Paper Title: Trust: Different Views, One Goal

International Journal of Security, Privacy and Trust Management (IJSPTM) Vol 6, No 1, February 2017
DOI : 10.5121/ijsptm.2017.6101 1
TRUST: DIFFERENT VIEWS, ONE GOAL
Mubarak Almutairi
College of Computer Science & Engineering, University of Hafr Albatin, Hafr Albatin,
Saudi Arabia
ABSTRACT
A thorough review of trust models is carried out in this paper to reveal the key capabilities of existing trust
models and compare how they differ among disciplines. Trust decisions are risky due to uncertainties and
the loss of control. On the other hand, not trusting might mean giving up some potential benefits. Advances
in electronic transactions, mutliagent systems, and decision support systems create a necessity to develop
trust and reputation models. The development of such models will allow for trust reasoning and decisions
to be made in situations with high risk and uncertainty. In recent years, several attempts have been made to
model reputation and trust. However, perceiving trust differently and the lack of having a unified trust
definition are among the main causes of the proliferation of many trust models across different disciplines.
1. INTRODUCTION
Despite its usefulness in both human and artificial societies, trust was and will continue to be a
risky proposition. Trust has been always an integral component of human social life and actions.
The advances in autonomous intelligent systems, communications, and electronic transactions
motivated the execution of research regarding trust and reputation in order to span the spatial and
temporal separation among the partners involved in a social interaction or an exchange of
commodities or goods.
Reputation is used as a means to build and update trust after a certain number of successful
transactions [3, 15, 28, 29, 34, 40, 102]. Anonymity, uncertainty, risk, lack of control, and
potential opportunism are key elements in most online transactions. Using trust evaluation and
models to compensate for the lack of information and control in online environments will allow
one to make decisions in regard to whom to trust and engage within a transaction or cooperative
action. Some of the associated risks with online transactions include the exchange of some
personal information, the absence of the physical goods, the non-immediate exchange of goods
and money, and how secure the transaction media is [8, 41, 42, 54].
Trust is inevitably involves uncertainty. In general, uncertainty is the absence of credible
knowledge about future events. Trust is supposed to assure an agent that the desirable course of
events will be realized in the unknowable future, as if being guaranteed from past knowledge. As
Luhmann [81] wrote, “trust rests on illusion. In actuality, there is less information available than
would be required to give assurance of success. The actor willingly surmounts this deficit of
information”. A trustful person can comprehend new experiences and carry out actions that have
been previously undesirable or unachievable. This is due to the fact that when trusting, in favour
of an inner confidence, one simplifies the complexity of the outer world and removes any
uncertainties.
When trusting, we allow ourselves to be vulnerable to others by depending on them to achieve or
care for something we value. This interdependence relationship occurs when it is in the mutual
benefit for both parties to fulfill their obligations towards the achievement of their common goal.

