Multilevel and multidimensional scale for online trust

Abstract

This paper examines the nature of the construct of consumers' trust toward the electronic channel of their financial institution. Through a study of a total of 372 individual users of Internet banking in Spain, we have managed to develop a third-order measuring instrument that integrates a total of seven dimensions. The exploratory and confirmatory factor analyses were used to test the validation and reliability of the proposed scale. Findings provide useful information to professionals who seek to identify how customer's trust is formed in the online channel and in the financial sector.

Full text

187
ISSN 0034-7590 © RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
MARIA JESÚS LÓPEZ MIGUENS
chusl@uvigo.es
Professor at Departament of
Business Management and
Marketing, University of Vigo,
Vigo – Spain
ENCARNACIÓN GONZÁLEZ VÁZQUEZ
egzlez@uvigo.es
Professor at Departament of
Business Management and
Marketing, University of Vigo,
Vigo – Spain
PALOMA BERNAL TURNES
paloma.bernal@urjc.es
Lecturer at Departament of Business
Management, Rey Juan Carlos
University, Madrid – Spain
ARTICLES
Submitted 09.06.2012. Approved 07.02.2013
Evaluated by double blind review. Scientific Editor: Bento Alves da Costa Filho
MULTILEVEL AND MULTIDIMENSIONAL
SCALE FOR ONLINE TRUST
Escala multinível e multidimensional para confiança online
Escala multinivel y multidimensional para la confianza en línea
ABSTRACT
This paper examines the nature of the construct of consumers’ trust toward the electronic channel
of their financial institution. Through a study of a total of 372 individual users of Internet banking
in Spain, we have managed to develop a third-order measuring instrument that integrates a total of
seven dimensions. The exploratory and confirmatory factor analyses were used to test the validation
and reliability of the proposed scale. Findings provide useful information to professionals who seek to
identify how customer’s trust is formed in the online channel and in the financial sector.
KEYWORDS | Scale, trust, online banking, users, validation.
RESUMO
Este artigo analisa a natureza do construto- confiança dos consumidores em relação ao canal ele-
trônico de sua instituição financeira. Por meio de um estudo com 372 usuários individuais de ope-
rações bancárias via internet na Espanha, conseguimos desenvolver um instrumento de medida de
terceira ordem que integra sete dimensões. Foram utilizadas análises fatoriais exploratórias e con-
firmatórias a fim de testar a validade e a confiabilidade da escala proposta. Os resultados fornecem
informações úteis aos profissionais que procuram identificar como se constitui a confiança do cliente
no canal online e no setor financeiro.
PALAVRAS-CHAVE | Escala, confiança, operações bancárias online, usuários, validação.
RESUMEN
Este trabajo examina la naturaleza del constructo confianza de un consumidor hacia el canal electróni-
co de su entidad financiera. A través de un estudio efectuado sobre un total de 372 usuarios particu-
lares de la banca en Internet en España se ha conseguido desarrollar un instrumento de medida de
tercer orden formado por un total de siete dimensiones. Los análisis factoriales exploratorio y confir-
matorio han sido las herramientas utilizadas para efectuar las pruebas de validación y fiabilidad a la
escala propuesta. Las conclusiones del estudio proporcionan información útil a los profesionales que
persiguen identificar cómo se forma la confianza del cliente en el canal y sector referido.
PALABRAS CLAVE | Escala, confianza, banca electrónica, usuarios, validación.
RAERevista de Administração de Empresas | FGV-EAESP
DOI: http://dx.doi.org/10.1590/S0034-759020140206

188
ISSN 0034-7590
ARTICLES | Multilevel and multidimensional scale for online trust
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
INTRODUCTION
As a similar trend has occurred in countries with closed econo-
mies, the Spanish banking sector has experimented significant
changes over the last decades, such us the increase of the bank-
ing activity, deregulation, disintermediation or introduction of
new technologies (Perez & Maudos, 2001; Carbó, 2004; Bravo,
Montaner & Pina, 2007; Garrido, 2007). In particular, the incor-
poration of Internet in the financial sector has led to substan-
tial implications at an economic level, changes in the way firms’
activities are developed and has dramatically changed the dai-
ly lives of customers. Thus, related to companies, the invest-
ment in information technologies has led to a reduction in la-
bour costs and a set of improvements in eciency, productivity
and business performance (Bitner, Zeithaml & Gremler, 2010;
Dabholkar, 1996). Internet has also enabled the development of
alternative distribution channels to the traditional oces-based
one (cashier, phone banking, and electronic banking) and fa-
vours the entry of other financial and non-financial institutions
in the banking sector, this last situation has further enhanced
the level of competition (Garrido, 2007). Related to the banking
consumers’ behaviour, these consumers are increasingly edu-
cated and demanding (Alcaide & Soriano, 2005) and they have
seen the advantages of convenience, independence and quali-
ty (Oliver, Livermore & Farag, 2009; Carbó, 2004; Gerrard & Cun-
ningham, 2003; Meuter, Ostrom, Roundtree & Bitner, 2000) as
determinants for the adoption of the medium. At the same time,
the lack of consumer trust in the financial service provided by
online banks has been argued to be one of the most important
barriers to developing the potential of the electronic banking
(Gefen, 2000; Jarvenpaa, Tractinsky & Vitale, 2000; Yoon, 2002;
Chouk & Perrier, 2004; Harris & Goode, 2004), due to the per-
ception of high risk by Internet when carrying out certain trans-
actions over the Internet.
This situation has prompted a growing number of theoret-
ical and empirical researches in order to study the construct of
trust in the electronic banking. However, trust has been under-
stood in dierent ways in terms of composition and dimensions
(see Cheung & Lee, 2006). These works have been developed
from the firm’s perspective (supply) neglecting the perspective
of the consumers, whose perception enhances the success of a
firm (Bravo, Montaner & Pina, 2007).
According to the above mentioned motives, banking strat-
egies should be defined based on the identification of all indica-
tors that are involved in the building of customer trust over the
Internet in order to reduce risk. So, the aim of our work is to deep-
en on the understanding of a more eective strategic mix that de-
fines the marketing eorts to build online trust in a financial busi-
ness that uses the electronic channel. With the development of a
measurement scale from the perspective of customer’s percep-
tion, we try to understand how the trust of users who utilize elec-
tronic services of a financial institution is explained.
The article is structured as follows. The first section dis-
cusses the theoretical principles based on the conceptualiza-
tion of the construct and then we formulated the measuring in-
struments of online trust. In the second part, the measurement
scale developed is tested at dierent levels with regard to the
dimensionality, reliability and validation, in both exploratory
and confirmatory terms. The third section highlights the conclu-
sions and managerial or scientific implications of the obtained
results. The article concludes with the presentation of the main
limitations of the research.
THEORETICAL AND CONCEPTUAL
FRAMEWORK
The term trust plays a key role in explaining the online consum-
ers’ behaviour (Pavlou, 2003). Since ancient times, trust has
been investigated in the marketing literature; however, Das
and Teng (2004) argue that, despite being one of the most used
terms in the social sciences, it is the “least understood” of the
most important concepts of the discipline.
Building and maintaining trust in the online distribu-
tion channel is more important (Sultan & Mooraj, 2001; Gefen,
Karahanna & Straub, 2003; Gefen & Straub, 2004; Walczuch &
Lundgren, 2004; Riegelsberger, Sasse & McCarthy, 2005; Har-
ridge-March, 2006; Pavlou & Fygenson, 2006) than in an of-
fline environment. The online context entails greater diculties
(Grewal, Lindsey-Mullikin & Munger, 2003; Reichheld & Scheft-
er, 2000; Bhattacherjee, 2002) and the degree of uncertainty is
greater (Grabner-Krauter, 2002). In addition, the peculiarities of
online banking enhance the importance of trust (Grabner-Kräut-
er & Faullant, 2008), and distrust is one of the main reasons,
stated in the recent literature, that justify the fear that users still
show when conducting financial transactions over the Internet
(Mukherjee & Nath, 2003; Rotchanakitumnuai & Speece, 2003;
Luarn & Lin, 2005; Flavián & Guinalíu, (2006a). Hence, this lack
of confidence can be enhanced if the user does not know “in
depth” the company (Cheung & Lee, 2006), if he or she is not fa-
miliar with the network, or if the user has suspicion towards the
technology or the features that define the personality of the in-
dividual (Ruiz, Izquierdo & Calderón, 2007).
In the large body of literature on the construct trust au-
thors highlights the lack of unanimity about the definition of
the term that has been “explained in a very vague and unsys-

