We investigate the group processes involved in effort estimation in the context of project management. The groups considered are formed by ‘‘experts’’ (people with specific technical competence) and ‘‘nonexperts’’ (people with less specific technical competence, usually experts in related fields), because the typically complementary bias of the two classes contribute to a more balanced estimate. In this paper we exploit further the synergies between experts and non-experts in an MCDM framework, aggregating the individual estimates by means of non-additive Choquet integration, and representing the complementary bias by the multiagent interaction structure underlying the capacity. We present some examples and computer simulations whose aggregation results outperform those of the classical weighted mean (additive case), showing lower MMRE (mean magnitude of the relative error between the central estimate and the actual value) and higher HitRate (at which the interval estimate contains the actual value).

Modelling group processes and effort estimation in project management using the Choquet integral: An MCDM approach

Bortot, Silvia;Fedrizzi, Mario;Marques Pereira, Ricardo Alberto;Molinari, Andrea
2012-01-01

Abstract

We investigate the group processes involved in effort estimation in the context of project management. The groups considered are formed by ‘‘experts’’ (people with specific technical competence) and ‘‘nonexperts’’ (people with less specific technical competence, usually experts in related fields), because the typically complementary bias of the two classes contribute to a more balanced estimate. In this paper we exploit further the synergies between experts and non-experts in an MCDM framework, aggregating the individual estimates by means of non-additive Choquet integration, and representing the complementary bias by the multiagent interaction structure underlying the capacity. We present some examples and computer simulations whose aggregation results outperform those of the classical weighted mean (additive case), showing lower MMRE (mean magnitude of the relative error between the central estimate and the actual value) and higher HitRate (at which the interval estimate contains the actual value).
2012
18
A., Bonetti; Bortot, Silvia; Fedrizzi, Mario; Marques Pereira, Ricardo Alberto; Molinari, Andrea
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/92859
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