An empirical study of online shopping customer sat

Xia Liu

Department of Marketing,Shanghai Jiaotong University,Shanghai,

People’s Republic of China and

Research Center of Hospital Management,Shanghai Sixth People’s Hospital,

Shanghai,People’s Republic of China,and Mengqiao He,Fang Gao and Peihong Xie

Department of Marketing,Shanghai Jiaotong University,Shanghai,

People’s Republic of China

Abstract

Purpose –The purpose of this study is to identify factors that may influence Chinese customers’online shopping satisfaction,including those which are ignored by prior studies,from the perspective of total online shopping experience.

Design/methodology/approach –In this paper,the authors propose a model of the satisfaction process in the e-commerce environment,identifying key constructs proposed by prior studies and developing hypotheses about which dimensions of online retailer constructs are significant predictors of online shopper satisfaction.The authors test the hypotheses through multiple regression analysis based on a survey of 1,001online customers.

Findings –The analysis suggests that eight constructs –information quality,web site design,merchandise attributes,transaction capability,security/privacy,payment,delivery,and customer service –are strongly predictive of online shopping customer satisfaction,while the effect of response time is not significant.

Research limitations/implications –This study does not control the differences across product categories;the use of self-reported scales to measure both independent and dependent variables may imply the possibility of a common method bias for the results.

Originality/value –This research contributes to the study of online shopping customer satisfaction by:developing a model of the satisfaction process in the e-commerce environment,and identifying factors that may influence Chinese customers’online shopping satisfaction including those which are ignored by prior studies.

Keywords Electronic commerce,Customer satisfaction,China

Paper type Research paper

1.Introduction

After years of development of China’s online shopping market,there has been a drastic increase in the number of online shopping web sites in China.Statistics released by the PRC Ministry of Information Technology indicate that the number of retail web sites in 2001totaled 2,046and reached 2,219by 2004.Retail web sites accounted for

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0959-0552.htm

The authors would like to thank Acme Translations Co.,Ltd for their support of the research.Online shopping customer satisfaction 919Received 31August 2007Revised 3January 2008Accepted 28February 2008

International Journal of Retail &Distribution Management Vol.36No.11,2008pp.919-940q Emerald Group Publishing Limited 0959-0552

DOI 10.1108/09590550810911683

49.5per cent of China’s Ecommerce in 2004with transaction volume of online shopping estimated at 4.2billion RMB.By 2005,the transaction turnover of online shopping amounted to 5.6billion RMB,a 33per cent increase.With China’s online shopping environment maturing and offering improved levels of service,it is predicted that the volume could reach 46billion RMB by 2010[1].The rapid growth of online shopping in China underscores the importance of

focusing on the issue of customer satisfaction as a key factor to address when designing any online retail outlet.Customers must be satisfied with their online shopping experience;otherwise they will not return (Kim and Stoel,2004).A recent survey conducted by CNNIC found that only 3.5per cent of the Chinese respondents were very satisfied with the online shopping experience.Dissatisfaction usually leads to lost customers and income.Compared with American customers,Chinese customers have several characteristics:their perception of safety is lower;they undertake higher purchasing risks because of fake goods and false advertising;the buyer sometimes is not the consumer;they are more sensitive to price;they are more cautious in making purchase decision (Lu,2005).Therefore,a fundamental understanding of the factors affecting Chinese online shopping customers’degree of satisfaction is of great importance to e-commerce.

If companies can better understand their customers,they can present products or services more effectively and continuously improve them in order to strengthen their competitive advantage.Market orientation and customer satisfaction research show there is direct connection between customer satisfaction and organizational performance (Garver and Gagnon,2002).Consequently,in the turbulent e-commerce environment,Internet companies need to know how to satisfy customers.This will enable them to sustain their growth and market share (McKinney et al.,2002).

It is known that online shopping environment and behavior is fundamentally different from that of a conventional retail environment (Degeratu et al.,2000;Lynch and Ariely,2000;Shankar et al.,2001,2003;Ranganathan and Ganapathy,2002;Heiner et al.,2004).It can be expected that the key drivers of customer satisfaction and retention in the Internet economy may be also different from those in the traditional economy.From different perspectives,researchers have developed and tested instruments to measure customer satisfaction with online shopping (Szymanski and Hise,2000;Koivumaki,2001;Heiner et al.,2004;Kim and Stoel,2004).These researchers have done some innovative and pioneering work,but revealed conflicting findings,such as Szymanski and Hise (2000)find that web site design has the secondary significant impact on e-satisfaction,the study conducted by Kim and Lim (2001)shows that information quality has relationship with online shoppers’satisfaction,but Kim and Stoel’s (2004)study indicate that web appearance and information attribute have little impact on customer satisfaction.

In addition,China differs from foreign countries greatly in cultural tradition,logistic infrastructure and credit system.Chinese culture belongs to eastern culture system,and the infrastructure of logistics in China lags behind other developed countries.Moreover,there has not sound credit system in China.Prior researches indicate that culture (David,2007),logistics (Sharma et al.,1995)and credit (Gentry,1982)have important impact on customer behavior and satisfaction.Therefore,it is understandable that key drivers of online shopping customer satisfaction in China may be different from that of other countries.Just as de Mooij and Hofstede (2002)indicated,

IJRDM 36,11920

Based on earlier research(Szymanski and Hise,2000;Koivumaki,2001;Heiner et al., 2004;Kim and Stoel,2004),the purpose of this research is to identify key constructs and corresponding measurement scales for examining Chinese online shopping customer satisfaction.This is done by developing a satisfaction process model in e-commerce environment,identifying key constructs proposed by prior studies and designing a group of hypotheses.

Our research contributes to the study of online shopping customer satisfaction by: .Developing a model of the satisfaction process in the e-commerce environment.

.Identifying factors that may influence Chinese customers’online shopping satisfaction,including payment which are ignored by prior studies.

The outcome of the study may be relevant to businesses,consumers and researchers.

The paper proceeds as follows.Section2is literature review.Section3proposes a satisfaction process model in the e-commerce environment and designs a group of hypotheses.Section4describes the survey used to test the above model.Section5 presents the results of statistical data analysis.Section6discusses the study’s implications for research and practice and outlines the study’s limitations.

