Not more, but strategic collaboration needed to conserve Borneo's orangutan

Abstract

In conservation, Collaboration is thought to improve returns from investment and is frequently encouraged, however not all collaborations are equal and may therefore lack characteristics important for addressing collective action problems. Furthermore, partnerships that are advantageous for a collective may not necessarily be advantageous for an individual. This study investigated collaboration within the Bornean orangutan (Pongo pygmaeus) conservation sector – a system with reported inefficiencies and for which there has been a renewed call for collaborative partnerships. Collaborative partnerships were conceptualised as a social network and analysed using exponential random graph modelling. The prevalence of structural attributes associated with social processes considered to be important for solving collective action problems such as trust and innovation were investigated. Qualitative surveying techniques were used to measure the perceptions of collaboration held by individual actors within the network and the impact of organizational attributes on network formation and perceptions was assessed. Collaboration was found to be occurring within the conservation network and was positively perceived at the individual organisational level. At the collective level, the current collaborative network contains some structural characteristics important for addressing the collective-action problem of orangutan conservation, particularly through innovation and knowledge sharing. However efforts to develop trust between organisations may be needed. To improve returns on investment, future collaborative partnerships must be strategically implemented with individual roles and desired overall outcomes explicitly articulated. Increased operational transparency and improved performance evaluation will be critical for achieving improved collaborative efficiency.

Keywords

• Bornean Orangutan
• Collaborative conservation
• Conservation networks
• Exponential random graph modelling
• Pongo pygmaeus
• Social network analysis