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In this case, no party has a dominant power over the other. While engaging in a dependence
relationship, none of the parties is willing to exploit its situation. The realization of this
dependency relationship by the trustee will put him or her in a relatively more powerful situation
[81]. If properly used, this kind of power will strengthen the trust relationship. Some trustees
might refrain from using this power to avoid the negative consequences associated with
exploiting the dependent trustor.
Section 2 reviews trust definitions from different disciplines. In Section 3, different approaches to
modeling trust are explained. Section 4 highlights the common shortcomings of the current
approaches to modeling trust and suggests ways of improving them. Some concluding remarks
and insights are given in Section 5.
2. TRUST DEFINITIONS FROM DIFFERENT DISCIPLINES
Different disciplines handle trust differently according to their own perceptions and what fits their
specific goals. In order to consolidate sensible measures of trust, one needs to step back and
analyze why different disciplines view trust differently. What follows is a thorough review of the
existing trust definitions from different disciplines like, Psychology [9, 76, 80, 104, 105],
Sociology [18, 48, 52, 78, 81, 118], Philosophy [6, 32, 63, 68, 101], Economics [25, 57, 85, 124,
130], Finance [45, 61], Marketing [39, 49, 50, 93, 117], Management [51, 69, 82, 88, 91, 123], E-
Commerce [71, 89, 90], and Computer Science [8, 36, 44, 100, 112].
2.1. TRUST IN PSYCHOLOGY
In his 1973 book, M. Deutsch defines trust as confidence that one will find what is desired from
another person rather than what is feared [37]. Many researchers find this definition to be a
specific characteristic of a relationship. Deutsch, however, presents many other aspects of trust in
his 1973 work. He presents trust as being connected to despair, innocence, social conformity,
virtue, gambling, risk-taking and faith, among others.
From a psychological perspective, risk in trust is approached as one of the characteristics of
individuals. While some people are willing to take risks, there are some who are too cautious and
distrustful to take any chances. Trusting behavior depends on how individuals perceive an
ambiguous path or unclear situation. In such cases, the occurrence of a good or bad result is
dependent on other’s actions. Knowing that a negative result is more harmful than a good one, a
trusting decision should be made.
The use of the word “perceive” in the previous paragraph is to emphasize the subjective nature of
trust. If trust is based on individual perception, it is likely that the same situation will be seen
differently by different individuals. Estimates of chances and expected gains or losses are
subjective. Thus, some individuals might make unwise risks, thereby acting as if they are taking
chances while, in fact, they are trusting unwisely.
2.2. TRUST IN SOCIOLOGY
The sociology of trust has been investigated from different angles: rational choices, culture,
functionality, symbolic interaction, and others. Trust is a social relationship subject to its own
special system of rules [81]. Trust occurs within interactions that are influenced by both
personality and social systems [78]. Most sociologists agree with: “the clear and simple fact that,
without trust, the everyday social life which we take for granted is simply not possible” [52, p.
32]. We always find ourselves in a condition of uncertainty about and uncontrollability of future

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actions. We have no way of knowing and controlling what others will do independently of our
own actions and we are not even sure how they will react to ours. In general, uncertainty and risk
are integral components of human interactions that can’t be ignored or avoided.
In situations in which we have to act in spite of uncertainty and risk, the third factor that comes to
the fore is that of trust [118]. Trusting becomes a crucial strategy for dealing with an uncertain
and uncontrollable future. Since there is no way of knowing what is in the minds of others, we
need trust to deal with an unknown future and others’ uncontrollable actions.
When participating in uncertain and uncontrollable conditions, we take risks, we gamble, and we
make bets about the future and the actions of the others. A simple and general definition of trust
is: “trust is a bet about the future contingent actions of others” [118, p. 25]. In this sense, trust
consists of two main components: beliefs and commitments. First, it involves specific
expectations: “trust is based on an individual’s theory as to how another person will perform on
some future occasion” [52, p. 33]. When placing trust, we behave as if we know the future.
Second, trust involves commitment through action or roughly speaking, placing a bet. Thus:
“trust is the correct expectations about the actions of other people that have a bearing on one’s
own choice of action when that action must be chosen before one can monitor the actions of those
others” [48, p. 51]. In order to have a better and deeper understanding of trust, we need to pay
attention to the mental and subjective attitudes of the trusting person. It is important to focus on
what happens in an individual’s mind when trusting someone else.
2.3. TRUST IN PHILOSOPHY
Trust and distrust are subjective attitudes that affect our thinking and feelings [63]. When
trusting, we are more likely to let ourselves be vulnerable to others and allow ourselves to depend
on others. Trust is a cooperative activity in which we engage so that we can assist one another in
the care of goods [6]. We trust others when we afford them the opportunity to care for something
we value. We trust things as well as people. While trusting things is based on the properties of the
things that we know in advance, trusting people is based on past experiences. When we trust, we
hold expectations toward another person. To expect is to look forward to something without
anticipating disappointment. When holding expectations of another, we project into the future,
making an inference about the sort of person someone is going to be in the future. When trusting,
the expectations alone are not enough but we must anticipate that the other has good intentions
and the ability to carry out what is expected of him or her.
In order to trust someone, we need to have a sense of his or her values. A person who lacks
commitment to any values or principles doesn’t give us the ability to predict either good or bad
intentions or treatment. Knowing the other’s values, commitments, and loyalty will help us to
decide to what extent risk would be involved if we count on that person. We trust others more
fully when we believe that they have positive feelings towards us personally and not just as
members of some group. Trust is a risky business because people whom we trust can let us down
and we are vulnerable to harm when they do so. It is important to accept the risks of trust and try
to handle them rather than taking the simplistic view that trust is always good. Sometimes we
trust too easily and risk a great deal in doing so [32, 63]. Our trust is generally based on
experiences with other people. On the basis of those experiences, we construct a characterization
or picture of them but in reality they are free agents with different characterizations that go
beyond our beliefs about them.