2.Literature review

While the subject of satisfaction has been discussed extensively in the traditional retailing literature(Mason and Bearden,1979;Oliver,1981;Anderson et al.,1994; Terblanche and Boshoff,2001a,b;Johan,2006;Ofir and Simonson,2007),the exploration of dimensions and determinations of satisfaction under e-commerce context is at a nascent stage(Heiner et al.,2004).Recently,some researchers have started to investigate how the attributes of a web site will influence customers’satisfaction.These studies have presented various characteristics as important factors for an effective B2C e-commerce web site;however,up to now there is no consensus on how this affects online customer satisfaction(Schaupp and Be´langer,2005).

Table I summarizes several previous studies of the determinants of online shopping customer satisfaction.

There have been several other attempts to build an evaluation framework or identify dominant factors concerning customer satisfaction with online shopping from the perspective of web site quality(Ranganathan and Ganapathy,2002),purchasing behavior(Koivumaki,2001;Park and Kim,2003),consumer attitude(Elliott and Speck, 2005),customer value Shun and Yunjie,2006and service quality(Zhilin et al.,2003).

The foregoing studies provide a broad basis for gaining insight into customer satisfaction with online shopping.Few empirical studies have been conducted to uncover the underlying constructs of customer satisfaction with online shopping,from the perspective of the total retail experience and following the purchase process. What’s more,the impact of payment was seldom touched on.A consumer buying process can be viewed as a sequence of several stages(Kotler,1997;Oliver,1981;Online shopping

customer

satisfaction

921

Ranganathan and Ganapathy,2002),thus,satisfaction is a consequence of the customer’s experiences during various purchasing stages (Kotler,1997).Berman and Evans (1998)define total retail experience as all the elements that encourage or inhibit consumers during their contact with the retailer.In this perspective,dimensions tested by prior studies,such as information quality,web site design are only one component of the online shopping customers’total retailing experience.From a management perspective,it seems preferable to develop an instrument that covers all the dimensions of an online shopping experience that can be controlled by an online retailer.If only one component of the total retailing experience is considered at a time,it might be detrimental to our understanding of customers’experience and this in turn could lead to strategies that either overemphasize or under appreciate the importance of one or more of such components (Terblanche and Boshoff,2001a,b).

Although some other studies touch on consumers’shopping experience and their evaluation are based on perceptions of the online shopping web sites (Jarvenpaa and Todd,1997;Griffith et al.,2001;Koivumaki,2001;Park and Kim,2003),these research mainly discuss the consumer’s information processing style,shopping pattern,etc.Chen and Chang (2003)innovatively proposed an overall model of Internet shopping process and identified three common online shopping components:interactivity,transaction and fulfillment,but their study lack theoretical background.

Independent variable

Key references Dependent variable Convenience Szymanski and Hise (2000)E-satisfaction

Kim and Lim (2001)Consumers’satisfaction with internet shopping

Heiner et al.(2004)E-satisfaction

Web site design Szymanski and Hise (2000)E-satisfaction

Heiner et al.(2004)E-satisfaction

Kim and Stoel (2004)Shopper satisfaction of apparel web site

Hsuehen (2006)Customer satisfaction

Financial security Szymanski and Hise (2000)E-satisfaction

Heiner et al.(2004)E-satisfaction

Trust Kim and Stoel (2004)Shopper satisfaction of apparel web site

Assurance Devaraj et al.(2002)Consumer attitudes and satisfaction

Reliability Kim and Lim (2001)Consumers’satisfaction with internet shopping

Information Szymanski and Hise (2000)E-satisfaction

Kim and Lim (2001)Consumers’satisfaction with internet shopping

Heiner et al.(2004)E-satisfaction

Kim and Stoel (2004)Shopper satisfaction of apparel web site

Ballantine (2005)Customer satisfaction

Hsuehen (2006)Customer satisfaction

Merchandise variety Szymanski and Hise (2000)E-satisfaction

Heiner et al.(2004)E-satisfaction

Perceived ease of use Devaraj et al.(2002)Consumer attitudes and satisfaction

Perceived usefulness Devaraj et al.(2002)Consumer attitudes and satisfaction

Entertainment Kim and Lim (2001)Consumers’satisfaction with internet shopping

Kim and Stoel (2004)Shopper satisfaction of apparel web site

Speed Kim and Lim (2001)Consumers’satisfaction with internet shopping

Response time Kim and Stoel (2004)Shopper satisfaction of apparel web site

Transaction capability Kim and Stoel (2004)

Shopper satisfaction of apparel web site Table I.Empirical research on determinants of online shopping customer satisfaction IJRDM 36,11922

There have been several other attempts to study user satisfaction in the context e-services or online services (Zhang et al.,2006;Ha,2006;Yang and Fang,2004).For instance,Zhang et al.(2006)examine several factors (user computer proficiency,perceived convenience,site characteristics,perceived security,user satisfaction)affecting user satisfaction with e-services and find that perceived convenience,users’skills and experiences,and perceived security have impact on user satisfaction with e-services.

In the proceeding section,we will reorganize the web site quality studied in the prior research from the perspective of total retail experience of online shoppers.In addition,delivery and payment are examined in our study as unique features in the context of Chinese online shopping.

3.Research model and hypotheses

Satisfaction is the consequence of the customer’s experiences during various purchasing process:need arousal,information search,alternatives evaluation,purchase decision,and post-purchase behavior (Kotler,1997).In the increasingly technology-oriented online shopping environment,it is quite safe to assume that online shopping consumer satisfaction can be affected at every stage.The model of Turban et al.(2000)suggests that,in addition to selection and different properties of the goods,various features are related to the web shop,such as speed of operation,ease of use,that determine the navigation experience of the customer.

Based on Kotler’s (1997)study,this study divides the purchasing process into three stages:information search and alternatives evaluation stage,purchase stage and post-purchase stage,and proposes a model of the satisfaction process in the e-commerce environment outlined in Figure 1.

As indicated by the above model,customers’overall satisfaction can be affected by all factors relevant to the process of online shopping.Based on the studies of

Figure 1.Model of the satisfaction process in e-commerce

environment

Stage 3: Post-purchase Stage 1: Information search

and alternatives evaluation

Stage 2: Purchase Online shopping customer satisfaction 923

Oliver (1980),Cadotte et al.(1987),and Spreng et al.(1996),we define overall satisfaction as an affective state representing an emotional reaction to the entire online shopping experience.This definition focuses on the process evaluation associated with online shopping behavior.In the following analysis,the concept of overall satisfaction is referred to simply as “satisfaction”,referring to a customer’s degree of satisfaction upon completion of an online shopping experience.

