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Trust in Technology: Its Components and Measures
Trust in a Specific Technology: An Investigation of its Components
and Measures
D. H. MCKNIGHT
Eli Broad College of Business, Michigan State University, U. S. A
M. CARTER
College of Business and Behavioral Sciences, Clemson University, U. S. A.
J. B. THATCHER
College of Business and Behavioral Sciences, Clemson University, U. S. A.
and
P.F. CLAY
College of Business, Washington State University, U. S. A.
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1. INTRODUCTION
Trust is commonly defined as an individual’s willingness to depend on another party because of the characteristics
of the other party [Rousseau et al. 1998]. This study concentrates on the latter half of this definition, the
characteristics or attributes of the trustee, usually termed ‘trust’ or ‘trusting beliefs.’ Research has found trust to be
not only useful, but also central [Golembiewski (& 89:;< "
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The primary difference between this study and prior studies is that we focus on trust in the technology itself
instead of trust in people, organizations, or human surrogates. The purpose of this study is to develop trust in
technology definitions and measures and to test how they work with a nomological network. This helps address the
problem that IT trust research focused on trust in people has not profited from additionally considering trust in the
technology itself. Just as the Technology Acceptance Model’s (TAM) perceived usefulness and ease of use
concepts directly focus on the attributes of the technology itself, so our focus is on the trust-related attributes of the
technology itself. #%"
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what it is about technology that makes the technology itself trustworthy, irrespective of the people and human
structures that surround the technology. This focus should yield new insights into the nature of how trust works in a
technological context.
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surrounding trust in technology? What is the inuence of trust in technology on individuals’
post-adoptive technology use behaviors?
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Trust in Technology: Its Components and Measures
2. THEORETICAL FOUNDATION
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Different Types of Trust
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Contextual Condition
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Trust in People Trust in Technology
Contextual Condition Risk, Uncertainty, Lack of total control Risk, Uncertainty, Lack of total user control
Object of Dependence People—in terms of moral agency and both volitional
and non-volitional factors
Technologies—in terms of amoral and non-volitional
factors only
Nature of the Trustor’s
Expectations
(regarding the Object of
Dependence)
1. Do things for you in a competent way. (ability
[Mayer et al. 1995])
1. Demonstrate possession of the needed functionality
to do a required task.
2. Are caring and considerate of you; are benevolent
towards you; possess the will and moral agency to
help you when needed. (benevolence [Mayer et al.
1995])
2. Are able to provide you effective help when needed
(e.g., through a help menu).
3. Are consistent in 1.-2 above. (predictability
[McKnight et al. 1998])
3. Operate reliably or consistently without failing.
Object of Dependence
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Competence vs. Functionality Q R
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Note that the above expectations are perceptual, rather than objective, in nature. Having delimited a role for the
knowledge-based trust in technology construct and described similarities and differences between trust in people and
trust in technology, we turn to developing definitions of different types of trust in technology. In each case, the trust
in technology definition corresponds to a trust in people definition in order to be based on the trust literature.
Trust in Technology: Its Components and Measures
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Trust in People Trust in Technology
Study Label Definition Label Definition
General Trusting Beliefs in People and Technology
Mayer et
al. 1995
Propensity to
trust
A general willingness to trust others. 1. Propensity to
Trust General
Technology
The general tendency to be willing to depend
on technology across a broad spectrum of
situations and technologies.
McKnight
et al. 1998
Disposition to
trust
[The] extent [to which one] demonstrates a
consistent tendency to be willing to
depend on others across a broad spectrum
of situations and persons.
McKnight
et al. 1998
Faith in
humanity
Others are typically well-meaning and
reliable.
2. Faith in General
Technology
One assumes technologies are usually
consistent, reliable, functional, and provide
the help needed.
McKnight
et al. 1998
Trusting stance Irrespective of whether people are reliable
or not, one will obtain better interpersonal
outcomes by dealing with people as
though they are well-meaning and reliable.
3. Trusting Stance-
General
Technology
Regardless of what one assumes about
technology generally, one presumes that one
will achieve better outcomes by assuming the
technology can be relied on.
