CONSUMER BEHAVIOUR TOWARDS E-MARKETING: A STUDY OF JAIPUR CONSUMERS Abstract (summary)

This paper examine the key consumer behaviour attribute and relation among them in E-marketingperspective.

Attempt has been made to study the acceptance rate of e-marketing among the Jaipur consumers and its

impact on their purchase decision. Result shows that people irrespective of age and gender surf internet.

However significant difference exists between the age and attributes of online trading but it do not have any

relation with the gender. Most of the respondents are hesitant to purchase items over internet because of

security concerns. Most of the respondents irrespective of gender of different age group (especially age group

of 18-30 years) find e-shopping more convenient & time saving and prefer credit card as the convenient mode

of the payment. Paper give direction to improving delivery and advertising web-products & services to achieve

objective of E-marketing and E-commerce in long run. [PUBLICATION ABSTRACT]

ABSTRACT

This paper examine the key consumer behaviour attribute and relation among them in E-marketingperspective.

Attempt has been made to study the acceptance rate of e-marketing among the Jaipur consumers and its

impact on their purchase decision. Result shows that people irrespective of age and gender surf internet.

However significant difference exists between the age and attributes of online trading but it do not have any

relation with the gender. Most of the respondents are hesitant to purchase items over internet because of

security concerns. Most of the respondents irrespective of gender of different age group (especially age group

of 18-30 years) find e-shopping more convenient & time saving and prefer credit card as the convenient mode

of the payment. Paper give direction to improving delivery and advertising web-products & services to achieve

objective of E-marketing and E-commerce in long run.

Keywords: Consumer, Behaviour, E-Marketing, E-commerce, Online, Internet.

1. INTRODUCTION:

E-marketing can be defined as marketing of products and services on electronic media. E-marketing is one of

the latest and emerging tools in the marketing world. It include the creative use of internet technology

including use of various multimedia, graphics, text etc with different languages to create catchy

advertisements, forms, eshop where product can be viewed, promoted and sold. E- marketing does not simply

entail building or promoting a website, nor does it mean placing a banner ad on another website. It include

advertisement (flash, text, graphics, audio or video), product display, product navigation, 3-D products view,

basket selection, checkout and payment. E-marketing & internet marketing terms are used in the same sense.

This form of marketing is equally applicable in most of the business models:

* E-commerce - Direct sales of goods to the mass customer/consumer or the business customers.

* Publishing Services - where advertisement are sold

* Lead-based websites - like policy bazaar, sulekha where sales leads are generated are sold to either third

party or used in-house to convert them into sales through appropriate channel.

* Affiliate marketing - a referral marketing strategy where reward is given for referring product, company,

orwebsite to other friends, relative or in nutshell other potential customer or target segment.

Think of a situation where each time marketer has to do media planning and repeated telecast of same

advertisement to reach the different customer as and when they can be targeted and very less option of

customization per segment is available but E- marketing is a very cost effective tool where customization is

very easy and affordable along with very less criticality of managing the marketing efforts. As respondent hit

can be stored easily with the monitoring and statistical software's it become inexpensive, fast, reliable to

perform data analytics and majorly all the aspects of an e- campaign can be traced, stored, analysed, and

tested. The advertisers can use a variety of methods: pay per impression, pay per click, pay per play, or pay

per action. Therefore, marketers can determine which messages or offerings are more appealing to the

audience. Emarketing is convenient than the traditional marketing for both customer and the marketer. It

offers large number of variety for the particular product relatively with lower prices and in less time.

But use of E-commerce requires customers familiarity with the latest innovation both in digital technology as

well financial and legal domain. In this way it appeal is limited due to requirement of High speed Internet

connections, overly-complicated websites, from the buyer's perspective, the inability of customer to touch,

taste or to smell or to have the trail before making them purchase online , and among them biggest is the

concern of security with online payments etc.

2. LITERATURE REVIEW:

The Internet is an open worldwide communication network, linking countless number of computer networks

throughout the world, through an intensive network of telephone lines. The increased availability of Internet is

influencing the growth of Internet users around the world. The popularity of e-marketing has been increased

tremendously in last 15 years. Companies are investing heavily in promotion of their products & services via

internet based marketing. But its growth rate is relatively slower as compared to other emerging technologies.

The prominent reason of slower growth than expected may be due a large proportion of population in India as

well as other developing & under developed countries that people are still not aware of computers & internet

technology also security concern regarding personal information on websites. Companies need to create buying

behavior of the consumers.

Studying buying behaviour, motives and intention along with the attitude of the online buyers is within the

theoretical constructs of the Theory of Reasoned Action. The Theory of Reasoned Action (Fishbein, 1980)

examines the relationship between attitudes and future intention to participate in these buying behaviors. The

behaviors include: when they click on banner ads (with which site and age group), response to e-mail

advertisements, way in which product information is searched using search engines and within the site, use of

comparision engines, attention and time to customer review and reaction toward them, product basket, online

support services, use of e-mail service, feedback form, checkout.

According to Cheung et al (Online Consumer Behavior: A Review and Agenda for Future Research, 2003), a

base model called Model of Intention, Adoption, and Continuance (MIAC) for the development of an online

consumer behavior framework. This model predicts that behavior is governed by intention. Satisfied consumers

are most likely to continue hence adoption and continuance are connected to each other through several

mediating and moderating factors such as trust and satisfaction. Their are Individual/Consumer characteristics,

Environmental Influences, Product/Service Characteristics, Medium Characteristics, and Online Merchants and

Intermediaries Characteristics which affect the consumer behaviour.

Culture can also be considered as one of the critical factors in both adopting and the success of E-marketing.

The first element in the adoption of E-marketing is the availability of a supportive atmosphere and

environment. In order for the E-marketing tools (i.e. the Internet) to serve as an effective marketing tool, all

parties in the relationship or the transaction must be familiar with PCs and appreciate the benefits and the

potential applications of the Internet and WWW. Without a supportive culture, technology may not be able to

replace fully the enterprise-customer relationships. If the culture place more value on strong relationships in

business and people prefer informal and personal relationship based communication there will be either no or

low implementation for E-marketing. This strong human orientation can make the self service mode of many

Emarketing based activities somewhat unattractive. On the other hand, there are a lot of cultural aspects that

can affect E-marketing adoption enterprises. These aspects include: people attitude towards E-

marketingactivities, trust, security, lack of social acceptance for electronic economic activity and customer

acceptance and participation in the E-marketing transaction.

3. OBJECTIVES & HYPOTHESIS OF RESEARCH:

Our research to study consumer behavior on e-marketing is based on certain objectives:

* To study awareness of e-marketing among the people in Jaipur city.

* To study the acceptance of e-marketing among consumers.

* To study the impact of e-marketing on purchase decision of consumers.

* To study the impact of frequency of web adds on purchase decisions of consumers.

MAJOR HYPOTHESIS INCLUDES:

* Age group between 18-30 years surf internet most.

* Gender does not play any role in internet surfing.

* There is high degree correlation between income of the respondents and their purchase decision.

* Respondents find e-shopping more convenient because it is time saving, availability of alternatives to choose

from & possibly less expensive products and services.

* Most of the respondents are hesitant to purchase items over internet because of security concerns.

* Usage of newer technology in online trading has made process more complicated, affect buying behavior of

respondents. Most of the respondents prefer traditional buying because they do not prefer changes.

4. RESEARCH METHOD:

Research on the effect of consumer behaviour towards e-marketing is a descriptive research. Here population

represents residents of JAIPUR (Rajasthan, India) city. Sample selected comprises of business professionals,

students & other educated people of urban area only. Study undertaken use stratified sampling i.e. population

is divided into a 3 strata according to age, income & occupation. For each stratum, 25 respondents were picked

by random means from different areas. Sample size of research is arbitrarily taken as 75 for the convenience

of research. Questions were prepared using Nominal scale & Ordinal scale as attributes studied were non

parametric. After checking the validity & reliability of the questionnaire primary data was collected from

respondents in city malls(City Pulse, Vishal Mega Mart, Inox) , cyber cafes including Reliance Web World, Sify

internet cafe. Since scale used in the questionnaire was non- parametric in nature therefore data was coded in

order to analyze data. SPSS (Statistics Packages of Social Software) 17.0 was used as analysis tool. To

determine the causal-effect relationship between different variables, CHI Square test was used.

