A Preliminary Examination of Citizen Orientation and Multiple Dimensions of Organizational Performance

ABSTRACT

In this article, I discuss citizen orientated public management in relation to extant frameworks and theories in public management and organization research, including the role of the public servant, collaborative public management, citizen coproduction, and relational bureaucracy. Following the discussion, I hypothesize about the relationship between public organizations’ citizen orientations and multiple dimensions of organizational performance. I use data from approximately 900 New York City elementary and middle schools from 2008 to 2011 to examine the relationship. Preliminary findings indicate that a citizen orientation is positively related to multiple dimensions of public organization performance.

KEYWORDS:

• Citizen orientation
• organizational performance
• public management
• education

Notes

¹ This market orientation is a construct distinct from general free market principles.

² While the term “client orientation” also might seem appropriate in extending the market orientation to public organizations, there are concerns with calling those who receive public services “clients.” According to Vigoda (2002), “the term client, or customer, which is so applicable in the private sector…, contradicts the very notion of belonging, contribution to society, and self-derived participation in citizenry actions. When someone is defined as a client, he or she is not actively engaged in social initiatives, but is merely a passive service (or product) consumer, dependent on the goodwill and interest of the owner.” (p. 534)

³ This is not to say that exogenous shocks never affect public organizations. A notable example is the “shock” that occurred when families displaced by hurricane Katrina relocated to Houston and other areas of Texas and enrolled children in the local schools.

⁴ I only used schools where at least 25% of the teachers participated in the survey to ensure representativeness.

⁵ In contrast with principal component analysis, the common factor model allows for the estimation of both common and unique variances (Brown, 2006).