189
ISSN 0034-7590
AUTHORS | Maria Jesús López Miguens | Encarnación González Vázquez | Paloma Bernal Turnes
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
tematic way”, despite the relevance of the concept (Cheung &
Lee, 2006). Numerous definitions have been proposed, some of
them are coincident, but most picks up one or more specific as-
pects. In this study, we understand online trust reflects the ex-
tent to which a banking online user expects an honest, benevo-
lent and competent behaviour of the company and company will
cover measures in order to reduce insecurity and lack of privacy.
DATA COLLECTION
A structured questionnaire, completed electronically, was used
to collect data. It has allowed us to collect a total of 578 respons-
es of individual users of online banking, of which 372 have been
found valid after a depuration process. Table 1 presents the data
sheet of the investigation.
TABLE 1. Technical details of the investigation
Sampling unit. Individual 16 to 74 years, resident in
Spain and users of online banking.
Geographical scope of
the study Spain
Sampling procedure. Non-probabilistic method. Convenience
sampling. Snowball
Sample size (n) 372
Method of collection of
information
The information was collected through
structured questionnaires, self-
administered electronically
Dates of fieldwork November 2008 to February 2009
Number of
questionnaires 518
Results of data analysis shows that the profile of the
user of online financial services is: young, male or female, with
a high level of education and income, he/she accesses to the
Web every 7 days or more often to see extracts, balance report-
ing or movements, or to make a transfer.
MEASUREMENT SCALE
According to the literature reviewed, the construct of trust in the
electronic context includes general and specific attributes. Gen-
eral attributes refer to the part in which you trust and they are
present in a traditional buyer-seller relationship, and specific
attributes refer to the online context. Those general attributes
shape trust as reliability and belief, according to the perspec-
tive of social psychologists (Cheung & Lee, 2006), and corre-
spond with the first moment of trust, according to Ramón and
Martin (2007). The specific attributes of online context are se-
curity and privacy.
Reliability refers to the perception that one person has
about the dignity of another subject. In order to describe the
reliability of the seller (object of trust), customer (partner who
trusts) makes an analysis of certain characteristics and be-
haviours that seller could developed in the future (Ganesan,
1994; Coulter & Coulter, 2002; Das & Teng, 2004; Ramón & Mar-
tin, 2007). However, despite the absence of a unified approach
to establish what should be the attributes or dimensions that an
individual must meet to be considered reliable (Ramón & Mar-
tin, 2007), from the review we include three dimensions of trust:
honesty, benevolence, and competence. Despite the condition
of interpersonal relationship defended by Grabner-Kräuter and
Faullant (2008), in the dimensions of benevolence and honesty,
it is not strictly adhered to in the context of online banking; we
opt for including these dimensions because we understand us-
ers feel that not only does the technology participate in the rela-
tionship, but a group of people of the financial entity also do it.
Honesty arises from an evaluation process and refers to
the conviction that consumer shows respect to sincerity and
the degree of fulfilment of the promises the other party made
(Anderson & Narus, 1990; Gundlach & Murphy, 1993; Doney &
Cannon, 1997; Geyskens, Steenkamp & Kumar, 1998, 1999).
Benevolence is strongly related to the goodwill of the seller.
Thereby, a company will be considered benevolent during the
exchange whether it seeks the correct development of the ex-
change rather than corporate profits (Lee & Turban, 2001; Be-
langer, Hiller & Smith, 2002). Benevolence has been measured
by searching consumer welfare (Crosby, Evans & Cowles, 1990;
Ganesan, 1994; Doney & Cannon, 1997; Cheung & Lee, 2006;
Flavián & Guinalíu, 2007), obtaining a joint benefit (Doney &
Canon, 1997), as well as avoiding opportunistic behaviour (Lar-
zelere & Huston, 1980), and so on. Competence of the compa-
ny is also measured through the perceptions of customers. They
assess whether the company has the skills (Blomqvist, 1997),
abilities and characteristics (Cheung & Lee, 2006) required to
make something that has been previously promised. This attri-
bute is particularly important in the electronic context (Roy, De-
wit & Aubert, 2001; Bhattacherjee, 2002; Pavlou, 2003; Suh &
Han, 2003), because seller should prove that has the needed re-
sources to accomplish that with what has been committed in a
safe and ecient way (Flavián & Guinalíu, 2007).
Based on the literature review, the indicators and authors
proposed to explain the construct reliability (Table 2) are sum-
marized.

