=Paper=
{{Paper
|id=None
|storemode=property
|title=
A Trust Ontology for Business Collaborations
|pdfUrl=https://ceur-ws.org/Vol-933/pap5.pdf
|volume=Vol-933
|dblpUrl=https://dblp.org/rec/conf/ifip8-1/FatemiSW12
}}
==
A Trust Ontology for Business Collaborations
==
https://ceur-ws.org/Vol-933/pap5.pdf
A Trust Ontology for Business Collaborations
Hassan Fatemi, Marten van Sinderen, and Roel Wieringa
Information Systems (IS) Research Group,
Electrical Engineering, Mathematics and Computer Science (EEMCS) Department,
University of Twente, Enschede, The Netherlands
h.fatemi@utwente.nl, m.j.vansinderen@ewi.utwente.nl, roelw@cs.utwente.nl
Abstract. There are currently some ontologies of business collabora-
tion that facilitate automated collaboration, such as e3 value, REA, and
BMO. However, these ontologies model the situation that all business
actors can be trusted. This is not true in practice. To realize automated
business collaboration, trust needs to be added to the business ontology.
In this paper, we extend the e3 value ontology with the concept of trust
and show how this can be used to reason about trust on actors in a busi-
ness network. We take a minimal approach, i.e. rather than adding all
the nuances of the concept of trust, we provide the minimal extension
that allows an actor to reason about trusting other actors in a useful
way. We end the paper with a discussion of how this approach can be
generalized to other approaches.
1 Introduction
Nowadays, the networks that enterprises operate in, become increasingly com-
plex. There are many reasons for this. Among others we can refer to more ad-
vanced user needs, upward tendency toward specialization, changing customer
demands, higher customer satisfaction criteria, advancement in information and
communication technology (ICT), globalization of markets and manufacturing,
increasing competitiveness, exposure to a bigger audience, etc. In fact, collabo-
ration of different enterprises to co-produce a product or service is nothing new,
however, here in this paper, we focus only on those business collaborations which
are facilitated by ICT. In other words, we are concerned with the design and use
of IT in IT-enabled business collaborations.
A collaborative network is a network consisting of a set of autonomous actors
(e.g. enterprises, organizations and people) that collaborate to achieve common
or compatible goals [1, 2]. Collaborative networks come with different names in
the literature, such as business webs [3], Virtual enterprises (VE) [4, 5], extended
enterprises [6, 7], strategic alliances [8, 9], value constellations [10–12], to name a
few. The common theme among all these names is the alliance of some business
actors - which often involves technology transfer (access to knowledge and exper-
tise), economic specialization, shared expenses and shared risk [9] to co-produce
value with each other.
In a collaborative network each enterprise contributes with its own specific
products or services to satisfy the consumer need. The model which shows the
2
creation, distribution, and consumption of goods or services of economic value
in such a network is called value model. The main goal of the value modeling
is to reach agreement amongst profit-and-loss responsible actors regarding the
question ”Who is offering what of value to whom and expects what of value
in return?” It also enables the actors to assess their potential profitability in
the collaborative network and develop an insight into the economical viability
and sustainability of the whole collaborative network. The value model assumes
that all partners in the business web behave in accordance with the rules and
promises expressed in it (they do not act opportunistically). However, the risk in
any business network is that a partner will not behave according to the rules and
promises and act in favor of its own goals, to the detriment of other partners’
goals. This forces a business to take appropriate and sufficient measures against
those who it does not trust, i.e. who may not live up to its commitments.
In fact, for doing any business in the real world, trust is crucial for the success
of the business, because, after all, we need to trust at least some actors, such as
a bank or other trusted third parties. This basically means trust is an inevitable
concept in business collaborations. Here in this paper we propose an ontology
for business collaborations by enriching the e3 value ontology with trust and risk
related concepts.
