MULTICRITERIA DECISION ANALISYS TO LEAD ABOUT MESSES PROBLEMS: AN
ILLUSTRATED CASE
André Andrade Longaray
FURG - Federal University of Rio Grande, Brazil
E-mail: longaray@yahoo.com.br
Leonardo Ensslin
UNISUL - Universidade do Sul de Santa Catarina, Brazil
E-mail: leonardoensslin@gmail.com
John Robert Mackness
LUMS - University of Lancaster, United Kingdom
E-mail: mackness@lums.edu.uk
Submission: 22/09/2013
Revision: 06/10/2013
Accept: 20/01/2014
ABSTRACT
This
paper shows the use of two approaches in Operations Research - Soft Systems
Methodology (SSM) and Constructivist MultiCriteria Decision Aid (MCDA-C) - into
one decision aid model (SSM/MCDA-C) to lead about messes problems. In order to
this, describes the approaches which give theoretical framework support to the
proposal, MCDA-C and SSM, as well as presenting the SSM/MCDA-C model. There is
also a demonstration of its practical application. Finally, presents the
general theoretical and practical considerations and recommendations with
regard to the integrated problem structuring model proposed.
Keywords:
Decision Aid; Multicriteria Methods; SSM/MCDA-C
1.
INTRODUCTION
This
paper describes how the researchers developed a model to integrate SSM and
MCDA-C to lead about messes problems. The integrated model had three phases. In
the first structuring phase, SSM helped to scope and structure the situation
and smooth the path towards a hierarchical tree structure for use by MCDA-C
with its exploration of situation descriptors. In the evaluation phase, the values
of local preferences and the compensation rates between the descriptors were
determined together with local and global evaluations of the different criteria
used in the model. Finally, using a comparison between different scenarios of
decision-maker performance together with sensitivity analysis, the
recommendations phase led to the development of a really useful decision aid
model for the decision-maker.
Section
one of the paper shows how the SSM/MCDA-C integrated model was developed and
how this contributed to the structuring of the problem of the decision-maker in
question. Section two describes the approaches which give theoretical framework
support to the proposal, MCDA-C and SSM. Section three describes the
methodological procedures of research. In section four, as well as presenting
the SSM/MCDA-C model, there is also a demonstration of its practical
application. Finally section five presents the general theoretical and
practical considerations and recommendations with regard to the integrated problem
structuring model proposed.
2.
THEORETICAL
FRAMEWORK
The
decision aid process for the problematic situation in question was elaborated
based on the theoretical-methodological model developed by the researchers,
which made the integration of the Soft Systems Methodology (SSM) with the Multi
Criteria Decision Aid Constructivist (MCDA-C) (LONGARAY, 2004).
The
MCDA-C methodology originates from the development of the ideas and convictions
proposed by Bernard Roy (1996) (for more details, see ENSSLIN et al., 2010).
Roy (2005) describes a process of an eminently practical nature, based on the
use of knowledge constructed with the user, which requires the participation
and interaction between the facilitator (in this case, the researchers) and the
decision-maker. This results in better understanding about that situation which
for the decision-maker is problematic. MCDA-C is the main decision aid process
and has three phases: the structuring phase, the evaluation phase and the
recommendations phase (BANA E COSTA, 1990).
The
principal objective of the structuring phase of the MCDA-C is to increase
understanding about the problem and of its context (LONGARAY; ENSSLIN, 2013).
In order to achieve this objective, the structuring phase is subdivided into
three steps: the use of a soft approach to understand the complexity of the
decision-making context and the identification of the criteria judged by the
decision-maker as relevant to the context; the hierarchical classification of
the criteria through the construction of a criteria tree; and the construction
of descriptors (ordinal scale). For each descriptor there are different impact
levels, linked to a base criterion, which serves as a reference to describe the
possible impacts of potential actions (alternatives) of that criterion (BANA E
COSTA; VANSNICK, 1995).
The
evaluation phase consists of the development of a multi-criteria model, which
enables the measurement of the performance of both local and global potential
actions. Using the single synthesis criterion method (KEENEY; RAIFFA, 1976),
the MCDA-C evaluation phase develops in three stages: the construction stage of
the multi-criteria model; the local and global evaluation of the actions stage;
and the results analysis stage.
