents			Percentage(%)
Gender	Male	114	42
	Female	159	58
Total		273	100
College	Business	178	65
	Human Ecology	57	21
	Social Sciences	38	14
Total		273	100

<Table 2> Sources and Operationalization of the Questionnaire Items

Construct	Questionnaire Item	Source
Information Quality	IQ1: information understandability IQ2: information reliability IQ3: information adequacy IQ4: information scope IQ5: information usefulness	Mckinney et al.(2002)
System Quality	SQ1: system user-friendliness SQ2: system entertainment SQ3: system hyperlink effectiveness SQ4: system navigation effectiveness	Mckinney et al. (2002)
Service Quality	SERVQ1: service reliability SERVQ2: service responsiveness SERVQ3: service assurance SERVQ4: service empathy	Jarvenpaa and Todd (1997)
Satisfaction	SATIS1: satisfaction of shopping experience SATIS2: satisfaction of shopping pleasure SATIS3: satisfaction of shopping comfortability	Mckinney et al. (2002)
Customer Loyalty	LOYAL1; willingness of future purchase LOYAL2: willingness of recommending the site LOYAL3: willingness to visit the site over other sites	Srinivasan et al.(2002) and Zeithaml et al.(1996)

3.2 Operationalization of research variables

The questions used in the survey were adopted from existing studies with modification for the purpose of this study. They were summarized in <Table 2>. A 7-point Likert scale was used for each questionnaire item.

3.3 Reliability and validity analysis of the research instrument

Among the 300 responses, 27 were dropped for data analysis due to respondents' insincerity in answering the survey questions such as missing answers and uniform answers. For reliability analysis and exploratory factor analysis of the survey items, SPSS 14.0 was used.

<Table 3> shows the results of reliability analysis of the sample of 273 responses. Cronbach's α of .60 to .70 is deemed the lower limit for reliability test (Hair et. al, 1998) and test results show that α values of all constructs are greater than .70. Thus, it can be said that the questionnaire items used for this study are reliable.

<Table 4> shows the results of exploratory factor analysis. To obtain a orthogonal rotation of factors, VARIMAX rotational approach was used. Hair et al. (1998) suggest that factor loadings greater than 0.3 and total explained variance greater than 0.5 are considered to meet the minimal level. Since the results of exploratory factor analysis show that both minimum requirements are satisfied, it can be said that the validity of factors are maintained.

<Table 3> Reliability Analysis of the Questionnaire Items

Construct	No. of Items	Questionnaire Item	Cronbach's α
Information Quality	5	information understandability information reliability information adequacy information scope information usefulness	0.907
System Quality	4	system user-friendliness system entertainment system hyperlink effectiveness system navigation effectiveness	0.884
Service Quality	4	service reliability service responsiveness service assurance service empathy	0.834
Satisfaction	3	satisfaction of shopping experience satisfaction of shopping pleasure satisfaction of shopping comfortability	0.918
Customer Loyalty	3	willingness of future purchase willingness of recommending the site willingness to visit the site over other sites	0.940

<Table 4> Exploratory Factor Analysis

Construct	Questionnaire Item	Factor Loading	Eigenvalue	Total explained variance (%)	Cumulative total variance (%)
Information Quality	IQ1	.596	9.810	51.632	51.632
	IQ2	.665
	IQ3	.782
	IQ4	.813
	IQ5	.740
System Quality	SQ1	.819	1.771	9.323	60.955
	SQ2	.748
	SQ3	.745
	SQ4	.753
Service Quality	SERVQ1	.763	1.193	6.281	67.236
	SERVQ2	.765
	SERVQ3	.617
	SERVQ4	.776
Satisfaction	SATIS1	.722	.668	3.620	70.856
	SATIS2	.707
	SATIS3	.635
Customer Loyalty	LOYAL1	.859	1.315	6.922	77.778
	LOYAL2	.849
	LOYAL3	.904

Ⅳ. Data Analysis and Findings

4.1 Confirmatory factor analysis

To test the proposed research model and research hypotheses, the two-step approach of structural equation model suggested by Anderson and Gerbing(1988) was used with Amos 5.0.  <Table 5> shows the results of confirmatory factor analysis(CFA) and goodness-of-fit measures for CFA. Although GFI and AGIF values of 0.9 is preferable, Tayor and Todd(1988) assert that acceptable model fits are indicated by values of GIF and AGIF exceeding 0.8. Thus, it can be said that GIF and AGIF values of 0.882 and 0.843 are marginal acceptance level. In addition, composite reliability and average variance extracted(AVE) values are all greater than the acceptable levels of 0.6 and 0.5, respectively, as suggested by Bagozzi and Yi(1988). Therefore, it can be assumed that the convergent validity of the research instrument is verified.