Trusting Beliefs in a Context or Class of Technologies
McKnight
et al. 1998
Situational
Normality
The belief that success is likely because
the situation is normal, favorable, or well-
ordered.
4. Situational
Normality-
Technology
The belief that success with the specific
technology is likely because one feels
comfortable when one uses the general type
of technology of which a specific technology
may be an instance.
McKnight
et al. 1998
Structural
Assurance
The belief that success is likely because
contextual conditions like promises,
contracts, regulations and guarantees are in
place.
5. Structural
Assurance-
Technology
The belief that success with the specific
technology is likely because, regardless of the
characteristics of the specific technology, one
believes structural conditions like guarantees,
contracts, support, or other safeguards exist in
the general type of technology that make
success likely.
Trust in Specific Trustees or Technologies
Mayer et
al. 1995
Trust Reflects beliefs that the other party has
suitable attributes for performing as
expected in a specific situation...
irrespective of the ability to monitor or
control that other party.
6. Trust in a
specific
technology
Reflects beliefs that a specific technology has
the attributes necessary to perform as
expected in a given situation in which
negative consequences are possible.
Mayer et
al. 1995
Factor of
Trustworthiness:
Ability
That group of skills, competencies, and
characteristics that enable a party to have
influence within some specific domain.
7. Trusting belief-
specific
technology-
Functionality
The belief that the specific technology has the
capability, functionality, or features to do for
one what one needs to be done.
McKnight
and
Chervany
2001-2002
Trusting Belief -
Competence
One has the ability to do for the other
person what the other person needs to have
done. The essence of competence is
efficacy.
Mayer et
al. 1995
Factor of
Trustworthiness:
Benevolence
The extent to which a trustee is believed to
want to do good to the trustor, aside from
an egocentric profit motive.
8. Trusting belief-
specific
technology-
Helpfulness
The belief that the specific technology
provides adequate and responsive help for
users.
McKnight
and
Chervany
2001-2002
Trusting Belief -
Benevolence
One cares about the welfare of the other
person and is therefore motivated to act in
the other person’s interest….does not act
opportunistically toward the other...
McKnight
and
Chervany
2001-2002
Trusting Belief -
Predictability
One’s actions are consistent enough that
another can forecast what one will do in a
given situation.
9. Trusting belief-
specific
technology-
Reliability
The belief that the specific technology will
consistently operate properly.
Mayer et
al. 1995
Factor of
Trustworthiness:
Integrity
The extent to which a trustee adheres to a
set of principles that the trustor finds
acceptable.
3. DEFINITIONS AND RESEARCH MODEL
Rooted in the trust in people definitions offered by Mayer et al. [1995] and McKnight et al. [1998] (Table II), we
operationalize trust in technology constructs as components of three sets of concepts: a) propensity to trust general
technology b) institution-based trust in technology, a structural concept, and c) trust in a specific technology,
Trust in Technology: Its Components and Measures
referring to a person’s relationship with a particular technology (e.g., Microsoft Excel). The trust literature suggests
a causal ordering among trust constructs, such that one’s propensity to trust directly influences institution-based trust
and indirectly shapes trust in a specific technology [McKnight and Chervany 2001-2002]. Moreover, given their
specificity, we believe (differing from McKnight and Chervany) that trust in a specific technology should fully
mediate more general constructs’ influence on behavior. To evaluate trust’s nomological net, we examine trust in
technology constructs’ interrelationships as well as their relationship with two post adoption outcomes: a) intention
to explore and b) deep structure use (see Fig. 1). This also differs from the McKnight and Chervany model.
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performing as expected in & [Mayer, et al. 1995].
