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Abstract

Trust is the enabler of social interaction. Although the origins of research on trust traditionally lie outside the Information Systems (IS) domain, the importance of trust for IS research rapidly grew in the late 1990s, and it is still growing with the increasing ubiquity and advancement of technology in organizations, virtual teams, online markets, and user-technology interactions. Theoretically, the central role of trust is tied to the growing social change that Information and Communication Technology (ICT) has always created, a trend increased by the introduction of electronic commerce, and with it the need to interact and commerce with total strangers. This trend is mirrored in major IS research fields, such as virtual teams and technology acceptance, and thus also naturally in the pages of MIS Quarterly. The importance of trust for IS research and its impact on the IS literature are also reflected by the fact that a trust-related paper (Gefen et al. 2003) is among the most highly cited articles published in MIS Quarterly, together with papers on TAM, knowledge management, and design science. Besides, two trust-related papers have won the MIS Quarterly Paper of the Year Award in 1998 (Kumar et al. 1998) and 2009, respectively (Cyr et al. 2009), and a Special Issue on trust was published in 2010 (Benbasat et al. 2010). Coupled with the facts that we have identified 33 papers relevant for this curation, and that these papers account for about 20,000 total citations, it is perhaps safe to argue that trust is one of the popular and well-cited areas of research in the IS literature, especially during the last 20 years.
Trust: An MIS Quarterly Research Curation 1
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Trust: An MIS Quarterly Research Curation
Research Curation Team:
Matthias Söllner (Universities of St. Gallen and Kassel)
Izak Benbasat (University of British Columbia)
David Gefen (Drexel University)
Jan Marco Leimeister (Universities of St. Gallen and Kassel)
Paul A. Pavlou (Temple University)
Trust is the enabler of social interaction. Although the origins of research on trust traditionally
lie outside the Information Systems (IS) domain, the importance of trust for IS research
rapidly grew in the late 1990s, and it is still growing with the increasing ubiquity and
advancement of technology in organizations, virtual teams, online markets, and user-
technology interactions. Theoretically, the central role of trust is tied to the growing social
change that Information and Communication Technology (ICT) has always created, a trend
increased by the introduction of electronic commerce, and with it the need to interact and
commerce with total strangers. This trend is mirrored in major IS research fields, such as
virtual teams and technology acceptance, and thus also naturally in the pages of MIS
Quarterly. The importance of trust for IS research and its impact on the IS literature are also
reflected by the fact that a trust-related paper (Gefen et al. 2003) is among the most highly
cited articles published in MIS Quarterly, together with papers on TAM, knowledge
management, and design science. Besides, two trust-related papers have won the MIS
Quarterly Paper of the Year Award in 1998 (Kumar et al. 1998) and 2009, respectively (Cyr
et al. 2009), and a Special Issue on trust was published in 2010 (Benbasat et al. 2010).
Coupled with the facts that we have identified 33 papers relevant for this curation, and that
these papers account for about 20,000 total citations, it is perhaps safe to argue that trust is
one of the popular and well-cited areas of research in the IS literature, especially during the
last 20 years.
Focus of the Research Curation
This curation adopts a broad definition of trust based on Gefen et al. (2003) who combined
the theoretical background of trust as a behavioral antecedent from the sociology literature
along with its antecedent beliefs about the trustworthiness of another party. This was
suggested by philosophers as early as Aristotle and also highlighted in management research.
According to that definition, trust is a willingness of one party (the trustor) to rely on another
party (the trustee), i.e., about setting aside concerns the trustor has about the trustee’s taking
advantage of the situation in cases that involve risk and potential loss to the trustor. This
willingness to rely is based on assessments about the trustee’s characteristics, mainly about
ability (competence), benevolence, and integrity.
This curation highlights all 33 articles published in MIS Quarterly that focus on the study of
trust (see Table 1 at the end of this curation). Since the goal of this curation is to provide a
starting point for future research on trust, it focuses on papers in which trust plays an
important role in the proposed model, hypotheses, or overall study. Thus, the curation
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excludes articles in which trust is merely used as part of another construct (e.g., Mithas et al.
2008) or in which trust is used as a synonym for other kindred concepts, such as friendship in
peer-to-peer lending (e.g., Liu et al. 2015). Due to the large number of articles on trust, the
curation, furthermore, excludes articles that deal with related topics such as risk, privacy and
security.
Progression of Research in MIS Quarterly
Early research on trust in MIS Quarterly, starting mainly just before 2000, was closely tied to
research in the broader management literature. Perhaps because of those origins, trust research
in MIS Quarterly initially concentrated on trust relationships where an ICT is a conduit to
traditional trust-based relationships, such as buyer-seller relationships in electronic commerce,
or where trust is a defining characteristic of the software development process, such as
outsourcing relationships among organizations. Representative topics of this initial period
include studies of how ICT affects the performance of work teams (e.g., Piccoli and Ives
2003; Paul and McDaniel Jr. 2004), how online markets and channels change the way
transactions take place among consumers and businesses online (e.g., Ba and Pavlou 2002;
Gefen et al. 2003), and how groups collaborate in virtual settings (Nelson and Cooprider
1996). Parallel to that stream, also early on, there was conceptual research on how to increase
trust in technology (Gregor and Benbasat 1999). Importantly, right from this initial period on,
research tied trust directly to key constructs used in MIS theories, which is probably why trust
became a key theme in MIS research. Representative of this integration of trust into the heart
of existing theories utilized in MIS are Gefen et al. (2003) who integrated trust into TAM, and
Pavlou and Feygenson (2006) who added trust into the theory of planned behavior.
