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Record W4383957508 · doi:10.24928/2023/0205

Collaborative Dialogue During the Pre-Tendering Phase to Maximize Project Value Generation

2023· article· en· W4383957508 on OpenAlexaff
Valeria Del Vecchio, Abbey Dale Abellanosa, Bernadette Konwat, Yu Wei, Farook Hamzeh

Bibliographic record

VenueAnnual Conference of the International Group for Lean Construction · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsProcurementPhase (matter)Value (mathematics)Computer scienceBusinessPhysicsMarketing

Abstract

fetched live from OpenAlex

The construction industry has widely adopted traditional project delivery methods, such as design-bid-build, to develop conventional construction projects, where only one main contractor is granted the project contract.Selecting only one main contractor for the project results in the waste of valuable ideas coming from the rest of the bidders who participated in the tendering process but did not win the bid.These ideas, coming from the contractors that lost the bid, are usually not considered during the project execution, even though they could increase the value of a project, shorten the schedule, and reduce costs.As an alternative to solve the current gap of lost creativity and ideas coming from contractors that were not awarded the project contract, this study will explore the workarounds to promote partnership between key stakeholders during the pre-tendering phase by involving multiple contractors instead of a single construction project, to develop innovative ideas that could maximize the value of a construction project.The importance of collaboration and co-creation of value is widely emphasized in lean construction.Experts in the construction industry with a background in collaborative delivery were surveyed and interviewed to understand their opinion on the proposed topic.The experts from both backgrounds concluded that involving multiple contractors instead of just one main contractor is a feasible idea, but it will take effort from all the stakeholders to compromise on this type of agreement.The benefits and constraints of implementing collaborative dialogue are further discussed in the following sections of this study.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.001
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 score0.477
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.094
GPT teacher head0.376
Teacher spread0.281 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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