190
ISSN 0034-7590
ARTICLES | Multilevel and multidimensional scale for online trust
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
TABLE 2. Proposed instrument for measuring the reliability (honesty, benevolence and competence) of online banking
Nomenclature Items Author/s
Realib1 The firm fulfils the commitment it assumes
Doney and Cannon (1997)
Roy, Dewit and Aubert (2001)
Flavián and Guinalíu (2006a, 2006b)
Sohn et al. (2008)
Realib2 The information the firm provides is sincere and honest
Harris and Goode (2004)
Flavián and Guinalíu (2006a, 2006b)
Ramón and Martin (2007)
Realib3 I can trust the promises they make
Ganesan (1994)
Doney and Cannon (1997)
Flavián and Guinalíu (2006a, 2006b)
Realib4 The firm ever makes false statements Ganesan (1994)
Flavián and Guinalíu (2006a, 2006b)
Realib5 This firm is characterized by frankness and transparency of the services it oers Flavián and Guinalíu (2006a, 2006b)
Realib6 Advice and recommendations are made to provide mutual benefit
Doney and Cannon (1997)
Roy, Dewit and Aubert (2001)
Harris and Goode (2004)
Flavián and Guinalíu (2006a, 2006b)
Realib7 The firm worries about present and future interests of its users
Ganesan (1994)
Roy, Dewit and Aubert (2001)
Flavián and Guinalíu (2006a, 2006b)
Realib8 They take into account the repercussions that their actions could have on their
users Flavián and Guinalíu (2006a, 2006b)
Realib9 They would not do anything intentional that might prejudice their users Roy, Dewit and Aubert (2001)
Flavián and Guinalíu (2006a, 2006b)
Realib10 This company designs its commercial oer taking into account of the desires and
needs of users Flavián and Guinalíu (2006a, 2006b)
Realib11 The firm has the ability (capacity) to carry out its work
Roy, Dewit and Aubert (2001)
Cheung and Lee (2006)
Flavián and Guinalíu (2006a, 2006b)
Ramón and Martin (2007)
Realib12 He has a wide experience in the financial market
Roy, Dewit and Aubert (2001)
Cheung and Lee (2006)
Flavián and Guinalíu (2006a, 2006b)
Realib13 It has a good reputation Roy, Dewit and Aubert (2001)
Realib14 The firm knows its users enough to oer products and services adapted to their
needs Flavián and Guinalíu (2006a, 2006b)
Particularities of the channel indicate specific measures
are needed to approximate online trust, in order to consider
comprehensively the security condition in the medium. Unlike
the traditional channel, consumer’s behaviour over the Internet
is recorded from accessing the Web and throughout the naviga-
tion process. Related to this fact there are two aspects that ex-
ceptionally worry users: security and protection of the privacy in
treatment of private data. Although they are related, these two
criteria have been used separately in the literature (e.g., Kee-
ney, 1999; Ranganathan & Ganapathy, 2002). This has led us to
propose two dimensions in our research: security and privacy.
The first dimension refers to technical aspects of the se-
curity of information systems on which data protection mea-
sures are based. According to Kolsaker and Payne (2002) se-

191
ISSN 0034-7590
AUTHORS | Maria Jesús López Miguens | Encarnación González Vázquez | Paloma Bernal Turnes
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
curity includes the mechanisms of transmission and storage
of information. Security mechanisms are: digital signature, uti-
lizing platforms of data encryption, certificates of a safe con-
nexion, creating secure passwords, utilizing authentication
and access control mechanisms, and so on. The second dimen-
sion, privacy, refers to the process of protecting users’ data
against accidental or voluntary transfer to third people or en-
tities to which users have not actually allowed their data to be
used, modified or destructed (Udo, 2001). Companies could re-
spect their users’ privacy by not providing personal information
to other sites, protecting their anonymity, and requesting users
their consent (Friedman, Kahn & Howe, 2000). Table 3 shows
the items we have used to create the second-order construct of
security in the medium, its description and authors who have
integrated them into their measurement scales exactly or in an
adapted way.
TABLE 3. Proposed instrument for measuring the security in the Internet medium
Nomenclature Items Author/s
Sec-Med1 The firm implements security mechanisms to protect users
Cheung and Lee (2006)
Flavián and Guinalíu (2006a)
Grabner-Kraut and Faullant (2008)
Sec-Med2 The information of a transaction is protected from disturbance during a
connection
Parasuraman, Zeithaml and Malhotra (2005)
Cheung and Lee (2006)
Sec-Med3 It has a safety system of identification of users (service access) Cheung and Lee (2006)
Sec-Med4 The firm do not sell my personal information to other organization without
my permission Cheung and Lee (2006)
Sec-Med5 The firm shows concern for the privacy of its users Cheung and Lee (2006)
Flavián and Guinalíu (2006a)
Sec-Med5 The firm does not disclose users' personal information to others
Gerrard and Cunningham (2003)
Parasuraman, Zeithaml and Malhotra (2005)
Cheung and Lee (2006)
Flavián and Guinalíu (2006a)
Based on the above insights, we propose a third-order construct
of online trust with two second-order dimensions: reliability
(formed by honesty, benevolence and competence) and securi-
ty in the Internet medium (formed by security and privacy).
The measurement scale development
In order to reduce as far as possible the errors of measurement,
the development of the measurement scale was based on as-
sessing the compliance of its psychometric properties. The pro-
cess has been developed in 5 stages: content validity, one-di-
mensionality, reliability and convergent and discriminatory
validity.
Content validity. The first revision to the validity of the
scale is applied to the conceptual content. According to the re-
viewed literature and a group of experts, it has been checked
that the scale reflects all aspects of the term that represents and
considers the context. As a result of this process, a set of 20 to-
tal items has been generated.
One-dimensionality. As the second stage, the scale has
been refined in relation to its dimensionality, using an explor-
atory factor analysis (EFA) and a confirmatory one (CFA).
The first analysis was carried out on each of the 20 items
proposed, applying principal components analysis with Vari-
max rotation. The significant factor loads should be higher than
0.30, following the criterion indicate by Hair, Anderson, Tatham
& Black (1999) that attend to the size of the sample. Results of
the factor loads obtained for analysis in second and third-or-
der exceed the limit. In terms of commonalities, the assessment
shows values above 0.50, so all variables contribute to the ex-
planation of the factor solution obtained. Consequently, we
have generated a total of 5 dimensions, as shown in Table 4.

192
ISSN 0034-7590
ARTICLES | Multilevel and multidimensional scale for online trust
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
TABLE 4. Exploratory analysis of one-dimensionality (second and third-order)
Dimension Item
Second level Third level
Factor loads Commonality Factor loads Commonality
Honesty
Reliab1 0.732 0.658 0.704 0.765
Reliab2 0.803 0.645 0.791 0.816
Reliab3 0.740 0.766 0.709 0.837
Reliab4 0.793 0.676 0.766 0.815
Reliab5 0.591 0.751 0.553 0.758
Benevolence
Reliab6 0.714 0.726 0.711 0.729
Reliab7 0.776 0.819 0.782 0.837
Reliab8 0.803 0.763 0.807 0.803
Reliab9 0.739 0.725 0.750 0.744
Reliab10 0.762 0.618 0.750 0.800
Competence
Reliab11 0.570 0.661 0.538 0.672
Reliab12 0.835 0.819 0.790 0.819
Reliab13 0.829 0.806 0.794 0.814
Reliab14 0.655 0.638 0.632 0.758
Security
Sec-Med1 0.868 0.803 0.843 0.803
Sec-Med2 0.737 0.695 0.751 0.749
Sec-Med3 0.841 0.766 0.797 0.767
Privacy
Seg-Med4 0.931 0.926 0.899 0.928
Sec-Med5 0.838 0.880 0.794 0.882
Sec-Med6 0.922 0.920 0.883 0.922
From the results obtained at the exploratory analysis, we
carried out a confirmatory analysis that allows us to accept or re-
ject the proposed dimensions.
We began the analysis by estimating, using AMOS 7.0, a
first-order model for each of the proposed dimensions. To iden-
tify the security and privacy models, the factor loadings sec-
med1 and sec-med4 have been fixed because they had provid-
ed the highest values in the EFA. We have assigned them the
values that had been registered in this analysis. The initial mod-
els show adjustment values below the acceptable level for the
dimensions: honesty, benevolence and competence (Table 5).
The standardized chi-squared (χ2/df) of the three initial mod-
els was not between 1 and 5, which are the limits recommend-
ed by Hair, Anderson, Tatham and Black (1999). Neither do the
values of RMSEA, NFI, CFI, GFI and AGFI show a good fit. RM-
SEA should be less than 0.08 (Steiger, 1990) and in the mod-
els shows values between 0.202 and 0.090; NFI is acceptable if
it is over than 0,90 (Lévy & Varela, 2003), and results show val-
ues between 0.794 and 0.871; CFI, recommended instead of chi-
square for samples over 100 observations (Lévy & Varela, 2003),
should be close to 1 to reflect a good fit; GFI might be over than
0.9 (Jöreskog & Sörbom, 1986), the first-order model match this
condition and AGFI shows a good fit it is above 0.9 (Jöreskog
& Sörbom, 1986; Hair, Anderson, Tatham & Black. 1999; Lévy
& Varela, 2003), this last criterion does not occur with the ini-
tial dimensions. The modification indices (MI), the oending es-
timates (Hair, Anderson, Tatham & Black, 1999; Luque, 2000)
and the SMC were reviewed, and the results recommend items
reliab1 (in the honesty dimension), reliab6 (benevolence) and
reliab12 (competence) were removed. The identification of the
first-order model of competence has been done in accordance
to the previous indications of the security and privacy scales.
So, we have fixed the reliab13 value. The final first-order models
show very good fit (see Table 5).