The
purpose of the last stage of a model based on the MCDA-C is to identify
possible actions which come about to help the decision-maker to make good
decisions in relation to the situation which is perceived as problematic. These
actions are specific and individual to each case (ENSSLIN; MONTIBELLER NETO;
NORONHA, 2001).
Of
the MCDA-C phases, the structuring phase is the one which requires great
flexibility in its operation, specifically with regard to its first step, the
use of a soft approach to explore the problem and help the decision-maker to
improve the understanding of the situation. This stage offers the opportunity
for the decision-maker to explore the situation which is perceived to be
problematic without any type of restriction imposed by the use of the
methodology (BANA E COSTA, 1993).
Taking
into consideration current literature, one can say that the MCDA-C approach,
the soft approach of cognitive mapping (EDEN, 1988) has been used in a
significant number of researches (ENSSLIN; MONTIBELLER NETO; NORONHA, 2001).
However, there are other problem structuring soft approaches in operations
research literature, for example Strategic Choice (FRIEND; HICKLING, 1987),
Robustness Analysis (ROSENHEAD, 1989), Hypergame Approach (BENNET; HUXHAM;
CROPPER, 1989) and Soft Systems Methodology (CHECKLAND; SCHOLES, 1999).
Among
these, Soft Systems Methodology (SSM) resonates with the vision proposed by the
MCDA-C methodology, as it postulates that real-world situations are often
perceived by people as complex and confusing and for one same situation, each
observer may make a different reading of the facts, based on that person’s
knowledge, presuppositions and convictions, as well as the influences that this
observer receives from his environment.
As
Checkland and Scholes (1999) states, SSM, enables the exploration, questioning
and learning about complex and badly structured problems. It emphasizes the
possibilities of identifying opportunities for change and encourages the actors
who are involved to understand the diverse inter-relationships, which are
present in a determined decision-making context.
To
achieve its objectives SSM requires the use of certain techniques such as rich
pictures, to characterize the situation which is perceived as problematic;
conceptual models, constructed from human activity systems, identified in the
decision-making context and a list of desirable systemic and cultural actions,
which emerge from the amplified understanding of the problem. The outcome of
this process does not however result in an exact reply to the problem.
As
Checkland and Scholes (1999) points out, in problems of human activity, the
idea of “solution” must be substituted by the understanding that to resolve a
problematic situation, is a process of “knowledge construction”, in which
reality is undergoing constant change and is being continually recreated by the
participants.
The
process of SSM however is to some extent limited in its capability to analyze
the impact of which actions contribute most to achieve the objectives of the
decision-maker. This is because the approach does not include any form of
performance measurement of the various actions which might be made. Therefore,
it is not possible to measure which actions are preferable in relation to
others which also might be options for change. Adoption of a possible action is
carried out by an informed debate rather than a quantitative analysis.
This
paper has as its aim to demonstrate how the increased understanding and
representation of a problem which emerges through the SSM process can be augmented
in a quantitative way by the robustness of the MCDA-C, which runs through all
the phases of the decision-making process.
3.
METHODOLOGICAL PROCEDURES OF THE RESEARCH
This
section discusses the methodological design of the research and classifies the
work as to its purpose, nature, source of data collection, search logic,
methodological approach and the intervention instrument employed.
Regarding
its purpose, the research is classified as an exploratory study. According to
Gil (2002), the main objective of exploratory studies is to develop ideas and
to lead to relatively systematic procedures for obtaining empirical
observations, as well as to enable the identification of the relationships
between the studied phenomena. This perspective is consistent with the
objective of this research.
The
objective is to build an integrated SSM/MCDA-C model to lead about messes
problems.
The
nature of this research is described as a case study. The case study was
conducted in order to help a determined decision-maker to understand, organize
and structure the context and the circumstances which led this person to suffer
from stress, as well to enable the measurement and comparison of the different
options available to improve her quality of life. The person concerned found it
difficult to establish a cause and effect relationship between emotional and
behavioral factors and the physiological manifestations of stress. This was
shown by the development of hyperthyroidism, migraine and teeth grinding
without an apparent organic cause.
As
sources of data collection, this study used interviews, document analysis, and
bibliographic search (GIL, 2002). Unstructured interviews were conducted to
obtain primary data and a survey of documents and bibliographic search was done
as a source of secondary data.
