Decision Support System for Sustainability Assessment of Power Generation Technologies - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 518

identifying their preferences. The Kendall's coefficient of correlation (Kendall, 1970) is the
most popular tool in assessments of survey results.
The methods used to identify the values and weights of criteria that define environmental
factors may be classified conditionally into two groups:
 methods for expression of criteria in quantitative terms (e.g. expression in money,
technical parameters).
 methods for expression/description of criteria in conditional measures (scores,
percentages). Such criteria are qualitative.
While quantitative criteria may be expressed in money or technical parameters for
technologies, the measurement of the values and weights of qualitative criteria is a more
complex task. Weights for qualitative criteria may be determined through analysis, scientific
studies and databases, by comparing equivalents, and by analysing macro, meso and
microenvironment in regions with similar development degrees or development trends.
Values and weights of qualitative criteria are most often identified through expert or
sociological surveys.
The expert assessment must necessarily include identification of criteria weights; otherwise it
is difficult to assess the reliability of the research. Such calculations aim to determine whether
different experts agree to a sufficient degree for expert assessment results to be a reliable basis.
Kendall's coefficient of concordance W is the measure that describes the degree of agreement
between expert opinions. This coefficient is calculated using a specific table of expert
assessment indicators and the formulae available in literature sources. The calculated
coefficient W shows the degree of agreement between individual opinions. This coefficient will
be equal to 1 if all experts share one opinion. When all ranks differ and expert opinions do not
match, the coefficient will be equal to 0 (Kendall, 1970; Zavadskas et al., 1994).
It is often difficult to reconcile opinions on most economic decisions, particularly in the
energy sector. Reliable research demands for choosing experts from such social and interest
groups, and with such knowledge and qualifications in the respective area, as to make it
possible to reconcile the opinions on qualitative indicators. Decisions on the development of
the energy sector, on choice of technologies, their performance and application, encompass a
multidimensional and conflicting task: to minimise costs, to minimise the effect on
environment, to ensure reliable energy supply, to supply more energy, to ensure socially-
responsible pricing, to develop renewable resources, etc. Strategic decisions on the
development of the energy sector, therefore, must be based on multiple criteria analysis or
multiple criteria evaluation, because it helps to consider the relative importance of criteria to
the decision-maker thus reconciling political, economic, environmental, social and other
criteria, and to select the best solution in view of all criteria. Multiple criteria methods for
evaluation or decision-making are, therefore, an attempt to simultaneously assess several
alternative solutions on the basis of a set of contradictory criteria.
Multiple criteria analysis methods are, first and foremost, applied to determine the
preferences of stakeholders involved in the decision-making process. These methods are of
particular importance now, when public participation is part of all evaluation procedures
dealing with strategic assessment of the impact on the environment. Community consulting
is the best way to ensure that national policies serve the public. The energy sector is of
particular relevance, because it is strategically important to each citizen both in terms of
economic and social welfare. It explains increasing popularity of multiple criteria evaluation
methods in decision-making on important issues of energy development.