193
ISSN 0034-7590
AUTHORS | Maria Jesús López Miguens | Encarnación González Vázquez | Paloma Bernal Turnes
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
TABLE 5. Adjustment fit measures (first, second and third-order)
Dim.
χ2 / df RMSEA NFI CFI GFI AGFI
initial final initial final initial final initial final initial final initial final
FIRST LEVEL
Honesty 4 .033 2 .944 0 .090 0 .072 0 .871 0 .96 0 .896 0 .972 0 .945 0 .980 0 .835 0 .901
Benevol. 5 .651 1 .924 0 .112 0 .050 0 .866 0 .976 0 .884 0 .988 0 .941 0 .991 0 .824 0 .953
Compet. 16 .131 0 .395 0 .202 0 .000 0 .794 0 .996 0 .799 1 .00 0 .907 0 .999 0 .535 0 .993
Security 0 .211 0 .000 0 .997 1 .00 0 .999 0 .993
Privacy 1 .049 0 .011 0 .988 0 .999 0 .994 0 .964
SECOND LEVEL
Reliabil. 3 .260 1 .268 0 .078 0 .027 0 .717 0 .952 0 .778 0 .989 0 .865 0 .979 0 .783 0 .947
Security in
the medium 3 .195 2 .053 0 .077 0 .53 0 .843 0 .930 0 .881 0 .962 0 .923 0 .964 0 .798 0 .893
THIRD LEVEL
Online trust 1 .625 0 .041 0 .860 0 .939 0 .933 0 .893
Furthermore, to guarantee the validity of these results, a bootstrap procedure using 500 random samples was applied. The
results obtained are presented in table 6. As can be seen, all parameters are significant.
TABLE 6. Parameters Bootstrap (first-order). Means and confidence intervals at 90%
Reliab2 Reliab3 Reliab4 Reliab5 Reliab7 Reliab8 Reliab9 Reliab10 Reliab11
Estimate 0.827 0.917 0.888 0.875 0.900 0.911 0.831 0.766 0.727
Lower 0.782 0.870 0.864 0.836 0.872 0.887 0.775 0.719 0.653
Upper 0.879 0.950 0.916 0.912 0.938 0.944 0.880 0.823 0.789
p 0.004 0.004 0.004 0.004 0.004 0.004 0.004 0.004 0.004
Reliab13 Reliab14 Sec-med1 Sec-med2 Sec-med3 Sec-med4 Sec-med5 Sec-med6
Estimate 0.755 0.862 0.851 0.740 0.766 0.951 0.884 0.927
Lower 0.714 0.813 0.772 0.683 0.712 0.928 0.841 0.899
Upper 0.795 0.903 0.888 0.809 0.804 0.970 0.924 0.951
p 0.004 0.004 0.025 0.001 0.011 0.004 0.004 0.004
In the second-order, the initials models proposed to
represent reliability and security in the Internet medium was
re-specified, the items reliab5 (honesty), reliab9 and reliab10
(benevolence), reliab13 (competence) and sec-med4 (security
in the Internet medium) were suppressed.
The review of the parameters (values of the covariance
matrix lower than 2, fit measures and squared multiple correla-
tion (SMC) whose values were between 0.572 and 0.914) of the
proposed third-order model show that the model is good.
Consequently, the model is accepted and integrates five
second-order dimensions (benevolence, honesty, competence,
security and privacy) and two third-order dimensions (reliabil-
ity and security-medium) as shown in the Figure 1. This model
collects all the discussed factors in the conceptual framework.

194
ISSN 0034-7590
ARTICLES | Multilevel and multidimensional scale for online trust
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
Figure 1. Measurement model (third-order) of online trust
Reliab2
Reliab3
Reliab4
Reliab7
Reliab8
Reliab11
Reliab14
Sec_Med1
Sec_Med2
Sec_Med3
Sec_Med5
Sec_Med6
Honest
e_reliab2e_honest
e_reliab
e_sec-med
e_benev
e_compet
e_sec
e_priv
e_reliab3
e_reliab4
e_reliab7
e_reliab8
e_reliab11
e_reliab14
e_sec-med1
e_sec-med2
e_sec-med3
e_sec-med5
e_sec-med6
Benev
Compet
Online Trust
Sec
Sec-Med
Reliab
Priv
Consequently, results suggest the multidimensional and
multilevel character of the construct of online trust, and the ac-
ceptance of the proposed dimensions.
Reliability. In order to confirm the reliability and consis-
tency of the used indicators in each level of the scale, we use
five measures: total item correlation, correlation inter-items,
Cronbach alpha coecient, composite reliability and AVE. Re-
sults are shown in Table 7.
All Cronbach’s alpha coecients exceed the minimum
level set by 0.70 and it is not possible to improve the alpha re-
moving any item. Those results show a high degree of internal
consistency. On the other hand, the reliability measure based
on the analysis of inter-item correlations is not strictly complied
(in the third-order construct correlations are between 0.258 and
0.832, in some cases they are below the limit of 0.3 established).
After checking, the involved items were not removed from the
analysis because their elimination did not improve the value of
Cronbach’s alpha (Alén, 2003). All item-total correlations exceed
the value of 0.50. With regard to the composite reliability and av-
erage variance extracted (AVE), statistical values significantly ex-
ceed in all cases the limit recommended of 0.7 (Luque, 2000)
and 0.5 (Bagozzi, Yi & Phillips, 1991), respectively.