The study of trust in MIS Quarterly evolved toward the mid-2000s, showing an increase in
research on trust between organizations, especially in the context of IT/IS outsourcing. Trust
was shown to be a key construct in successful IT/IS outsourcing relationships (Ågerfalk and
Fitzgerald 2008; Gefen et al. 2008; Goo et al. 2009; and Rai et al. 2009).
Also beginning in the mid-2000s and lasting until today, there has been an increase in
research on trust and the IT artifact as well as a more nuanced look into the construct of trust.
This period saw a shift from understanding the importance of trust toward more interest in
how to design trustworthy systems (e.g., Komiak and Benbasat 2006) and better understand
how cultural and gender differences affect the relationships between trust and other constructs
(e.g., Cyr et al. 2009; Sia et al. 2009; Riedl et al. 2010). Another stream of research in this
period includes the application of neuroscience methods to better measure trust constructs
(Dimoka 2010; Riedl et al. 2010) and to investigate whether trust and distrust are distinct
constructs (Dimoka 2010).
The richness and diversity of the study of trust is reflected in the many methodologies used to
study trust (please see Table 1 for details). These methodologies include theoretical reasoning
(e.g., Gregor and Benbasat 1999), literature reviews (e.g., Xiao and Benbasat 2007), a single
case study (Kumar et al. 1998) or many case studies (e.g., Watson-Manheim and Bélanger
2007), different experimental approaches (e.g., Ba and Pavlou 2002; Piccoli and Ives 2003;
Sia et al. 2009), surveys and field studies (e.g., Gefen et al. 2003; Paul and McDaniel Jr.
2004; Kankanhalli et al. 2005; Kanawattanachai and Yoo 2007), fMRI (e.g., Riedl et al.
2010), archival data (e.g., Gefen et al. 2008; Burtch et al. 2014), as well as combinations of
these approaches, e.g., a lab experiment including qualitative interviews, quantitative surveys
and eye-tracking methods (Cyr et al. 2009), or lab and fMRI experiments (Dimoka 2010).
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Thematic Advances in Knowledge
Four overarching clusters of trust-based relationships were investigated in the studies listed in
Table 1: (1) between people or between groups, (2) between people and organizations, (3)
between organizations, and (4) between people and technology. Within each of these clusters,
different research themes were investigated.
The first cluster of studies focuses on trust relationships between people or between groups.
These studies can be further divided into studies that focus on trust within virtual teams
(Nelson and Cooprider 1996; Piccoli and Ives 2003; Paul and McDaniel Jr. 2004; Kankanhalli
et al. 2005; Stewart and Gosain 2006; Watson-Manheim and Bélanger 2007; Kanawattanachai
and Yoo 2007; Iacovou et al. 2009; Thomas and Bostrom 2010), and studies focusing on trust
in buyer-seller-like relationships in online markets (Ba and Pavlou 2002; Dimoka 2010; Riedl
et al. 2010; Burtch et al. 2014; Ou et al. 2014). With regards to trust in virtual teams, multiple
studies have shown the importance of trust among team members as an antecedent of team
success. Nelson and Cooprider (1996), for example, showed that mutual trust between
members of the IS group and line groups of an organization increases shared knowledge, and
thus performance. Paul and McDaniel Jr. (2004) showed a direct positive effect of trust
among team members on team performance in telemedicine, while Iacovou et al. (2009)
showed that the absence of trust between IS project managers and executives can lead to
biases in their communication. With regard to online markets, research shows that feedback
mechanisms have an impact on how buyers rate the trustworthiness of sellers and that buyers
were willing to pay price premiums to sellers they trust more (Ba and Pavlou 2002).
The second cluster focuses on trust relationship between people and organizations. These
studies focus mainly on (potential) customer trust in internet businesses (Gefen et al. 2003;
Pavlou and Fygenson 2006; Pavlou et al. 2007; Sia et al. 2009; Fang et al. 2014), with one
study focusing on trust in web-based channels in general (Choudhury and Karahanna 2008).
Choudhury and Karahanna (2008) showed that informational trust is a driver of the relative
advantages of web-based channels. Research also embedded trust into well-established
models of human behavior, such as the technology acceptance model (Gefen et al. 2003) and
the theory of planned behavior (Pavlou and Fygenson 2006), showing that trust in web
vendors drives online shopping behavior.
The third cluster focuses on trust relationships between organizations. These studies can be
divided into studies focusing on IT/IS outsourcing (Ågerfalk and Fitzgerald 2008; Gefen et al.