5. DATA ANALYSIS & FINDINGS:

Since data collected is nonparametric in nature therefore data analysis is done using CHI SQUARE test at 5%

significance level (=0.05). Null hypothesis is rejected where .0.05 & it is accepted when >0.05.

SPSS software is used to analyze data. Distribution of study samples according to three strata of the research

is as follows:

Hypothesis 1: Age group between 18-30 years surf internet most. In order to prove above hypothesis CHI

SQUARE test is conducted.H0: There is no significant difference between age & internet surfing or there is no

relation between age of the respondents & internet surfing. HA: There is significant difference between age of

the respondents & internet surfing, in other words there is relation between age of the respondents & internet

surfing. Test statistics showed that Chi-Square calculated at 12 degree of freedom is 111.373 at 0.00%

significance level (Table-1). Hence null hypothesis is rejected at =0.00 & alternate hypothesis (i.e. there is

strong relation between age of the respondents & internet surfing) is accepted. However Test statistics shows

that there is significant relationship between occupation and internet surfing frequency of the respondents

(Table-2)

Hypothesis-2: Gender does not play any role in internet surfing. Chi-square test between gender of the

respondent & internet surfing data is done. Test statistics shows that Chi-square calculated at 72.9%

significance level is 31.093 (Table-3). It means that null hypothesis is accepted i.e. there is no relation

between gender and internet surfing of the respondents.

Hypothesis-3: There is high degree correlation between income of the respondents and their purchase decision.

Chi-square test is conducted between income of the respondents & their purchase decision affected by

emarketing. Chi-square statistic shows that at 0.0% of significance level calculated value comes out to be

57.653 at 15 degree of freedom (Table-4a). Hence it can be concluded that null hypothesis is rejected &

alternate hypothesis is accepted that there is significant difference of a strong relation between income of the

respondents & purchase decision. Also a significant difference is found between age, occupation of the

respondents and their purchase decision (Table-4b, 4c).

Hypothesis-4: Respondents find e-shopping more convenient because it is time saving, availability of

alternatives to choose from & possibly less expensive products and services. In study likert scale (five point

agreement-disagreement scale) was used to determine respondents' response. It was found that 65% were

highly agreed on easy accessibility of online products. Further, most of the respondents found online shopping

more convenient & time saving than brick & mortar system. Pie chart depicting the same is shown below.

Chi-Square test is conducted to determine significant difference between easy accessibility, convenience & time

saving attributes of online trading and age of the respondents. Statistics showed that null hypothesis is

rejected at =0.00% (Table-5a). Hence alternate hypothesis is accepted; it implies that there is a significant

difference or relation exists between age and attributes of online trading. Also a significant difference is found

between income, occupation and above attributes (Table-5b, 5c). Furthermore it was found that there is no

significant difference between gender of the respondents and above three attributes. At =72.9% (Table-5d)

null hypothesis is accepted; hence gender has no relation with above attributes.

Moreover respondents had positive response regarding seasonal/special offers on internet. Respondents'

reaction is shown below. To determine the relationship between age of the respondents and special/seasonal

offers in web advertisements, Chi-Square test is conducted. Test statistics showed that null hypothesis is

rejected at 0.00% significance level (Table-6a); hence alternate hypothesis is accepted i.e. there is significant

difference between the two variables. Since sample size largely consists of respondents of age group between

18-30 years hence it can be inferred that young respondents are more attracted towards seasonal or special

offers. Also it was found that gender has no relation with seasonal offers (Table-6b).

Respondents' reaction was mixed regarding price & quality of the products/services offered online. 35% of the

respondents agreed regarding fair price & 31% on quality of products/services offered, while 28% disagreed on

the former & 33% on the later. 37% & 36% of the respondents had a neutral view on the two attributes

respectively.

There was higher percentage of disagreement on "privacy of personal information & on time delivery of

products/services". 61% & 50% of the respondents disagreed on above two attributes respectively. 24% &

28% agreed & 15% & 22% had neutral view on two attributes respectively.

To determine relationship between price, quality, on time delivery of products/sevices & personal information

privacy of the online traded products/services and gender & age of the respondents, Chi-Square test was

conducted. Test statistics showed that at =72.9% (Table-7a) there is no relation between above attributes of

the online traded products/services and gender of the respondents. It can be inferred that both male & female

have simiar response regarding above attributes. While a significant relationship is found between age of the

respondents and price, quality, & personal information privacy of the online traded products/services(Table-

7b). It implies that a significant number of respondents of all age groups have a neutral view regarding fair

pricing & quality of the products/services, while other respondents of younger age between 18-30 years agree

and respondents of higher age than 30 years disagree on two attributes. While there was no significant

difference found between age & personal information privacy of the online traded products/services of the

respondents (Table-7c). It implies that nearly all respondents have a similar view they highly disagree on

above attribute.

Hypothesis-5: Most of the respondents are hesitant to purchase items over internet because of security

concerns.

In order to prove the above hypothesis respondents were asked to rate the drawbacks of the online shopping

in the rating scale of 1-5 and it was observed that 52% of the respondents claimed security concern regarding

disclosure of personal information as first rank. 47% of them rated lack of physical approach on

products/services offered, second. While quality & authenticity of products/services offered was rated fourth by

48% of the respondents. Chi-Square test is conducted to determine that whether there is any relation between

gender and security concern, lack of physical approach and quality & authenticity of the products/services

offered via online trading. Test statistics showed that null hypothesis is accepted at alpha is equal to 72.9%

(Table-8a) between gender and security concern, lack of physical approach and quality & authenticity of the

products/services offered via online trading. Hence it implies that there is no relation or there is no significant

difference between drawbacks of online trading & gender of the respondents. Chi-Square test showed that

there is relation between age group, income of the respondents and above drawbacks (Table-8b, 8c).

Hypothesis-6: Usage of newer technology in online trading has made process more complicated, affect buying

behavior of respondents. Consumers were asked if product/service of their requirements is being offered online

at reasonable price, then will they prefer to buy that product/service online or purchase the same from brick &

mortar system. It is found that 68% of the respondents claimed product/service of their requirement through

traditional shop, while 32% favoured online purchases. To prove the hypothesis statistically Chi-Square test is

conducted between age & preference of the respondents in purchasing product/service. Test statistics showed

that null hypothesis is rejected at significance level 0.00% (Table-9) and alternate hypothesis is accepted i.e.

there is relation between the two variables. Hence people do not prefer online trading as compared to

traditional purchasing. It can be inferred that besides other drawback of online trading, respondents are

conventional and have traditional approach towards shopping. People resist changes and introduction of newer

technology has indeed made process of online shopping much complicated.

Mode of Payment:Respondents were asked to select the mode of payments while shopping online. 52%

preferred credit card payment, while 28% opted for debit card payments, 12% preferred payments through

cheques and 8% preferred for demand draft or pay order services. Chi square test is conducted to determine

whether the relationshSip between mode of payment & income group of the respondents exist or not. Test

statistics showed that null hypothesis is rejected at =0.00% (Table-10) and alternate hypothesis is accepted

i.e. there is significant difference between the two variables or mode of payment is depended upon income of

the respondents. People having monthly income Rs 10,000 or more prefer credit card payments.

