Network dynamics in local governments
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The majority of governmental programs have been implemented in the setting of interorganizational relationships. In this context, explaining how and why organizations are involved in network relationships has been a central and enduring quest of scholars in public management. However, relatively little scholarly attention has been devoted to examining how these network relationships emerge, grow, and change over time. This study aims to make a contribution to the literature on managerial networking behaviors in public organizations by systematically testing hypotheses regarding the forces that influence changes in networking patterns. Both exogenous and endogenous organizational factors can influence the dominant networking types and the extent of involvement in each type of networking. Exogenous factors cover both institutional and task environments, and endogenous factors include historical aspects of networking relationships, top manager characteristics, and past performance. The present study categorizes networking types into two: local politics networking and professional networking, particularly in the context of Texas school districts. A variety of quantitative methods was employed to test hypothesized relationships, using data from a series of Texas school district superintendent management surveys and non-survey data from the Texas Education Agency. The findings provide empirical support for the relationship between resource availability and networking activities. More statistically significant relationships are revealed among endogenous forces, and in particular, historical aspects of network relationships make a significant contribution to the explanatory power of the model. However, individual characteristics generally did not provide a good explanation for the model. This study contributes to building a more comprehensive model of determinants of networking behaviors of public managers by incorporating both environmental factors at the organizational level and managerial factors at the individual level. Furthermore, the multidimensional approach in the current study allows one to develop a more specified explanatory model of managerial networking and to capture distinct networking patterns driven by different motives and situational factors. Additionally, bringing a dynamic perspective to bear on the study of networking relationships might yield important insights on networking dynamics. In such ways, the current study provides opportunity for greater theoretical and empirical development of the networking management research agenda.