3.1Information search and alternatives evaluation stage

At the stage of information search and alternatives evaluation,information quality,the ambience associated with the site itself and how it functions,variety of merchandise and price all play roles in whether consumers are satisfied or dissatisfied with their online shopping experiences.It is argued that,since a primary role of an online store is to provide price-related information and product information to help reduce consumers’search cost (Bakos,1997),more extensive and higher quality information available online leads to higher levels of customer satisfaction (Peterson et al.,1997).Manes (1997)indicates that good web site design lies in good organization and easy search.Shopping is thought to be pleasurable and satisfying to consumers when the retailing sites are uncluttered and easy-to-navigate (Pastrick,1997).In the alternatives evaluation stage,merchandise attribute including merchandise variety and price is important for decision making.Szymanski and Hise (2000)indicate that wider assortment of products may be attractive to customers and e-satisfaction would be more positive when online stores offer superior product assortments.Although some scholars think price sensitivity may actually be lower online than offline (e.g.,Degeratu et al.,2000;Lynch and Ariely,2000;Shankar et al.,2001),one most commonly cited reason for online shopping is price,and many early online marketers used price as bait to lure consumers to their sites (Chen and Chang,2003).Moreover,the Chinese are quite sensitive to price (Lu,2005).Therefore,we hold the view that product price has a lot to do with Chinese customers’satisfaction.

Based on the discussion above,we propose the following hypotheses:

H1.Higher level of information quality will improve customer satisfaction in

online shopping.

H2.Good web site design will have a positive effect on online shopping customer

satisfaction.

H3.Wider merchandise variety and low price will have a positive effect on online

shopping customer satisfaction.

3.2Purchase stage

At the purchase stage,privacy/security,payment mechanisms,transaction capabilities and speed of operation may affect satisfaction.Compared with the traditional economy,online consumers are more keenly aware of the need for privacy/security (Culnan,1999;Friedman et al.,2000;Grewal et al.,2004).Inadequate infrastructure,lack of trust,and privacy and security concerns often lead to lost sales (Yianakos,2002;Grabner-Kraeuter,2002).Moreover,online shoppers are known for low tolerance (Chen and Chang,2003),it is estimated that,on average,online shoppers only wait for eight seconds for system feedback before bailing out (Dellaert and Kahn,1999).A web page designer has to consider not only appearance and functionality,but also loading time IJRDM 36,11924

(Weinberg,2000).A commonly cited reason for online shopping is convenience(Chen and Chang,2003).Therefore,it will raise the customer’s degree of satisfaction to improve the web site’s transaction capability,design a secure and convenient payment mechanism,ensure completion of all online shopping operations and save the customer’s operation time.

Hence,the study designs the following hypotheses:

H4.Great transaction capability will have a positive effect on online shopping customer satisfaction.

H5.Rapid response time will have a positive effect on online shopping customer satisfaction.

H6.Security/privacy will have a positive effect on online shopping customer satisfaction.

H7.A convenient payment mechanism will have a positive effect on online shopping customer satisfaction.

3.3Post-purchase stage

Post-purchase evaluation can be influenced by the efficiency of logistics and customer service.The most common types of complaints about Internet transactions include refund and billing disputes,return and exchange policies,defective products,and poor customer service(Chen and Chang,2003).Consumers want careful,continuous,useful communication across geographic barriers(Lohse and Spiller,1998).In the e-commerce environment,not only is the consumption of goods separated from production,thus making it necessary for goods to be delivered to consumers before consumption,there is also a delay in the delivery of goods.Delayed delivery may have a negative effect on satisfaction.As shown by the2004China Online Shopping Report by CNNIC25per cent of Chinese customers were not satisfied due to delayed delivery or wrong product delivery(CNNIC,2004).One customer complained that he bought a digital camera from an online company but received sports equipment instead.

Thus,we have the following hypotheses:

H8.Safe and rapid delivery will have a positive effect on online shopping customer satisfaction.

H9.A higher level of customer service will result in greater satisfaction.

4.Research methodology

4.1Survey instrument

All constructs were measured using multiple items,seven-point,Likert scales ranging from strongly disagree to strongly agree.Wherever possible,initial scale items were taken from previously validated measures in e-satisfaction,online shopping customer satisfaction and web site quality literature and then reorganized and adapted to the current context.

Information quality was evaluated from four dimensions:information accuracy, information comprehensibility,information completeness and information relevancy. The items were adapted from the items initially developed by Jeong et al.(2003)and Muyllea et al.(2004).Web site design was evaluated from four aspects:navigation,Online shopping

customer

satisfaction

925

web site structure,color combination and ease of use.The items were taken from Muyllea et al.(2004),Jeong et al.(2003)and Kim and Stoel (2004).Merchandise attribute was evaluated from two dimensions:product variety and product price.This thesis consulted the study of Szymanski and Hise (2000)which evaluates product variety from two perspectives:number of offerings and variety of offerings.Based on this we designed four items.We designed another two items to evaluate product price through in-depth discussion with 30online shoppers and site administrators,who all agree that these two items can reflect price level.The transaction capability and response time scale were adapted from Kim and Stoel (2004).Based on the in-depth interview with online shoppers and managers of B2C web sites such as www.joyo.com,www.dangdang.com,we develop two items to evaluate payment:the web site has complete payment options;I accept the payment options provided by the web site.Security/privacy and customer service scale were taken from Wolfinbargerhe and Gilly (2003).Delivery scale consists of four items,among which two are taken from Wolfinbargerhe and Gilly (2003).The other two are developed on the basis of in-depth interviews:the items sent by the site are well packaged and perfectly sound I am satisfactory with the delivery mode of the web site.Satisfaction scale consists of four items taken from Oliver (1981),referring to a customer’s degree of satisfaction upon completion of an online shopping experience.The survey instrument consists of two sections.In the first section,respondents were asked to fill in their gender,age,educational level and latest purchased product.In the second section,they were asked to identify the extent to which they agree/disagree with the items related to their latest online shopping experience.Each item was measured on a seven-point Likert scale from 1(strongly disagree)to 7(strongly agree).