195
ISSN 0034-7590
AUTHORS | Maria Jesús López Miguens | Encarnación González Vázquez | Paloma Bernal Turnes
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
TABLE 7. Reliability (exploratory and confirmatory level) of the scales (first, second and third-order)
Cronbach's alpha Alfa possibility
improves Inter-Item Item-Total Composite
reliability
Variance
extracted
FIRST LEVEL
Honest 0 .904 NO ✔ 97 .14 91 .90
Benev 0 .908 NO ✔ ✔ 95 .71 91 .78
Compet 0 .757 NO ✔ ✔ 93 .16 87 .30
Sec 0 .823 NO ✔ ✔ 95 .83 88 .49
Priv 0 .905 NO ✔ ✔ 96 .33 92 .93
SECOND LEVEL
Reliab 0 .923 NO ✔ ✔ 98 .84 92 .42
Sec-Med 0 .872 NO ✔ ✔ 98 .22 91 .75
THIRD LEVEL
Online trust 0 .914 NO (0 .258-0 .832) ✔ 99 .44 93 .71
Convergent validity. The measure of convergent validity
estimates the extent to which the indicators of a construct or
scale contribute to measure this construct. According to Lévy
(2001), the factor loads of each indicator should be higher than
0.75. The results of the analysis (Tables 8 and 9) allow us to con-
firm the convergent validity.
Discriminant validity. Discriminant validity measures the
level of disagreement between two concepts or constructs (Hair,
Anderson, Tatham & Black. 1999). (Three tests were employed
for testing empirically the discriminant validity (Table 10). The
first test has an exploratory character and consists in assessing
the correlations between constructs. If correlations have a value
higher than 0.8 (Hair, Anderson, Tatham & Black. 1999), (it may
indicate that the variables measure a similar concept, although
this must be checked from a confirmatory perspective. Two of
the ten measured correlations between pairs of the second-or-
der constructs have values around the limit: honesty and com-
petence (0.83), and benevolence and competence (0.82). The
following methods used have a confirmatory character. The first
method, previously outlined by Fornell and Larcker (1981), con-
sists of verifying that the square correlation between each pair
of factors of a construct should be smaller than the variance ex-
tracted of their respective constructs. All of the pairs studied ful-
fil the condition, this demonstrates sucient discriminant valid-
ity. Third, we applied the procedure described by Anderson and
Gerbing (1988), so we calculate the confidence intervals of the
correlation between the constructs and verify none of them con-
tains the unit. This fact has also been contrasted; therefore, the
discriminant validity of the measurement model is confirmed.
TABLE 8. Convergent validity for the first-order scale
Dim. HONEST BENEV COMPET
Item Reliab2 Reliab3 Reliab4 Reliab7 Reliab8 Reliab11 Reliab14
Factor load 0 .859 0 .929 0 .881 0 .956 0 .902 0 .855 0 .757
Dim. SEC-MED
Item Sec-Med1 Sec-Med2 Sec-Med3 Sec-Med5 Sec-Med6
Factor load 0 .855 0 .798 0 .813 0 .952 0 .879

196
ISSN 0034-7590
ARTICLES | Multilevel and multidimensional scale for online trust
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
TABLE 9. Convergent validity for the second and third-order scales
SECOND-ORDER THIRD-ORDER
Dim. Reliability Sec-Med Online Trust
Item Honest Benev Compet Sec Priv Reliab Sec-Med
Factor load 0 .900 0 .890 0 .956 0.825 0 .889 0 .762 0 .777
TABLE 10. Discriminant validity measures
Constructs Correlation Squared Correlation Variance Extracted Confidence Intervals
SECOND-ORDER
Honest-Benev 0 .79 0 .624
Honest: 0 .919
Benev: 0 .918
Compet: 0 .873
Sec: 0 .885
Priv: 0 .929
(0 .612-0 .988)
Honest-Compet 0 .83 0 .688 (0 .618-0 .982)
Honest-Sec 0 .43 0 .185 (0 .333-0 .537)
Honest-Priv 0 .44 0 .193 (0 .331-0 .555)
Benev-Compet 0 .82 0 .672 (0 .602-0 .998)
Sec- Benev 0 .31 0 .096 (0 .189-0 .441)
Priv-Benev 0.39 0 .152 (0 .243-0 .551)
Compet-Sec 0 .48 0 .230 (0 .37-0 .59)
Compet-Priv 0 .51 0 .260 (0 .387-0 .643)
Sec-Priv 0 .72 0 .518 (0 .597-0 .857)
THIRD-ORDER
Reliab-Sec-Med 0 .59 0 .348 Reliab: 0 .924
Sec-Med: 0 .918 (0 .47-0 .714)
For all these reasons, we accept that the results obtained from
the analysis satisfy the psychometric characteristics for the pro-
posed scale.
CONCLUSIONS AND MANAGERIAL
IMPLICATIONS
The aim of this study is to develop a scale to measure the trust
of users in the online banking, to expand the current concep-
tualizations and to use it in future research. Compared to the
found scales in previous studies, the developed scale contrib-
utes to the understanding of a concept that has been recognized
as highly complex (Cheung & Lee, 2006) and very important in
the electronic context (Gefen, Karahanna & Straub, 2003; Ge-
fen & Straub, 2004; Riegelsberger, Sasse & McCarthy, 2005). To
advance in the literature in which there is a lack of uniformity in
the conceptualization and dimensionality with respect to this
construct, we have developed a measure model that integrates
a general dimension of trust and a specific dimension of the In-
ternet channel.
Particularly, this paper presents two major contribu-
tions. First, we have developed a third-order scale for online
trust in banking that shows good results in terms of dimen-
sionality, reliability, and convergent and discriminant valid-
ity. In the literature, this variable has been conceptualized
from both one-dimensional and multidimensional perspec-
tive (Grabner-Kräuter & Faullant, 2008), but this last option
is the most investigated. Most researchers have proposed a
second-order factor model (for example, Flavián & Guinalíu,
2006a; Battacherjee, 2002) but we have not found any study
that proposes a third-order construct. In our study we have
confirmed the multilevel and multidimensional character
proposed of online trust. Thus, it is designated a third-order
construct, divided into two second-order factors: reliability of
online seller, and security and privacy policies on the Inter-
net. These factors raise five sub-dimensions that participate
in the evaluation of users about the online trust of the com-