The
search logic adopted was inductive and deductive. It is inductive in the
structuring stage of the model, which does not presuppose the existence of
principles, but of facts and observations resulting from insertion into reality.
It assumes a deductive approach in the evaluation stage, since it is from the
constructed model that particular conclusions are established (GIL, 2002).
Finally, the logic is inductive in the development of the recommendations
stage, since the analyses are based on the understanding gained throughout the
development of the entire model.
The
methodological approach of the study is quali-quantitative. Gil (2002)
advocates the idea of combining qualitative and quantitative methods in order
to provide a richer contextual basis for the interpretation and validation of
research results. From this point of view, the present study is quantitative at
the evaluation stage and qualitative in the structuring and development of
recommendations stages.
The
intervention instrument employed in the study is the SSM/MCDA-C. This
methodology for decision aiding is used because of its ability to provide
conditions for the identification, implementation, and measurement of the
criteria that represent the perception of the decision makers about the
possibilities of evaluating the performance of trade marketing activities of
the company. It also enables the incorporation of improvement suggestions for
alternatives, with a performance profile incompatible with expectations.
4.
SSM-MCDA-C METHODOLOGICAL PROCEDURES TO SUPPORT AN INDIVIDUAL COMPLEX
DECISION
Respecting
the logical order of the steps presented in the previous section and of the
methodological bases of the model, which uses a combined SSM and MCDA-C
approaches (LONGARAY; ENSSLIN; MACKNESS, 2013), this section describes the
personalized decision aid model in three phases: the structuring phase, the
evaluation phase and the elaboration of recommendations phase.
4.1.
Structuring Phase
Initially,
using SSM, the researchers elaborated a soft model of the decision-maker
composed from the rich picture of the problem situation, of the list of
preoccupations, of conceptual models, of the transformation map (Ts) and from
the list of possible desirable and feasible actions.
Table 1 presents a list of preoccupations identified
by the decision-maker in its context of decision, based on the analysis and
legitimation of the rich picture of the context of decision.
Table 1: List of
preoccupations identified by the decision-maker in the analysis of the rich
picture
LIST OF CONCERNS OF THE DECISION-MAKER |
|
RELEVANT SYSTEMS |
COMPONENT CONCERNS |
physical health |
11. have vital organs working well 12. have good aesthics |
mental health |
01. have emotional control 07. have good cerebral capacity |
harmony at home |
06. share home chores 08. administer time at home |
relationship with husband |
03. have life in common with husband 02. have sentimental equilibrium 04. have affective goals |
material comfort |
09. have professional aspirations 15. have economic aspirations |
productivity |
14. administer time at work 05. have control over the situation in the sector in which you work |
harmony at work |
13. get on well with colleagues 10. get on well with the boss |
In
the right hand column of Table 1, it is possible to identify the
preoccupations, which the decision-maker defined as being the most relevant for
the problematic situation, already grouped by a criterion of relationship. In
the left hand column there is the name given by the decision-maker for each
group of preoccupations, which Checkland and Scholes (1999) calls, relevant
systems.
Once
the relevant systems were established, the next step in the construction of the
soft model was the development of the charts with the root definitions and the
CATWOE for each one of these systems. Table 2 shows, as an example, the chart
developed for the relevant system “physical health”.
The
following step was the construction of the conceptual models for each relevant
system, taking into consideration the charts with the root definitions and
CATWOE. A worksheet was developed along the lines presented by Mackness (2002)
as it offers a graphic mode for better visualization of the systems and of the
information, which subsidizes its elaboration, to be utilized as a guide in the
construction of each conceptual model.
