The Performance Information Processing Framework: Four cognitive models of performance information use
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Authors
Webeck, Sean
Subjects
Advisors
Date of Issue
2019-06-13
Date
Publisher
Monterey, California: Naval Postgraduate School.
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Abstract
The question of how public managers use public sector performance information received significant scholarly attention in recent years. The promise of performance management systems was to rationalize the decision making process by creating objective performance metrics that citizens, political officials, and public managers could use to assess the performance of public organizations. Some theoretical work suggests, however, that there is a certain subjectivity to these data, which arises from an individual’s role in their organization or broader political environment. Furthermore, a recent spate of experimental work in this area suggests subjectivity might also arise, at the individual level, through cognitive bias. I bridge these two bodies of scholarship with a framework of performance information processing, which incorporates four models of political information use into the story of how public managers use performance information. I suggest that cognitive bias can contribute to the subjectivity of performance information when public managers process performance information. In other words, a model of meaning avoidance suggests that managers accurately receive performance information from management systems, but that cognitive biases influence the ways in which they interpret or act upon that information. In this essay, I provide empirical evidence for this model. I show that despite different presentations, public managers can accurately recount the objective information they saw when asked to recall it. I also provide evidence that despite being equally aware of objective raw performance metrics, public managers exhibit evidence of cognitive bias when asked to interpret the meaning of that information. This study contributes to the broader discussion of how individuals use performance information.
Type
Conference Paper
Description
DRMI Working Paper Series
PMRC 2019: Public Management Research Conference (PMRC)
Note by author: "This manuscript is in progress and will be presented at PMRC 2019. Please do not cite without permission from the author."
PMRC 2019: Public Management Research Conference (PMRC)
Note by author: "This manuscript is in progress and will be presented at PMRC 2019. Please do not cite without permission from the author."
Series/Report No
Department
Business & Public Policy (GSBPP)
Organization
Defense Resources Management Institute
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NPS Report Number
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Format
52 p.
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Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.