McKnight, et al. defined trusting beliefs in people as a perception that another “person is benevolent, competent,
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rusting beliefs in a specific technology is reflected in three beliefs: functionality, helpfulness, and
reliability. A) Functionality refers to whether one expects a technology to have the capacity or capability to
complete a required task (see Table II, entry 7). B) Helpfulness excludes moral agency and volition (i.e., will) and
refers to a feature of the technology itself—the help function, i.e., is it adequate and responsive? (See Table II, entry
8) C) Reliability suggests one expects a technology to work consistently and predictably. The term reliable (i.e.,
without glitches or downtime) is probably used more frequently regarding technology than the terms predictable or
consistent [Balusek and Sircar 1998]. Hence, trusting belief-specific technology-reliability refers to the belief that
the technology will consistently operate properly (see Table II, entry 9). These three beliefs reflect the essence of
trust in a specific technology because they represent knowledge that users have cultivated by interacting with a
technology in different contexts, gathering data on its available features, and noticing how it responds to different
actions.
Trusting beliefs in a specific technology is a superordinate second-order construct. Superordinate implies
higher rank or status in the relationship between the trust in a specific technology and its dimensions. This means
that trusting beliefs in a specific technology exists at a deeper level than its individual trusting beliefs [Law et al.
1998], with the relationships flowing from trusting beliefs in a specific technology to its dimensions [Edwards 2001;
Serva et al. 2005]. When individuals trust more in a specific technology, they will report corresponding increases in
trusting beliefs about functionality, helpfulness, and reliability. In contrast, if the construct were aggregate, trust in a
specific technology would be formed by its dimensions which would not necessarily covary [see Polites et al.
Forthcoming]. Moreover, we believe each dimension of trust in a specific technology is reflective, and should be
conceptualized as superordinate and reflective at each level of analysis.
Because trust in specific technology is grounded in users’ knowing the technology sufficiently well that
they can anticipate how it will respond under different conditions, this construct should be positively related to post-
adoption use. We propose that users will be more willing to experiment with different features (intention to explore
Trust in Technology: Its Components and Measures
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a technology because they understand it well enough to believe that it has the attributes (i.e. capability, helpfulness,
and reliability) necessary to support extended use behaviors. Because trust in a specific technology is tied to
specific software applications, we anticipate it will mediate the effect of more broadly defined technology trust
concepts on post-adoption technology use.
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4. METHODOLOGY
Item Development and Pilot Study
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Variable Value Frequency % Respondents
Gender Male 220 61.3
Female 139 38.7
Trust in Technology: Its Components and Measures
Experience using Excel
Mean: 3.209; Median: 3.00;
S.D: 2.875
< 2 years 137 38.2
>= 2 and < 5 years 70 30.1
>= 5 years 152 31.8
Education
Mean: 2.117; Median: 2.00;
S.D: 0.645
High School 47 13.1
Some College 232 64.6
Associate’s Degree 71 19.8
Bachelor’s Degree 9 2.5
Total Subjects 359
Evaluating Validity vis-à-vis Perceived Usefulness and Computer Self-Efficacy
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Trust in Technology: Its Components and Measures
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Trust in Technology: Its Components and Measures
Appendix A. Representave research on trust in MIS literature
Object of Trust Trust Attributes Roles in Model / Empirical Relationships Type of Trust Studies
Institution Structural assurances,
situational normality
Beliefs that outcomes are likely to be
successful due to the presence of supportive
situations and structures
Initial McKnight et al., 1998
Effectiveness of 3rd
party certifications,
security infrastructure
Trust Attributes. No empirical test Initial Lee and Turban, 2001
Protective legal or
technological structures
Institutional-based trust affects trust in vendor Initial McKnight et al., 2002
Situational normality,
structural assurances
Institution-based trust affects trust (in
merchant) and PEOU/PU1.
Initial Gefen et al., 2003
Situational normality,
structural assurances
System trust affects trust in vendor. Initial Pennington et al., 2003
Feedback mechanisms,
escrow services, credit
card guarantees
Effectiveness of institutional mechanisms
affects trust in the community of sellers.
