The Impact of Electronic Service Quality on Online Shopping Behavior

Authors: Wen-Chin Tsao1

Biographical Information

Associate Professor, Department of Business Administration, National Chin-Yi University of Technology

Affiliation Address:

No. 35, Lane 215, Sec. 1, Chung-Shan Rd., Taiping City, Taichung County, 411, Taiwan, R.O.C.

TEL: 886-4-23924505 ext. 7775FAX: 886-4-23929584E-mail: tsao@nc u t.edu.tw

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The Impact of Electronic Service Quality on Online Shopping Behavior

Abstract

Although the Internet has had significant worldwide effects in many domains, including business behaviors in the 21st century, research to explore the effects of e-service quality on online shopping behavior is insufficient. This study mainly explores the influence of e-service quality on website brand equity, and then further investigates that of brand equity on perceived risk and customer value. A structure equation model is developed to test the casual effects between variables. The empirical results show that (1) e-service quality has a significant positive effect on web brand equity; (2) web brand equity has a significant negative effect on perceived risk and has a significant positive effect on customer value; (3) customer value has a significant positive effect on behavioral intention. The implications for marketing managers are discussed.

Keywords: Online shopping; e-service quality; Web brand equity; Perceived risk; Customer value

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The Impact of Electronic Service Quality on Online Shopping Behavior

1. IntroductionThe Internet has significantly affected many domains of human

interaction in the 21st century. It has established completely new conventions in how people share information; and this, in turn has created completely new business behaviors. Despite the recent global depression, in which Taiwan’s retailing has suffered negative growth for an almost unprecedented three months in a row, online shopping appears to be on the rise. The reason for this seems to be that consumers under economic depression circumstances generally cut back on traditional “brick-and-mortar” shopping, but their consumption related needs remain. And, with 24-hour shopping, to-your-door delivery, and the same discount structures and payment plans that the department stores offer, shoppers go online instead.

Looking at this dynamic in Taiwan, Europe, and America, the U.S. takes the lead. In 2008, the ratio of online to brick-and-mortar retailing in the U.S. has been estimated at 9.4%, with the European market next to it, at 7.3% (Institute for Information Industry (III), 2008). While a number for this ratio isn’t available for Taiwan, there are nonetheless impressive stats: The B2C online shopping market for 2008 in Taiwan was estimated at NT$136.5 billion; a 27.8% increase from 2007. The MIC survey conducted by III reveals that online shopping has surpassed department store shopping and is now in fifth place of consumers’ most frequently visited distribution channels, whereas the percentage of online shopping in retailing has risen from 3.3% of last year to 4% and will grow against the adversity of depression to an estimated 4.7% in 2009. This momentum of growth owes to the influence of web surfers’ increasing willingness to shop online, diversity and completeness of merchandise and services, as well as the effects of word-of-mouth, both in the actual and virtual worlds.

The development of e-shops is rapid. In Taiwan, shopping websites have emerged in great number, very quickly, with many competing entrants in most merchandise categories. How many of these websites will survive the tough competition and operate sustainably? One way for website operators to compete is to elevate service quality (Parasuraman, Zeithamal & Berry, 1988). [raz]

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Brand is an impression, an inner recognition arising at the time of contact with the good/service provider; this is as true for brick-and-mortar shoppers as it is for online shoppers interacting via a browser. If browser interaction fosters a negative recognition, the User will not likely visit that e-shop again. From the consumer’s perspective, the virtual nature of the Internet imposes special demands on this brand recognition process, different from what they’re used to, and failing to meet these demands can produce a sense of insecurity. On the other hand, a good brand could at least partially mitigate and survive such e-interface induced insecurity. Hence, in the virtual world of the Internet, the value of brand is the more important. As such, for any website operator to build a successful website, the website brand is crucial. Brand equity can assist the customers in interpreting, storing and processing the merchandise or brand related messages, to facilitate the differentiation with competitors and to be able to vest the consumers with the confidence in purchase decision, while reducing perceived risks, as well as the satisfaction at and value of usage (Aaker, 1991). Therefore, the establishment of brand equity of a website by fostering shoppers’ loyalty, providing high profile of the website as well as high service quality is closely relevant to the success of the website operation. Also, in the ceaseless growth of the business mode that products and services are provided via the internet in future, whether the online service quality is good or not is particularly important to the brand operation of e-shops.

Many an enterprise aware of the business opportunities brought about by e-commerce in addition to the low threshold of opening an e-shop begins to devote itself to the e-shopping channel, be it a traditional firm or a late cyber firm, totaling a great number of enterprises active in e-commerce to make the competition fierce. Hence, if an enterprise wants to generate values for customers over the internet that is a means different from traditional one in pursuit of better performance, it should understand the customer values that consumers care about and try best to satisfy customers’ needs to enhance their word of mouth as well as their willingness to buy again. Furthermore, because e-shopping pattern is different from that in the traditional physical environment, for example, a consumer cannot inspect the product beforehand or talk to the businessman face to face, the perceived risk of e-shopping is higher than shopping in physical stores (Tan, 1999). But, the building of website brand equity can lessen the disadvantages in marketing and

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increase the effective marketing communications. Also, when a consumer is unable to fully assess the product property prior to purchase, the products of reliable brands can reduce his/her perceived risk at time of purchasing (Keller, 2001).