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2.4. TRUST IN ECONOMICS
The study of trust and reputation in a free economy tries to address the relationship between trust
and competition. By supplying quality goods at competitive prices, firms are building good
reputations in order to secure their future market position and share. Firms will refrain from being
concerned about the short-term profits when compared to building a good reputation and long-
term profits thereafter.
In free-markets economy, consumers are faced with the dilemma of getting quality good for the
least prices from profit-maximizing entities (firms). The trade-off between the price of goods and
their quality is bridged by means of good reputation and trust between the consumer and the
goods’ providers. Some of the pioneers in this field are [26, 27, 47, 65, 66, 77, 103, 114, 116,
120, 121].
2.5. TRUST IN FINANCE
The allocation of financial resources to certain activities includes buying assets, investments, and
loans. These activities, and all financial activities, in general, are associated with some risk and
uncertainty due to one of the involved parties not honoring his or her obligations. For example,
borrowing money for a specific investment is highly related to the future ability of the borrower
to pay back the loan. This highly depends on the trustworthiness and the associated evaluation of
risks. Jensen and Meckling [70] strongly believe that trust, reputation, and social bonds will
always be present in such interactions. The formation of trust and what factors would affect it
were a topic for research in finance. Hart [64] studied trust within agency theory. Others, like
Shapiro and Stiglitz [115], investigated the ethical side of trust in terms of the reliability of one of
the parties. This required importing some of the sociological concepts such as social capital and
social networks [55, 56, 57, 58]. Guth and Kliemt [62] analyzed the evolution of trust in a simple
game of trust between a buyer and a seller.
2.6. TRUST IN MARKETING
Studying trust relationship between a marketer and a customer is a key factor in the relationship
between the two. Most of the research in this area focuses on the customer’s trust [93]. The
research of trust in marketing dates back to the 1970s. Establishing a high level of trust in a
marketing relationship allows the two parties to focus more on long lasting term benefits [49].
Some of the developed marketing theories are based on trust [93]. Trust could assume different
phases like, the trust between the firm and its marketers [119], the marketers and the customers,
and the customers and the firm [113]. These three trust phases interact and affect each other one
way or another [93]. This explains why most marketing researchers have included trust in their
relationships channel models where a vendor provides a service or a good to a distributor who
resells it to the end user [50].
2.7. TRUST IN MANAGEMENT
Different parties within an organization need to work together to accomplish specific goals at
both the personal and the organizational levels. This often requires some teamwork and
dependence on others to execute certain assigned tasks. Risk will be always present in such
relationships due to a lack of knowledge to do a specific task or the unwillingness to do it [88].
The presence of trust will reduce the risks associated with group interactions. However, some of
the problems associated with trust in such environments are: lack of a specific definition of trust,
difficulties of defining the boundaries of each task, lack of well defined regulations governing the