Table 2: Root
definitions and CATWOE of relevant system “physical health”
RELEVANT SYSTEM physical health |
||
ROOT-DEFINITIONS |
CATWOE |
|
Concern: 11. have vital organs working well RD: a system to rate the possibilities
of keeping vital organs working well, taking preventive measures, in order to
improve physical health and contribute to the decision-maker to lead a life
without stress. |
C |
decision-maker |
A |
decision-maker, medical professionals in the area |
|
T |
not able to cope with illnesses which affect the nervous, cardiac and
hormonal systems ↓ able to cope with illnesses which affect the nervous, cardiac and hormonal
systems |
|
W |
problems with organs like the heart, affect the quality and expectation
of life |
|
O |
decision-maker |
|
E |
family, work |
|
ROOT-DEFINITIONS |
CATWOE |
|
Concern: 12. have good aesthics RD: a system to rate the possibilities of having good aesthics, by
investing in body care, which improves physical health and assists the decision-maker
to lead a life without stress. |
C |
decision-maker |
A |
decision-maker, sporting and medical professionals |
|
T |
not satisfied with your body ↓ be satisfied with your body |
|
W |
If decision-maker feels beautiful her self-esteem is improved |
|
O |
Decision-maker |
|
E |
work, study, home
chores |
This is filled in with the relevant
system, the preoccupation, from which the conceptual model will be constructed,
the CATWOE, identifying what transformation, (T) should occur, as well as the
systemic layers. Table 3 shows a support worksheet for the construction of the
conceptual preoccupation model “11.have vital organs working well”, of the
relevant system “physical health”.
Table 3: Support
plan for the construction of the conceptual model “11. have vital organs
working well”
RELEVANT SYSTEM: physical health CONCERN: 11. have vital organs working well ROOT-DEFINITIONS-(RD): a system to rate the possibilities of keeping vital organs working
well, taking preventive measures, in order to improve physical health and
contribute to the decision-maker to lead a life without stress. |
CATWOE: C →decision-maker A →decision-maker, medical professionals in the area T →not able to cope with illnesses which affect the nervous, cardiac
and hormonal systems ► able to cope with illnesses of the nervous, cardiac
and hormonal systems W →problems with organs like the heart, affect the
quality and expectation of life O →decision-maker E →family, work |
||||||||||
CONCEPTUAL MODEL
Measured by: E1=
whether there is adoption of reasonable behavior and regular medical
follow up E2=
whether illnesses of the
nervous, cardiac and hormonal system are prevented |
The next stage was to effectively
construct each one of the conceptual models. In order to do this, the steps
suggested by Checkland and Scholes (1999) were followed. Figure 1 shows a
conceptual preoccupation model “11.have vital organs working well”.
Figure 1:
Conceptual preoccupation model “11. have vital organs working well”
Having constructed the conceptual
models for all the preoccupations, listed by the decision-maker, the next step
was to determine which of the possible actions identified in the conceptual
models (for example, in Figure 4, the possible actions are in activity 7) could
be put into place by the decision-maker. Having determined the possible
actions, the use of the soft model was considered as terminated.
The
transition in this case, of the soft model to a tree structure for the MCDA-C
approach was made based on a map which shows how the possible actions from each
relevant system relate to the overall objective – the decision support for the
person with stress. This map contained the seven relevant systems described in
Figure 1 and the possible actions which were thrown up by each conceptual model
for the component concerns for each relevant system.
Table
4 presents the complete criteria hierarchical tree for the MCDA-C, after the
transition process.
Table 4:
Criteria hierarchical tree to problem of the “patient suffering stress” problem
L E A D S A L I V E W I T H O U T S T R E E S |
1.
phisical Health |
1.1
vitals organs |
1.1.1-avoid
risk behavior |
|
1.1.2-have
periodical chekup |
|
|||
1.2-aesthetics |
1.2.1-sporty
activities |
|
||
1.2.2-control
feed |
|
|||
1.2.3-aesthetic
treatment |
|
|||
2.
mental health |
2.1-emotional
control |
2.1.1-professional
support |
|
|
2.1.2-curtailment
strategies |
|
|||
2.2-cerebral
capacity |
2.2.1-rest |
|
||
2.2.2-share
of the activities |
|
|||
5.
harmony at home |
3.1-share
of the tasks |
3.1.1-responsibilities |
|
|
3.2-administration
of the time
in home |
3.2.1-
services of 3°s |
|
||
3.2.2-appliances |
|
|||
3.2.3-chronogram |
|
|||
6.
relationship with
husband |
4.1-
life in common |
4.1.1-leisure |
4.1.1.1-entertainment |
|
4.1.1.2-breakage
of the routine |
||||
4.1.2-social
activities |
|
|||
4.2-sentimental
balance |
4.2.1-complicity |
|
||
4.2.2-negotiation |
|
|||
4.3-affective
goals |
4.3.1-sons |
|
||
4.3.2-
couple’s feeling |
4.3.2.1-time
to the couple |
|||
4.3.2.2-romantic
activities |
||||
5.