4.2 Correlation matrix of constructs

<Table 6> shows the correlation matrix of constructs. For the discriminant validity of the research model, Fornell and Larcker(1981) suggest that average variance extracted(AVE) be greater than the squared correlation of constructs. The correlation matrix of constructs shows that AVEs are greater than squared correlations of constructs. Thus, the discriminant validity of the research instrument is verified.

<Table 5> Confirmatory Factor Analysis

Construct	Questionnaire Item	Estimate	S.E.	t-value (C.R.)	Composite Reliability	AVE	Model Fit Summary
System Quality	SQ1	.829			.885	.658	χ²=323.016 (p=.000), χ²/df=323.016/142=2.275, GFI=.882, AGFI=.843, RMR=.073, IFI=.956, TLI=.946, CFI=.956, RMSEA=.068
	SQ2	.779	.066	14.438
	SQ3	.826	.069	15.619
	SQ4	.810	.065	15.217
Information Quality	IQ1	.807			.907	.662
	IQ2	.845	.067	16.051
	IQ3	.846	.067	16.083
	IQ4	.729	.068	13.173
	IQ5	.834	.064	15.771
Service Quality	SERVQ1	.795			.837	.562
	SERVQ2	.759	.077	12.699
	SERVQ3	.759	.073	12.696
	SERVQ4	.681	.083	11.237
Satisfaction	SATIS1	.911			.922	.799
	SATIS2	.947	.041	26.226
	SATIS3	.819	.048	18.926
Customer Loyalty	LOYAL1	.899			.944	.848
	LOYAL2	.899	.043	23.157
	LOYAL3	.963	.036	26.925

<Table 6> Correlation Matrix of Constructs

	Information Quality	System Quality	Service Quality	Satisfaction	Loyalty
Information Quality		.524	.471	.579	.328
System Quality	.724*** (.088)		.424	.452	.268
Service Quality	.686*** (.097)	.651*** (.100)		.508	.156
Satisfaction	.761*** (.105)	.672*** (.104)	.713*** (.120)		.438
Loyalty	.573*** (.099)	.518*** (.101)	.395*** (.107)	.662*** (.126)

주) *** Significance level p<.01

<Table 7> Goodness-of-Fit Measures of the Research Model

Measures of Fit	Comparison Criterion	Recommended Minimum Acceptable Level	Analysis Results
Absolute Fit Measures	χ² (df, p-value)	-	336.125 (df=145, p=0.000)
	χ²/df	≦ 3.0	2.318
	GFI	≧ 0.9	.880
	RMR	≦ 0.08	.084
	RMSEA	≦ 0.08	.070
Incremental Fit Measures	AGFI	≧ 0.8	.842
	NNFI	≧ 0.9	.945
	NFI	≧ 0.9	.921
	CFI	≧ 0.9	.953
Parsimonious Fit Measures	PGFI	≧ 0.6	.671
	PNFI	≧ 0.6	.781

4.3 Goodness-of-fit of the research model

To test research hypotheses, the goodness-of-fit of the research model was measured with Amos 5.0. <Table-7> shows goodness-of-fit measures of the research model. Only the likelihood-ratio chi-square (χ²) is considered to have statistical significance among goodness-of-fit measures in SEM (Joreskog and Sorbom, 1989). The χ²value of 336.125 is statistically significant at the 0.01 significance level. Thus, it can be asserted that the overall goodness-of-fit of the research model is supported. In addition, although GFI and AGIF values of 0.9 is preferable, Tayor and Todd(1988) assert that acceptable model fits are indicated by values of GIF and AGIF exceeding 0.8. Thus, GIF and AGIF values of 0.880 and 0.842 are at a marginal acceptance level. Furthermore, as shown in <Table 7> all incremental fit measures and parsimonious fit measures exceed the recommended acceptable levels. This also supports the overall goodness-of-fit of the research model.

4.4 Testing research hypotheses

As shown in <Table 7>, the overall goodness-of-fit of the research model is supported at a marginal acceptance level and it is  presented in <Figure 2>. The results of research hypotheses are summarized in <Table 8>.

Hypothesis 1, Information quality of B2C e-commerce web site will positively affect the perceived satisfaction of customer, was supported at the significance level of 1%. with a regression weight of 0.45. This result implies that as the information quality of the web site of e-tailer improves, customer satisfaction will increase.

Hypothesis 2, System quality of B2C e-commerce web site will positively affect the perceived satisfaction of customer, was also supported at the significance level of 5%. with a regression weight of 0.16. Thus, B2C e-commerce stores can expect to increase customer satisfaction by improving the system quality of their web site.

Hypothesis 3, Service quality of B2C e-commerce web site will positively affect the perceived satisfaction of customer, was supported at the significance level of 1%. with a regression weight of 0.30. This tells that by improving service function, e-commerce stores can expect to enhance customer satisfaction.