2008, Goo et al. 2009; Rai et al. 2009), and studies focusing on trust in other forms of inter-
firm relationships (Kumar et al. 1998; Klein and Rai 2009). Comparable to the results about
virtual teams, research on IT/IS outsourcing highlights the necessity of trust as a basis for a
mutually beneficial outsourcing relationship across different types of outsourcing, such as
open sourcing (Ågerfalk and Fitzgerald 2008), IT outsourcing (Goo et al. 2009), and IS
offshoring (Rai et al. 2009). Furthermore, Gefen et al. (2008) showed that trust influences
what type of contract is used in software development outsourcing. Research also showed that
trust can often reduce the positive effects of new systems, leading to acceptance problems
(Kumar et al. 1998), and that trust is an important antecedent of strategic information flows
within inter-firm logistics relationships (Klein and Rai 2009).
The fourth cluster focuses on trust relationships between people and technology. These studies
can be divided into studies focusing on trust in systems, such as recommendation systems or
decision-support systems (Gregor and Benbasat 1999; Komiak and Benbasat 2006; Xiao and
Benbasat 2007; Han et al. 2015) and studies focusing on trust in websites (Cyr et al. 2009;
Xiao and Benbasat 2011). Also in this cluster is the study of trust in the nation-wide initiative
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to introduce identity smart cards in Nigeria (McGrath 2016). Studies focusing on user trust in
systems showed the importance of trust in the context of using or relying on those systems
(e.g., Komiak and Benbasat 2006; Han et al. 2015). Research in this stream also provided
insights into how systems should be designed so that their users perceive them as being more
trustworthy. In that regard, Gregor and Benbasat (1999) conceptualized the importance of
suitable explanations to increase trust in systems. Komiak and Benbasat (2006) highlighted
the need for personalization of systems to increase user trust. Cyr et al. (2009) showed how
user trust across different cultures can be influenced by varying image appeals and perceived
social presence in the context of building trust in websites. Finally, Xiao and Benbasat (2011)
propose that people perceive potential deception on an e-commerce website differently
depending on whether they interact with a trusted website or not.
Conclusion
The extensive research on trust and the broad range of methodological approaches in MIS
Quarterly shows the centrality and complexity of trust in contexts of interest to the MIS
community. It is our intent that this curation will contribute to the continued interest and
development of the study of trust in the MIS discipline through this curation.
MIS Quarterly References beyond the Papers Included in Table 1
Benbasat, I., Gefen, D., and Pavlou, P. A. 2010. “Introduction to the Special Issue on Novel
Perspectives on Trust in Information Systems,” MIS Quarterly (34:2), pp. 367–371.
Liu, D., Brass, D. J., Lu, Y., and Chen, D. 2015. “Friendship in Online Peer-to-Peer Lending:
Pipes, Prisms, and Relational Herding,” MIS Quarterly (39:3), 729-A4.
Mithas, S., Jones, J. L., and Mitchell, W. 2008. “Buyer Intention to Use Internet-Enabled
Reverse Auctions: The Role of Asset Specificity, Product Specialization and Non-
Contractibility,” MIS Quarterly (32:4), pp. 705–724.
Please cite this curation as follows: Söllner, M., Benbasat, I., Gefen, D., Leimeister, J. M.,
Pavlou, P. A. “Trust,” in MIS Quarterly Research Curations, Ashley Bush and Arun Rai, Eds.,
http://misq.org/research-curations, October 31, 2016.
Please feel free to contact Matthias Söllner (matthias.soellner@unisg.ch) if you have
comments on or questions regarding this curation.
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Table 1. MIS Quarterly Papers on Trust
ID Author(s) Title Year
Vol. (I.) Trust relationship
(Cluster-#) Methodological
approach(es) Key trust-related insights
1 Kay M. Nelson and Jay
G. Cooprider
The Contribution of Shared
Knowledge to IS Group
Performance
1996
20 (4) IS groups and line
customers (1)
Cross-sectional field
study (DC) & path
analysis (DA)
Mutual trust impacts shared
knowledge which impacts IS
performance
2 Kuldeep Kumar, Han G.
van Dissel and Paola
Bielli
The Merchant of Prato Revisited:
Toward a Third Rationality of
Information Systems
1998
22 (2)
Organizations of
the Prato textile
district (3)
Single case study
including interviews and
archival data
Existence of trust made a new IS
irrelevant, and lead to its failure
3 Shirley Gregor and Izak
Benbasat
Explanations from Intelligent
Systems: Theoretical Foundations
and Implications for Practice
1999
23 (4)
Users and
intelligent systems
(4) Theoretical reasoning Explanations that conform to
Toulmin’s model of argumentation
should lead to greater trust
4 Sulin Ba and Paul A.
Pavlou
Evidence of the Effect of Trust
Building Technology in Electronic
Markets: Price Premiums and
Buyer Behavior
2002
26 (3)
Buyers and sellers
on electronic
(auction) markets
(1)
Online field experiment
and field data (DC) &
regression analysis (DA)
Properly designed feedback
mechanisms can influence trust,
and trust impacts buyers'
willingness to pay price premiums
5 David Gefen, Elena
Karahanna and Detmar
W. Straub
Trust and TAM in Online
Shopping: An Integrated Model 2003
27 (1) Consumers and
online vendors (2) Field study (DC) &
CBSEM (DA) Trust impacts perceived usefulness
and intended use
6 Gabriele Piccoli and Ives
Blake Trust and the Unintended Effects of
Behavior Control in Virtual Teams 2003
27 (3)
Between members
of temporary virtual
student teams (1)
Longitudinal experiment
(DC) & Case and
statistical analyses (DA)
Behavior control mechanisms for
traditional teams have a negative
effect on trust in virtual teams
7 David L. Paul and
Reuben R. McDaniel Jr.