material confort |
5.1-professional
aspirations |
5.1.1-languages
course |
|
|
5.1.2-post
graduation course |
|
|||
5.2-economic
aspirations |
5.2.1-provision
for accidental |
|
||
5.2.2-retirement |
|
|||
5.2.3-patrimony |
|
|||
6.
productivity |
6.1- administration of the time at work |
6.1.1-allocation |
|
|
6.1.2-priorities |
|
|||
6.2-control
of the situation |
6.2.1-leadership |
|
||
6.2.2-hierarchical
structure |
|
|||
7.
harmony at work |
7.1-conviviality
with colleagues |
7.1.1-dialog |
7.1.1.1-meetings |
|
7.1.1.2-intervals |
||||
7.1.2-integration |
7.1.2.1-work
in group |
|||
7.1.2.2-confraternity |
||||
7.2-conviviality
with the
boss |
7.2.1-performance
standards |
|
||
7.2.2.control
of the standards |
7.2.2.1-term |
|||
7.2.2.2-results |
||||
7.2.2.3-satisfaction
degree |
After established the transition of
the soft model to a hierarchical
structure, the third stage of the arrangement leads to the construction of
describing elements, which enable the decision maker to measure how much a
potential action could impact upon a determined criterion. In this sense, it
was created ordinal scales for each criterion, with impact possible levels.
The Table
5 presents the impacts levels to “1.1.1 - avoid risk behavior” criterion.
Table 5: Impact
levels descriptor to criterion “1.1.1 - avoid risk behavior”
Impact levels to “1.1.1 – avoid risk behavior” criterion |
||
level |
anchorage |
Description |
N5 |
|
Do not smoke, do not take coffee or another stimulant, do not ingest
drunk alcoholic and to do not do analgesic use and tranquilizing |
N4 |
Good |
Do not smoke, do not take coffee or another stimulant and to do not
ingest drunk alcoholic |
N3 |
|
Do not smoke and do not take coffee or another stimulant |
N2 |
Neutral |
Do not smoke |
N1 |
|
Smoke, take coffee or another stimulant, ingest drunk alcoholic and to
do analgesics use and tranquilizing |
It
was developed possible impact levels descriptors for all the remainder criteria
of the model.
4.2.
Evaluation Phase
The
evaluation phase consists of the development of a multi-criteria model, which
enables the local and global measurement of the potential actions. Using the
single synthesis criterion method (KEENEY; RAIFFA, 1976), the MCDA-C evaluation
phase develops in three stages: the construction stage of the multi-criteria
model (preference scores); the local and global evaluation of the actions; and
the results analysis stage.
The
construction of the local preference scores, usually called value functions,
for the multi-criteria model of the problematic situation, was made based on
the Direct Scoring method. The Measuring Attractiveness by a Categorical Based
Evaluation Technique – MACBETH (BANA E COSTA; VANSNICK, 1995) was used to
determine the compensation rates.
Table
6 presents hierarchical structure of SSM/MCDA-C with compensation rates of
criteria and neutral/good levels anchorage of descriptors to the “patient
suffering stress” problem.
The local and global evaluation
stage of the multi-criteria model was carried out in two steps. The first
defined the profile of the impact of the potential actions (local evaluation)
and the second, the additive aggregation of the criteria (global evaluation) of
the model.
Attending
to the decision-makers’ request, we sought to identify what would be the effect
of different actions. From the moment in which the decision aid process was
initiated, called Performance Profile 1 (PP1) to the end of the construction of
the evaluation model, labeled Performance Profile 2 (PP2).