Hypothetical Web Advertisement Attributes: Respondents were asked to rate hypothetical web advertisement

having attributes; frequency of occurrence (very high-very low), attractiveness in presentation of web

advertisement (high, average), content of web advertisement (good, average, below average), offers (yes,

no). Different combinations of these attributes were assigned hypothetical web advertisements. It was found

that 32% respondents ranked WEB AD. A as their first choice having attributes; frequency (very high),

attractiveness in presentation of web advertisement (high), content of web advertisement (average), offers

(yes). Also 32% of the respondents ranked WEB AD. B as their first choice having attributes; frequency of

occurrence (high), attractiveness in presentation of web advertisement (high), content of web advertisement

(good), offers (yes). While 23% of the respondents ranked WEB AD.C as their first choice having attributes;

frequency of occurrence (average), attractiveness in presentation of web advertisement (high), content of web

advertisement (below average), offers (yes). And WED AD. D & WEB AD. E were ranked 7% and 4% as their

first choice respectively.

Chi-Square test is conducted to determine the relation between age of the respondent and hypothetical web

advertisement. Test statistic showed that null hypothesis is rejected at =0.00 (Table-11a) between Web Ad.

A, B, D, E & age of the respondents. It means that there is significant difference between age & web

advertisement attributes or there is strong relation between age of the respondents and attributes of web ad.

preference. Chi-Square test to identify the relationship between web ad. preference and gender of the

respondents is also conducted. Test statistics showed that at =72.9% (Table-11b) null hypothesis is accepted

i.e. there is no significant difference between the two variables or gender does not play any role in preference

of web advertisement attributes.

Preferred Products/Services & Websites For Online Shopping: Respondents were asked to rate various online

products/services according to their preference. It was observed that respondents preferred e-ticketing (660

out of maximum rating points 750) followed by e-billing (553 out of maximum rating points 750), ebanking

(525 out of maximum rating points 750) & online shopping of products (305 out of maximum rating points

750). E-ticketing was found to be the most preferred choice out of four choices.

Chi-Square test statistics showed that there is no significant difference between gender and eticketing, e-

billing, e-banking online shopping of products (Table- 12).It can be inferred that preference of online

products/services has no relation with the gender of the respondents. Also it was found that there is significant

difference between age, income and above online services. It implies that people of younger age between 18-

30 years and monthly income Rs.20,000 or less prefer e-ticketing. Respondents were asked to recall name of

any three websites where they prefer/would prefer online shopping.

It was observed that 19% of the respondents preferred IRCTC website (Indian railways online

reservationwebsite), 15% preferred Yahoo (comprehensive website for products/services), while 14% opted for

ebay (comprehensive website for products/services).

6. Inferences

Purpose of study was have a thorough analysis regarding different attributes of e-marketing with age, gender

& income of the respondents. Our analysis on the respondents of Jaipur city showed various results.

* It was found that there is no significant difference between internet surfing & gender of the respondents.

While age group of 18-30 years surf internet most. Main possible reason behind this may be that younger

people are more technology oriented & also they may be working in organizations where they need to work

upon computer and internet.

* A strong relation exists between monthly income, occupation and purchase decision of the respondents.

People with higher income group usually have little time to go and purchase products/services from tradition

shops because of their busy schedule. Hence in order to save time they trade online.

* Most of the respondents (irrespective of gender) are hesitant to trade online because of security reasons.

There have been cases in the past where personal information regarding passwords & identification theft has

occurred. Those incidences have feared consumers. Besides this lack of physical approach, time required to

deliver products & authenticity of the product merchandised are other factors. Consumers do not have faith in

most of the online trading sites. Also usage of newer technology has made online trading more complicated &

people resist changing, that is why consumers prefer traditional shopping as compared to online trading.

* Most of the respondents irrespective of gender of different age group (especially age group of 18-30 years)

find e-shopping more convenient & time saving. A wide range of products/services with variety are available to

choose from and also in general traditional shopping in India has never been pleasant for Indian consumers.

There has been a mixed reaction in response to quality & authenticity of the products offered.

* Most of the respondents irrespective of gender of different age group prefer credit cards as the most suitable

option of payment followed by debit cards. This is probably due to the fact that with credit cards we can

purchase products/services on credit and also now a days they can be easily obtained from different banks. It

was also found in our analysis that there is a strong relationship exist between mode of payments and income

of the respondents. It implies that electronic payment (credit cards, debit cards) has also gained popularity in

middle income group.

* Most of the respondents responded similarly as predicted when they have given options to rate various

attributes of hypothetical web-advertisement. By interpreting their reaction graph it can be inferred that

information content, additional service-offered & frequency of web-advertisement leave behind major impact

on people mind. Service offered & the way of presentation of information plays a major role in positioning an

e-product in consumer mindset.

* Most of the respondents irrespective of gender of different age group prefer e-ticketing as the most

preferred/popular service followed by e-booking & e-billing. This is most popular among all age groups as it

escapes people from long queues, saves time & distance which might people would have to travel to get their

billing & ticketing done on time. Reservation of hotel rooms & tours has become quite easier at finger-tips.

* Most preferred websites among the respondents comes out to be IRCTC, followed by yahoo & e-bay when

given a freedom to recall three website on their own. By analyzing their response we can interpret that e-

ticketing is the major choice among the people for which they use web services followed by ebooking i.e

(YAHOO) & online shopping option i.e (E-BAY) available to them.

7. CONCLUSION:

E-marketing is rapidly changing the way people do business all over the world. In the business-to-consumer

segment, sales through the web have been increasing dramatically over the last few years. Customers, not

only those from well-developed countries but also those from developing countries, are getting used to the new

shopping channel. Understanding the factors that affect intention, adoption and repurchase are important for

researchers and practitioners alike. E-marketing is gaining popularity among people specially the younger

generation but in today scenario to become equally popular among all age groups e-marketing will have to

cover a longer distance. People have hesitations in using e-services due to security concerns, lack of physical

approach towards product offered, delays in product delivery along with price & quality concerns. More-over

people are more resistant to change & not easily adaptable to newer technology. 68% of respondent found

shopping from shop easier, convenient & preferable over online purchasing. Above finding clearly supports our

conclusion that people are tradition bound & have doubt in mindset as far as issue of online shopping/purchase

of product is concerned.

People have dubious attitude towards e-marketing of product & services mainly due to security concern related

to privacy of personal information. Personal information privacy should be given preference by the companies

involved in online marketing of product & services. The other major concern among people includes

authenticity of product & services offered online. Companies involved in online trading should focus on building

their brand awareness among people so that trust-worthy relationship can be developed between producers &

consumers. On-time delivery of products purchased through online shopping will prove to be quite beneficial in

a long run. Significant price-cuts should be offered to customers as there are relatively no/lesser intermediaries

involved as far as e-marketing is concerned. Currency fluctuation should be dealt with great care & steps

should be taken both by government & companies so as to reduce currency fluctuation to its minimal.

Promotional schemes should be launched to promote e-marketing business. Advertising of web-products &

services is one of the major issues where companies fail to attract potential consumers attention. Companies

should focus on offering informative advertisements which would contain product information along with

additional products & services offering which best suits needs of people. Such advertisements frequency should

be high so as to position the products & brands in consumer mindset. In a nut shell we can conclude that

emarketing has a potential to grow, only proper boosting needs to be done both at producer and consumer

level apart from government efforts.

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AuthorAffiliation

Dr. Sanjay Hooda,

Assistant Professor

Indira Gandhi P.G. Regional Center

Maharshi Dayanand University-

Rohtak, India

Mr. Sandeep Aggarwal,

Assistant Professor

Indira Gandhi P.G. Regional Center

Maharshi Dayanand University-

Rohtak, India

Appendix

(ProQuest: Appendix omitted.)