The rest of the paper is organized as follows. First, in section 2, we discuss
the related work and then in section 3 we briefly introduce the e3 value business
ontology/methodology. After that, in section 4, we introduce a trust ontology
for business collaboration settings based on the e3 value business ontology. We
conclude the paper in section 5.
2 Related Work
An ontology is defined as ”a specification of a conceptualization.” [13]. It specifies
the concepts and the relation between the concepts of a specific domain and they
play an important role in knowledge sharing in the specific domain.
In [14], Akkermans and Gordijn introduce the e3 value ontology and discuss
about the necessity of ontologies for scientific research. Baida et al. [15] developed
a multi-actor business model for e-service bundles by ontology-based analysis of
e-service bundles in networked enterprises. However, their model represent an
ideal situation that lacks the trust related issues.
Andersson et al. [16] represented a reference ontology for business models
based on three business ontologies - the REA, e3 value, and BMO. The core
concepts in the REA [17, 18] ontology are Resource, Event, and Actor and it
claims that every business transaction can be described as an event in which
two actors exchange resources. The Business Model Ontology (BMO) [19] aims
at providing an ontology that enables us to describe the business model of an
enterprise accurately and in detail by considering a single enterprise and its
environment which faces a particular customer’s demand. Surprisingly non of
these ontologies consider trust related concepts.
3
Chang et al. [20] presented the ontological representation of agent trust, ser-
vice trust, and product trust in e-service environments. The work presented here
is similar to the general service/product ontology of Chang. The main difference
is that Chang et al do not look at service and product provision necessarily from
a business point of view and consequently they do not include financial risks in
their ontologies. They also do not discuss about the source of trust and the way
in which trust develops. Schmidt et al. [21] also proposed a number of ontologies
to formalize and facilitate autonomous interactions between intelligent agents
in centralized and decentralized e-business environments however they also do
not consider the financial perspective and consequences of trust in the business
collaborations.
Haung and Fox [22] try to formalize the semantics of trust and study the
transitivity of trust. From the formal semantic, they identify two types of trust
- trust in belief and trust in performance and formally prove the transitivity of
trust in the former and introduce some conditions under which trust relations of
the second type can be propagated. Viljanen [23] surveys and classifies thirteen
computational trust models by nine trust decision input factors and creates
a comprehensive ontology for trust to facilitate interaction between business
systems. Later in the paper we analyze our proposed business trust ontology
against those nine factors.
3 E 3 value Business Methodology
The e3 value methodology [12] is a tractable and lightweight methodology to
explore the innovative e-business ideas - starting from understanding which en-
terprises and actors are actually involved, to an assessment of profitability for
each enterprise.
An e3 value model consists of a graphic part and a computational part. The
graphic part is a diagram and the computational part is a spreadsheet with al-
gorithms that can perform Net Present Value (NPV) estimations for the partic-
ipating actors to assess their potential profitability in the business collaboration
over a specific period. In the e3 value methodology, we model a collaborative
network as a graph in which the nodes represent economic actors and the edges
represent economic value transfers. In addition, an e3 value model shows how a
consumer need is met by a set of economic exchanges between actors in this web
[12, 24, 25].
3.1 E 3 value Ontology
Consider the simple e3 value model (Figure 1) in which Buyer gives Money to
Seller and receives Good in return. Seller, in turn, gives Money to Transporter
and receives Transport. This simple model illustrates the following modeling
constructs of e3 value:
– Contract Period. A value model describes economic exchanges during a spe-
cific period of time, which is called contract period. The contract period
4
Fig. 1. A simple value model
should be specified in supporting documentation and the model will be used
to analyze economic sustainability during this period only.
– Actor. An actor is an independent economic (and often also legal) entity
with a specific interest in the collaboration (making profit, increasing utility,
earning experience, ...). Actors in Figure 1 are Buyer, Seller and Transporter.
The actor for whom the business web is made to satisfy his needs is called
the consumer. We represent the consumer need by a bullet placed inside this
actor (Buyer in Figure 1).