4.2Sample and data

Prior to the survey,the survey instrument was pilot tested using five doctoral students and 20others who had online shopping experience.Pre-test interviews were undertaken to refine the questionnaire.The items were revised based on the feedback.Since we want to gather data of customers’perception of the online shopping experience,we asked only those subjects with some prior web shopping experience.Data was collected as follows:.

Field survey .Field surveys were conducted mainly in big cities such as Beijing,Shanghai,Nanjing,Hefei,Changsha and Jinan.We interviewed shoppers at some large shopping malls in these cities,and inquired if they had online shopping experience.The incentive was a lottery ticket.742respondents answered the questionnaire with 709usable respondents..

E-mail survey .The e-mail was sent to a sample of 542valid e-mail addresses,drawn from a large e-mail list provided by a company.The number of each e-mail address was randomly produced by computer.Internet users (115)agreed to participate in the study.The e-mail containing questionnaire was then sent to these 115Internet users.A total of 98respondents provided usable answers to the questionnaire.This was a return of 18.08per cent on the original mailing and of 85.2per cent among the people that agreed to cooperate.

IJRDM 36,11

926

com/diaocha.php),which is linked to a company’s BBS web site which has a daily visit volume of3,000persons.Respondents online answered the questionnaire,and the data was saved in the database of the company.This campaign produced211usable responses.Online surveys have several advantages over traditional surveys:not restricted to a particular geographical location(Shankar et al.,2003),lower costs(Shankar et al.,2003),faster responses (Shankar et al.,2003),more effective in identifying and seeking online shoppers (Szymanski and Hise,2000),and more interesting(Edmonson,1997).

This survey altogether collected1,018responses,deleted17outliers and kept1,001 valid responses.Before combining the three sub-samples,we performed one-way ANOVA analysis and the result indicates that there have not significant differences in the three sub-samples.

The demographic characteristics of respondents were as follows:respondents’age averaged32years and ranged from19to56;.3per cent of respondents have a college degree and15.7per cent have master’s degree or above;47.9per cent were female and 52.1per cent were male.

4.3Validity and reliability

In this study,construct,convergent and discriminant validity are assessed by exploratory factor analysis with SPSS13.0and confirmatory factor analysis with LISREL8.7.

The main sample is divided into two sub-samples,one(501respondents)for exploratory factor analysis and second(500respondents)for confirmatory factor analysis.By exploratory factor analysis(principal component analysis and varimax rotation is used),we have nine factors for the importance with the eight values greater than one as shown in Table II.The total variance explained by the nine factors is 67.434per cent.Five items with large standardized residuals were removed,resulting in the retention of44items,with two to ten items per construct(Table II and Appendix1).

A second study was carried out in order to further asses the factor structure as well as to establish convergent and discriminant validity through confirmatory factor analyses.Confirmatory factor analysis provides satisfactory support for the nine-dimension model(x2¼1739.97;df¼704;p,0.001;RMR¼0.1; GFI¼0.85;AFGI¼0.83;CFI¼0.97;RMSEA¼0.054).Following the procedures suggested by Fornell and Larcker(1981)and Bagozzi and Yi(1988), convergent validity was assessed by verifying the significance of the t values associated with the parameter estimates(Table II).All t values were positive and significant(p,0.01).Discriminant validity was tested by comparing the square root of average variance extracted(Ave)by each construct to the correlations between the construct and all other variables.For each construct,the square root of Ave exceeded all the correlations(Tables III and IV).In order to verify the reliability of the instrument,a statistical reliability analysis was conducted using Cronbach’s a s. Cronbach’s a s value for each of the factors ranged from0.705to0.908(Table II)and clearly exceed the0.70cutoff recommended by Nunnally(1978)for basic research.Online shopping

customer

satisfaction

927

Factor and items

Exploratory factor

loading (n ¼501)

Confirmatory factor loading (t -value)(n ¼500)

Cronbach’s a

Factor 1:web site design (j 1)0.878

Color combination 10.7160.72(18.87)Color combination 20.7160.66(15.88)Ease of use 10.6960.69(17.02)Ease of use 20.6690.67(16.32)Ease of use 3

0.5910.67(16.19)Web site structure 30.5830.55(12.79)Navigation 10.6230.55(12.66)Navigation 20.7260.62(14.60)Navigation 30.7340.65(15.52)Navigation 4

0.6800.59(13.70)

Factor 2:information quality (j 2)0.797

Understandablity 10.6930.68(15.92)Understandability 20.7390.71(17.01)Accuracy 10.6350.58(18.15)Accuracy 20.5670.62(14.32)Completeness 10.5780.59(13.48)Completeness 20.6300.44(9.66)Relevancy 1

0.5910.55(12.32)

Factor 3:merchandise attributes (j 3)0.908

Merchandise variety 10.8840.82(21.83)Merchandise variety 20.8610.80(21.04)Merchandise variety 30.8480.83(22.08)Merchandise variety 40.8160.74(18.59)Price level 10.7870.71(17.65)Price level 2

0.7800.71

(17.74)

Factor 4:transaction capability (j 4)0.716

Transaction capability 10.7240.74(15.78)Transaction capability 20.7430.71(15.17)

Factor 5:response time (j 5)0.705

Response time 10.8560.76(15.50)Response time 2

0.8410.72(14.)

Factor 6:security/privacy (j 6)0.829

Security/privacy 10.6580.65(15.10)Security/privacy 20.7680.79(19.84)Security/privacy 30.7520.81(20.60)Security/privacy 40.7490.70

(16.80)

Factor 7:payment (j 7)0.6

Payment 10.8470.90(21.47)Payment 2

0.8380.87(20.)

Factor 8:delivery (j 8)0.5

Delivery 10.7700.83(22.74)Delivery 20.7910.80(20.78)Delivery 30.8290.86(23.39)Delivery 4

0.7680.82

(21.80)

Factor 9:customer service (j 9)0.886

Customer service 10.8150.90(25.04)Customer service 2

0.822

0.83(21.96)

(continued )

Table II.

Construct measurement summary:exploratory and confirmatory factor analysis

IJRDM 36,11

928

4.3Regression results

Then,multiple regression analysis (SPSS13.0)was used to estimate the effect of nine constructs on online shopping consumer satisfaction level.The regression results are presented in Table V.