A Field Study of the Effect of
Interpersonal Trust on Virtual
Collaborative Relationship
Performance
2004
28 (2)
Between different
physicians in virtual
telemedicine teams
(1)
Interviews (DC) & case
analysis and POSAC
(DA)
Interpersonal trust among
physicians increases team
performance
8 Atreyi Kankanhalli,
Bernard C. Tan and
Kwok-Kee Wei
Contributing Knowledge to
Electronic Knowledge Repositories:
An Empirical Investigation
2005
29 (1)
Between users of an
electronic know-
ledge repository (1)
Survey (DC) &
moderated multiple
regression analysis (DA)
If there is no generalized trust
among users, codification effort
hinders system usage
9 Paul A. Pavlou and
Mendel Fygenson
Understanding and Predicting
Electronic Commerce Adoption:
An Extension of the Theory of
Planned Behavior
2006
30 (1) Consumers and web
vendors (2) Longitudinal study (DC)
& PLS (DA)
Trusting beliefs influence both, the
attitude to getting info and the
attitude to purchasing from a
vendor
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10 Katherine J. Stewart and
Sanjay Gosain
The Impact of Ideology on
Effectiveness in Open Source
Software Development Teams
2006
30 (2)
Between members
of large OSS
development teams
(1)
Two surveys and
archival data (DC) &
PLS (DA)
Cognitive trust impacts affective
trust and affective trust influences
both, team size and team effort
11 Sherrie Y. X. Komiak
and Izak Benbasat
The Effects of Personalization and
Familiarity on Trust and Adoption
of Recommendation Agents
2006
30 (4)
Users and
recommendation
agents (4)
Online experiment (DC)
& PLS (DA)
Personalization and familiarity
impact cognitive trust which
impacts emotional trust that has an
impact on intention to adopt
12 Paul A. Pavlou, Huigang
Liang and Yaijong Xue
Understanding and Mitigating
Uncertainty in Online Exchange
Relationships: A Principal-Agent
Perspective
2007
31 (1) Consumers and web
vendors (2) Two surveys (DC) &
PLS (DA) Trust mitigates uncertainty
antecedents
13 Bo Xiao and Izak
Benbasat
E-Commerce Product
Recommendation Agents: Use,
Characteristics, and Impact
2007
31 (1)
Users and
recommendation
agents (4) Literature review Different configurations of
recommendation agents are
proposed to influence trust
14 Mary Beth Watson-
Manheim and France
Bélanger
Communication Media Repertoires:
Dealing with the Multiplicity of
Media Choices
2007
31 (2)
Between members
of virtual sales
teams (1)
Multiple case study
including interviews and
archival data
Low trust can lead to decreased
communication effectiveness,
frustration, and wasted effort and
resources
15 Prasert Kanawattanachai
and Youngjin Yoo
The Impact of Knowledge
Coordination on Virtual Team
Performance over Time
2007
31 (4)
Between members
of virtual student
teams (1)
Three surveys and
archival data (DC) &
PLS (DA)
Cognition-based trust impacts task-
knowledge coordination across all
time periods
16 Vivek Choudhury and
Elena Karahanna
The Relative Advantage of
Electronic Channels: A
Multidimensional View
2008
32 (1)
Consumers and web
channels in general
(2)
Survey (DC) & PLS
(DA)
Informational trust impacts the
relative advantage of web-based
channels
17 Pär J. Ågerfalk and
Brian Fitzgerald
Outsourcing to an Unknown
Workforce: Exploring
Opensourcing as a Global Sourcing
Strategy
2008
32 (2)
Commercial
companies and
open source
communities (3)
Multiple qualitative
sources and survey (DC)
& coding techniques and
Mann-Whitney tests and
regression (DA)
Trust is a key requirement for
building a successful opensourcing
relationship
18 David Gefen, Simon
Wyss and Yossi
Lichtenstein
Business Familiarity as Risk
Mitigation in Software
Development Outsourcing
Contracts
2008
32 (3)
Between
organizations in
software
development
outsourcing (3)
Archival data (DC) &
multiple linear and
logistic regressions (DA)
Trust reflected in business
familiarity leads to more time and
materials outsourcing contracts
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19 Jahyun Goo, Rajiv
Kishore, H. R. Rao and
Kichan Nam
The Role of Service Level
Agreements in Relational
Management of Information
Technology Outsourcing: An
Empirical Study
2009
33 (1)
Between
organizations in IT
outsourcing
relationships (3)
Survey (DC) & PLS
(DA)
Harmonious conflict resolution and
mutual dependence impact trust
and in interaction they impact
commitment
20
Choon Ling Sia, Kai H.