Copyright Educational Research Multimedia & Publications Apr 2012

The moderating effect of customer perceived value on online shopping behaviour Abstract (summary)

The purpose of this research is to examine the impact of e-service quality, customer perceived value, and

customer satisfaction on customer loyalty in an online shopping environment. There were two studies

performed in this research. Study 1 validated the self-regulating processes; Study 2 tested the moderating

effects of customer perceived value between satisfaction and loyalty. Structural equation modelling techniques

and linear hierarchical regression models were used to test the causal model. The study demonstrated that e-

service quality and customer perceived value influence customer satisfaction, and then influence customer

loyalty. In addition this study found that customers with a high perceived value have a stronger relationship

between satisfaction and customer loyalty than customers with a low perceived value. We found that there are

emotional and rational routes influencing customer loyalty in the online shopping process. This will contribute

to other research that clarifies the influencing process of online shoppers' motivation and behaviour. In the

pre-purchase stage, online retailers should focus on attracting consumers by the quality of e-service. In the

purchase stage, online retailers should address the emotional factors, such as customer satisfaction. In the

post-purchase stage, rational factors - such as customer perceived value - play important roles because they

can strengthen the relationship between satisfaction and loyalty. This study viewed the purchase process as a

different stage as consumers may make a choice at each of the purchase stages. Moreover this study found a

way to examine the relationship between customer satisfaction and loyalty by exploring the moderating effects

of customer perceived value.

Full Text

Introduction

The business-to-customer (B2C) online market has been growing rapidly and changing business patterns over

the past several years. In the USA online retail sales are estimated to have grown from $172bn in 2005 to

$329bn in 2010 ([51] Johnson, 2005); thus, electronic marketing activities have drawn a lot of attention. E-

commerce changes the business pattern, with manufacturers, distributors, and customers using the internet as

a tool for communication, and transactions have been creating new platforms for a competitive strategy ([15]

Celuch et al. , 2007). Therefore an understanding of how consumers leverage the features of the internet to

make purchasing decisions in the e-commerce environment would help managers devise suitable marketing

strategies ([110] Wu and Lin, 2006).

Online shopping exhibits different characteristics from traditional shopping ([11] Burke, 2002; [36] Eroglu et

al., 2003; [60] Koernig, 2003). Online shopping can offer greater product selection, accessibility and

convenience without the restrictions of time and space ([10] Brynjolfsson and Smith, 2000). There are also

fewer tangible and intangible transaction costs in an online shopping process, such as product searches, price

comparisons and transportation, which result in higher shopping convenience values ([8] Blake et al. , 2005;

[20] Childers et al. , 2001; [44] Grewal et al. , 2004) than those of traditional shopping. Customer loyalty has

been recognised as one of the important factors in creating profitability for companies. However in online

environments it is more complicated to establish a social connection between firms and customers due to the

lack of a physical environment, social distances between companies and customers ([93] Schijns, 2003) and

anonymous and automated shopping contexts ([47] Head et al. , 2001). Furthermore consumers can compare

competing products and services with minimal expenditure of personal time or effort, which results in

competitive business markets and lower brand loyalty ([99] Srinivasan et al. , 2002). Therefore, this study

intends to explore the determinants of loyalty in an online shopping environment.

Customer perceived value has recently received considerable attention in the field of marketing strategy ([106]

Ulaga and Eggert, 2006). This is because it plays an important role in predicting purchase behaviour ([19]

Chen and Dubinsky, 2003), achieves sustainable competitive advantages ([58] Khalifa, 2004; [71] Lindgreen

and Wynstra, 2005), and affects relationship management ([90] Payne et al. , 2001). E-commerce research

should pay special attention to the motivations or desired values behind consumers' use of the online medium

([26] Cowles et al. , 2002). In an online environment customers can easily find alternatives, and therefore how

to build long-term relationships presents a more difficult challenge for an e-commerce firm. Perceived value

contributes to the loyalty of an electronic business by reducing an individual's need to seek alternative service

providers ([2] Anderson and Srinivasan, 2003). Most studies have examined customer value in the context of

offline rather than online consumer behaviour ([82] Overby and Lee, 2006). Although customer perceived

value in the online shopping environment is of crucial importance, previous studies have neglected that

variable ([17] Chang et al. , 2005). Hence it is necessary to understand the role of customer perceived value in

online shopping behaviour.

Although there is a large body of evidence from e-commerce contexts that supports the notion that higher

levels of overall customer satisfaction generate higher levels of loyalty ([2] Anderson and Srinivasan, 2003;

[21] Chiou, 2004; [105] Tsai et al. , 2006), some researchers believe that the relationship between satisfaction

and loyalty may be influenced by perceived value ([2] Anderson and Srinivasan, 2003). Others believe that

perceived value is only a psychological process between customer satisfaction and loyalty ([21] Chiou, 2004;

[33] Devaraj et al. , 2002; [101] Szymanski and Hise, 2000). Therefore this study intends to explore whether

a moderating effect of perceived value between customer satisfaction and loyalty exists.

Previous marketing studies have pointed out that service quality, perceived value and customer satisfaction are

important success factors in gaining competitive advantage ([117] Zeithaml et al. , 1996; [84] Parasuraman et

al. , 1988; [89] Patterson and Spreng, 1997; [59] Khatibi et al. , 2002; [64] Landrum and Prybutok, 2004;

[113] Yang and Peterson, 2004; [114] Yu et al. , 2005). Among these factors, some are emotional variables

and some are rational variables, which lead to distinct routes or processes of influencing consumer loyalty, i.e.

emotional decision processes and rational decision processes. Although previous studies have examined the

relationships between these constructs, they neglect to explain what type of influencing route or process is the

most effective one in influencing consumer loyalty. Moreover consumers may change their minds and switch

from one shop to another at different purchase stages ([42] Frambach et al. , 2007; [25] Choudhury and

Karahanna, 2008). Therefore understanding the dynamics of influence processes on customer loyalty can assist

companies to make better decisions regarding different consumer purchase stages.

Among the factors influencing consumer loyalty, consumer satisfaction has considerable impact on customer

loyalty ([14] Castaneda et al. , 2009). Although this relationship between consumer satisfaction and loyalty is

intuitive, few studies explore how to strengthen it. In an online environment, even if consumers are satisfied

by a specific website, they are still likely to find alternative sites and switch to them. Because consumers can

easily compare information and find other websites that provide similar products or services ([2] Anderson and

Srinivasan, 2003; [104] Terblanche and Boshoff, 2010), the relationship between consumer satisfaction and

loyalty is weaker than in offline shops. However past studies have not attached importance to this issue.

Therefore this study aims to find a variable to strengthen the relationship, such as customer perceived value.

[4] Bagozzi's (1992) self-regulatory process explains consumer behaviour in three parts:

the appraisal process (the evaluation of internal or situational conditions as they apply to one's wellbeing);

emotional reactions (satisfaction); and

coping responses (behaviour).

In this research we adopt this process to clarify online shopping behaviour. The objectives of this research are:

- to examine the sequence and relationships of the customer behaviour process, including the appraisal

process (e-service quality, customer perceived value), emotional reactions (satisfaction), and coping responses

(loyalty) and find different routes to influence customer loyalty across different purchase stages; and

- to explore the moderating effect of customer perceived value on the relationship between customer

satisfaction and customer loyalty.

Theoretical framework

E-service quality

Service quality is generally defined as the difference between expected service and perceived service ([45]

Gronroos, 1982; [84] Parasuraman et al. , 1988, [85] 1991). The conceptualisation of service quality has its

roots in the expectancy disconfirmation theory ([24] Collier and Bienstock, 2006), so the evaluation of service

quality results from comparing the perception of service received to prior expectations of what that service

should provide ([22] Choi et al. , 2004). Today the internet has become a critical channel for the sale of most

goods and services ([118] Zeithaml et al. , 2002; [103] Teo, 2006), but the traditional service quality

dimensions cannot directly be applied to internet retailing, because they represent a different and unique

service delivery process. For example consumers can compare a product's technical features and price more

easily through internet channels than traditional channels ([92] Santos, 2003; [107] Warden et al. , 2006;

[103] Teo, 2006). Generally, online customers always expect equal or higher levels of service quality than

traditional channel customers ([65] Lee and Lin, 2005). Therefore understanding the key determinants of the

success of online retailers is important. Most electronic commerce companies are beginning to realise the

importance of e-service quality in determining the success or failure of online retail businesses ([112] Yang and

Jun, 2002; [118] Zeithaml et al. , 2002; [92] Santos, 2003; [55] Jun et al. , 2004).

