2. 550 MARTIN AND CAMARERO
satisfaction and trust is expected because a positive emo-tional
condition regarding the relation with this Web site
(satisfaction with the Web site) will most likely lead to con-sumer
emotional security that this Web site will meet their
expectations of outcome or performance (trust in the Web
site). The positive influence of satisfaction on trust has been
supported in an online context.20
H3: Satisfaction with previous results has a positive influ-ence
on the consumer’s trust in the Web site.
The moderator role of motivating and inhibiting factors of
online purchasing
Many studies have dealt with the driving and inhibiting
factors that influence initiation of a business-to-consumer
(B2C) online relationship.21,22 It is proposed here that indi-vidual
attitudes and rules of behavior influence consumers’
perceptions of Web site actions consequently their degree of,
and willingness to, trust. Although there is a shortage of ref-erence
literature, if it is possible that while certain individu-als
feel many inhibitors toward online shopping23 and are
prepared to trust a certain Web site only if they perceive
many positive signals from a firm and have had a satisfac-tory
experience with previous results, other individuals who
are more incline to online shopping and perceive the exis-tence
of sufficient motives for the purchase,24,25 require fewer
signals from the firm in order to be willing to trust. There-fore,
H4: The motives and inhibitors for online shopping will
perform as moderating factors in the relations between the
Web site characteristics, the satisfaction with previous out-come,
and the consumer’s trust in the Web site.
Methods and Results
Sample and data collection
The empirical study is based on information gathered
through a questionnaire given to Internet users and online
shoppers. In order to reach these users, questionnaires were
sent to several cyber-centers. Several regional development
agents and cyber-center supervisors collaborated in the
data-collection process, distributing and collecting the ques-tionnaires
in several Spanish regions. The agents and su-pervisors
were asked to deliver the questionnaires to those
users of the cyber-centers who had previously stated that
they buy products and services over the Internet. The ques-tionnaire
asked each participant to name a Web site he or
she most used to shop, and the participant’s subsequent
evaluation on terms of satisfaction in shopping and trust
was conducted on his or her specified Web site. The survey
took place from May through July 2006, after which a sam-ple
of 533 individuals was obtained. After an initial filter
process whereby 26 questionnaires were eliminated due to
incompleteness or wrong answers, the final sample included
507 individuals. Once the questionnaires were collected, we
performed a series of tests to analyze the validity of the ob-tained
responses. We compared the characteristics of con-sumers
that had answered in the first month of the survey
with those of consumers answering in the last month, and
we did not find any significant difference.
Variables measurement
Five-point Likert scales were used to measure the model
variables, taking different literature projects as refer-ence1,3,17,26
and undertaking the necessary adaptation (Table
1). The measures of Web site characteristics are formative
scales. In each case, an index was created from the average
of the corresponding items. For satisfaction and trust, reflec-tive
scales were used. These scales were subjected to a con-firmative
factor analysis (CFA) and convergent validity was
proved (2(24) 71.96 (p 0.000); GFI 0.967; AGFI
0.939; CFI 0.989; RMSEA 0.064). These scales were also
reduced to a single indicator.
To measure the motives and inhibitors for online shopping,
24 indicators were used. The six factors obtained from a fac-tor
analysis clearly reflect the three types of motives and the
three types of inhibitors that were taken into consideration
(Table 2): the search for rationality when shopping; the scope
of possibilities and the greater convenience (as motives or dri-ving
factors); and the greater transaction costs, the technical
difficulties and the lack of physical contact (as inhibitors).
Once these factors were obtained, a cluster analysis was
performed with the objective of identifying the individual
profiles in relation to the type of driving and inhibiting fac-tors
encountered during the online shopping process. Four
types of e-commerce users were found: Potential users are not
afraid of online shopping because they are less aware than
other groups of the transaction-cost problem or the lack of
personal contact. Motivated users are inclined to shop online,
they positively value the many benefits of online shopping
more than do other individuals, and they do not see too
many inhibitors; the main inhibitor could be the technical
difficulties. Indifferent users perceive the fewer advantages
over traditional shopping except for the rationality of the
purchase. Relational users place highest value on personal
contact; the main inconvenient for this group is the lack of
personal contact in online shopping.