Based on the aforementioned literature review, this research wishes to discuss the influence of e-service quality on website brand equity, and further to investigate that of brand equity on perceived risk and customer value, further to explore that on consumers’ behavioral intention, to provide the basis of reference for the firms devoted to e-service and further to elevate the service level of the e-shops and to strengthen consumers’ willingness to shop online.

2. Literature Review

2.1 E-Service Quality Rust and Lemon (2000) described e-services as “… providing a

superior experience to consumers with respect to the interactive flow of information”. Bauer et al. (2006) argued with a complete definition that it should cover all causes and encounters that have occurred before, occur during and after the electronic service delivery. Hence, like shopping in physical channels, the consumption experience of shopping online also gives the consumers the impression on whether the service quality is good or not. What is different is that e-shopping takes more serious, than shopping in physical channels, of how to convey, by means other than persons, the functional dimension in which the service results are considered and the technical dimension in which the service process is considered (Gronroos et al., 2000). Among the literatures regarding e-service quality, Zeithamal, Parasuraman & Malhotra (2002) pointed out that the key to the success of e-retailers lies no longer in merely the presentation of web pages or low-price strategy, but rather, in particularly the e-service quality. To encourage customers to repeat buying and to build up their loyalty, the enterprises should shift their focus from the transaction costs in e-commerce to the service quality.

Zeithamal, Parasuraman & Malhotra (2002) were the first to propose the formal definition for E-service Quality, or E-SQ, by which e-service quality can be deemed as how well a website facilitates effective and benefiting purchase and delivery of products or services. It can be observed from such definition that the meaning of service is general and

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includes both before-hand and after e-services. And it is clear from above literature review that traditional service quality refers to all customer-firm contacts and processes that are not based on the internet (Zeithamal, Parasuraman & Malhotra, 2005), while given that the e-commerce is getting more prevalent, the factor of the success of e-shops is no longer the websites offering at low prices or the websites’ existence, but rather the customer loyalty and willingness to repurchase that should have been established by the excellent service quality conveyed by the websites.

2.2 Website Brand EquityFarquhar (1990) believed that brand equity is the added value a

brand endows to the products, and brand equity, if in consumers’ perspective, comes from the increase of intensity of attitude when a consumer uses such brand, where attitude means an individual’s association with brand evaluation on a physical product in his memory, and intensity of attitude is the major decisive factor of the purchasing behavior. Aaker (1991) thought that brand equity can be defined as a brand’s equity and liability combined, and that brand equity associated with the brand name and symbol and existed outside of a product or service’s own value yet was able to provide values to the consumers and the firm. And the assets that form the basis of brand equity can be divided into brand loyalty, brand profile, perceived quality, brand association and other assets such as patents and trademarks. Keller (2008) provided the CBBE model, and argued that the power of brand lies in what customers have learned, felt, seen, and heard about the brand as a result of their experiences over time. Hence, he defined customer-based brand equity as the differential effect that brand knowledge has on consumer response to the marketing of that brand, and argued the three key ingredients to brand are by this definition: (1) “differential effect,” (2) “brand knowledge,” and (3) “customer response to marketing.” On the internet, a website name is a brand name; hence “brand equity” in the cyber environment is “website brand equity” and can be defined as “the combined assets and liabilities linking to a website brand and logo, that can increase or decrease the values of the merchandise or services toward such website or consumers” (Page & Lepkowska-White, 2002).

2.3 Perceived Risk

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Bauer (1960) first proposed the concept of perceived risk in the contents of consumer behavior; regarding perceived risk, he (1960) thought that the consumers being unable to predict accurately the results of their buying actions, their behaviors involve risks. In other word, no consumer behavior can produce anticipated results that are certain, and at least some of these results may be unpleasant. Following his research (1960) and being the first to specifically describe and disambiguate perceived risk was Cox (1967). Cox (1967) believed that in each buying action, a consumer has his/her object of purchase, and when he/she is unable to decide which purchase best satisfies his/her object or fails to achieve the anticipated object after the purchase, adverse results may be caused, which is perceived risk.

Stone and Gronhaug (1993) and Sweeney et al. (1999) used the definition by Peter and Ryan (1976) to define perceived risk as a “subjective anticipated loss” in their research in perceived risk of products. In the scope of e-shopping, Forsythe & Shi (2003), Lim (2003) and Tao & Yeong (2003) defined the risk perceived in e-shopping as the anticipated loss an e-shopper subjectively perceives in order to pursue his/her desired results when deliberating on a particular e-shopping decision, i.e., as the possibility of loss occurring.

2.4 Customer ValueCustomer value is a cognitive value, a trade-off between “give” and

“take”, and a distinction between “anticipated values” and “cognitive values” (Monroe, 1990). Keeney (1999) defined customer value of e-commerce as the net value between the costs at time of purchase and of the benefits obtained after purchase for a customer. Han and Han (2001) also defined customer value on the internet as the benefits brought about to customers by the cost down that can be made from transactions over the internet, and that the values customers need can be generated by, e.g., quality elevation, cost down and customization.