According to [118] Zeithaml et al. (2002, p. 363) e-service quality is defined as "the extent to which

a websitefacilitates efficient and effective shopping, purchasing, and delivery of products and services". Service

is broadly defined to include both pre-web and post-website service aspects. Numerous researchers have

developed scales to measure how customers assess e-service quality. For example [65] Lee and Lin (2005)

identified the main factors influencing customer perception of the e-service quality in online

shopping: website design (degree of user friendliness), reliability (reliability and security), responsiveness

(responsiveness and helpfulness), trust (trust mechanisms provided by an website), and personalisation

(differentiating services to satisfy specific individual needs). [72] Loiacono et al. (2000) established a scale

called WEBQUAL with 12 dimensions:

informational fit to task;

interaction;

trust;

response time;

design;

intuitiveness;

visual appeal;

innovativeness;

flow;

integrated communication;

business processes, and

substitutability.

Overall these WEBQUAL dimensions are more pertinent to interface design than to service quality

measurement ([118] Zeithaml et al. , 2002).

In order to consider the customer-to-employee interaction aspect, other studies have developed more

complete measurements of e-service quality. For example [108] Wolfinbarger and Gilly (2003) used online and

offline focus groups, a sorting task, and an online survey of a customer panel to develop a scale named.comQ,

which has four dimensions:

website design;

reliability;

privacy/security; and

customer service.

After an extensive literature review [118] Zeithaml et al. (2002) developed the e-SERVQUAL model for

measuring e-service quality to study how customers judge it. This new model was drawn up through a three-

stage process involving exploratory focus groups and two phases of empirical data collection and analysis. It

contains seven dimensions:

efficiency;

reliability;

fulfilment;

privacy;

responsiveness;

compensation; and

contact.

[86] Parasuraman et al. (2005) recently split the seven dimensions into two separate scales:

E-S-QUAL; and

E-RecS-QUAL.

The first four dimensions are classified as the core service scale, and the latter three dimensions are regarded

as a recovery scale, since they are only salient when online customers have questions or problems. This study

compared the.comQ and e-SERVQUAL scales and found that the two scales have many similar aspects. In

order to simplify our dimensions we adopted.comQ scales (website design, reliability, security, and customer

service) as our measurable variables of e-service quality.

Customer satisfaction and loyalty

Customer satisfaction is fundamental to the marketing concept, which holds that satisfying customer needs is

the key to generating customer loyalty. Customer satisfaction generally means customer reaction in the

context of the state of fulfilment, and customer judgment of the fulfilled state ([79] Oliver, 1997). It is defined

as an overall positive or negative feeling about the net value of services received from a supplier ([109]

Woodruff, 1997). [63] Kotler (2000) described satisfaction as a person's feeling of pleasure or disappointment

resulting from comparing a product's perceived performance (or outcome) in relation to their expectations.

Now we consider the construct of satisfaction in the online context. [2] Anderson and Srinivasan (2003)

defined e-satisfaction as the contentment of the customer with respect to their prior purchasing experience

with a given electronic commerce firm. [73] McKinney et al. (2002) also posited that web-customer satisfaction

has two distinctive sources:

satisfaction with the quality of the website's information content; and

satisfaction with the website's system performance in delivering information.

Based on the definitions in the literature this study defines customer satisfaction as the overall positive or

negative feeling regarding their purchasing experience from a given online shopping firm, which is a subjective

judgment from personal emotions.

Maximising loyalty and the long-term value of customers' purchases is one of the most important goals of

awebsite ([98] Smith, 2005). Customer loyalty is complex and comprises many dimensions. [35] Engel et

al.(1982) defined brand loyalty as the preferential, attitudinal and behavioural response toward one or more

brands in a product category expressed over a period of time by a consumer. In addition, [79] Oliver (1997)

distinguished four phases of loyalty:

cognitive loyalty;

affective loyalty;

conative loyalty or behavioural intention; and

action loyalty.

It is currently accepted that loyalty includes two dimensions: attitudinal; and behavioural ([80] Oliver, 1999;

[116] Zeithaml, 2000; [18] Chaudhuri and Holbrook, 2001; [2] Anderson and Srinivasan, 2003; [62] Koo,

2006).

Attitudinal loyalty indicates a higher-order, or long-term and psychological commitment of a customer to

continue a relationship with a service provider ([30] Czepiel and Gilmore, 1987; [13] Caruana, 2002; [95]

Shankar et al. , 2003). Behavioural loyalty is defined as repeat patronage, meaning the proportion of

purchases of a specific brand ([74] Neal, 1999; [62] Koo, 2006). However action loyalty is too difficult to

observe and measure, so research tends to employ the conative or behavioural intention to measure customer

loyalty ([113] Yang and Peterson, 2004).

Therefore this study only investigates attitudinal loyalty and measures it from two dimensions:

repurchase intention; and

word-of-mouth.

Repurchase intention refers to consumers' evaluation of future purchases from the same company based on

their previous experience ([89] Patterson and Spreng, 1997; [48] Hellier et al. , 2003; [34] Durvasula et al. ,

2004; [94] Seiders et al. , 2005; [77] Olaru et al. , 2008). "Word of mouth" refers to evaluation in oral form of

a supplier's performance ([12] Buttle, 1998), which is positively associated with satisfaction ([37] File et al. ,

1994) and contains consumers' positive or negative statements about a product for sale on a

shoppingwebsite and is helpful for decision-making on purchases ([88] Park et al. , 2007; [87] Park and Lee,

2009).

It is considered difficult to gain loyal customers on the internet ([43] Gommans et al. , 2001). In previous

studies satisfaction and service quality were usually used for explaining customer loyalty, but the relationships

among them are complex and researchers have not reached a consensus on this. Most marketing studies also

seem to accept a theoretical framework in which quality leads to satisfaction ([31] Dabholkar et al. , 2000;

[83] Parasuraman et al. , 1985, [84] 1988), which in turn influences purchasing behaviour ([52] Johnson and

Gustafsson, 2000; [80] Oliver, 1999; [70] Lin and Sun, 2009). This quality-satisfaction-behavioural intentions

link is consistent with the generally accepted cognitive evaluations-emotional responses-behavioural outcome

causal chain ([79] Oliver, 1997). Furthermore service quality not only influences loyalty through satisfaction

but also directly. Many studies have modelled service quality as an antecedent to behavioural intentions and

found a significant link ([7] Bitner, 1990; [9] Boulding et al. , 1993; [117] Zeithaml et al. , 1996). Moreover, in

the online environment some researchers have suggested that better websites can make consumer

transactions easier and thus attract consumers to revisit or make a repeat purchase ([43] Gommans et al. ,

2001; [68] Li and Zhang, 2002; [110] Wu and Lin, 2006).

Satisfaction is the most relevant variable in the study of customer loyalty ([14] Castaneda et al. , 2009). In the

online environment researchers have found that the overall satisfaction experienced by online customers

reduces the perceived benefits of switching service providers, and thus yields stronger repurchase intentions in

the case of online e-retailing services ([101] Szymanski and Hise, 2000; [33] Devaraj et al. , 2002; [2]

Anderson and Srinivasan, 2003; [21] Chiou, 2004; [105] Tsai et al. , 2006; [69] Lin, 2007; [14] Castaneda et

al. , 2009; [70] Lin and Sun, 2009). In other words a dissatisfied customer is more likely to search for

information from alternatives and is more likely to yield to competitor overtures than is a satisfied customer

([2] Anderson and Srinivasan, 2003). Therefore this study intends to test the relationships among e-service

quality, customer satisfaction and customer loyalty as follows:

H1. E-service quality has a significant positive effect on customer satisfaction in an online shopping

environment.

H2. E-service quality has a significant positive effect on customer loyalty in an online shopping environment.

H3. Customer satisfaction has a significant positive effect on customer loyalty in an online shopping

environment.