Lim, Kwok Leung,
Matthew K. O. Lee,
Wayne Wie Huang and
Izak Benbasat
Web Strategies to Promote Internet
Shopping: Is Cultural
Customization Needed?
2009
33 (3) Consumers and web
vendors (2)
Lab experiment (DC) &
standard and multigroup
PLS (DA)
The way trust in web vendors via
their websites can be built differs
across cultures (here Australia
versus Hong Kong)
21 Dianne Cyr, Milena
Head, Hector Larios and
Bing Pan
Exploring Human Images in
Website Design: A Multi-Method
Approach
2009
33 (3)
Users and e-
commerce websites
(4)
lab experiment including
eye-tracking, survey, and
interviews (DC) &
coding-based theory
building, PLS, eye-
tracking analysis (DA)
Image appeal and perceived social
presence impact trust, and human
figures with facial features foster
the highest level of trust among all
cultures
22 Arun Rai, Likoebe M.
Maruping and Viswanath
Venkatesh
Offshore Information Systems
Project Success: The Role of Social
Embeddedness and Cultural
Characteristics
2009
33 (3)
Between
organizations in IS
offshore
relationships (3)
longitudinal field study
(DC) & random
coefficient modeling
(DA)
Client trust leads to lower cost
overruns and higher satisfaction
23 Richard Klein and Arun
Rai
Interfirm Strategic Information
Flows in Logistics Supply Chain
Relationships
2009
33 (4)
Between organi-
zations in logistics
supply chain
relationships (3)
Interviews and survey (DC)
& PLS (DA)
Trust impacts strategic information
sharing
24 Charalambos L. Iacovou,
Ronald L. Thompson
and H. Jeff Smith
Selective Status Reporting in
Information Systems Projects: A
Dyadic-Level Investigation
2009
33 (4) IS project managers
and executives (1) Survey (DC) & PLS (DA)
Executive's knowledge and
communication impact trust in
executive which has a negative
impact on optimistic biasing
25 Dominic M. Thomas and
Robert P. Bostrom
Vital Signs for Virtual Teams: An
Empirically Developed Trigger
Model for Technology Adaptation
Interventions
2010
34 (1) Between members
of virtual teams (1)
Critical incident
technique including
interviews and survey
(DC) & interpretive
content analysis (DA)
Lack of trust among team members
as one trigger of technology
adaptations
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26 Angelika Dimoka What Does the Brain Tell Us About
Trust and Distrust? Evidence from
a Functional Neuroimaging Study
2010
34 (2)
Buyers and sellers
on electronic
(auction) markets
(1)
Lab and fMRI experiment
(DC) & EFA, CFA,
regression and fMRI
analysis (DA)
Trust
and distrust are different, since
different regions of the brain are
active, and both affect price
premiums as expected
27 René Riedl, Marco
Hubert and Peter
Kenning
Are There Neural Gender
Differences in Online Trust? An
fMRI Study on the Perceived
Trustworthiness of eBay Offers
2010
34 (2)
Buyers and sellers
on electronic
(auction) markets
(1)
fMRI experiment (DC) &
fMRI analysis and general
linear modeling (DA)
Assessment of trustworthiness
differs across genders (different
brain regions active), women
activate more regions
28 Bo Xiao and Izak
Benbasat
Product-Related Deception in E-
Commerce: A Theoretical
Perspective
2011
35 (1)