197
ISSN 0034-7590
AUTHORS | Maria Jesús López Miguens | Encarnación González Vázquez | Paloma Bernal Turnes
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
pany. Reliability is explained through honesty (related to us-
ers’ belief that seller fulfils the promise he/she assumes and
the accuracy of the provided information), benevolence (re-
lated to the willingness of the company that avoids opportu-
nistic behaviour and seeks the users’ welfare), and compe-
tence (related to the firm’s ability and knowledge to support
its commercial offer). Security in the medium consists of the
dimensions of security (linked to security systems installed
that prevent or mitigate possible errors and fraud during the
electronic connection) and privacy (referred to the applica-
tion and transmission of practices in order to protect the
privacy of the personal data that are transferred during the
transaction).
The second contribution is the inclusion of the dimension
of channel security in the scale of online trust, since we have
not found any study that has done it previously in the context
of Internet banking. So, we consider that the consumer search-
es not only trust in the business (Harris & Goode, 2004; Cheung
& Lee, 2006) but also trust in the Internet channel (Kini & Coo-
binch, 1998; Novak, Homan & Yung, 2000). Most of research-
ers use general factors that can be applied to any environment
but not specifically from the electronic environment. From a re-
view of the specific literature, the main dimensions of online
trust are: honesty, competence, and benevolence (for instance,
Torres, Manzur, Olavarrieta and Barra (2009), in the Latin Amer-
ica context and Casaló, Flavián and Guinalíu (2007) in the Span-
ish one). For their part, Grabner-Kraüter and Faullant (2008) in
Austria, consider that “the technology itself has to be consid-
ered as an object of trust and they have been limited to measur-
ing Internet trust for the online banking through four items relat-
ed to perceived reliability and predictability of the Internet, and
the willingness to depend on the Internet. In this context, oth-
er authors such us Casaló, Flavián and Guinalíu (2007) and Fla-
vián and Guinalíu (2006a) have taken into account security and
privacy as variables that are part of a second-order construct
that influences in the online trust, but they do not incorporate
them as a dimension. Neither do Aldas, Ruiz, Sanz and Lassala
(2011) consider channel security as a dimension of trust; these
authors consider it as a second-order construct called perceived
risk. Other authors, such as Sohn and Tadisina (2008), incorpo-
rate the variable trust in the e-service quality scale. Neverthe-
less, we should point out that the privacy dimension has a rec-
ognized limitation.
For management purposes, the obtained results suggest
that bank managers should invest in providing reliability and se-
curity in the Internet channel.
Particularly, if these companies want to gain the trust
of their users, they should be, first, honest in their actions. In
our context of study, they could take some measures, such as
to instantly update the customers’ information that it would be
an accurate reflection of reality, to provide transparency of the
rates that will be applied, and to make truthful and accurate
communications.
Second, they must also assume a benevolent character
when making business decisions. For instance, they could de-
velop websites with useful information and a simple and intu-
itive navigation structure that does not lead to mistake; make
communications that do not omit relevant information to the de-
cision making process; inform accurately and in an understand-
able language about the potential risks, restrictions and con-
sequences; or enable a common space in the website where
users can express their opinions and comments (Cheung & Lee,
2006), it would also improve the decision making. These mea-
sures might imply, to some extent, that the balance of power
would be equilibrated, by building a relationship based on co-
operation with the consumer.
Third, our results also suggest managers must transmit
to users that the firm is competent. To achieve it, they could
use a quality website with a professional appearance (Cheung
& Lee, 2006) since it might reduce the disadvantage of imper-
sonality that the own website has (Yousafzai, 2005). Because,
as this author suggests, it provides “a solid feel, and clear nav-
igation conveys respect for customers and an implied promise
of good service”. Cheung and Lee (2006) advise that profes-
sional appearance involves: ease of navigation, correct gram-
mar and spelling, accurate and complete information, and a
good graphic design. Moreover, they could oer financial prod-
ucts and/or services more appropriate to the needs of users,
since they may use the better knowledge of the customer that
online channel gives.
Forth, in order to response to insecurity, the firm could
employ dierent mechanisms that allow the authentication of
each partner and the safety access (for example, the digital
signature, key authentication, coordinate cards, electronic ID,
certificates of a safe connection, secure passwords and so on);
making an explicit mention in the website about the use of se-
curity elements, as Mukherjee and Nath (2003) or Cheung and
Lee (2006) suggest or; using certificates such as TRUSTe, BB-
BOnline, Verisign, and so on, since, as Benassi (1999) suggest,
they lead online customers to have more willingness to pro-
vide personal information (Kuchinskas, 2003). It could be use-
ful also to send instant communications to the user when an
online connection has been done, indicating hour, day and ac-
cess channel.
Finally, regarding privacy, managers could adopt sev-
eral measures to treat appropriately all private data that are

198
ISSN 0034-7590
ARTICLES | Multilevel and multidimensional scale for online trust
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
collected in the financial relationship. For instance, they
could create a specific privacy policy (Wu, Huang, Yen & Pop-
ova, 2012). This policy should allow to the consumer to con-
trol his/her personal information all the time (Mukherjee &
Nath, 2003), and, this results in the recognition that he/she
has the property of the data that are in the Internet (Yousafzai,
Pallister, Foxall & Gordon, 2003). They could justify, in this pri-
vacy policy, what type of data will be required to complete
the transaction, how data will be used, which entity will man-
age them, and which entity should be contacted whether user
want to rectify or cancel his/her registration in the database;
and whether data would be transferred or sold. And/or they
could communicate the privacy policy to the user (Yousafzai,
Pallister, Foxall & Gordon, 2003).
LIMITATIONS
The major limitation of the study is the composition of the
sample, particularly, the sampling procedure that has been
selected: non probabilistic and for convenience (snowball).
Despite not being a method with good statistical properties,
AIMC (2008) qualifies this method as appropriate to the elec-
tronic context because of the impossibility of accessing to a
suitable framework. Nevertheless, this situation should be
considered regarding the generalizability of the results, its
inference, and its prediction about the population. A second
limitation is the possible omission of relevant dimension and
indicators when approximate the measurement models, such
as the failure to include a broader set of indicators in the con-
struct of first-order privacy that, explicitly, picks up the entire
concept. Accordingly, we suggest the need to develop new
research containing the precise indicators conceptually. We
also recognize the lack of verification of the nomological va-
lidity as a limitation. In subsequent studies, this could be re-
viewed through a structural model in which quality of service
is inserted as a precursor variable of online trust (Sultan &
Mooraj, 2001; Harris & Goode, 2004) or satisfaction (Reichheld
& Schefter, 2000; Shankar, Smith & Rangaswamy, 2003; Harris
& Goode, 2004) and loyalty (Luarn & Lin, 2005; Chouk & Per-
rien, 2004; Harris & Goode, 2004) as consequential variables
of online trust. Another limitation of this study is its nation-
al scope, Spain. Additional research might use other coun-
tries for greater generalizability. Finally, one limitation is the
cross-sectional research design employed that leads to con-
clude in a specific situation and environmental circumstanc-
es, but it may not be applicable under different conditions.
REFERENCES
Aimc (Asociación para la Investigación de Medios de Comunicación).
(2008). Navegantes en la Red. 10ª Encuesta AIMC a Usuarios de Inter-
net. Retrieved from: www.aimc.es.
Alcaide, J. C. & Soriano, C. (2005). Marketing bancario relacional. Mc-
Graw-Hill Interamericana de España, S.A.U. Madrid.
Aldas-Manzano, J, Ruiz-Mafe, C, Sanz-Blas, S. & Lassala-Navarré, C.
(2011). Internet banking loyalty: evaluating the role of trust, satisfac-
tion, perceived risk and frequency of use. The Service Industries Jour-
nal, 31(7), 1165-1190.
Alén, M. E. (2003). Análisis de la calidad de servicio percibida en los
establecimientos termales: conceptualización, medición y relación con
otras variables de marketing. Tesis doctoral en Marketing turístico. Uni-
versidad de Vigo.
Anderson, J. C. & Gerbing, D. W. (1988). Structural equation modeling in
practice: a review and recommended two-step approach. Psychological
Bulletin, 103 (3), 411-423.
Anderson, J. C. & Narus, J. A. (1990). A model of distributor firm and man-
ufacturer firm working partnerships. Journal of Marketing, 54(1), 42-58.
Bagozzi, R. P, YI, Y. & Phillips, L. W. (1991). Assessing construct validity in
organizational research. Administrative Science Quarterly, 36(3), 421-458.
Belanger, F, Hiller, J. S. & Smith, W. J. (2002). Trustworthiness in elec-
tronic commerce: the role of privacy, security, and site attributes. Jour-
nal of Strategic Information Systems, 11(3-4), 245-270.
Benassi, P. (1999). TRUSTe: an online privacy seal program. Communica-
tions of the ACM, 42(2), 56–59.
Bhattacherjee, A. (2002). Individual trust in online firm: scale devel-
opment and initial test. Journal of Management Information Systems,
19(1), 211-241.
Bitner, M. J, Zeithaml, V. A. & Gremler, D. D. (2010). Technology’s impact
on the gaps model of service quality. In Maglio Paul P, Kieliszewski Cher-
yl A, & Spohrer James C. (Eds). Handbook of Service Science: Research
and Innovations in the Service Economy. New York: Springer, pp. 197-
218. DOI 10.1007/978-1-4419-1628-0_10.
Blomqvist, K. (1997). The many faces of trust, Scandinavian Journal of
Management, 13(3), 271-286.
Bravo, R, Montaner, T. & Pina, J. M. (2007). La imagen corporativa de
las entidades financieras: formación e impacto en el consumidor. XIX
Encuentro de Profesores Universitarios de Marketing, Vigo. Ed. ESIC,
Madrid, p. 202.
Carbó, S. (2004). Diez hechos estabilizados del sector bancario en Es-
paña (1980-2004). Papeles de Economía Española, 100(1), 232-245.
Casaló, L. V, Flavián, C. & Guinalíu, M. (2007). The role of security, pri-
vacy, usability and reputation in the development of online banking.
Online Information Review, 31(5), 583-603.
Cheung, M. K. & Lee, K. O. (2006). Understanding consumer trust in in-
ternet shopping: a multidisciplinary approach. Journal of the American
Society for Information Science and Technology, 57(4), 479-492.
Chouk, I. & Perrien, J. (2004). Consumer trust towards an unfamiliar web
merchant: a signaling approach. Actas de la 33ª EMAC Conference, Mur-
cia, mayo, pp. 1-6.
Coulter, K. & Coulter, R. (2002). Determinants of trust in a service pro-
vider: the moderating role of length of relationship. Journal of Services
Marketing, 16(1), 35-50.

