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DERIVED IMPORTANCE-PERFORMANCE ANALYSIS OF CITIZEN SURVEY DATA

Importance-performance analysis has been advocated as a useful technique for understanding citizen satisfaction data. In this paper, we enhance this technique by incorporating derived, rather than stated, importance and by using benchmarked measures of performance. Using data from New York City, we demonstrate the use of this enhanced technique and compare its conclusions to the simpler version of importance-performance analysis. We then show that derived importance-performance analysis produces results that remain fairly stable over time and can offer insight into citizen satisfaction within subgroups of the population. We argue that derived importance-performance analysis deserves more widespread use because it provides a better framework for interpreting what citizens say about local government services for policy- and managerial decision-making.