Effect of company and Web site characteristics on
satisfaction and trust
The next step of the analysis was to estimate the effect of
the company and Web site characteristics on satisfaction and
trust as well as the moderating role of motives and inhibi-tors
for purchasing. The proposed hypotheses were tested
by means of a multigroup analysis. First, the model was es-timated
taking into consideration identical coefficients for
the four e-commerce user groups (Table 3). Second, the
multigroup model was estimated, leaving the parameters
free for each group (Table 4). In both cases, the goodness-of-fit
indicators are positioned within the suggested limits and
are considered as proof of a good fit. However, after intro-ducing
the moderating effect of the user type, the model
goodness-of-fit improves, showing a significant decrease in
the chi-square value 2(27) 64.68 (p 0.000).
As shown in Table 1, the quality of service and the secu-rity
and privacy policies have a significant influence on trust
and satisfaction, as proposed under H1a and H1b, although
the effect of warranty is not significant. As for the rest of
Web site characteristics that determine online customer sat-isfaction,
the design of the Web site does in fact have a pos-itive
influence; however, the effect of the interactivity of the
purchasing experience is not significant. Hence, H2 can be
3. CONSUMER TRUST TO A WEB SITE 551
TABLE 1. VARIABLES MEASUREMENT
Variables Description Mean SD Lambda
Warranty A warranty is provided to cover possible unforeseen events or 3.37 1.08 —
product/service faults.
There is the possibility of returning a product if the customer 3.18 1.16 —
is not satisfied.
Security It is safe and has a privacy policy regarding customer 3.80 1.02 —
and privacy information.
policies The site informs the customer about security and privacy 3.78 1.10 —
policies.
I feel safe when sending personal information. 3.56 1.16 —
I think my rights regarding my personal details are respected. 3.57 1.09 —
I do not think my details are used to be transferred to other 3.44 1.21 —
companies or to send me advertising which I have not
consented to.
I think the site has mechanisms that warrantee the safe 3.60 1.07 —
transmission of its users’ information.
Quality of Detailed information is provided regarding the range of 3.84 1.00 —
service products and services offered.
Compliance with promised quality and delivery term 3.79 1.01 —
conditions.
It offers good price-quality level products. 3.80 0.96 —
It offers customized products and services. 3.26 1.15 —
It offers wide range of products. 3.86 1.05 —
Interactive The intention is to promote interactivity with the visitors. 3.15 1.00 —
experience I perceive the shopping experience as if I were buying in the 3.00 1.20 —
only partially accepted. Finally, the effect of satisfaction with
previous experiences (H3) is significant; in fact, is the variable
that mostly explains the trust of the online customer and a me-diating
variable that links Web site characteristics and trust.
After introducing the moderating effect and allowing different
parameters, the difference between groups was confirmed
(H4). Regarding potential users, their main difference, com-pared
with the average, is that service quality does not have a
direct influence on trust, only indirectly via satisfaction. Per-ceived
previous satisfaction and warranty, security, and pri-vacy
policies are the variables that have a direct influence on
trust. For motivated users, the main determining factors of sat-isfaction
and, indirectly, of trust are service quality, security
and privacy policies, and the design of the Website. The in-different
users, who perceive few advantages of online shop-ping,
are the group that values the most Web site characteris-tics
as determining factors for satisfaction and trust. The effect
of warranty and Web page design on satisfaction is more im-portant
in this group. Finally, relational users highlight the pos-itive
effect of Web site interactivity as a key factor for satisfac-tion,
and they highlight the neutral effect of the Web site’s
quality, maybe because in this case the Web site cannot sub-stitute
for the salesperson.
Discussion
This study shows that some characteristics of online trade
firms, such as security and privacy policies, service quality,
physical store.