Past research has conceptualized value as simply a tradeoff between quality and price (Bolton and Drew, 1991), though a number of recent researchers argue that value is more complex, that other dimensions of value should be considered. In the past, product/brand attitude has historically been treated as one-dimensional (e.g., Osgood, Suci and Tannenbaum, 1957). During the 1980s, there were substantial discussions concerning the experiential and symbolic aspects of products. Hirschman

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and Holbrook (1982) advocated the experiential aspect of human consumption, in which emotions and feelings of enjoyment or pleasure are key components, and contrasted information-processing (similar to utilitarian) and experiential (similar to hedonic) views of consumer behavior. More recently, however, researchers have focused on two major dimensions of product relevance, and have attempted to measure these “hedonic” and “utilitarian” aspects of products (Batra and Ahtola, 1990; Babin, Darden and Griffin, 1994; Spangenberg, Voss and Crowley, 1997; Voss, Spangenberg and Grohmann, 2003). Viewed broadly, these two aspects of hedonic and utilitarian values correspond to the archetypal constructs of emotion and reason wherein goods/services possessing hedonic value key to experientially driven consumption, fun, pleasure, and excitement, and goods/services possessing utilitarian value are primarily instrumental and functional (Strahilevitz and Myers, 1998; Dhar and Wertenbroch, 2000).

However, among the research related to e-shopping, the hedonic and utilitarian shopping motives and values began to be taken seriously and widely investigated as well (Bauer et al., 2006; Overby and Lee, 2006). It becomes clear from the definition for customer value by related documents that both traditional customer value and online customer value include both hedonic and utilitarian values. Traditional customer value emphasizes the tradeoff between the quality or benefits customers obtain and the time, search and mental efforts they pay (monetary and non-monetary values) when they assesses the effects of an activity or a product; online customer value is the benefits customers obtain from the total gain deducted by total costs via e-transactions. But, as online customer value obtains products and services through online channels and build correspondences with customers by information technology, it would take more serious, than traditional transactions, of the issues related to online information technology, such as ease of use, privacy weighed, security of transaction, interaction and credit so as to increase the customer values.

Therefore, two value dimensions are adopted in this study: utilitarian value and hedonic value.

2.5 Behavioral IntentionBehavioral intention means one’s inclination to take action when

he/she judges subjectively his future; it can be used to predict people’s

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behaviors. Fishbein and Ajzen (1975) believed that behavioral intention is an individual’s inclination of action in which he/she wants to conduct a certain behavior, which means the expression of certain extent of whether to conduct certain behavior, that results from the decision process in choosing a behavior, and that behavioral intention is a necessary process of any behavior; it is a decision prior to the manifest of the behavior. In the definition by Zeithamal et al. (1996) for behavioral intention: “customers come out with many changes in behavioral intention after they have perceived and assessed the services, such changes having positive and negative effects on the shops, of which the positive effects include: recommendation to others, customer loyalty arising and willingness to buy again; the negative effects include customer complaints and customers turning to other shops or brands”. Blackwell et al. (2001) pointed out that though behavioral intention is changeable and it is impossible to control whether consumers will act by their will, behavioral intention can serve as the basis for predicting how online buyers would act for online sellers. In respect of e-shopping, the definition by Hans and Tibert (2004) for behavioral intention is consumers’ willingness to revisit a website and use it again for e-shopping.

3 Hypotheses and Conceptual Model

3.1 E-service Quality and Web Brand EquityAs the competition in cyber world will be fiercer than in physical

world due to low threshold of entering in the former, the establishment of compelling brands will be a crucial factor of survival on the internet for enterprises. To enhance the values of website brands, service quality of websites is thus important. Zeithamal (1988) pointed out that perceived quality is one of the elements of brand value, and hence, higher perceived quality will direct the customers to choose high quality brands instead of other rivaling brands. Berry (2000) pointed out that in service-based companies, the company is brand and marketing and external communications help building the brand, and it is, however, customers’ experience in the service that is the most powerful tool of brand equity. From the review on the literatures related to brand equity, it is noticed that a number of researchers took perceived quality into the dimension of brand equity measurement (Keller, 1993; Cobb-Walgren, Ruble &

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Donthu, 1995; Aaker, 1996); this implies that whether perceived quality is good or not will directly affect the brand equity for customers. Yoo, Donthu and Lee (2000) pointed out in their research that the hypothesis that perceived quality has positive influence upon brand equity was supported. This is true with both the physical shopping environment and virtual one. Therefore, this study presets the following hypothesis:

H1. E-service quality has a significant positive effect on web brand equity.

3.2. Web Brand Equity and Perceived Risk When consumers cannot fully assess the product property before purchasing, the products of high reliable brand can lessen the perceived risks for them when they purchase the products. Roselius (1971) proposed several strategies capable of reducing consumers’ perceived risks, such as money-back guaranty, brand image, brand loyalty, word of mouth, product endorser, store image and compliances. These strategies encompass the basic concepts of brand equity: brand profile, brand image, brand loyalty and perceived quality. The above indicates that when shopping at the virtual e-shops, website brand equity can truly lessen consumers’ perceived risks.

That is, website brand equity has negative influence on perceived risk. Keller (2008) thought that compelling brands have many advantages, which include improved perceptions of product performance and less vulnerability of consumers to marketing crises. Thus, it is hypothesized that:

H2. Web brand equity has a significant negative effect on perceived risk.

3.3. Web Brand Equity and Customer ValueHolbrook (1994) pointed out that of the four characteristics of

customer value, ‘preference’ means when a consumer determines whether to purchase a product or service, his/her preference would affect his/her assessment on such product value. Cobb et al. (1995) pointed out in their study that brands of high brand equity tend to induce higher brand preference and purchasing intention in consumers’ mind. It is thus clear that the level of brand equity would affect the degree of preference by consumers and further custom value.

