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608 A. H. Himes

pairwise comparison can also be determined. A consistency index (CI) is measured for the
comparison matrix where
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λ max − n
CI = (4)
n − 1

The matrix A is considered to be consistent when w i = a ij w j and its principal eigenvalue
is equal to n (i.e., the dimension of A). The matrix A is said to be inconsistent when λ max
> n. The variance of the error inherent in estimating a ij (a quantitative measure of each
respondent’s judgment concerning the importance of objective i over objective j) may then
be shown to equal (λ max − n)/(n − 1) (Mardle & Pascoe, 1999; Wattage & Mardle, 2005). An
indication of a respondent’s consistency can be determined and compared to an indicative
consistency produced from randomly developed matrices. From this, a consistency ratio
(CR) for an individual can be produced, calculated by

(λ max − n)/(n − 1)
CR = (5)
RI
where the variance of the error is divided by an average consistency index derived from
the RI. Perfect consistency occurs when λ max equals n (CR = 0); therefore, the closer λ max
is to n, the better the consistency. CR values of less than 10% are desired; however, many
authors have accepted values up to 20% in post analysis (Mardle & Pascoe, 1999).

An Analysis of MPA Performance Indicators
Only 39 of the 53 individual matrices could be used in the analysis, resulting in 1,092 usable
pairwise comparisons. The remaining 14 matrices were unsuitable for use in the analysis
due to the respondent’s high inconsistency (CR greater than 20%) in responses to the
pairwise comparisons in the questionnaire. The analysis of the AHP results was conducted
at the stakeholder group level in order to make comparisons within and between groups.
Individuals were invited to partake in the survey and were asked to assign themselves to one
of five stakeholder groups: local residents, artisanal fishers (i.e., small-scale commercial
fishers using low-intensity technology), researchers, EIMR managers, and tourists. Of those
surveys used, 13.6% are researchers (biologists) from nearby universities, 18.2% engage in
1
artisanal fishing activities, some also partaking in pescaturismo, 40.9% are local residents
(37% of which run tourism businesses), 11.4% take part in MPA management, and 15.6%
are tourists. The aggregated priorities for each stakeholder group were derived by adding the
priorities obtained for the two components of each category. Table 2 and Figure 3 compare
the aggregated priorities of the four indicator categories for each of the five stakeholder
groups.
From Table 2 and Figure 3, it is apparent that stakeholders are only somewhat divided
over their preferences for the four main performance indicator categories. With the exception
of managers who rank management twice as important as other groups and fishers who rank
the economic category almost twice as important as the other groups, an overall pattern
of similarity appears in Figure 3. Apart from these exceptions, the general trend ranks the
social and biological/environmental categories relatively equal for each of the groups and
considerably higher than the management and economic categories.
However, at the indicator level, there is much greater disparity between individual
and stakeholder group preferences. In order to uncover these differences, individual and