The data in Table IV shows that the regression coefficient for delivery,customer service,security/privacy,transaction capability,merchandise attributes,information quality,payment and web site design are all statistically significant.Response time has no effect on customer satisfaction.Additionally,we find that delivery has the greatest impact on satisfaction (b ¼0.214).The data also indicates that transaction capability is the second most important element driving satisfaction levels (b ¼0.191).Meanwhile,security/privacy,customer service,information quality,merchandise attributes and payment are statistically significant,but have less impact on satisfaction compared with delivery and transaction capability.Finally,the data indicates that web site design (b ¼0.055)is of less practical significance to satisfaction assessment.

Factor and items

Exploratory factor

loading (n ¼501)

Confirmatory factor loading (t -value)(n ¼500)

Cronbach’s a

Customer service 3

0.7550.82(21.49)

Dependent variable:satisfaction 0.826

Satisfaction 10.7880.67Satisfaction 20.8310.76Satisfaction 30.8360.79Satisfaction 4

0.811

0.73

Table II.

Factor 1234567Ave 0.410.360.590.530.550.550.780.690.72Sqrt

0.

0.60

0.77

0.73

0.74

0.74

0.88

0.83

0.85

Table III.

The average variance

extracted by each

construct

Dimensions j 1j 2j 3j 4j 5j 6j 7j 8j 8

j 1 1.00j 20.467** 1.00j 30.250**0.213** 1.00j 40.428**0.452**0.183** 1.00j 50.313**0.280**0.078*0.206** 1.00j 60.421**0.462**0.201**0.359**0.279** 1.00j 70.415**0.312**0.232**0.345**0.138**0.322** 1.00j 80.421**0.401**20.0540.410**0.230**0.356**0.395** 1.00j 9

0.451**

0.407**

0.173**

0.376**

0.337**

0.488**

0.267**

0.455**

1.00

Notes:*Correlation is significant at the 0.05level (two-tailed);**correlation is significant at the 0.01level (two-tailed)

Table IV.

Pearson correlations

matrix

Online shopping

customer satisfaction

929

Thus,our hypotheses that delivery,customer service,security/privacy,transaction capability,merchandise attribute,information quality,payment and web site design are positively correlated with online shopping customer satisfaction were supported.The hypothesis that rapid response time will have a positive effect on online shopping customer satisfaction was rejected.

An examination of excessive multicollinearity and autocorrelation was performed.First,the value of Durbin-Watson was 1.914.Second,the variance inflation factors (VIF)were scrutinized and all were found to be within the range of 1.206-1.665.Myers (1990)indicates that only if the rpramila VIF is above ten is there cause for concern about multicollinearity.Therefore,multicollinearity and autocorrelation were well within acceptable limits and not unduly influencing the regression estimates.5.Discussion and implications

This study offers several important findings in the Chinese context,summarized as follows:.

Delivery has a positive impact on customer satisfaction,which is consistent with the study of Sharma et al.(1995)..

Transaction capability has a significant effect on customer satisfaction.This finding is consistent with the study of Kim and Stoel (2004)..

The effect of security/privacy on satisfaction is in a positive direction.This finding is consistent with the studies of Szymanski and Hise (2000)and Schaupp

and Be

´langer (2005),but contradictory to Kim and Stoel’s (2004)finding..

As hypothesized,customer service is found to exert a significant positive influence on customer satisfaction.This finding is consistent with the study of Wolfinbargerhe and Gilly (2003)..

Information quality has significant impact on customer satisfaction as well,which is consistent with the research conclusion by Kim and Stoel (2004),Kim and Lim (2001)and McKinney et al.(2002).

Constructs

Proposed effect

Standard coefficient

(SE)t -value

VIF Hypothesis result Delivery

þ0.214(0.021)8.667** 1.665H8was supported Transaction capability þ0.191(0.021)8.237** 1.468H4was supported Security/privacy þ0.187(0.025)7.869** 1.539H6was supported Customer service þ0.186(0.023)7.688** 1.601H9was supported Information quality þ0.153(0.029) 6.365** 1.592H1was supported Merchandise attribute þ0.119(0.019) 5.654** 1.206H3was supported Payment

þ0.105(0.019) 4.687** 1.385H7was supported Web site design þ0.055

(0.030)

2.230*

1.652

H2was supported Response time H5

was

rejected

F model

218.514*R 2(R 2adjusted)0.639(0.636)Durbin-Watson

1.914

Notes:*Statistically significant at the 0.01level;**statistically significant at the 0.001level

Table V.

Regression results

IJRDM 36,11

930

.The role of merchandise attributes in customer satisfaction is evident,unlike the finding reported by Szymanski and Hise(2000).

.The data also reveals that payment has an impact on online shopping customer satisfaction.Previous research on customer satisfaction seldom touches on it.

This study uncovers its effect on customer satisfaction.

.The effect of web site design on satisfaction is in a positive direction.This finding is consistent with the study of Szymanski and Hise(2000),but somewhat contradictory to Kim and Stoel’s(2004)finding.

.Nevertheless,the effect of response time on customer satisfaction is not significant.Thisfinding differs from previous studies(Kim and Lim,2001;Kim and Stoel,2004).

Ourfindings have both managerial and research implications:

.Delivery and customer service play a critical role in Chinese customer satisfaction.To satisfy customers in today’s competitive e-marketplace,online retailers must keep a close eye on delivery and customer service.Prompt delivery and prompt response to customers’concerns and inquiries are crucial because order fulfillment still remains a weak spot for Chinese online retailers.In the online shopping environment,delayed delivery and ignorance of customers’concerns and inquiries will cause customer dissatisfaction.Especially,in the Chinese context,which can be worse because in China the logistic infrastructure lags behind other countries and the sense of customer service is relatively weak.

Because customers lack direct,face-to-face interaction with service providers, many issues still demand human intervention.Therefore,company representatives must be able to answer customer inquiries and solve problems as soon as they occur.

.Detailed and complete product information should be provided.In the online shopping environment,products are intangible.Customers cannot touch,taste, observe,smell or listen to the goods as they do in traditional ways.To know the quality and functionality of a commodity,customers can only rely on the pictures and descriptions of the goods on the web pages.Therefore,to enhance customers’degree of satisfaction,B2C web sites should provide clear and understandable information to online shoppers.Meanwhile,web sites should provide descriptive information of the goods that is as complete as possible,including the color, functionality,producer,model,etc.This is to ensure the customers can make purchase decisions.Koivumaki(2001)finds that displaying pictures of the goods’has greater influence on customer’s purchase decision than just listing out the product description.