Web site Browsing is easy. 3.92 1.00 —
design The site contains images, and it is fun to shop on it. 3.68 1.05 —
The site has an attractive, modern, and professional design. 3.72 0.92 —
Trust I think this Web site keeps its promises. 3.77 1.07 0.815
0.788; I think the information provided on this Web site is true and 3.82 0.86 0.859
AVE honest.
0.481 I think I can trust this Web site. 3.80 0.93 (a)
This Web site never issues false statements. 3.48 1.04 (a)
This Web site stands out for its honesty and transparency while 3.65 0.92 0.716
offering its products to the user.
I think this Web site operates in an ethical manner. 3.65 0.95 0.533
I think this Web site has the necessary resources to successfully 3.88 0.91 0.454
carry out its activities.
Satisfaction I think I made the right decision by using this Web site. 3.89 1.03 (a)
0.890; My shopping expectations have been met by this Web site. 3.88 0.92 0.866
AVE The shopping experience on this Web site has been satisfactory. 3.92 0.90 0.894
0.713 I am happy with the products I have bought on this Web site. 3.96 0.86 0.833
I am generally happy with the service provided by this 3.97 0.90 0.830
Web site.
(a) Deleted items.
4. 552 MARTIN AND CAMARERO
TABLE 2. MOTIVES AND INHIBITORS FOR ONLINE SHOPPING
Motives for online shopping Mean SD Inhibitors for online shopping Mean SD
Convenience
Shopping speed 4.19 1.03
Convenience 4.36 0.88
Easy price comparison 4.04 0.95
More alternatives
Wide product range 3.98 1.02
Access to special products that 3.89 1.03
are not available in physical
stores
Search for ideas 3.32 1.13
Timetable flexibility 4.04 1.10
Enjoyment 3.15 1.24
Rationality
Few stores in area of residence 2.92 1.30
Less stress while shopping 3.17 1.29
Fewer impulsive and nonplanned 3.21 1.26
purchases
and warranties, have a more direct influence on trust, while
the quality of the Web site has an indirect influence on con-sumers’
satisfaction. Among all these variables, satisfaction
with the previous purchases is undoubtedly the main de-terminant
for trust, which reinforces findings of previous
studies. With regard to the satisfaction determinants, secu-rity
Lack of physical contact
Lack of personal relationship 3.19 1.25
and salesperson advice
Lack of relationships with other 2.87 1.15
people
The impossibility to see, touch 3.98 1.11
or smell the product
Lack of client service 3.20 1.23
customization
Greater transaction costs
Difficulty regarding refunds 3.85 1.11
and claims
High postal and delivery costs 3.51 1.14
The need to place large orders 3.40 1.18
to reduce the delivery costs
Lack of payment security 3.99 1.22
Possible losses caused by the 2.98 1.12
short expiry date of certain
products such as food
Technical problems
Excessive complication while 3.07 1.21
browsing or buying on Internet
Technical problems while 3.23 1.27
connecting to or browsing
Internet
Lack of Internet knowledge 2.73 1.27
The need to plan the purchase 2.80 1.13
and privacy policies, service quality, and Web site de-sign
become key factors for the purchase satisfaction.