Table 6:
Compensations Rates and anchorage of descriptors to the “patient suffering
stress” problem
Cluster |
Criteria |
Compensations
Rates |
Levels |
Anchorage |
|||
1.1-
vital
organs |
|
|
|
|
|
||
|
1.1.1-avoid
risk behavior |
62,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
1.1.2-have
periodical check-ups |
38,00% |
N2 |
N4 |
0,00 |
100,0 |
|
1.2
– aesthetics |
|
|
|
|
|
||
|
1.2.1-sporty
activities |
33,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
1.2.2-
control feed |
56,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
1.2.3-
aesthetic treatment |
11,00% |
N2 |
N4 |
0,00 |
100,0 |
|
2.1-
emotional control |
|
|
|
|
|
||
|
2.1.1-
professional suport |
70,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
2.1.2-
curtailment strategies |
30,00% |
N2 |
N4 |
0,00 |
100,0 |
|
2.2-
cerebral capacity |
|
|
|
|
|
||
|
2.2.1-
rest |
33,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
2.2.2-
share of the activities |
67,00% |
N2 |
N4 |
0,00 |
100,0 |
|
3.1-
share of the tasks |
|
|
|
|
|
||
|
3.1.1-
responsibilities |
0,00% |
N2 |
N4 |
0,00 |
100,0 |
|
3.2- administration of the time in the home |
|
|
|
|
|
||
|
3.2.1-
services of 3°s |
55,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
3.2.2-
appliances |
35,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
3.2.3-
chronogram |
10,00% |
N2 |
N4 |
0,00 |
100,0 |
|
4.1-
life in common |
|
|
|
|
|
||
|
4.1.1-
leisure |
75,00% |
|
|
|
100,0 |
|
|
4.1.1.1-
entertaiment |
60,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
4.1.1.2-
break of the rotine |
40,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
4.1.2-
social activities |
25,00% |
N2 |
N4 |
0,00 |
100,0 |
|
4.2-
sentimental balance |
|
|
|
|
|
||
|
4.2.1-
complicity |
42,00% |
N2 |
N3 |
0,00 |
100,0 |
|
|
4.2.2-
negotiation |
58,00% |
N2 |
N4 |
0,00 |
100,0 |
|
4.3-
affective goals |
|
|
|
|
|
||
|
4.3.1-
sons |
72,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
4.3.2-
couple’s feeling |
28,00% |
|
|
|
100,0 |
|
|
4.3.2.1-
time to the couple |
57,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
4.3.2.2-romantic
activities |
43,00% |
N2 |
N4 |
0,00 |
100,0 |
|
5.1-
professional aspirations |
|
|
|
|
|
||
|
5.1.1-
languages course |
67,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
5.1.2-
post graduation course |
33,00% |
N2 |
N4 |
0,00 |
100,0 |
|
5.2-
economic aspirations |
|
|
|
|
|
||
|
5.2.1-
provision for accidental |
12,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
5.2.2-
retirement |
25,00% |
N2 |
N3 |
0,00 |
100,0 |
|
|
5.2.3-
patrimony |
63,00% |
N2 |
N4 |
0,00 |
100,0 |
|
6.1- administration of the time at work |
|
|
|
|
|
||
|
6.1.1-
allocation |
29,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
6.1.2-
priorities |
71,00% |
N2 |
N3 |
0,00 |
100,0 |
|
6.2-
control of the situation |
|
|
|
|
|
||
|
6.2.1-
leadership |
40,00% |
N2 |
N3 |
0,00 |
100,0 |
|
|
6.2.2-
hierarchical structure |
60,00% |
N2 |
N3 |
0,00 |
100,0 |
|
7.1-
conviviality with colleagues |
|
|
|
|
|
||
|
7.1.1-dialog |
54,00% |
|
|
|
100,0 |
|
|
7.1.1.1-
meetings |
33,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
7.1.1.2-
intervals |
67,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
7.1.2-
integration |
46,00% |
|
|
|
100,0 |
|
|
7.1.2.1-
work in group |
55,00% |
N2 |
N3 |
0,00 |
100,0 |
|
|
7.1.2.2-
confraternity |
45,00% |
N2 |
N3 |
0,00 |
100,0 |
|
7.2-
conviviality with the boss |
|
|
|
|
|
||
|
7.2.1-
performance standards |
57,00% |
N2 |
N3 |
0,00 |
100,0 |
|
|
7.2.2-
control of the standards |
43,00% |
|
|
|
100,0 |
|
|
7.2.2.1-
term |
38,00% |
N2 |
N4 |
0,00 |
100,0 |
|
|
7.2.2.2-
results |
16,00 |
N2 |
N4 |
0,00 |
100,0 |
|
|
7.2.2.3-
satisfaction degree |
46,00 |
N2 |
N4 |
0,00 |
100.0 |
|
For
each criterion, for we developed descriptors, the decision-maker defined the
level of the impact which best described its performance in PP1 and PP2. From
the determination of the level of impact, we obtained the local evaluation of
the potential actions PP1 and PP2 for each one of the model’s criteria.