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In the concepts about brand that Martin and Brown (1990) proposed, perceived quality is an important dimension for measuring brand equity; it was defined as the consumers’ perception of whether such brand can fulfill the functions of products or services. Whereas the reason why consumers think a product or service is better than others is they possess stronger perceived quality. Dodd et al. (1991) found in their research that customers’ perceived product quality can bring about the benefits of their use of the products. The research by Chen and Dubinsky (2003) also indicated that perceived quality has positive effects on customer values. Therefore, this research infers that when e-shops have high brand equity, it is possible to enhance customers’ perceived quality and arouse positive association of brands, further to affect customer value. Thus, this study posits:

H3. Web brand equity has a significant positive effect on customer value.

3.4. Perceived Risk and Behavioral IntentionMurray and Schlater (1990) pointed out that as consumers seek

various methods to reduce the risk when making decisions, with perceived risk lessened, their willingness to purchase the product or service will increase. Vijayasarathy and Jones (2000) proposed that perceived risk has negative effect on the intention of e-shopping. Pavlou and Gefen (2004) considered perceived risk increases negative anticipation, resulting in negative effects on purchasing intention. Liaw et al. (2005) discovered that in the environment of e-shopping, perceived risk apparently affects the purchasing intention of consumers, where consumers of lower risks would perceive higher intention of e-shopping. Hence, this research considers perceived risk plays a significant part to affect during consumers’ purchase process, also affects their willingness to shop, and that if consumers cannot lessen the perceived risk, they may give up purchase. Thus, it is hypothesized that:

H4. Perceived risk has a significant negative effect on behavioral intention.

3.5. Customer Value and Behavioral Intention Many factors affect consumers’ intention of repurchase; but that

consumers are willing to repurchase is basically because such product

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works for them, that is, the product is of value to the consumers, so, customer value affects the intention of repurchase. In addition, from the model that Zeithamal (1988) proposed for the relationship between perceived price, perceived quality, customer value and intention of repurchase, it becomes clear that customer value affects the intention of repurchase and that the higher the customer value is, the more capable it is of enhancing customers’ intention of repurchase. Grewal et al. (1998) also thought that customers’ intention of repurchase depends generally on the perceived interest and value they acquire. In the market of e-shopping, as Chen and Dubinsky (2003) pointed out, customer value plays an important role in whether the customers have the intention of repurchase. With the above summarized, it becomes clear that customer value affects customers’ intention of purchase. Accordingly, the following hypothesis is proposed:

H5. Customer value has a significant, positive effect on behavioral intention.

3.6. Conceptual Model

Through aforementioned documentary reviews and induction of research hypotheses, the conceptual construct of this research is as shown in Figure 1.

Figure 1 Conceptual Model

4. Methodology4.1 Data Collection

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E-service QualityH1

H3

H2H4

H5

Website Brand Equity

Perceived Risk

Customer Value

Behavioral Intention

The samples in this research were general consumers who have had transactions at e-shops. But, due to the inability to be certain of the population number, there was no way to be certain of the number of people who practice e-shopping. As a result, this research employed convenience sampling and e-questionnaires, and prepared questionnaires on website http://www.my3q.com and released them therefrom.

This research conducted survey by questionnaires, which were posted on various major forums and released from Oct. 17 to Nov. 3, 2008, with 685 valid questionnaires returned. In the basic information on the 685 subjects, analysis was made in terms of gender, age, education, averaged monthly earning or allowance, kind of trade, internet using time, number of times of e-shopping each year, averaged consumption of each e-shopping and so on. A profile of the sample is presented in Table 1. A majority (76.6%) of the respondents was male, and 74.3% were 21-30 years of age. Regarding education, 87% of the interviewees were college graduate or above, and 56.6% were students. In internet using history, it was predominantly over 3 years (87.9%); an averaged over 13 times of purchase each year also predominated (32.3%), as the averaged e-consumption below NT$3,000 (89.3%) did.

Table1 Sample profileFrequency % Frequency %

Gender EducationFemale 160 23.4% high school or under 52 7.6%

Male 525 76.6% Vocational College 37 5.4%

University 506 73.9%

Master/ Doctorate 90 13.1%

685 100% 685 100%

Age Years on InternetUnder 20 140 20.4% Under 6 months 11 1.6%

21-30 509 74.3% 6-12 months 21 3.1%

31-40 25 3.7% 12-18 months 14 2.0%

41-50 8 1.2% 18-24 months 15 2.2%

51-60 2 0.3% 24-30 months 11 1.6%

Over 61 1 0.1% 30-36 months 11 1.6%

Over 37 months 602 87.9%

685 100% 685 100%

Income Occupation

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Less than $5,000 167 24.4% Agriculture 1 0.2%