199
ISSN 0034-7590
AUTHORS | Maria Jesús López Miguens | Encarnación González Vázquez | Paloma Bernal Turnes
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
Crosby, L. A, Evans, K. R, & Cowles, D. (1990). Relationship quality in
services selling: an interpersonal influence perspective. Journal of Mar-
keting, 54(3), 68-81.
Dabholkar, P. A. (1996). Consumer evaluations of new technology-based
self-service options: an investigation of alternative models of service
quality. International Journal of Research in Marketing, 13(1), 29-51.
Das, T. K. & Teng, B. S. (2004). The risk-based view of trust: a conceptual
framework, Journal of Business and Psychology, 19(1), 85-116.
Doney, P. M. & Cannon, J. P. (1997). An examination of the nature of trust
in buyer-seller relationships. Journal of Marketing, 61(2), 35-51.
Flavián, C. & Guinalíu, M. (2007). Un análisis de la influencia de la con-
fianza y del riesgo percibido sobre la lealtad a un sitio web: el caso de
la distribución de servicios gratuitos. Revista Europea de Dirección y
Economía de la Empresa, 16(1), 159-178.
Flavián, C. & Guinalíu, M. (2006a). Consumer trust, perceived security
and privacy policy. Three basic elements of loyalty to a web site. Indus-
trial Management & Data Systems, 106(5), 601-620.
Flavián, C. & Guinalíu, M. (2006b). La confianza y el compromiso en las rel-
aciones a través de Internet. Dos pilares básicos del marketing estratégico
en la red. Cuadernos de Economía y Dirección de Empresa, (29), 133-160.
Flavián, C, Guinalíu, M. & Torres, E. (2006). How bricks-and-mortar at-
tributes aect online banking adoption. International Journal of Bank
Marketing, 24(6), 406-423.
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models
with unobservable variables and measurement error. Journal of Market-
ing Research, 18(1), 39-50.
Friedman, B, Kahn, P. & Howe, D. C. (2000). Trust online. Communica-
tions of the ACM, 43(12), p. 34-40.
Ganesan, S. (1994). Determinants of long-term orientation in buyer-sell-
er relationships. Journal of Marketing, 58(2), 1-19.
Garrido, A. (2007). Sistema financiero. In García, J. L, & Myro, R. (Dir.). Lec-
ciones de Economía Española. Editorial Aranzadi, S. A. (8ª edición), Navarra.
Gefen, D. (2000). E-commerce: the role of familiarity and trust. The Inter-
national Journal of Management Science, 28(6), 725-737.
Gefen, D, Karahanna, E. & Straub, D. W. (2003). Trust in TAM in online
shopping: an integrated model. MIS Quarterly, 27(1), 51-90.
Gefen, D. & Straub, D. W. (2004). Consumer trust in B2C e-Commerce
and the importance of social presence: experiments in e-Products and
e-Services. Omega – The International Journal of Management Science,
32(6), 407-424.
Gerrard, P. & Cunningham, J. B. (2003). The diusion of Internet banking
among Singapore consumers. The International Journal of Bank Market-
ing, 21(1), 16-28.
Geyskens, I, Steenkamp, J. B. & Kumar, N. (1998). Generalizations about
trust in marketing channel relationships using meta-analysis Interna-
tional Journal of Research in Marketing, 15(3), 223-248.
Geyskens, I, Steenkamp, J-B. E. M. & Kumar, N. (1999). A meta-analysis
of satisfaction in marketing channel relationships. Journal of Marketing
Research, 36(2), 223-238.
Grabner-Kraüter, S. (2002). The role of consumers trust in online shop-
ping, Journal of Business Ethics, 39(1-2), 43-50.
Grabner-Kraüter, S. & Faullant, R. (2008). Consumer acceptance of inter-
net banking: the influence of internet trust. International Journal of Bank
Marketing, 26(7), 483-504.
Grewal, D, Lindsey-Mullikin, J. & Munger, J. (2003). Loyalty in e-tailing: a
conceptual framework. Journal of Relationship Marketing, 2(3-4), 31-49.
Gundlach, G. & Murphy, P. E. (1993). Ethical and legal foundations of
relational marketing exchanges. Journal of Marketing, 57(4), 35-46.
Hair, J. F, Anderson, R. E, Tatham, R. L. & Black, W. C. (1999). Análisis
multivariante. Prentice Hall. Madrid.
Harridge-March, S. (2006). Can the building of trust overcome consumer
perceived risk online. Marketing Intelligence & Planning, 24(7), 746-761.
Harris, L. C. & Goode, M. H. (2004). The four levels of loyalty and the piv-
otal role of trust: a study of online service dynamics. Journal of Retailing,
80(2), 139-158.
Jarvenpaa, S. L, Tractinsky, N. & Vitale, M. (2000). Consumer trust in an
Internet Store. Information Technology and Management, 1(1-2), 45-71.
Jöreskog, K. G. & Sörbom, D. (1986). Advances in factor analysis and
structural equation models. Ed. Abt Associates. Cambridge.
Keeney, R. L. (1999). The value of internet commerce to the customer.
Management Science, 45(4), 533-542.
Kini, A. & Choobinech, J. (1998). Trust in electronic commerce: definition and
theoretical considerations. In: Proceeding of the thirty-first Hawaii Interna-
tional Conference on System Sciences (HICSS), Maui, HI, January, pp. 51-61.
Kline, R. B. (2011). Principles and practice of structural equation model-
ing, Third Edition, 3rd ed. The Guilford Press. New York..
Kolsaker, A. & Payne, C. (2002). Engendering trust in e-Commerce: a
study of gender-based concerns. Marketing Intelligence & Planning,
20(4), 206-214.
Kuchinskas, S. (2003). Trust issues loom over E-commerce. Internet-
news.com. Retrieved December 2, 2003, from http://boston.internet.
com/news/article.php/3115091
Larzelere R. E. & Huston, T. L. (1980). The dyadic trust scale: toward un-
derstanding interpersonal trust in close relationships. Journal of Mar-
riage and the Family, 42(3), 595-604.
Lee, M. K. O. & Turban, E. (2001). A trust model for consumer Internet
shopping International Journal of Electronic Commerce, 6(1), 75-91.
Lévy, J-P. (2001). Modelización y programación estructural con AMOS.
Instituto Superior de Técnicas y Prácticas Bancarias. Madrid.
Lévy, J-P, & Varela, J. (2003). Análisis multivariable para las Ciencias So-
ciales. Pearson Educación, S.A. Madrid.
Luarn, P. & Lin, H-H. (2005). Toward an understanding of the behavioral inten-
tion to use mobile banking. Computers in Human Behavior, 21(6), 873-891.
Luque, T. (2000). Técnicas de análisis de datos en investigación de mer-
cados. Pirámide. Madrid.
Meuter, M. L, Ostrom, A. L, Roundtree, R. I. & Bitner, M. J. (2000). Self-ser-
vice technologies: understanding customer satisfaction with technolo-
gy-based service encounters. Journal of Marketing, 64(3), 50-64.
Mukherjee, A. & Nath, P. (2003). A model of trust in online relationship
banking. International Journal of Bank Marketing, 21(1), 5-15.
Novak, T. P, Homan, D. L. & Yung, Y. (2000). Measuring the customer
experience in online environments: a structural modeling approach.
Marketing Science, 19 (1), 22-42.
Oliver, D, Livermore, C. R. & Farag, N. A. (2009). An explanatory model
of self-service on the internet. In Oliver, D., Livermore, C, & Sudweeks,
F, (Eds.). Self-service in the internet age: expectations and experiences.
Springer. New York, pp. 257-274.

