Fast and frugal heuristics for portfolio decisions with positive project interactions
MetadataShow full item record
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.
Durbach , I N , Algorta , S , Kantu , D K , Katsikopoulos , K V & Şimşek , Ö 2020 , ' Fast and frugal heuristics for portfolio decisions with positive project interactions ' , Decision Support Systems , vol. 138 , 113399 . https://doi.org/10.1016/j.dss.2020.113399
Decision Support Systems
Copyright © 2020 Elsevier B.V. All rights reserved. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1016/j.dss.2020.113399.
DescriptionFunding: ID is supported in part by funding from the National Research Foundation of South Africa (Grant ID 90782, 105782).
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.