Another part of the study centered on the analysis of the
differential effect of firm and Web site characteristics on sat-isfaction
and trust according to individuals’ attitudes toward
online buying. Four types of individuals were identified: po-
TABLE 3. MULTIGROUP ANALYSIS; IDENTICAL COEFFICIENTS
Satisfaction Trust
Quality of the service 0.290 (6.512) 0.140 (3.991)
Warranty 0.006 (0.144) 0.008 (0.275)
Security and privacy 0.325 (7.673) 0.216 (6.374)
Interactive experience 0.004 (0.109) —
Website design 0.143 (3.463) —
Satisfaction — 0.566(16.302)
R2 0.263 0.546
Goodness of fit 2(41) 94.503 (p 0.000);
CFI 0.972; RMSEA 0.101
Potential users Contribution to 2 12.88 (13.63%)
RMR 0.063
GFI 0.970
Motivated users Contribution to 2 29.82 (31.56%)
RMR 0.085
GFI 0.944
Indifferent users Contribution to 2 24.14 (25.55%)
RMR 0.103
GFI 0.949
Relational users Contribution to 2 27.63 (29.24%)
RMR 0.070
GFI 0.933
5. TABLE 4. MULTIGROUP ANALYSIS; DIFFERENT COEFFICIENTS BETWEEN GROUPS
Potential users Motivated users Indifferent users Relational users
Satisfaction Trust Satisfaction Trust Satisfaction Trust Satisfaction Trust
Quality of the service 0.606*** 0.196*** 0.222*** 0.093*** 0.528*** 0.237*** 0.834*** 0.918***
Warranty 0.100*** 0.328*** 0.039*** 0.028*** 0.386*** 0.108*** 0.047*** 0.109
Security and privacy 0.409*** 0.262*** 0.325*** 0.165*** 0.132*** 0.215*** 0.194*** 0.087***
Interactive experience 0.071*** — 0.111*** — 0.125*** — 0.270*** —
Website design 0.078*** — 0.243*** — 0.363*** — 0.039*** —
Satisfaction — 0.481*** — 0.639*** — 0.512*** — 0.579***
R2 0.311*** 0.539*** 0.504*** 0.650*** 0.392*** 0.564*** 0.289*** 0.584***
Group goodness of fit Contribution to Contribution to Contribution to Contribution to
2 2.284 (7.658%) 2 18.37 (61.60%) 2 7.930 (26.58%) 2 1.237 (4.14%)
RMR 0.020 RMR 0.029 RMR 0.023 RMR 0.018
GFI 0.995 GFI 0.963 GFI 0.983 GFI 0.997
Goodness of fit 2(14) 29.823 (p 0.008); CFI 0.992; RMSEA 0.085
***p 0.01.
6. 554 MARTIN AND CAMARERO
tential users inclined to online purchase; motivated users, who
value the benefits, although to a lesser extent than others; in-different
users who are neutral about online trade; and rela-tional
users, who perceive the lack of personal contact as a
great barrier. The common element to all these groups is the
importance they give to security and privacy policies and to
satisfaction with previous experiences as determinants for
trust. In the rest of variables, some significant differences be-tween
the groups have been found. Potential users show a
more rational trust, based on the security and privacy offered
by the Web site. Although service quality also influences trust,
it only does so indirectly through satisfaction. Motivated in-dividuals
value service quality offered by the Web site, which
influences both satisfaction with and trust in the Web site. This
group also values the design of the Web site as reason for sat-isfaction
and subsequent trust. In general, Web site charac-teristics
have the greatest effect on the generation of trust in
motivated individuals. They are the group more prone to trust.
For indifferent individuals, the warranty is a factor that gen-erates
satisfaction. Also, the service quality and the Web site
design have a great indirect influence on trust through satis-faction.
Since the motives for trust are mainly the results of
previous satisfaction, this group relies on more experience-based
trust. Finally, in the case of relational individuals, it is the in-teractivity
of the experience that has value. It is therefore the
case of a trust based on the relational experience.
As regards managerial implications, the findings suggest
that although satisfaction with previous encounters and results
is the main antecedent of online trust, online vendors can also
engender consumers’ trust by offering good service quality,
fulfilling their security and privacy promises, and selling
through a well-designed and appealing Web site. The results
indicate the importance of achieving the client total experience
in an online environment purchase. Experience in virtual con-text
is tied not only to Web site design and achieved interac-tivity
but also to data privacy, security systems in payment,
quality of the offer and delivery of products and services, pre-and
postsale support service, and relationships with the clients.
Disclosure Statement
The authors have no conflict of interest.
References
1. Ranaweera C, McDougall G, Bansal H. A model of on-line
customer behavior during the initial transaction: moderat-ing
effects of customer characteristics. Marketing Theory
2005; 5:5–6.
2. Gefen D. E-commerce: the role of familiarity and trust. In-ternational
Journal of Management Science 2000; 28:725–37.
3. Harris LC, Goode MMH. The four levels of loyalty and the
pivotal role of trust: a study of on-line service dynamics.
