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Record W4220933368 · doi:10.1061/9780784483978.012

Current State of Practice in Selection and Implementation of Airport Capital Project Delivery Methods

2022· article· en· W4220933368 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConstruction Research Congress 2022 · 2022
Typearticle
Languageen
FieldEngineering
TopicAir Traffic Management and Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIntegrated project deliveryProcurementBusinessGeneral partnershipAgency (philosophy)AviationProcess managementBasis of estimateFinanceProject planningEngineering managementProject managementRisk analysis (engineering)Project charterEngineeringMarketingSystems engineering

Abstract

fetched live from OpenAlex

Selection and implementation of project delivery methods are important decisions in an airport capital project that will determine how the airport agency employs procurement and financing strategies, management structures, and cash flows. Most current delivery method selection approaches in the aviation sector rely on experience and opinions of construction experts. A research gap exists regarding understandings of existing and emerging delivery methods as well as their alignment with procurement and management structures, organizational capabilities, and financial planning considerations. The objective of this study was to investigate the current state of practice in selection and implementation of project delivery methods in airport projects. A content analysis of 26 airport projects across the US was performed to synthesize documents regarding selection and implementation of project delivery methods and procurement approaches. The results show that alternative contracting methods, including construction manager-at-risk, design-build, and public–private partnership, are increasingly used in authority/quasi-government airports because of their connection to financial planning, contract strategies, and procurement methods. This study contributes to the body of knowledge by providing a comprehensive review of current practices of selecting and implementing project delivery methods in capital airport projects. The results also imply the importance of considering risk-based methodologies for project delivery selection in the aviation sector.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.399
Teacher spread0.373 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it