Initial Pavlou and Gefen,
2004
Structural assurances Structural assurances influence trust in
mobile banking
Initial Kim et al. 2009
Technology Technical competence,
reliability, medium
understanding
Trust Attributes. No empirical test Initial Lee and Turban, 2001
Technology Information quality,
good interface design
Perceived site quality aids formation of trust
in vendor
Initial McKnight et al., 2002
Site quality, technical
trustworthiness
Perceived technical trustworthiness and
perceived site quality affects trust in web
vendor
Initial Corbitt et al., 2003
Competence,
benevolence, integrity
Trust in e-commerce environment mediates
the relationship between perceptions of
security controls and behavioral intentions
Initial Suh and Han, 2003
Correctness,
availability, reliability,
security, survivability
Trust in e-channel influences adoption of e-
banking
Initial
(based on
perceived
competence)
Kim and Prabhakar,
2004
Competence,
benevolence, and
integrity
Trust in recommendation agent influences
intention to adopt and PU
Initial Wang and Benbasat,
2005
Cognitive: Integrity,
competence
Emotional: feelings of
security and comfort
Cognitive trust influences emotional trust
(toward the behavior), which influences
intention to adopt online recommendation
agent
Initial Komiak and Benbasat,
2006
Competence,
benevolence, integrity
Trust in a website, based on experience,
influences intention to continue using the
website
Relationship Li et al., 2006
Technology Predictability,
reliability, utility
Trust in technology solution affects
perceptions of supply chain technology and
long-term interaction between supply chain
partners.
Knowledge Lippert, 2007
1 PEOU = Perceived Ease of Use; PU = Perceived Usefulness
Trust in Technology: Its Components and Measures
Object of Trust Trust Attributes Roles in Model / Empirical Relationships Type of Trust Studies
Accuracy, reliability,
safety
Initial trust in mobile banking influences
behavioral intentions
Initial Kim et al. 2009
Functionality,
dependability,
helpfulness
Trust in IT influences PU and PEOU Knowledge Thatcher et al., 2011
Online
Vendor
Ability, integrity,
benevolence
Trust in vendor (or agent of the vendor)
affects intention to use the technology
Initial Lee & Turban, 2001;
Bhattacherjee 2002;
McKnight et al., 2002;
Gefen et al., 2003;
Kim, 2008; Vance et
al., 2008
Benevolence,
credibility
Trust in vendor determines attitudes and
behavioral intentions
Initial Jarvanpaa et al., 2000;
Corbitt et al., 2003;
Pennington et al., 2003
Benevolence,
credibility
Trust in vendor, based on past transactions
and reputation, determines risk perceptions,
beliefs, and behavioral intentions
Knowledge Pavlou, 2003
Online
Vendor
Expectation of
particular action
Trust in online stores and PEOU and PU
jointly determine online purchasing
intentions
Initial Van der Heijden et al,
2003
Commitment, avoiding
excessive advantage
Trust in internet bank influences adoption of
internet banking.
Initial Kim and Prabhakar,
2004
Willingness to
customize, reputation,
size
Trust attributes. No empirical test. Initial Koufaris and
Hampton-Sosa, 2004
No separate dimensions Trust in web merchant, as well as innovation
characteristics, determine intention to use web-
based shopping
Initial Van Slyke et al., 2004
Ability, integrity,
benevolence of an
identifiable population
Trust in a community of sellers determines
transaction intentions
Knowledge Pavlou & Gefen, 2004
Cognitive: Competence,
benevolence, integrity,
predictability
Emotional: feelings of
security and comfort
Trust in the intermediary, and trust in the
community of buyers influences sellers’
