Measuring Innovativeness of Public Organizations: Using Natural Language Processing Techniques in Computer-Aided Textual Analysis

We propose a new method for measuring innovativeness in the public sector using natural language processing techniques. Our approach extends traditional content analysis techniques by combining insights from linguistic theory and recent developments in computational techniques. We develop and employ phrase-level data dictionaries (using both noun phrases and verb phrases) from organizational documents. We use letters to the board of education from a sample of New Jersey school districts to develop measures of innovativeness—one measure is based on expert assessments and the other is inductively derived. We perform rigorous tests of content validity, external validity, and predictive validity on these measures. We conclude with a discussion of implications of this new measurement approach and its potential applications to other public management contexts.