Hypothesis 4, Customer’s perceived satisfaction (shopping experience) will positively affect customer loyalty, was supported at the significance level of 1%. with a regression weight of 0.67. This result is congruent with the B2C e-commerce literature. Thus, e-commerce stores should exert more efforts to enhance customer satisfaction and in turn, improve customer loyalty.

<Table 8> The Results of Research Hypothesis Testing

Hypothesis	Path	Path Coefficient	S.E.	C.R.(t)	p-value	Result
H1	Information Quality --> Satisfaction	0.445	0.100	5.651	0.000	Supported
H2	System Quality --> Satisfaction	0.162	0.088	2.226	0.026	Supported
H3	Service Quality --> Satisfaction	0.297	0.080	4.121	0.000	Supported
H4	Satisfaction --> Loyalty	0.666	0.059	12.000	0.000	Supported

<Figure 2> Test Results of the Proposed Model

Ⅴ. Discussion and Implications of the Research Findings

Support for H1, H2, and H3 indicates that the basic ideas of IS success models (DeLone and McLean 1992, 2003; Seddon, 1997) is valid in B2C e-commerce context. H1 supports the research findings of Liu and Arnett (2000) that information quality of web sites is highly related to customer satisfaction. In addition, the results of testing H1 are also congruent with the research findings of Liang and Lai (2002). That is, the quality of web site design and the quality of information contained on the web site affect consumer choice that in turn, influences shoppers' current and future purchases. The results of testing H1 and H2 are consistent with the findings of Seddon and Kiew (1994) that higher levels of information and system quality are associated with higher levels of net benefits, which can be considered customer loyalty in this study.

Angehrn (1997) asserted that providing information was the basic goal of a web site. The Internet (information system) is the primary means of contact and communication between customers and e-commerce stores for business transactions in B2C e-commerce, as customers mainly obtain information about products and services provided by e-commerce stores from their web sites. Therefore, the result of testing H1 implies that well-designed B2C e-commerce shopping mall web sites must provide accurate, relevant, complete, current, and consistent information about the products and services they offer to improve customer satisfaction. It also implies that B2C e-commerce stores can expect to strengthen the relationship with customers by providing non-commercial information regarding company background (Huizingh, 2000).

By the same token, as indicated by the result of testing H2 customers would feel more satisfied with B2C e-commerce stores when their web sites are easy to use, easy to navigate, entertaining, reliable, available, and user-friendly (Jarvenpaa and Todd, 1997). This implies that B2C e-commerce stores make the user interface of their web site from the customers' point of view to make shopping more enjoyable and generate greater customer satisfaction.

Researchers (DeLone and McLean, 2003; Moad, 1989; Rockart, 1982; Wilkin and Hewitt, 1999; Kettinger et al., 1995) argue that service quality be a success measure in determining the effectiveness of information systems, since the role of the IS department is  a provider of not only information systems, but also ongoing services once information systems are put in place. The primary tools of e-commerce are the Internet (information system) and the web sites. In addition, any services before, during, and after transactions in B2C e-commerce are provided mainly through the Internet. Thus, service quality concept in IS success models can be adopted as a factor in studies of examining the success of B2C e-commerce in IS success perspective that influences customers to form their perception toward B2C e-commerce stores.

Shostack (1997) asserts that when a customer buys a tangible product,  he or she also buys a service. Later, he or she might need such after-sale services as technical support from the e-store. Furthermore, customers might need some additional services, such as exchange, return or refund of merchandise. Therefore, as shown in the result of testing H3, a higher level of service quality provided by an e-tailer, both online and off-line, can be a reinforcer that can favorably influence customer satisfaction toward the Internet store. As a result, support for H3 implies that B2C e-commerce stores consider how to improve their services in terms of reliability, responsiveness, assurance, and empathy to increase the level of customer satisfaction.

Support for H4 is consistent with the findings of Bruhn and Grung (2000) that  customer shopping experience and customer satisfaction influence behavior(customer loyalty in this study). Fishbein and Ajzen (1975) found that there is a strong link between attitude, a person's general feeling of favorableness or unfavorableness, and behavior. Thus it can be inferred that customers having pleasant shopping experiences through high levels of information quality, system quality, and service quality from B2C e-commerce  stores they visit would be more satisfied with the stores. This could lead to a higher level of customer loyalty such as future purchase, recommending the store, or visiting the site over other sites. Therefore, B2C e-commerce stores must develop various business strategies such as web site design, promotional events to increase customer satisfaction and eventually lead to greater customer loyalty.