intentions to use an e-marketplace again
Knowledge Sun, 2010
Trusting beliefs: ability,
integrity, benevolence
Trusting attitude: a
willingness to rely on a web
vendor
The influence of trusting beliefs in a web vendor
on intentions is fully mediated by trusting
attitude
Initial Benamati et al., 2010
IT Support
Staff
Ability Trust in IT support staff influences trust in
IT and PEOU
Knowledge Thatcher et al., 2011
Interfirm Reliability, integrity Trust in the supplier increases utilization of
new technologies
Knowledge Lippert, 2007
Trust in Technology: Its Components and Measures
Appendix B: Trust in Technology—Measures
Trusting Belief-Specific Technology—Reliability
1. Excel is a very reliable piece of software.
2. Excel does not fail me
3. Excel is extremely dependable.
4. Excel does not malfunction for me
Trusting Belief-Specific Technology—Functionality
1. Excel has the functionality I need.
2. Excel has the features required for my tasks.
3. Excel has the ability to do what I want it to do.
Trusting Belief-Specific Technology—Helpfulness
1. Excel supplies my need for help through a help function.
2. Excel provides competent guidance (as needed) through a help function.
3. Excel provides whatever help I need2.
4. Excel provides very sensible and effective advice, if needed.
Situational Normality—Technology (Adapted from McKnight et al. 2002):
1. I am totally comfortable working with spreadsheet products.
2. I feel very good about how things go when I use spreadsheet products.
3. I always feel confident that the right things will happen when I use spreadsheet products.
4. It appears that things will be fine when I utilize spreadsheet products.
Structural Assurance—Technology (Adapted from McKnight et al. 2002):
1. I feel okay using spreadsheet products because they are backed by vendor protections.
2. Product guarantees make it feel all right to use spreadsheet software.
3. Favorable-to-consumer legal structures help me feel safe working with spreadsheet products.
4. Having the backing of legal statutes and processes makes me feel secure in using spreadsheet products.
Faith in General Technology (Adapted from McKnight et al. 2002):
1. I believe that most technologies are effective at what they are designed to do.
2. A large majority of technologies are excellent.
3. Most technologies have the features needed for their domain.
4. I think most technologies enable me to do what I need to do.
Trusting Stance—General Technology (Adapted from McKnight et al. 2002):
1. My typical approach is to trust new technologies until they prove to me that I shouldn’t trust them.
2. I usually trust a technology until it gives me a reason not to trust it.
3. I generally give a technology the benefit of the doubt when I first use it.
2 This item was dropped prior to CFA
Trust in Technology: Its Components and Measures
APPENDIX C: PCA—LOADINGS AND CROSS-LOADINGS
Rotation Method: Oblique with Kaiser Normalization.
Component
Trust.
Beliefs-
reliab. Sit. Norm
Trust
Stance
Struct.
Assur
Faith in Gen.
Tech.
Trust.
Beliefs-
help.
Trust
