Drivers and Dynamics of Collaborative Governance in Environmental Management

Abstract

This special issue brings together new case studies and comparative works highlighting the drivers and dynamics of collaborative environmental governance. Each case is part of the Collaborative Governance Case Database, which is an open-access resource allowing individuals to contribute and access cases to support research projects. This article highlights the special issue’s contributions to collaborative governance theory. Common themes that cut across the studies include: the importance of using a broad definition of collaborative governance to capture the diversity in interorganizational relationships across contexts; improving our understanding of the drivers for initiating collaborative governance; an enhanced understanding collaboration’s lifecycle dynamics and developmental trajectories; the importance of individuals and their roles in collaborative processes; the political dynamics of collaboration; the role of accountability; and the challenges associated with assessing the performance of collaborations. Collectively, the cases also demonstrate the value of using resources such as the Collaborative Governance Case Database to undertake small-n and medium-n comparative studies that further theory building.

Network governance as an alternative policy response to managing infectious disease outbreaks: Lessons from Uganda's response to the COVID‐19 crisis

“…The president encouraged collaborations among network actors and highly enforced restrictive measures. This showed that while nondemocratic governments such as Uganda may not usually prefer collaborative governance approaches (Escribà‐Folch, 2013; Katusiimeh, 2015; Ryan, 2022; Ulibarri et al, 2023), when confronted with large complex wicked problems they can rely on multiple actors for a common national goal. The study findings relate to the evidence that effectiveness of managing COVID‐19 did not depend on country's democracy, but rather on the state leadership's ability to take the crisis serious and effectively use collaborative mechanisms (Boossabong & Chamchong, 2020; Chen, 2020; Engler et al, 2021; Greer et al, 2021; Sharma et al, 2021; Yan et al, 2020).…”

“…Furthermore, nondemocratic governments such as Uganda may encounter challenges with collaborative public management due to political regimes that restrict civil liberties by repressing collective action (Escribà‐Folch, 2013; Katusiimeh, 2015). While contextual evidence is still growing on whether democracy played a significant role in COVID‐19 management (Boossabong & Chamchong, 2020; Cassan & Van Steenvoort, 2021; Chen, 2020; Engler et al, 2021), collaborative governance approaches can be used to manage public problems, even in nondemocratic nations as demonstrated by the learnings of Ryan (2022), Ulibarri et al (2023). Therefore, exploring how Uganda utilized network governance to manage COVID‐19 could contribute to the growing literature on the use of collaborative governance in nondemocratic governments in times of crisis.…”

Organizational Capacity for Collaborative Adaptive Governance: An Empirical Assessment of a Large Landscape Network

“…The network dimension of adaptive governance suggests that actors are connected and form stable and long-term relationships through the sharing of resources, spatially adjacent or nested overlapping authorities, and in coordinated work together to plan and implement policies and programs (Ulibarri et al 2023;Kapucu, Hu, and Hu 2020;Carlsson and Sandström 2007). The multi-issue, multi-scale, multi-actor context of SES, particularly when thinking about large landscapes (Bixler, McKinney, and Scarlett 2016), makes networks an inherent characteristic of adaptive governance (see Figure 1a).…”

Exploring the Complex Landscape of Electric Vehicle Adoption: Understanding Incentives and Overcoming Barriers for Sustainable Transportation in the US

“…In the context of future research, we suggest the utilization of various multi-criteria decision-making approaches, including the Simple Additive Weighting (SAW) method, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and cognitive valuation techniques. These methodologies have been employed by researchers in the field of environmental management to evaluate and address topics related to development and adaptation (Bourdin & Chassy, 2023;Dolge et al, 2023;Morkunas & Volkov, 2023;Ulibarri et al, 2023). By identifying the most significant factors, policymakers can focus their actions and resources on addressing the most crucial obstacles and incentives to EV adoption.…”