– Value Object. A value object is a service, good, money, or experience, that is
of economic value to at least one actor and that is exchanged between actors.
In our example value objects are Money, Good, Money and Transport.
– Value Port. An actor uses a value port to provide or request value objects
to or from other actors. A value port is a conceptual construct indicating
that during the contract period, an actor is capable of giving or receiving a
value object. Value ports are represented by small triangles on the edge of
the shapes representing actors.
– Value Interface. Value interfaces group value ports and indicate atomicity: if
one value port in the interface is triggered in the contract period, all of them
are triggered in this period (however the model makes no statement about
when this will happen: this has to be specified in a corresponding coordina-
tion model). Value interfaces are represented by oval shapes surrounding the
value ports.
– Value Exchange. A value exchange is used to connect two value ports with
each other. It represents one or more potential trades of value object in-
stances between value ports.
– Value transaction. The concept of value transaction is used to aggregate
all value exchanges between two actors to indicate that all value exchanges
should occur or none at all.
– Market Segment. A market segment is a set of actors that assign economic
value to objects equally. They are shown as overlapping rectangles.
– Dependency Path. In most cases an actor has multiple value interfaces and
these value interfaces can be related. A dependency path connects value
interfaces of the same actor together, meaning that if one of the value in-
terfaces is triggered the connected value interfaces also must be triggered
[12]. A dependency path consists of dependency nodes and connections. A
dependency node is a consumer need, an AND-fork (the sign in the actor
Seller ) or AND-join, an OR-fork or OR-join, or a boundary element (Bull’s
5
eye sign). A consumer need is the trigger for the transfer of value objects. A
boundary element models that no more value transfers can be triggered. A
dependency is represented by a dashed line.
– Transaction. A transaction starts when the consumer need triggers and com-
pletes when all the value exchanges connected to that consumer need are
triggered.
Figure 2, which is taken from [14], depicts the e3 value ontology for networked
business models. Obviously, there is no notion of trust in the e3 value ontology.
Consequently, the profitability analysis of the e3 value ontology is based on an
ideal situation in which all actors are assumed to act trustworthy.
In e3 value methodology, after modeling a business case, the value model is
attributed with quantitative estimations (for example, the number of consumer
needs per contract period and the monetary values of exchanged objects) and a
contract period. Then, the revenue of each actor in the specified contract period,
is estimated by subtracting the amount of money which the actor loses from
the amount of money which he earns during that period. Strictly speaking, the
amount of money that a business actor loses in a specific period, is the amount of
the monetary value of all value objects which he provides for other actors during
that period and likewise, the amount of money that a business actor earns in a
specific period, is the amount of the monetary value of all value objects which
he receives from other actors during that period.
The result of this simple calculation is the first indication whether the model
at hand can be economically profitable for each actor or not. However, even if
the results show a profitable collaboration for all actors, it does not necessarily
mean that the collaboration would be profitable in the real world. Because, this
calculations are based on the assumption that all business actors are trusted and
they all respect the agreements. Hence, to refine the profitability analysis and
to make the calculations more precise, we need to drop the trust assumptions
and then refine the profitability analysis by taking trust into account.
4 Trust Ontology for Business Collaboration Settings
Trust is a ubiquitous phenomenon in everyone’s life. For example when we cross
a street we trust the drivers to a certain extent that they follow the traffic rules.
Trust exists inherently and latently in all our actions that we might even not
be fully aware of that. This is the reason why it is overlooked in many cases
and most of the time, people take it for granted. Nevertheless trust has a major
impact on our decisions.
In business settings, trust plays even a more important role because in con-
trast to the social settings in business settings a misplaced trust might result
in financial loss and after all, financial profit is the main thing that matters in
business settings. Hence, we need to identify the trust factor and evaluate the
financial risks that it might create and be fully aware of them before making a
decision in the business collaborations. Nevertheless, trust is inevitable and in
6
Fig. 2. The e3 value ontology for networked business models
doing any business activity, actors need to trust some other actors and as Ken-
neth J. Arrow [26, page 24] pointed out without trust no market could function
and there is an element of trust in every transaction. In addition, as Luhmann
[27] indicated trust reduces the complexity of interactions.