Stance
situationalnormality2 0.97 -0.02 0.01 -0.01 -0.02 -0.02 0.02
situationalnormality1 0.96 -0.02 -0.04 0.01 0.01 0.01 0.00
situationalnormality3 0.94 0.00 0.01 0.02 0.01 0.00 -0.05
situationalnormality4 0.91 0.05 0.01 -0.01 -0.02 0.01 0.03
structuralassurance4 -0.02 0.96 -0.02 -0.02 -0.02 0.02 0.00
structuralassurance3 0.00 0.94 0.00 0.05 -0.03 0.02 -0.05
structuralassurance2 -0.01 0.92 -0.01 0.02 0.03 -0.03 0.01
structuralassurance1 0.03 0.86 0.03 -0.04 0.03 -0.01 0.05
reliability4 -0.06 0.02 0.95 -0.08 -0.04 -0.05 0.05
reliability3 -0.01 -0.02 0.92 0.05 -0.04 -0.01 -0.03
reliability1 0.01 -0.02 0.83 0.05 0.00 0.10 -0.01
reliability2 0.08 0.02 0.77 -0.01 0.10 -0.01 0.00
faithgeneraltech2 -0.03 0.01 -0.01 0.90 -0.07 0.00 -0.08
faithgeneraltech3 0.02 0.01 -0.01 0.87 0.03 0.00 -0.04
faithgeneraltech1 0.04 -0.02 -0.10 0.78 0.00 -0.01 0.15
faithgeneraltech4 -0.02 0.01 0.14 0.68 0.06 0.01 0.01
helpfulness4 -0.02 -0.03 -0.01 0.00 0.94 -0.01 0.01
helpfulness1 0.00 0.03 -0.04 -0.05 0.92 0.07 0.01
helpfulness2 0.00 0.01 0.05 0.04 0.92 -0.05 -0.03
functionality2 -0.04 -0.01 -0.03 0.04 -0.01 0.95 0.05
functionality1 0.03 0.01 -0.02 -0.01 0.03 0.91 -0.02
functionality3 0.02 0.01 0.07 -0.03 -0.02 0.90 -0.03
trustingstance2 -0.07 0.05 0.03 0.02 -0.04 0.00 0.89
trustingstance1 0.00 -0.01 -0.02 0.05 0.05 -0.03 0.88
trustingstance3 0.07 -0.04 0.02 -0.06 -0.02 0.03 0.87
Rotated Eigenvaluesa 5.18 5.62 6.12 4.35 5.23 5.66 3.52
% Variance Explaineda36.16 12.40 8.65 7.91 6,26 5.30 4.81
Extraction Method: Principal Components Analysis with Promax
Rotation converged in 6 iterations
a. When components are correlated, sums of squared loadings cannot be added to obtain a total variance
Trust in Technology: Its Components and Measures
APPENDIX D: PCA—LOADINGS AND CROSS-LOADINGS with PU and CSE
Rotation Method: Oblique with Kaiser Normalization.
Component
PU Sit Norm Struct. Assur.
Trust. Beliefs-
reliab.
Faith in Gen.
Tech CSE-internal
Trust. Beliefs-
help. Trust Stance CSE-external
Trust. Beliefs-
funct.
usefulness2 0.95 -0.05 0.00 0.03 -0.05 0.00 -0.01 0.01 0.02 -0.02
usefulness3 0.91 0.00 0.02 -0.03 -0.04 0.05 -0.01 -0.01 -0.03 0.03
usefulness1 0.89 -0.03 -0.02 0.02 0.03 -0.02 0.01 0.01 -0.01 -0.04
usefulness4 0.88 0.05 0.02 0.01 0.02 -0.03 -0.01 0.01 0.00 -0.05
situationalnormality2 0.01 0.98 -0.02 0.01 -0.01 0.00 -0.02 0.02 0.00 -0.03
situationalnormality1 0.00 0.96 -0.02 -0.04 0.01 0.01 0.02 0.00 0.01 0.01
situationalnormality3 -0.03 0.93 0.00 0.01 0.02 0.02 0.01 -0.04 0.01 0.02
situationalnormality4 0.03 0.91 0.05 0.02 -0.02 -0.03 -0.02 0.03 -0.01 -0.01
structuralassurance4 0.06 -0.01 0.96 -0.03 -0.03 -0.02 -0.03 0.00 0.01 -0.01
structuralassurance3 0.02 0.00 0.94 -0.01 0.04 0.00 -0.03 -0.05 0.01 0.02
structuralassurance2 -0.05 -0.01 0.92 0.00 0.02 -0.02 0.04 0.01 0.00 -0.01
structuralassurance1 -0.03 0.03 0.86 0.03 -0.04 0.01 0.04 0.05 -0.03 0.01
reliability4 -0.08 -0.05 0.02 0.97 -0.07 -0.06 -0.03 0.04 -0.04 -0.03
reliability3 0.07 0.00 -0.02 0.89 0.04 0.04 -0.05 -0.02 0.01 -0.02
reliability1 0.07 0.01 -0.02 0.81 0.04 0.03 -0.01 -0.01 -0.01 0.08