Ⅵ. Conclusion

It has been widely known that information systems, especially the Internet, have been the primary enabler of e-commerce. However, previous research on the success of B2C e-commerce has been conducted in various perspectives such as web design, trust, and web site familiarity (Kim, 2008; Kho and Choi, 2005; Kim and Kwak, 2004; Torkzadeh and Dhillion, 2002; Gefen, 2000). This study thus identified factors affecting the success of B2C e-commerce in terms of customer loyalty through perceived customer satisfaction from an IS success perspective, considering the fact that the primary enabler of e-commerce is information technology and information system. Although the overall fit of the proposed model is at a marginal acceptance level, hypothesis testing shows that the constructs affecting satisfaction in the IS success models (DeLone and McLean 1992, 2003; Seddon 1997) such as information quality, system quality, and service quality  are associated with perceived customer satisfaction in B2C e-commerce context at varying degrees. Perceived customer satisfaction is in turn strongly associated with customer loyalty.

This study made two contributions. First, it empirically showed that the basic ideas of IS success models are still valid in B2C e-commerce context. In other words, the constructs of IS success models affect customer loyalty in B2C e-commerce store through perceived user satisfaction. Thus, the empirical evidence found in this study provides an understanding of the success factors of B2C e-commerce in terms of customer loyalty from an IS success perspective. Secondly, the findings of this study provide B2C e-commerce stores and IS practitioners with an insight into a success of B2C e-commerce in a new perspective. Therefore, when developing effective B2C e-commerce business strategies, business managers and IS practitioners must pay attention to those constructs that showed a relatively strong relationship to the perceived customer satisfaction in order to leverage customer loyalty to a higher level.

This study used a convenience sample of college students in various majors and thus their characteristics may not be the same as those of B2C e-commerce shoppers in general. Therefore, the findings of this study may have some limitations in its generalizability. This study adopted the basic ideas of IS success models in developing the proposed research model and thus the constructs affecting perceived user satisfaction are limited to those used in IS success models. This led to a simplified research model which might overlook some potentially important constructs affecting perceived user satisfaction.

The findings of this study is based on the respondents' shopping experiences of B2C e-commerce stores in general. Therefore, future studies are called for to explore the validity of the proposed research model and the differences of relationships among constructs in specific types of B2C e-commerce stores such as specialty B2C e-commerce stores. In addition, future studies can explore the effects of gender or cultural differences on the proposed model.

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박용태(Yong-Tae Park)

영남대학교 경영학과를 졸업하고, Claremont Graduate School에서 경영정보학 전공으로 박사학위를 취득하였다. University of Illinois, Springfield에서 조교수 그리고 California State University, Fullerton에서 부교수를 역임하였으며, 현재 울산대학교 경영대학 경영학부 부교수로 재직하고 있다. 주요 연구 관심분야는 전자상거래, 정보화전략, 데이터 웨어하우징, 정보시스템의 전략적 이용 등이다.

문용은(Yong-Eun Moon)

서강대학교를 졸업하고 동 대학교 대학원에서 경영학(MIS 전공) 석사와 박사 학위를 취득하였다. 선문대학교 경영학부를 거쳐 현재 신라대학교 경영정보학과 교수로 재직 중에 있다. 미국 Claremont Graduate University의 방문교수를 역임하였으며, 주요 관심분야는 e-비즈니스 전략, 정보시스템 전략계획, 프로젝트관리 등이며, 경영정보시스템(박영사), EC와 e-비즈니스(사이텍미디어) 등의 저서와 한국경영정보학회, 한국정보시스템학회 등의 저널에 50 여편의 논문이 있다.

<Abstract>

정보시스템의 성공 관점에서 본 B2C 전자상거래의 고객충성도에 영향을 미치는 요인에 관한 연구

박용태․문용은

다양한 관점에서 B2C 전자상거래의 성공에 대한 연구가 진행되어왔다. 많은 사람들이 전자상거래를 가능하게 한 것은 정보시스템이며 고객의 태도와 행동을 이해하는 것이 B2C 전자상거래의 성공을 위한 필수조건이라고 생각하고 있다. 본 연구는 B2C 전자상거래 관련 문헌에서 고객의 행동에 영향을 미치는 요인들을 찾아낸 후 정보시스템 성공 모델의 기본 생각을 응용하여 고객충성도를 B2C 전자상거래의 성공으로 표현하는 구조방정식 모델을 제시하고 있다. 본 연구의 결과는 정보시스템 성공 모델에서 사용된 개념들(정보의 질, 시스템의 질, 그리고 서비스의 질)이 고객의 인지된 만족도를 통해서 고객의 충성도에 영향을 미친다는 것을 보여주고 있다. 본 연구에 사용된 모델은 정보시스템 연구자와 전자상거래 실무자들이 B2C 전자상거래의 성공 요인에 대한 이해의 폭을 넓히는데 도움을 줄 수 있을 것이라고 기대한다.

Keywords: 고객 충성도, B2C 전자상거래, 전자상거래 성공 요인, 정보시스템 성공

* 이 논문은 2008년 10월 28일 접수하여 2차 수정을 거쳐 2008년 12월 1일 게재 확정되었습니다.