Journal of Retailing 2004; 80:139–58.
4. Bart Y, Shankar V, Sultan F, et al. Are the drivers and role
of on-line trust the same for all Web sites and consumers?
A large-scale exploratory empirical study. Journal of Mar-keting
2005; 69:133–53.
5. Lee B, Ang L, Dubelaarc C. Lemons on the Web: A signal-ing
approach to the problem of trust in Internet commerce.
Journal of Economic Psychology 2005; 26:607–23.
6. Biswas D, Biswas A. The diagnostic role of signals in the
context of perceived risks in online shopping: do signals
matter more on the Web? Journal of Interactive Marketing
2004; 18:30–45.
7. Schlosser AE, Barnett T, Lloyd SM. Converting Web site vis-itors
into buyers: how Web site investment increases con-sumer
trusting beliefs and online purchase intentions. Jour-nal
of Marketing 2006; 70:133–48.
8. Wang S, Beatty SE, Foxx W. Signaling the trustworthiness
of small online retailers. Journal of Interactive Marketing
2004; 18:53–69.
9. Yousafzai SY, Pallister JG, Foxall GR. Strategies for building
and communicating trust in electronic banking: a field ex-periment.
Psychology Marketing 2005; 22:181–201.
10. Wood SL. Remote purchase environments: the influence of
return policy leniency on two-stage decision process. Jour-nal
of Marketing Research 2001; 38:157–69.
11. Sultan F, Mooraj HA. Designing a trust-based e-business
strategy. Marketing Management 2001; 10:40–5.
12. Gummerus J, Liljander V, Pura M, et al. Customer loyalty
to content-based Web sites: the case of an online health-care
service. Journal of Services Marketing 2004; 18:175–86.
13. Lee GG, Lin HF. Customer perceptions of e-service quality
in online shopping. International Journal of Retail Distri-bution
Management 2005; 33:161–76.
14. Park CH, Kim YG. Identifying key factors affecting con-sumer
purchase behaviour in an online shopping context.
International Journal of Retail Distribution Management
2003; 31:16–29.
15. Rodgers W, Negash S, Suk K. The moderating effect of on-line
experience on the antecedents and consequences of on-line
satisfaction. Psychology Marketing 2005; 22:313–31.
16. Shankar V, Smith A, Rangaswamy A. Customer satisfaction
and loyalty in online and off-line environments. Interna-tional
Journal of Research in Marketing 2003; 20:153–75.
17. Montoya-Weiss MM, Voss GB, Grewal D. Determinants of
online channel use and overall satisfaction with a relational,
multichannel service provider. Journal of the Academy of
Marketing Science 2003; 31:448–58.
18. Selnes F. Antecedents and consequences of trust and satis-faction
in buyer-seller relationships. European Journal of
Marketing 1998; 32:305–22.
19. Szymanski DM, Hise RT. E-satisfaction: an initial examina-tion.
Journal of Retailing 2000; 76:309–22.
20. Ribbink D, van Riel ACR, Liljander V, et al. Comfort your
online customer: quality, trust, royalty on the Internet. Man-aging
Service Quality 2004; 14:446–56.
21. Wolfinbarger M, Gilly MC. Shopping online for freedom, con-trol
and fun. California Management Review 2001; 43:34–55.
22. Yang B, Lester D. Attitudes toward buying online. Cy-berPsychology
Behavior 2004; 7:85–91.
23. Cho CH, Kang J, Cheon HJ. Online shopping hesitation. Cy-berPsychology
Behavior 2006; 9:261–74.
24. Yang B, Lester D, James S. Attitudes toward buying online
as predictors of shopping online for British and American
respondents. CyberPsychology Behavior 2007; 10:198–203.
25. Rohm A, Swaminathan V. A typology of online shoppers
based on shopping motivations. Journal of Business Re-search
2004; 57:748–57.
Address reprint requests to:
Dr. Carmen Camarero
Department of Business and Marketing
University of Valladolid
Avenida Valle de Esgueva, 6
47011 Valladolid
Spain
E-mail: camarero@eco.uva.es