Customer perceived value

Customer perceived value has been discussed in marketing research for a long time. Indeed, understanding

and delivering customer value is seen as a cornerstone of marketing, competitive strategy ([58] Khalifa, 2004;

[71] Lindgreen and Wynstra, 2005), retention of customers and relationship management ([91] Roberts, 2000;

[90] Payne et al. , 2001). Perceived value has its root in equity theory, which represents the trade-off between

the quality or benefits which the customer receives, and the costs such as financial, energy, time and mental

transaction costs that the customer incurs by evaluating, obtaining and using a product ([81] Oliver and

DeSarbo, 1988; [63] Kotler, 2000; [61] Komulainen et al. , 2007). However this simplification has been

criticised for ignoring some important intangible constructs (e.g. shopping experience, risk) and may be

misleading in measuring perceived customer value ([96] Sinha and DeSarbo, 1998). Hence [116] Zeithaml

(2000) defined perceived value as the consumer's overall assessment of the utility of a product based on

perceptions of what is received and what is given. In online retailing settings not only the product itself, but

also the website, the internet channel and the processes of finding, ordering, and receiving products contribute

value to customers ([57] Keeney, 1999). Therefore this study defines perceived customer value as a

consumer's perception of the net benefits gained based on the trade-off between relevant benefits and

sacrifices derived from the online shopping process, which is an objective evaluation from personal cognition.

Although perceived customer value has long been recognised in marketing research as an important concept in

influencing preference, satisfaction, loyalty, and other important outcomes ([29] Cronin et al. , 2000), most

studies have examined customer value in the context of offline rather than online consumer behaviour ([82]

Overby and Lee, 2006). In an online environment customers can find alternatives easily, therefore building

long-term relationships presents a more difficult challenge for e-commerce firms. Therefore it is necessary to

understand the role of customer perceived value on online shopping behaviour.

[56] Keng et al. (2007) suggested that the perceived excellence value reflects the product performance and

general consumer appreciation of a service provider who demonstrates expertise and maintains a reliable

service performance. Therefore service quality becomes the indicator for determining customer values. In the

customer satisfaction index (CSI) model the value perceptions will be directly influenced by perceived service

quality. Therefore we propose the following hypothesis:

H4. E-service quality has a significant positive effect on customer perceived value in an online shopping

environment.

Perceived value is the consequence of an overall assessment of perceived benefits and sacrifices, whereas

satisfaction is an overall positive or negative feeling about the net value of services received from a supplier

([109] Woodruff, 1997). There is no general consensus on the relationships among perceived value,

satisfaction, and loyalty in the field of marketing research. The assumption that perceived value directly

influences satisfaction or loyalty has been questioned. In this study we integrate empirical results and explore

the causal relationships linking perceived value, satisfaction, and loyalty from the perspectives of means-end

chain theory and economic theory.

First the means-end chain theory explains that personal values guide people's evaluations of relevant

attributes and the benefits of a product or service, and then these evaluations initiate goal-direct purchase

behaviour ([62] Koo, 2006). Therefore when customer perceived value is high they have positive evaluations

of and affection for the product, which is consistent with the result of the well-known customer satisfaction

index model ([39] Fornell et al. , 1996). This means that customers will always search for a business that can

provide better customer value. Second the economic theory of utility assumes that consumers are economically

rational, so they will try to achieve the maximum utility with minimum resources, for example budget, time

and cognitive capabilities ([49] Henderson and Quandt, 1958). Perceived customer value reflects consumers'

net gain from their consumption behaviour, thus it is likely to be used as an indicator of purchase intention

([19] Chen and Dubinsky, 2003). In other words, consumers are believed to choose certain products based on

their superior value compared to competing products. Based on these relationships among consumer perceived

value, consumer satisfaction and consumer loyalty, this study proposes the following hypotheses:

H5. Customer perceived value has a significant positive effect on customer satisfaction in an online shopping

environment.

H6. Customer perceived value has a significant positive effect on customer loyalty in an online shopping

environment.

Satisfaction is important for establishing long-term customer relationships and further generates loyalty ([2]

Anderson and Srinivasan, 2003; [21] Chiou, 2004; [105] Tsai et al. , 2006). The relationship between

satisfaction and loyalty seems intuitive and has been confirmed by many researchers ([76] Newman and

Werbel, 1973; [28] Cronin and Taylor, 1992). However the strength of the relationship between satisfaction

and loyalty has varied significantly under different conditions ([53] Jones and Sasser, 1995; [80] Oliver, 1999;

[2] Anderson and Srinivasan, 2003). Moreover the relationship between satisfaction and loyalty in traditional

commerce will differ from that in electronic commerce. In traditional commerce a dissatisfied customer is more

likely to search for information on alternatives and more likely to yield to competitor overtures than a satisfied

customer ([2] Anderson and Srinivasan, 2003). However in electronic commerce because of the lower search

costs ([6] Bakos, 1991) consumers can easily evaluate product benefits and costs objectively by comparing

product characteristics and prices online ([2] Anderson and Srinivasan, 2003). Therefore even if a customer

has previously been satisfied by a particular website, they still are likely to switch to competing businesses

which offer higher customer perceived value. Based on the above relationship we propose the following

hypothesis:

H7. The impact of customer satisfaction on customer loyalty is moderated by customer perceived value, and

the impact is stronger for the higher level of customer perceived value group than for the lower group.

Research design

Conceptual model

This research proposes an integrative model to explain users' online shopping behaviour based on established

relationships among e-service quality (website design, reliability, security and customer service), customer

satisfaction, customer loyalty, and customer perceived value (presented in Figure 1 [Figure omitted. See Article

Image.]). The model of this research is based on [4] Bagozzi's (1992) self-regulation processes in which

appraisal processes lead to emotional responses, which then lead to coping responses (behaviour). The

cognitive evaluations in this model are similar to the e-service quality and customer perceived values of

products. Customer satisfaction loyalty belongs to emotional reactions and coping responses separately.

Therefore we use [4] Bagozzi's (1992) self-regulation processes to develop and test specific research

hypotheses linking e-service quality, customer perceived value, customer satisfaction, and customer loyalty.

Measures

In order to measure the various constructs, validated items used by other researchers were adopted and the

various dimensions of e-service quality were discussed. For example [108] Wolfinbarger and Gilly (2003)

developed a scale called.comQ. [118] Zeithaml et al. (2002) and [86] Parasuraman et al. (2005) developed

two scales - E-S-QUAL and E-RecS-QUAL - that were used for measuring service quality delivered

by websites in which customers shop online. We consider that the two scales have many similar aspects and

therefore combine them as our measurable variables of e-service quality using four dimensions:

website design;

reliability;

security; and

customer service.

Customer perceived value was assessed with two items based on the perceived utility/worth resulting from the

trade-off of "get" versus "give-up" ([115] Zeithaml, 1988). This paper measures customer perceived value

using the scales from [32] Dodds et al. (1991) and [2] Anderson and Srinivasan (2003). Customer satisfaction

was assessed by adapting the scales developed by [78] Oliver (1980) and [2] Anderson and Srinivasan (2003).

Lastly, customer loyalty was evaluated by using scale items adapted from [117] Zeithaml et al. (1996), [2]

Anderson and Srinivasan (2003) and [111] Yang and Lester (2004). Each item used a seven-point Likert scale

ranging from 1="strongly disagree" to 7="strongly agree". A questionnaire initially including 29 items was

generated, consisting of 14 items for e-service quality, three items for customer satisfaction, eight items for

customer loyalty and four items for customer perceived value.

Questionnaire design and pilot test procedures

The structure of the online shopping model incorporates four constructs:

e-service quality;

customer perceived value;

customer satisfaction; and

customer loyalty.

The questionnaire was developed from the dimensions of the research constructs identified from the qualitative

survey and literature review. In order to measure reliability and validity, a pre-test was conducted. A pilot test

of the measures was conducted by 70 respondents who were asked to provide comments on the relevance and

wording of the questionnaire items and it was then adjusted based on their comments. The results of the pilot

were tested using Cronbach's reliability and exploratory factor analysis.