$5,001-10,000 195 28.5% Manufacturing 59 8.6%

$10,001-15,000 66 9.6% Information industry 23 3.4%

$15,001-20,000 27 3.9% Service industry 100 14.6%

$20,001-25,000 67 9.8% Public Service 44 6.4%

$25,001-30,000 55 8.0% Students 388 56.6%

$30,001-35,000 44 6.4% Housewives 4 0.6%

$35,001-40,000 24 3.5% Self-employed 40 5.8%

$40,001-45,000 14 2.0% other 26 3.8%

$45,001-50,000 9 1.3%

Over $50,001 17 2.5%

685 100% 685 100%

Shopping times Average amount1-3 129 18.8% Less than $1,000 325 47.4%

4-6 150 21.9% $1,001-3,000 287 41.9%

7-9 95 13.9% $$3,001-5,000 43 6.3%

10-12 90 13.1% $5,001-7,000 12 1.8%

Over 13 221 32.3% $7,001-9,000 8 1.2%

$9,001-15,000 3 0.4%

Over $15,001 7 1%

685 100% 685 100%

4.2 Development of Measures With the reference to related research of a multiple of researchers for

e-service quality, this research proposed the dimensions of efficiency, reliability, fulfillment, privacy/safety, responsiveness, compensation and contact to measure it (Zeithamal et al., 2002; Parasuraman et al., 2005; Wolfinbarget et al., 2003; Swinder et al., 2002; Szymanski et al., 2000; Allard et al., 2003). Of these, “efficiency” means the ease of use of the website by users to search for the products or information, which, in terms of physical channel, can effectively reduce the transaction costs including search, coordination and decision; “reliability” means all of the website functions work normally, with no compensation interrupted operation in hardware, software and system platform; and “fulfillment” means accuracy of service commitment, including on-time delivery and others. Further, “privacy/safety” means the guaranty of security for transaction information; “responsiveness” means the ability to solve

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problems when they face the users; and “compensation” means whether the website offers at lower prices than physical channels; while “contact” means whether the website provides online customer service or contact window; under which there were a total of 27 measuring items. All items were measured via responses to questionnaire items on a seven-point Likert scale ranging from 1 (Strongly disagree) to 7 (strongly agree).

Website brand equity is an item that was developed based on the brand equity Aaker (1991) proposed, and is applicable to website brand equity in the virtual environment of internet. Hence, this research used the four sub-dimensions of brand loyalty, brand profile, perceived service quality and brand association to measure website brand equity. These four sub-dimensions contain a total of 14 items, each measuring on a seven-point Likert scale ranging from 1 (Strongly disagree) to 7 (strongly

agree)。For perceived risk, reference was made mainly to the documents by

Forsythe et al. (2006); its measuring dimensions include “financial risk”, “product risk” and “time risk”. “Financial risk” was defined as the possibility of monetary loss during e-shopping and consumers’ sense of insecurity in using credit cards online; and “product risk” is the loss incurred from a brand or product that underperforms below expectation when in e-shopping. “Time risk” is the inconvenience of e-transaction, normally due to difficulties in transport and ordering or delayed delivery of product. A total of 11 items were measured on a seven-point Likert

scale ranging from 1 (Strongly disagree) to 7 (strongly agree)。Based on the previous literature research, utilitarian value is defined

as an overall assessment of functional benefits and sacrifices (Overby and Lee, 2006). Utilitarian value is relevant to task-specific and instrumental considerations of online purchase, such as purchase deliberation (i.e., considering the performance, features, price, and convenience for the desired product/service before actual purchase). Therefore, this research applied the items of quality and price matching, time saving and the product worth buying to measure utilitarian value.

In respect of hedonic value, it is defined as an overall assessment of experiential benefits and sacrifices, such as adventure, excitement of social interaction, an enjoyment derived from internet using (Voss et al., 2003; Bauer et al., 2006; Overby and Lee, 2006). Consequently, this

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research used the items of it is pleasant to use the website, I am reluctant to leave, and I am having my boredom relieved to measure it. Six items were measured on a seven-point Likert scale ranging from 1 (Strongly disagree) to 7 (strongly agree).

This research cited the arguments of Zeithanml et al. (1996), Sirohi et al. (1998) and Bloemer et al. (1999) to further divide behavioral intention into recommending intention and repurchasing intention. The former, i.e., recommending intention was defined as that the performance of a product or service which a customer consumes on would affect whether he/she is to tell an enquirer about this e-shop to build positive word of mouth; this was measured by the items “I will tell others about the advantages of this e-shop”, “If I am asked to provide comments on consumption, I will recommend this e-shop” and “I will encourage my friends and relatives to consume at this e-shop”. While for the latter, it was defined as that the performance of a product or service which a customer consumes on would affect whether he/she is willing to shop again here; this was measured by the items “When choosing e-shops to shop, I would give priority to considering this website”, “I would come to this e-shop to shop by my past purchasing experience” and “I would come to this e-shop lesser to shop by my past purchasing experience”. Thus, there are totally six measuring items, each item was measured on a seven-point Likert scale ranging from 1 (Strongly disagree) to 7 (strongly agree).

5. Analysis and Results

5.1 Reliability and Validity

Unidimensionality, reliability, convergent and discriminant validity were then evaluated. First, Cronbach’s reliability coefficients were calculated for the items of each higher-level construct (e.g., E-service quality). As illustrated in Table 2, five coefficient alpha estimates, ranging from .81 to .94, all exceed .7. As such, every of the five dimensions complied with the requirement of internal consistency (Nunnally, 1978).

Then, CFA was applied to detect the unidimensionality of each construct (Anderson and Gerbing, 1988). This unidimensionality check verifies the validity and reliability of our five constructs. PRELIS was used to generate the correlation matrix, and the LISREL 8.72 maximum-

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likelihood method was used to produce a completely standardized solution (Joreskog and Sorbom, 1993). The results are provided in Table 2. Average Variance Extracted (AVE) and composite reliability (ρc) are also provided.

