Crisp mathematical programming techniques
have shortcomings when used for measuring and
evaluating achievement of organizational goals
in a decision-making environment.
Generally, in most real-life situations optimal
achievement of multiple goals is rarely possible.
In such cases, a compromise achievement of goals
that leads to a satisfycing solution rather than
an optimal solution bears more relevance.
The present research introduces a framework to
measure and evaluate the goals of efficiency and
effectiveness in a fuzzy environment and is
developed using Goal Programming, Data Envelopment
Analysis and Fuzzy Set Theory. The proposed
framework is called Fuzzy GoDEA and uses
surrogate constraints to represent the efficiency
and effectiveness goals. DEA type constraints
are used to model the efficiency goal. The
effectiveness goal is represented by the
aggregate efficient contribution of the individual
decision-making units toward achievement of the
global organizational targets. Concepts of fuzzy
set theory and goal programming are used to model
the imprecision in goal achievement and the
relative importance between goals. Additionally,
the concept of minimal operational viability is
introduced, though not included in the application
due to unavailability of suitable data.
The Fuzzy GoDEA framework accommodates crisp input
and output data but allows imprecise specification
of the aspiration levels for the efficiency and
effectiveness goals. The imprecision in goal
achievement is allowed through the specification
of an interval of acceptable achievement rather
than a crisp value. A membership function is
defined for each fuzzy constraint associated with
the efficiency and effectiveness goals and
represents the degree of achievement of that
constraint. Further, the Fuzzy GoDEA framework is
extended into several variations that (i) allow
the assignment of relative importance to the goals
of efficiency and effectiveness and (ii) model
scenarios where one of the goals of efficiency and
effectiveness is crisp and the other fuzzy.
The applied component of the research involves the
application of the Fuzzy GoDEA framework to a
newspaper preprint insertion process (NPIP).
Detailed analyses of the results are presented to
describe the information available from the Fuzzy
GoDEA methodology that can be used in conjunction
with conventional DEA analysis to assess and
improve the efficiency and effectiveness
performance of the NPIP system.
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