One e-service quality item and two customer loyalty items were deleted after the pilot test. In its final form our

questionnaire contained 26 questions: 13 on e-service quality, four on customer perceived value, three on

customer satisfaction and six on customer loyalty. The instrument also included some demographic variables

such as gender, age, education, employment, average surfing time per week, average spending, and the

methods of bill payment.

Samples and procedures

Online shoppers are often divided into two types. One is actual shoppers who have made purchases on

awebsite; another is browsers who have only visited such websites without making purchases ([66] Lee and

Johnson, 2002; [40] Forsythe and Shi, 2003). In this study our research participants are people who have

online purchase experience. Most sampling schemes fall into three general classes ([41] Fowler, 2002; [97]

Singleton and Straits, 2005):

sampling from a more or less complete list;

sampling from a set of people who go somewhere or do something that enables them to be sampled; and

sampling from multi-age procedures.

In this study, because we cannot obtain a complete list of consumers shopping online, we adopted the second

type of sampling. We wanted to observe online shopping behaviour; therefore we set a rule for selecting our

sample based on purchase times, such as actual purchase experience with a specific shopping website during a

year. Moreover we obtained a convenience sample in Taiwan via a web-based survey and recruited participants

through related online shopping discussion boards or internet communities. In order to motivate the public to

reply, respondents who completed the questionnaire were eligible for a prize draw and had a chance to win a

cash prize of between $US15-30.

The internet questionnaire was hosted by Chungwa Telecom. A web-based survey has many advantages. First

it can maximise the questionnaire's coverage. The internet is believed to be the most effective way to assure

respondents' variety and quantity, because online field surveys can elicit faster responses and are

geographically unrestricted ([50] Hsu and Lu, 2004; [102] Tan and Teo, 2000). Second we can also confirm

that our sample interviewees have experience in using the internet by using an online questionnaire.

This study collected 350 respondents, 20 of whose questionnaires were invalid due to being incomplete. We

eliminated the invalid questionnaires and retained 330 questionnaires for analysis. Therefore the percentage of

valid responses out of all responses was 94.3 per cent. The online questionnaire also confirmed that our

sample had experience in using the internet. In the aggregate sample 44.8 per cent of respondents were men

and 55.2 per cent were women.

There are three characteristics of a sample that a researcher should evaluate ([41] Fowler, 2002):

comprehensiveness;

probability of selection; and

efficiency.

Comprehensiveness

Although this study used a convenience sampling method which may create doubt as to the representativeness

of the target population, we intended to find a population framework from a secondary survey and tried to

make the distribution of the samples consistent with the target population. Previous work which compared the

online and offline shopping populations found that online shoppers appear to be younger, better educated and

spend more time on their computer and on the internet ([100] Swinyard and Smith, 2003). [75] A.C. Nielsen's

(2004) survey also indicated that the main online shopping users are university students or those who have

just graduated and started work. Moreover shopping websites are most likely to be used by people in their

twenties ([75] A.C. Nielsen, 2004). In this study 85 per cent of respondents were in that age group. Nearly half

(48 per cent) of the respondents used the internet for more than 20 hours each week. Most (71 per cent) of

the respondents had less than $US300 disposable income per month. Many (67 per cent) of the respondents

paid for internet purchases by credit card or ATM transfer accounts. The respondents exhibited some

interesting characteristics. The top three products purchased online in our study were computer equipment (38

per cent), books (33 per cent), and clothes (29 per cent). From the above evidence our sample results reflect

the population of online buyers in Taiwan.

Probability of selection

In this study we can understand the probability of selection of each selected individual by asking our

respondents about their purchase times at a specific shopping website. We found that over a six month period

43.7 per cent of respondents shopped there once or twice while 33.9 per cent shopped 3-5 times. According to

[75] A.C. Nielsen's (2004) survey in Taiwan 70 per cent of online shoppers did so between one and five times

every six months. Therefore the sample is consistent with the target population.

Efficiency

In this study we adopted convenience sampling and posted the recruiting information on related online

shopping discussion boards or internet communities, which was an efficient way to gain access to our sample.

Analysis and results

There are two studies performed in this research. Study 1 validated the attitude-intention link ([4] Bagozzi,

1992): appraisal process (e-service quality, customer perceived value)[arrow right]emotional reactions

(customer satisfaction)[arrow right]coping responses (customer loyalty). Study 2 tested the moderating effects

of customer perceived value between satisfaction and loyalty.

Study 1: Attitude-intention link (appraisal process, emotional reactions and coping responses)

This study focused on identifying the relationships among research constructs (e-service quality, customer

perceived value, customer satisfaction and customer loyalty) perceived by consumers. According to the two-

step approach ([1] Anderson and Gerbing, 1988) we first developed the measurement model to perform a

validity and reliability analysis on the measurement scale and then used a structural model to examine the

research hypotheses. Both the measurement model and the structural model were assessed using AMOS 5.0

by the maximum likelihood method ([3] Arbuckle, 2003).

Validity and reliability in the measurement model

The measurement model contains four constructs:

e-service quality;

customer perceived value;

customer satisfaction; and

customer loyalty.

The questionnaire was developed through a literature review and practitioner interviews. Therefore content

validity for the questionnaire should be acceptable. We then proceeded to evaluate the reliability, convergent

validity and discriminant validity of the research model with a confirmatory factor analysis using AMOS 5.0.

The reliability and convergent validity of the factors were estimated by composite reliability and average

variance extracted (see Table I [Figure omitted. See Article Image.]). The composite reliability for all factors in

our measurement model was above the recommended 0.70 level ([5] Bagozzi and Yi, 1988). The average

extracted variances were all above the recommended 0.50 level ([38] Fornell and Larcker, 1981), which meant

that more than half of the variances observed in the items were accounted for by their hypothesised factors.

Convergent validity can also be assessed by factor loading. Following the recommendations of [46] Hair et

al.(2006) factor loadings greater than 0.50 were considered to be very significant. All of the factor loadings of

the items in the measurement model ranged from 0.72 to 0.89, therefore they were significant (see Table I

[Figure omitted. See Article Image.]).

To examine discriminant validity we compared the shared variances between factors with the average variance

extracted from the individual factors ([38] Fornell and Larcker, 1981). Chi-square was used to examine the

statistical significance of the differences between the two models at p

has a significant impact on customer loyalty ( =0.84, t -value=4.81). Thus the results of the analysis

supported H1, H3 , and H4 . These results indicate that e-service quality does not directly affect online

shopping customer loyalty, but it does so indirectly through the mediation of perceived value and customer

satisfaction (see Table IV [Figure omitted. See Article Image.]). Finally customer perceived value has a

significant impact on customer satisfaction ( =0.332, t -value=4.812) and customer loyalty ( =0.341, t -

value=3.595). Therefore the results of the analysis supported H5 and H6 . These results conform to the

theories of experiential consumer behaviour.

The path coefficients and explained variance for this structural model are shown in Figure 2 [Figure omitted.

See Article Image.]. E-service quality influence accounted for 54.3 per cent of the variance in customer

perceived value. Together, the predictors such as e-service quality and customer perceived value explained 81

per cent of the variance in customer satisfaction. E-service quality, customer perceived value and customer

satisfaction influence collectively accounted for 78 per cent of the variance in customer loyalty.

Study 2: Moderating effects of customer perceived value

The objective of this section is to examine if customer perceived value might influence the relationship between

customer satisfaction and customer loyalty. The moderating effects of customer perceived value were tested

using a hierarchical linear regression analysis ([23] Cohen and Cohen, 1983). In the regression analysis we

view consumer loyalty - which included repurchase intentions and word of mouth - as a dependent variable,

and customer perceived value, satisfaction and interaction effects between them as independent variables. As

reported in Table V [Figure omitted. See Article Image.] satisfaction accounted for 55.9 per cent of the

variance in customer loyalty. When the variable of perceived value was added into the regression, the

independent variable increased to 62.9 per cent of the variance in word of mouth. Finally when we added the

interaction variables (satisfaction with perceived value) into the regression, the two independent variables

(satisfaction and perceived value) became insignificant and the interaction variable had significant effects in

the regression model. The results show a strong moderating effect of perceived value in the relationship

between satisfaction and loyalty.