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interactions between the different inter-organization parties, and the unclear relationship between
trust antecedents and consequences. There are some studies suggesting that trust is highly
influenced by factors of which some are individual and others are organizational. In his 1998
work, Doney and Cannon [39] suggested that social values and norms, besides behavioral
attitudes, are key factors in trust. The length and the type of the relationship between the different
parties within an organization and between the different organizations, the presence of previous
interactions, and the interpersonal relations, if any, are other factors suggested by Inkpen and
Currall [69]. Gill and Butler [51] focused on the presence of some personal knowledge or quality
for fulfilling some delegated tasks. Therefore, they define trust as an elaboration from current
qualities as the most reliable for attaining a future goal. Some hidden factors or mental processes
could be accounted for in explaining the high levels of trust for entities interacting for the first
time [91]. Trust leads to some interdependencies which will eventually involve some sort of
sharing of the control and management of things we care for [69]. Nevertheless, trust has not been
appreciated enough within the management field. This is in part because managers didn’t devote
sufficient time, energy, or resources to creating it within their organizations or because they look
at it as a matter of strategic choice [123].
2.8. TRUST IN E-COMMERCE
Trust in electronic transactions goes beyond risk and uncertainty to include other factors like lack
of information, lack of control, ease of use, privacy and security issues [13, 31]. On-line
transactions and exchange relationships are not only characterized by uncertainty, but also by
secrecy, lack of control and potential fraud, thereby making risk and trust crucial elements of
electronic commerce [21].
The process of buying over the internet being perceived as risky, presents numerous risks for
consumers during and after the transaction itself. Online firms may be located in different
locations of the country or even in different countries. This requires a non-immediate exchange of
information, goods, and money. As a result, some sensitive information is exchanged online like,
personal and financial information. The limited history about the seller prior to the interaction
adds to the risk and uncertainty involved in this transaction [8].
Some of the system-dependent uncertainties go beyond the control of the parties involved in the
transaction. These are environment related uncertainties which could be characterized as
exogenous. Generally speaking, the concept of exogenous uncertainties refers to the uncertainties
of the world [67]. The environment dynamics and system complexity are two main factors when
considering exogenous uncertainties. In the context of electronic commerce, exogenous
uncertainty relates to the potential technological errors or security gaps that can’t be avoided [10,
11, 12]. The utilization of encrypted transactions, firewalls, authentication mechanisms and
privacy seals are means of reducing the effects of system uncertainties [100]. Transaction-specific
uncertainties are caused by decisions of parties exchanging information over the transaction
media. The consumer may interpret the uncertainties as seller’s potential behavior in the
transaction process. In computer mediated transactions, element of personal interaction like body
language, gestures, and facial expressions are eliminated.
In general, the more trust present in a given situation, the less additional information is needed to
make a certain decision. On the other hand, if there is little or no trust, there will be a need for
complete information in order to reduce system-dependent and transaction-specific uncertainties.
Uncertainties are perceived differently and, hence, the level of the perceived uncertainties
influences the needed balance between trust and information [122]. Trust and additional
information could be seen as means to reduce uncertainties [81, 123].

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2.9. TRUST IN COMPUTER SCIENCE AND INFORMATION SYSTEMS
Computer scientists tried to formalize the measures of knowledge derived from sociology and
psychology into agents’ architectures. One can understand trust as an attitude of an agent who
believes that another agent has a given property. Therefore, one can analyze the meaning of trust
as a function of the attributed properties [46]. For instance, the property may be that the agent one
trusts fulfills his obligations, like the case of a buying agent. Properties one considers are the
ability of the agent to do the job, to make decisions, or just to deliver information [36].
With the emergence of electronic commerce, trust issues became important for many people.
Generally speaking, it is agreed that in order for electronic commerce to become successful, most
people have to trust it. The person's trust in a transaction is determined by the trust in the counter
party and the trust in the transaction media based on the assumption that party and media trust
supplement each other. If there is not sufficient party trust, then the media trust and its control
protocols should be brought in to supplement the party trust [38]. Trust in the counter party can
be defined as "The subjective probability by which an individual A expects that another
individual B performs a given action on which its welfare depends" [45, p. 56]. According to this
definition, it could be argued that trust has both objective and subjective attributes. The first
depends on the media structure, such as the functionality of the control mechanisms in place. The
second depends on personal experiences in dealing with a specific party, or with specific
procedures and control protocols.
2.10. TRUST AS A GLOBAL VIEW
Gambetta (2000) attempted to gather different thoughts regarding trust from many areas [5, 48].
The most important aspect of their work is the use of values. On the other hand, using explicit
values for trust can be problematic due to the subjectivity of trust in which the same value could
be seen differently by different agents. Yet the use of values for measuring trust allows one to talk
more precisely about certain circumstances or behaviors concerning trust. Also, it permits a
straightforward implementation of the formulation.
In his research, Gambetta [48, p. 217] defines trust as “a particular level of subjective probability
with which an agent assesses that another agent or group of agents will perform a particular
action both before he can monitor such action or independently of his capacity ever to be able to
monitor it and in a context in which it affects his own action”. This definition excludes certain
aspects which are important to trust like referring only to the trust relationship between the agents
themselves and not, for example, the agents and the environment. It also excludes those agents
whose actions have no effect on the decision of the truster, despite the fact that trust is present.
An interesting point in Gambetta’s work is the concern regarding competition and cooperation. In
some cases, cooperation is not good, such as the cooperation among thieves or drug dealers, while
it is very desirable among policemen. Then, it is beneficial to find “the optimal mixture of
cooperation and competition rather than deciding at which extreme to converge” [48, p. 215]. In
competitive situations, cooperation is of great importance since “even to compete in a mutually
non-destructive way one needs at some level to trust one’s competitors to comply with certain
rules” [48, p. 215]. Despite the importance of using values for trust, Gambetta didn’t develop the
idea in any concrete fashion [86].
3. APPROACHES TO MODELING TRUST
Different approaches have been used in an attempt to model trust, of which some have
commercial applications and others are only meant for academic purposes. Some of these