200
ISSN 0034-7590
ARTICLES | Multilevel and multidimensional scale for online trust
© RAE | São Paulo | V. 54 | n. 2 | mar-abr 2014 | 187-200
Parasuraman, A, Zeithaml, V. & Malhotra, A. (2005). E-S-QUAL: A multi-
ple-item scale for assessing electronic service quality. Journal of Service
Research, 7(3) 213-233.
Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: in-
tegrating trust and risk with the technology acceptance model. Interna-
tional Journal of Electronic Commerce, 7(3), 101-134.
Pavlou, P. A. & Fygenson, M. (2006). Understanding and predicting elec-
tronic commerce adoption: an extension of the theory of planned behav-
ior. MIS Quarterly, 30(1), 115-143.
Pérez, F. & Maudos, J. (2001). La eficiencia del sector bancario español
en el contexto Europeo. Economistas, (89), 63-70.
Ramón, M. A. & Martín, E. (2007). Estudio del desarrollo de la confianza
considerando diferentes contextos de riesgo. XIX Encuentro de Profe-
sores Universitarios de Marketing, Vigo. Ed. ESIC. Madrid, pp. 180.
Ranganathan, C. & Ganapathy, S. (2002). Key dimensions of business to
consumer web sites. Information & Management, 39(6), 457-465.
Reichheld, F. F. & Schefter, P. (2000). E-loyalty: your secret weapon on
the web. Harvard Business Review, 78(4), 105-113.
Riegelsberger, J, Sasse, A. M. & McCarthy, J.D. (2005). The mechanics
of trust: a framework for research and design. International Journal of
Human-Computer-Studies, 62(30), 381-422.
Rotchanakitumnuai, S. & Speece, M. (2003). Barriers to internet banking
adoption: a qualitative study among corporate customers in Thailand.
International Journal of Bank Marketing, 21(6), 312-323.
Roy, M, Dewit, O. & Aubert, B. (2001). The impact of interface usability
on trust in web retailers. Internet Research, 11(5) 388-398.
Ruiz, A. V, Izquierdo, A. & Calderón, E. (2007). Actitudes hacia internet,
riesgo percibido y confianza: su influencia sobre la compra de per-
noctaciones hoteleras. In: Conocimiento, innovación y emprendedores:
camino al futuro. Ayala Calvo, J. C (Coord). Ed. Universidad de La Rioja.
España.
Shankar, V, Smith, A. K. & Rangaswamy, A. (2003). Customer satisfac-
tion and loyalty in online and oine environments, International Journal
of Research in Marketing, 20(2), 153-175.
Sohn, C. & Tadisina, S. K. (2008). Development of e-service quality
measure for internet-based financial institutions. Total Quality Manage-
ment, 19(9), 903-918.
Steiger, J. H. (1990). Structural model evaluation and modification: an
interval estimation approach. Multivariate Behavioral Research, 25(2),
173-180.
Suh, B. & Han, I. (2003). The impact of customer trust and perception of
security control on the acceptance of electronic commerce. International
Journal of Electronic Commerce, 7(3), 135-161.
Sultan, F. & Mooraj, H. A. (2001). Designing a trust-based e-business
strategy. Marketing Management, 10(4), 40-44.
Torres, E, Manzur, E, Olavarrieta, S. & Barra, C. (2009). Análisis de la rel-
ación confianza-compromiso en la banca en internet. Revista Venezola-
na de Gerencia, 14(47), 371-392. 
Truste. (2003). Identity theft and spam will deter online shopping this
holiday season. Press release of Truste. Cited in: Flavián, C, & Guinalíu,
M. (2006a). Consumer trust, perceived security and privacy policy.
Three basic elements of loyalty to a web site. Industrial Management &
Data Systems, 106(5), 601-620.
Udo, G. (2001). Privacy and security concerns as major barriers for
e-commerce: a survey study. Information Management & Computer Se-
curity, 9(4), 165-174.
Walczuch, R. & Lundgren, H. (2004). Psychological antecedents of insti-
tution-based consumer trust in e-retailing. Information & Management,
42(1), 159-177.
Wu, K. W, Huang, S. Y, Yen, D. C. & Popova, I. (2012). The eect of online
privacy policy on consumer privacy concern and trust. Computers in Hu-
man Behavior, 28(3), 889-897.
Yoon, S. J. (2002). The antecedents and consequences of trust in on-line
purchase decisions. Journal of Interactive Marketing, 16(2), 47-63.
Yousafzai, S. Y. K. (2005). Internet banking in the UK: a customer be-
haviour perspective. Doctoral dissertation. Cardi University.
Yousafzai, Y, Pallister, G, Foxall, G. & Gordon, R. (2003). A proposed
model of e-trust for electronic banking. Technovation, 23(11), 847-860.