Multi-Tiered Selection of Project Delivery Systems for Capital Projects
Notice bibliographique
Résumé
In this thesis, a decision support system (DSS) for selecting the most suitable project delivery systems (PDSs) for capital projects is proposed. Project delivery systems continue to evolve, to meet challenging project objectives. Selecting a PDS is an early project decision, which can greatly affect the project execution process and its outcomes. The proposed DSS encompasses a multi-tiered process; designed on the basis of an in-depth analysis of 15 case studies of projects constructed in the USA and 207 projects in Canada which utilized public-private partnership delivery methods. The selection criteria were developed utilizing related literature and the findings of the analysis of the case studies. The developed system operates in two distinct modes; elimination, first, to narrow the search field, and ranking, second, to find the most suitable delivery method. In the first mode, the suitability of public-private partnership (PPP) is identified and a number of PDSs are eliminated based on a set of key project characteristics. In the second mode, evaluation and ranking of the remaining PDSs are performed using multi-attributed decision method (MADM). The MADM model utilizes relative effectiveness values (REV) of PDS’s in the evaluation process. These values build upon those developed by CII (2003) to account for PDSs and selection factors beyond those considered in the CII study. The proposed DSS is intended for decision makers of owner organizations, and their consultants. It incorporates knowledge about PDSs and their suitability in meeting a set of targeted project objectives. The decision maker provides project-specific inputs including project information and judgments regarding the importance of specific evaluation and selection criteria. An automated software tool was developed to facilitate the use of the proposed DSS. Three case projects were analyzed using the proposed DSS, including one private sector project and two public sector projects. Two of these cases where also analyzed in the CII study. The results obtained by the proposed DSS were identical to those of the CII study, under the same criteria and the same set of alternative DSSs. The two cases were further analyzed to consider the expanded set of PDSs and the developed criteria. In the latter case, the results revealed a more suitable PDS method. This also applies to the third case. In two of the three cases, the selected PDS was recently developed and known as an integrated project delivery (IPD). The developed method, aside from expanding upon the CII study in the criteria and in the number of PDSs, introduces and makes available newly developed PDSs including IPD and the family of PPPs. The developed method is expected to be useful to owners of capital and public projects.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».