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Performance Indicator Importance in MPA Management 605

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Figure 2. Key performance indicators defined by EIMR stakeholder groups (numbers represent
aggregated priorities of all respondents).

Expanding the range of application, it was used in the present study to define
and analyze stakeholder group preferences for performance indicators in the EIMR.
The AHP allows the decision maker to focus on developing and analyzing a formal
hierarchy of all the important factors likely to differentiate good from poor decisions.
It reduces the cognitive burden of prioritizing decision-making problems through the use
of simple pairwise comparisons. Specifically, the methodology encourages respondents to
make subtle trade-offs between two non-quantifiable attributes at a time, thus offering a
more complete understanding of the qualities of the objectives or indicators at hand. The
resulting pairwise comparison matrix provides a method to crosscheck relative values due
to built-in redundancy from the comparison of all possible pairs of objectives (Dodgson
et al., 2000). Also, the AHP requires no probabilistic assumption about the decision
alternatives. Finally, although the original methodology was developed to allow a single
decision maker to select one of many alternatives, it has been successfully extended to group
decision-making where the single decision maker is actually a cohort of N individuals (e.g.,
Duke & Aull-Hyde, 2002).

An Analysis of MPA Performance Indicators

Definition of the Performance Indicators (Step 1)
Stakeholder preferences for MPA performance indicators were investigated in 2004 using
semi-structured interviews with a random sample of five stakeholder groups in the Egadi
Islands: small-scale fishers, local residents, tourists, EIMR managers, and researchers
(Himes, 2007). The main goal of the questionnaire was for stakeholders to determine what
aspects of MPA management needed to be improved for the EIMR to be successful. The
results of these interviews were then grouped and categorized to assist in defining potential
performance indicators for the AHP analysis. Using the AHP framework, an indicator tree
was then created from the most frequently cited performance indicators (Figure 2).