The assessment of the measurement properties of all five constructs indicated that the factor loadings (lambdas) were high and significant (the t values for factor loading ranged from 9.49 to 23.68), which satisfies the criteria for convergent validity (Simonin, 1999). Content validity was established through a literature review and by consulting experienced researchers.

Discriminant validity was assessed using a series of chi-square

difference tests (Bagozzi and Phillips, 1982), where the of

unconstrained CFA model (with all factors freely correlated) was compared with that of a constrained model (with covariance between two factors set equal to unity) and discriminant validity between the

constrained pair of factors was indicated by a significant change.

According to Table 3, the chi-square differences due to the added constrain to a baseline model were all significant, i.e., the constrained model was worse-fit than the unconstrained one. This implied the five factors exhibit discriminant validity.

Fornell and Larcker (1981) also stressed the importance of examining composite reliability and AVE. Bagozzi and Yi (1988) suggested two criteria: Composite reliability (ρc) should be greater than or equal to .60, and AVE should be greater than or equal to .50. For this study, all five composite reliabilities (ρc) were greater or equal to .6, and all AVE figures exceeded .58.

5.2 Analysis of the Measurement Model

The fit of the measurement model was acceptable based on the fit indices. The chi-square test was significant (2

(125) = 1146.24, p<0.01), which is not surprising given the large sample size (n=685). The other fit indices are showed in Table 2. However, these indicated a reasonable level of fit in favor of the model (Bagozzi and Yi, 1998).

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Table 2Scale Items and Measurement Prosperities

Item Standardized Loadings

t value αb

E-service Quality ( =.83；AVE=.69)a 0.94(X1) Efficiency 0.57 ---(X2) Reliability 0.64 13.12(X3) Fulfillment 0.84 15.46(X4) Privacy/safety 0.42 9.49(X5) Responsiveness 0.77 14.79(X6) Compensation 0.65 13.30(X7) Contact 0.58 12.24

Website Brand Equity ( =.87；AVE=.71) 0.93(Y1) Brand Loyalty 0.82 ---(Y2) Brand Awareness 0.79 23.28(Y3) Brand Association 0.80 23.68(Y4) Perceived Service Quality 0.75 21.82

Perceived Risk ( =.78；AVE=.63) 0.81(Y5) Financial Risk 0.84 ---(Y6) Product Risk 0.83 19.61(Y7) Time Risk 0.50 12.59

Customer Value ( =.60；AVE=.58) 0.83(Y8) Utilitarian Value 0.74 ---(Y9) Hedonic Value 0.55 14.26

Behavioral Intention ( =.83；AVE=.80) 0.90(Y10)Recommend Intention 0.78 ---(Y11)Repurchase Intention 0.89 22.64

Goodness-of Fit2

(125) =1146.24 /df=1.67

NFI=0.94 NNFI=0.94 CFI= 0.95IFI=0.95 GFI=0.84 AGFI=0.94 PNFI=0.77 PGFI=0.62 RFI=0.93 RMSEA=0.10

a For each construct, scale composite reliability ( ) and average variance extracted (AVE) are provided. These are calculated using the formula provided by Fornell and Larcker (1981) and Baggozzi and Yi (1988).

b Cronbach’s α (α) means internal consistency.

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Table 3 Confirmatory Factor Analysis for the modified ModelConstrained Factor Covariance df df

None 1146.24 125E-service Quality Website Brand Equity 1502.07 126 355.83* 1

Perceived Risk 1267.45 126 121.21* 1Customer Value 1592.99 126 446.75* 1Behavioral Intention 1327.33 126 181.09* 1

Website Brand Equity Perceived Risk 1293.74 126 147.5* 1Customer Value 1467.40 126 321.16* 1Behavioral Intention 1421.63 126 275.39* 1

Perceived Risk Customer Value 1295.48 126 149.24* 1Behavioral Intention 1446.46 126 300.22* 1

Customer Value Behavioral Intention 1340.42 126 194.18* 1*p<0.05

5.3 Structural Model and Tests of Hypotheses

5.3.1 The Fit of Structural ModelStructural Equation Model (SEM) was used to estimate parameters

of the structural model shown in Figure 1, and the completely standardized solutions computed by the LISREL 8.72 maximum-likelihood method are reported in Table 4. The structural model specified the E-service quality (1) as the exogenous construct. There were four endogenous constructs in this study: website brand equity (1), perceived risk (2), customer value (3), and behavioral intention (4). As shown in Table 4, all fit measures in the structural model had a reasonable fit to the

data ( (130) =1346.88; /df=1.97; GFI=0.82; AGFI=0.8; CFI=0.94;

NFI=0.94; NNFI=0.93). These indicated a reasonable level of fit in favor of this model (Bagozzi and Yi, 1998).

