*Names in bold indicate Presenter
While governance networks are important to address complex social problems (O’Toole 1997), they often fail to produce expected results (Huxham & Vangen 2000). In order to effectively address complex social problems, performance management is essential in governance networks (Koliba et al. 2011). For instance, performance management could mitigate collective action problems by enhancing social learning (Klijn 1996). However, while there are a number of studies about how to assess network performance (e.g., Provan and Milward 2001), performance information use in governance networks has not been fully studied (Moynihan et al. 2011), even though performance measurement has little impact without performance information use (Hatry 1999).
Studies on performance information use do not fully explore performance information use in network settings, either. Contrary to most studies that focus on performance information use by single actor, the interactive dialogue model of performance information use proposed by Moynihan (2008) is applicable for governance networks (Koliba et al. 2011). The model explains that social interactions and dialogue processes influence performance information use, and that performance information is more likely to be used during intra-organizational interactions than inter-organizational interactions. However, the model does not fully capture how interactions among actors affect performance information use, given that interaction patterns and relational characteristics among actors affect their perceptions and behaviors regardless of organizational boundary (Granovetter 1985).
To bridge the research gap, this research will explore two research questions.
1) Which actors use performance information in governance networks?
2) How do actors’ interactions, positions, and relational characteristics in governance networks influence their performance information use?
Identifying the actors who use performance information is important because they “serve as critical agents around which the governance of complex governance networks can (and in many cases does) take place” (Koliba et al. 2011, p.279). Finding these critical agents would mitigate accountability problems in governance networks by clarifying who should be accountable for network performance. Understanding how interaction processes or interdependence among actors affect performance information use is also important because it is essential to consider the complexity of governance networks in order to foster performance information use (Moynihan et al. 2011).
To explore the questions, I will use data from a collaborative governance network which provides social services in Orange County, New York. Treating performance information use between actors as a tie, (1) I will use descriptive network analysis methods (e.g., Block models) to identify actors or communities of actors who regularly use performance information (first research question); and (2) I will use stochastic network analysis methods (e.g., ERGMs) to model the effects of interaction patterns and relational characteristics on the ties (performance information use) between actors (second research question).
This study will review studies on governance network as well as performance information use. Then, it will introduce the data, methods, and procedure, and will show the findings from network analysis. Finally, it will draw out implications for how to enhance performance information use in governance networks.
