Fast and frugal heuristics for portfolio decisions with positive project interactions

Abstract

We consider portfolio decision problems with positive interactions between projects. Exact solutions to this problem require that all interactions are assessed, requiring time, expertise and effort that may not always be available. We develop and test a number of fast and frugal heuristics – psychologically plausible models that limit the number of assessments to be made and combine these in computationally simple ways – for portfolio decisions. The proposed “add-the-best” family of heuristics constructs a portfolio by iteratively adding a project that is best in a greedy sense, with various definitions of “best”. We present analytical results showing that information savings achievable by heuristics can be considerable; a simulation experiment showing that portfolios selected by heuristics can be close to optimal under certain conditions; and a behavioral laboratory experiment demonstrating that choices are often consistent with the use of heuristics. Add-the-best heuristics combine descriptive plausibility with effort-accuracy trade-offs that make them potentially attractive for prescriptive use.