Users and e-
commerce websites
(4) Theoretical reasoning
Anomalies should less likely be
attributed to deception by users
with high prior or calculative-based
trust
29 Carol Xiaojuan Ou, Paul
A. Pavlou and Robert M.
Davison
Swift Guanxi in Online
Marketplaces: The Role of
Computer-Mediated
Communication Technologies
2014
38 (1)
Buyers and sellers
on electronic
(auction) markets
(1)
Longitudinal field study
including surveys and
archival data (DC) & PLS
(DA)
Interactivity and presence impact
trust, and trust impacts swift guanxi
and repurchase intention
30
Yulin Fang, Israr
Qureshi, Heshan Sun,
Patrick McCole, Elaine
Ramsey and Kai H. Lim
Trust, Satisfaction, and Online
Repurchase Intention: The
Moderating Role of Perceived
Effectiveness of E-Commerce
Institutional Mechanisms
2014
38 (2) Consumers and web
vendor (2) Survey (DC) & PLS (DA)
PEEIM moderators the
relationships
between satisfaction and trust as
well as trust and repurchase
intention
31 Gordon Burtch, Anindya
Gose and Sunil Wattal
Cultural Differences and
Geography as Determinants of
Online Prosocial Lending
2014
38 (3)
Borrowers and
lenders on peer-to-
peer lending
platforms (1)
Archival data (DC) &
Poisson pseudo-
maximum likelihood
estimator (DA)
Trust is a key mechanism in
lending decision, and third party
trust mechanisms can help to
overcome culture-related lender
concerns
32 Wencui Han, Serkan
Ada, Raj Sharman and
H. Raghav Rao
Campus Emergency Notification
Systems: An Examination of
Factors Affecting Compliance with
Alerts
2015
39 (4)
Students and
campus emergency
notification systems
(4)
Survey and focus group
(DC) & logistic
regression analysis (DA)
Information quality trust is the only
factor that impacts intention to
comply across all five scenarios
33 Kathy McGrath
Identity Verification and Societal
Challenges: Explaining the Gap
between Service Provision and
Development Outcomes
2016
40 (2)
Nigerian citizens
and identity smart
cards (4)
Comparative case study
analysis
Workable combination of trust and
distrust needs to be in place when
aiming to introduce identity smart
cards
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Legend:
CBSEM = covariance-based structural equation modeling; CFA = confirmatory factor analysis; DA = data analysis; DC = data collection; EFA = exploratory factor analysis;
OSS = open
source software;
PEEIM = Perceived Effectiveness of E-Commerce Institutional Mechanisms; PLS = partial least square; POSAC = partial order scalogram analysis with base coordinates
... Por exemplo, em nossas compras, ao adquirirmos um produto ou ao contratarmos um serviço, confiamos no vendedor, na loja, no fabricante, no prestador do serviço e até no poder de compra que o papel moeda representa. Como descrito no artigo de Rotter (1971, p. 443)," the entire fabric of our day-to-day living rests on trust -buying gasoline, paying taxes, going to the dentist, flying to a convention -almost all our decisions involve trusting someone else." Na área das TICs, a confiança tem sido um tópico muito explorado, a ponto de Management Information Systems Quarterly (MISQ) ter uma edição especial -3 que destaca 33 artigos sobre confiança lá publicados (Söllner, Benbasat, Gefen, Leimeister, & Pavlou, 2016). ...
... Sobre o tema, o artigo afirma: "…it is perhaps safe to argue that trust is one of the popular and well-cited areas of research in the IS literature, especially during the last 20 years" (Söllner et al., 2016) Para confirmar esta popularidade, fizemos uma busca dos artigos mais citados sobre confiança, utilizando-nos do Web of Science, com as palavras-chave trust e information system*. Utilizamos como referência para este tópico, os artigos Josang, Ismail, & Boyd, (2007) e Pavlou & Gefen (2004) que são os mais citados. ...
... Autor Publicação Citações The richness and diversity of the study of trust is reflected in the many methodologies used to study trust These methodologies include theoretical reasoning (e.g., Gregor and Benbasat 1999), literature reviews (e.g., Xiao and Benbasat 2007), a single case study (Kumar et al. 1998) or many case studies (e.g., Watson-Manheim and Bélanger 2007), different experimental approaches (e.g., Ba and Pavlou 2002;Piccoli and Ives 2003;Sia et al. 2009), surveys andfield studies (e.g., Gefen et al. 2003;Paul and McDaniel Jr. 2004;Kankanhalli et al. 2005;Kanawattanachai and Yoo 2007), fMRI (e.g., Riedl et al. 2010), archival data (e.g., Gefen et al. 2008Burtch et al. 2014), as well as combinations of these approaches, e.g., a lab experiment including qualitative interviews, quantitative surveys and eye-tracking methods (Cyr et al. 2009), or lab andfMRI experiments (Dimoka 2010). (Söllner et al., 2016, p. 3) De acordo com Söllner et al. (2016), podemos dizer que existem quatro classificações em relação à confiança: ...
Thesis
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In this Master’s thesis, we investigate how reputation systems can interfere on trust building between strangers who are participants in the sharing economy. It can be defined as an economic activity, powered by a technological platform, based on the interactions between providers and users. Our focus is to study how a provider may feel more comfortable lending his asset or providing his time to a stranger. We explore how a system of mutual reputation can be the catalyst for the development of initial trust among strangers. By doing so, we have tried to fill a gap, identified in the literary review, about the use of mutual reputation systems in sharing economy. Since this is based on mutual interference, the theoretical lens of sociomateriality was used, allowing us to analyze the dynamic construction of the reputation systems and its use and the agential cuts related to the incentive and punishment of users of this economy. The empirical part of how the reputation system is used has been done through a single case study where we verify the use of the reputation system of the Uber passenger by the driver on provision of ridesharing services. Through semi-structured driver interviews, documentation analysis and netnography of Facebook’s and WhatsApp’s drivers groups, we were able to identify provider’s profiles with different initial trust requirements. We also identify the strong interference that intermediaries can exert on the usage of the reputation system by creating forms of provider’s oppression. And finally, we identify the result of sociomaterial bricolage when providers adopt new practices of using the reputation system to compensate the idiosyncrasies of intermediaries like Uber. As practical contributions, we emphasize the importance of equal treatment to the players of Sharing Economy platforms. On mutual evaluation reputational systems, the favoring any of the players contaminates the evaluation and the use of the reputation, invalidating it as apparatus of measuring the initial trust. We also emphasize the need to regulate the intermediaries’ behavior, by limiting abuses on information manipulation, provider’s management (providing a right of defense) and abusive pricing practices. There are also several suggestions for enhancing platform capabilities to facilitate the use of the reputation system such as disclosing punishments and incentives to users or what should be evaluated by providers and users after collaboration.
