Alliance Bioversity-CIAT, Palmira, Valle del Cauca, Colombia.
PLoS One. 2021 Nov 12;16(11):e0259734. doi: 10.1371/journal.pone.0259734. eCollection 2021.
In research portfolio planning contexts, an estimate of research policy and project synergies/tradeoffs (i.e. covariances) is essential to the optimal leveraging of institution resources. The data by which to make such estimates generally do not exist. Research institutions may often draw on domain expertise to fill this gap, but it is not clear how such ad hoc information can be quantified and fed into an optimal resource allocation workflow. Drawing on principal components analysis, I propose a method for "reverse engineering" synergies/tradeoffs from domain expertise at both the policy and project level. I discuss extensions to other problems and detail how the method can be fed into a research portfolio optimization workflow. I also briefly discuss the relevance of the proposed method in the context of the currently toxic relations between research communities and the donors that fund them.
在研究组合规划的背景下，对研究政策和项目协同作用/权衡（即协方差）的估计对于优化机构资源的利用至关重要。进行此类估计的数据通常不存在。研究机构可能经常依靠领域专业知识来填补这一空白，但尚不清楚如何对这种临时信息进行量化并将其纳入到最佳资源分配工作流程中。我借鉴主成分分析，提出了一种从政策和项目层面的领域专业知识中“反向工程”协同作用/权衡的方法。我讨论了该方法在其他问题上的扩展，并详细说明了如何将该方法纳入研究组合优化工作流程。我还简要讨论了在研究社区与资助它们的捐赠者之间目前存在的紧张关系背景下，所提出的方法的相关性。