Here, we aim at designing a meta-model for trust ontology in business collab-
orations. To do that, we use the practical recommendation of a noble sociologist,
Howard Becker [28] for designing middle-range theories and hypotheses in sci-
entific research, which is describing case-study conclusions in an abstract way
without referring to a specific case. This enables us to capture and articulate the
core of the business case in more generally valid formulations.
Our goal is to extend e3 value ontology with the minimal ontology of trust to
be able to usefully reason about trust in a business network. So, we do not want
to express all possible meanings of trust, nor do we want to add to the literature
on the meanings of ”trust” one more bit of insight. We simply want to extend
the e3 value ontology to make it more realistic in the intended settings, that of
business networks.
By analyzing different business interactions in different case studies and also
by studying the existing trust ontologies we identified the major trust related
concepts in business collaborations. Then, by delineating the relations between
those concepts, we developed a lightweight ontology which contains the minimal
set of trust related concepts in business settings. The ontology is shown in Figure
3. The shaded concepts are those of the e3 value ontology and the rest are the new
added concepts. For brevity, we exclude those concepts of the e3 value ontology
7
which are not directly related to new added concepts. According to this ontology,
a trust relation between two business partners is as follows:
A business actor (Trustor) trusts another business actor (Trustee) with a
specific confidence (Confidence value). The confidence value is in the range [0, 1]
and it is calculated based on (1) the reputation (business profile) of Trustee or
(2) direct trust ( past experiences / collaborations between the two actors) or 3)
indirect trust (the value of the trust of other business actors in the collaboration
with Trustee i.e. collaborative trust). A combination of all these three factors is
also imaginable.
In fact, Trustor expects Trustee to accomplish a certain action during a spe-
cific period of time (Time Slot) with agreed upon quality/conditions. In a business
collaboration context, this action is transferring a specific value object (Value
Transfer) with explicit quality specifications in a specified time slot. There is a
risk associated with every trust relation which means in case Trustee does not
fulfill the agreement (transferring the value object with agreed upon quality), it
will result in a financial loss for Trustor. The setting of the relation is described
in the value model of the business collaboration.
The financial losses associated with the trust relations originate from the
value objects and their monetary values. But, how can we calculate the financial
loss associated with each business actor? One way to do it is to investigate
each value exchange and evaluate the financial loss associated with that value
exchange. Each value exchange indicates two business actors that are exchanging
value objects with each other.
The financial loss which a business actor might incur, is the case in which that
business actor receives a value object with less value than what he was expecting
according to the agreements and the worst case is the one in which a business
actor provides his partner with a value object according to the agreements, but
his partner does not give him anything back. This happens because a business
actor trusts another business actor but the trustee acts opportunistically.
The crucial question here is, how often does this happen and consequently
how much loss should a business actor expect during the collaboration? Accord-
ing to the trustor’s expectation, the probability of the trustee to act opportunis-
tically is (1 − T ), where T is the value of trust (confidence value) of the trustor
in the trustee. Strictly speaking, the potential financial loss of a trust relation
is (1 − T ) ∗ V , where T is the value of trust (confidence value) and V is the
monetary value of the agreed upon value object. Here we assume the total loss
of value object V in case the trustor acts opportunistically, which is obviously
the worst case.
In fact, this is not the worst case, because in some cases a business actor in-
vests a considerable amount of money in the collaboration with another business
actor in the hopes of many value exchanges. However, the other actor misuses
the trust early at the collaboration or even at the very beginning and in this
special case the financial loss of the trustor actor would be much more than the
monetary value of the single lost value object.