.Providing varied types of commodities and preferential price is important.

Customer satisfaction still depends on product variety and product price.With this in mind,smart online retailers will offer abundant choices to customers,as well as provide competitive product prices.The Chinese are especially sensitive to price and are accustomed to comparing prices(Lu,2005).Many are not willing to spend extra money in shopping.Moreover,on the Internet,customers have access to more information.Their ability to compare and analyze forces web sites to revalue the products and allows customers to gain material benefits.Online shopping

customer

satisfaction

931

.

Expending more effort on web page design and making online shopping enjoyable is also important.The visitor’s first impression on the web site is derived from the page design,the layout and color match.Then,it is the content.Comfortable and pleasing pages can attract customers and prolong their stay,which increases the possibility of purchase and helps to improve the customer’s degree of satisfaction..

It is also vital to strengthen the web site’s transaction capability and make sure all operations can be completed online.This saves the customer’s time and fully reflects the convenience of online shopping..Because China lacks network ID authentication and online transaction credit system,credit,security and privacy become the spotlight of online shopping.It is important for online retailers to create a safe online shopping environment,provide convenient and safe payment methods,protect customers’privacy and guarantee financial security.

Some limitations of this research are noteworthy:

.Some researchers suggest that web site attributes considered important by shoppers may differ by product (Peterson et al.,1997;McGoldrick et al.,1999;Elliot and Fowell,2000).This study does not control such differences across product categories.

.This study dose not control for tangible versus intangible products/services in the analysis.

.The use of self-reported scales to measure both independent and dependent variables may imply the possibility of a common method bias for the results.Future research can develop more detailed models that can capture and explain the differences across product categories or focus on one category,such as books,CDs or airline tickets.Furthermore,the relationship between customer satisfaction,e-loyalty and continuous shopping intention in the Chinese online shopping environment should be scrutinized.

Note

1.http://market.ccidnet.com/pub/report/show_8380.html

References

Anderson,E.W.,Fornell,C.and Lehmann,D.R.(1994),“Customer satisfaction,market share,and

profitability:findings from Sweden”,Journal of Marketing ,Vol.58No.3,pp.53-66.Bagozzi,R.P.and Yi,Y.(1988),“On the evaluation of structural equation models”,Academy of

Marketing Science ,Vol.16No.1,pp.74-94.

Bakos,J.Y.(1997),“Reducing buyer search costs:implications for electronic marketplaces”,

Management Science ,Vol.43No.12,pp.1676-92.

Ballantine,P.W.(2005),“Effects of interactivity and product information on consumer

satisfaction in an online retail setting”,International Journal of Retail &Distribution Management ,Vol.33No.6,pp.461-71.

Berman,B.and Evans,J.R.(1998),Retail Management ,7th ed.,Prentice-Hall,Upper Saddle River,

NJ,p.P19.

IJRDM 36,11932

Cadotte,E.R.,Robert,B.W.and Roger,L.J.(1987),“Expectations and norms in models of consumer satisfaction”,Journal of Marketing Research,Vol.24No.3,pp.305-14. Chen,S.J.and Chang,T.Z.(2003),“A descriptive model of online shopping process:some empirical results”,International Journal of Service Industry Management,Vol.14No.5, pp.557-69.

Culnan,M.J.G.(1999),Internet Privacy Policy Study:Privacy Online in1999:A Report to the FTC, Georgetown University,Washington,DC.

David,M.(2007),“Culture,context,and behavior”,Journal of Personalit,Vol.75No.6, pp.1285-320.

de Mooij,M.and Hofstede,G.(2002),“Convergence and divergence in consumer behavior: implications for international retailing”,Journal of Retailing,Vol.78No.1,pp.61-9. Degeratu,A.,Rangaswamy,A.and Wu,J.(2000),“Consumer choice behavior in online and traditional supermarkets:the effects of brand name,price,and other search attributes”, International Journal of Research in Marketing,Vol.17No.1,pp.55-78.

Dellaert,B.and Kahn,B.(1999),“How tolerable is delay?consumers’evaluations of internet web sites after waiting”,Journal of Interactive Marketing,Vol.13No.1,pp.41-54. Devaraj,S.,Fan,M.and Kohli,R.(2002),“Antecedents of B2C channel satisfaction and preference:validating e-commerce metrics”,Information System Research,Vol.13No.3, pp.316-33.

Edmonson,B.(1997),“The wired bunch”,American Demographics,Vol.19No.6,pp.10-15. Elliot,S.and Fowell,S.(2000),“Expectations versus reality:a snapshot of consumer experiences with internet retailing”,International Journal of Information Management,Vol.20No.5, pp.323-36.

Elliott,M.T.and Speck,P.S.(2005),“Factors that affect attitude toward a retail web site”,Journal of Marketing Theory and Practice,Vol.13No.1,pp.40-51.

Fornell,C.and Larcker,D.F.(1981),“Evaluating structural equation models with unobservable variables and measurement error”,Journal of Marketing Research,Vol.18No.1,pp.39-50. Friedman,B.,Peter,H.K.Jr and Howe,D.C.(2000),“Trust online”,Communications of the ACM, Vol.43No.12,pp.34-40.

Garver,M.S.and Gagnon,G.B.(2002),“Seven keys to improving customer satisfaction programs”,Business Horizons,Vol.45No.5,pp.35-42.

Gentry,J.W.(1982),“The impact of credit decisions on shopping behavior”,Advances in Consumer Research,Vol.9No.9,pp.385-8.

Grabner-Kraeuter,S.(2002),“The role of consumers’trust in online-shopping”,Journal of Business Ethic,Vol.39Nos1/2,pp.43-51.

Grewal,D.I.,Gopalkrishnan,R.and Levy,M.(2004),“Internet retailing:enablers,limiters and market consequences”,Journal of Business Research,Vol.57No.7,pp.703-13.

Griffith,D.A.,Krampf,R.F.and Palmer,J.W.(2001),“The role of interface in electronic commerce: consumer involvement with print versus online catalogs”,International Journal of Electronic Commerce,Vol.5No.4,pp.135-53.

Ha,H.Y.(2006),“An integrative model of consumer satisfaction in the context of e-services”, International Journal of Consumer Studies,Vol.30No.2,pp.137-49.