5.3.2 Hypotheses TestsThe standardized estimates for the various paths and the associated t-

values are provided in Table 4. Test results are explicated as follows:

The influence of E-service quality on website brand equity. As expected,

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the causal path from E-service quality to website brand equity is

significant ( = 0.96, t = 13.36). This result verifies that E-service quality

has positive impact on website brand equity. Thus, the results provide support for H1. This relationship has previous empirical support (Yoo,

Donthu and Lee, 2000)。The influence of website brand equity on perceived risk. The results shown in Table 4 indicate a significant negative relationship between website brand equity and perceived risk ( = -0.41, t = -12.34). Thus, H2 is supported. Aaker (1991) pointed out that the significance of brand profile lies in that famous brands are liable to be taken into buying options and assessed by consumers; he also believed that brand equity can reduce the purchase decision risk that customers perceive. Therefore, the level of brand equity has influence on how consumers’ perceived risk of products is as well (Dunn, Murphy & Skelly, 1986), which is consistent with our research results. The influence of website brand equity on customer value. As evident in Table 4, website brand equity significantly affects customer value ( = 0.91, t = 20.55). Thus, H3 is supported. The customer value in this research is composed of the dimensions of “utilitarian value” and “hedonic value”. The overall research results in this part suggested that the higher the customers’ e-shop brand equity is, the higher the level of “utilitarian value” and “hedonic value” in customer value tend to be. Hence, a higher website brand equity means consumers think the products and services they purchase at an e-shop are worthwhile, inexpensive and useful, that is, the product quality and product price are equivalent. Also, the products and services such e-shop offers are pleasant and boredom-relieving enough to keep consumers lingering in this e-shop.

Of all the studies today, not only few had empirical research in the influence between brand equity and customer value, but also every one took physical products as the subject of empirical study. Urde (1994) contended brand orientation is a key strategy for maintaining existence and growth for enterprises. Hence, whether in physical environment or virtual one, brands are very powerful, because they are a means of conveying products and service overall (Hanson, 2000). Therefore, in the

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e-shopping environment of fierce competition, only by establishing and enhancing brand equity and further creating customer value can competitive edge be sustained.

The influence of perceived risk on customer value. As showed in Table 4, the results do not support the link between perceived risk and behavioral intention, which means the negative effect of perceived risk on behavior intention is not verified in this study ( = -0.04, t = -1.45). It was found from structural equation modeling that Hypothesis H4, which is the effect of perceived risk on behavioral intention, did exhibit negative influence, yet it was not significant. The reason of which, when inducted, was most e-shoppers are students, while the majority of students are over three years in terms of their history of internet use, meaning that most e-shoppers are very acquainted with the cyber world. Also, each e-shopping expense was low, which means most e-shoppers are low in buying power, so that the e-shopping expense are all low, and the perceived risk is relatively low, too; this resulted in insignificance of the relationship between perceived risk and behavioral intention. Therefore, Hypothesis 4 of this research was not supported.

The influence of customer value on behavioral intention. As can be seen in Table 4, the causal path from customer value to behavioral intention is significant ( = 0.90, t = 15.16). This result verifies that customer value has positive impact on behavioral intention. Thus, the results provide support for H5.

Customer value has positive influence on customer behavioral intention, which reveals that the higher the customer value is, the more capable it is of enhancing customer behavioral intention. In other words, it will help to strengthen customer behavioral intention when the products and services, and product quality and prices at an e-shop meet the demands that consumers care about, and during the transaction process where consumers purchase products or services, the e-shop is capable of providing them positive sensual mood (e.g., pleasure, joy and security) to leave with good experience of usage.

Table 4 Structural Parameter Estimates and Goodness-of-Fit Indices

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Hypotheses Paths Estimatea t valueH1 ESQ WBE 0.96 13.36*

H2 WBE PR -0.41 -12.34*

H3 WBE CU 0.91 20.55*

H4 PR BI -0.04 -1.45H5 CU BI 0.90 15.16*

(130) =1346.88 /df=1.97 GFI=0.82 AGFI=0.8

NFI=0.94 NNFI=0.93 CFI= 0.94PNFI=0.80 PGFI=0.62 IFI=0.94RFI=0.93 RMSEA=0.11

Legend: ESQ = E-service Quality; WEB = Website Brand Equity; PR = Perceived Risk; CU = Customer Value; BI = Behavioral Intentiona Standardized estimate* Significant at p< .05 (t>1.96 or t<-1.96)

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E-service Quality品質 up (u/ ((

Website Brand Equity

Perceived Risk

Customer Value

Behavioral Intention

X3 X4 X5 X6 X7

X2

X10.58

Y1 Y2 Y3 Y4

Y5 Y6 Y7

Y8 Y9

Y10 Y11

0.650.84 0.43 0.77 0.65 0.59

0.800

0.77 0.79 0.77

0.840.83 0.51

0.73 0.56

0.78 0.89

0.96(13.36)-0.41(-12.34)

0.91(20.55)

-0.04(-1.45)

0.90(15.16)

Note: Continuous lines are supported paths and dotted lines, unsupported.

Figure 2 Results of research model

6. Discussion6.1 Summery of Findings

In examining the affecting relationship between e-service quality, website brand equity, perceived risk, customer value and behavioral intention, this research tested the applicability of the gathered samples of e-shop users with LISREL model. It was shown that the overall arrangement of theoretical model this research presented met an accepted level for testing, indicating that the theoretic model of this research was supported, suggesting that there are influencing relationships between these five constructs. From the research results it is found that e-service quality positively affects website brand equity, that website brand equity affects perceived risk negatively but customer value positively, and that customer value positively affects behavioral intention, except the preset negative relationship between perceived risk and behavioral intention which was not supported herein.