8
Fig. 3. Trust ontology in business collaborations settings
4.1 E 3 value Ontology Enriched with Trust
After introducing the trust concept, we would like to explain the way in which it
can be used with the e3 value methodology. To do that, we summarize our three
previous papers which deal with the issue of trust in business collaborations.
The first step is to develop a method to assess/calculate and quantify the
trust relations between actors in a business collaboration. To do that, in [29], we
first modeled a collaboration with e3 value methodology and then analyzed the
trust relations between the involved actors. After that, we explained the impli-
cations of trust relations on the coordination patterns and finally we introduced
a method for measuring and managing trust relations between business actors
in a collaborative network.
To measure the value of the trust of the trustor in the trustee, trustor uses
(1) its own opinion based on reputation or past experiences and (2) the opinions
of other direct partners of the trustee in the collaboration, because in case the
trustee has a trust problem with any of its partners, it might break their relation
and consequently the whole collaboration will collapse since the collaboration
works only as a whole. Therefore, it is necessary for the trustor to take the trust
of the direct partners of the trustee into account. For more details regarding
the way in which we identify and measure the trust relations in a business
collaboration interested readers are referred to [29].
After measuring and quantifying the trust relations, the next step is to refine
the profitability analysis by taking trust into account. To do that, in [30], we
analyzed the collaborative networks from endurability and profitability points of
view based on the trust relations between the collaboration partners. The goal
was to provide the partners with value models supplemented by extra informa-
9
tion regarding the endurability and profitability of the collaboration so that the
business actors would be able to decide on those collaborations which are more
durable and profitable.
In [31], we discussed about the financial impact of trust in special value
exchanges that the collaboration is purely based on trust. In those situations, the
trustor trusts the trustee to act according to the agreements and the only way for
the trustor to know about the trustworthiness of the trustee is to run inspections
which cost money. To find a balance between the frequency of the inspections
and the profit of the collaboration for each actor, we used game theory technique
and therefore proposed a new method for adjusting the profitability analysis of
the e3 value methodology in those special situations.
4.2 Discussion
In this subsection we briefly analyze the presented trust ontology (Figure 3) with
those nine trust decision input factors enumerated by Viljanen [23]. Trust in our
ontology is:
– Identity based: Identity of actors is known to each other.
– Action aware: The trustor trusts the trustee with a specific action (reci-
procity in value exchange).
– Business value aware: The financial implications of trust in terms of po-
tential loss or benefit are the major themes in our ontology.
– Not competence aware: We have no specific representation of competence
of an actor to perform the value transfer as promised. Nevertheless we use a
competence in a higher level. We claim that one of the reasons that makes a
business actor trust another business actor in a collaborative network is the
somehow related to competence because if the trustee does not act trustwor-
thy, the collaboration would fail and it will lose the opportunity to another
business actor.
– Not capability aware: In Viljanen’s paper capability is defined as a form
of an access granting token. This is not relevant in our ontology.
– Confidence aware: We explicitly define the strength of the belief that the
trustee transfers the promised value object as confidence value.
– Not context aware: Viljanen defines context as the internal or external
status at a particular point of time. In this sense our ontology is not fully
context aware however we emphasise that the trust relation is valid for a
specific period of time regarding a particular action and in a special business
collaboration setting which is modeled in the e3 value methodology.
– History aware: In our ontology past experiences is considered as one of the
factors in trust calculation.
– Third-party aware: In out ontology the trustor uses the opinion of the
trustee’s direct partners in trust calculation.
10
5 Conclusion
In this paper we discussed about the trust relation between business actors in a
business collaboration and we proposed a lightweight ontology with the minimal
set of concepts for trust in business collaborations. Here we presented the trust
ontology in conjunction with e3 value business ontology however despite their
differences the three main business ontologies (REA, e3 value, and BMO) share
the core concept of value exchange between two business actors and therefore
the trust concept can be added to the other two ontologies analogously.
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