... The inconclusive evidence on user attitudes toward algorithmic decision supports calls for detailed investigations of the reliance decision's antecedents. Prior research on human interaction with technology has suggested trust as an important psychological driver for the acceptance of automated systems (Lee and See, 2004;Söllner et al., 2018). Theoretically rooted in interpersonal trust, trust in technology builds on experience with and attitudes toward the particular information technology (IT) artifacts (McKnight et al., 2011). ...
... Central to the definition of trust is the readiness to rely on another party to perform a task based on expectations toward it in the context of uncertainty (Mayer et al., 1995). Conceptually rooted in interpersonal relationships, trust in technology developed into a prominent area for IS literature (Söllner et al., 2018) and connected streams. Research acknowledges trust as a prerequisite for system usage and adoption (McKnight et al., 2011). ...
... Loss of trust resulted in disuse of algorithmic aids and a higher reliance on the individuals themselves; hence, performance and reliability are strongly connected to trust and can lead to enhanced or reduced utilization (Hoff and Bashir, 2015;Lee and See, 2004). Previous studies in IS literature highlight the strong link between trust, intention to use, and adoption (Söllner et al., 2018). Trust has been integrated into the Technology Acceptance Model and its extensions, with multiple studies confirming trust as an antecedent for IS acceptance (Venkatesh et al., 2016). ...
Conference Paper
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Artificial intelligence enables the emergence of novel intelligent decision support systems (IDSSs). Despite the potential for increased efficiency, mixed evidence on user aversion to or appreciation for such intelligent systems prevails, questioning user trust in algorithmic decision support. Recent advances in machine learning facilitate the incorporation of a promising driver of trust into the systems: the systems' ability to learn. In this study, we conduct an experiment, manipulating the type of decision support (human vs. automated) and their learning ability in the context of a clinical decision support system. Results indicate increased trust in automated decision support with the ability to learn. Our findings contribute to theory and practice, identifying (machine) learning as an antecedent of trust, thereby enhancing our understanding of user perceptions of IDSSs. Furthermore, we add to literature on algorithm aversion by showing that people readily rely on algorithmic support in the context of clinical decision making.
... According to Söllner et al. [31], four clusters of trust-based relationships are central to studies in IS research: ...
... Our study is positioned in the latter cluster, which focuses on trust in IT artifacts. This line of literature encompasses many facets and approaches regarding how trust influences the mechanisms of technology adoption, thereby improving our understanding of how to enhance the design of trustworthy artifacts [31]. To this end, trust is often embedded as an external variable in the TAM, with a variety of studies examining its nomological validity for different technologies and contexts [12]. ...
Conference Paper
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With their human-like nature, conversational agents (CAs) introduce a social component to human-computer interaction. Numerous studies have previously attempted to integrate this social component by incorporating trust into models such as the technology acceptance model (TAM) to decipher the adoption mechanisms related to CAs. Given the heterogeneity of these previous works, the aim of this paper is to integrate empirical evidence on the role and influence of trust within the nomological network of the TAM. For this purpose, we conduct a meta-analytic structural equation modeling approach based on 45 studies comprising k = 155 correlations, and N = 13,786 observations. Our findings highlight the multifaceted role of trust as a mediator transmitting the effects of the technology-related perceptions that drive the intention to use CAs. Our results present a comprehensive overview in a thriving research field that can guide both future theory building and the designs of more trustworthy CAs.
... One large stream of research in the IS literature has focused on trust between people or between groups [14]. Trustors decide to trust a trustee based on their perceptions of the trustee's abilities, benevolence and integrity [13]. ...
... Whether a trustor decides to be vulnerable to another party or not, depends on his risk perceptions and how much he trusts the trustee [13]. While the main focus of the IS community has been on virtual teams and online markets [14], trust-related research pertaining to professionals in the health care sector also exists. ...
... The importance of trust in the Information Systems discipline at large-and, hence, in the online shopping context in particular-has been widely studied (see, e.g., Gefen, 2000;McKnight et al., 2002a;Gefen et al., 2008;Riedl et al., 2010;Söllner et al., 2016). Given the vast body of literature on the subject, we refer below only to those studies that specifically considered the direct effects of TP (also called "disposition to trust" or "trust disposition") and EVT (or "trust in the e-vendor") on online or in-store purchase intentions. ...
Article
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Nowadays, customers can utilize both online and in-store retail channels. Consequently, it is crucial for retailers to understand the possible drivers of retail channel selection, including customers’ personalities, degrees of trust, and product touch preferences. Unfortunately, current omnichannel research only scarcely addresses the effects of personality, trust, and desire to touch a product before purchasing it on willingness to purchase and how those effects vary between online and in-store shopping. Thus, we conducted an exploratory study. Our analysis of survey data ( N = 1,208)—which controls for respondents’ age, gender, and education—reveals that across both the willingness to purchase in-store and online, a higher level of e-vendor trust is a significant, positive predictor. However, we also identify several channel-related differences, including that Trust Propensity, as well as the Big Five traits of Extraversion, Agreeableness, and Conscientiousness are significantly positively related to in-store, but not online, purchase willingness. We also find that Instrumental Need for Touch (defined as goal-motivated touch of a product) is positively related to in-store, but negatively related to online, purchase willingness. Finally, we highlight opportunities for future research and discuss how retail managers might enhance customer experiences in their physical and online stores.