reliability2 -0.04 0.09 0.01 0.77 -0.01 -0.01 0.11 0.00 0.03 0.02
faithgeneraltech2 -0.05 -0.05 0.00 0.00 0.90 0.03 -0.05 -0.07 -0.05 0.03
faithgeneraltech3 0.02 0.02 0.01 -0.01 0.87 -0.02 0.02 -0.04 0.01 0.00
faithgeneraltech1 -0.01 0.04 -0.02 -0.11 0.78 -0.04 0.00 0.15 0.06 0.02
faithgeneraltech4 0.06 -0.01 0.02 0.14 0.68 -0.03 0.05 0.01 -0.09 -0.05
CSE2 0.04 -0.01 0.01 -0.05 -0.11 0.96 0.02 0.05 -0.13 0.03
CSE1 -0.01 0.05 -0.03 -0.05 0.05 0.93 -0.01 -0.02 -0.08 0.02
CSE3 -0.03 -0.06 -0.01 0.11 0.03 0.77 0.03 0.00 0.18 -0.03
helpfulness4 0.01 -0.01 -0.03 -0.02 0.00 -0.01 0.94 0.01 0.03 -0.01
helpfulness2 -0.03 0.00 0.03 -0.03 -0.04 0.03 0.93 0.01 -0.06 0.07
helpfulness1 0.05 0.01 0.02 0.03 0.04 0.01 0.90 -0.03 0.04 -0.07
trustingstance2 0.01 -0.06 0.05 0.03 0.02 -0.04 -0.04 0.89 0.05 0.00
trustingstance1 0.02 0.00 -0.01 -0.03 0.05 0.03 0.05 0.88 0.00 -0.03
trustingstance3 -0.02 0.07 -0.04 0.03 -0.05 0.03 -0.01 0.87 -0.04 0.03
CSE6 0.03 -0.02 -0.04 0.02 -0.07 -0.11 0.02 0.02 0.96 0.01
CSE5 -0.01 0.02 -0.01 -0.05 0.00 -0.06 0.02 0.00 0.96 0.05
CSE4 -0.02 0.02 0.08 0.01 0.07 0.37 -0.06 -0.03 0.60 -0.08
functionality2 0.02 -0.04 -0.01 -0.03 0.05 0.00 -0.01 0.05 -0.01 0.93
functionality1 0.00 0.02 0.01 -0.02 0.00 0.01 0.04 -0.01 0.02 0.91
functionality3 0.04 0.02 0.01 0.08 -0.03 0.01 -0.03 -0.03 0.02 0.87
Rotated Eigenvalues 7.23 5.49 6.00 7.09 4.78 2.91 6.10 3.74 2.65 6.90
% Variance Explaineda30.11 9.81 8.39 7.21 5.97 4.39 4.24 4.06 3.65 2.95
Extraction Method: Principal Components Analysis with Promax
Rotation converged in 6 iterations
a. When components are correlated, sums of squared loadings cannot be added to obtain a total variance
Trust in Technology: Its Components and Measures
APPENDIX E: Latent correlation matrices for 1st and 2nd order confirmatory factor analysis
Latent Correlation Matrix: 1st Order CFA
C.A. AVE 1 2 3 4 5 6 7 8 9 10
1.Trusting Stance 0.86 0.68 0.83
2.Faith General Tech. 0.83 0.56 0.43 0.75
3.Situational Normality 0.94 0.84 0.15 0.14 0.92
4.Structural Assurance 0.94 0.81 0.29 0.42 0.30 0.90
5.Functionality 0.91 0.78 0.29 0.37 0.44 0.42 0.88
6.Reliability 0.90 0.70 0.33 0.41 0.42 0.44 0.63 0.84
7.Helpfulness 0.93 0.77 0.13 0.31 0.40 0.43 0.50 0.51 0.88
8.Perceived Usefulness 0.92 0.76 0.27 0.36 0.24 0.33 0.62 0.56 0.50 0.87
9. Internal CSE 0.86 0.68 -.04 -.01 0.13 0.07 0.00 0.08 0.05 -.06 0.83
10. External CSE 0.84 0.67 -.07 -.05 -.02 -.03 -.11 -.02 -.04 -.06 0.31 0.82
C.A = Cronbach’s alpha; square root of AVEs given in diagonal; all correlations significant at p<0.05, unless indicated by grey shading
Means and Std. Deviaons for Constructs
Mean Std. Dev
1.Trusting Stance 4.91 0.19
2.Faith General Tech. 5.26 0.17
3.Situational Normality 3.98 0.12
4.Structural Assurance 4.37 0.07
5.Functionality 5.10 0.10
6.Reliability 5.03 0.24
7.Helpfulness 4.43 0.04
8.Perceived
Usefulness 5.51 0.20
9. Internal CSE 3.95 0.39
10. External CSE 5.50 0.24
Latent Correlation Matrix: 2nd Order CFA
C.A. AVE 1 2 3 4 5 6 7 8
1.Trusting Stance 0.86 0.68 0.83
2.Faith General Tech. 0.83 0.56 0.43 0.75