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modeling attempts are only informative while others are conceptual. In the following sections,
different approaches for modeling trust are classified based on their underlying methodologies.
3.1. SIMPLE SCORING
Considered a relatively simple approach, some basic mathematical operators like, multiplication
and addition, are used to compute trust values. The average and the weighted average are the two
most common methods in this category. Getting direct ranking or feedback from the users and
then averaging all the responses is a simple and intuitive way of the many techniques used in e-
commerce [3]. A slightly modified version of this technique is being used in e-Bay [40]. Both
positive and negative scores are summed separately and then subtracting the total negatives from
the total positives to get the overall score. The values often used are 1, 0, and -1 for the positive,
neutral, and negative ratings, respectively. In some cases, the weighted average is being
implemented to put more emphases on the most recent transactions or to highlight some factors
more than others.
3.2. STATISTICAL
When using this technique, a history of all previous interactions is maintained. This history is
combined with the new interactions to compute the overall trust value using statistical
approaches. The most common approach is Bayesian. The Bayesian system takes a binary input
and utilizes the beta-Probability Density Function (PDF) to compute the updating. Within the
PDF distribution, the two parameters ( ,
α β ) refer to the positive and negative ratings,
respectively [72, 74, 95, 97, 125].
The Bayesian system starts with 1 assigned to both parameters and keeps updating after each
interaction. While this provides a sound theoretical basis for computing a trust value, it might not
be easily understood by average users.
3.3. LINGUISTIC
Sometimes, it is easier describing the level of trust using some linguistic terms rather than
numerical values. Using fuzzy or probabilistic approaches, those linguistic terms could be
matched with appropriate or approximated numerical values that are easy to calculate and
program. Al-Mutairi et al. [2] used the linguistic terms absolutely low, very low, low, fairly low,
medium, fairly high, high, very high, and absolutely high to describe the trust level. This enables
the agent to calculate the trustworthiness of another agent before engaging with it in an
interaction. Fuzzy logic is used to match those linguistic terms with approximated values to carry
on some computations and obtain the overall expected trust value. This also depends on some
other factors like the importance of the interaction for a specific agent, the expected value, the
availability of other alternatives, and the risk attitudes of the agent.
3.4. COGNITIVE
This technique tries to mimic the human way of thinking and reasoning about trust. It attempts to
go beyond sensible things and explore what transpires in the mind of one when trusting [7]. This
is highly linked to one’s belief and social community. For an inner feeling or confidence one may
or may not trust another person. The thresholds of what is trustworthy or not will be different for
different agents. Some authors [73] use the belief theory to predict a trust value. Belief theory is a
framework based on probability theory where the total of the probabilities doesn’t necessarily add
up to 1. This is in part due to the presence of some uncertainties. It is important to mention that