The values obtained from the factor loading that has been standardized can reflect the extent to which the observed variables and the latent variables are correlated. In other words, the correlation between different observed variables and their corresponded latent variables can help clarify the connotation of each of the latent variables. It is known from Figure 2 that in relation to website service quality, the standardized coefficient of meeting demand at 0.84 is an important factor for the cognition about website service quality by consumers who are to visit the e-shops. Also known is that in meeting demands, e-shop operators should bear in mind what the consumers care about most and should understand their needs, for example, to deliver the exact products of customers purchase on time. Providing clear statement about return goods and sending confirming e-mails are also among the demands that consumers most concern now.

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In respect of website brand equity, of the dimensions of website brand equity for e-shoppers, the standardized coefficient of brand loyalty at 0.80 is the most significant factor. This result suggests that treasuring brand loyalty is the most crucial factor to enhance e-shopper’s brand equity. Kotler and Keller (2008) pointed out that the cost of retaining existed customers is far lower than that of attracting new ones; whereas loyal customer will become a strong fence in competition, as consumers generally lack the motive to change their satisfactory brand to another. So, brand loyalty is a source of profit and, what is more, treasuring brand loyalty is an effective means to manage brand equity (Keller, 2008). In which, customer satisfaction and repeated purchases are two useful measures, and the marketing activity capable of enhancing brand loyalty also helps reinforce the strength of the website brand. Consequently, it is necessary to strengthen customers’ brand loyalty to the e-shop before it can increase their use of the e-shop.

In respect of customer value, of the cognitions about customer value of consumers at e-shops, the standardized coefficient of utilitarian value at 0.73 is the most important factor. Such result suggests that treasuring utilitarian value is the key factor to upgrade the cognitions about customer value for consumers at e-shops. In upgrading utilitarian value, e-shop operators should provide more convenient shopping method to save shopping time for consumers and offer more useful products at better prices to meet consumers’ requirement for utilitarian value.

In respect of perceived risk, the standardized coefficient of financial risk at 0.84 contributes most to the dimension of e-ship consumers’ perceived risk. Thus, when shopping on the internet, consumers may have monetary loss and, if using credit card, would have sense of insecurity. EC Times (2007) also pointed out that the risks facing e-shopping include stealth of personal information, e-fraud and purchased merchandise or service failing to meet expectation. Besides, also included in the insecurity of transaction for consumers when shopping on the internet are improper disclosure of credit card password or personal information and fraud over the internet, hence, all these issues should be handled with more efforts by e-shop owners.

In respect of behavioral intention, the standardized coefficient of repurchasing intention at 0.89 contributes most to the e-shoppers’ cognition about behavioral intention. Such result suggests that e-shop owners should ponder over how to intensify consumers’ willingness to

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revisit the website and to shop thereby.

6.2 Managerial ImplicationsIn past research, the relationship between service quality and brand

equity has been tested in relation to physical shops; this research did the investigation in terms of virtual shops instead. This research also found such relationship with a significant level. In other words, the higher the e-service quality is, the more able it is to increase website brand equity. For website operators who are constructing their e-service, the dimension of “privacy/safety” is worth every operator’s attention. Though the “privacy/safety” dimension turned out with the less influence on users’ website brand equity than any other dimension in this research, it is still among the major dimensions of service quality under the studies of many researchers. With few notable differences in the service with safety provided by today’s major websites, if a website operator can make the consumers feel of a safer service with better privacy, and even emphasize safe as its website quality, it should be able to better elevate consumers’ brand equity from itself and further to intensify their purchasing intention.

It is further believed in this research that the higher cognition about its own brand equity for consumers an enterprise can provide, the lower their perceived risk is. That is, the cognitive value brought to consumers through brand would mitigate the buying decision risk when uncertainty is faced.

Amid the prevalence of internet use and online purchase becoming popular, an enterprise should know the customer value that consumers care about and should make best efforts to satisfy customer requirement if it is to create values for customers over the internet and by non-traditional methods to seek better performance. The dimension “hedonic value” is taken least seriously among customer values; however, it is believed in this research that it is what e-shops should make more efforts in in future if they wants to stand out among the many websites and become consumers’ favorite e-shops. This is because it was already pointed by research that background music can stimulate consumers and affect consumptive behavior (Morris and Boone, 1998). Music of fast rhythm is more potential of cheering, pleasing and exciting people than slow rhythm (Hevner, 1937; Bruner, 1990) and merry music can bring out cheerful emotion in consumers. Hence, e-shops can also put background

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music on their web pages to create a pleasant and easy atmosphere for shoppers and increase their frequency of visiting and further entice their buying intention. The related managerial implications above are hoped to be provided as reference for website operators.

6.3 Limitations and Further Research6.3.1 Limitations

Limitations to this research are as follows:(1)Limitation to sampling design: due to the limitation by time and

expenses, this research adopted online convenience sampling, and the samples thus might less powerful than random samples. As there would be restricted in theory, large sample was used to compensate for such limitation.

(2)This research took chiefly e-shops as subjects, whereas every industry are different, the results hereof cannot be inferred to other industries.

6.3.2 Further Research Below are recommendations for subsequent researchers: (1)Many factors affect consumers’ online behavioral intention; this

research investigated these intentions with only e-service quality, website brand equity, customer value and perceived risk; the other factors which are not covered and discussed here can be further explored by subsequent researchers.

(2)This research took online purchase shops as example; we suggest subsequent researchers to continue to use the research framework hereof to compare, among diversified e-shops in different forms, such as auction website and paid downloadable software or service, the differences in service quality, brand equity, customer value, perceived risk and behavioral intention brought to customers by different types of e-shops.

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