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stakeholders; a negotiation is required so that the concerns can be ranked. The process
starts by analysing two concerns to identify the dominant one, then take this and
analyse it with a third concern and so forth until we have taken into consideration all
the concerns. The result is the concern with higher priority between them all. Next the
process is repeated to identify the second dominant concern among the remaining
concerns, and so forth until we have a dependency hierarchy between all the concerns.
Moreira et al. [17] and Rashid et al. [18] use a similar idea, by assigning weights to
those aspects that contribute negatively to each other. Weighting allows them to
describe the extent to which an aspect may constrain a base module. The scales used
are based on ideas from fuzzy logic. Again, concerns contributing negatively to each
other and with the same weight with respect to a given base module require explicit,
but informal, negotiations with the stakeholders.
The main limitations of these approaches are:
(1)
each concern must be allocated one single different importance using intuition;
(2)
conflict handling is based on one criterion, the importance, not considering
other parameters that may have an impact on the decision;
(3)
different stakeholders may have different interests on the same concern, and
the relative importance/power of each one might be different (so their relative
position might have to be taken into account);
(4)
trade-offs must be negotiated informally with the stakeholders without any
rigorous and systematic analysis technique or tool.
It was with these limitations in mind that we started exploring rigorous alternatives
that could be used effectively without having to rely so strongly on a single criterion
(importance), taking into consideration other possible useful information collected
during the application of the methods.
The informal process discussed in the current approaches, may lead to wrong
decisions, especially in situations where several different stakeholders have different
expectations on the same system and the number of potential conflicting aspects is high.
Moreover, there are other criteria that have an impact on the decision and which are not
usually considered, as we will discuss in Sect. 4. Therefore, guaranteeing that the
solutions being suggested are as good as possible, or finding the combination that better
satisfies the stakeholder goals, may turn into a complex process. For example, to increase
the number of clients being served simultaneously, to reduce the time of response and to
improve the security access, may require a difficult analysis of trade-offs. So that we
consciously know how much we are able to give up to get a little more of what we want
most, we need rigorous tools that help us deal with these type of problems.
The main goal of this paper is to address this issue, by investigating the advantages
of using MCDM methods to help in this difficult process. Given that several factors
may have a different, sometimes opposite, impact on the end result, MCDM methods
seem adequate for this job because they provide a mathematical framework to handle
subjective judgments in conflicting situations.
3 MCDM: An Overview
MCDM (Multiple Criteria Decision Making) models aim at supporting decision
makers to solve conflicting situations [21]. The MCDM field is usually divided into
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