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transitivity is an underlying assumption in most of the models in this category where an agent is
considered as trustworthy if referred to as trustworthy by other agent or agents.
3.5. FUZZY
When using fuzzy logic to evaluate trust, it is possible to refer to trust using a linguistic label that
describes a specific fuzzy function rather than using numerical values. The trust level can have
different memberships to different fuzzy sets like belonging to trustworthy and very trustworthy
with memberships of 0.4 and 0.6, respectively. The models proposed by Al-Mutairi et al. [2],
Manchala [84], and Sabater and Sierra [106, 107, 108] are good examples of this type of
modeling.
3.6. FLOW CHAINS
The main assumption underlying in this category of models is transitivity. By that, one means that
if agent a trusts agent b, agent b trusts agent c, then agent a must trust agent c. It could be as
simple as an interaction between three agents or through long chains and loops of iterative deals.
However, it could be the case that trust values from different agents are assigned different
weights depending on the previous history of that particular agent. More interaction chains
through a particular agent means higher trust value and vice versa [4]. In web semantics, the more
hyperlinks to a site the higher its rank and more hyperlinks out of that page the less its rank [14,
99]. Makino [83] used the same concept to calculate the reputation based on the number of
citations in a research environment.
4. DISCUSSION
Table 1 shows a chronological summary of some of the existing work in trust modeling. From
this extensive review, one can highlight the following issues for further investigation when
modeling trust.
4.1. UNRATED TRANSACTIONS
Though sighted as one of the most common ways of evaluating the rules of trust, feedback is not
always given for all transactions [102]. This is in part due to the following:
• Lack of incentive (no direct benefits of providing feedback).
• Retaliation from the seller or service provider in response to negative feedback.
• Competition for a limited service or commodity.
• Feedback mechanism is lengthy or not easy to use.
• Ignorance.
Thinking of feedback as only being important in case it is negative (a way of warning others)
while neglecting the positive ones could give a misleading trust value. For example, on e-Bay,
assume that only 50 out 1000 transactions are assigned a negative feedback (the remaining 950
are positive). The score will be 950 when all transactions are given a feedback while the score for
the same seller will be 750 if only 800 out of the 950 positive transactions are reported. This will
cause the positive feedback ranking for this seller to drop from 0.95% in the first case to only
0.75% in the second case.

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4.2. MISLEADING FEEDBACK
Feedback could be misleading when, for some reason, it is unfair or not justified whether they are
positive or negative [34]. Some of the sited reasons for having a false positive feedback are:
• Reciprocation: a positive feedback for a positive feedback in return.
• Being rewarded with a discounted price.
• Building a good reputation through prearranged fake interactions.
• In contrast, false negative feedback could be due to:
• Based on a specific identity of a specific agent whether it is because of a previous
interaction history or personal reasons.
• Blaming the seller or the service provider for a shortcoming on behalf of the buyer or the
service recipient.
• Reasons that are beyond the control of the seller which could be related to the transaction
media or the delivery system.
The process of providing feedback is a very subjective issue that is hard to monitor and control
[92].
4.3. IDENTITY VERIFICATION
One of the risks associated with electronic environments is verifying that an agent is what he or
she is claiming to be [128]. Some of the identity associated risks are:
• Stolen verification information (username and passwords).
• Identity change to escape from a past transaction history.
• Validating the information supplied during the registration process.
Based on the assumption that trust is the result of acquired cumulative reputation over a period of
time through a number of interactions, not being able to verify the agents’ identities will give a
misleading trust index [23].
4.4. BEHAVIORAL CHANGES
When showing good intentions, regardless of the current low trust index, agents need to be given
a chance to recover and start a corrective process [74]. An agent might start with a low trust index
for one or more of the following reasons:
• Focusing on the short term benefits and not worrying about a long lasting one.
• Lack of knowledge about the importance of building a good reputation on the virtual
environments.
• Reasons that are related to the transaction media which is beyond the control of the agent.
• Change of the service provider’ management in order to recover from the current
situation.
• Change of the service type or product.
• Behavioral changes over time.
Giving more weight on the most recent transactions, like for the past six months or last year
without entirely neglecting the past interactions [16, 17], will give a more reflective index of the

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agent’s current situation. This will also allow one to analyze any behavioral trends over a period
of time.
5. SUMMARY
From this extensive review, one can appreciate the importance of trust across many disciplines.
However, trust research is still in its early stages and varies greatly depending on the trust context
and use. Most of the models are based on feedback through direct interactions or conveyed
through a third party. Though agreeing on the importance of direct experiences, there are more
factors that contribute to trust that should be taken into consideration. By its nature, trust is
complex, multidimensional, and subjective. It might be time to merge traditional game theoretic
approaches with cognitive, sociological, and psychological ones in order to better understand and
model trust. Due to the variations in defining and using trust, as of now, there is no single set of
unified trust data that could be tested and compared among the different trust models. Testing and
comparing trust models are still an arbitrary issue. Developing test data sets and general test
frameworks will enable fine tuning and improving some of the proposed models. It will also
allow researchers to examine which model works better for which uses.
Table 1. Chronological Summary Of Existing Trust Models.

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Table 1. (continued)

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