Heiner,E.,Gopalkrishnan,R.I.,Josef,H.and Dieter,A.(2004),“E-satisfaction:a re-examination”, Journal of Retailing,Vol.80No.3,pp.239-47.Online shopping

customer

satisfaction

933

Hsuehen,H.(2006),“An empirical study of web site quality,customer value,and customer satisfaction based on e-shop”,The Business Review ,Vol.5No.1,pp.190-3.Jarvenpaa,S.L.and Todd,P.A.(1997),“Consumer reactions to electronic shopping on the world wide web”,International Journal of Electronic Commerce ,Vol.1No.2,pp.59-88.Jeong,M.,Oh,H.and Gregoire,M.(2003),“Conceptualizing web site quality and its consequences in the lodging industry”,Hospitality Management ,Vol.22No.2,pp.161-75.

Johan,A.(2006),“Sources of customer satisfaction with shopping malls:a comparative study of

different customer segments”,International Review of Retail,Distribution &Consumer Research ,Vol.16No.1,pp.115-38.

Kim,S.and Stoel,L.(2004),“Apparel retailers:website quality dimensions and satisfaction”,

Journal of Retailing and Consumer Services ,Vol.11No.2,pp.109-17.

Kim,S.Y.and Lim,Y.J.(2001),“Consumers’perceived importance of and satisfaction with

internet shopping”,Electronic Markets ,Vol.11No.3,pp.148-54.

Koivumaki,T.(2001),“Customer satisfaction and purchasing behavior in a web-based shopping

environment”,Electronic Markets ,Vol.11No.3,pp.186-92.

Kotler,P.(1997),Marketing Management:Analysis,Planning,Implementation,and Control ,

Prentice-Hall,Engelwood Cliffs,NJ.

Lohse,G.L.and Spiller,P.(1998),“Electronic shopping”,Communications of ACM ,Vol.41No.7,

pp.81-9.

Lu,H.T.(2005),The Behavior Differences of Chinese Consumers ,Chinese Social Science Press,

Beijing.

Lynch,J.Jr and Ariely,D.(2000),“Wine online:search costs affect competition on price,quality

and distribution”,Marketing Science ,Vol.19No.1,pp.83-104.

McGoldrick,P.,Vasquez,D.,Lim,T.Y.and Keeling,K.(1999),“Cyberspace marketing:how do

surfers determine website quality”,in Broadbridge, A.(Ed.),Tenth International Conference on Research in the Distributive Trades.Institute for Retail Studies ,University of Stirling,Stirling,pp.603-13.

McKinney,V.,Kanghyun,Y.and Zahedi,F.M.(2002),“The measurement of web-customer

satisfaction:an expectation and disconfirmation approach”,Information System Research ,Vol.13No.3,pp.296-315.

Manes,S.(1997),“Web sites:slow by design?”,Information Week ,Vol.4No.2,p.124.Mason,J.B.and Bearden,W.O.(1979),“Satisfaction dissatisfaction with food shopping among

elderly consumers”,Journal of Consumer Affairs ,Vol.13No.2,pp.359-69.

Muyllea,S.,Moenaert,R.and Despontin,M.(2004),“The conceptualization and empirical

validation of web site user satisfaction”,Information &Management ,Vol.41No.5,pp.543-60.

Myers,R.(1990),Classical and Modern Regression with Applications ,2nd ed.,Duxbury Press,

Boston,MA.

Nunnally,J.C.(1978),Psychometric Theory ,2nd ed.,McGraw-Hill,New York,NY,p.245.Ofir,C.and Simonson,I.(2007),“The effect of stating expectations on customer satisfaction and

shopping experience”,Journal of Marketing Research ,Vol.1No.1,pp.1-74.

Oliver,R.L.(1980),“A cognitive model of the antecedents and consequences of satisfaction

decisions”,Journal of Marketing Research ,Vol.17No.4,pp.460-9.

Oliver,R.L.(1981),“Measurement and evaluation of satisfaction processes in retail settings”,

Journal of Retailing ,Vol.57No.3,pp.25-48.

IJRDM 36,11934

Pastrick,G.(1997),“Secrets of great site design”,Internet User,Fall,pp.80-7.

Peterson,R.A.,Sridhar,B.and Bart,J.B.(1997),“Exploring the implications of the internet for consumer marketing”,Journal of the Academy of Marketing Science,Vol.25No.4, pp.329-46.

Ranganathan,C.and Ganapathy,S.(2002),“Key dimensions of business-to-consumer web site”, Information&Management,Vol.39No.6,pp.457-65.

Schaupp,L.C.and Be´langer,F.(2005),“A conjoint analysis of online consumer satisfaction”, Journal of Electronic Commerce Research,Vol.6No.2,pp.95-111.

Shankar,V.,Amy,K.and Rangaswamy,A.(2003),“Customer satisfaction and loyalty in online and offline environments”,International Journal of Research in Marketing,Vol.20No.2, pp.153-75.

Shankar,V.,Rangaswamy, A.and Pusateri,M.(2001),“The online medium and price sensitivity”,working paper,University of Maryland,College Park,MD.

Sharma,A.,Grewal,D.and Levy,M.(1995),“The customer satisfaction/logistics interface”, Journal of Business Logistics,Vol.16No.6,pp.1-21.

Shun,C.and Yunjie,X.(2006),“Effects of outcome,process and shopping enjoyment on online consumer behavior”,Electronic Commerce Research and Applications,Vol.5No.4, pp.272-81.

Spreng,R.A.,MacKenzie,S.B.and Olshavsky,R.W.(1996),“A Reexamination of the determinants of consumer satisfaction”,Journal of Marketing,Vol.60No.3,pp.15-32. Szymanski,D.M.and Hise,R.T.(2000),“E-satisfaction:an initial examination”,Journal of Retailing,Vol.76No.3,pp.309-22.

Terblanche,N.S.and Boshoff,C.(2001a),“Measuring customer satisfaction with the controllable elements of the instore shopping experience”,South African Journal of Business Management,Vol.32No.4,pp.11-19.

Terblanche,N.S.and Boshoff,C.(2001b),“Measuring customer satisfaction with some of the controllable elements of the total retail experiences:an exploratory study”,South African Journal of Business Management,Vol.32No.2,pp.35-41.