... There are many relationships of trust. Trust research can be split into trust (1) between people or between groups, (2) between people and organisations, (3) between organisations, and (4) between people and technology (Söllner, Benbasat, et al., 2016). In general, trust is defined as a latent variable made up of different dimensions (Bühner, 2011). ...
Conference Paper
In recent years the digitisation of healthcare has been moving forward. Emerging technologies, such as smart glasses, are being tested for allowing healthcare workers information access at the point of care, while being able to work hands-free. Yet it remains unclear how the use of smart glasses will affect the trust relationship between patients and caregivers. The patient is not an active user of the smart glasses but is nevertheless dependent on outcomes influenced by the smart glasses. The patient, therefore, becomes a passive trustor of this technology. Building upon existing trust research literature, we present a research model and extend it by interviewing 20 patients about their experiences with caregivers and their perceptions regarding the use of smart glasses in healthcare. We find that communication with patients is a key driver of passive trust in technology and trust in caregivers. This research contributes to a better understanding of the trust relationship between patients and caregivers and provides insights into the construct of passive trust in technology. In order to extend the qualitative data analysis, future research should investigate the extent of the acceptance of smart glasses by patients within healthcare facilities.
... Granting access to privately owned goods from peer to peer necessitates overcoming reservations about possible vulnerability to strangers -in a nutshell: the sharing economy runs on trust [2]- [6]. Trust in its own right is a research topic of interdisciplinary nature and (as an enabler of social interaction) of imperturbable recency [7], [8]. Consequently, concepts and theories addressing trust in the sharing economy are complex and diverse [4]. ...
Chapter
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Blockchain is frequently considered as a trust enabling or even trust-free technology. At the tip of the Gartner Hype Cycle, it is therefore assumed to become a key technology for various domains, inter alia leading to a “Sharing Economy 2.0”. The focus of this short paper is to investigate the nature of trust relationships in a blockchain-enabled sharing economy context. A scenario-based pilot survey is conducted to investigate how blockchain as a platform technology for peer-to-peer sharing of IoT assets influences consumer trust. First results suggest that trust in blockchain technology itself is an important driver of trust in blockchain-based platforms and renting intentions. This pilot study contributes to theory and practice by shedding light on the multitude of targets and trust relationships in blockchain-enabled peer-to-peer sharing and by demonstrating the need for establishing trust in blockchain technology itself.
Article
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Networked online environments can effectively support political activism. In Sweden, the #metoo movement resulted in over 100,000 people participating in activities challenging sexual harassment and abuse, including collecting testimonies via social media and drafting and discussing petitions published in print news media. Participation involved many risks, such as social stigma, losing one’s job, or misogynist terrorism, which meant that participation required a high level of trust among peers. Human-computer interaction (HCI) research on trust generally focuses on technical systems or user-generated data, less focus has been given to trust among peers in vulnerable communities. This study, based on semi-structured interviews and surveys of participants and organizers of 47 petitions representing different sectors in society, found that trust was aggregated over networks of people, practices, institutions, shared values, and technical systems. Although a supportive culture based on a feeling of solidarity and shared feminist values was central for safe spaces for participation, when activism was scaled up, social interaction had to be limited due to increased risk. HCI research views trust as a process of crossing distances, increasing over time; however, our results reveal that trust decreased over time as the movement grew and public exposure increased, a trend most evident when the participants actually came from a tightly knit community. Therefore, this study points out the significance to balance the need for transparency and community with the need for anonymity and distance in the development of tools to support large-scale deliberative processes that involve conflicts and risks.
Conference Paper
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Today’s environment of data-driven business models relies heavily on collecting as much personal data as possible. Besides being protected by governmental regulation, internet users can also try to protect their privacy on an individual basis. One of the most famous ways to accomplish this, is to use privacy-enhancing technologies (PETs). However, the number of users is particularly important for the anonymity set of the service. The more users use the service, the more difficult it will be to trace an individual user. There is a lot of research determining the technical properties of PETs like Tor or JonDonym, but the use behavior of the users is rarely considered, although it is a decisive factor for the acceptance of a PET. Therefore, it is an important driver for increasing the user base. We undertake a first step towards understanding the use behavior of PETs employing a mixed-method approach. We conducted an online survey with 265 users of the anonymity services Tor and JonDonym (124 users of Tor and 141 users of JonDonym). We use the technology acceptance model as a theoretical starting point and extend it with the constructs perceived anonymity and trust in the service in order to take account for the specific nature of PETs. Our model explains almost half of the variance of the behavioral intention to use the two PETs. The results indicate that both newly added variables are highly relevant factors in the path model. We augment these insights with a qualitative analysis of answers to open questions about the users’ concerns, the circumstances under which they would pay money and choose a paid premium tariff (only for JonDonym), features they would like to have and why they would or would not recommend Tor/JonDonym. Thereby, we provide additional insights about the users’ attitudes and perceptions of the services and propose new use factors not covered by our model for future research.
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