Absorptive capacity for responding to environmental: change an assessment of three public-sector agencies

In a time of global environmental instability, public-sector organisations that manage and protect natural resources, which are needed for human wellbeing, play an increasingly important role. These organisations frequently have to weigh up the costs and benefits of managing natural resources and their services for the public good. Management of social-ecological systems is commonly characterised by uncertainty, disagreement and trade-offs. In South Africa, these challenges are compounded by the fact that mandated organisations are often inadequately resourced in terms of finances, skilled staff and infrastructure. In order to maintain the resilience and robustness of social-ecological systems, public-sector organisations need to cultivate a set of dynamic capabilities, with strong emphasis on learning from their experiences and adapting their management strategies, to innovate and improve their performances. Absorptive capacity (AC) has been described as the ability of an organisation to recognise the value of new external information, acquire it and assimilate it within the organisation, transforming it by applying it with existing knowledge and exploiting the new knowledge for benefit. Organisations with good AC are able to recognise rapidly changing environments and address them by renewing and building on their levels of skill, knowledge and capability to deal with change. This construct has been extensively researched in industries related to business and technology, where its development has been found to stimulate innovative capabilities. There has, however, been little research into its relevance for public-sector organisations or organisations with environmental mandates. This study used methodological triangulation to assess the perceptions of employees on the current state of AC in three public-sector organisations with environmental mandates. This was done to gain insight into their capacity to absorb information and apply their new knowledge in decision-making, in a manner that navigates through environmental change. The key findings of this research suggest that knowledge transformation and exploitation are enhanced by in-house research capabilities and cross-functional interface between internal departments. These findings also suggest that the acquisition of knowledge is not only determined by the in-house research capacity but also depends on the resources available to these departments in terms of time, finances and skilled staff. There was minimal evidence of knowledge exploitation; however, obstacles that were highlighted as hindering this process included individual responsibility and motivation, as well as general organisation capacities, such as communication hierarchies, funding, time and organisational silos. This research found that the well-studied concept of AC can be used as an institutional mechanism to assess and promote adaptive capacity in public-sector organisations with environmental mandates to navigate and innovate through the Anthropocene

Social network analysis of a landscape-scale conservation initiative in South Africa

Assessment of social relations, including social network analysis, is central to understanding collaborative processes for environmental decision-making and action. The capacity of network role players to learn and adapt appropriately to uncertainty and change is a critical determinant of the resilience of social-ecological systems. Poor social network structure can predispose failure. In this study, we used social network analysis to explore learning capacity and network resilience in a multi-authority conservation initiative on the West Coast of South Africa (Dassenberg Coastal Catchment Partnership). Our analysis focused on structural variables for network learning and resilience, namely connectivity, heterogeneity, and centrality. The governance network was found to be structurally connected, with the interaction between heterogeneous organisations and sectors, and centralised around a core group of actors. The network had good structural features to enable learning. However, the high level of centrality, and dependence on a small number of core actors, rendered the network potentially vulnerable to dealing with complex challenges. We recommend that core actors (1) reflect on their core functions and whether the network can absorb these functions if they were to leave and (2) tap into the knowledge potential of actors on the network periphery or invite new actors to the network when dealing with complex challenges. This may require the network to diverge into decentralised subgroups to deal with complex issues. We further suggest that the Dassenberg Coastal Catchment Partnership network incorporate social network research with qualitative monitoring into a long-term plan to monitor the movement and influence of actors as the initiative evolves. Significance: This study illustrates how social network analysis can help researchers, public-sector organisations, and donor agencies to monitor the structural features of governance networks that enable or disable learning and resilience within landscape-scale conservation initiatives. Our results illustrate how social network analysis can assist public-sector actors to reflect on their roles and whether there is redundant competency within the network to maintain its resilience

Social network analysis of a landscape-scale conservation initiative in South Africa

Assessment of social relations, including social network analysis, is central to understanding collaborative processes for environmental decision-making and action. The capacity of network role players to learn and adapt appropriately to uncertainty and change is a critical determinant of the resilience of socialecological systems. Poor social network structure can predispose failure. In this study, we used social network analysis to explore learning capacity and network resilience in a multi-authority conservation initiative on the West Coast of South Africa (Dassenberg Coastal Catchment Partnership). Our analysis focused on structural variables for network learning and resilience, namely connectivity, heterogeneity, and centrality. The governance network was found to be structurally connected, with the interaction between heterogeneous organisations and sectors, and centralised around a core group of actors. The network had good structural features to enable learning. However, the high level of centrality, and dependence on a small number of core actors, rendered the network potentially vulnerable to dealing with complex challenges. We recommend that core actors (1) reflect on their core functions and whether the network can absorb these functions if they were to leave and (2) tap into the knowledge potential of actors on the network periphery or invite new actors to the network when dealing with complex challenges. This may require the network to diverge into decentralised subgroups to deal with complex issues. We further suggest that the Dassenberg Coastal Catchment Partnership network incorporate social network research with qualitative monitoring into a long-term plan to monitor the movement and influence of actors as the initiative evolves. Significance: This study illustrates how social network analysis can help researchers, public-sector organisations, and donor agencies to monitor the structural features of governance networks that enable or disable learning and resilience within landscape-scale conservation initiatives. Our results illustrate how social network analysis can assist public-sector actors to reflect on their roles and whether there is redundant competency within the network to maintain its resilience

Appraising strategic adaptive management as a process of organizational learning

Adaptive management is a systematic approach for linking learning with implementation to facilitate ongoing improvement in natural resource management. The idea of learning from experience and adapting subsequent policies, strategies and actions, is intuitively appealing. However, application of adaptive management has been hindered by several obstacles, including a paucity of documented lessons from existing adaptive management practices and inadequate attention to the complex social aspects of learning. Here we address these two impediments through (i) a case study of an established version of adaptive management and its application in the context of protected area management plans, and (ii) its critical comparison and conceptual integration with the seminal theory of organizational knowledge creation (TOKC), which emphasizes the social aspects of learning. As case study, we focus on Strategic Adaptive Management (SAM), which has been iteratively developed and implemented by South African National Parks for more than 20 years. We used TOKC as a conceptual sounding board to reflect on and appraise the learning that takes place through SAM. A comparison of the main steps of the SAM cycle with corresponding stages outlined by TOKC revealed remarkable complementarity between these two approaches, but also important differences. The conceptual comparison deepened our understanding of SAM's learning performance as well as potential, revealing strengths, weaknesses and opportunities for improvement. Key insights include that valuable and different forms of learning takes place during each step of the SAM cycle. This learning can be enhanced through careful attention to approaches for creating, sharing and making explicit the tacit knowledge of individuals. Furthermore, dialogue and co-learning with stakeholders should be maintained beyond the visioning and objectives setting step of SAM. Based on insights gained, we developed a new and complementary conceptualization of SAM, as a spiraling process of organizational learning enabled by the interplay between tacit and explicit forms of knowledge, which in turn is mediated by different types of social interactions, media and engagement with practice. We believe that this conceptualization can help to better acknowledge and enable learning as one of the most fundamental purposes and outcomes of SAM, and adaptive management more generally