The primary challenge in supply chain management(SCM) is matching supply with uncertain demand.Risk pooling is an efficient and promising strategy to meet this challenge by reducing the underlying demand uncertainty through aggregation.The main focus of this paper is to analyze the effects of risk pooling under different supply chain settings.There are two main contributions.First,we propose a mathematical framework which serves the multi-purpose of(1) unifying existing models on risk pooling in the literature,(2) providing new facets and insights of understanding existing results on risk pooling,and(3) setting up new ground for extending existing models and results.Second,we investigate one interesting effect of risk pooling,namely, the decreasing marginal return(or supermodularity).We show that there are decreasing marginal returns in risk pooling practices under certain conditions,specifically when the demand is independent and identically distributed(I.I.D.) and normally distributed. The primary challenge in supply chain management (SCM) is matching supply with uncertain demand. Risk pooling is an efficient and promising strategy to meet this challenge by reducing the underlying demand uncertainty through aggregation. The main focus of this paper is to analyze the effects of risk pooling under different supply chain settings. Here are two main contributions. First, we propose a mathematical framework which serves the multi-purpose of (1) unifying existing models on risk pooling in the literature, (2) providing new facets and insights of understanding existing results on risk pooling, and (3) setting up new ground for an existing existing models and results. Second, we investigate one interesting effect of risk pooling, namely, the decreasing marginal return (or supermodularity) .We show that there are decreasing are pooling marginal returns in risk pooling practices under certain conditions, specifically when the demand is independent and identically distributed (IID) and normally distributed d.