3.Situational Normality 0.94 0.84 0.15 0.14 0.92
4.Structural Assurance 0.94 0.81 0.29 0.42 0.30 0.90
5.Trust in a specific technology 0.89 0.58 0.35 0.49 0.53 0.57 0.77
6. Perceived Usefulness 0.92 0.76 0.27 0.36 0.24 0.33 0.75 0.87
7. Internal CSE 0.86 0.68 -.04 -.01 0.13 0.07 0.05 -.06 0.83
8. External CSE 0.84 0.67 -.07 -.05 -.02 -.03 -.08 -.06 0.31 0.82
C.A = Cronbach’s alpha; square root of AVEs given in diagonal; all correlations significant at p<0.05, unless indicated by grey shading
Trust in Technology: Its Components and Measures
APPENDIX F: NON-TRUST Measures
Usefulness (Adapted from Davis, 1989):
1. Using Excel would improve my ability to present data graphically
2. Using Excel for my data analysis would help me evaluate information
3. Using Excel would make it easier to perform calculations on my data.
4. I would find Excel useful for analyzing data.
Internal Computer Self-Efficacy (Adapted from Thatcher et al, 2008):
1. There was no one around to tell me what to do
2. I had never used a package like it before
3. I had just the built-in help facility for reference
External Computer Self-Efficacy (Adapted from Thatcher et al, 2008):
1. I could call someone to help if I got stuck
2. Someone showed me how to do it first.
3. Someone else helped me get started.
Intention to Explore—Specific Technology (Excel) (Adapted from Nambisan et al., 1999)
1. I intend to experiment with new Excel features for potential ways of analyzing data.
2. I intend to investigate new Excel functions for enhancing my ability to perform calculations on data.
3. I intend to spend considerable time in exploring new Excel features to help me perform calculations on data.
4. I intend to invest substantial effort in exploring new Excel functions
Deep Structure Usage (Adapted from Burton-Jones and Straub, 2006)
When I use Excel, I use features that help me
1. … analyze the data.
2. … derive insightful conclusions from the data
3. … perform calculations on my data
4. … compare and contrast aspects of the data
5. … test different assumptions in the data
Trust in Technology: Its Components and Measures
APPENDIX G: latent correlation matrix and fit indices
Nomological Validity: Latent Correlation Matrix for 2nd Order CFA
C.A. AVE 1 2 3 4 5 6 7
1.Trusting Stance 0.86 0.68 0.83
2.Faith General Tech. 0.83 0.56 0.43 0.75
3.Situational Normality 0.94 0.84 0.15 0.14 0.92
4.Structural Assurance 0.94 0.81 0.29 0.42 0.30 0.90
5.Trust in Technology 0.89 0.78 0.29 0.37 0.44 0.42 0.77
6.Deep Structure Use 0.93 0.72 0.14 0.24 0.44 0.33 0.65 0.85
7.Intention to Explore 0.94 0.80 0.08 0.20 0.25 0.22 0.44 0.35 0.89
C.A = Cronbach’s alpha; square root of AVEs given in diagonal; all correlations significant at p<0.05, unless indicated by grey shading
Nomological Validity: summary of fit indices
Model Chi-square df Chi-square/df CFI NNFI RMSEA RMSEA 90% CI
1ST Order CFA 731.468 398 1.84 0.963 0.956 0.048 0.043, 0.054
2nd Order CFA 770.332 410 1.89 0.960 0.954 0.050 0.044, 0.055
Structural Model 945.866 445 2.13 0.948 0.942 0.056 0.051, 0.061