Turban,E.,Lee,J.,King,D.and Chung,M.H.(2000),Electronic Commerce:A Managerial Perspective,Prentice-Hall,Upper Saddle River Hall,NJ.

Weinberg,B.(2000),“Don’t keep your internet customers waiting too long at the(virtual)front door”,Journal of Interactive Marketing,Vol.14No.1,pp.30-9.

Wolfinbargerhe,M.and Gilly Mary, C.(2003),“EtailQ:dimensionalizing,measuring and predicting etail quality”,Journal of Retailing,Vol.79No.3,pp.183-98.

Yang,Z.and Fang,X.(2004),“Online service quality dimensions and their relationships with satisfaction:a content analysis of customer reviews of securities brokerage services”, International Journal of Service Industry Management,Vol.15Nos3/4,pp.302-26. Yianakos,C.(2002),“Nameless in cyberspace:protecting online privacy”,Journal of Banking and Financial Service,Vol.116No.6,pp.48-9.

Zhang,X.,Prybutok,V.and Huang,A.(2006),“An empirical study of factors affecting e-service satisfaction”,Human Systems Management,Vol.25No.4,pp.279-91.

Zhilin,Y.,Peterson,R.T.and Cai,S.(2003),“Services quality dimensions of internet retailing: an exploratory analysis”,The Journal of Service Marketing,Vol.17Nos6/7,pp.685-98.Online shopping

customer

satisfaction

935

Further reading Carman,J.M.(1990),“Consumer perceptions of service quality:an assessment of the SERVQUAL dimensions”,Journal of Retailing ,Vol.66No.1,pp.33-55.Helson,H.(19),Adaptation-Level Theory ,Harper &Row,New York,NY.Loiacono, E.T.(2000),“WebQualTM:a website quality instrument”,unpublished doctoral dissertation,University of Georgia,Athens.

Solomon,R.L.(1980),“The opponent process theory of acquired motivation:the costs of pleasure

and the benefits of pain”,American Psychologist ,Vol.35No.8,pp.713-28.

Solomon,R.L.and Corbit,J.D.(1974),“An opponent-process theory of motivation:I.Temporal

dynamics of affects”,Psychological Review ,Vol.81No.2,pp.119-45.

Corresponding author

Xia Liu can be contacted at:liuxia1213@163.com

IJRDM 36,11936To purchase reprints of this article please e-mail:reprints@emeraldinsight.com Or visit our web site for further details:www.emeraldinsight.com/reprints

Appendix1.QuestionnaireIJRDM 36,11 938

Online shopping

customer

satisfaction

939

Appendix 2.Exploratory factor loading

C o m p o n e n t s I t e m s

F a c t o r 1F a c t o r 2F a c t o r 3F a c t o r 4F a c t o r 5F a c t o r 6F a c t o r 7F a c t o r 8F a c t o r 9

C o l o r c o m b i n a t i o n 10.7160.1010.0940.0400.1550.0850.0540.0050.048P a y m e n t 20.2450.1270.1300.2280.1570.0800.0540.0050.048

D e l i v e r y 10.14020.0910.1710.7700.1780.1850.0610.14920.022D e l i v e r y 20.25220.1040.0540.7910.1140.1510.0930.0090.030D e l i v e r y 30.14420.0800.1350.8290.0060.1260.1490.1280.063D e l i v e r y 40.16620.0580.2300.7680.0800.1170.1370.1110.068C u s t o m e r s e r v i c e 10.2130.0860.1030.1860.2580.8150.0170.0350.128C u s t o m e r s e r v i c e 20.1290.0820.1380.2020.2550.8220.0080.0530.026C u s t o m e r s e r v i c e 30.1920.0730.1920.2020.1980.7550.0950.1450.090N a v i g a t i o n 4i n f o r m a t i o n 0.6800.0700.0550.0680.0020.0690.1360.0300.101U n d e r s t a n d a b i l i t y 1i n f o r m a t i o n 0.1410.1030.6930.08520.0530.1810.1080.1450.056U n d e r s t a n d a b i l i t y 2i n f o r m a t i o n 0.1670.0940.7390.06320.0700.1590.0460.1840.024I n f o r m a t i o n a c c u r a c y 10.0850.0850.6350.0230.31720.0590.1700.0220.149I n f o r m a t i o n a c c u r a c y 220.0060.0830.5670.1280.3660.04320.0590.1780.160I n f o r m a t i o n c o m p l e t e n e s s 120.00720.0330.5780.1300.1450.08020.00.3210.054I n f o r m a t i o n c o m p l e t e n e s s 20.15720.0040.6300.0600.0990.0520.05520.19420.048I n f o r m a t i o n r e l e v a n c y 10.1180.0690.5910.1910.1950.0180.03720.03420.050M e r c h a n d i s e v a r i e t y 10.0810.8840.05120.0070.0530.0270.0360.04120.033M e r c h a n d i s e v a r i e t y 20.0510.8610.02920.0490.0240.0460.1010.03520.039M e r c h a n d i s e v a r i e t y 30.1100.8480.09820.0250.0050.0230.1100.0220.028M e r c h a n d i s e v a r i e t y 40.0400.8160.06320.06520.0180.0650.0170.01620.055P r i c e l e v e l 10.1040.7870.02720.1040.11120.0100.00320.0040.054P r i c e l e v e l 20.1290.7800.05020.0030.1530.06920.0110.09420.003T r a n s a c t i o n c a p a b i l i t y 10.2510.1090.2010.2040.0990.0600.1750.7240.076T r a n s a c t i o n c a p a b i l i t y 20.1610.1060.1620.1760.2100.1340.0290.74320.047R e s p o n s e t i m e 10.1070.0110.0700.0850.0300.09220.00520.0270.856R e s p o n s e t i m e 20.10320.0650.0760.0100.1170.0710.0150.0510.841S e c u r i t y /p r i v a c y 10.2060.0130.1230.0120.6580.1720.0630.1130.130S e c u r i t y /p r i v a c y 20.10.0600.1380.1060.7680.1900.1240.0070.008S e c u r i t y /p r i v a c y 30.1250.1660.2000.0650.7520.1990.1190.1040.003S e c u r i t y /p r i v a c y 40.0970.0860.1340.2270.7490.0850.0150.0680.031P a y m e n t 1

0.2420.1400.1260.2160.1600.0280.8470.075

0.003

Table AI.

IJRDM 36,11

940