Complex problems are being approached through collaborations that cross sectors including businesses, nonprofits, public institutions, and academia. Social Network Analysis (SNA) methods have been adopted to help manage these large collaborations, and it is useful not only for exploring the network dynamics of the collaboration as a whole, but also for exploring where an individual organization lies within the network. Universities can benefit from understanding their position and ties within a network and utilize that information to strengthen their position within these collaborations while fostering collaborations within the network. This study applied SNA to determine the influential position of an urban university within a multi-stakeholder collaborative network (MSCN). The university in this study holds more formal intra-sector relationships and more informal inter-sector relationships with the organization types in the MSCN. The findings also show that the university does hold a prominent position within the informal network of the MSCN; however, it does not hold a position of prominence within the formal network of the MSCN. Fostering these formal and informal relationships would allow the university to strategically promote beneficial collaborations for the university and the network as a whole
This paper provides a chronology and overview of events and policy initiatives aimed at addressing irrigation sustainability issues in the San Joaquin River Basin (SJRB) of California. Although the SJRB was selected in this case study, many of the same...
Collaborative approaches are being promoted as inclusive forums for bringing state and non-state interests together to solve complex environmental problems. Networks have been recognized through previous research as important ways to involve stakeholders in such forums with members participating in...
The purpose of this study is to explore the factors that drive producers to market their products through Community Support Agriculture (CSA) by using a county-level data set from the US. Results using a Tobit model indicate that specific operator characteristics,...
Regional agroecological systems are examples of complex adaptive systems, where sustainability is promoted by social networks that facilitate information sharing, cooperation, and connectivity among specialized components of the system. Much of the existing literature on social capital fails to recognize...
So far, numerous studies have exhibited Silicon Valley and other thriving innovation ecosystems by distinguishing special characteristics in which their survival rely on sustaining activities that convert them to specific regions. These regions provide ready-made grounds for networking to be...