Utilizing the additive aggregation function formula, the global evaluation of
the potential actions was obtained.
As an
example, Table 7 shows the local and global evaluation to PP1 profile.
Table 7: performance PP1
Cluster |
% |
Local Scores |
Global Contribution |
1.1- vitals |
8,00% |
-19 |
-1,5 |
1.2- aesthetics |
7,00% |
-50 |
-3,5 |
2.1-
emotional control |
8,00% |
-65 |
-5,2 |
2.2-
cerebral capacity |
7,00% |
-50 |
-3,5 |
3.1-
share of the tasks |
6,00% |
-50 |
-3 |
3.2- administration of the time in the home |
6,00% |
-32,5 |
-2 |
4.1-
life in common |
9,00% |
-50 |
-4,5 |
4.2-
sentimental balance |
10,00% |
-42 |
-4,2 |
4.3-
affective goals |
9,00% |
-44,8 |
-4 |
5.1-
professional aspirations |
3,00% |
-33,5 |
-1 |
5.2-
economic aspirations |
4,00% |
-62,5 |
-2,5 |
6.1-administration of the time at work |
5,00% |
-85,5 |
-4,3 |
6.2-
control of the situation |
5,00% |
-100 |
-5 |
7.1-
conviviality with colleagues |
7,00% |
-73 |
-5,1 |
7.2-conviviality
with boss |
6,00% |
-78,5 |
-4,7 |
Global Evaluation |
100,00% |
|
-54 |
4.3.
Recommendations’ Elaboration Phase
The
recommendations for the problematic situation are provided as and when the
facilitator requested the decision-maker to authorize any procedure, or even
from requests, which came from the decision-maker herself. These came about
during the decision aid process.
Indeed,
the result of the local and global evaluations enabled the decision-maker to
see that, globally the model performance improved from PP1 to PP2.
Furthermore,
the individual performance analysis of each criterion in PP1 and PP2, made it
possible for the decision-maker to identify in which criteria its performance
could be improved and which of them had already reached a satisfactory
performance.
5.
CONCLUSIONS
This
paper presented the development process of a decision aid model, based on the
integration of SSM to MCDA-C, with the purpose of helping an individual who
suffers from an high degree of stress by identifyimg opportunities to improve
her quality of life. In order to do this, the researchers brought together into
one model, the capacity of the understanding and representation of a problem
made possible by the SSM process, with the robustness of the MCDA-C process.
Given its constructivist orientation, the decision aid process involved the
effective participation of the decision-maker in all its phases.
In
the first structuring phase, SSM was used for the elaboration of the soft model
and the transition from this model to a hierarchical tree structure and the
construction of the descriptors. In the evaluation phase, the local
preferential rates and the compensation rates between the criteria were
determined, as well as the local and global evaluations of the multi-criteria
model. Following comparisons between some of the decison-maker performance
profiles PP1 and PP2 and sensitivity analysis, the elaboration of
recommendations phase enabled model adjustments to be made.
As
such, the SSM/MCDA-C model proved to be sufficiently robust to be applied in a
decision aid process, in which the decision-maker had little knowledge of the
decision-making complexity. When beginning the decision aid process, the
decision-maker did not manage to perceive how she would identify and cope with
the generating factors of the stress problem. Currently the decision-maker
utilizes the SSM/MCDA-C model developed for the accompanying of the performance
of the desirable and culturally possible systemic actions.
In
closing, the value of the paper methodologically speaking is to show how SSM
and MCDA-C can be combined to develop a fuller understanding of a complex
situation in its context. We believe that this approach can be used in other
complex situations.
The
limitations of the study were the time spent during interviews with the
decision-maker and interveners, the need for involvement of the decision maker
throughout the research process, and the singularity of the constructed model,
which cannot be generalised. It is noteworthy that while the process can be
replicated in other contexts, the developed model itself, since it was constructed
to suit the specific conditions of the environment, cannot be used as
constructed.
As a
suggestion for future studies, the use of the SSM/MCDA-C model is recommended
for integrated evaluation of the performance of others individual contexts.
Another possibility is the replication of this research in an organizational
segment. Finally, it is interesting that other aspects of the SSM and MCDA-C
will be analysed.
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