Table V [Figure omitted. See Article Image.] shows the hierarchical regression results of the analyses for

customer satisfaction, customer perceived value and customer loyalty. Consistent with expectations the main

effects of customer satisfaction and customer perceived value positively and significantly affected consumer

loyalty ( 1 =0.474, t =8.761; 2 =0.413, t =7.862) (see Model 2 in Table V [Figure omitted. See Article

Image.]). When we put the interaction effect of perceived value in the model, the parameter estimate for the

main effect of perceived value on loyalty became insignificant (1 =0.088, t =0.986; 2 =-0.025, t =-0.272),

but the parameter estimate for the interaction term (satisfaction with perceived value) was significantly

positive (=0.088, t =23.581) for customer loyalty (see Model 3 in Table V [Figure omitted. See Article

Image.]). This indicated that perceived value indeed positively moderates the impact of satisfaction on

customer loyalty, and thus H7 was supported. Further we continued to examine the moderating effect in the

relationship between satisfaction and customer loyalty for low perceived value and high perceived value. In

order to understand the differences in the moderating effects of customer perceived value on the relationship

between satisfaction and loyalty, we used a cluster analysis to divide customer perceived value into high and

low groups. The first group is low perceived value ( n =163); the second group is high perceived value

(n =167). In the two groups we used satisfaction as the independent variable and loyalty as the dependent

variable to form two regression models (see Table VI [Figure omitted. See Article Image.]). Then we used the

Chow test to determine whether the coefficients in a regression model were the same in separate perceived

value groups. The results from the Chow test showed a significant difference between the two regressions

( F =41.55, p

Because customer satisfaction is such an important factor influencing customer loyalty, understanding possible

antecedents affecting the formation of it can be useful for managers. The results showed that the development

of customer satisfaction with a shopping website ( R2 =81 per cent) is related to high e-service quality

(=0.65) as well as perceived value from that website ( =0.33). Moreover e-service quality played an

important role in developing the online shoppers' perceived value ( =0.74) (R2 =54.3 per cent). This implies

that websitemanagers need to pay more attention to improving e-quality. In an online environment it is much

easier to compare product technical features and prices than through traditional channels ([92] Santos, 2003),

because customers can easily switch to competing businesses ([67] Lee and Overby, 2004). Therefore, online

customers expect equal or higher levels of service quality than traditional channel customers ([65] Lee and Lin,

2005). When online shoppers perceive high e-service quality, they will exhibit high customer perceived value

and attain customer satisfaction and customer loyalty.

We conducted the second study in response to our second research issue concerning the influence of

moderating variables on customer perceived value. The results showed that customer perceived value has a

moderating effect on the relationship between customer satisfaction and customer loyalty. We found that

customers with high perceived value have a stronger relationship between satisfaction and customer loyalty

than customers with low perceived value. This means that even satisfied customers are likely to switch to an e-

business that offers better value, so perceived value contributes to the loyalty of an e-business by reducing an

individual's need to seek alternative service providers ([2] Anderson and Srinivasan, 2003). The findings of this

study provide the following theoretical implications as well as managerial implications.

Research implications

There are several important theoretical implications of this study. First because of the fundamentally

differentcharacteristics of online and offline shopping, such as the context of traditional service quality and e-

service quality, and transaction costs of customers, customer loyalty is very different online compared to

traditional physical shops. Previous studies found obvious factors influencing consumer loyalty, such as service

quality and consumer satisfaction, but neglected to understand the influencing processes. This study has

demonstrated that the process of attaining customer loyalty in online shopping is consistent with the self-

regulation process: appraisal processes, emotional reactions and coping responses ([4] Bagozzi, 1992). From

the self-regulation process ([4] Bagozzi, 1992) this study found that there are two distinct routes influencing

customer loyalty in the online shopping process: one is an emotional way based on better moods and feelings;

another is a rational way based on comparative analysis of benefits and costs. These two routes have been

found to have different impact on consumer loyalty at different purchase stages.

Second the most famous customer satisfaction model is the customer satisfaction index (CSI) ([39] Fornell et

al., 1996). The fundamental difference between the CSI and this research model lies in the role of the

perceived customer value variable. This research assumes that the perceived customer value variable has a

direct effect on both satisfaction and loyalty. It also has a moderating effect between satisfaction and loyalty.

When consumers are shopping online their search costs and switching costs become lower than when shopping

at physical shops. Therefore consumers can easily compare different shopping websites and weaken the

traditional link between satisfaction and loyalty. The traditional CSI model was developed for physical shops,

thus it cannot explain this e-commerce phenomenon well.

Third the purchase process consists of several distinct stages: pre-purchase, purchase and post-purchase.

Previous researchers have viewed the purchase process as a monolithic decision and assume consumers will

use the same channel for all purchase stages ([25] Choudhury and Karahanna, 2008). This study found that

online retailers should use appropriate marketing strategies for each of the different consumer purchase

stages. For example e-service quality occurs before a consumer's purchase, thus there are tangible cues that

can be used to heighten a consumer's perceptions of it. When consumers engage in purchasing they will

conduct emotional and rational assessments about the product. This study found that the emotional variable is

more important that the rational variable in the purchase stage. Then after purchasing, online retailers can

strengthen consumer loyalty by promoting rational assessments.

Managerial implications

The results of this study provide several implications for managers promoting intention to purchase at

shoppingwebsites. This study found two alternative ways to enhance consumer loyalty. These are the

emotional and rational influencing routes, both of which should be applied at different purchase stages. There

are three stages in a shopping process - i.e. pre-purchase, purchase, and post-purchase ([42] Frambach et

al. , 2007; [25] Choudhury and Karahanna, 2008) - and the results of this study can provide specific

recommendations for online retailers during these three stages.

In the pre-purchase stage in which consumers acquire information about products from the website, online

retailers should focus on attracting consumers who visit their websites by controlling the tangible variables

rather than intangible variables, such as e-service quality. Furthermore, this study found that different

dimensions of e-service quality have different impacts on consumers' emotional and rational assessments

about products. Among the four dimensions of e-service quality (website design, reliability, security and

consumer service), this study found that website design is an important dimension, because it affects both

customer satisfaction and consumer perceived value. Therefore online retailers should pay attention

towebsite design by adding abundant information, personalisation and a friendly interface. In addition

towebsite design customer perceptions of transaction security are important, thus online retailers should

address the common perceptions of risks involved in transmitting sensitive information, such as credit card

numbers ([16] Chang and Chen, 2009). There are other dimensions of e-service quality that need to be

emphasised to increase perceived value and customer satisfaction respectively. For enhancing consumer

satisfaction the other dimension is consumer service, which gives the consumer a feeling of respect and

protection. Therefore online retailers have to establish a good channel of communication with their consumers.

For improving consumer perceived value the other important dimension is reliability, which is related to

consumers' benefits or losses. Therefore online retailers should pay attention to the delivery of dependable

services for consumers.

In the purchase stage, in which consumers are proceeding with their transaction, this study found that there

are two paths influencing customer loyalty, of which the emotional influencing route is more effective than the

rational influencing route. This means that although consumers can easily get information about products and

compare them to those on other websites, allowing them to make a rational decision, they prefer to patronise

a site based on emotional factors. For example, if consumers are shopping on a website with which they have

had a highly satisfying experience, they will trust that site and not compare it with others before making

purchase decisions. Therefore, in the process of shopping online, the most important thing consumers are

concerned about is whether the website offers good e-service quality which will give them emotional

satisfaction.

In the post-purchase stage in which consumers complete their purchase and evaluate the next purchase, this

study found that rational factors play an important role. In this rational approach online retailers can

strengthen the causal relationship between satisfaction and loyalty by raising their customer perceived value.

Therefore after shopping online, consumers become rational and start to analyse the ov